Podcasts about Elastic

Don’t Fade and Die in AI Subscribe to our Newsletter: https://theultimatepartner.com/ebook-subscribe/ Check Out UPX: https://theultimatepartner.com/experience/ Matt Yanchyshyn, VP AWS Marketplace, Rekha Thangelapalita, Elastic GSI Leaders; Allison McFadden, Accenture AWS Leader; and James Kang of Nvidia join Ultimate Partner. In this panel discussion, leaders from Elastic, Accenture, Nvidia, and AWS dissect the urgent shifts in the ecosystem, emphasizing that partners must adapt to AI and agentic co-selling or risk fading away completely. The conversation explores the necessity of deep co-engineering, the power of multi-product solutions in the AWS marketplace, and how automated agents are now replacing traditional human sales pipeline progression. By embracing data readiness and strategic collaboration, organizations can survive the “token maxing” era, effectively scale their enterprise opportunities, and align with NVIDIA’s five-layer strategy to dominate the new cloud landscape. https://youtu.be/zUkL4Wqsa68 Key Takeaways AI agents will automate the majority of AWS partner co-selling attachments and opportunity progressions this year. Partners who fail to embrace agentic workflows and automated governance face the existential risk of fading into obsolescence. Successful multi-product offerings require a “blood to all organs” approach that benefits the client, the ISV, the GSI, and the hyperscaler simultaneously. Nvidia’s “five-layer cake” model emphasizes that successful outcomes at the application layer automatically drive growth for all underlying infrastructure. The “token maxing” phenomenon is forcing enterprises to seek cost-effective, open-model alternatives to scale their generative AI securely. Integrating GSIs and ISVs on the AWS marketplace significantly increases enterprise deal sizes and long-term customer renewal rates. If you're ready to lead through change, elevate your business, and achieve extraordinary outcomes through the power of partnership—this is your community. At Ultimate Partner® we want leaders like you to join us in the Ultimate Partner Experience – where transformation begins. Key Tags strategic collaboration agreement, data readiness engine, agentic co-sell, semantic layer, token maxing, five layer cake, accelerated computing platform, open models, cloud consumption, multi-product solutions, partner central agents, propensity data, automated opportunity progression, generative AI governance Transcript Matt Y and Panel Audio Podcast [00:00:00] Vince Menzione: You have a choice. You can embrace them and figure it out and get governance and, and make your data available. Um, use the partner, central agent, move to Agen Co-sell, or you can fade and die. [00:00:11] Vince Menzione: You can feel it happening. The ecosystem is shifting beneath us, the way Hyperscalers are partnering, how AI is remaking the channel and what it means to win in 2026. [00:00:22] Vince Menzione: Welcome to the Ultimate Partner Podcast. I’m Vince Menzi. Own your host. And each week I sit down with leaders at the intersection of technology, partnerships and outcomes. The voices shaping how ecosystems actually work. We talk about what’s real, what’s changing, and what it takes to lead in this era where the partner channel isn’t just part of the strategy. [00:00:44] Vince Menzione: It is the strategy because [00:00:46] Vince Menzione: being in the room changes everything. Let’s start. [00:00:51] Vince Menzione: We’ve got some amazing leaders joining us. So I think probably for a little bit of context, maybe just start with Rika. You can introduce yourself, your role and, uh, what, what you’ve been doing at Elastic. Yeah. [00:01:03] Rekha Thangellapalli: Yeah, sounds great. [00:01:04] Rekha Thangellapalli: Hi everyone. I’m Reka and I lead GSI Alliances at Elastic. Um, for the past 14 years, I’ve had the pleasure of building different kinds of partner ecosystems across companies such as SAP. MuleSoft, Salesforce, Coupa, and now Elastic. Um, I wanna thank Ultimate partner and Vince for having us here today. Thank you and the panel of these incredible speakers for joining me on stage. [00:01:31] Rekha Thangellapalli: Um, very excited for the conversation today. [00:01:33] Vince Menzione: We love Elastic, and you’ve had some of your other leaders on stage at other events. As such, the quality of your leadership team is amazing. Thank you. [00:01:42] Rekha Thangellapalli: I wholeheartedly agree. [00:01:45] Allison McFadden: Excellent. Um, hello everyone. Allison McFadden. I lead our North America AWS practice at Accenture. [00:01:52] Allison McFadden: Uh, I’ve been there for five years, and truth be told, it was my first partnership role, my first formal partnership role. Uh, so I can take some tips from all of you in the room here today. Prior to that, I was 21 years with IBM, and I got into partnerships because my last role at IBM was actually trying to build. [00:02:14] Allison McFadden: Linux business on the mainframe, and I had to have partners. I had to have partners to help me with workloads to run there. So I kind of learned, uh, trial by fire. But I’m excited for the conversation today. Excited to be in this room and excited to talk about what we’re doing with, uh, elastic. Thank you. [00:02:34] James Kang: Uh, my name is James Kang. Nice to see and meet everyone here. Vince, thank you for the opportunity. Thank you [00:02:38] Vince Menzione: for being here. [00:02:39] James Kang: Um, I’m with Nvidia, so I help manage the AWS partnership at Nvidia all up. Um, I guess fun fact, I’m former AWS and so I see a lot of very familiar faces here in the front row. Uh, former colleagues and then current friends. [00:02:56] James Kang: And so, uh, looking forward to the conversation. [00:02:59] Vince Menzione: Great. Well, we’ll start with an easy tia. Matt. This is not directed to you, directed to the others. So what does a successful AWS partnership look like from your C? So we’ll start with Eureka. [00:03:09] Rekha Thangellapalli: Sure. So from an ISV perspective, I think we really are looking at three things. [00:03:15] Rekha Thangellapalli: Uh, mutual investment building together. And scaling together. So when we talk about mutual investment, elastic recently signed a five-year SCA or strategic collaboration agreement with AWS. And while that is a significant milestone in our partnership, for us, what matters more is what it represents, and that is really a long-term commitment from both companies. [00:03:39] Rekha Thangellapalli: Towards product engineering, um, and joint go to market initiatives to deliver value to customers over time. And that’s what we see is that the best partnerships really compound and they build upon each other every year. Um, they don’t necessarily kind of reset every year. Um, next we talk about building together. [00:03:59] Rekha Thangellapalli: So, um. When we talk about joint solutions, we want to deliver solutions that are better together and the customers have to see us that way. And so whether it’s search, observability, or security, we’re looking at taking to market solutions that we can’t or necessarily don’t wanna take on our own. And finally we talk about scaling together. [00:04:22] Rekha Thangellapalli: And this is where marketplace, for instance, plays a big role, um, when customers can draw down on their cloud commitments, transact online and go from, you know, pilot to enterprise scale adoption in hours, not days. Um, this is when really everyone wins. Um, and this is also where partners like Accenture play a critical role. [00:04:47] Rekha Thangellapalli: Um, you know, the incredible amount of expertise that they bring, uh, the managed services capabilities and, um, their data assets actually play a huge role in having our customers realize that value faster. And, um, like Vince mentioned, at the end of the day, best partnerships are all all about creating kind of that. [00:05:07] Rekha Thangellapalli: Self-sustaining flywheel. And so it starts with investing together, building something unique, and having the customers realize that success faster because that success is really the only thing that’s gonna keep that flywheel going for everyone involved. I [00:05:26] Vince Menzione: absolutely. [00:05:26] Allison McFadden: Okay, amazing. I’m gonna riff off a few things Ika said, but from a GSI perspective. [00:05:32] Allison McFadden: A relationship with a WSA successful relationship with AWS looks slightly different. Um, so I think the first thing that we think of in the GSI Community common thread is that the client outcome and delivering value for clients is what we, what we’re striving for. Um, and so the partnership with AWS in that case, um, um, it has to, it has to. [00:06:01] Allison McFadden: Look like one team in front of our clients. So we have to show up indistinguishable, and that’s with AWS and with an ISV partner, it has to look like one solution in front of the client, especially moments that matter. So board meetings, um, you know, the time we’re gonna sign a deal, like we have to look like one team, uh, and keep our our client outcome, um, first and foremost in mind. [00:06:24] Allison McFadden: The second thing, and this is I think where the magic of all the people in this room comes into play. We can have as many discussions at a CEO level as we want. And if our client teams on the ground are not working together, it falls apart. Falls apart directly in front of the client. Yes. And that is a really hard thing to do. [00:06:45] Allison McFadden: So I’m passionate about the alliance work because that that work is what makes it happen at the corporate level. [00:06:53] James Kang: Cool. Um. I’ll start here. So in Nvidia is a accelerated computing platform company. Um, if you asked. Anyone on the, on the street about a year ago, what is ai? A lot of times they would say AI is, is open ai, or it’s philanthropic. [00:07:12] James Kang: Um, Jensen and I’ll, I’ll reference Jensen a lot today, um, because he is our leader, um, but he also sets the strategy in the direction for Nvidia. He talks a lot about AI in the metaphor of a five layer cake. And in terms of the five layer cake, you start off with the foundational bottom layer being power and energy, which sustains. [00:07:32] James Kang: All of our data centers, you move up the stack in terms of chips. So things think of Foxconn, think of TSMC. Next you have the infrastructure layer. So obvious choice is AWS, and then you get to the models where you do have the philanthropics and the open ais. But finally in at the precipice, you have the application layer. [00:07:53] James Kang: Ultimately, the reason why I mentioned all different stacks of the layers, the five layer cake, is the fact that the application layer is the most important. And so when you think about. Partners like Elastic or ServiceNow Trend, ai, CrowdStrike. Every time you pull from the application layer and you see a success, it pulls all five different components of that layer up. [00:08:13] James Kang: And so ultimately, as I think about success, it’s it’s being able to develop these co-sell wins at the application layer and really demonstrating that through extreme co-engineering and co-design with all the different application. Infrastructure, power and energy layers in mind. Um, Jensen also likes to think of himself not only as the CEO and founder, but also as the, the chief Marketing Officer. [00:08:35] James Kang: We are a very event driven company, and so at our big events like GTC or at big industry events like CES or Computex, he likes to show up on the biggest stage, biggest stages and showcase the partnerships with not only ISVs and GSIs, but also with end customers. And so that’s what I think about when I think of SA success. [00:08:56] Vince Menzione: That’s a really good point. You talked about, Allison, you talked about having an alliance strategy, or at least you teed it up, so I thought maybe we would go there for a second. Right? Like, what does a great alliance strategy look like and why is it important to the success of the partnership? [00:09:11] Allison McFadden: Man, I, uh, I have so many opinions on this. [00:09:13] Allison McFadden: We could probably be up here all day. That’s [00:09:15] Vince Menzione: okay. [00:09:16] Allison McFadden: Um, no, I think. Uh, there, there are a couple things, and the first one that comes to mind is focus. We cannot be all things to all people. Um, so when it comes to think about some of the, the work we’re doing with Elastic, we have a very, very clear point of view on what client problem we’re solving, what clients we want to talk to. [00:09:38] Allison McFadden: It helps if, um, from an ISV perspective, if there’s a very clear fit in. The Accenture portfolio or whatever, you know, SI consulting partner. You’re working with a very clear fit in the portfolio and we know what we’re not gonna go after, what we’re not gonna spend our time on because we have, we have this tendency, there’s millions of people. [00:10:00] Allison McFadden: The ecosystem chart that, you know, Vince, you showed up there, there’s so many connections. There’s probably more connections there than there are atoms in the universe, right? So, um. Defining what we do together and what we don’t do together is the first thing that pops to my mind. [00:10:19] Vince Menzione: Reka, do you have a perspective on it since we’re gonna, we’re gonna talk next about what you’ve done together, but, and I also wanna get mass perspective as a hyperscaler partner here as well. [00:10:29] Rekha Thangellapalli: Yeah, I mean from my perspective, I, I’m gonna, you know, kinda echo what Allison said is to be just maniacally focused. Yep. Um, because, especially from my perspective, so Elastic has three different solutions, right? We’ve got search, we’ve got observability, we’ve got security that map to completely different business units within Accenture. [00:10:47] Rekha Thangellapalli: And of course Accenture does a lot of things. And so, you know, when we first came together it was like. Okay, what are we gonna focus on? What industries are we gonna go after? Which segments are we gonna go after? Which customers, you know, um, outcomes are we trying to solve? And I think that sort of maniacal focus is the number one contributing factor to, to the fact that I’m like, up here on stage today. [00:11:12] Rekha Thangellapalli: Great. [00:11:14] Vince Menzione: Matt? Perspective? [00:11:16] Matt Yanchyshyn: Yeah, I, I, I guess I was trying to. To add something, uh, additional from an AWS perspective, uh, when it comes to, you know, what does a great alliance look like? Uh, AWS is obsessed with data, you know, in data we trust. And, and so the best, um, and, and this goes sales business problem, and it’s not just the engineering teams. [00:11:34] Matt Yanchyshyn: And so, uh, you know, Accenture does a good job of this elastic, definitely. And if you can come to the table with, um, quantifiable proof of the value of customer outcomes and partnerships. Um, you’ll win all the time and it’ll be a durable relationship with AWS ’cause we really are this data obsessed company and, and even the most senior sales leaders. [00:11:54] Matt Yanchyshyn: Uh, and so what I mean by that specifically is like if you, if you can show like your a RR to land an a RR conversion ratio, like in in numerical format, it’ll light up our sales leaders and, and they’ll be all, and they will co-sell with you all day long. If you can show the, I mentioned this earlier, like the AWS service, uh, whether you’re consulting company or, um, elastic and, and how the shape of customer accounts change positively when we work together. [00:12:15] Matt Yanchyshyn: That type of sort of quantifiable data works particularly well from an alliance perspective. With AWS as a partner, we, we really are like this data in sort of results out company. Um, so I, yeah, that’s just adding to the great points that were already made. I would say specific to AWS that that’s key. [00:12:30] Matt Yanchyshyn: Yeah. And I’m gonna bring up one more thing. I want to dive in on the, the joint value proposition, but you mentioned something that made a lot of sense and resonated to me about the organizations once you get out of partner, the partner world that we all know and love. Mm-hmm. Once you get down into a field organization or account management organization. [00:12:49] Matt Yanchyshyn: Not as much understanding and really organizations do a bad job here, honestly, in terms of enabling the field organizations. Do you agree? [00:12:58] Allison McFadden: I agree because I, I agree. And, um, you know, I think that’s one of the things, and, and I, I, when I joined Accenture, what we had was a lot of wicked smart architects delivering programs to clients in the field. [00:13:15] Allison McFadden: Very smart, very deep in AWS knowledge. Um, and that was awesome for the 10 clients they were staffed on and to get that understanding of how AWS works and I dream about lar, right? Like, this is a good, you know, but that takes real effort and real work. Yeah. And it’s, it’s um, almost like being a language translator. [00:13:37] Allison McFadden: Yes. For me. Yeah. So, you know, I had to deeply learn AWS so that I could. [00:13:42] Rekha Thangellapalli: Sure. [00:13:42] Allison McFadden: Teach my account teams. My account teams are really smart. They know who they’re selling to. They know their customers. They know what their customers need. They do not know what AWS has to offer always because they’ve got 20 partners lining up to try to tell their stories. [00:13:57] Allison McFadden: Um, they don’t know how to ask of the AWS team or the elastic team or the Nvidia team. Yeah. What they need [00:14:02] Vince Menzione: this co-selling piece. Yeah. [00:14:04] Allison McFadden: And so that is where, um. We had to build that muscle even around our AWS practice, which was a huge practice at Accenture, but we didn’t necessarily surround it with that kind of enablement and um, almost deal coaching layer. [00:14:21] Vince Menzione: So Elastic and Accenture came together. I dunno which one of you wants to lead this part of the conversation, but you will, right? Yeah. So tell us about the genesis of this and why. And a lot of people dunno what Elastic does, but you do some really incredible work. Like I, somebody told me one day was like, oh, you know, Uber, like, that’s elastic, powering all that. [00:14:41] Vince Menzione: Like, we don’t think about that. That the engines that you have and the, the backend to the customers, huge customers. [00:14:48] Rekha Thangellapalli: Yeah, absolutely. Um, so when AWS launched this feature last, um, reinvent where basically it allowed, you know, channel partners such as Accenture to be able to bundle up their services, their data assets with an ISV solution and put it on marketplace, um, you know, Accenture and Elastic immediately saw an opportunity. [00:15:09] Rekha Thangellapalli: Um, at the time most customers were doing gen ai. But they were running into the same challenge, which was that their data just was not ready. And by the way, this is a problem we were solving. Outside of marketplace. I think the, the feature that you guys launched just gave us a way to package it up and to be able to create this repeatable solution, which we call data readiness engine for gen ai and put it on marketplace. [00:15:40] Rekha Thangellapalli: And, um, this to me was a success because. Each company had a clear reason to invest. Um, so for Accenture, they were able to, you know, create a very differentiated services led offering. Uh, for Elastic, we were able to expand on our AI story. And for AWS, um, you know, it drives marketplace adoption, increases cloud consumption, all of that great stuff. [00:16:07] Rekha Thangellapalli: And customers, of course get. A solution to a very real problem that, that they were having. Um, and you know, the surprising part for me going through that journey was that, um. The pitching, the idea, getting the budget, getting the executive sponsorship was actually the easy part. The hard part was getting all three companies to come together, uh, to go from idea to launch in a very ambitious timeline of six weeks. [00:16:37] Rekha Thangellapalli: Nice. And so, you know, this was very much like. Doesn’t matter your title. We’re rolling up our sleeves and we are on this outcome together. Um, and so we literally built a RACI matrix, a project plan, and you know, we had daily standup calls for six weeks where literally. At least one person from each three of these companies called in, you know, got rid of any blockers and we made sure we were on target for that timeline. [00:17:07] Rekha Thangellapalli: Um, and you know, at the end we had a successful launch. But I think my favorite part about the story is the impact that we’re having and, um. My favorite story comes from a global pharmaceutical company that, you know, had basically nine petabytes of data spread across six different continents. Wow. And by working with Accenture and Elastic, they were able to build that trusted foundation that their AI and their agents can, you know, kind of safely tap into and be accessible at scale. [00:17:41] Rekha Thangellapalli: Um, so that’s my version. Allison. [00:17:44] Allison McFadden: Yeah. Well, I don’t have a lot to add. I just, I would say this is a good example of a couple of principles, right? One is having a forcing function is never a bad idea. Sign up for a big event, sign up. I’m like, I’m here with my, you know, Nvidia guys saying, sign up for the event. [00:17:58] Allison McFadden: It’ll make you move quick, right? [00:18:00] Audience Member: Yes. [00:18:00] Allison McFadden: Um, so that is one, but two, one of my mentors once told me, when you’re designing any kind of, you know, offering go to market motion, it has to get blood to all organs. If it does not get blood to all organs, it does not go [00:18:14] Vince Menzione: nice. [00:18:14] Allison McFadden: Um, [00:18:14] Vince Menzione: I love that analogy. [00:18:15] Allison McFadden: Oh, I love it. And I can talk all day. [00:18:17] Allison McFadden: That guy was brilliant. I love him. But, um, no, and, and so Elastic did a really nice job of bringing the tech to the table. Um, our team has to trust in that technology and its ability to scale, right? Um, because at Accenture we have to be able to deploy across 700,000 consultants. Um. And yeah, so I think those are the two, two things that really worked well here is we had, uh, trust in the technology solved a customer need. [00:18:50] Allison McFadden: Um, it drives, we don’t even talk about, like, yes, it drives marketplace revenue, but it unlocks work that we do that drives even more revenue to our AWS Friends. Right. So this is a, this is a, um, product that’s getting your data ready for AG agentic. It’s a messy problem that everyone’s dealing with, and it removes blockers for clients and it unlocks more, you know, ag agentic work on top of that. [00:19:15] Allison McFadden: So, blood to all organs. [00:19:17] Vince Menzione: So, was that the proposal going forward to say we need to have, we need to have trust in the solution. We need to drive significant revenue. It needs to be something all of our, you know, seven, 700,000 people. Can be a part of and help drive? Is that how you think about? [00:19:32] Allison McFadden: Yeah, and for us right now, um, it’s an interesting time for Accenture. [00:19:36] Allison McFadden: Our clients are asking a lot of us, and what it does is it having some of these accelerators helps us deliver cheaper, better, faster to our clients, which is what they’re demanding of us right now. Um, so it’s an accelerator to client outcomes. [00:19:55] Vince Menzione: James, what is NVIDIA’s role and how do, how do you enter the equation here? [00:20:00] James Kang: Yeah, it’s, um, it’s a good question. Um, I, I would say that Nvidia is probably one of the most misunderstood organizations in the world. Um, despite the, uh, the market capitalization in the valuation of the company, we have a very tiny organization. Um, what I mean by that is, um, if you think about. [00:20:20] James Kang: Salesforces and field sales organizations. Um, we’ll take Salesforce as the account or the customer. As an example, we have one account manager at NVIDIA that no, not only covers and is responsible for the relationship with Salesforce, um, but also manages. Automation Anywhere as well as DocuSign. Whereas at AWS, in contrast, like there are full armies and teams Yeah. [00:20:45] James Kang: That are supporting the Salesforce relationship. And so as you think about partnering and working with Nvidia, the focus has to be on really. Extreme co-design, but also being very prescriptive in terms of what are the very specific customer outcomes that we are solving for. And the guidance that I would give is bring in Nvidia into that equation and that conversation as early as possible because that [00:21:10] James Kang: co-engineering and co-design needs to be part of the foundational building blocks in order for you to come out with a end solution that checks all those different requirements. [00:21:20] James Kang: And so I think. Again, like going back to Nvidia, um, we like to talk about two different types of brains. A brain one and a brain two. Uh, brain One you think about the next quarter and making sure that you’re hitting the revenue targets for the next quarter. Brain two, you think about a long-term goals and potentials looking around corners and being very strategic. [00:21:41] James Kang: The saying internally is without Brain one, there is no oxygen, but without brain two, there is no future. And everyone at NVIDIA is trained to think in that brain two mentality. [00:21:52] Vince Menzione: Wow, Matt. [00:21:54] Matt Yanchyshyn: Yeah, I, I was just thinking I love the blood doll organs. Uh, and so just on, on that note, um, and, and, you know, the multi-product solutions that, that you, you built together, uh, that is a really good example of blood do organs because like we all know, that’s how customers buy. [00:22:07] Matt Yanchyshyn: They, they buy solutions and increasingly they’re looking for combinations of ISV, sometimes multiple products from multiple ISVs with services. Uh, often they’re buying it through a resell motion. You know, and they, and, and so that from a customer perspective, they want a single place to go. And so that’s the multi-product solution. [00:22:24] Matt Yanchyshyn: They wanna find everything they need, they need Accenture, they need Elastic to solve a specific solution. And I think where that’s headed is even more specific listings, like with AI powered listing experience, like, you know, elastic Plus Accenture for, I’ll make something up like a manufacturing workload. [00:22:37] Matt Yanchyshyn: And so this solution based. Uh, sort of buying is, is very customer centric. It’s what customers want. We all know that. But that’s, that’s the customer sort of organ, I guess. Um, but then, you know, you all have SCAs and those SCAs have marketplace commits. It helps if that gets transacted through marketplace helps the AWS relationship, you know that that’s an organ. [00:22:55] Matt Yanchyshyn: It’s the relationship. It’s, it’s the commercial construct and that you have, uh, that that’s another organ. You’re marketing people. They, that’s another organ. They don’t wanna land, uh, leads on a static marketing page. They wanna land a lead on a, a storefront with a multi-product solution that can actually convert and that you can actually buy it through that. [00:23:12] Matt Yanchyshyn: So the marketing person’s happy because they, they have less churn. Uh, and then, you know, our reps are happy ’cause guess how they get paid? They retire quota when they sell Marketplace. And they, we also, Jay McMain will tell you, that’s another organ called Jay or on, on you now. Um, [00:23:27] Matt Yanchyshyn: he’ll like that. I’ll call him up and tell him that. [00:23:29] Matt Yanchyshyn: Yeah, [00:23:30] Matt Yanchyshyn: but he, he’ll tell you, you know, don’t believe me. Obviously, never believe Matt, believe, believe the, the data and, and his data shows that. Those deals will close faster and larger if you use marketplace. So that’s, that’s a lot of organs. That’s the whole body. Um, but you know, when you have your customer happy ’cause that’s how they wanna buy your field happy. [00:23:45] Matt Yanchyshyn: Um, and, you know, the relationship happy and you know, your marketing team happy. Uh, and, and Jay happy. Um, and, and you know, I think that multi-product construct and, and the way you kind of use it to model a partnership and the way buyers ultimately wanna buy is, is really powerful. And so I, I think it’s, you know, it’s really a manifestation of how. [00:24:04] Matt Yanchyshyn: We kind of intend and to go to market anyway. Uh, so I think, you know, and thanks for leading the way, by the way. You’re, you’re amongst the very first, so that’s great to see. [00:24:11] Matt Yanchyshyn: So these storefronts are really helping this drive, drive this. Well, [00:24:13] Matt Yanchyshyn: that’s the next evolution. Like we’re talking about the multiproduct solution. [00:24:16] Allison McFadden: I’m JJ Accenture storefront. [00:24:17] Vince Menzione: Yeah. Oh, there you go. I mean, j and j Accenture storefront. [00:24:20] Allison McFadden: We’re gonna talk about that. [00:24:20] Matt Yanchyshyn: Yeah. I mean, [00:24:21] Matt Yanchyshyn: Accenture also leading the way yet again with storefronts. And so I think the combination of. You know, again, I was talking a lot about conversion. Yeah. And you know, buyers know sometimes they know what they wanna buy and, but if you really wanna convert that lead, you wanna land them again, something that combines, you know, elastic Accenture’s services plus software, but in a storefront that is, you know, surrounding with just the solutions they want so they don’t need to kind of go searching. [00:24:42] Matt Yanchyshyn: So, you know, ultimately reducing that time to close, I guess, really ’cause meeting the customer where they are with what they need. [00:24:51] Matt Yanchyshyn: So we talk about co-selling a little bit. We, Jay and I talk about this all the time. We gotta keep looping Jay in here, even though he is not even in town this week, but Reko, um, what does co-sell look like inside Elastic? [00:25:02] Matt Yanchyshyn: You’ve got, we talked about an incredible leadership team. I’ve gotten meet some of your leaders. Seems like you drive, you do a good job internally driving that. Let’s talk a little bit about it. [00:25:11] Rekha Thangellapalli: Yeah, and this is something I’m, I’m personally very passionate about. Um, co-sell is. Very much a journey, not a destination. [00:25:20] Rekha Thangellapalli: And I think step one for us is recognizing the different partner types that we have. Because at Elastic we work with, you know, OEMs, MSPs, resale distributors, GSIs, um, and they all bring something very unique. To the customer lifecycle and they all contribute very differently within, you know, our own sales cycle and sales process. [00:25:45] Rekha Thangellapalli: And so, you know, figuring out what is the unique benefit they bring, how do we enable them? So training and enablement is a huge piece of it, and so is making sure we’ve got the right metrics to measure success. Um, I know a lot of companies look at partner sourced as the north star, and that’s great, right? [00:26:06] Rekha Thangellapalli: Because that is undeniable. You can say, Hey, that would not exist if it wasn’t for my partner team. Um, but we’ve also noticed that when we bring in GSIs, it actually increases renewal rates. It significantly increases. Um, a RR over time. Um, it expands deal sizes and so these are very real metrics that we can point to, um, beyond just the co-sell and the partner sourced number. [00:26:32] Rekha Thangellapalli: Um, so for us it’s looking at it from a very holistic perspective, but also catering it towards that unique partner and making sure we’re doing everything we can to set them up for success and setting up the partnership for success. [00:26:47] Vince Menzione: So clo close win ratios, deal size and renewal rates? [00:26:52] Rekha Thangellapalli: Yes. For specifically for geos size. [00:26:54] Rekha Thangellapalli: Yeah. [00:26:55] Vince Menzione: Very interesting. Allison, uh, what had to change internally to produce these co-selling? We talked a little bit about the field organization and enabling a, a group of, and, you know, account sellers that are very customer focused and enabling them on the co-sell side. What had to change internally to drive that? [00:27:13] Vince Menzione: Yeah. [00:27:14] Allison McFadden: I, I might have already alluded to this a little bit in a previous answer, but, um, creating the capacity to develop, build, and sell these solutions, um, inside of a large GSI, where billable hours is kind of the number one metric on the table. Um. Is part of the investment that we had to make within Accenture to get this done? [00:27:36] Audience Member: Yeah, [00:27:36] Allison McFadden: so expert technology time. So we have technologists that understand the elastic technology. We do similar with Nvidia, by the way, we. We released some of their time to go co-develop the solution because it has to hold technical water, right? It can’t just be a marketing pitch. It can’t just be, it has to be a real, um, what’s the there, there. [00:27:59] Allison McFadden: So in order to actually do proper co-sell, we had to release some of that time. Um, to invest in those partnerships. Um, we’ve also done similar with some industry aligned business development leaders recently, so we have freed their time up to go. Uh. Open new conversations, educate client, account teams, go to clients, have conversations. [00:28:26] Allison McFadden: Um, so that, that’s a new motion that we, uh, have just kind of recently made, um, to allow them, I love this brain one, brain two also, right? So to allow them to focus on brain two, because a lot of our time. Typically spent delivery issues, you know, getting my hours, where am I charging my time? And so just freeing up a little of that capacity to do this work, um, helps get us in this brain two mode where we’re not just living to survive. [00:28:56] Vince Menzione: I. So, Matt, you’ve removed a lot. I mean, one of the things I admire, I admire AWS for being first to market and removing the most friction in marketplace of any of the vendors. Really, truly that. You talked about some of the announcements. How does some of, how does some of this tie PC central agents propensity sales plays, MCP, how does some of this tie to how, how you’re thinking about the future? [00:29:18] Vince Menzione: And how to enable more motions like this. [00:29:20] Matt Yanchyshyn: Yeah. Well, I, I think if you know my boss, UBA Borno, uh, you’ll know that she has a maniacal focus on automation. Yeah. Um, and, uh, co-sell is increasingly automated. You know, you were asking earlier about propensity data. You can get that propensity data in addition to sales plays and, uh, opportunity scores through the partner central agents. [00:29:38] Matt Yanchyshyn: So things that used to require multiple calls to A PDM, if you’re lucky to have one. Yeah. Or a p sm. Uh, you, you can now get through, through these agents, you know, uh, tech Systems, TGS, they, they manage what, over 5,500 customer opportunities with agents that they built on top of our partner Central APIs. [00:29:55] Matt Yanchyshyn: Um, and work Span has built a whole product and business that’s right on leveraging, uh, our APIs, our capabilities to sort of tie into your CRM. So, majority of all opportunities will be progressed and managed by agents. This year at AWS, we already have a majority of all customer opportunities, all app have a partner attached and I, I took a personal goal for a majority of those partner attachments, not to happen from a human. [00:30:22] Matt Yanchyshyn: But from our solution matching engine. And how do you get recommended by that solution? Matching engine, having a healthy ACE pipeline, thanks to partner central agents and the integrations you’re doing. And in addition to being the specializations and doing things like multi-product solutions and ultimately closing opportunities, you dream of LAR and so LAR will help that. [00:30:40] Allison McFadden: It’s more like a nightmare. [00:30:41] Vince Menzione: And so, you know, [00:30:42] Allison McFadden: it’s more like a nightmare, but [00:30:44] Vince Menzione: nightmare. Well, it’s, it’s, yeah. Nightmare of Laura and, and. Nice dreams of PRM, but the, um, but that’s the loop, right? I, I think, uh, increasingly co-sell for us, and in my mind, is largely a hundred percent automated. Yeah. Except for what matters most, those most largest, most strategic, most complex deals. [00:31:01] Vince Menzione: Where our highly paid and very skilled salespeople are most effectively used. [00:31:05] Vince Menzione: Yeah. [00:31:05] Vince Menzione: You know, the days of, you know, this person with 20 years experience selling, clicking, progressing opportunities through a pipeline, uh, should be over. Uh, and, and we need those people out, out selling and, and co-selling. And so that for me. [00:31:19] Vince Menzione: Yeah. That, you know, we talk a lot about co-sell, but I, I’m obsessed with automating as much of the co-sell as possible. [00:31:24] Vince Menzione: I remember going back to the ex Excel spreadsheets and, and that, that seems to be be Viva became spreadsheet jockeys. [00:31:31] Vince Menzione: Yeah. [00:31:32] Vince Menzione: And, and they stopped selling. They forgot how to sell. [00:31:34] Vince Menzione: Yeah. And people spend all this time doing lunch and learns and things like that. [00:31:36] Vince Menzione: And then, you know. Then the salespeople rotate out after 18 months and, and it, that’s, that’s the old days. Uh, you know, the new days are, are AI powered matching algorithms, uh, ag agentic co-sell, using the partner essential agents to get your data and, and putting that data to use automatically and, and what sounded like magic. [00:31:51] Vince Menzione: 12 months ago is being done, you know, by partners at massive scale across thousands of opportunities. You can do it today. And you know, I, there’s a guy named another Mike, right? Mike another Mike who they have, there’s like a guy who’s doing all this and I’m picking on Mike ’cause I, I know their system really well and I know the guy Mike grew easily built it for them. [00:32:08] Vince Menzione: Um, but, you know, I think, yeah, again, in the days of having 10 people sort of doing lunch and learn could be replaced by one or two people, building agents, uh, managing a massive pipeline. And, and that’s the future. [00:32:18] Vince Menzione: Exactly. James, your perspective on what breaks with co-selling? [00:32:22] James Kang: Oh, what breaks co-sell? Um, I would say. [00:32:25] James Kang: It, it starts and finishes with just misalignment and a loss of trust with the customer, especially when you have multiple partners or stakeholders involved. If you’re trying to do a three-way deal with a end customer and you’re not on the same page, you’re not gonna get to a successful outcome on, on the backend. [00:32:44] James Kang: Uh, the fix is a much more complicated story. I would say that to take a step back, um. We’ve talked about the five layer cake. We’ve talked about where NVIDIA kind of fits within the equation. We are invested in the ecosystem and so as different players and application organizations win and see these outcomes for end customers, we celebrate that success. [00:33:07] James Kang: Um, and as part of that kind of ethos of where NVIDIA fits within the ecosystem, we wanna make sure that not only. Our customers, but our partners like ISVs and GSIs are set up for success. Um, we do not as Nvidia sell hardware or GPUs directly to customers We use. Hyperscalers like AWS as kind of our force multiplier. [00:33:31] James Kang: And similarly we think of ISVs and GSIs as the force multipliers in terms of our extensions of how we, we kind of leverage the relationships and build the trust with our end customers. And so going back to kind of the question, Vince, I would say that it all comes back to trust and being able to build that mutual trust. [00:33:48] James Kang: Um, a lot of what we do when we co-sell with AWS is really on the software layer. Um, we actually have more software engineers at NVIDIA than we have hardware engineers, which is a weird thing to say, um, because everyone knows us for our GPUs. But because of that fact, we are heavily invested in Cuda and making sure that Cuda becomes the foundational layer for how not only our ISVs and GSIs, but also our end customers are building. [00:34:12] Vince Menzione: Very cool. So Reiki, you and James together on this production. Versus pilot with the Gentech ai. Tell us a little bit more about that. Where, where are you in the process? [00:34:24] Rekha Thangellapalli: Yeah. So I mean, in general, what we’re seeing out in the market in, in relation to sort of AI and, and customer’s journeys is that, um, at least from an elastic perspective, um, we’re seeing people very much in production when it comes to, you know, kind of AI assistant co-pilot use cases. [00:34:42] Rekha Thangellapalli: So, you know, things like, um, software development, customer support is a big one. Um, any sort of employee productivity use cases where there’s. Still a human in the loop somewhere. Um, and there’s a very like, clear path to value. And so we see the customers being in production excelling there. Um, no problem. [00:35:01] Rekha Thangellapalli: Where we’re seeing people still kind of in the pilot phase is those fully autonomous workflows where there is no human involved. The agent is reasoning on its own. Um, accessing multiple systems and taking an action on the user’s behalf. And what we’re seeing is that it’s not the intelligence of the agent that’s holding it back. [00:35:26] Rekha Thangellapalli: It’s more about giving the right context to the agent and having the right. Security kind of governance controls in place for the company to feel comfortable in putting these fully autonomous workflows into production. And that’s really the conversation we’re having is all right, what are the controls you need in place? [00:35:47] Rekha Thangellapalli: For you to release this to your business unit. Um, and what is the context that the agent is needed before we can comfortably let the agent make the decision on the user’s behalf? Um, James, I’d be interested to hear what you’re, what you’re seeing in the market [00:36:03] James Kang: plus one on all things context. I, I would even go so far as to say, um. [00:36:09] James Kang: H how many folks in the audience have heard of token maxing? Like this new term? [00:36:13] Rekha Thangellapalli: Yeah. Yeah. [00:36:14] James Kang: Um, I’ll, I’ll give a very specific example of, of Uber that went public. With the example of Claude, like they allowed all of their employees to use as many tokens as possible, and within the span of four months, they exhausted their full budget for the year, and so they had to pull back, and now there’s a cap on every employee. [00:36:33] James Kang: I think the number that’s circulating is $1,500 per month per employee, and so I think that is at least. In this multi-phase evolution of where we’re going to be and where we’re today, cost has become kind of the prohibitive force in terms of agentic AI at scale. Um, I think we are working on some very creative solutions in-house and Nvidia. [00:36:55] James Kang: Um. And we saw some really dynamic announcements this week when it comes to all things agent core, um, where we want to focus on very nimble ways for customers to be able to execute and go to market. And one extreme example of that is our investment within our open model strategy. So Nvidia, not only, again, providing GPUs, we actually offer our own op open models, which we call our Nitron models. [00:37:21] James Kang: And through our Nitron models, we are allowing customers to really develop and fine tune their own proprietary models in a cost effective manner. So right alongside the frontier models like OpenAI and Anthropic. It’s not a if then, it’s not an either or statement. It’s a, it’s a permutation, it’s an and So we’re giving you a cost effective alternative to not only bring your AgTech applications at scale by training on Nibo tron, which is open source, but then once you’ve kind of finished and fine tuned that specific training job to be able to. [00:37:53] James Kang: Go ahead and utilize your frontier models, whether it be OpenAI or Claude. And I know there’s other partners here that are providing those kind of different model capabilities. And so I think for us it’s, it’s a matter of choice. We know that this market is dynamic. It’s gonna be evolving over the next coming months as well as the next coming years. [00:38:10] James Kang: Uh, but we believe that we are positioned for a really unique dynamic expansion of AgTech use cases over the, at least the next three to six months. [00:38:20] Vince Menzione: Allison, for the partners in the room who are glazed over right now going, what do I, what do I do over the next 12 months? [00:38:26] Allison McFadden: Should I wake everybody up by saying, yeah, please. [00:38:27] Allison McFadden: Say go hurricanes. [00:38:28] Vince Menzione: Yes. [00:38:29] Allison McFadden: Is there anyone, anybody? Everyone’s like, boo. I get to leave the parade today to go home to parade. I live in Raleigh, so we’ve got our parade on Saturday. Nice. [00:38:39] Vince Menzione: Nice. [00:38:40] Allison McFadden: All right. Wake up. Um, all right. So for the $50 million partners in the room, um. $50 million is not small. You have something that works. [00:38:50] Allison McFadden: Right. This is great. What I would be thinking about is, you know, we’ve talked about focus before, but really doubling down on, you know, what is, what is your industry, what is your client like, ideal client that you serve. And build, um, almost that kind of community. You know, the, the clients we have move from firm to firm to firm. [00:39:17] Allison McFadden: And if you’ve done good work at one, you’re gonna follow ’em to the next. Um, so build that client demand in a specific place or specific client profile that is just like really knocking it out out of the park for you. Um. Scale with marketplace, right? So if you, I, I love some of the data that you were sharing in your talk earlier, um, because it’s like no overhead scaling mechanism. [00:39:45] Allison McFadden: I mean, it’s, it’s fantastic. Um, Accenture, other GSIs like us, we are investing in marketplace. So we’re investing in resources, um, to help us. Use marketplace more with our clients and we’re gonna capture, right, those storefronts. And if you’re present on marketplace, you’re gonna be able to catch, uh, yourself in that wheel. [00:40:09] Allison McFadden: So I think those are the, the kind of couple of things I would say is focus, focus, focus to drive that client demand and use scaling mechanisms like marketplace to really kind of, uh, accelerate. [00:40:24] Vince Menzione: Matt, anything to add there on the. [00:40:26] Vince Menzione: Well just, you know, Ja, James, you, I love the token maxing reference in Uber and it reminds me, you remember when cloud came out and everyone was like, oh, all these people are, are gonna use the cloud and costs are outta control and. [00:40:39] Vince Menzione: Um, a lot of people pulled back from the cloud and, and a lot of those companies no longer exist. And it’s similar with, with, uh, token maxing, like, oh, these agents are outta control. You have a choice. You can embrace them and figure it out and get governance and, and make your data available. Um, use the partner, central agent, move to agent to co-sell, or you can fade and die. [00:40:58] Vince Menzione: And, and that’s, that’s where we’re at. Uh, is, is the, the companies sitting here today embraced the cloud years ago and won. Uh, and and there’s a set of companies here today who are gonna embrace agents in the, for both buyers and sellers, and will win. And there are those who won’t and they won’t win. And so for me, it’s like we’re, we’re at a, we’re at a crossroads. [00:41:18] Vince Menzione: And, and if you’re gonna win, you gotta leap into that, you know? I love it. And, uh, and, and, and it’s, it means the cost of experimentation is so much lower now. Development and, and even business development or software development is, is agent enabled. And so you can take risks, you can experiment and, and you have to, it’s, it’s an existential moment. [00:41:37] Vince Menzione: Agreed. We’ve got a couple minutes left over for any questions. What do you think? Sure. Are there any here. I think there are a couple. Yeah, we’ve got, we’ve got a co-sell question I’m sure coming up here. [00:41:51] Audience Member: Um, I’m Cassandra, I’m the CEO of Partner Tap. And one of the questions I had was, I think, you know, the co-selling between the sellers is where things get. Really, really hard when you’re multi-partner. And so when I was listening, um, with, you know, the Accenture and Elastic together, you talked about how you had, you, you had to get these BD business development people. [00:42:22] Audience Member: Um, is this a new team that is over the client team? And how do these teams interact like with the elastic sellers? Are you doing a lot of coaching to the field and then with if AWS sellers are, are involved, like what is that whole picture? What does look like, [00:42:43] Allison McFadden: like [00:42:44] Audience Member: on the ground? I mean, that is the hardest part, I think, and that’s what we hear. [00:42:48] Allison McFadden: It’s so, it’s so, it’s so tough. Um, and I will, I’ll just say, so our business development leaders that we now have kind of. Expanded their capacity. They have always been, they have always been there. Um, but they have not been well resourced. They haven’t, they haven’t had very clear kind of job description. [00:43:12] Allison McFadden: I’m gonna say I, in the past they have been kind of focused on partner relationship. And so like more like an alliance manager and maybe working on some of the data. Right? So when I say I have nightmares about Lars, because we’re always trying to increase the LAR for Accenture and, and they were focused like in those detailed weeds of like trying to pass ACE and trying to call the PDM and all this stuff. [00:43:39] Allison McFadden: What we are doing is really pivoting them to be proper sales, business development focused on client outcomes and focused on. Technical skills to be able to describe what this solution is to the field. So, um, and because we need, I have many, many questions about, I gotta get agents to work with Eurogen co-sell so that that part somehow goes away. [00:44:05] Allison McFadden: So that’s a, that’s the thing we gotta solve still, but, um, so we’re pivoting them to be kind of driving. More of that co-sell enablement with the field, um, and taking that message to the field rather than being there, waiting for questions to come in from the field, waiting for like our field teams to discover, oh, I saw something that we’re doing with Elastic, like on a press release on LinkedIn. [00:44:30] Allison McFadden: Right. So we’re kind of trying to pivot them to be more proactive. [00:44:33] Vince Menzione: Very cool. [00:44:34] Rekha Thangellapalli: Yeah. And uh, Cassandra, that’s an excellent question because I think. Multi-party, you know, sort of tri-party offerings. The hardest part is operationalizing it at scale, right? Yeah. And so for this particular offering, we are basically having three routes to market. [00:44:51] Rekha Thangellapalli: So one is seeing how this offering fits into our existing elastic go to market. And so I am constantly enabling our field sellers to say, okay, within our three field sales place, here’s exactly where this fits in. Here are, you know, uh. Keywords that you hear in customer conversations where you bring up this offering and here’s a process of how it works. [00:45:14] Rekha Thangellapalli: Um, exactly At what sales stage do I bring in Accenture, how, you know, what are the roles and expectations? Right? So that’s on the elastic side. We’re doing the same thing on the Accenture side. So we’re doing a ton of training enablement and lunch and learns, and we’re also looking at how do we fit into. [00:45:31] Rekha Thangellapalli: Uh, Accenture’s AI transformation projects, we are the semantic layer, right, of their enterprise brain. And so it’s a whole different sales motion, um, and, you know, having the right assets, having the right process again to make sure that that goes smoothly. And then finally, we’re going directly to the customer. [00:45:49] Rekha Thangellapalli: So we are launching multiple external campaigns where, you know, if the customer raises their hand. We will, we will line up immediately. Right. Um, and so, [00:46:01] Allison McFadden: I mean, I can’t, I can’t, I can’t say how important that third leg of the stool is. ’cause the second part, she talked about getting into our catalog is the first thing. [00:46:09] Allison McFadden: ’cause my BU business development leaders have the catalog. Right. And that’s what they’re selling. So what Elastic has done has gotten into one of those offerings and then. If we have a customer that asks for it, that is the fastest way to alignment. That is like the number one thing that we respond to [00:46:26] Vince Menzione: customer at the center. [00:46:27] Vince Menzione: This is great. Well, I think we’re up to time. This was a great session. I want to thank you. This is what a great, what a great group. [00:46:34] Vince Menzione: Thanks for listening to the Ultimate Partner Podcast. If today’s conversation resonated, share it with a partner leader in your network. Subscribe where [00:46:43] Vince Menzione: you listen, and head over to the ultimate partner.com. [00:46:47] Vince Menzione: For show notes related content and the resources for this episode. And if you haven’t already, now’s the time to register for the Ultimate Partner Live Event in Reston, Virginia, October 26th through October 28th. Until next time, keep showing up in the rooms that matter because being in the room changes everything [00:47:09] I.

Why are companies investing heavily in AI, analytics, and data platforms while business leaders still struggle to see what is happening across their operations quickly enough to make confident decisions? In this episode of Tech Talks Daily, I speak with Massimo Merlo, Vice President for UK, Iberia, and Italy at Elastic, about why the next stage of enterprise AI adoption will depend less on who deploys the most advanced models and more on which companies can give people and AI systems access to relevant, trusted, and secure information when decisions need to be made. Massimo describes the problem as a lack of decision-grade visibility. Most large companies are not short of data. They have spent decades building data platforms, analytics systems, dashboards, cloud infrastructure, and reporting tools. Yet information remains fragmented across departments and applications, insights arrive too late, and employees often struggle to find the small amount of information that matters among enormous volumes of data. The result is a growing gap between having information and being able to act on it. Massimo explains why simply adding an AI model to this environment does not solve the underlying problem. If an AI system is connected to fragmented, outdated, poorly governed, or irrelevant information, it can produce convincing answers without providing reliable business outcomes. The quality of an AI model matters, but the context available to that model increasingly determines whether AI becomes a useful business asset or an operational liability. This leads to one of the biggest technology conversations emerging around enterprise AI: context engineering. Massimo explains how context engineering provides AI systems with the relevant data, tools, permissions, organizational knowledge, and guardrails required to complete a task safely. Rather than sending ever-larger volumes of information to AI models, companies need infrastructure capable of retrieving the right information and making it available at the moment a person or software agent needs to act. Fraud detection provides a practical example. An AI agent evaluating a transaction needs more than access to a powerful model. It requires customer history, behavioral patterns, company risk thresholds, permissions, compliance requirements, and the ability to recognize activity that falls outside normal behavior. Without that context, the system could block legitimate customers or approve fraudulent transactions while presenting its decision with complete confidence. We also discuss why digitally mature companies can still struggle with real-time decision-making. Massimo shares lessons from Elastic's work with organizations including Reed, the Met Office, and Rightmove, explaining why having sophisticated technology systems does not automatically make a company context mature. Information can still remain trapped between applications, teams, and databases, preventing employees and AI agents from seeing the complete picture when it matters. The conversation challenges another long-standing enterprise technology habit: adding more dashboards. Massimo explains why dashboards often provide visibility into what has already happened without helping people decide what to do next. Companies can continue adding reporting layers while employees become overwhelmed by information and remain unable to identify the actions that will improve customer experience, productivity, security, or business performance. A healthcare example demonstrates what becomes possible when companies solve this problem. Massimo shares how CogStack at King's College Hospital brought together unstructured patient information during the COVID-19 pandemic and made it searchable using natural language processing. Clinicians could find relevant information without waiting for technical teams to build new queries or systems, helping medical professionals access information when patient decisions needed to be made. For CEOs, CIOs, CTOs, data leaders, and technology teams trying to improve AI ROI, Massimo offers practical advice on where to begin. Do not start with another model, tool, or dashboard. Start with a business decision or workflow that is currently too slow, unreliable, or difficult to execute. Identify what information that decision requires, where the data is stored, who or what system needs access to it, which permissions should apply, and where information currently becomes delayed or disconnected. That process can reveal the visibility gaps preventing companies from turning their existing data and AI investments into measurable results. We also examine why search and retrieval are becoming infrastructure concerns for companies introducing AI agents. As software agents begin making recommendations and taking actions across business systems, their performance will depend on whether they can securely retrieve relevant information at scale. For business and technology leaders facing pressure to demonstrate returns from AI investment, this conversation provides a practical framework for improving enterprise search, context engineering, AI agent reliability, real-time operational visibility, and decision-making. The companies that gain the greatest value from AI may not be those collecting the most data or deploying the most models. They will be the companies capable of finding what matters, understanding its context, and getting trusted information to people and AI systems quickly enough to act on it. That is where better visibility can become better decisions, stronger productivity, and business growth.

Don’t let the AI wave crush you. Subscribe to our Newsletter: https://theultimatepartner.com/ebook-subscribe/ Check Out UPX: https://theultimatepartner.com/experience/ Dive into the seismic shifts happening within the AWS Marketplace and discover how AI, self-service product-led growth (PLG), and advanced co-selling strategies are redefining partner success. Matt Yanchyshyn, VP of Marketplace at AWS breaks down the recent announcements from the summit, illustrating how agility and adaptation are crucial to surviving the new agentic future. From lowering professional services fees to the explosion of business applications like ServiceNow, this conversation reveals the hidden mechanics of modern cloud procurement and how you can position your organization to capture massive enterprise opportunities before your competitors do. https://youtu.be/gaWxU1kgCLk Key Takeaways Adapting to the new agentic future requires agility rather than fighting the influx of AI tools. Lowering the listing fee for professional services from 2.5% to 0.5% drastically improves partner economics. Organizations without a self-service or PLG motion on the marketplace are literally leaving money on the table. Millennial buyers increasingly initiate complex enterprise procurements through self-service and AI-driven research. New AI-powered opportunity scoring empowers partners to prove their value internally and to AWS. Marketplace success hinges on optimizing metadata for AI agents, not just traditional SEO. If you're ready to lead through change, elevate your business, and achieve extraordinary outcomes through the power of partnership—this is your community. At Ultimate Partner® we want leaders like you to join us in the Ultimate Partner Experience – where transformation begins. Key Tags: AWS Marketplace, agentic workflow, med pick scoring, phoenix.ai, Cara Cloud, branded storefronts, product-led growth strategy, intrinsic value boost, SaaS evolution, self-service motion, Databricks credit model, Trend Micro companion app, MCP servers, opportunity score tracking, PPA drawdown, concurrent agreements, AAMI structural debt, CXML procurement Transcript: Matt Y Audio Podcast [00:00:00] Matt Y: The ability to adapt with change and kind of roll with punches. ’cause a lot of people are saying like, agents are gonna destroy everything. And, and the opposite has been true. [00:00:08] Vince Menzione: You can feel it happening. The ecosystem is shifting beneath us, the way hyperscalers are partnering, how AI is remaking the channel and what it means to win in 2026. [00:00:19] Vince Menzione: Welcome to the Ultimate Partner Podcast. I’m Vince Menzi, own your host. And each week I sit down with leaders at the intersection of technology, partnerships and outcomes. The voices shaping how ecosystems actually work. We talk about what’s real, what’s changing, and what it takes to lead in this era where the partner channel isn’t just part of the strategy. [00:00:42] Vince Menzione: It is the strategy because being in the room changes everything. [00:00:46] Matt Y: Let’s start. [00:00:50] Vince Menzione: And now on to the really important stuff. So, Matt, I don’t wanna butcher it ’cause I, a couple people have told me how to pronounce your last name and they said use the word magician and you’ll get close to it. But I’m just gonna introduce you as Matt Wy and I’m gonna ask you to pronounce your name on stage, but I want to have you join us. [00:01:08] Vince Menzione: So excited to have Matt wy. After a super busy day and night last night, come over from Brooklyn and join us today. Matt, so great to have you. Thanks. Thank you so much. Thank you so much. Alright, so pronounce your name for us. [00:01:23] Matt Y: Anyone wanna guess? Ian’s? It’s like magician. [00:01:27] Vince Menzione: It’s not that hard, [00:01:28] Matt Y: it’s not that [00:01:28] bad, [00:01:28] Vince Menzione: but I don’t wanna butcher. [00:01:29] Vince Menzione: I wanted to let you do it. Good. [00:01:30] Matt Y: What calls me Matt White. [00:01:31] Vince Menzione: That’s great. [00:01:32] Matt Y: Yeah. [00:01:32] Vince Menzione: So 13 years. [00:01:34] Matt Y: Four coming up on 14 next month. Yeah. [00:01:36] Vince Menzione: Wow. Congratulations. Yeah. So you’ve been there, you’ve been there since the early days. And we, we had a conversation. I had some Microsoft, former Microsoft colleagues. Uh, Theresa Carlson, for those of you who knew the public sector business. [00:01:48] Vince Menzione: Yeah. Who started, I mean, Andy came out, it was so funny because I was there and she was hosting Andy for a dinner and with all the CIOs of the federal government. [00:01:57] Matt Y: Yeah. [00:01:58] Vince Menzione: And she was still at Microsoft and it was actually kind of an interesting time. And she came over and did a lot of great things for a number of years. [00:02:04] Matt Y: Yeah. She [00:02:05] Vince Menzione: and a lot of great [00:02:05] Matt Y: business. [00:02:06] Vince Menzione: Yeah. She really like, it went from employee number one to 7,000. [00:02:09] Matt Y: Yeah. [00:02:09] Vince Menzione: And you, you were, you’ve been there all that whole time. Pretty much. [00:02:12] Matt Y: Yeah, I guess when I started in New York, just down the road, we were, uh, in a Regis facility. There were like 11 of us in, uh, just sitting around a table and we had to speak quietly sometimes because there was a, um. [00:02:21] Matt Y: Some type of a financial services organization down the hall and they’d listen to try and get stock tips on Amazon. Yeah, [00:02:28] Vince Menzione: I love it. [00:02:29] Matt Y: Never leaked. That’s [00:02:29] Vince Menzione: good. I love it. [00:02:30] Matt Y: Yeah, [00:02:30] Vince Menzione: you probably got some great stories and, um, we won’t have time for today ’cause I wanna leave some room for conversations on marketplace end questions. [00:02:38] Matt Y: Yeah. [00:02:38] Vince Menzione: But I would love to invite you back for a real, like, in-depth podcast and I would love to get the whole genesis story. [00:02:44] Matt Y: Let’s do it. [00:02:45] Vince Menzione: We’ll do it. Okay, so let’s talk about, let’s talk about yesterday for you. Uh, some, some really big announcements as well. I thought maybe you could recap a little bit of what’s been going on in the marketplace business and it’s an, it’s been an exciting time. [00:02:58] Matt Y: Yeah. Yeah. You know what’s, I think what was really nice yesterday is it was sort of the combination of bringing, uh, our partner services like Partner Central and all those other services together closer to marketplace. We’ve been doing that over, over several years. So Marketplace has some of its own. [00:03:12] Matt Y: Big announcements, like, uh, we have a, we formalized our list and sell initiative. For example. We have a new, so it we essentially reducing the cost, uh, to list on marketplace through a partner program. [00:03:22] Vince Menzione: Yep. [00:03:22] Matt Y: And incentives associated with that. We have a new AI powered listing experience, which I think is particularly important ’cause I think many of you are like me and watching your SEO numbers go down and watching your agent traffic go up. [00:03:33] Matt Y: And so having, uh, an AI assistance in marketplace to optimize your listings for not just to, you know, retain what you can of your SEO, but prepare for the newent future and improve your GEO as we’re calling it. So that, [00:03:45] Vince Menzione: so it’s GEO now? [00:03:46] Matt Y: Yeah. You know, there’s a little debate right now in the acronym Moral A A EO versus GO I’m going, I’m on the G team, so, yeah. [00:03:52] Vince Menzione: Alright. GEO [00:03:54] Matt Y: It’s like the, the, yeah, they’re gonna win. They’re like the Knicks, but the, um, [00:03:57] Vince Menzione: yeah, yeah, exactly. [00:03:57] Matt Y: But yeah, so AI assisted, uh, I mean, making. The most of, like, essentially marketplace is an excellent conversion engine. And so using AI to help improve that conversion engine in the form of your PDPs for both humans and agents. [00:04:08] Matt Y: So that was an exciting launch. Um, I got the most applause when I announced that. We lowered, we made the economics better for, uh, consulting offers professional services, nice to marketplace. We lowered the listing fee from 2.5 to, to 0.5% and wow, it goes even lower in certain circumstances. So just improving the economics. [00:04:24] Matt Y: I’m really excited to. Really partner with a lot of you to reinvent services through, through the marketplace like we did with SAS and other areas. Uh, and we’re doing with agents right now. So that was a big one. And then a whole series of announcements around, um, how we’re making it easier and more cost effective and more efficient to partner with AWS. [00:04:41] Matt Y: So using AI to, uh, using med pick scoring to automatically progress opportunities so you don’t have to kind of wait on a human. To, to click and progress, you know, that that can take days. And, uh, if you, if you wanna have an opportunity and have that be cos sold with AWS, that can be through a mix of agents for the long tail and with humans in the, in the sort of top end and more complex. [00:05:00] Matt Y: And allowing AI to help all the partners improve their opportunity quality so that we can better co-sell together. So. Yeah, I said AI a lot intentionally. Um, [00:05:09] Audience Guest: yeah, [00:05:10] Matt Y: AI sort of in the whole cycle for buyers, for sellers, uh, for operational efficiency, cost of sales. So a lot of announcements. I think I hit the big ones, so yeah. [00:05:18] Matt Y: I’m Might have missed something there. There we go. [00:05:21] Vince Menzione: George. [00:05:21] Matt Y: Oh, and storefront. Yeah. Thanks George. See, I look at George to see what I missed. Uh, we, we acquired a great company called phoenix.ai late last year. Okay. And you, you actually were said Caresoft and Yeah. Be down. Uh, [00:05:30] Vince Menzione: yeah. [00:05:30] Matt Y: So if you’re familiar with Cara Cloud, they have a procurement portal. [00:05:33] Matt Y: It’s heavy use by the US government, and they, um. Uh, we, we acquired them, uh, the really great growth company. They have over 70 logos now, and they help you build a branded storefront on marketplace, which obviously is important in the government space. If you’re procuring on a certain contract with a certain reseller, um, you know, there’s a certain set of products you’re allowed to buy. [00:05:51] Matt Y: But what we’re finding is even down on Wall Street, you hear, um, enterprises are, are using storefronts for internal procurement and they wanna have a curated collection of, of partner products and, and your own ecosystems internally. So we’re selling to both customers. And also to channel partners to build custom storefronts, branded storefronts for, and [00:06:07] Vince Menzione: it makes total sense, right? [00:06:08] Vince Menzione: Yeah, because you wanna li you wanna limit the, the viewing and, uh, and get, because I mean, how many different listings do we have? Like over 30,000? [00:06:16] Matt Y: Yeah. Yeah. There’s, I think the official numbers over th we have over 36,000. I was checking from over 6,000 vendors. Um, it’s a lot. And, and that’s gonna explode with the AI powered, uh, listing, uh, experience that we launched. [00:06:26] Matt Y: We’re gonna make it easier. And I guess what I’ve been telling partners is. You know, customers aren’t clicking through categories anymore. They’re using AI to search. And so it doesn’t matter how big our catalog is, what matters is being found. And what matters is converting that buyer. So if you have a. [00:06:39] Matt Y: If you’re running a demand gen campaign for say, like, you know, life sciences in, in Jersey and there’s a specific buyer at j and j, you wanna capture, that person doesn’t wanna be just dropped onto a generic marketplace, 30,000 listings. They wanna be dropped in a very specific place where they’re seeing like life sciences offers from Accenture, for example, coupled with a life sciences power thing with Elastic, you know, like, but a solution. [00:07:00] Matt Y: And that they want to land in a curated place where that highly intention buyer can be converted effectively. So that, that’s what we’re doing with all this. [00:07:06] Vince Menzione: And that’s where the GEO comes in because [00:07:09] Matt Y: Yeah. ’cause that buyer might be an agent That’s right. With, and that agent has is even more fickle, honestly. [00:07:14] Matt Y: And you know, what used to be milliseconds for the human before they kind of click away is, is now perhaps microseconds. Yeah. And so, uh, you know, having the right metadata and, and the right positioning, uh, the right story that an agent or a human can pick up to ultimately. Uh, complete their product research and choose your product is, is critical. [00:07:30] Vince Menzione: Very cool. Very cool. So before I, I, I’ve been asked to ask you this because I, I’ve had this con, people have brought come to me and said, you gotta ask Matt about music. He’s a big music guy. And, uh, so what are your favorite bands? [00:07:49] Matt Y: So, I mean, the, the real answer is, uh. I, I go to about a show about every week. [00:07:54] Matt Y: As, as Mike Trill knows, uh, we heard a show last night. Um, we were, uh, just a few hours ago, really? And, uh, um, favorite band, uh, well, I’ll tell, I’ll tell a story. I, I had a side hustle with MTV for years. Um, I used to run a music website. Um, oh, that’s cool. I didn’t know that. It got, it got kind of popular. It got sponsored by, if, if anyone’s into like early hip hop. [00:08:16] Matt Y: It got sponsored by a group called Jurassic Five. ’cause he, one of them reached out to me and said, nice. Hey, uh, you know, I’ve been, I like your website. And he ended up paying for a web, hosting a Dream host, if you remember, of cost back then. [00:08:26] Vince Menzione: Oh, Jesus. [00:08:26] Matt Y: Because I was broke and couldn’t afford it. And then, uh, and then this band sent me like a, a single and said, Hey, you know, trying to get the word out about our little band, can you help us out? [00:08:35] Matt Y: And I put their, uh, I put their, you know, single up on my, on my website and it blew up. And that band is Vampire Weekend. So they’re kind of big now. Wow. Yeah. Um, and uh, that got picked up by like Vanity Fair and all these other guys. And then I got sponsored by MTV to essentially write. Music reviews for years on the side. [00:08:51] Matt Y: So I was working for the Associated Press, laying cable in sports and war and, and, uh, yeah. So Vampire Weekend was good to me that, that they, they kind of paved a way to go to a lot of free shows over the years and a lot of bands and see a lot of great music. But yeah. [00:09:03] Vince Menzione: That is very cool. And that, and how did that get your day? [00:09:05] Vince Menzione: WS It was just a, it was just the technology path that was like, [00:09:09] Matt Y: I mean, it’s a, it’s a, I guess it’s a bit of a long story, but, um, the. There’s many versions of this story. I’ll tell the, tell the one quickly. I was living for free in a Fulbright scholarship house in West Africa. You, we can talk about how that happened another time. [00:09:23] Matt Y: And, uh, a guy had sort of fallen down on the floor ’cause he’d had too much to drink. And I, I sort of lay down beside and be like, Hey man, are you all right? And, um, he, uh. He worked, he, he worked for the Associated Press and next day I had the job, um, being West Africa, head of technology for West Africa. [00:09:37] Matt Y: And because of that, um, and as I learned years later, the AP didn’t have dr they had no disaster recovery. Yeah. And I, I can tell you that now ’cause um, you know, 16 years since I worked there, but they, uh, I put the DR in, um, on AWS and we’re talking like, yeah, 16, 17 years ago. This is early. It was early days. [00:09:56] Matt Y: And I, I swear to God, I paid for. Uh, our AWS bill using, um, taxi receipts, fake taxi receipts that I bought in on Nigerian market, um, because there was no budget and so, you know, it was like 30 bucks. [00:10:08] Vince Menzione: I was gonna say swipe a credit card, but they didn’t [00:10:09] Matt Y: knew that this is the entire press this before. [00:10:11] Vince Menzione: This is before, yeah. [00:10:12] Matt Y: Yeah, like the entire ap. Um, and, uh, so AWS called me like, who are you? Like, why, why are you paying on like this like low limit credit card for like the ap? Like, who are you? And, uh. Next day I had the job. Well, a week later I had the job with aw WS. That so cool. So that’s the story’s [00:10:29] Vince Menzione: cool thing. [00:10:29] Matt Y: Yeah. [00:10:30] Vince Menzione: Very cool. [00:10:31] Vince Menzione: Uh, sports teams. So Knicks fan. [00:10:34] Matt Y: Yeah, I mean, I like the Knicks. Um, they’re h hockey, I’m not allowed to say anything different. No. I appreciate them. Uh, I’m a Raptors fan. I grew up in Toronto mostly. Yeah, yeah. Uh, so, and you know, when they won, uh, that was very exciting as well. So no, Nicks are great. I like the Knicks. [00:10:49] Matt Y: Nothing against the Knicks. Um. They’re fine. Yeah. [00:10:54] Vince Menzione: Hockey, hockey fan. Favorite hockey teams? [00:10:56] Matt Y: Oh yeah. Itron. Maple leaf. Maple leaf. Yeah. They’re gonna, they’re gonna win. Of course. Of course. Yeah. Um, like every year they’re actually, we [00:11:02] Vince Menzione: have some Canadians laughing in the sand. [00:11:03] Matt Y: Well, the leaf are, are, are the Knicks of hockey? [00:11:05] Matt Y: Like Yes, they are. You know, it’s 67 years out, coming up on 68 since they won, so That’s crazy. 53 is nothing. I know. Pain. So. Yeah, definitely the least. Yeah. [00:11:15] Vince Menzione: I love it. I love it. It’s so cool. Yeah. So what was the, uh, what was the, what was the last concert you went to? [00:11:22] Matt Y: Well, literally last night. Oh, it was last, [00:11:23] Vince Menzione: oh, that [00:11:24] Matt Y: was actually concert were my favorite bar in the world. [00:11:26] Matt Y: This place called Sunny’s. Uh, it’s, you know, I, I took Mike and, and Matt from, from Texas and from TGS down there to sort of see my neighborhood and they’re like, where are we? And I’m like, yeah, I live here. Uh, sort of an industrial part of Brooklyn. And, and we went to see, um, I dunno what you would call it, like. [00:11:40] Matt Y: I guess it’d be like roots music. There was a woman with an accordion and a guy with a big cowboy hat. Yeah, it was, it was fun. Yeah. [00:11:47] Vince Menzione: That is so funny. Alright, we’re gonna shift back years. Um, important time right now for partners. What, what should partners be looking out for the most? What would you say to them in terms of what’s the, what’s their real headline for them? [00:11:59] Matt Y: Well, I, I, you know, to borrow from you actually, you know, I liked, uh, the, the principles you had up there and, and with agility, um, you know, there’s a lot of fud flying around right now. You know, people. People were like, oh, it’s the demise of sis with the arrival of ai, you know, everyone’s gonna be using agents. [00:12:13] Matt Y: And then it turns out it’s been a huge boon for most, uh, you know, system integrators and consulting companies that I work with. They all have, you know, the, the good ones especially have vibrant consulting practices now, and everyone is deploying fds, uh, you know, um, the new, the new cool acronym. But it’s, it’s essentially created a huge opportunity for the consulting space. [00:12:31] Matt Y: Uh, and similarly, uh, you know, there there’s this narrative around the sa sa apocalypse, which I really hate, you know, ’cause it was, uh, premature and kind of a trigger reaction from the stock market. And, you know, just look, look what Snowflake did. And, you know, they did what a lot of SaaS companies are doing, but they, they added a nice sort of glaze of positioning and, and, you know, their stock popped and they did pretty well. [00:12:50] Matt Y: And so I think the ability to adapt with change and kind of roll with the punches. ’cause a lot of people are saying like, agents are gonna destroy everything. And, and the opposite has been true. For the more successful consulting companies and software companies who have become agentic. But SaaS hasn’t gone away, you know? [00:13:05] Matt Y: No. Look at our own marketplace. We have this agent marketplace, but people aren’t buying atomic agents at scale. They’re buying ified SaaS solutions with sort of agent sidecars, which has created new opportunities for candidly additional licenses, [00:13:16] Vince Menzione: right? [00:13:16] Matt Y: Um, as customers sort of want to consume more AI services on top of their. [00:13:20] Matt Y: On top of their SaaS solutions. So I think being agile, you know, you see like ServiceNow as part of our billionaires club. Yes. They’re not going anywhere. They’re, yeah. They’re gentrifying. You know, Salesforce has pivoted to this headless model, um, along with Asian Force and using sort of Slack as the operating system. [00:13:34] Matt Y: And, you know, you said like a lot of companies from the seventies aren’t around anymore. They’re gonna be winners and losers. Yeah. Um, but the winners are gonna win even more. And so I, I think what’s so important right now for partners is to not, not bite too hard at the, the latest trend. You know, models are changing and everyone’s like, oh, you know, philanthropics really in the world and they’re wonderful, great to work with, amazing technology. [00:13:55] Matt Y: That’s what people are saying about open AI six months ago. That’s right. And before that, you know, and it, I, I was with Fireworks AI yesterday, a great company and they have some really cool stuff with sort of, um, they believe in more cost effective, uh, open source models essentially, that you can find tune. [00:14:08] Matt Y: Maybe that’s gonna win. I don’t know. Um, is it gonna be sort of domain specific models? Is it gonna be highly capable LLMs? Are LLMs gonna level off as soon as Fable and Mythos are allowed to launch? Maybe. I, I don’t think anyone can predict the future right now. So you have to be agile and you have to kind of seize the opportunities and take a couple punches. [00:14:25] Vince Menzione: Yeah. [00:14:26] Matt Y: You know, and marketplace too, like we’re, you have to be unafraid to experiment right now. Um, you know, that’s hard if your stock’s taking a beating. Um, but this is, it’s a, it is a disruptive time, uh, but it’s creating actually enormous opportunities for growth for partners and, and we really see that, you know, in marketplace specifically within AWS. [00:14:45] Vince Menzione: It, it, it does still feel like the deer in the headlights moment. Right. Would you agree? Like you’re probably taking a lot of meetings and, and calls from ISVs specifically? [00:14:54] Matt Y: Well, [00:14:54] Vince Menzione: that are still trying to figure it out. [00:14:56] Matt Y: Yeah. But it’s everyone. Yeah. I think what’s really interesting, I had a meeting [00:14:58] Vince Menzione: with, it’s not just one. [00:14:59] Matt Y: Yeah. I, well, I had a meeting with one of the leading AI companies, like one of the biggest ones. And they, uh, they demonstrated how they work and they were really proud. They were like, you know, look at our agentic workflow. And I came out at me. I’m like, that’s it. Ours is way better. Like really like, you know, ’cause we we’re, we’re using quick desktop with MCP servers and connectors and all this, and you know, we, we have our own sort of ecosystem of partners, a mix of homegrown software and third party. [00:15:20] Matt Y: And I kinda walked out there and, and looked at, you know, my phone, which has been populated by agents this morning with all the, and I was like, I have a way better agent workflow than this world’s leading supposedly AI company. And I think, um, that really, so during, I, I would, during the headlights, you can call it deer in the headlights, I call it chaos. [00:15:36] Matt Y: And in times of chaos there are people who create. Opportunity again. And so, yeah, there are some people who are stuck and who don’t know what to do, who are over worried about token costs, um, who are not experimenting. But there are a lot of companies, uh, taking this opportunity to kind of pivot their business. [00:15:53] Matt Y: Um, I think, I think we’re in a moment and, uh, yeah, I, I candidly I see more of the latter. I see more experimenting. [00:15:59] Vince Menzione: You mentioned ServiceNow. Any other great examples of that? Organizations that really embraced it? [00:16:04] Matt Y: Uh, yeah. Well, you know, ServiceNow is part of this business applications category, as we call it, in marketplace. [00:16:09] Matt Y: That outside of AI, I think is the fastest growing category in marketplace, which is wild when you think about it. ’cause we’ve historically been an infrastructure partner marketplace with security and data and analytics and, you know, security with channel partners, et cetera. But Salesforce, ServiceNow, Workday, Adobe, you know, I could go on. [00:16:23] Matt Y: They, they are actually. You know, our fastest growing category and yeah, ServiceNow, obviously reinventing itself for ai, Salesforce, but Workday, you know, the workday’s done some, who knows if it’s gonna work, but they, they’re experimenting with essentially like a Databricks, uh, credit style model for like, units of work, uh, which I think is fascinating. [00:16:41] Matt Y: Like everyone’s talking about value-based, outcome-based pricing and meter. And, and you have companies that are ERP companies, you know, like traditional business applications, experimenting with effectively like a metered pay as you go, value based credit model. Again, like who knows if it’s gonna work. [00:16:54] Matt Y: But I think that’s really amazing to see and we need more ISVs experimenting. I, I was talking about trend ai and I know they’re, they’re, they’re one of the sponsors yesterday. You know, many of you know them as Trend Micro back in the day. They’ve successfully reinvented themselves. They built that companion app. [00:17:10] Matt Y: Um, you know, that I think we’re seeing. Just a ton of experimentation in the market across categories. Uh, I could go on and on about partners. Um, yeah, there, I I wouldn’t pick a winner right now. Yeah. [00:17:24] Vince Menzione: You, you, we’ve talked about ai. We’ve talked, talk more about the buying journey and how that’s changing, because again, it feels, it feels like that’s also [00:17:33] Matt Y: Yeah. [00:17:33] Matt Y: So, you know, one of, one of the core, uh, strategic objectives, or we’ll say like the philosophy marketplace is that. Um, financial incentives are important, you know, EDP or PPA drawdown, uh, credits. Like we need to act as an efficient and effective vehicle for allowing buyers to exercise their discounts for, and, and sort of partners to exercise their credits, et cetera. [00:17:55] Matt Y: That, that’s actually important. But what, what a lot of people over rotate on that, and we’re really, one of the things we say a lot inside at Amazon or at AWS marketplace is we want to continue to boost the intrinsic value of marketplace beyond the financial incentives. And well over a quarter of all private offers, private pricing, private, uh, custom terms, et cetera. [00:18:14] Matt Y: Um, begin with a self-service or PLG motion. And partners who don’t have a PLG or self-service motion are literally leaving money on the table. Like if you look at like a Databricks for example, and they did a good job integrating buy with a WS within their SaaS application. They have free trials, they have really strong pego and, and, uh, and PLG motion. [00:18:33] Matt Y: They’re making, I can’t share their numbers obviously, but they’re making a ton of money. On purely self-service motions. And importantly, they’re acquiring new business, new logos that they nurture, you know, really like not just leads but closed opportunities, right? That they lead, they’re growing, uh, at a reasonable conversion rate or or success rate into the next big logos. [00:18:50] Matt Y: And these are over multi-year horizons. They’re patient, you know, they bring in these new logos with PLG, and they’re also bringing banking, a lot of large enterprises. Through self-service. I, I was with data Mask. There’s this great little startup from New Zealand. They’re a New Zealand based company. Um, super nice guy. [00:19:06] Matt Y: And, and, uh, they, they got huge logos. I think they got, what was it? A DP and some huge American logos. Okay. And this like logo in, I think it was Chile, or no, it was Peru. They’ve never been to Peru. They don’t have sales in Peru. Um, and they. Buyers were discovering them self-service and they, they, I think they got something like 13 logos entirely through a self-service motion. [00:19:26] Matt Y: One password will tell you the same thing. I was just with them in Toronto and companies big and small startups and the largest are getting enterprise wins in addition to net new small logos through that PLG. Buyer motion. And that’s because you have a whole generation of CFOs, CTOs, CROs, whatever. The C is [00:19:43] Vince Menzione: millennial [00:19:43] Matt Y: who grew up on their phones. [00:19:45] Vince Menzione: Yeah. [00:19:45] Matt Y: And, and it sounds like, you know, hyperbole, but it’s true. They, they want immediate apps, immediate access. And that actually, you’re like, oh, that never translates to business applications. Turns out it does. It does. And they might not be buying on their phone, but what they are doing is researching and we see the numbers, the amount of customers who are doing their research, and then eventually landing on the page from chat, GPT. [00:20:06] Matt Y: From major financial, like Fortune 500 companies is extremely high. Yeah. Uh, you have procurement team, sourcing team, uh, developers who are starting the research increasingly, like in clawed in chat, GPT, and then, you know, building a proposal and then handing it to their enterprise procurement team. Yeah. [00:20:22] Matt Y: Which is still largely unchanged. So buyer behavior is on the front end, on the research side is really changing. So the [00:20:29] Vince Menzione: discovery is happening through PLG. [00:20:32] Matt Y: Yeah. [00:20:32] Vince Menzione: And then the backend work on private offers and things like that sometimes still happens the old way. [00:20:36] Matt Y: Yeah. Well, and so, you know, it’s [00:20:37] Vince Menzione: fax machine, [00:20:38] Matt Y: some people Yeah, sure. [00:20:39] Matt Y: They’re bringing the deal directly to Marketplace last minute. But even if that deal goes direct, sometimes they’re still beginning their research journey and increasingly using Marketplace as a research vehicle, which is why we launched Agent Mode, um, to help you sort of help you and agents do research. [00:20:51] Matt Y: But that I think if, if I have one piece of device for any partner consulting or ISV is. Don’t leave those leads and that money on the table by not having a PLG self-service strategy like you’re fooling yourself. Uh, and it’s, it’s a huge, it’s a huge, huge business for us. The, the majority of all customers by far on marketplace don’t even have a PPA, uh, and a huge percentage of even those with PPA spend beyond the p. [00:21:17] Matt Y: And so if you’re just think if you’re just using marketplaces as like BPA retirement, you are literally losing money. [00:21:22] Vince Menzione: Yeah. [00:21:22] Matt Y: Yeah. [00:21:23] Vince Menzione: We have a session with Vinod. We’re gonna talk a little bit about that right after. Great. So good. Um, so I, yeah, I think, um. We talked about, we talked about agents, we’ve talked about the millennial buyer, the change in buying behavior. [00:21:40] Vince Menzione: What other, what other areas of aspect I, I, I, I do wanna think about like opening it up though for a second. I think that maybe with maybe nine minutes left. Sure. I just want to get a read from the people in the room. People have questions for Matt that we weren’t able to ask them. Yeah, I think, I think we probably have a few of those. [00:21:57] Vince Menzione: I think that would probably be great. [00:21:58] Matt Y: I can sense the hardball coming. [00:22:00] Vince Menzione: You’ve known each other [00:22:00] Matt Y: a long time. [00:22:01] Vince Menzione: Yeah. No, no. Hardball. We have a mic back here. Okay. I’ll just, we’ll, we’ll, we’ll get you a mic as we are recording. So good. Thank you. [00:22:11] Audience Guest: Uh, Boris Geller with a, a Click PLG is near and dear to my heart. [00:22:17] Audience Guest: We’ve been doing a lot of business in marketplace and I’m still struggling to sell my vision internally on, on, uh, on PLG. Uh, I think. Ag Agent AI is gonna be one of the drivers, and we are already on, uh, agent Marketplace, but I would appreciate guidance on, uh, best practices. How do we kind of, uh, operationalize it? [00:22:41] Audience Guest: It’s, it’s on us, not on you. [00:22:43] Matt Y: Well, no, I think it’s on both of us. You know, we, uh. One thing that we’re trying to do is give you more data to, to sell to your internal stakeholders in your executive suite. The value of co-sell with AWS all up, like finally with what we launched at, uh, the summit yesterday, you now get an opportunity score. [00:23:02] Matt Y: You, you get a number. People have been asking for this for years, so, so you can say when we do this and we, when we give AWS this information. The score goes up and we have a higher propensity to be cos sold by humans or agents before you had to kind of, it was like this mystery you had to guess. And similarly with marketplace, um, we, we have new dashboards that you can use to sort of, you used to have to sit down with us and go through spreadsheets to trace sort of lead to trace the funnel to sort of a close opportunity. [00:23:28] Matt Y: And we’re gonna continue to launch more there. But you now have more data that you can show. You can be like, listen, these are our inbound leads, this how’s converting, and now we have PRM, the partner revenue measurement where we can say like, this is what it’s translating into in terms of. AWS service revenue driven by our product. [00:23:41] Matt Y: And so that being able to tie from that inbound lead from your demand gen campaign through to a converted opportunity to what you actually drive from an AWS impact perspective, so you can, and then what your opportunity score is that data you can use to sell. Not only internally, but to us as well. Yeah, to a skeptical sales team or whatever who’s not maybe, you know, hype on partners in the, in the US West. [00:24:03] Matt Y: You can be like, listen, I don’t care what you think about my business. This is what I’m gonna drive for you with your quarter retirement from an AWS perspective, and this is how the shape of your customer accounts are gonna change. And this is why you should pay attention to my opportunities. ’cause my opportunity score is, is crazy high and I’m giving you insights into business that AWS would not otherwise have. [00:24:19] Vince Menzione: That’s your brand story we’re talking about. [00:24:21] Matt Y: Yeah. [00:24:22] Vince Menzione: Building your story up with within [00:24:25] Matt Y: So it’s, it’s about the data, I guess. And, and you should, you know, you should all actually be [00:24:28] Vince Menzione: Yeah. [00:24:29] Matt Y: Asking me for more data, so, you know, and tell me like, what do you need to sell to your internal stakeholders? ’cause if I can draw a clear line. [00:24:35] Matt Y: From your demand chain campaign that lands on a marketplace, which I know is a conversion machine, it has way better than industry levels of, of conversion rates. And then you can show, hey, if we have a PLG strategy and we land those leads on marketplace, we will convert them with high efficiency, low cost of sales and, and, and have sort of a bifurcated where we can close some through self service, some through express private offers and some through private offers, depending on deal size. [00:24:57] Matt Y: Like you tell A CFO that, and they’re my number one customer now and they love it ’cause they see cost of sales going down, cost of operations going down and business going up. Um, so I think we have more data than we used to use that data. And let me know what other data do you need to make that pitch and make that pitch to the CFO go around the head of sales, all those other people. [00:25:15] Matt Y: Honestly, the CFO is where we get the best leverage. [00:25:18] Vince Menzione: Awesome. Great question. [00:25:23] Matt Y: Gonna bring your mic. [00:25:23] Vince Menzione: We’re, we’re gonna get your mic here. There you go. Oh, [00:25:25] Audience Guest: thank you. So my name’s Jody Cheval and I’m a consultant now, but I was at Workday during when they adopted AWS and it, a sales organization needs propensity to buy data. [00:25:34] Audience Guest: To really drive the sales team to realize the opportunity kind of makes them visualize it. We didn’t struggle, but it was challenging to get that data because at that time we’re getting spreadsheets. So does AWS have a vision of making that API based data that our client, my clients, can get at and bring into a tool to start building account hypothesis based on that data? [00:25:57] Audience Guest: ’cause it really is important to an enterprise sales guy to have the sense that OAWS can help me close this deal. [00:26:03] Matt Y: Yeah. I mean. Part of that. So we, we launched, we’ve been launching part of that in stages and we’re not done. There’s, there’s more coming. Um, part of that is embedded really within the new, uh, partner agent workflows. [00:26:13] Matt Y: We are giving sort of more, uh, information back to you, not just about like what funding programs you’re eligible for, but like, you know, and when, when we will co-sell this deal with you, which is effectively a signal like we, we see this as a high value opportunity, that you have a likelihood of winning internally. [00:26:28] Matt Y: We, we have this solution matching engine that we’re using and we announced. That, that that ties you the partner to a customer specific opportunity that you have a high propensity or the partner has a high propensity to assist with and ultimately win. And now we’ve tied that to our express private offers, which we announced this week. [00:26:44] Matt Y: So it’s an indirect answer to what you’re asking, but a rep can essentially say. Send a private priced offer to the customer on behalf of the partner without having to ring up the partner because they have a high propensity to win this deal with the customer. So we’re progressively launching features like that. [00:26:59] Matt Y: In addition to the propensity to buy data that we do now share. It used to be kind of, again, manual magic depending on who you knew we could share. Now we do share that programmatically, and there’s more to come specifically in that space. Uh, I’d say watch that space. In the next few months, there’s gonna be more data coming away, but we do have the APIs, we have the agent. [00:27:16] Matt Y: We have things like express private office solution matching, and we have been sort of in that space progressively launching features over the last six to 12 months. And, and you should expect to see some more there soon, not just from us or from our partners. [00:27:27] Vince Menzione: Nice. Any announcement dates? [00:27:30] Matt Y: I can’t commit to a date or else my engineers will get mad at me. [00:27:33] Vince Menzione: It looks like we Another question number. Is the mic still back there? Okay. There’s a gentleman over here [00:27:40] Audience Guest: first Go leaves. Um, it’s awesome. I’m right next to. I was right next. [00:27:46] Vince Menzione: We’ve got a lot of great plants here, so, [00:27:49] Audience Guest: um, so this may be a little bit myopic or, or a challenge that we run into, but I love a lot of the innovation that’s looking forward and all the future things that we’re doing. [00:28:00] Audience Guest: One of the things that we’re struggling with is a little bit of almost like tech or structural debt. How do you think about bringing flexibility to the core pieces that underpin all of the innovation, which is. We are self-hosted. So one of our listings is an a MI. You can’t amend an a MI, you have to cancel and start over. [00:28:18] Audience Guest: So a lot of the building blocks, when you think about PLG, if somebody wants to add to that in an a MI listing, it’s, it’s sort of broken. So how are you thinking about taking all of the, the rapidly changing buyer behavior and then looking back at the structural foundation that underpins all of those things, like offers and, and amendments and changes and all of that? [00:28:39] Matt Y: Yeah. I, I promise I didn’t seed that question, but that, that’s a great one. Um, so not to get too in the weeds, but fundamentally, marketplace was built up, um, a bit like AWS like a set, a series of services somewhat independently. And each product type was effectively its own service, SaaS, server images, ais. [00:28:59] Matt Y: Um, what we’ve done recently is now we, we have, we got rid of product types basically on the backend. You, you don’t see it, but what that means, for example, like another thing AAMIs don’t support today, future data agreements. Um, or concurrent agreements, uh, they will all be supported by amis before the end of the year. [00:29:14] Matt Y: ’cause what we’re doing, this fundamental thing that you won’t even see called product offer decoupling. Uh, and it’s a fundamental piece of things that we need to unwind. ’cause we built up, we were moving very quickly over the years. We had a distributed engineering model and we built each product type independently. [00:29:28] Matt Y: And so yeah, if you’re a seller and you’re selling containers, agents, SaaS, amies, um, we’re breaking down the silos between those so that each of them will get the same benefits. And, and by the way, we’re taking the same approach to international. Hopefully you’ve noticed now that. It’s not like a feature launches in the US only and then takes five years to launch in either public sector or another country. [00:29:48] Matt Y: We, we’ve taken a global approach to feature launch and increasingly a product type neutral approach to feature launches. Uh, that’ll be largely resolved before the year’s out. We’re working on it right now. So again, it’s, it should be transparent to you, like you shouldn’t actually see any difference in the, in the experience. [00:30:05] Matt Y: Except that all of those features will be available. So, so that is, uh, actively under work. And that’s actually something if you’d like to try, um, you’re, you’re welcome to. So, yeah, [00:30:17] Vince Menzione: we have time for maybe one more question and we we’re actually gonna have you up here with a couple partners. [00:30:24] Matt Y: Sounds [00:30:24] Vince Menzione: good. Kind of fun. [00:30:32] Audience Guest: Hey, Matt, uh, met Natasha from Dondo. Uh, quick. So great announcements. And you know, you talked about the million, multi-billion dollar, uh, club, and, uh, that’s all great. Uh, in terms of the. Propensity data. I think that’s coming at the center of a lot of things, right? You know, for enterprises, oh, there’s an investment and you tap into that investment. [00:30:53] Audience Guest: But also there’s the other side of the procurement where a lot of customers, sometimes we work with, they’re like, they still wanna go direct for whatever reason, right? So I think there’s an education piece there, but also trying to understand like how we can work together to, you know, get some of that side of the things sorted out as well. [00:31:11] Audience Guest: You know? ’cause a lot of times it’s not about. Just, you know, retiring the, uh, the, the spend comets, but also like, Hey, I’m used, I’m already used that for something else. So maybe that’s not an, uh, something that applies here. And in also in tying that the PLG motion, uh, you know, for the customers you said, you talked about, you know, if there is. [00:31:34] Audience Guest: Leads on the TA table, like where the, it’s not the enterprise, but you know, the others. Um, I feel like it’s more to do, changing the business model at some times. Like with the enterprises, you have the revenue stream coming through, say large deals, right? And all of a sudden you tap into this, you know, PayGo. [00:31:51] Audience Guest: Where it flips the whole equation with, you know, the financing and the, and the, and the revenue measurement. So I think there’s two aspects of how do you kind of cons reconcile those things in terms of, you know, the revenue measurements going forward. [00:32:05] Matt Y: Yeah. So, so two things real quick on the procurement. [00:32:07] Matt Y: Um, yeah, like, yeah, I sort of alluded to this earlier, but, uh. Procurement is a bit late to the AI ag agentic transformation. They’re trying, and there’s a lot of great new incumbents in this space. And the big leaders like, you know, Coupa and Ariba and Oracle are, are, are evolving their products, albeit a bit slowly. [00:32:26] Matt Y: Um, but the, I think, uh, it’s still the long pole in the tent. You know this. And so like, there are two reasons why deals tend to go direct, because it kind of hits a wall of. Legal, uh, you know, procurement, governance, like all that kind of after the selection’s been made, et cetera, or, or they’re, you know, we can’t change. [00:32:44] Matt Y: People are gonna optimize for, for finance, you know, they’re, they’re going to, if they’re getting big discounts. I mean, that is life. I always say it’s like sellers at the most agented company are still gonna chase quota no matter how, you know, crazy. Uh, your, your company is, and it’s the same with, um, with the chief, uh, financial officer and chief procurement officer. [00:33:01] Matt Y: They are going to, they’re literally. Paid to find discounts. And so we’re not, we’re not gonna get rid of financial engineering. That’s a, that’s a thing. What we can do is reduce the friction for procurement. So we launched, for example, like mandatory purchase orders. That was a big thing. We, we have buyer notifications, now we’re making other procure to pay enhancements. [00:33:17] Matt Y: I mean, procurement systems still use like CXML. It’s like, that was, that was cool when I worked for the ap. And like I, I have teenagers that are old, like older than, so they, I, I think, um. Procurement needs to evolve and we’re gonna help it evolve. We’re gonna push it forward and, and we need to make it more seamless for procurement teams so that we remove those objections. [00:33:38] Matt Y: Uh, I can’t remove the financial engineering objection, like, you know, that’s just life. Um, but I can make it irresponsible not to use marketplace ’cause it’s so easy to use. And, uh, that, that’s kind of the approach we’re taking on, on the front end. Uh, you, you know, I think you, you, again, I didn’t see this question. [00:33:52] Matt Y: You, you stepped into a trap. Un unwittingly, um, PLG is not just is for enterprise. And, and PLG doesn’t necessarily mean pego or self-service. Uh, doesn’t necessarily like, uh, most of our self-service efforts are actually focused on private offers. And not necessarily for pego. Uh, when, when I say self-service and, and PLG, uh, it, it can mean all kinds of things like it. [00:34:14] Matt Y: We have requested private offer, requested demo call to actions, buttons that you can put on your listing. For example, you don’t necessarily need a free trial or a metered pay as you go listing to take advantage of those inbound self-service leads. So, and those inbound self-service leads are often massive enterprise deals, like I mentioned specifically, uh, the data mask. [00:34:31] Matt Y: Those giant enterprise deals that they launched came from an enterprise like Fortune 1000 Enterprise in the US that organically discovered their solution on the marketplace using our AI search. And that was a massive enterprise. And so I, I think yes, there is the long tail, you wanna capture a new logo acquisition, but you should think of your product like growth in your self-service strategy as a way to, um, acquire all kinds of leads, including large enterprise. [00:34:54] Matt Y: And so when I say leave money on the table, I’m not just talking about things that are gonna mature over two years or tiny little deals. These could be massive deals. Uh, and, and you’ll accelerate those deals by accelerating their discovery and, and research so that I think that, so, and my advice is don’t, you don’t have to go all in if you don’t have, if you don’t have metering, if you don’t have PayGo, that’s cool. [00:35:13] Matt Y: Start with something simple. Start with a public listing, with a request to private offer like that. That is a, a huge step. That doesn’t take much, and, and it kind of blows my mind still that a lot of companies aren’t doing that yet. [00:35:25] Vince Menzione: Great answer. Well, it’s now time we’re gonna bring, we’re gonna bring, it’s time. [00:35:29] Vince Menzione: We, we’ve got some great partners coming up here, Nvidia Elastic, Accenture gonna all join us for a conversation. Great. And I’m glad that you’re gonna stay with us. And let’s, let’s, well, let’s thank Matt, by the way, for that session. [00:35:41] Matt Y: Thanks. [00:35:42] Vince Menzione: And [00:35:42] Matt Y: thanks for listening to the Ultimate [00:35:44] Vince Menzione: Partner Podcast. If today’s conversation resonated, share it with a partner leader in your network. [00:35:51] Vince Menzione: Subscribe where you listen. And head over to the ultimate partner.com. For show notes related content and the resources for this episode. And if you haven’t already, now’s the time to register for the Ultimate Partner Live Event in Reston, Virginia, October 26th through October 28th. Until next time, keep showing up in the rooms that matter because being in the room changes everything.

We've been running a bit of an Agent Cloud series surveying all the top inference/compute/cloud providers, from Databricks to Daytona to Railway and, even further back, E2B, but we're excited to conclude this series returning to Modal, which has just raised a monster $355M Series C.The cloud was built for developers. But agents are now changing that.The old infra stack was designed for a human who could read docs, reason through YAML, and understand dashboards to figure out what they need when something broke. While this was painful for developers, it worked since they could fill in missing context in their heads.However, agents don't have that luxury. Now in this new era of agents, everything has to be tighter.They need a place to write code, run it, inspect the output, change the environment, debug failures, and try again. Fast iteration and feedback loops with all the necessary context are crucial for agents to operate properly. Furthermore, sandboxes are a clear representation of this shift as agents can easily spin up isolated environments. This programmatic infra even extends to research:Two years ago, we were one of the first to cover Modal with CEO Erik Bernhardsson and Alessio designed our favorite LS thumbnail of all time:At the time, Modal was just a teeny little company with a $17M Series A.Today, fresh off their $355M Series C, Modal is one of the clearest examples of the agent cloud future being built in real time: a cloud platform moving past traditional web app assumptions toward the workloads AI actually creates such as elastic inference, sandboxes, GPU burst, post-training, background agents, and infrastructure that agents themselves can operate.In this episode, Modal CTO Akshat Bubna joins swyx and Vibhu to unpack why AI applications don't fit traditional cloud assumptions, why Kubernetes was never designed for bursty compute-heavy workloads, and why Modal is now shifting from developer experience to agent experience.We go deep on Modal's AI infra stack: serverless functions, decorator-based infrastructure, elastic inference for custom models, GPU snapshotting, DeFlash, speculative decoding, Auto Endpoints, sandboxes, persistent storage, networked containers, private IPv6, RDMA, multi-node training, and Modal's capacity pool across 17 cloud providers. Akshat also explains why RL rollouts can require 100,000 sandboxes, why production agents need hard guardrails, why observability may matter more than reading code, and why AI has made infrastructure exciting again.We discuss:* Why Kubernetes wasn't built for bursty AI workloads* How Modal started as a better runtime before becoming an AI cloud* Why Modal added GPUs before ChatGPT* The shift from developer experience to agent experience* Why observability matters when agents are writing the code* Elastic inference for custom models across audio, video, robotics, and comp bio* GPU snapshotting, cold starts, and why inference workloads are so bursty* Why RL rollouts can require 100,000 sandboxes* DeFlash, speculative decoding, and frontier-level inference performance* Auto Endpoints and making optimized inference easier to deploy* What Modal adds beyond vLLM, SGLang, and raw GPU rental* Modal's 17-cloud capacity pool and supercloud strategy* Networked sandboxes, sidecars, private IPv6, and RDMA* Serverless multi-node training for post-training and research workloads* Auto-research, model-guided sweeps, and agents launching GPU experiments* Compute strategy, capacity planning, and batch tiers* Why production agents need specialized sandboxes and hard guardrails* Modal's take on managed agents, CI, Gitpod/Ona, Python, TypeScript, and Modal BenchAkshat Bubna* LinkedIn: https://www.linkedin.com/in/akshat-bubna-188885103* X: https://x.com/akshat_bModal* Website: https://modal.comTimestamps00:00:00 Introduction00:00:39 Modal's origin and why Kubernetes wasn't enough00:04:32 Developer Experience → Agent Experience00:06:21 Modal's AI cloud primitives00:09:14 Sandboxes, agent loops, and proto-Cognition00:12:12 Elastic inference, GPU snapshotting, and 100,000 sandboxes00:15:24 DeFlash, speculative decoding, and Auto Endpoints00:19:59 Production-grade inference beyond raw GPUs00:22:00 Background agents, Ramp Inspect, and the agent lifecycle00:24:08 Modal's 17-cloud supercloud strategy00:26:40 Networked sandboxes, private IPv6, and RDMA00:32:48 Multi-node training, post-training, and auto research00:37:36 Compute strategy, capacity planning, and batch tiers00:40:55 Open models, real-time AI, and production agent infra00:43:06 Hard guardrails, managed agents, and specialized sandboxes00:46:06 Why AI made infrastructure exciting again00:48:30 Model APIs, differentiated products, and agentic video00:51:50 CI, coding-agent infra, SDKs, and Modal Bench00:57:28 Closing ThoughtsTranscriptIntroduction: Modal, Series C, and the Art PartySwyx [00:00:00]: We're here with Akshat, CTO of Modal, together with Vibhu. Congrats on your Series C.Akshat [00:00:10]: Thank you.Swyx [00:00:11]: Your party yesterday was amazing.Akshat [00:00:15]: Yeah.Swyx [00:00:15]: From all the photos and all the swag.Akshat [00:00:17]: We had a bunch of art installations, which was fun, seeing, like, our products on pedestals next to, like, Rodin.Swyx [00:00:25]: Very nice. Very nice. When you started, it was not the GPU inference company. Maybe it was in your mind. Take us back to the origin story.Modal's Origin: A New Runtime Beyond KubernetesAkshat [00:00:39]: I first met Eric, who's the CEO, through an investor. Back then Eric was already thinking about building, a new runtime, and he got there thinking through why are workflow orchestration products so hard to use. It's because you have to run them on Kubernetes. Kubernetes is hard to manage. It's not built for burstiness and, custom images,Swyx [00:01:03]: YeahAkshat [00:01:03]: It has a terrible developer experience.Swyx [00:01:05]: And I'll, I'll interjectAkshat [00:01:06]: YeahSwyx [00:01:07]: For listeners, who are new, we interviewed Eric two years ago, and there's a bit more of the story there from Spotify and all those things.Swyx [00:01:14]: And I came across Eric through Data Council because he did that talk on the serverless container stack that you guys did, which was like, that was my first like, “Okay, I need to take Modal very seriously” moment.Akshat [00:01:26]: Yeah.Swyx [00:01:26]: But it was still very unclear, like, do I need all this for just my data pipelines?Akshat [00:01:33]: Yeah. initially what we were thinking about was if we build a better runtime, it's a very useful primitive in itself. It's There's a lot of things that, get solved by serverless functions, like you can do, ETL stuff, you can do job queues, you can do all this, like, bursty processing, which it turns out every company had needs for. but then we also were thinking about this as like, this is a primitive that we can build a whole collection of products on, which are very verticalized. So perhaps data engineering would've been the first one, but we were thinking about inference. Back then it was more classical inference, like computer vision stuff and running XGBoosts and whatnot. But we added GPUs to the product a year before ChatGPT came out.From Serverless Containers to GPU WorkloadsSwyx [00:02:19]: Nice.Akshat [00:02:19]: We just didn't think it would be that big of a deal.Swyx [00:02:22]: Yeah, just like add A100.Vibhu [00:02:23]: Was there any, like, early key problem that really sparked off why you built it?Akshat [00:02:28]: Yeah. Primarily it's just, none of the tooling that was out there was built for, one, a really great developer experience, and also there's a general trend of, a lot of the workloads that we were seeing were very. I wish there was a better word for it, but compute-heavy. Like, they need, one, like, need a lot more resources, so you need to burst up and down a lot, versus like Kubernetes designed for, like, slow scaling and, more for, like, web server use cases. And also there's just a lot more specialization in, like, what kinds of environments these workloads run in. Like, we had sometimes they need accelerators, sometimes they need different kinds of images, and this is just like a consistent thing that we saw across a lot of companies. That would be the next step.Software-Defined Infrastructure and Decorator-Based DXSwyx [00:03:13]: Yeah. Yeah. Be nice. I don't know how much this factored into the early story, but I wrote a post when I was at Temporal about infrastructure, software-defined infrastructure or something like that.Akshat [00:03:22]: Yeah, the self-provisioningSwyx [00:03:23]: Self-provisioning.Akshat [00:03:24]: Yeah.Swyx [00:03:24]: Yeah. I can't even remember my own post.Swyx [00:03:26]: And then you put me on the landing page.Akshat [00:03:28]: Yeah. We really like, the term and so we stole it.Swyx [00:03:32]: Because you had the insight that everything can just be in decorators co-located with the code, right?Akshat [00:03:37]: Yeah.Swyx [00:03:37]: Was that a big part of the originalAkshat [00:03:39]: YesSwyx [00:03:39]: Story or it was just like a DX layer?Akshat [00:03:41]: That was, really important because we really didn't want people to spend, so much time, writing YAML, and it seemed like you could really condense the surface area of what you're doing, put it in code so you can operate on it just like you operate on other code, and like build stuff that's more expressive and dynamic. and so yeah, that was always a very important part.Swyx [00:04:04]: Then the pushback is this is a DSL.Akshat [00:04:07]: Yeah.Swyx [00:04:07]: It's you're closed source. I am locked into Modal.Akshat [00:04:11]: Yeah. We never really got pushback for that because the nice thing about Modal is you can bring whatever code you have, and sure, the DSL is at the configuration layer for, what hardware you're using, how you're scaling things up, but you still own the code.Akshat [00:04:27]: And that's, that's been an important, part of our story, even as we do inference now.Swyx [00:04:32]: Yeah.Vibhu [00:04:32]: How much of do you think still stays the same today? Like if you were to build something today, DevX very important, but I feel like, a lot of this has been changed with just hook it up to an agent, have Claude Code, have Codex implement a tool. there's very agent native primitives that are different than if I'm doing this myself, right?Developer Experience → Agent ExperienceAkshat [00:04:54]: We've changed our SDK team to think about agent experience instead of, developer experience and we think that the same benefits that apply for DX also apply for AX, which is why would you have an agent read through hundreds of Kubernetes files and like write YAML that's not even typed when it can make a couple of changes in a decorator and it gets this self-provisioning runtime of, being able to see its changes live in action? yeah, it just seems from the customers we talk to, they find Modal is much faster for agents to use versus operating on a different substrate.Swyx [00:05:34]: Yeah, because like you, again, you co-locate the infrastructure requirements to the code that runs it.Akshat [00:05:38]: Yeah.Swyx [00:05:38]: Well, the negative thesis now is that nobody's looking at their code anymore, so there's no point.Akshat [00:05:44]: Yeah, people aren't looking at code. one thing we still see is really important is observability.Swyx [00:05:51]: Yeah.Akshat [00:05:51]: Like how good is your dashboard? And of course, like we have, we push a lot of it to the CLI so the agents can do their own investigation, but you still need humans to go interpret what's going on and, make judgment calls and whatnot. and that's I feel like, Maybe more important now than looking at the code itself.Swyx [00:06:11]: Yes, because like, you can try to treat the code as a black box and then use, see the observable action that comes out of it, and then just prompt a change.What Modal Is For: AI Cloud PrimitivesAkshat [00:06:21]: Yeah.Swyx [00:06:22]: So I think it takes a bit of restraint to not specialize, to say, “I want to ship a new primitive,” and then just be general purpose.Swyx [00:06:31]: People ask you, “What are you for?” You're like, “ I don't know. We can do this, we can do that.”Vibhu [00:06:36]: Well, I'd be curious to see, like, okay, if we were to ask you, like, what is Modal for even at a high level? There's a lot you guys do, sandboxes, GPUs, everything. How do you answer?Akshat [00:06:46]: Modal is a cloud platform that's built for, where we've built the primitives from scratch for AI applications. and right now it covers, inference, training, batch processing, and sandbox workloads.Akshat [00:07:00]: But we're building a lot moreSwyx [00:07:02]: I noticed you didn't say web server, so there is still a role for, like, the always-on large-scale Kubernetes type things.Akshat [00:07:09]: Yeah, absolutely. We're, we're not trying to compete with the renders of the world, because yeah, we think the differentiator for us is the, are the workloads that need specialized compute, need to scale up and down a lot. yeah, they're, they're, they're just shaped differently.Working Alongside Frontier StartupsVibhu [00:07:26]: I think you're building a lot of it alongside the startups, right? They're innovating quite a bit, even in your, like, latest blog post. Like, even in the series C, the customers that you mention here, the cognitions, technical ones, ramps and whatnot, they're, they're innovating with you, right? And that's not something AWS is doing directly with.Akshat [00:07:45]: Yeah, absolutely. I think, this is again classic. We're a small team. We can move really fast. our engineers are working with our customers and figuring it out. Yeah.Swyx [00:07:54]: So my first week at Cognition, I walked in, there was someone wearing a Modal shirt. I was like, “What are you doing here?” They're like, “Yeah, I just. I am embedded inside of Cog.”Akshat [00:08:05]: Yeah, I think that was Peyton. We sent him overSwyx [00:08:07]: Yeah.Akshat [00:08:07]: Because, the latency of communication was too high otherwise.Swyx [00:08:12]: Yeah, distributed node, you have to - you have to place one and collocate.Vibhu [00:08:16]: Yeah.Swyx [00:08:16]: So I had a, I had direct personal experience, right? So I worked on smol developer three years ago. it was inspired by Claude 1. I think you onboarded me at some point, like, just before, and I was like, “Oh, like, I need some bursty compute. Like, I was just gonna try using Modal.” And it was a, it was a pretty pleasant experience. apparently, I showed up in the board meeting, like the analytics.smol developer, Sandboxes, and Proto-CognitionAkshat [00:08:39]: Yeah, you blew up on Hacker News and,Swyx [00:08:41]: YeahAkshat [00:08:41]: We got a big traffic spike. I. I think the way you used smol developer was Modal functions for running stuff, which was. Like, the, that was a good use case. but then, yeah.Swyx [00:08:53]: Yeah. That - So to me, that was proto-cognition.Akshat [00:08:55]: Right.Swyx [00:08:56]: If only I had, like, stuck to it.Swyx [00:08:58]: Like, that was like, if - did you say draw the tech treeAkshat [00:09:00]: AbsolutelySwyx [00:09:00]: You're just like, “Yeah, like, probably this will happen.”Akshat [00:09:02]: Yeah. Like, he was so close. You were just rebuilding upon usSwyx [00:09:04]: I just didn't realize.Akshat [00:09:05]: But the funny story there is at the same time, we were talking to a bunch of customers who needed something like sandboxing.Swyx [00:09:14]: Yeah.Akshat [00:09:14]: This is like twenty-three.Swyx [00:09:15]: Yeah.Akshat [00:09:16]: So we builtSwyx [00:09:17]: You introduced a new API right after that.Akshat [00:09:18]: Yeah.Swyx [00:09:19]: Yes.Akshat [00:09:19]: Like, we built sandboxes in May of twenty-three before anyone was even knew this was gonna be a thing. And the first example we published was, we took smol developerSwyx [00:09:28]: Smol developerAkshat [00:09:28]: And put it in a loop, so the agent can iterate on itself.Swyx [00:09:33]: Loops are hot these days.Vibhu [00:09:34]: It's the looper.Akshat [00:09:34]: Yeah.Vibhu [00:09:35]: Loops in. When was this, twenty-three?Akshat [00:09:38]: Yeah.Vibhu [00:09:39]: A small check.Akshat [00:09:39]: Yeah.Swyx [00:09:39]: It's like twenty-three. so the. the, those for listeners, like, the problem was the models are not built for any of this, right?Swyx [00:09:46]: Like, you're just trying to like. They're not post-training to understand, like, looping and, like, self-correction and tool calling was there, but, like, also not that great.Akshat [00:09:55]: Yeah.Akshat [00:09:55]: I don't remember if you used tool calling in this one, but yeah, the models would just diverge after like ten iterations and not produce anything meaningful.Swyx [00:10:03]: Yeah. But like, then. So okay, like now talking to myself three years ago, the answerVibhu [00:10:08]: Of course they will get betterSwyx [00:10:09]: Collect all the failures, build benchmark, and then collect all the, examples, build the RL environmentAkshat [00:10:15]: RightSwyx [00:10:15]: Sell it for like ten billion dollars to Meta.Swyx [00:10:17]: And then also train a model and then sell that for sixty billion dollars to Elon. And this isAkshat [00:10:23]: Yeah, of courseSwyx [00:10:23]: The funny machine. Like, it's like, it's about the hardware.Akshat [00:10:28]: It's hard to have that inherent conviction that the stuff will get that much better.Swyx [00:10:33]: In retrospect, it's so f*****g obvious.Akshat [00:10:36]: Fair enough.Swyx [00:10:37]: Like, what else were we doing back then? I don't know. anyway. Yeah. So this. That was the start of your sandboxing journey, right? I feel like it didn't blow up until, like, last year.Akshat [00:10:49]: Yeah.Swyx [00:10:50]: So there was like a couple years of quietness.Akshat [00:10:52]: Exactly, yeah. We wereVibhu [00:10:53]: I think very underrated product value. Like, my experience with Modal, Charles, before he had joined Modal, met this guy at a hackathon, and he really insisted we wanted to run some small model, not hosted anywhere, and he's like, “ there's this cool company, Modal. They'll like spin up a GPU sandbox, we can throw it on there. They'll take a Hugging Face link.” And like there's so much value just right there, right? Like instant hosting, spin it up, spin it down. It'll stay cold, but we run the demo a few days later, it'll come back up and like all this stuff in retrospect, like it's still what we needed like today.Akshat [00:11:27]: Yeah, it's still needed today. workload shapes have changed a lot as, we run stuff for people with really massive production scale and, there it's it's not about scaling from zero to one, but it's how do we scale really elastically, from like thousand to fifteen hundred GPUs very quickly in a given region. It's the same shape problem.Elastic Inference, GPU Autoscaling, and Custom ModelsVibhu [00:11:50]: Okay. So you look at, say, Cursor Composer, right?Akshat [00:11:53]: Yeah.Vibhu [00:11:53]: They had a. “We'll do RL on a model every couple hours.” you guys have a whole version of RL inference gym and whatnot.Vibhu [00:12:01]: When you look at workloads like that, you're doing train runs where you need to scale up, scale down every hour thousands of GPUs, right? That's the example for we do need it, right?Akshat [00:12:12]: Yeah. Well, so I'll, I'll take a step back and, maybe talk about like how people use Modal today. because our biggest use case is, elastic inference. And the thing we first found product market fit, with was inference for custom models. So we stayed away from the LLM space, and we were serving companies like Suno for audio, Runway for video, robotics, comp bio companies that train their own model elsewhere. But Modal is the best black box that for deployment, scaling to however many GPUs you need as your traffic pattern changes. And we saw all of them like have a very unpredict- predict- predictable, traffic pattern. it's like diurnal. It's Some days, like the company will do a launch and, they'll need like, way more. And it's not just one model that they deploy. They-- all these companies deploy, lots of different models in different regions, and so the autoscaling problem becomes even harder because then you have to scale within a certain region, and those cycles are offset. So different times you scale up in different regions.Akshat [00:13:20]: So that's like our sortVibhu [00:13:22]: And thatAkshat [00:13:22]: YeahVibhu [00:13:22]: That in and of itself is a huge category. There's a bunch of inference providers which, provide this fireworks, does this as a service together, whatnot, Base10. that's carved into its own niche for language models, at least right now.Akshat [00:13:36]: Yeah. the thing that we have specialized in is the autoscaling aspect.Vibhu [00:13:41]: Yeah.Akshat [00:13:41]: Because we found that it's not universally true that everyone else can autoscale, and we've gone deeper into it on the tech side by, we've incorporated GPU snapshotting into the product so we can take the GPU state, like your torch.compile model, snapshot it, and the next cold start is way faster. And so going back to your question, it's That's why you need a lot of burstiness for inference. But then people also do a lot of demand training, like for RL stuff, your rollouts are bursty, as you said. People also do a lot of batch jobs. So we'll see, a lot of companies, before they have a training run, they'll need thousands of GPUs to run encoding or something like that. And I think those things are much more bursty than. I agree that agents are not that bursty. sandboxes are, except when you're doing RL. RL is justRL, Batch Jobs, and 100,000 SandboxesVibhu [00:14:28]: Or commerceAkshat [00:14:28]: Insanely bursty.Vibhu [00:14:29]: Yeah.Akshat [00:14:30]: Yeah. Like when you're doing, rollouts, you sometimes need a hundred thousand sandboxes in your sandboxes.Vibhu [00:14:37]: Yeah. I'm curious if you've seen early sparks of continual learning. There are some people, like our friends, ngram, recently announced thisAkshat [00:14:45]: YeahVibhu [00:14:45]: They're, they're trying to do training. That also seems like a different workload, right? If you're doing training twenty-four/seven per se, there's a very weird dynamic of how you're using GPUs between people and whatnot, but seems like something you guys would work for.Akshat [00:15:00]: As you said, we're, we're fortunate to work with a number of, customers at the frontier and grab some of our customers. and they are taking the primitives we have, and trying to use them in very interesting ways, like continual learning. It's possible as the stuff gets better, some of that will be part of, our offering as well if, more people need it. but we're, we're just waiting to seeVibhu [00:15:23]: YeahAkshat [00:15:23]: How it shakes out.Vibhu [00:15:24]: Is there a primitive that you added after sandboxing that was the next step in the story?LLM Inference, DeFlash, and Speculative DecodingAkshat [00:15:32]: I guess we've been going much deeper into LLM inferenceVibhu [00:15:35]: YeahAkshat [00:15:35]: Because we realized that some of the advantages we have with like autoscaling, again, especially in different regions and whatnot, are, not present elsewhere. and the place where we had a gap was we weren't, working on the model layer itself. Like we were a black box. And, we realized that, we can get to frontier-level model performance, with, by having great people who work on this. And, we've been open sourcing a lot of our work, in terms of, Recently, we, shared our work on DeFlash, which is a block-based, speculator, and we've open sourced, all of it. So, you can - By using open source DeFlash, you can get the same performance as you would with one of the proprietary providers. And the next thing we're thinking about hereVibhu [00:16:23]: I thought this wasAkshat [00:16:24]: YeahVibhu [00:16:24]: An interesting blog post as well, right? Like, I think in here you make a claim that. Not a claim, just that how effective speculative deco-decoding really just get to.Akshat [00:16:33]: Yeah.Vibhu [00:16:33]: Anything you wanna point out from this around, what people should know?Akshat [00:16:39]: Yeah, absolutely. the high-level summary is, it would help to describe what speculative decoding is.Vibhu [00:16:44]: Yes.Akshat [00:16:44]: I will, yes.Vibhu [00:16:45]: I think, likeAkshat [00:16:46]: YeahVibhu [00:16:46]: So we've covered like Eagle and all thisAkshat [00:16:47]: YeahVibhu [00:16:47]: Like Hydra and all those things, but it was like two years ago.Akshat [00:16:51]: Yeah.Vibhu [00:16:51]: I think it doesn't hurt, right?Akshat [00:16:52]: Yeah. Speculative decoding is you have a smaller model, called a draft model, predict tokens ahead of the bigger model, and then you have the bigger model, verify all of this, all the tokens are predicted. And the reason it's faster is if you're predicting, one token at once, you're bound by memory bandwidth. But if you can batch the verification of, the draft model, then you're much more efficient using compute, and it's faster, and as long as your draft model is producing a lot of tokens that can get accepted, which is called the accept length, you can get a speed up that's, multiple times of, the original model speed. and well, that's what we highlight here. It's Like people talk a lot about we made these kernels faster and whatnot, but improving kernel will only give you like few percentage points of improvement, and, increasing accept length, literally is a multiplicative decreaseVibhu [00:17:47]: Like two to four X.Akshat [00:17:48]: Yeah, exactly.Vibhu [00:17:48]: Without much head-on performance.Akshat [00:17:50]: Yeah. I think it may - you are running a second model, right? So it may be something more expensive in the compute,Vibhu [00:17:57]: I meant quality performanceAkshat [00:17:58]: Probably not by muchVibhu [00:17:58]: But yeah. I thinkAkshat [00:17:59]: So there's no drop in quality performanceVibhu [00:18:01]: YeahAkshat [00:18:01]: Because you're always. You're never accepting a token that the big modelVibhu [00:18:04]: It's strictly betterAkshat [00:18:05]: YeahVibhu [00:18:05]: Or it's same.Akshat [00:18:06]: Exactly.Vibhu [00:18:07]: Right. Yeah.Akshat [00:18:08]: And so we've been working a bunch on DeFlash, which is a block-based speculator. so it's instead of predicting, one token at a time, it's predicting a block. And we've been open sourcing our work with it. The next thing for us here is for helping people train speculators and custom models. it's it's something that traditionally is very forward-deployed engineering driven, support deployed, engineer driven, like you work with customers and help them do that. And our vision for. This is why we launched Auto Endpoints, is we want to make frontier-level performance available to everyone. And so, we mentioned this in the announcement, we teased it. The next thing we're, we're launching is, as you run an auto endpoint, we shadow trafficAuto Endpoints and Frontier-Level PerformanceVibhu [00:18:54]: Do you want to explain what auto endpoints are?Akshat [00:18:57]: Yeah.Vibhu [00:18:57]: I lovely, yeah.Akshat [00:18:58]: Yeah. So, this is, I guess, going back to your Modal is you touch the code, but, sometimes people don't wanna touch the code, and they wanna get started with an endpoint that works and has all the great performance and, scalability that Modal has. So we've made that easier with, a way to create an endpoint from our UI, from the CLI, that has all of our optimizations that we talked about, like the DeFlash stuff already baked in, and there's full transparency. So we give you the code, you can go run it yourself, and if you want, you can eject out into the full Modal experience, which we see as people get sophisticated, they do wanna tweak the models, they wanna, fine-tune stuff. You can still do all of that. It's it's not a black box. And yeah, the next thing, as we teased later in the post, is how do we give you value even beyond this in terms of having your draft models evolve as your data distribution evolves, again, without having to talk to a person and, yeah.Vibhu [00:19:59]: I guess just to understand it directly, you have the GPUs, you have an endpoint that's compatible, you serve open model. If someone was to do this themselves, what's the delta that you guys provide? So you do a lot of open source great work on effective inference. how does it compare to, say, I take the same model, 5.2 FP8, take shelf inference engine, vLLM, SGLang, get compute of similar capacity, similar cost. What's the delta that plugging into something this, like this offers outside of the benefit of, scaling?Production Inference Beyond Raw GPUsAkshat [00:20:34]: It's interesting because we've taken the approach of open sourcing our contributions and upstreaming them. we work closely with the SGLang team. We want the improvements that our team, comes up with to be, there in open source for others to use, even outside of Modal. The benefit to us is we have a team that has significant expertise in terms of if you do have something that is not there, our team can help you get that performance, first. the other thing is with these endpoints, we are way more elastic, as you said, than, anyone else, and you have true scaling to zero. you have true, burstiness, and in practice, that matters a lot more to people than just finding, the GPU and, running Modal code on something.Vibhu [00:21:20]: Yeah. And I will say it's not that straightforward to just. like what I said is easier said than done, right?Akshat [00:21:26]: Yeah.Vibhu [00:21:27]: It's I think still for the average person, still hard to just gut check using different. There's, there's quite a bit of combinations you can make there. the trade-offs aren't really known at face value.Akshat [00:21:40]: Yeah. it's it's not just that. I think it's it's that running production-grade inference is a hard infer problem.Vibhu [00:21:49]: YeahAkshat [00:21:49]: Even if you subtract out the autoscalingVibhu [00:21:50]: YeahAkshat [00:21:51]: Is controlling things like tail latency and, making sure every, request is delivered at least once and whatnot.The Model and Agent LifecycleVibhu [00:22:00]: There's a lot of innovation that you can do here. I think, it's very interesting that you're starting to encroach on, like as you become a full cloud, you're starting to encroach on other people's turf.Vibhu [00:22:09]: What will you not do?Akshat [00:22:13]: Well, we wanna follow our users and, make sure they get like a platform that has everything that works well together. so right now we're focused on the model lifecycle and the agent, lifecycle. so both like going from data prep to training to inference, and then also if I want to deploy a background agent, let's say, sandbox, do persistent storage, a whole bunch of other stuff.Vibhu [00:22:38]: We talked to Cole, who did, OpenInspect. Yeah.Akshat [00:22:42]: Yeah.Vibhu [00:22:42]: And RealInspect also is on Modal.Akshat [00:22:44]: Yeah. So Ramp Inspect was a great example of a background agent that was really successful because they, were able to use some of the primitives like snapshotting and fast scaling to just have something that feels really reactive and works well.Ramp Inspect and Background AgentsVibhu [00:23:02]: Yeah. That's the new CTO of, Ramp right there.Akshat [00:23:05]: Yeah, Rahul.Vibhu [00:23:08]: It was really fun. yeah, okay, I think, all very bullish. Like, one of my reflections was also I did not originally. So when I met you guysThe Inference Inflection: CPU, GPU, and Co-LocationVibhu [00:23:19]: You weren't that much in the GPU game, and now you're all about, inference. And one of the points that I hinged on for Jensen's keynote at GTC this year was, what we're calling like the inference inflection, right? That let's say in AI workloads or machine learning workloads, it used to be like, let's call it eight to one GPU to CPU, and now it's more like one to one, which is like a interesting. Like, - because of how much agents are blocked or call out to this, to CPU heavy stuff the actual, like, limiting factor, like, swings back and forth from GPU to CPU a lot more than it used to be all GPU and then occasional CPU.Akshat [00:24:01]: Yeah.Vibhu [00:24:02]: GPU, CPU. And now it's like just constantly, and you just have to locate everything.Seventeen Clouds and the Supercloud StrategyAkshat [00:24:08]: Yeah. And that's one of the things that, again, we see as, something appealing about Modal, which is we've built this capacity pool that spans, 17 cloud providers, so we're, we're very good at Running on various kinds of cloud capacity across the worldSwyx [00:24:24]: You don't have your own data centers?Akshat [00:24:25]: We don't have our own data centers. We just run across a lot of neo cloudsSwyx [00:24:29]: Yeah. AreAkshat [00:24:30]: Metal providers.Swyx [00:24:30]: Yeah. Question mark.Swyx [00:24:31]: Yeah. You're, you're running the math, and you're like, “What's the cutover point where you're like.”Akshat [00:24:36]: Yeah, it's a good question. part of it is we see our differentiator in the software layer, and, being capital light and focusing on the software helps us move really fast. so far it's worked out well because there are so many other people building data centers that we're able to work effectively with them, and again, focus on what makes us, special.Swyx [00:24:55]: Yeah.Swyx [00:24:56]: 17 gets you into, like, the local providers sometimes. LikeAkshat [00:25:00]: The,Swyx [00:25:01]: Which was the most interesting one?Akshat [00:25:02]: There are a lot more neo clouds than you expect, and they all have various degrees of, various levels of reliability. And, that's why it's something we've invested a lot of time in, is building our own reliability layer on top. so if the GPU falls off the bus or something happens, we user workloads are not affected, and that lets us use a lot more capacity than,Swyx [00:25:30]: YeahAkshat [00:25:30]: You as a user would be able to.Swyx [00:25:32]: It's a useful thing to have because like now everyone knows, like, what layer you are and, like, you optimize for being the super cloud of all clouds.Akshat [00:25:41]: Yeah. That's, that's, that's the idea. and so I guess when you mentioned colocation, that's, that's another interesting thing where, one thing we've seen is people come to us when they want, very specifically located, CPUs or GPUs, like they wantSwyx [00:25:57]: Oh, they pin it in likeAkshat [00:25:58]: YeahSwyx [00:25:58]: EU?Akshat [00:25:59]: Exactly. Or EU, US.Swyx [00:26:01]: Right. Data resiliencyAkshat [00:26:02]: AustraliaSwyx [00:26:02]: Locality thing or performance or what?Akshat [00:26:04]: It's either data locality or latency, yeah.Swyx [00:26:07]: Yeah.Akshat [00:26:07]: Like, you want your. They're running sandboxes and model. They want them to be right next to aSwyx [00:26:10]: Yeah, it's easy thenAkshat [00:26:11]: YeahSwyx [00:26:12]: To. That is important in all those things. and so, like, you've accidentally, I don't know if it's accident, but, like, you've built the perfect primitive for agents to express themselves. And then, like, it's almost very funny how every extra development just involves more file system, just involves more CPU.Akshat [00:26:30]: Yeah.Swyx [00:26:31]: Just like the things that you already have. I don't know much about, if there's any, like, networking usages that are interesting, but you've also done some good work on networking.Networking, Sidecars, Private IPv6, and SandboxesAkshat [00:26:40]: Yeah, that's exactly right. Like, we're just taking compute storage and networking and building stuff on that layer, for, again, the stuff people need.Swyx [00:26:49]: YeahAkshat [00:26:50]: We see a few interesting networking things coming up. one is people want networked sandboxes. so we haveSwyx [00:26:57]: For like a Docker cluster type thing.Akshat [00:26:59]: Yeah.Swyx [00:26:59]: Sorry, Docker Swarm. Oh, f**k. What is it called?Akshat [00:27:02]: Compose.Swyx [00:27:03]: Compose type thing.Akshat [00:27:04]: Yeah. So if you want Docker Compose, our sandboxes now support, this thing called sidecars. So you can. A sandbox is a pod of containers, and you can run multiple containers in, a sandbox. also useful because, going back to networking, people want a lot of control over, outbound networking from a sandbox.Swyx [00:27:23]: Yeah.Akshat [00:27:23]: Like, they might wanna run a middle proxy for, like, maybe logging stuff for RL or, controlling how egress can happen to a domain, injecting credentials. and yeah. So we've, we've had to build a lot of that stuff ourselves.Swyx [00:27:38]: Yeah.Akshat [00:27:39]: But then also sometimes people want, sandboxes spanning multiple nodes to talk to each other, which is an emerging thing we're seeing. We have support for that for a different reason, and yeah, we'll see if that becomes stable.Swyx [00:27:52]: Like, just an open socket. It's a. This is directly like mTLS.Akshat [00:27:56]: We do support that, which is you can, expose a tunnel inside a sandbox.Swyx [00:28:01]: Yeah.Akshat [00:28:01]: And then you can either expose it to public internet or it can be, you can add like a HTTP, auth layer above it. But we have this thing called I6PN, which we haven't talked about, which is this, like, overlay network using IPv6 addresses. so if Modal containers, within the same workspace, when this is enabled, can address each other using this private IPv6 address, and no one else can.Akshat [00:28:28]: So it's like private networking, for containers. We built it because we needed it as a primitive for our distributed training product. so we have this other feature, which is you can add a decorator to a function, and you get a cluster of GPUs. and they have RDMA networking. so you can run a distributed training job, that's truly serverless. and we did the overlay network for that. But then we've seen that people are using it for other reasons, and, I'm intrigued to yeah, what would people do with it.Swyx [00:28:59]: Build primitives and let people figure it out, right?Akshat [00:29:01]: Yeah, exactly.Swyx [00:29:02]: You put out a pretty interestingAkshat [00:29:03]: They're like, they read the docs webpage. Let me use thatSwyx [00:29:06]: YeahAkshat [00:29:06]: Something they never intended to work. This is literally not even in our docs page. People somehow found it, and they're using it.RDMA, Memory Movement, and Distributed TrainingSwyx [00:29:12]: Huh.Swyx [00:29:14]: The way you portrayed it with, like, RDMA versus TCP, like, very well laid out, but just the transfer speed change at scale for RL, like yeah, you have it, you have it built in. I'm sure someone found it. It's found it to be a lot more efficient before you made a thing out of it, right?Akshat [00:29:32]: Yeah. And not to split hairs, I guess the overlay network is the TCP overlay network.Akshat [00:29:39]: The reason we have that is you need that to do the key exchange for RDMA before you set up the RDMA network on top of that. but then people found the TCP part.Swyx [00:29:48]: Can I tell you, this is like a big aha moment for me becauseAkshat [00:29:51]: YeahSwyx [00:29:51]: So I review 2,200 submissions for the World's Fair.Akshat [00:29:56]: Yeah.Swyx [00:29:57]: And then I got this from John OsterhoutAkshat [00:29:58]: HuhSwyx [00:29:59]: Who I don't know if. Do John Osterhout by name?Akshat [00:30:01]: The name sounds familiar.Swyx [00:30:02]: He published a. He's a well-known professor, published a lot of interesting software design books, and this is the talk he chose to submit, is on RDMA at Inference. And I'm like, you wouldn't think that this guy, who is like operating systems guy, would care about RDMA.Akshat [00:30:20]: I, it makes sense to me because I,Swyx [00:30:24]: This is the cloud, right? YeahAkshat [00:30:25]: Like, the way you move around your KV cache and how efficiently you can do it, how efficiently you move, your weights from your training GPUs to your inference GPUs in RL is there's a lot of degrees of freedom, and it is a systems problemSwyx [00:30:41]: YeahAkshat [00:30:41]: Moving memory aroundSwyx [00:30:42]: YeahAkshat [00:30:43]: Scheduling.Swyx [00:30:44]: This shows you how primitive my understanding of networking stuff is.Swyx [00:30:46]: Is this like the domain of WireGuard as well?Akshat [00:30:50]: Not quite.Swyx [00:30:51]: It's adjacent?Swyx [00:30:53]: Explain everything.Akshat [00:30:54]: Sure.Swyx [00:30:56]: How do we move memory around GPUs?Akshat [00:30:58]: Well, so sorry. Yeah, that is memory. Sorry, I was talking more, and maybe I was talking like five minutes back, about the private IPv6, addressing that you've set up.Swyx [00:31:09]: Yeah.Akshat [00:31:09]: Is it like it's a VPN?Swyx [00:31:10]: Yeah, it is like a VPN, and yeah, WireGuard is, yeah, you're right. It is,Akshat [00:31:16]: Right. Yeah, you already moved on to new topicsSwyx [00:31:17]: A similarAkshat [00:31:18]: OkaySwyx [00:31:19]: In the same space, WireGuard is, encrypted and this is,Akshat [00:31:23]: And you don't need encryption.Swyx [00:31:23]: Yeah.Akshat [00:31:24]: Yeah.Swyx [00:31:24]: This is not encrypted. that's the main difference. This is TCP and we have eBPF programs that will reject or allow the TCP connection based on whether you're allowed to do it.Akshat [00:31:35]: Used to involve a full sidecar, but now you have eBPF in the Linux kernel.Swyx [00:31:39]: Yeah.Akshat [00:31:40]: Yeah. I don't know if this is a natural follow-on to the topic of like my skepticism on distributed training is that while, like, people spend a lot of money on, like, cables to hook up GPUs, and even that is not, like, fast enough, and that's the bottleneck, is your networking fast enough?Swyx [00:31:59]: Yeah. So I guess you're talking about fully distributed training like, Dialog or something which is like cross data centerAkshat [00:32:06]: That would be, yes.Swyx [00:32:07]: That's the extreme.Akshat [00:32:08]: Yeah.Swyx [00:32:08]: You're in the middle, and then other people would have like the Mellanox cables up in, like, their actual data center.Akshat [00:32:14]: When you run multi-node training on Modal, RDMA, I think Mellanox, is, or InfiniBand is like a, is all seen as RDMA. but it's a way to bypass the TCP networking stack and, transfer, stuff much faster, between one node, to the other. And we have I think like 3 terabit per second, internal networkingSwyx [00:32:40]: OkayAkshat [00:32:40]: Which is the standard that's needed.Swyx [00:32:42]: Okay. So I misunderstood whatAkshat [00:32:43]: 50Swyx [00:32:43]: What part of the stack you wereAkshat [00:32:44]: 50 gigs overSwyx [00:32:45]: YeahAkshat [00:32:45]: If you wentSwyx [00:32:45]: YeahAkshat [00:32:46]: RDMA.Swyx [00:32:46]: Okay.Swyx [00:32:48]: Yeah. I, very impressive work.Multi-Node Training, Post-Training, and Auto ResearchSwyx [00:32:52]: So effectively you're extending like the model philosophy to the training cluster, like, yeah.Akshat [00:32:59]: Yeah. And we're, we're not going for like large scale training runs. the thing that we've built multi-node training for is, we see a lot of, smaller scale post-training. like, people are post-training like medium sized fund models, so they can, get higher quality on inference. this is a perfect fit, for something like that.Swyx [00:33:21]: Yeah. That is my impression of how a lot of these labs explore branches in post-training and then eventually merge whatever they find in.Akshat [00:33:31]: Yeah. The other use case we've seen for multi-node training is even if you have a big cluster, your researchers are still doing small runsSwyx [00:33:38]: YesAkshat [00:33:39]: Having elasticity thereSwyx [00:33:40]: Right, sureAkshat [00:33:40]: Matters a lot more.Swyx [00:33:41]: Yeah. the, like, this is like the current limiting factor for auto research, which is like you need to give your model some GPUs in order for it to completely run.Akshat [00:33:51]: We have a blog post on auto resource and model is,Swyx [00:33:55]: YeahAkshat [00:33:56]: Yeah, like, turns out to be pretty good substrate for that.Swyx [00:33:59]: So my impression is auto research means many things, likeAkshat [00:34:01]: YeahSwyx [00:34:01]: Anything that Andrej coins. Right now it's still science fair, right? Like not like, I don't know how many people are doing this.Akshat [00:34:08]: We're having a golf.Swyx [00:34:08]: Yeah.Akshat [00:34:09]: I thought the same thing.Swyx [00:34:11]: Yeah, you would know.Akshat [00:34:12]: We, like, our internal both training and inference teams use this the general shape of this quite a bit. like we have this one internal repo called auto inference, which essentially we've automated our own forward-deployed engineering efforts using, this harness, which is, the agent will just spin up a sweep of different things. It'll even run like, NVIDIA inside profiler and it'll like tweak configs and it'll arrive the right thing. it'll change your GPUs both from H200 to B200, and works really well.Swyx [00:34:47]: Nice.Akshat [00:34:47]: So yeah.Swyx [00:34:48]: By the way, I enjoy that your forward-deployed engineering is so technical that you have to do these things.Swyx [00:34:52]: It's very different from forward-deployed engineering from other people.Akshat [00:34:54]: Yeah. For our forward-deployed engineering team is, essentially they're like applied inference researchers or applied training researchers.Swyx [00:35:02]: Someone told me like they have to be able to build, but they also have to be able to sell. do they have to sell or are they like they're good, they're just like post-sale type of thing?Akshat [00:35:09]: It does, being able to talk to a customer and engage effectively with themSwyx [00:35:13]: YeahAkshat [00:35:13]: Matters a lot.Swyx [00:35:14]: They want the same thing.Akshat [00:35:15]: Yeah.Swyx [00:35:15]: ?Akshat [00:35:15]: But it's it's not really a sales, thing. We pair them with-- We have solution architects as well that are more on the sales side.Swyx [00:35:23]: Okay. Let's spend a bit more time on auto research. This is a big focus for for this year. Where does this go? like, have people explored enough? Like, there's all these beautiful charts of like improve and then level off a bit and then you find the next thing. Is this one abstraction up from normal training? Is that how we think about it, or do you think about it differently? Like model level training versus high, like driven hyperparameter search.Auto Inference and Modal BenchAkshat [00:35:51]: Yeah, like,Swyx [00:35:51]: Someone, some people call it like neural architecture search or whatever, right? Like.Akshat [00:35:54]: Yeah, - So the stuff I've seen people do with it is nowhere on the architecture level. It's pretty much tweaking parameters, but it's it's a hyperparameter sweep that's guided by some model intuition, so it's like much more efficient than, whatever other, sweep you would have.Swyx [00:36:12]: Yeah, it's just, it's just a question of where you want to spend your compute?Akshat [00:36:16]: Right.Swyx [00:36:16]: ‘Cause yeah, you can just throw infinite amounts of money on this and somehow you'll bang out Shakespeare?Akshat [00:36:22]: Yeah, infinite monkey.Swyx [00:36:24]: Yeah, so like the very good for model. and I think it's also very important that agents can spin up other agents, can spin up their infrastructure. Like very good for you. how good is our LLMs at generating model code? Like the benefit of existing LLMs is that you are in the data.Akshat [00:36:42]: Yeah. They're, they're surprisingly good. I think like pre Cloud 4 they were not, and then now they're able to shot, stuff out of the box. But we're playing around with releasing like a Modal Bench for like the harderSwyx [00:36:55]: YeahAkshat [00:36:55]: Things, that the LLMs cannot do yet and maybeSwyx [00:36:59]: What's an example of that?Akshat [00:37:01]: I think the things that- Sometimes agents struggle with, without right guidance and a skill is, how to, use the rest of our observability. Like how to. Something is failing, like how do you look at the logs and then update the right thing? It's reasoning about that. But they're able to shot, likeSwyx [00:37:23]: Yeah. You can just add a skill to it?Compute Strategy and Capacity PlanningAkshat [00:37:26]: Yeah. So we have a Modal skill now that. Which is why we built this Modal Bench. It's to find things like that, so we can address them in our tool.Swyx [00:37:35]: Tune a skill. Yeah.Akshat [00:37:36]: Yeah.Swyx [00:37:36]: No. it's it's good. are you facing any shortages? like we talk a lot about GPU shortages, but also CPU, also memory.Swyx [00:37:44]: Yeah.Akshat [00:37:45]: We have had a lot of growth, which means that, there's - we've had to be much better aboutSwyx [00:37:53]: PlanningAkshat [00:37:54]: Proactive capacity planning.Swyx [00:37:55]: Yeah.Akshat [00:37:55]: So we have,Swyx [00:37:57]: Which by the way, like it's like a MBA's like dreamAkshat [00:38:00]: YesSwyx [00:38:00]: Is like just planning this stuff. I think last time you and I talked about something maybe about this.Akshat [00:38:03]: Yeah. we have a really competent team of people that we call, The role is called compute strategy. so yeah, if anyone listening here or wants to work on thatSwyx [00:38:13]: Compute strategy?Akshat [00:38:13]: Yeah.Swyx [00:38:14]: I think,Akshat [00:38:14]: I feel like,Swyx [00:38:15]: I think the normies call it FP&A or something.Akshat [00:38:18]: Well, it's more It's it's not FP&A. It's it's There's a lot of interesting financial questions of like what is the blend between one year and three-year reservations? how do we forecast our own capacity? how do we. especially since our capacity is very fungible across different GPU types and different regions, like you have to model a lot of it. and you also have to have an opinion on how the supply chain is gonna evolve, and then you have to like, take bets,Swyx [00:38:49]: YeahAkshat [00:38:49]: Based on that.Swyx [00:38:50]: Tokenomics.Akshat [00:38:50]: Yeah.Swyx [00:38:51]: This is like probably a not a real point, but, I was trying to think about like what other industries. I was trying to think about like, we cannot be first to like these kinds of problems.Akshat [00:38:59]: Yeah.Swyx [00:39:00]: And what other industries have had this? And I was like, airlines with fuel and like they have to hedge their fuel and like, I think for a long time Southwest because they made like a hero fuel bet, they like were like super low cost becauseAkshat [00:39:12]: OhSwyx [00:39:12]: Compared to everyone else.Akshat [00:39:14]: Yeah. I hadn't thought about that.Vibhu [00:39:16]: We're at a fun time too?Akshat [00:39:18]: Yeah. It's. A lot of the compute business in general, for us is also about being very good about capacity management. That is how you have great unit, economics. but also over time it's how you can unlock more value for customers. Like, one of the things we're building now is like a way for customers to get, If they don't care about latency, like get much cheaper pricing and they'll get results back in like next 24 hours or something, like a batch tier essentially.Batch Tiers and Latency-Insensitive WorkloadsSwyx [00:39:47]: Yeah.Akshat [00:39:47]: And those are levers we have because we control the whole stack and scheduling and whatnot to give people a sufficientSwyx [00:39:53]: Yeah. I feel like they're not as popular. Like those, like the Frontier Labs have all those APIs. They're not as popular as they should be.Akshat [00:40:00]: The demand that we see for something like that is not for LLMs. although sometimes people wanna run evals andSwyx [00:40:08]: OkayAkshat [00:40:08]: Synthetic data prep and there it makes sense.Swyx [00:40:10]: Okay.Akshat [00:40:11]: But it's from a lot of LLM companies, like people who are doing computational bio, like they have to run really big batch jobs and they don't care about when they get it back.Swyx [00:40:22]: Yeah. And like they have a reasonable. It's it's also like a cousin to the stopping problem of like, will this finish in time?Akshat [00:40:30]: Yeah. You can bound it.Swyx [00:40:33]: Yeah.Akshat [00:40:33]: Like you can give peopleSwyx [00:40:34]: YeahAkshat [00:40:34]: SLAs on it.Swyx [00:40:35]: Yeah. I think what's, what's interesting is like the next phase of model.Swyx [00:40:38]: Like what, do people expect from you, now that you're established and you're like well-known compute player among all these leading companies. You had an inference launch week, and we talked a little bit about the launches. like what else? Like what else should people know?What Modal Builds NextAkshat [00:40:55]: We are building primitives that make our users' lives much easier. So, I think for example, with LLM inference, thousands more companies are gonna post-train their own models and, deploy open source models for inference. so we're thinking a lot about what is the best product shape for that. And, that involves everything from our training gym to, then, endpoints that get frontier-level performance. again, but I haven't talked to anyone. It looks somewhat different on other verticals. Like, we're also seeing a lot of real-time, audio-video stuff in there, which is why like, we're working on things like regional routing, with fallbacks. So you can get GPUs that are as close to users as possible. so you get like low latency for video streaming and whatnot. And then on the agent side, it's,Akshat [00:41:52]: We're still working very closely with our customers because stuff is changing so fast in terms of what they need. And, I think beyond sandboxes and persistent file systems, there's a lot of other things people will need from this agent stack as they build production agents. So yeah, we're thinking about those other things that fit in there.Swyx [00:42:13]: I want to ask what the other things are.Akshat [00:42:15]: Yeah. I probably should share right now.Swyx [00:42:17]: I think-- I think, okay, so, I do think a lot about the principal components of cloud, and you do talk about compute storage networking.Akshat [00:42:25]: Yeah.Swyx [00:42:25]: Because so far for me, it's fine. so far for the. the first couple generations of cloud, it's fine. What's different, qualitatively different about agents that you need some new permission level? Like a lot of people, okay, and I'll just kinda spew tokens at you until it like hopefully sparks something.Akshat [00:42:43]: Yeah.Swyx [00:42:44]: Like the new level now is whatever Claude Code does, which is dangerously scope permissions or like allow list by command or like whatever, right? And sometimes they're like, “Well, okay, we have like this adaptive thinking mode where like, just trust me, bro. I will make the calls for you.” Is that it? like mediated permissions.Hard Guardrails vs. LLM-Mediated PermissionsVibhu [00:43:03]: Now you're looping it with a goal and letting it roll.Akshat [00:43:06]: Yeah, I'm, I'm skeptical of LLM media permission for stuff that is at the sandbox level because you do want hard boundaries.Swyx [00:43:16]: Yeah.Akshat [00:43:16]: Otherwise, someone can exfiltrate stuff.Swyx [00:43:20]: But likeAkshat [00:43:20]: YeahSwyx [00:43:20]: Maybe that's old school thinking. Maybe we're the dinosaurs.Swyx [00:43:23]: Maybe the AI OS or the LLM OS is really the kernel is a goddamn LLM.Swyx [00:43:30]: Like it makes you feel uncomfortable.Akshat [00:43:31]: Yeah, I'm, I'm toldSwyx [00:43:32]: But that's what trusting the LLM is. Like imagine a spherical cow perfect LLM.Akshat [00:43:36]: Right.Swyx [00:43:37]: That it.Akshat [00:43:39]: Maybe.Swyx [00:43:41]: I wanna test the boundaries, right?Akshat [00:43:42]: Yeah.Swyx [00:43:42]: Like, and I don't believe that, but I wanna see where I'm wrong ‘cause that's, that's the consensus.Akshat [00:43:49]: Yeah. I think you always need hard guardrails when you want, And you can pair those with softer guardrails, right? And that's gonna be a lot of mediated.Managed Agents and Specialized SandboxesSwyx [00:44:00]: There. I'll also get you a end with a couple of your commentary on like the ecosystem outside of Modal. Manage agents. Everyone has one. Gemini, OpenAI, Claude, very useful for you, but also like it is their way of starting to edge into your space.Akshat [00:44:17]: Yeah.Swyx [00:44:17]: What's going on?Akshat [00:44:19]: Yeah, we're, very excited to partner with Anthropic and some of the other foundation labs, will not name who we're also working with. the way we see it is the manage agent thing is a great place to start if you're starting out building an agent and, But then when you get to, building something more production grade, like you're a company that's like Ramp that's building their own, Ramp also runs their accounting agent on us, so their external-facing agent. You need a lot more control over, your compute primitive on things like, what sort - how do you persist different files that the agent has access to, and how do you snapshot and restore? How do you control the networking? maybe you want GPUs. When you get to that point, you kinda want, a specialized sandbox provider, that gives you those things, and that's the role that we are trying to play.Swyx [00:45:15]: YeahAkshat [00:45:16]: We don't really have an opinion on the harness, whether it runs - it's a cloud-managed agent, and you hook it up to Model Sandbox, or you run the harness in Model Sandbox. We'll see where people converge with that.Swyx [00:45:26]: Yeah. Do you any opinions on like the meta harnesses, or just another layer on top of these things?Akshat [00:45:31]: You mean like the OpenPipeSwyx [00:45:33]: OpenPipe is one. I think Vercel had one, which I can't remember the name of right now. Fredshot had one. and then, to me, most recently was Data Databricks that had Omnigen. All these are meta harness. Like it's kinda pseudo agent cloud type things.Akshat [00:45:50]: I personally have not played around with them.Swyx [00:45:53]: Yeah.Akshat [00:45:53]: Build agents with them.Swyx [00:45:54]: Everything's bullish Modal, as long as it consumes more infra.Akshat [00:45:57]: That's why we're focusing on the infra layer. It's somewhere where our, relative competence is and, also it's a hard problem to solve.Swyx [00:46:06]: Yeah. I will say like just generally reflecting on that, I don't know if - if there's other topics on Modal, but like just generally reflecting as an infra person, not as intense as you, but in that field, this has like been the most exciting time in infra. Like it was boring for a while, and you couldn't really get people excited about data infrastructure. Like Eric would get on Data Console, everyone just watched the video and like say, “Look at how many sandboxes I can spin up,” and no one gave a crap.Why Infrastructure Became Exciting AgainAkshat [00:46:39]: Yeah.Swyx [00:46:40]: And like now everyone gives a crap.Akshat [00:46:42]: That's true. It is a very exciting time, and I think a lot of that's driven by just the amount of scale all of this stuff needs.Swyx [00:46:50]: I think the, like a lot of your initiatives or a lot of your like product directions make sense in retrospect, which is like the best kind, but I wouldn't necessarily have thought about it myself, which.Akshat [00:47:00]: We need the predictions.Swyx [00:47:02]: I think there's a lot that you just don't even see, right? Like you have the batch, you have the voice, you have the multimodal, but what else?Akshat [00:47:10]: What else is coming up for usSwyx [00:47:11]: Yeah. Where do you see things going?Akshat [00:47:13]: Yeah. I, in generalBiotech, Robotics, and Non-LLM AI WorkloadsAkshat [00:47:15]: It's it's clear that there's there's a huge shift happening. I think one thing that's not as obvious to people because LLM inference gets talked about so much and is also we work a lot of companies that are, doing things like drug discovery and computational bio, like the Chai Discoveries of the world. Big things are probably gonna happen there. we work a lot of robotics companies that are putting robots in like active deployments and getting good results out of them.Swyx [00:47:45]: Is there Air Gap Modal? Is there a version that is like prem air gapped whatever?Akshat [00:47:50]: No. We,Swyx [00:47:51]: You should cloud only.Akshat [00:47:51]: Yeah.Swyx [00:47:52]: Yeah. Okay. But yeah, so what you're saying is like because you're focused on primitives and they're good primitives, you find use cases in all these kinds of things.Akshat [00:48:01]: Yeah.Swyx [00:48:01]: Probably diversifies you a little bit away from LMS all the time.Akshat [00:48:05]: Yeah, absolutely. We're, we'- our goal isn't to only serve the LLM inference market.Swyx [00:48:10]: There are a lot just on the website, the audio,Akshat [00:48:12]: Yeah. We said both onSwyx [00:48:14]: Computational bio images. Yeah, there's a lot here. There's QTA TTS, customizing. Oh, Chatterbox. there was customizing Whisper.Akshat [00:48:24]: Okay. Yeah.Swyx [00:48:25]: This screen reminds me of a fallen competitor, which Replicate.Model APIs vs. Differentiated AI ProductsSwyx [00:48:31]: What's your postmortem on what happened?Akshat [00:48:34]: This is one thing we've stayed away from is providing an API for models because I think providing model APIs is some of it ends up serving like a really hobbyist market, which is much less sticky.Swyx [00:48:50]: Yeah.Akshat [00:48:50]: And we've always wanted to build for companies that are building products and need more flexibility that's not just an API.Swyx [00:48:57]: Which you can build an API for a model and this is clearly what it is. But you - but what you're saying, you can wrap it into a more fully functioning back end that you run.Akshat [00:49:06]: Yeah. So all of our examples, it's not that spin up this model, here's an API token, use it. They're all code.Swyx [00:49:13]: Okay.Akshat [00:49:13]: And so the point is that this is just an example.Swyx [00:49:16]: Starter code.Akshat [00:49:17]: Yeah. But you can tweak it however you want.Swyx [00:49:20]: Yeah.Akshat [00:49:21]: And if you're like a company building a product, like, computational bio whatnot, yeah.Swyx [00:49:26]: I guess I'm trying to tease out for listenersAkshat [00:49:28]: YeahSwyx [00:49:28]: When does it stop becoming, oh, you're just an API call and you're just a wrapper on API to becoming what you call a product, right?Swyx [00:49:36]: Like, what is that layer? Like what-- Like, more lines of code, but like beyond that, what is the substance that people add that qualifies it to be something more?Akshat [00:49:46]: I think there's a little bit of like a selection effect of like a lot of the companies who do wanna get deeper into that level are probably building something that's more differentiated. And, I think, an example is like - with LLM inference, originally we, worked with companies that were building their own post-training frameworks or they were, - Ramp early in the day was training their own tokenizer and like swapping out the tokenizer in Llama and whatnot. I'm not saying that's, that successful, in that case. But a better example is like, let's say Suno. because Suno, does not use Modal for training.Swyx [00:50:26]: Mikey on the pod. Yeah.Akshat [00:50:27]: But they use Modal for all their inference and that's because they have like a custom-- They have completely custom model architecture and that means that they have to be at the code level and tweak things that are not, just an API.Swyx [00:50:41]: It's interesting as well, like we had, Ethan, most recently on the xAI Groq team make a prediction that like the next tier in video gen is not a better video model, it's a better model or agent that orchestrates video models.Video Agents and Production WorkflowsAkshat [00:50:56]: Oh, interesting.Vibhu [00:50:56]: Language model backbone that can use toolsAkshat [00:50:58]: RightVibhu [00:50:59]: And write code.Akshat [00:51:00]: Like, yes, I can make my second video or my second video from Groq, but I want my minute video.Akshat [00:51:06]: And I'm not going there through normal video gen.Swyx [00:51:10]: Yeah, that's interesting. I - So we have GPU sandboxes and recently have seen a few companies doing agents that do video manipulation or,Akshat [00:51:22]: Yeah. Give it FFmpeg and just do it.Swyx [00:51:23]: Run FFmpeg. But likeAkshat [00:51:25]: That's not enough.Swyx [00:51:25]: Yeah.Akshat [00:51:26]: You need to give it Adobe.Swyx [00:51:27]: Yeah, I hadn't put it together with like it would be a video production thing. in my mind these things were going more towards editingAkshat [00:51:36]: Yeah.Vibhu [00:51:36]: Well, shout out Mantis.Akshat [00:51:37]: I think about this a lot.Swyx [00:51:38]: .Akshat [00:51:41]: Yeah. Sorry.Vibhu [00:51:41]: Luma. Luma Agent is a version of this for video production, but it's a off.Swyx [00:51:46]: I was gonna get your quick takes, on some other stuff that happensGitpod/Ona, CI, and Runtime SandboxesSwyx [00:51:50]: In recent news and just-just see if you have anything interesting. Gitpod, very li

AI agents are becoming one of the biggest topics in enterprise technology, but there is a critical challenge many organizations are still overlooking: context.In this conversation, I speak with Massimo Merlo from Elastic about why context engineering is becoming essential for the next phase of enterprise AI. We explore why powerful AI models are not enough on their own, why real-time enterprise data matters, and how businesses can make AI systems more useful, reliable and secure.We also discuss the debate around AI agents and the future of enterprise software. Will agents abstract away traditional software, or is the real story about where value is moving in the technology stack? As AI becomes more embedded in workflows, search, retrieval, observability, governance and data infrastructure all become increasingly important.See how Elastic makes context engineering possible at https://www.elastic.co/elasticsearch/context-engineering #sponsored In this interview, we cover:

When Hashem is a Vendor, You're Just a CustomerThis class is the third in a series on a Maamar (discourse) by the Alter Rebbe, "Ani Hashem Elokeichem," which he said on Shabbos Parshas Shlach, 28 Sivan, 5570, June 30, 1810, published in Likkutei Torah Shlach. It was presented by Rabbi YY Jacobson on Wednesday, Parshas Pinchas, 16 Tammuz, 5786, July 1, 2026, at Bais Medrash Ohr Chaim in Monsey, NY.View Source Sheets: https://portal.theyeshiva.net/api/source-sheets/9946

OpenAI has released GPT-5.6, but the majority of us will have to wait. ⌚After the Anthropic vs. U.S. Government feud, it now looks like we'll have to wait for frontier models. That wasn't the only big AI news headline that might change your company's AI strategy. Anthropic got the green light to roll out Mythos 5 to a select few, Google reportedly extended its strike team to catch up on coding and more. OpenAI's limited release of GPT-5.6, Mythos starts slow reinstatement, OpenAI gets spicy and more AI news -- An Everyday AI chat with Jordan WilsonNewsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageToday's Episode on LinkedIn: Thoughts on this? Join the convo on LinkedIn and connect with other AI leaders.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:OpenAI GPT-5.6 Limited Release ExplainedOpenAI Sol, Terra, Luna Model NamingUS Government Restrictions on AI RolloutsAnthropic Mythos 5 Access and StandoffAnthropic Fable 5 Suspension DetailsGoogle Gemini 3.5 Pro Release DelayedGoogle's AI Coding Mid-Training InitiativeRaiseUS Nonprofit: AI Workforce AdaptationAnthropic Accuses Alibaba of Model DistillationOpenAI & Broadcom Unveil Jalapeno AI ChipKey AI Industry Partnerships & Product LeaksTimestamps:00:00 OpenAI's GPT 5.6 limited release06:14 OpenAI's new model release details09:54 Access suspension and negotiations13:18 Google's AI strategy and delays16:33 Anticipating Gemini 3.5 Pro Release20:40 Accusations of AI model theft24:48 OpenAI and Broadcom chip partnership28:05 OpenAI's recent developments and updates29:56 OpenAI and AI weekly updatesKeywords: GPT-5.6, OpenAI, Anthropic, Mythos 5, Fable 5, Frontier models, Gemini 3.5 Pro, Google, model rollout, limited AI access, AI safety, US government AI regulation, Sol model, Terra model, Luna model, Max reasoning mode, Ultra mode, sub agents, advanced AI benchmarks, coding workflows, cybersecurity, third-party AI analysis, government licensing, AI model guardrails, AI model democratization, model naming scheme, model availability, AI model security, jailbreak resistance, safety filters, general model access, trusted testers, AI export control, national security, Anthropic pullback, supply chain risk, defense department, AI industry competition, talent loss, AI coding, mid training, engineering agents, AI strike team, RaiseUS nonprofit, workforce AI disruption, technology policy, industrial scale distillation, Alibaba, AI model theft, China-US tech tensions, distillation attacks, Jalapeno AI chip, Broadcom, AI inference, custom hardware, data center GPUs, Microsoft, Meta, Elastic compute, AI-powered career navigation, Slack Claude Tag, Canva Grow 2.0, Copilot skills, AI ad creation, AI automation, DigitalOcean plugin, Apple hardware AI, smart glasses, Vision Pro, portfolio tracking AI, Google Finance, home smart speakers, voice AI, GLM 5.2, open source AI, US labor market AI effects, AI job disruption, model leaks, government approval delays.Send Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info) Start Here ▶️Not sure where to start when it comes to AI? Start with our Start Here Series. You can listen to the first drop -- Episode 691 -- or get free access to our Inner Cricle community and all episodes: StartHereSeries.com Also, here's a link to the entire series on a Spotify playlist. 

*Another case of screwworms is confirmed in Texas.  *Texas A&M AgriLife is producing screwworm kits to help identify screwworms.  *Heavy rains are taking a toll on watermelons in South Texas.   *Drought conditions are improving in the Texas Panhandle.*The Houston Livestock Show and Rodeo is planning to build new facilities.  *The White House is asking for money to help U.S. farmers.*June was a wet month in Central Texas.  *Elastic therapeutic tape is being used on horses.  

When God's people respond with generosity, real lives are changed—and doors open for hope that lasts. That has been the story behind FaithFi's partnership with Heart for Lebanon, a ministry serving families displaced by the ongoing crisis in Lebanon. On today's show, we welcomed May-Lee Melki, U.S. Managing Director of Heart for Lebanon, to share what God has already made possible through the generosity of FaithFi listeners—and why the need remains urgent. Over the past few months, May-Lee and her father, Camille, have helped listeners understand the tremendous challenges facing families in Lebanon. The war has displaced thousands, placed communities under severe strain, and left many families carrying emotional, physical, and spiritual burdens. While there have been temporary pauses in the fighting, May-Lee explained that a ceasefire has not meant true peace for many families. “Families are beginning to experience different effects of the ongoing war, instability, and repeated disruption,” she said. “There's a lot of fear, and there's a lot of uncertainty.” Many are still facing food insecurity, damaged infrastructure, interrupted livelihoods, and the constant fear that conditions could worsen without warning. Generosity That Has Already Made a Difference FaithFi listeners originally set out to help 275 displaced families in Lebanon. By God's grace, that goal has now been met. Those 275 families represent more than 1,000 individuals receiving life-sustaining support through Heart for Lebanon. That support includes food, mattresses, blankets, hygiene kits, diapers for adults and children, and care for newborns entering a world marked by war and uncertainty. But the impact goes beyond supplies. May-Lee shared the story of Ibrahim, a six-year-old boy whose family had to flee in the middle of the night as violence intensified. His parents carried their children and ran into the unknown, unsure where help would come from. Through the generosity of Faith and Finance listeners and the ministry of Heart for Lebanon, Ibrahim's family received practical care and ongoing support. His mother later told the team, “Please don't stop your children's activities, even throughout the war.” Ibrahim's favorite Bible story is Jesus feeding the 5,000. For him, that story has become deeply personal. He told the team, “Jesus loves us, and I know He will not let us go hungry.” That is more than humanitarian aid. It is a picture of God's provision working through His people. Meeting Physical Needs and Building Trust Heart for Lebanon's ministry begins by meeting urgent physical needs wherever families are—whether in shelters, makeshift tent settlements, or other temporary spaces. Food, bedding, and hygiene supplies help families survive while preserving their dignity. But the ministry does not stop there. May-Lee emphasized that Heart for Lebanon is not simply dropping off supplies and leaving. Their team is present for the long haul, walking with families through an open-ended season of displacement and uncertainty. That consistent presence creates trust. And trust opens the door to deeper conversations about faith, hope, and the love of Christ. May-Lee shared the story of Najwa, a woman who first came to Heart for Lebanon looking for food for her family. Over time, through relationships with the team, she found something she had not expected. She said her heart had been longing for a kind of spiritual nourishment she did not even know existed. Through the ministry's care and the message of the gospel, Najwa came to understand that she had not been forgotten by God. That kind of transformation takes time. It does not happen through a single package of supplies. It happens as God's people listen, serve, build relationships, and bring the hope of Christ into the deepest places of need. Hope in the Midst of Crisis In times of crisis, hearts are often more open than before. But May-Lee said that what truly points people to Jesus is not only the immediacy of help but also the authenticity of a long-term relationship. Heart for Lebanon's team is made up of local believers serving other locals—many of whom are experiencing the same hardships. Some members of the team in southern Lebanon have been displaced themselves, yet they continue to serve. That shared experience gives their ministry a unique credibility. Families see that these believers are not there temporarily. They are staying, serving, and carrying the burden. As a result, families are attending Bible studies in growing numbers, asking questions about faith, and seeking spiritual truth. May-Lee shared another story of a single mother named Nawal, who said, “Even during the war, someone was still thinking about us.” Through that care, she began to understand Jesus' love in a tangible way. “He's with me even in my darkest hour,” she said. That is the opportunity before Heart for Lebanon—to model the gospel in action during an ongoing crisis. Caring for the Whole Person The needs in Lebanon are not only physical. Children have witnessed things no child should have to see. Families have lost homes, routines, stability, and a sense of safety. Heart for Lebanon is helping turn crowded shelters and temporary spaces into places of care. Their team provides trauma-informed activities, play, art, and listening—simple but meaningful ways to help children process fear and begin to experience safety again. The ministry's approach is holistic because people are whole persons, made in the image of God. Food and supplies matter. Dignity matters. Emotional care matters. And above all, eternal hope in Christ matters. May-Lee put it plainly: tangible aid is important because it restores dignity, but it also becomes a vehicle for building trust and creating relationships that can flourish for God's Kingdom. The Need Remains Great Because of the generosity of Faith and Finance listeners, more than 275 displaced families are already receiving ongoing care. We praise God for that. But the need remains tremendous. Heart for Lebanon has committed to continue supporting these families with monthly care, including food, bedding, hygiene supplies, and relational support. They also hope to expand that care to reach even more families who are still facing fear, displacement, and uncertainty. Every $90 given helps provide a full month of care for a displaced family, while also allowing Heart for Lebanon to continue building relationships and sharing the hope of Christ. If you would like to help, visit FaithFi.com/Lebanon or text the word FAITH to 98656. When God's people respond with generosity, families receive more than temporary relief. They receive care, dignity, relationship, and a glimpse of the lasting hope found only in Christ. On Today's Program, Rob Answers Listener Questions: I received a letter from Social Security about the Social Security Fairness Act and the end of the Windfall Elimination Provision. They also deposited a lump sum into my checking account. I'm confused about why I received it, what it means, and whether I'll owe taxes on it. A friend borrowed about $500 from a company called Elastic, but the balance quickly grew to around $3,200. My family and I want to help her pay it off, but I'm concerned it may be predatory or a scam. How can we protect her, and what steps should we take? My husband and I are 57 and 54. We once had about $200,000 in savings, but after COVID and serious health and life challenges, that money is gone. We earn about $65,000 a year, have only about $500 across our accounts, and are living paycheck to paycheck. We each have about $25,000 in life insurance or retirement, but we're essentially starting over. How can we rebuild a financial plan at this stage of life? Resources Mentioned: Faithful Steward: FaithFi's Quarterly Magazine (Become a FaithFi Partner) Heart for Lebanon Our Ultimate Treasure: A 21-Day Journey to Faithful Stewardship by Rob West Wisdom Over Wealth: 12 Lessons from Ecclesiastes on Money Look At The Sparrows: A 21-Day Devotional on Financial Fear and Anxiety Rich Toward God: A Study on the Parable of the Rich Fool Find a Certified Kingdom Advisor® (CKA) FaithFi App Remember, you can call in to ask your questions every weekday at (800) 525-7000. Faith & Finance is also available on Moody Radio Network and American Family Radio. You can also visit FaithFi.com to connect with our online community and partner with us as we help more people live as faithful stewards of God's resources. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, Liz Gleadle shares insights about rhythm, throwing, emotional training, and the deeper human elements of performance. She discusses how hanging, rings, dance, breath, sound, and object-based play shaped her understanding of movement, coordination, and javelin technique. They also explore strength training, elasticity, gratitude, coaching energy, cultural rhythm, and how athletes can learn to move with more joy, confidence, reverence, and authentic physical expression. Today's episode is brought to you by Hammer Strength and the Just Fly Sports Online Courses

Finding a needle in a haystack would seem like a minor endeavor compared to what today's federal systems managers must face. Let's take a stab at a correct farmyard analogy – the haystacks double in size every day and are moving. That sounds like an exaggeration, but recent reports show that nine million zero-day exploits are released every day. AI is putting malicious actors on steroids. Chris Townsend, Global Vice President of Public Sector at Elastic, discussed the company's role in federal cybersecurity and data management. His argument is, essentially, that cybersecurity is a data problem. If threats are viewed from that perspective, the more data you can bring into your security environment, the more effective you are at defending it. Elastic enables security operations analysts      who are responsible for detecting threats to keep up with today's tlandscape and cyber-attack velocity. Elastic's platform and tools     can reduce false positives and help federal security operations centers (SOCs) prioritize valid threats. Townsend highlighted Elastic's agentic AI tools, which help SOC operators prioritize and remediate threats, reducing mean time to detect and respond.  Elastic's partnership with CISA for a managed  Security Information and Event Management (SIEM) as-a- service was also mentioned, emphasizing the importance of standardizing data for effective AI-driven cybersecurity. Townsend goes on to articulate Elastic's launch of a SIEM-as-a-Service offering for federal civilian agencies, featuring Elastic Security on Elastic Cloud. SIEMaaS delivers a cloud-based platform for next-generation, AI-powered threat analytics, incident response, and open-standards-based cybersecurity data ingestion. Here is a link to Chris' blog describing     CISA's SIEMaaS offering and how it supports federal agencies' cybersecurity posture while reducing costs

Roman Chernin is Co-Founder and Chief Business Officer of Nebius, one of the fastest-growing AI infrastructure companies in the world. Today, Nebius operates some of the largest AI compute clusters globally and serves leading AI labs, enterprises, and developers. Today, Nebius has a market cap of $57BN.  AGENDA:  00:00 — Why AI Infrastructure Is Not a Bubble 05:00 — The Real Impact of Open Source on OpenAI & Anthropic 11:00 — Jevons Paradox: Why Cheaper AI Creates More Demand 13:00 — The Four Layers of AI Infrastructure Explained 19:00 — If Nebius Had 10x More Capacity Tomorrow 26:00 — The Shift from Training to Inference and Agents 31:00 — How Token Factory Cuts AI Costs by 70% 44:00 — Sovereign AI, Europe, and the Future of Model Building 49:00 — Competing Against Hyperscalers with 10x More Capital 59:00 — The Biggest Threat to Nebius Isn't Competition—It's Consolidation    

The partner ecosystem is changing. As AI reshapes enterprise technology and customers demand faster business outcomes, traditional partnership models built around co-marketing and channel reach are being challenged. In this episode of #ZinnovPodcast, Rajat Kohli, Partner at Zinnov, speaks with Alyssa Fitzpatrick, GVP, Partner Sales at Elastic, to discuss how partner ecosystems are evolving and what it takes to stay relevant in an increasingly competitive landscape. Together, they explore: • Why the future is customer-led, not partner-led • How AI is changing the way partner ecosystems are built • Why co-innovation is becoming more important than co-marketing and co-selling • The challenge of differentiation when every partner looks like an A+ player • How leading organizations identify and invest in the right ecosystem partners • The growing role of enablement, managed services, and ecosystem collaboration Whether you're a partner leader, alliance manager, technology executive, ecosystem builder, or GTM strategist, this episode offers valuable insights into the future of partnerships and ecosystem-led growth. Tune in now.

In der heutigen Folge sprechen die Finanzjournalisten Nando Sommerfeldt und Holger Zschäpitz über die Rüstungs-Rallye, die Anthropic-Ansage und eine perfekte Transformations-Wette. Außerdem geht es um Alphabet, Amazon, Super Micro Computer, MongoDB, Okta, NetApp, Autodesk, Elastic, SentinelOne, Rheinmetall, Hensoldt, Renk, TKMS, Leonardo, Thales, Eli Lilly, CVS Health, Dollar Tree, Best Buy, Nvidia, Nebius, Meta Platforms, CoreWeave, Bloom Energy, SanDisk, Broadcom, AMD, Oracle, Micron, VanEck Semiconductor UCITS ETF (WKN: A2QC5J), Schaeffler, Spire, Hexagon, Vanguard FTSE All-World ETF (WKN: A2PKXG). Wir freuen uns an Feedback über aaa@welt.de. Noch mehr "Alles auf Aktien" findet Ihr bei WELTplus und Apple Podcasts – inklusive aller Artikel der Hosts. Hier bei WELT: https://www.welt.de/podcasts/alles-auf-aktien/plus247399208/Boersen-Podcast-AAA-Bonus-Folgen-Jede-Woche-noch-mehr-Antworten-auf-Eure-Boersen-Fragen.html. Hier könnt ihr den AAA-Newsletter abonnieren: https://www.welt.de/newsletter/article232797673/Alles-auf-Aktien-Der-taegliche-Boersen-Newsletter-fuer-WELTplus-Abonnenten.html Und - ganz neu: AAA gibt es jetzt auch auf Instagram: https://www.instagram.com/alles_auf_aktien/ Disclaimer: Die im Podcast besprochenen Aktien und Fonds stellen keine spezifischen Kauf- oder Anlage-Empfehlungen dar. Die Moderatoren und der Verlag haften nicht für etwaige Verluste, die aufgrund der Umsetzung der Gedanken oder Ideen entstehen. Hörtipps: Für alle, die noch mehr wissen wollen: Holger Zschäpitz können Sie jede Woche im Finanz- und Wirtschaftspodcast "Deffner&Zschäpitz" hören. +++ Werbung +++ Du möchtest mehr über unsere Werbepartner erfahren? Hier findest du alle Infos & Rabatte! https://linktr.ee/alles_auf_aktien Impressum: https://www.welt.de/services/article7893735/Impressum.html Datenschutz: https://www.welt.de/services/article157550705/Datenschutzerklaerung-WELT-DIGITAL.html

OpenTelemetry has officially reached CNCF graduation this month, marking a major milestone for one of the most widely adopted open observability projects. In this episode of OpenObservability Talks, we unpack what this graduation really means for the project and for users out there. We also revisit the newest observability signal in OpenTelemetry, Continuous Profiling, which was released in public alpha. We explore where the effort currently stands, the adoption and usage best practices. Finally, we dive into the OpenTelemetry eBPF profiling agent and how it aims to dramatically simplify the adoption of continuous profiling for developers and platform teams.Our guest for this episode is Israel Ogbole, CEO & Co-founder of Zymtrace and member of the OTel Profiling SIG. Prior to founding zymtrace, he served as Principal Product Manager at Elastic, where he led Universal Profiling. He also led the donation of Elastic's eBPF CPU profiler to OpenTelemetry. Israel also worked at Cisco AppDynamics and at Microsoft, with rich background in observability. You can read the recap post: https://medium.com/p/c66dc2cd7d3cShow Notes:00:00 - episode and guest intro04:16 - OpenTelemetry reaches CNCF graduation15:25 - Continuous profiling reaches public Alpha34:19 - eBPF profiling agent 57:04 - outroResources:OpenTelemetry reaches CNCF Graduation: https://opentelemetry.io/blog/2026/otel-graduates/ OpenTelemetry Profiles Enters Public Alpha: https://opentelemetry.io/blog/2026/profiles-alpha/ OTel adds the eBPF profiling agent donated by Elastic: https://opentelemetry.io/blog/2024/elastic-contributes-continuous-profiling-agent/Unveiling OpenTelemetry eBPF Instrumentation: https://medium.com/p/377cb0432bf1  Continuous Profiling: a new observability signal: https://medium.com/p/8afd5bafd498   OTel Profiling SIG established: https://medium.com/p/4a9b407e48cc  eBPF for no-code observability instrumentation: https://www.youtube.com/watch?v=NYDBj5ctKaw&list=PLd57eY2edRXz4djMETYTm-2p8WGTdoX3DSocials:BlueSky: https://bsky.app/profile/openobservability.bsky.socialX (Twitter): ⁠https://x.com/OpenObserv⁠LinkedIn: https://www.linkedin.com/company/openobservability/YouTube: ⁠https://www.youtube.com/@openobservabilitytalks⁠Dotan Horovits============X (Twitter): @horovitsLinkedIn: www.linkedin.com/in/horovitsMastodon: @horovits@fosstodonBlueSky: @horovits.bsky.socialIsrael Ogbole===========X (Twitter): https://x.com/israel_ogboleLinkedIn: https://www.linkedin.com/in/israelo/OpenObservability Talks episodes are released monthly, on the last Thursday of each month and are available for listening on your favorite podcast app and on YouTube.

Steve Albini left this planet 2 years ago, and we recorded an episode (back in 2024; unreleased) covering his last release with Shellac, as well as The Fall's influence on his own music. He may or may not have been in collusion with Virgin trains, but enjoy this mini side-journey!

Three cheap and simple hacks to help your sweep rowing. Small clever fixes to real problems that sweep rowers deal with all the time. Timestamps 00:45 What is a rowing hack? Tricks and techniques for your own rowing - a low cost, improvised fix to a persistent problem. The best hacks give you physical feedback in the moment as a constant reminder so you don't have to keep something front of mind. Moving you into unconscious competence. Learn more about unconscious competence and the 4 stage adult learning model https://fastermastersrowing.com/rowing-technique-makes-my-brain-hurt/ 02:00 Elastic band on the oar handle If your inside hand moves up and down the handle - it drifts. This affects the amount of effort / load you can put onto the oar from square off to the finish. Take an elastic band and wrap it around the oar handle so it sits on the outside of your hand next to your little finger. If the band is tight, when your hand starts to move it won't roll the elastic band - you'll feel it and realise if your hand has moved off position. If your hand goes the other way, put the elastic band next to your forefinger instead. First check you have the correct spacing between your hands first. 04:00 The coxing plank When you have someone who is too large to fit into the coxswain's seat - use the coxing plank. A plank of wood sitting across the transom / sax board of your eight. We put a sculling seat on top so it's comfortable to sit on. Put your feet into the bottom of the boat. And add a lanyard to attach to the steering wires in case the plank moved or fell off and it remained attached to the boat. The cox can then see above the heads of the athletes giving greater line of sight for coaching the crew. If your crew has to take turns steering the eight - this is the hack for you. 06:30 Wrist tape If you feather with both hands and twist your wrist to turn the oar when squaring and feathering - this is for you. The correct sweep feather action is to allow the oar handle to turn inside your hand grip for the outside hand, while only your inside hand wrist rises or lowers to turn the handle. Take a piece of tape - sellotape/scotch tape or micropore or masking tape or electrical tape. Run it from your knuckle across your wrist and to your lower forearm. The idea is that it sticks to the hairs on the back of your hand so when you turn your wrist (and you shouldn't) it pulls on the hairs. This hurts.... you feel the tape tighten and serves as a reminder not to move your wrist.

One common theme among technology leaders when they comment on deploying AI is the need for a definitive source.  If you don't have that, then none of the conclusions will be actionable. In this episode of Feds at the Edge, we have two experts who share with the audience ways they have accomplished this goal. The first concept is the importance of data quality.  Jared Pane from Elastic warned against blindly trusting AI.  We all know about standard problems, like inaccurate data. He mentions something new: malicious actors intentionally inserting code into datasets included in AI repositories. This is called white-space text that can't be seen yet but contains malicious code. Chris Burton addresses security and compliance issues through automation. To assist others, he has implemented a policy bot for new employees.  This can answer all questions about best practices for compliance 24 hours  a day.     Practical advice emphasized starting small, focusing on clear problems, and fostering a collaborative culture.  

 Greg Davidson is the Co-Founder and CEO of Lalo, a modern baby and toddler brand built around the idea that new parents deserve better: better design, better guidance, and products that actually grow with their kids. Greg's path to founding a baby brand is not what you'd expect. He came up through a series of fast-growing startups in sales and go-to-market roles at Elastic, Krossover, WayUp, and Artsy before co-founding Lalo in 2017 with his former WayUp colleague, Michael Wieder. Neither of them had kids at the time. His first child was born in 2020, just after officially launching the business in 2019 and right before a global pandemic. They were somehow still able to grow 400% that first year. Lalo has since raised a $10.1 million series A, and expanded into Target, Babylist, Pottery Barn Kids and beyond. Greg is based in Miami and is a dad of three.See omnystudio.com/listener for privacy information.

Strength coach Dario Saisan joins to discuss how AI and research are evolving the field. We dive into biomechanics, skill acquisition, and why the next generation is moving toward adaptive systems that sharpen human intuition.

Where Empathy Meets Artificial Intelligence in Customer Service    Shep interviews Jen Grant, Chief Marketing Officer at Quiq. She talks about how intentionally designed AI, combined with human empathy, can create effortless, personalized experiences at scale that customers embrace.  This episode of Amazing Business Radio with Shep Hyken answers the following questions and more:   How can businesses prevent AI from making customer service mistakes?  How can personalization through technology enhance customer loyalty?  Why is an effortless customer experience crucial for building loyalty?  How can technology help anticipate customer needs?  How has customer willingness to interact with AI changed over time?  Top Takeaways:    Artificial intelligence is a powerful tool for improving the customer and employee experience when it is designed with intention. Just as human agents need training, AI tools need enterprise controls, verification checks, and simulations to make sure they provide the right information and respond appropriately to customer needs.   More customers now consider interactions with AI to be part of the norm. But some are still hesitant to embrace it because of past frustrations with outdated systems, like confusing phone trees or long waits in loops they associate with all types of technology.  When interactions with technology, such as AI tools, create effortless experiences, customers are more willing to use them. Companies need to educate customers on how to use their technology and self-service solutions to improve their experiences.   Make it easy for customers to do business with you. This applies to every part of the customer's journey, not just technology.  Customers want answers and help fast. Give it to them with as little effort as possible.  Human empathy remains important, especially in high-stress situations. Customers need to be comfortable with how they are being helped and supported, whether it is AI, a human agent, or both working together. In stressful situations, customers appreciate the reassurance that a human agent will be there to provide empathy and assist them when tech-powered solutions are not working.  Technology should not replace people. Good technology makes it easier for employees to help customers and faster for customers to get solutions.  Personalization and empathy can be scaled through technology. Human employees can only remember so much. Technology can help them have instant access to a customer's data and history. When technology recognizes returning customers, anticipates their needs, and connects their history to current interactions, it replicates the feeling of being known and valued.   Plus, Shep and Jen talk about what could happen if companies began customer service interactions with a human for empathy, then transitioned to AI for efficiency, rather than forcing customers through automation before reaching a person. Tune in!  Quote:   "AI agents need clear guidance and verification checks to stop 'hallucination.' It is important that if AI goes off track, companies need to catch and correct it before it gets to customers."  About:    Jen Grant, Chief Marketing Officer at Quiq. She has held executive leadership roles, including CEO, COO, and CMO, as well as senior marketing positions at Appify, Box, Cube, Dialpad, Elastic, Google, and Looker.  Shep Hyken is a customer service and experience expert, New York Times bestselling author, award-winning keynote speaker, and host of Amazing Business Radio.   Learn more about your ad choices. Visit megaphone.fm/adchoices

In which there's Elastic Twang & Pluck, we price cutlery, consider a crooner's clobber, and get the blues. Full show notes are at https://offgrid.tlmb.net/Some General Knowledge, a mini-quiz, and some fun trivia we didn't necessarily know until just now.Before each recording, the hosts & their guest solve a cryptic crossword. In the podcast, we riff on words in the grid or clues (spoilers!), telling each other things we find funny or interesting about them. We'll also pick a favourite clue each, and explain how it works to the listener, and have a mini-quiz, also inspired by the puzzle. You don't have to solve or understand cryptic crosswords yourself to enjoy this podcast, but hopefully we might intrigue and tempt you to dip your toes in the water. Hosted on Acast. See acast.com/privacy for more information.

The dominant mechanism discussed is a shift from a focus on AI capability to trust and governance as the deciding factors in AI adoption for managed service providers and their clients. Vendors are increasingly positioning governance, control layers, and auditability as necessary operational functions, rather than add-on features. This is driven by enterprise demand for transparency and accountability across identity, data protection, compliance, and ongoing monitoring. Companies such as Acronis, Microsoft, and Elastic are introducing tools for managing AI access, monitoring sensitive data exposure, and embedding control processes directly into operational workflows. The episode highlights that, according to research from Gong, 58% of companies have stalled their AI projects due to a lack of trust in data handling and AI-generated outputs—not because of budget constraints. Nearly half (46%) of planned investments were paused specifically over concerns around privacy, explainability, and model transparency. Buyers cited the need for explicit policy controls, demonstrable security guarantees, and accountability safeguards before new capabilities are approved. Supporting developments include Acronis's Genai Protection, designed for MSPs to increase visibility over customer AI activities and detect risks such as prompt injection and shadow AI. Meanwhile, incidents like the unauthorized access to Anthropic's Claude Mythos preview through a contractor, reported by The Verge and Gizmodo, reinforce that even leading vendors face security and accountability challenges. Vendors such as Microsoft and Dropbox are moving to integrate centralized control layers that directly address these new operational risks, while tools like Watchguard and Halo are tying security events to key business workflows. For MSPs and IT leaders, the implications are operational rather than purely technical. AI governance now requires continuous policy management, exception handling, and documented evidence across multiple platforms—a scope that most internal teams are not resourced to handle. The market is shifting toward purchasing accountability as a managed service, and providers that fail to deliver clear governance frameworks, connector approvals, and audit-ready reporting will face increased contract risk, client loss following incidents, and potential liability under insurance and regulatory requirements. 00:00 Shadow AI Risk 03:07 Platform Consolidation 04:55 Stalled AI Spend 07:55 Why Do We Care?  Supported by:  ScalePad  Upcoming event: The Pivotal Point of IT: Building Services for the AI-First EraDate: May 13 at 1p.m. EDTRegister: https://go.acronis.com/davesobelaiera

For this week's B.S. Buster, Meir questions the growing obsession with vulnerability — the belief that you must publicly share your mess, your pain, and your failures - in order to heal or grow. It sounds meaningful… but is it actually true? Meir separates truth from comfort and reveals how this belief quietly does more harm than good.Next, we move into our main topic: self-sabotage. We explore why people hold themselves back without realizing it, how invisible limits begin to form, why people don't realize it, and the harm it creates. Meir breaks down these invisible elastic bands that restrict action, confidence, and direction. We also take a look at people-pleasing. We look at whether it's right or wrong, why it develops, and who's really responsible for it. Find all this and much more in this episode.We wrap up with The Extreme Wisdom – Part 2. In Part 1 (which was free), Meir revealed the single factor preventing most people from getting the results they want. This time, he goes deeper and shows exactly how to fix it. For just $29, with a money-back guarantee and an additional 10% back if you don't get what you came for, you truly have nothing to lose. Register now and get back control of your life www.Gprosperity.com/extreme

Chris Townsend, Global Vice President of Public Sector at Elastic joins the show to explore the evolving intersection of cybersecurity, AI, and data strategy in government. We dive into the shift toward continuous Authority to Operate (ATO) and why real-time, always-on security is becoming essential in an era of AI-powered threats. We also break down how both adversaries and defenders are leveraging AI and why “machine-speed attacks” demand equally fast, intelligent responses. Finally, we unpack the growing role of agentic AI in security operations, from automating threat detection and prioritization to augmenting SOC teams and how AI is transforming citizen services, with real-world examples of improving access to benefits and delivering more personalized government experiences.

Reflections from host Sarah Olivieri ... Imagination: The Missing Ingredient for Better Strategy Have you ever experienced a strategic planning process where you get a room full of smart, committed people? They agree on the words. They nod at the plan. And then six months later, everyone is pulling in slightly different directions. In my experience, this happens when the plan was created without real clarity and alignment around where exactly we are trying to go. Clarity and alignment come from shared understanding. And shared understanding starts with how clearly people can picture what "done" looks like. And in order to "see" what "done" looks like, we need … IMAGINATION!  I recently had a conversation about this with imagination expert and strategist Rebecca Sutherns. Imagination skills are critical for great strategy planning and execution.  Are You Planning Backwards? Most planning processes are built around looking in the rearview mirror. We review last year's data. We evaluate what worked. We talk about what didn't. None of that is wrong. But it's incomplete. Because strategy is not about explaining the past. It's about building the future. Rebecca said something that stuck with me: "Our strategies ought to be forward-facing, not backward-facing." That sounds obvious. But it's not how most organizations actually operate. What happens instead is this: We take what we've already done. We make incremental adjustments. We call it strategy. That's not a strategy. That's iteration without intention. And when you build a plan this way, you end up with a partially built system. It functions—but it doesn't move you meaningfully forward… Because you haven't clearly imagined, as a collective, what the future looks like, tastes like, feels like. Why Alignment Breaks Down Even when teams do talk about the future, they often still don't align. Because they're using the same words… but imagining different things. Rebecca put it this way: "If people are not watching the same movie in their heads, there's a good chance you're using the same language but moving in different directions." I see this often. We assume other people are thinking what we are thinking when we talk to them, but actually getting them to think what we are thinking is a much harder feat. When we talk, we usually communicate only a tiny fraction of what we intend to. Ask a leadership team what success looks like, and you'll get five versions of the answer. None of them are wrong. But they're not the same. And when that happens, execution becomes messy. What Actually Creates Alignment If you only take one thing away, it's this: Alignment is not about agreement. It's about shared imagination. You need people to be able to picture the same outcome. Not just intellectually—but concretely. That means moving beyond vague language like: "Make a bigger impact" "Expand our reach" "Strengthen the organization" Those sound good. But they don't mean anything operationally. Instead, you need to ask: What does this actually look like? Draw it! What's happening differently when we've succeeded? What would we see, hear, and feel if this worked? This is where imagination becomes a leadership skill—not a nice-to-have. Why Imagination Feels So Hard Most nonprofit leaders struggle with this. And it makes sense. They're operating at capacity. They're dealing with real constraints. They're trying to make payroll. So when you ask them to imagine a bold future, you often get: "I just want enough money to pay my staff." That's not a lack of ambition. It's a reflection of the state of being under-resourced. But constraints can actually enhance our ability to be creative. Rebecca shared a simple but powerful idea: Instead of removing constraints entirely, define them clearly. For example: "We have $50,000 and six months. Now what could we build?" This changes the conversation. It gives the brain edges to work within—without shutting down possibilities. How to Actually Build the Skill Imagination is not a personality trait. It's a muscle. And like any muscle, it gets stronger with use. One of the most useful insights Rebecca shared is that imagination is built from memory. We don't create from nothing. We recombine what we've already seen, experienced, or learned. That means the fastest way to improve your strategic thinking is not another framework. It's more inputs. Talk to people outside your sector Read widely Change your environment Expose yourself to different ways of thinking This expands your "pantry" of ideas. And the bigger the pantry, the better your ability to combine ingredients and imagine something new. Imagination Changes How Leaders Show Up. There's one more piece here that I don't want to skip. Imagination changes how leaders show up. Because when you can imagine better, you start asking better questions, and better questions lead to better answers. Also, we can't be great at imagining if we don't get great at being curious. When leaders come in with curiosity, people open up. And when people open up, you get better thinking. Better thinking leads to better decisions. And better decisions lead to better results. About the Guest Rebecca Sutherns, Ph.D., is the CEO and Founder of Sage Solutions, empowering purpose-driven leaders to align what's important to them with what they actually do. With 27+ years of global experience as a bestselling author, master facilitator, and coach, she uniquely helps clients leverage imagination as a strategic superpower, bringing analytical rigor, warm energy, and adaptability to strategy and governance. Her journey began by observing leaders across sectors staying stuck in past patterns, missing future possibilities. The turning point was realizing that a "failure of imagination" is often at the root of misalignment on teams and even of global-level mishaps. Now, she helps Boards and senior managers identify what's fixed and what's flexible as they shape their future amidst accelerating change. Through her ELASTIC framework, Rebecca helps non-profit leaders collectively reimagine their next chapter. She champions imagination as a learnable skill via strategic planning facilitation and her conversation-starting Possibility Packs, fostering vivid, shared mental pictures to proactively "dent the world". Connect with Rebecca:  https://rebeccasutherns.com/ https://www.linkedin.com/in/rebeccasutherns/ Be sure to subscribe to Inspired Nonprofit Leadership so that you don't miss a single episode, and while you're at it, won't you take a moment to write a short review and rate our show? It would be greatly appreciated! Let us know the topics or questions you would like to hear about in a future episode. You can do that and follow us on LinkedIn.

(Presented by TLPBLACK: High-fidelity threat intelligence and research tools for modern security teams. From curated Passive DNS and real-time C2 monitoring to actionable IOC feeds and daily malware samples, we help defenders detect, hunt, and disrupt threats faster, with seamless integration into SIEM and SOAR workflows.) Three Buddy Problem - Episode 92: Costin walks through real-world ransomware incident response while Juanito makes the case for AI-generated operating systems that never run anyone else's code. Plus, debates on whether vulnerability research is cooked, why nobody should pay ransoms, and what the security industry looks like after the massive AI flood. Cast: Juan Andres Guerrero-Saade, Ryan Naraine and Costin Raiu. 0:00 – Introductory banter 2:00 – Costin's ransomware incident response work 3:30 – How attackers break in: Fortinet vulnerabilities everywhere 6:30 – Hunting for ransomware decryption keys 9:00 – Breaking into ransomware C2s and monitoring leak sites 12:00 – The ransom payment debate: should you ever pay? 16:00 – Why "don't pay the ransom" is overgeneralized 21:00 – How ransomware gangs price their demands 24:00 – The AI-pilling of the security industry 28:30 – Nicholas Carlini, Ptacek, and "vulnerability research is cooked" 35:00 – Towards a generative-first operating system 41:00 – Code factories, trusted computing, and killing dependencies 48:00 – Microsoft and Apple's AI positioning 56:00 – Chris St. Myers' "Cognitive Rust Belt" essay 1:18:00 – Choice, The Matrix, and the illusion of control 1:38:00 – Supply chain attacks, North Korea, and dependency sprawl

What if employee experience isn't an HR initiative… but the system your entire business runs on? In this episode of Success Leaves Clues, Robin and Al sit down with Ashlea Desroches, People & Culture Leader at Elastic Path, to unpack a powerful shift in how organizations think about culture, performance, and leadership. Ashlea challenges the idea that employee experience is a “nice to have,” and reframes it as the true competitive advantage driving engagement, retention, customer experience, and ultimately, business results. From psychological safety and leadership behavior to pay transparency and growth-driven management, this conversation goes deep into what actually creates high-performing teams… and why most organizations are still getting it wrong. If you're leading a team, scaling a company, or trying to build a culture people don't want to leave, this episode will change how you think about performance, trust, and what it really takes to win. You'll hear about: Why employee experience is the operating system of your business The link between culture, customer experience, and profitability Why high performance does not always equal high engagement How employee referrals reveal your true internal culture The role of psychological safety in innovation and team performance Why great cultures are built on clarity, safety, and recognition The difference between comfort and true psychological safety How avoiding difficult conversations destroys team trust Why growth conversations outperform performance reviews The one question every leader should be asking their team How leaders create conditions where performance becomes inevitable Why pay transparency is becoming a leadership imperative The hidden trust gap created by compensation secrecy How to implement pay transparency without exposing salaries Why compliance is the floor, not the strategy The long-term impact of developing first-time leaders We talk about: 00:00 Introduction to Ashlea Desroches and her approach to people & culture 02:00 Why employee experience is a true competitive advantage 04:30 The connection between employee satisfaction and business performance 06:00 How culture shows up in customer interactions and reputation 08:00 Why retention is built when hiring is easy, not hard 10:00 What actually shapes the employee experience end-to-end 12:00 Common traits of high-performing cultures across industries 14:00 Psychological safety vs comfort, and why it matters 17:00 The danger of avoiding difficult conversations as a leader 19:00 How to create safe, open dialogue within teams 21:00 The leadership shift from performance to growth conversation 23:00 The question that transforms employee development 25:00 Where growth conversations should actually happen 27:00 The biggest people-related challenge leaders face today 29:00 Pay transparency, trust, and the future of compensation 32:00 Why most organizations misunderstand transparency 34:00 Building trust through clarity, not secrecy 36:00 Leadership legacy and developing future leaders Connect with Ashlea LinkedIn: https://www.linkedin.com/in/ashleadesroches/ Website: https://www.elasticpath.com/ Connect with Us LinkedIn: Robin Bailey and Al McDonald Website: Aria Benefits and Life & Legacy Advisory Group

Are you leaving hidden cash on the table after Airbnb's dramatic fee overhaul or, worse, losing it without knowing? In this data-charged episode, Kenny Bedwell breaks down the most misunderstood shift in recent STR history: Airbnb's transfer of guest fees to hosts. If you've ever worried you're charging the wrong nightly rate, or you're blindsided by shrinking net returns despite steady bookings, you're not alone.With surgical clarity (and zero fluff), Kenny Bedwell reveals who actually won, who lost, and why only the savviest hosts survived. This isn't another regurgitated news brief, it's your exclusive masterclass on elasticity, ranking risk, and tactical pivots that could save (or sink) your STR portfolio.Listen now to avoid sabotaging your own profits, act before your competition does, and get the unfiltered inside scoop you won't find scrolling social or Reddit.Timestamped Highlights[00:00] The day everything changed: Airbnb's shocking fee flip and what most hosts missed[01:08] The chaos and confusion: Why hosts panicked over math and which ones got it right[02:01] The 30/30/40 rule: Why most hosts failed to adjust and what it cost them[05:57] The big economic reveal: Does the guest really care, or do hosts pay the highest price?[07:09] The VRBO effect: How Airbnb's move handed business to its rivals[09:13] Secret algorithms: How fees, ranking, and property uniqueness now decide your fate[11:14] Elastic vs. inelastic: Why “average” properties are at greatest risk in 2024[15:20] How to future-proof your portfolio: Building your moat before the next big changeMentioned ResourcesVRBO (Vacation Rentals by Owner)Ranking algorithm discussions on AirbnbImportant LinksWant us to find the deals for you? https://strinsights.com Get Top Markers for STRs (2025) - https://rebrand.ly/28b1df Instagram – @kenny_bedwellYouTube – Cash Flow PositiveLinkedIn – Kenneth BedwellCash Flow Positive is an original podcast hosted by Kenny Bedwell. Brought to you by STR Insights. Production and editing by Podcast Your Brand.

Missing, Elastic, and Civil lead us to cloning pets, where you put the emphasis when pronouncing "rubber band", Stretch Armstrong, fitted sheets, cannonballs, and more.New episodes every Tuesday.Editing by: Julia WD HarrisonTheme by: Arne Parrott Logo by: Casey BordenSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Fresh out of the studio, Ken Exner, Chief Product Officer at Elastic, joins us to explore how Elastic evolved from the world's most popular open-source search engine into the context layer powering modern AI applications and agent systems. He shares his career journey from database programming to over 16 years at Amazon building AWS resilience practices, and now leading product strategy where search, observability, and security converge into a unified AI platform. Ken explains why context engineering is the defining discipline of the AI age, where developers become managers of agents, and how Elastic's 15-year enterprise head start positions it as the foundational retrieval layer between enterprise data and LLMs."I like to think of the future of software development is—developers will be managers of agents. They're no longer going to be ICs [Individual Contributors], they're going to be managers. Every developer is going to be a manager of agents and they're going to be doing context engineering. They're going to be figuring out how to pass context and data to an LLM or an agent. And they're going to be goal setting. They're going to have their team of agents, and they're going to give them goals, and they're going to review the output." - Ken Exner Episode Highlights: [00:00] Quote of the Day by Ken Exner from Elastic[00:51] Ken's origin story: database programmer to Amazon[02:07] What attracted Ken to Elastic[02:51] Lessons from building resilient systems at AWS[04:34] How Elastic evolved from search to AI infrastructure[07:06] Elastic today: context engineering, observability, security[09:42] Why observability will be fundamentally transformed by AI[10:48] How early vector search prepared Elastic for GenAI[12:53] Context engineering: ingestion, retrieval, evaluation[15:39] The 10-year head start over purpose-built competitors[20:57] A developer's day is now all context engineering[24:16] Elastic as the bridge between enterprise data and LLMs[26:13] Agent Builder capabilities for customers[28:09] Data, tools, and context in the Elastic framework[29:39] Elastic on battleships and a Mars rover[31:00] The disorienting acceleration of AI coding models[32:07] Developers will be managers of agents[34:00] Authentication and identity for autonomous agents[35:30] Great in five years: the foundational AI layer[36:14] Disrupting observability and security from within[36:36] ClosingProfile: Ken Exner, Chief Product Officer, ElasticLinkedIn: https://www.linkedin.com/in/ken-exner-b914542/Podcast Information: Bernard Leong hosts and produces the show. The proper credits for the intro and end music are "Energetic Sports Drive." G. Thomas Craig mixed and edited the episode in both video and audio format.

How does artificial intelligence become more sustainable? Richard chats with Darshna Shah about her experiences as Chief AI Officer at Elastic. Darshna discusses the resources required to run large language model experiments, the pressure this has put on the electrical grid, and more. The conversation turns to efficiency - and the idea that there is little incentive in the current land grab around LLMs to be more efficient - that the focus is on growing quickly. But as technologies mature, efficiency becomes a key competitive advantage!LinksRDeepEvalAzure AI Evaluation SDKGitHub Green Software FoundationRecorded January 29, 2026

In this special podcast series, we speak to the winners of the WTiN Innovate Textile Awards 2025.World Textile Information Network (WTiN) is thrilled to announce the winners of the Innovate Textile Awards 2025. In this special podcast series we speak with the winners of the awards about the challenges, possibilities and successes of innovation within the textile industry.In this final episode of the series we are joined by our Innovation of the Year winner – Yulex. The WTiN Innovation of the Year Award honours the industry's most groundbreaking developments. It recognises advancements that push boundaries and set new standards.In this episode Yulex's CEO Liz Bui speaks to us about the company's award-winning innovation Yulastic - a biobased elastic to replace spandex. Launched in 2025, Yulastic is a fine, natural rubber filament harvested from the Hevea brasiliensis tree. It is fully renewable, responsibly sourced and as Bui explains hopes to become the ‘go-to stretch fibre for brands looking to reduce their reliance on synthetic materials. Bui speaks about the advancement of Yulastic and how Yulex has grown its product offering in recent years. She speaks about the need for the textile industry to look towards biobased alternatives to synthetic fibres and how innovators can help brands and manufacturers adopt these alternatives.She also touches upon adoption throughout the supply chain and how Yulex designs products with existing production machinery in mind.You can learn more about Yulex at  yulex.com.WTiN announced the winners in a virtual ceremony on 5 December 2025, which you can now watch on demand atWTiN.com.

In dieser Folge spricht Markus mit Katrin Freihofner, Co-Founder von Straion, einer Plattform für AI Code Governance.Straion adressiert ein Problem, das viele Unternehmen gerade erst erkennen: AI kann zwar Code generieren, kennt aber keine firmenspezifischen Regeln, Sicherheitsanforderungen oder Architektur-Standards. Straion sorgt dafür, dass AI-generierter Code automatisch mit den internen Richtlinien eines Unternehmens abgeglichen wird und wirklich production-ready ist.Katrin erzählt von ihrem Weg vom Product Design bei Dynatrace und Elastic zur Startup-Gründerin – und wie aus einem Side-Project ein VC-finanziertes AI-Startup wurde.Wir sprechen darüber, wie Straion Enterprise-Kunden gewinnen will, warum Sicherheit und Zertifizierungen für junge Startups eine große Herausforderung sein können und wie AI den Arbeitsalltag von Gründer:innen verändert.Außerdem geht es um:wie Straion AI-generierten Code mit firmenspezifischen Regeln und Guidelines verbindetwarum große Softwareteams hunderte Coding-Standards verwalten müssenwarum Enterprise-Kunden für Startups besonders schwer zu gewinnen sindKatrins wichtigste Founder-Learnings: Fokus behalten und Prioritäten setzenwarum AI zwar produktiver macht, aber Arbeit gleichzeitig intensiver werden kannProduction: Hanna Moser Musik (Intro/Outro): www.sebastianegger.com

Powerful men need to honor both polarities within themselves. Men disconnected from their feminine side become rigid, cold, ineffective.The most powerful man is least likely to get into physical altercation—people unconsciously feel he's a menace if tested. Doctor stuck probe in man's calf, found pinched nerve in spine. Everything's interconnected. Trees bend with wind gust or they don't stand. Bend don't break defense. Surfing—you're not commanding the wave, you're working in tune with nature. There's no strength without flexibility. They go hand in hand.The feminine gives space, masculine uses space. Elastic band: pull too far it snaps, let it come back gently. Architecture can be integration of balance.Listen if you're ready to feel your emotions, trust your intuition, honor your sensitivity—then use masculine structure to build something the world has never seen. You become more powerful by integrating it.

Hillary Brenhouse is editor-in-chief and publisher of Elastic magazine, and Meara Sharma is senior editor, and in this conversation they describe their new approach to psychedelic art and writing. Playing with time and space, and dissolving the conventional lines between genres, they have produced a magazine of, "the ordinary, only slightly, weirdly, off".

Subscribe to our Newsletter:https://theultimatepartner.com/ebook-subscribe/Check Out UPX:https://theultimatepartner.com/experience/ The Shift from Attention to Trust In this compelling episode, Ashleigh Vogstad, CEO of Transcends, joins Vince Menzione to discuss the tectonic shifts occurring in the global partner ecosystem. Ashleigh shares her firsthand experiences studying AI at Oxford, the rise of the “Trust Economy,” and the controversial Amazon vs. Perplexity lawsuit. They dive deep into the practicalities of becoming a “Frontier Firm,” the importance of building proprietary AI agents, and the ways Gen Z and AI-driven marketplaces are revolutionizing the buyer journey. Whether you are looking to win Microsoft Partner of the Year or navigate the demise of traditional SaaS, this conversation provides a strategic roadmap for leading through the AI revolution. Key Takeaways The economy is shifting from a focus on human attention to a foundation of verified trust. Future commerce will involve “selling to machines” as AI agents begin making purchasing decisions on behalf of humans. Microsoft is prioritizing “Frontier Firms” that integrate AI into every customer interaction and internal process. Gen Z buyers are prioritizing product value and “dupes” over traditional brand names, with 75% of buyers expected to be Gen Z by 2030. To win Partner of the Year, organizations must publicly celebrate “better together” stories with validated customer wins. Modern leaders should transition from a “growth mindset” to a “frontier mindset” to keep pace with rapid technological change. https://youtu.be/xJmd43NvfnI If you're ready to lead through change, elevate your business, and achieve extraordinary outcomes through the power of partnership—this is your community. At Ultimate Partner® we want leaders like you to join us in the Ultimate Partner Experience – where transformation begins. Key Tags Trust Economy, Selling to Machines, Amazon vs Perplexity Lawsuit, Frontier Firm, AI Agents, Copilot Studio, Anthropic Claude, Microsoft Partner of the Year, B2B Marketplaces, Gen Z Buyer Behavior, Digital Freedom, AI Therapy, Ray Kurzweil Singularity, Substack Growth, Co-selling Partnerships, MCI Funding, Azure Accelerate, Agentic AI, Transcending Tech, Ashleigh Vogstad. Transcript Asleigh Vogstad Audio Podcast [00:00:00] Ashleigh Vogstad: The attention economy is about selling to human beings. Now, if you look at something like the Amazon versus Perplexity lawsuit, the whole underlying premise is around the shift of no longer selling to humans directly, but of selling to machines. [00:00:19] Vince Menzione: We just finished Ultimate Partners Winter Retreat here in beautiful Boca to a sold out crowd. Today I’m joined by Ashley Waad. The CEO of transcends for this compelling discussion. Ash, welcome back to the podcasts. [00:00:34] Ashleigh Vogstad: It’s so good to be here, Vince. Thank you. Uh, [00:00:37] Vince Menzione: so well, we’re back in Boca again and we were just here yesterday for the Ultimate Partner Executive Winter Retreat in person. [00:00:44] Vince Menzione: What a great event we had together. [00:00:46] Ashleigh Vogstad: It was phenomenal. Thank you so much for having us there and on stage and, and genuinely the community is like a family, so seeing so many familiar faces and spending some quality time was just great. [00:00:57] Vince Menzione: It has really, truly become like family. It really, I’m, I’m, I’m having so much fun with this and getting to watch. [00:01:04] Vince Menzione: Not just our business grow and our community grow, but to see all of our friends and, uh, organizations like Transcends that have been with us since the beginning, since the very first ultimate partner acting even before the first ultimate partner. And, uh. We were just talking about. I’d love to catch up with what you’ve been doing. [00:01:22] Vince Menzione: Like you just came, you’ve been on a whirlwind. I mean, you’re always, every time like it’s, where’s Ash? She’s, uh, she’s on a plane again, or she’s on, she’s on the slopes. But tell us where you were just this week. [00:01:34] Ashleigh Vogstad: Yeah. The week started in a snowstorm, actually transporting myself from Whistler. I didn’t know if I would make it to the airport, but then down to Silicon Valley and [00:01:45] Vince Menzione: Nice. [00:01:46] Ashleigh Vogstad: Wow, that place is just inspiring and eyeopening. I mean, seeing the Nvidia campus, a MD, it’s really just other worldly and it had me reflecting on, it’s [00:02:00] Vince Menzione: not Whistler. Yeah, it’s [00:02:02] Ashleigh Vogstad: definitely not Whistler. Definitely not Whistler [00:02:05] Vince Menzione: about, [00:02:06] Ashleigh Vogstad: um, yeah, it just had me reflecting on being down there. I used to spend a lot of time in the Valley around 2017 and. [00:02:13] Ashleigh Vogstad: In this theme of AI and kind of what’s really coming, I was, I was thinking about, I had met this woman, Julia Moss Bridge, who’s a neuroscientist studying ai. She had a project called Loving Ai, and I was down there when they had borrowed Sophia, this humanoid robot from S and Robotics. [00:02:32] Vince Menzione: Oh yes. Yes. [00:02:33] Ashleigh Vogstad: Really interesting. [00:02:34] Ashleigh Vogstad: Sophia’s actually a citizen of Saudi. Mm-hmm. First, first robot to actually be made citizen of a country. So they had Sophia set up and the part that was just mind boggling at the time was that Sophia was hosting in real life therapy sessions with actual human beings sitting across the table. And what really struck me as. [00:02:59] Ashleigh Vogstad: Kind of just, you know, that was only eight, nine years ago. And that was esoteric. Wacky and [00:03:05] Vince Menzione: eerie. [00:03:05] Ashleigh Vogstad: Weird. [00:03:05] Vince Menzione: Eerie at the time. [00:03:06] Ashleigh Vogstad: Incredibly eerie. Yeah. I mean, a, a human getting, uh, you know, therapy sessions from a robot sitting across the table. Yeah. And it just had me thinking how far we’ve come today. In 2025, Harvard Business Review said that therapy is actually the number one use case for ai. [00:03:26] Vince Menzione: I’ve heard that. That is striking. I go back to COVID. We were having this conversation last night at at the dinner for the Ultimate Partner event, and I think that COVID allowed us to transcend, [00:03:42] Ashleigh Vogstad: mm-hmm. [00:03:42] Vince Menzione: No pun intended there, but actually accelerate where we are today, that the acceptance of AI and the acceleration, or the ability to accept change so quickly. [00:03:56] Vince Menzione: Started with COVID because we were so, so we were forced on whatever it was, March 10th I think, here in the United States to shut down everything and move to this remote life. [00:04:08] Ashleigh Vogstad: Mm-hmm. [00:04:09] Vince Menzione: And I think we’ve been shocked by that. I think our systems have all been shocked by that. And then here comes chat GBT in November of 2022 and we’re like. [00:04:20] Vince Menzione: Shocked in some respects, but like really everyone has embraced it in such a strong way, and now we’re getting. It’s almost daily update. You know, we’re gonna talk, I know we’re gonna talk about Anthropic and some of the things that’s been happening just in this last month that are striking and changing that have a lot of organizations trying to navigate, which is what, you know, you, you help organizations do. [00:04:43] Vince Menzione: But it feels like this is happening so fast and will continue to happen so fast. And as I said yesterday, I don’t know what this world’s gonna look like by 2030. [00:04:53] Ashleigh Vogstad: You know, and I think the thing is, is that nobody knows what the world is gonna look like in 2030. I’ve been reading Ray Kurz Well’s, the Singularity is nearer, so the original book, the Singularity is near and he’s known to be a very accurate predictionist on the future. [00:05:11] Ashleigh Vogstad: Yeah. But even with someone like that, you know, there, there nobody really knows what the world is gonna look like. And when you talk about COVID. At transcends, we have a value of digital freedom. So I founded the business in 2018, which was pre COVID. I as a fully remote organization, and at the time that was, you know, more groundbreaking, but then very quickly with CI that, that became the so-called new normal. [00:05:37] Ashleigh Vogstad: But we’re always thinking about. You know, remote first doesn’t mean remote only, and I think in this tide of what you’ve talked about, technological change being more acceptable and the pace of change. One of the interesting things that we see as a go-to-market agency is that in-person events are increasing. [00:05:56] Vince Menzione: Yes. [00:05:57] Ashleigh Vogstad: People want and crave the face-to-face. Just like with the ultimate partner series. [00:06:02] Vince Menzione: I felt it. So it was striking yesterday. It, it seems like it’s, again, this was event number nine for us, but to see the, um, uh, receptiveness isn’t the right term, but it was this, uh, people, the, the embracing. Of seeing each other and hugging each other and being in the same room with each other. [00:06:22] Vince Menzione: And even people that didn’t know each other, like by the, the, as the day evolved, this, uh, connection that they all seemed to have with one another during the sessions and participating, everyone actively participated in the sessions. And, um, I said this in the beginning, we’re not a Slack channel and we’re not like some post on LinkedIn. [00:06:43] Vince Menzione: Uh, we’re there, there’s no playbook that’s set today around partnerships or even go to markets and marketing that we could espouse and say, this is the playbook for the next year. Right. It’s, it’s changing so rapidly. [00:06:55] Ashleigh Vogstad: So rapidly, [00:06:57] Vince Menzione: and you’ve embraced it. And I, and what we’re gonna talk about right now, I mean, I, I, you know, you’ve embraced AI in such a strong way. [00:07:04] Vince Menzione: Um, personally and with your business, I want to, I wanna dive in here a little bit. First of all, a couple things For those of those who are listening who don’t know you, I think maybe just a moment about transcends and your role, and then I wanna dive in on how you’re thinking about ai because I know you’re doing some things personally. [00:07:22] Vince Menzione: I want you to share that with, with our listeners and viewers today. [00:07:25] Ashleigh Vogstad: Yeah, great. And I just wanna comment that it was a cool moment yesterday being up on stage with yourself and Mark Monday from ServiceNow and having the audience so engaged and active and Nina Harding from Microsoft stepping up and entering the conversation. [00:07:40] Vince Menzione: So cool. [00:07:41] Ashleigh Vogstad: It just made for such a collaborative experience, which was a cool moment, but yeah. Um, so. I founded this business, transcends a go-to-market agency after being at Microsoft myself. And really our differentiation is deep strategic partnerships with hyperscalers, whether that’s AWS, Google, Microsoft, and you know, that. [00:08:03] Ashleigh Vogstad: It comes with a challenge to be on the leading edge of technology. [00:08:08] Vince Menzione: Yes, [00:08:09] Ashleigh Vogstad: it, it’s really an imperative for our business and we are an AI first firm. Microsoft talks a lot about Frontier Firm, and I’ll take a, a different kind of angle on it. You know, when I think about Frontier. I now think about it as instead of the growth mindset, I now think about a frontier mindset. [00:08:28] Vince Menzione: Frontier mindset. You have to change my principles. [00:08:32] Ashleigh Vogstad: You know, maybe, like you said, the world is changing so rapidly. Yeah, it’s [00:08:36] Vince Menzione: changing rapidly. [00:08:36] Ashleigh Vogstad: And what a frontier mindset means is that as we’re approaching work for our clients, we are thinking about AI innovation in every single customer. Interaction, customer innovation. [00:08:49] Ashleigh Vogstad: So today we’re building AI agents into much of the work that we’re delivering for clients. And as a business owner and leader, I’ve been challenged to also think critically around how I’m choosing to run the company. And right now we’re going through a huge overhaul of where we have data sitting in silos and different applications. [00:09:09] Ashleigh Vogstad: Yep. And getting that into one place with one view so we can start layering on more insight. AI innovation. [00:09:17] Vince Menzione: Yeah. And data’s such an critical part, part of this, as we, we talked about yesterday. But you know, even the, what you said, which is, would, would’ve been striking a year ago to say, we’re an AI first, uh, agency isn’t as striking anymore. [00:09:32] Vince Menzione: Uh, we heard Nina when we were having this conversation on stage yesterday, say that it’s an imperative at Microsoft that the agencies that they choose to work with, the third party vendors that they work with have to be an AI first organization. I have to be a frontier firm, and so I’m a, I am sensitive to the word frontier firm. [00:09:53] Vince Menzione: I understand why Microsoft uses it and I understand the value of what we used to call, you know, customer zero or back in the day we used to say eating your own dog food, but essentially being an organization that has leaned in, in a way, and with ai. Even more so, so important to do it. So tell us, I know you’ve done some things personally as well, but tell, tell us what you’ve done with the organization. [00:10:18] Vince Menzione: Uh, you talked about data and making data available and having, having a true data state as opposed to silos of data, but then you also made some personal investments and sacrifices. I would say. [00:10:30] Ashleigh Vogstad: Yeah. [00:10:30] Vince Menzione: Yeah. In terms of what you’re doing around ai, [00:10:32] Ashleigh Vogstad: so I mean, let’s start on the personal side. I’m the CEO of my organization, and you can read in books or news articles that it is critical for AI transformation to start at the C-suite and specifically in the CEO seat. [00:10:46] Vince Menzione: Yes. [00:10:46] Ashleigh Vogstad: And that really. Landed for me and so I’m personally leading in About two weeks ago, I built an agent, just end-to-end on my own, got into copilot studio. Wow. Got comfortable with the interface. You know, I was clunky moving around in there at first, chose my model. You know, I went with one of the anthropic Claude models for this particular project and built up an agent that can deliver executive communications like. [00:11:14] Ashleigh Vogstad: Thought leadership blogs, uh, LinkedIn posts, but in a particular human being’s voice by ingesting things like their social profiles, their SharePoint sites, where they live and work. And it has been so surprising doing an ab test between just what a chat GBT or a copilot could produce. [00:11:32] Yeah. [00:11:33] Ashleigh Vogstad: In comparison with the authenticity of the voice coming from the agent. [00:11:37] Ashleigh Vogstad: Uh, it was just a really cool experience to roll up the sleeves and get in there. But also I think the, the investment that you’re referring to is, I made a big decision to return to school and uh, got accepted to go to Oxford. [00:11:52] Vince Menzione: Wow. [00:11:52] Ashleigh Vogstad: And I’m studying artificial intelligence there. [00:11:54] Vince Menzione: That is incredible. That is incredible. [00:11:57] Vince Menzione: Oxford, uh, we’ve heard of that school before here in the United States. [00:12:03] Ashleigh Vogstad: You know, it’s been a really great experience. It’s in person, so I’m traveling there about every 60 to 90 days and living on campus. I mean, really, Oxford isn’t. Formally a campus, it’s sort of a, a city and a university all, all ruled into one and the experience has been really powerful. [00:12:21] Ashleigh Vogstad: Yes. One of the things I wanted to get outta the program was a more global perspective, and it’s been fascinating to me that about half the faculty so far, or or professors, guest lecturers that have been coming into the program have been from China or very direct experience working in the Chinese market. [00:12:38] Vince Menzione: That is fascinating. [00:12:39] Ashleigh Vogstad: It’s been a completely different view. Or for example, you know, really digging into some of the legal cases that are driving precedence for how AI is interacting with corporations. [00:12:51] Vince Menzione: Mm. [00:12:51] Ashleigh Vogstad: One of the big ones for me has been looking at Amazon versus p perplexity. This is still a live case that’s happening right now. [00:12:58] Ashleigh Vogstad: And you know, I think it was Forbes magazine that the headline was the End of Commerce for this case because it’s really about. How human beings are being replaced with machines and hearing some of the world’s leading thinkers, leading AI researchers on these topics has just been really expansive. [00:13:19] Vince Menzione: It’s fascinating. [00:13:20] Vince Menzione: I mean, it’s, this started a couple years ago with, uh, Hollywood, in fact. Suing the industry or suing the technology companies with regards to, uh, employment, right? Mm-hmm. About the, the, uh, copyright infringement and what’s gonna happen in the entertainment industry. And I think that was just a one very small example. [00:13:40] Ashleigh Vogstad: You know, voice people think about DeepFakes. Yeah. And they think about video, but actually voice is a big issue. And you look at the, um, you know, the what happened between Scarlett Johansson and her voice in her, and then open AI rolling out a voice that sounded identical. Sounds like her. [00:13:59] Vince Menzione: Yeah. [00:13:59] Ashleigh Vogstad: To Scarlett Johansen and, and where that went. [00:14:01] Ashleigh Vogstad: It’s, it, this is a new ground for, for everybody that we’re going through right now. [00:14:07] Vince Menzione: It is. We can dive and go in so many different directions, but let’s talk about marketing and advertising since that’s kind of. Transcends core, and a lot of the people that watch and listen to us are in the partnership world. [00:14:22] Vince Menzione: They’re leading organizations, they own organizations, the the chief executives or CVPs of organizations. Let’s talk about advertising and where that’s going. [00:14:32] Ashleigh Vogstad: Yeah, great. [00:14:33] Vince Menzione: Yeah, [00:14:33] Ashleigh Vogstad: I mean, uh, I love Marshall McCluen. He’s a Canadian theor, uh, media theorist, and in 1964, he very famously said, the medium is the message. [00:14:43] Ashleigh Vogstad: And what that really means when you peel back the layers is that every type of communication medium has these inherent biases. And I think what we’re experiencing right now is this new medium of artificial intelligence, and I’m really interested in exploring what that means for the media world. So. If I gonna take you back to 1997, there’s this really famous, the Innovator’s Dilemma. [00:15:10] Ashleigh Vogstad: Yes. Kind of a classic business 1 0 1 type book by Clayton Christensen. Yes. And he talks about this theory of disruption where new technologies, emerging technologies start at the low end of the market. They gain this momentum and they eventually displace incumbents. And you know, sometimes seemingly out of nowhere. [00:15:28] Vince Menzione: Yeah. And Microsoft was a good example of this at that time. [00:15:32] Ashleigh Vogstad: Def, [00:15:32] Vince Menzione: yeah. [00:15:33] Ashleigh Vogstad: All the big players. All the big players. I mean, Google go for search as well, right? So that’s one of the classic examples. And so. If we look at storytelling technology, you have things like chat, GBT and Sora entering the scene. And in the beginning, you know, they’re producing a shitty first draft. [00:15:51] Ashleigh Vogstad: Uh, you know, it’s things like post-apocalyptic dogs with five finger human beings. Yeah. Things like this. But, you know, and they really lacked emotional resonance. But as we all know. That’s not the case anymore. No, it’s [00:16:05] Vince Menzione: not. [00:16:06] Ashleigh Vogstad: AI is increasingly producing content that is very powerful and is starting to resonate with people. [00:16:13] Ashleigh Vogstad: You know, I’m definitely not a neuroscientist, but if we, we look into the neuroscience, it’s your cortical sal circuit that. Kind of is responsible for pattern recognition and it compares what you’re seeing in the real world with what you expect to see. So when you take this into a space of advertising, you know, if there’s an ad that is AI generated, that is just weird and kind of. [00:16:38] Ashleigh Vogstad: Tweaking for you. [00:16:39] Vince Menzione: Like that robot we were talking about earlier, [00:16:41] Ashleigh Vogstad: like the robot we were Exactly, yeah. Like Sophia, you enter what psychologists call the uncanny valley, so it’s like what you’re looking at isn’t exactly what you’re expecting to see and the Spidey sense is, is tweaking. You know, that’s a low place of emotional resonance. [00:16:58] Ashleigh Vogstad: This world is changing really, really quickly and we’re seeing AI generated media make huge impacts in the market Now, tools like Luma Dream Machine, I mean, it’s incredible what they can achieve today. [00:17:11] Vince Menzione: It’s fascinating. We see it in, you know, I spend a lot of time on LinkedIn. That’s sort of the world of our business community, and you can very easily detect when someone is doing a post. [00:17:22] Vince Menzione: Or they’re writing an art, whatever they’re doing. Right. Some type of draft of something. Uh, and you can tell when it’s ai, I mean, it’s so easy to tell, and even people are generating reports and claiming that their research papers or studies or whatever they call them, uh, and it’s AI generated and it’s just the authenticity isn’t there. [00:17:39] Vince Menzione: The, the sense that this is real. That it can be trusted is not there. And I think trust is what we’re talking about here too, as well. [00:17:47] Ashleigh Vogstad: Yeah. I mean, let’s go to authenticity ’cause that’s super important. Yeah. And I know a lot of your listeners, you come from the hyperscaler world of partnerships. You need to have that differentiated, better together story. [00:17:59] Ashleigh Vogstad: Yeah. It’s really important to have an authentic voice in market. And I think about that also in terms of platforms and channels. We’re seeing a decrease in certain major social media platforms, and yet Substack spiked 48% in monthly active users last month. [00:18:15] Vince Menzione: That’s [00:18:16] fascinating. [00:18:16] Ashleigh Vogstad: Um, you know, and I think that one of the reasons is it’s viewed as a more authentic channel where you’re getting thought leadership from people that you’re, you know, genuinely interested in hearing their, their points of view. [00:18:28] Ashleigh Vogstad: And I think that’s really an important piece in here. [00:18:31] Vince Menzione: Yeah, you mentioned this yesterday and you had me thinking about it as well because we have used LinkedIn for everything internally, our newsletter, which has been around for six or seven years now. But that Substack is really, and I go to Substack too, to, if I really wanna dig in on a topic. [00:18:47] Ashleigh Vogstad: Mm. [00:18:47] Vince Menzione: And there’s a particular author that I like their point of view, I’ll follow, I’ll follow them on Substack. [00:18:53] Ashleigh Vogstad: Yeah. I mean, and this comes, maybe brings us around to who is the buyer and who is the audience, and who do we need to be thinking about when we’re designing sales and marketing programs. And really we’re, we’re shifting into the place of the Gen Z buyer by 20 30, 70 5% of buyers are gonna be Gen Z. [00:19:12] Ashleigh Vogstad: They’re gonna control 12 trillion in. Spend [00:19:16] Vince Menzione: by 2030. ’cause we, we’ve been, we’ve been saying that the millennial is the new buyer the last three years. I think Jay said it right here at this stage. [00:19:23] Ashleigh Vogstad: Mm. [00:19:24] Vince Menzione: Um, so now it’s Gen Z. [00:19:27] Ashleigh Vogstad: And they’re buying online. Yeah, they’re buying in marketplaces. Yeah. So a stat recently was that roughly half of them made purchases on the social platforms of YouTube, Instagram, or TikTok in the last month. [00:19:39] Ashleigh Vogstad: I mean, that buyer behavior of being inside. Social type application and directly making a purchase. And I think in the B2B world, we need to take lessons from here and start thinking more front and center than we even have been around marketplaces. I mean, part of my reason for being in Silicon Valley this week was to celebrate a $12 million transaction that happened via Marketplace and two years ago that would’ve been a huge deal. [00:20:06] Ashleigh Vogstad: Huge, [00:20:07] Vince Menzione: huge. [00:20:07] Ashleigh Vogstad: And, and it still is a really big deal, but these things are becoming. More and more common experiences. Very much so. We need to be there and in that conversation. [00:20:16] Vince Menzione: So how are you thinking about it? How are you directing your clients to behave or act around it? What are you, what are you doing exactly that we could take to this community perhaps and share with them. [00:20:28] Ashleigh Vogstad: I’ll bring it back to the authenticity piece because you need to have a product that delivers value first and foremost. There is, there is no substitution for that. Yeah, and what I would say is. One of my professors at Oxford, Eric Zow, he has this theory that I’m really digging into and finding very fascinating, which is that for the last several decades we’ve been in the attention economy, and that’s shifting to the trust economy. [00:20:55] Ashleigh Vogstad: Now the attention economy is about selling to human beings. Yeah. It’s about the, the business model is essentially that you need human being eyeballs on lists of recommendation links. Yeah. Whether that’s from Google or from, you know, searching, shopping on Amazon, you get this list of recommendation links and the economic engine that drives that business model is advertising. [00:21:19] Ashleigh Vogstad: Now, if you look at something like the Amazon versus Perplexity lawsuit, the whole underlying premise is around the shift of no longer selling to humans directly, but of selling to machines, or in other words, agents who are making purchases, s on behalf on your behalf. And an agent isn’t going to be razzle dazzled by some inauthentic story. [00:21:44] Vince Menzione: Yeah. [00:21:44] Ashleigh Vogstad: They’re gonna be looking for third party validation on Exactly. You know, they need to be sure that they’re making the right decision. [00:21:51] Vince Menzione: They’re gonna look at surveys, they’re gonna look at customer comments. Like if I went through my Amazon site and I was looking to see what people said about the purchase or the product and specifically Exactly. [00:22:01] Vince Menzione: The agent’s gonna do this on my behalf, is what you’re saying. [00:22:04] Ashleigh Vogstad: This is what I’m saying. Yeah. And, and. I believe that to layer on top of, you know, Eric Z’s philosophy, I’ve been thinking about this in terms of the hyperscaler world, and I think that this is the time to lean into co-selling partnerships. [00:22:18] Ashleigh Vogstad: Yeah, because being third party validated by somebody like AWS Microsoft and having all that co-sell data, what are your recent wins? Yes, that’s really high integrity, trusted data source for an agent to make a purchasing decision, and marketplaces are a key part of that. [00:22:35] Vince Menzione: So we’ll move from AI will take a, a more active role in the marketplace. [00:22:40] Ashleigh Vogstad: I definitely believe so. [00:22:42] Vince Menzione: Which makes total sense. I, you know, we’ve been doing this for nine or 10 years now, and when I was at Microsoft, we started co-selling. In fact, it was, uh, Aaron Feiger was up on stage yesterday talking about it. Right? January of 2016, co-selling began. [00:22:55] Ashleigh Vogstad: Mm. [00:22:56] Vince Menzione: And there were only a few companies doing it. [00:22:59] Vince Menzione: Right. So she worked with one of the very first ones that were doing it. Uh, the challenge we have today is there are tens of thousands of partner organizations in the marketplace that are all trying to get the attention of the Microsoft sellers. Hmm. As, or the Google sellers or the AWS sellers and tell their story. [00:23:19] Vince Menzione: And a seller only has so many minutes in a day, they have a quota that they have to hit. These quotas are tens, if not hundreds of millions of dollars of annual quota of cloud consumption. And I wanna sell my $50,000 widget, whatever it is. Yeah. Right. And I, I don’t understand why I’m not getting a callback. [00:23:38] Vince Menzione: And this, this is the dilemma we’ve faced because of, because of this, uh, scarcity of time and this over overwhelming of tech, you know. Tech, tech buyers trying to make this all happen, so now the AI can come in and help me solve for it as a seller, right? [00:23:55] Ashleigh Vogstad: The AI is definitely acting as an interface to make recommendations to field sellers in different organizations and. [00:24:04] Ashleigh Vogstad: To, to kind of take this on a, a tangent. Dupes. So a dupe. I know people of my generation, we’d think about this like a knockoff Right. You know, a knockoff handbag. [00:24:15] Vince Menzione: Yep. [00:24:15] Ashleigh Vogstad: Dupes have exploded. [00:24:16] Vince Menzione: Fake. Fake Rolexes. [00:24:18] Ashleigh Vogstad: Exactly. The fake Rolex for sure. And I think it was in December, P WC rolled out a survey. 81% of Gen Z were planning to purchase a dupe this holiday season. [00:24:29] Vince Menzione: That’s wild. [00:24:30] Ashleigh Vogstad: Dupes can be, you know, we gave luxury, good examples, but Louis [00:24:34] Vince Menzione: Vuitton and yeah. So, [00:24:35] Ashleigh Vogstad: but furniture, these sorts of things. And the important takeaway here for tech is the same principle will land, is that people are looking for value out of a product, not necessarily a name brand. AI is accelerating this whole process, and agents are gonna be looking at the same thing. [00:24:56] Ashleigh Vogstad: They’re looking for that authenticity in terms of the actual product value. So, you know, beware there’s lots of disruption happening in the market right now with this dupe mentality, which is actually a cultural shift talking about I appreciate value over a superficial. Brand name. In some cases, there’s also a, a small contrary trend where certain luxury goods are rising because yes, things are never that simple. [00:25:22] Vince Menzione: So you work with a lot of these tech companies, a lot of SaaS companies, is we, we call them ISVs, we also call them, uh, software development companies. Now we keep changing these acronyms around. Uh, there’s been a lot of, uh, consternation in that segment, I would say, around ai. Right, because a lot of them are getting told that they’ll be outta business in a few years. [00:25:43] Vince Menzione: Mm-hmm. I think Satya Nadella famously said this last year that SAS will go away. Right? He’s predicting the demise. How do you help some of these organizations to differentiate? And there’s some of these are huge value organizations. We have have them in the room with us, ServiceNow and Veeam and Adobe. [00:26:01] Vince Menzione: Um, how do you help them achieve their results? ’cause that’s what you, you know, your organization is really helping these organizations to achieve their pinnacle as a partner. What do you, what do you say to them now and how do you help them through this time? [00:26:16] Ashleigh Vogstad: I’m on the side of the fence that I really can’t see an organization ripping out something like Salesforce, Adobe, ServiceNow. [00:26:24] Vince Menzione: Agreed. [00:26:24] Ashleigh Vogstad: I mean that the amount of change management and. The extent to which these, these platforms are embedded, actually running and operating organizations. I personally, if, if we’re calling those companies, SaaS companies, I don’t agree that that layer is gonna go away. I mean, we’re seeing these organizations lean into AI in a huge way to borrow Microsofts. [00:26:50] Ashleigh Vogstad: Term, you know, they’re all becoming frontier firms. [00:26:54] Vince Menzione: Yes. [00:26:54] Ashleigh Vogstad: So where I would go to, to answer that question, we do work with many, you know, organizations on that caliber, on things like their marketplace strategy on how to light up the fields of different hyperscalers. It really does come down to things like having a strong drumbeat with the Microsoft field, celebrating your win stories. [00:27:15] Ashleigh Vogstad: Maybe that’s where I’ll land as Please do the marketer, because it sounds so simple, and I don’t know why we kind of continue to come back to this, but we’re talking about that third party validation and really, um, in order to have that, like what the hyperscalers want is you jointly celebrating success. [00:27:36] Ashleigh Vogstad: Here’s the kicker. Publicly. [00:27:38] Vince Menzione: Publicly, [00:27:39] Ashleigh Vogstad: you know, you need a customer story on your website, a press release that contains a quote from your customer. Ideally, also a quote from an executive at one of the hyperscalers. Like, actually lean in to live the value of your better together story. And when you do that, when you, when it comes around to partner of the year time, and we talk to you about, okay, what client stories are we gonna feature? [00:28:03] Ashleigh Vogstad: We’re even gonna know because when we Google you, we can see the public press of the joint wins that you’ve been celebrating. And I can tell you that that is a huge indicator on whether or not you’re well-placed to be in the 4% of partners who actually win Partner of the Year award’s. [00:28:20] Vince Menzione: Fascinating to me. [00:28:21] Vince Menzione: ’cause to me it would feel like table stakes maybe ’cause where we sit is ultimate partner and where this room sits with all the top partners that I just assume that everybody follows that. That, that guidance. [00:28:34] Ashleigh Vogstad: Mm. [00:28:34] Vince Menzione: And so this is really impactful and I want to get here because I know you spent a lot of time here and we’ve talked about it before, but I think the partner of the year awards, when we first met many years ago, that was a you, you’ve expanded the business, but that’s still a core mission and and value that you bring to the community and to the partner ecosystem is helping them through this process. [00:28:55] Vince Menzione: So I know that that’s gonna be coming up soon, so I thought maybe we’d spend a couple moments on that. [00:29:00] Ashleigh Vogstad: Partner of the Year awards, regardless of which partner, I mean, Salesforce has their own awards there. There’s more and more award programs coming out, and they’re a great way to celebrate the incredible work that your organization has done. [00:29:13] Ashleigh Vogstad: Jay McBain is brilliant on this. He’ll talk a lot about the increase in valuation. Yeah. The, the increase in stock valuation or the likelihood that if you’re looking to be acquired, that you’re acquired within 12 months of a partner of the year win it. It’s really impressive. There is strong business value there. [00:29:33] Vince Menzione: He like, he likes, he likes to tell the story of that when the award is handed to them and they go back into the audience, that the private equity people are all over them right then and there and making offers. I mean, that’s the visual that you get [00:29:47] Ashleigh Vogstad: and it’s very powerful. Yeah. Very powerful. It’s very powerful and it, it can make it worthwhile to invest in the process, but don’t invest in the process if you haven’t been investing in the process for the 12 months. [00:29:57] Ashleigh Vogstad: Prior, [00:29:58] Vince Menzione: exactly. [00:29:58] Ashleigh Vogstad: The Microsoft field or you we’re talking about Microsoft Partner of the Year Awards. They need to know about your win that that needs to be top of mind for them. Yeah. How much Azure revenue is it driving? Was it a huge marketplace? Build sales and. You know, one of the questions I get asked a ton, everybody wants to know how do we get money out of the hyperscalers? [00:30:20] Ashleigh Vogstad: How do I get access to marketing development funds or all these different programs? Yeah. You know, at Microsoft, some of these programs are like EI and customer investment funds or Azure Accelerate, you know, and there’s millions and millions and millions of dollars in these, these buckets of funds, but. [00:30:36] Ashleigh Vogstad: An interesting point of view is that it’s actually a scorecard metric for many people at Microsoft who have partnership roles for you to be drawing down those funds. [00:30:45] Vince Menzione: Yes. [00:30:45] Ashleigh Vogstad: You know, your interests are actually aligned here, and so again, when it comes to Partner of the Year awards, how much money have you pulled down? [00:30:54] Ashleigh Vogstad: How much have you been an activating partner of key Microsoft programs that they’re pushing? What are you doing with marketplace rewards? How are you resing? Those into your business. These are the types of things that you really wanna be thinking about. Sitting it. You know, this time of year we probably will get the awards were likely be due in July. [00:31:13] Ashleigh Vogstad: They haven’t officially announced timelines, but you’ve got a few months to start moving these pieces into place. [00:31:18] Vince Menzione: And there are quite a few of them. And to your point, Nina, when she was up on stage here yesterday, there were at least 10 or 12 award. Uh. Funding categories that were on her, that were on her slide. [00:31:31] Vince Menzione: Her partner, her partner slide. So, [00:31:33] Ashleigh Vogstad: and what great looks like for a partner is that you understand your end-to-end funnel as it is mapped to Microsoft’s SEM model, the Microsoft customer Engagement model. Mm-hmm. The first stage there, inspire and design. That’s really the marketing space of lead generation. [00:31:50] Ashleigh Vogstad: So how are you generating leads with webinars, in-person, event activations, digital campaigns, and then at the very end, in the fifth column, you have the Microsoft outcomes that you’re driving. Yes. Whether that’s Azure consumed revenue, marketplace build sales, co-pilot, monthly active usage, these sorts of things. [00:32:10] Ashleigh Vogstad: And in each of those SEM swim lanes. There’s Microsoft funding associated to it. And that’s one of the things that Nina Harding was showing yesterday. When and where does it make sense to make requests for EA funds versus Azure accelerate the MCI funding? There’s different workshop proof of concept funding, and those all fall at specific stages in that EM model. [00:32:33] Vince Menzione: And what you’re also pointing out in this conversation is that the co the partners need to understand that mm, they need to understand MM. We talked about it years ago. I’ve had, haven’t had anybody on stage recently talk about m You could probably take us through that if we wanted to devote some time here, uh, and then understand all of those categories and how to access those funds. [00:32:52] Ashleigh Vogstad: Yeah, it’s critical and. The number one place we point partners, if you want a quick overview of what that looks like is to Microsoft’s FY 26 solution playbooks. Nice. They’re available on the web for download. There’s, well, there used to be three, but they’ve added a few agen being, being one. So, so there’s a handful of, they had [00:33:11] Vince Menzione: simplified it, now they’re, now they’re expanding it back again. [00:33:14] Ashleigh Vogstad: Yeah, exactly. I think there’s now a breakout for security as well. Yes. So take a look at those playbooks. It will map programs and incentives very specifically to each solution area and to each sales play that are gonna be available to you. And then we’re always happy to guide people through the details [00:33:32] Vince Menzione: as well. [00:33:32] Vince Menzione: I love that. I love that. And reach out to the. Ashley is just amazing at this process. I’ve, I’ve watched her for years now, work with some of the top, what have become the pinnacle partners of Microsoft and with the award season coming up. So we wanna make sure we have a plug there. But I also wanna talk about like, podcasts with you. [00:33:50] Vince Menzione: Um, you’ve been on this podcast multiple times, been in the studio before doing this, and I understand you have your own podcast now. So tell us about that. [00:33:58] Ashleigh Vogstad: Yeah, Vince, I just wanna say. As a friend and a mentor. You’ve been so inspiring. Thank you. And I think from years ago when we met, there was this seed in my brain of, you know, I, I should really get out there. [00:34:13] Ashleigh Vogstad: And you talk a lot about growth mindset and fear setting is, is one of Tim Ferriss’s terms? Yes. And models. [00:34:21] Vince Menzione: I love Tim Ferris. I’ve been, been a fan of his for 10 years now. So that’s settled. We all got started with this. Sorry. Sorry, I [00:34:26] Ashleigh Vogstad: interrupt. No, no, not at all. [00:34:27] Vince Menzione: Yeah. [00:34:28] Ashleigh Vogstad: And. I think it’s just been, it’s been back there. [00:34:31] Ashleigh Vogstad: Yeah. That I’m really passionate around having voice is how I think about it. And as a marketing agency, we’re really amplifying the voice, um, or helping companies to find their voice, particularly in hyperscaler partnerships. And what better way to assist, you know, authentically the amazing people in our network, in our community and our clients than with our own channel where we can celebrate their stories and success? [00:35:00] Vince Menzione: Very cool. [00:35:01] Ashleigh Vogstad: So the podcast is called Transcending Tech. It’s about [00:35:06] Vince Menzione: very cool transcending tech. Just so you don’t [00:35:08] Ashleigh Vogstad: transcending tech. [00:35:08] Vince Menzione: It’s out there now. [00:35:10] Ashleigh Vogstad: It, we just released our first episode. Okay. I think two days ago. [00:35:13] Vince Menzione: So by the time we’re live, yes. We’ll, we’ll be able to access it. Good. [00:35:17] Ashleigh Vogstad: You will be able to access it. [00:35:18] Ashleigh Vogstad: The first episode is with Alyssa Fit. Patrick from Elastic. [00:35:21] Vince Menzione: Oh my goodness. [00:35:22] Ashleigh Vogstad: And the concept of the podcast, it’s long form and it’s really about getting to the people behind the platforms. [00:35:29] Vince Menzione: Very cool. [00:35:29] Ashleigh Vogstad: And to the stories that transcend technology. So we’re here to get to know the human beings behind. Agents. [00:35:38] Vince Menzione: Yeah. [00:35:38] Ashleigh Vogstad: And taking the time to, to go in deep and really explore that. [00:35:43] Vince Menzione: So I am excited to see all the developments here with the, with the podcast. And you’re gonna be joining us again. You were just here, you in Boca. But you’ll be joining us again in Bellevue. Not too far a little bit. Closer ride or travel, uh, for you to come to Bellevue. [00:35:57] Vince Menzione: We’re gonna be hosting the first ultimate partner live, which is our larger events in this beautiful facility, this new Intercontinental hotel, which is fabulous. And, uh, you’re gonna be taking a more active role. Your leadership around AI is. Palpable and we’re gonna love to have you on stage and talking through some of the changes. [00:36:17] Vince Menzione: I, I suspect by the time we get to Bellevue we’ll have a lot more to talk about. That hasn’t even happened yet. [00:36:23] Ashleigh Vogstad: Yeah, I’m really excited. I’ll have been through my next cohort at at Oxford, kind of coming out hot from there back to the Pacific Northwest, and really excited to just share the learnings and Awesome. [00:36:35] Ashleigh Vogstad: Genuinely. It’s also helping me in my own research, really formulate particularly around the role of ag agentic AI in hyperscaler partnerships. [00:36:43] Vince Menzione: That’s so cool. And then what I’ll say is this, and I don’t know, we on the space perspective, and I’ll, the team will probably hang me for this because we haven’t done it yet, but if you wanna bring the podcast along with you, there might be, we’ll see if we can find an extra room for you to set up. [00:36:58] Vince Menzione: If you wanna do some interviews while you’re. In, at the event. So [00:37:02] Ashleigh Vogstad: you’re so generous, Vince. [00:37:03] Vince Menzione: That’s [00:37:04] Ashleigh Vogstad: amazing. [00:37:04] Vince Menzione: Thank you. Again, I can’t say for certainty yet, but, uh, let’s see, let’s see what happens with that. So, uh, let, let’s, uh, you know, I always, we, we have known each other for years and I just assume everybody knows this amazing Ashley sda. [00:37:19] Vince Menzione: But, um, we always, I like to ask this question because it helps us kind of dig in a little bit about you personally. And it’s my favorite question. I ask all my guests this question now, and it’s, um, you’re hosting a dinner party, Ashley, you are, pick a pace, place, you wanna have this dinner. We could talk about parts of the world. [00:37:36] Vince Menzione: You’ve traveled all extensively. Uh, and you can invite any three people, guests from the present. Or the past to this amazing dinner party you’re throwing. Whom would you invite and why? [00:37:52] Ashleigh Vogstad: It’s a beautiful question, Vince and. Instantly I go to a place in terms of the location, since you asked that part, which was surprising. [00:38:01] Ashleigh Vogstad: I, I like that is my home. I, I love where I live up in Whistler, Canada and [00:38:08] Vince Menzione: I hear it’s beautiful. I haven’t been yet, [00:38:10] Ashleigh Vogstad: it’s so gorgeous and it’s, it’s my own sanctuary. You know, I live on a plane 75% of the time and coming back to that place is really grounding for me. Yes. So, so I would love to have it at, at my home and to invite. [00:38:24] Ashleigh Vogstad: Pippa Malrin would be one. She, Pippa [00:38:26] Vince Menzione: Malrin. [00:38:27] Ashleigh Vogstad: Yeah. She’s sure. I get an advisor to the White House for many administrations. Okay. She’s an economist and she just has really interesting perspective on geopolitics. Uh, I follow her on Substack ’cause she’s a big substack. Okay, now [00:38:41] Vince Menzione: I need to look. This is awesome. [00:38:42] Vince Menzione: The [00:38:43] Ashleigh Vogstad: mal, she’s fantastic. I would say Dr. Lisa Sue, the CEO, Dr. Lisa of a md. [00:38:49] Vince Menzione: Okay. Yes, yes. I know a little bit about her. [00:38:51] Ashleigh Vogstad: So she was one of Time Mag, I think she was the only woman in Time Magazine’s, group of people of the year, which was basically this AI cohort in including, you know, the Elon Musks of the world. [00:39:03] Ashleigh Vogstad: Uh, it’s just so impressive what she’s doing with leadership in a MD. I don’t think it’s as public as. Anybody else who is on the cover of that magazine, but it’s incredibly powerful. [00:39:14] Vince Menzione: Yeah, they’ve made a com uh, turnaround’s probably not the right word, but it seems like they’ve made a tremendous, uh, gains turnaround probably in the last few years. [00:39:23] Ashleigh Vogstad: I would say that many would say turnaround. And then lastly is Dr. Fefe Lee, who. For those in the AI space, particularly AI research space. I mean, she’s arguably number one. Um, she’s leading at Stanford currently. [00:39:37] Vince Menzione: Wow. This is gonna be a heady conversation, but you know, I love conversations. So if you don’t mind, maybe I’ll bring dessert and come, come in for a few moments, maybe do some podcast interviews there. [00:39:48] Vince Menzione: How’s that? [00:39:49] Ashleigh Vogstad: That sounds absolutely perfect, Vince, [00:39:50] Vince Menzione: so, so good. So good to have you here today. So great. Good to have you in the studio again, and, uh, excited for transcends and all the great work you’re doing. Um. This time with ai. I think you, uh, we talked about this a little bit last night. I think you’ve made some really wise, personal and professional decisions about how to lead and how to take this forward and not kind of rest on your laurels, which you see so many organizations do People fear change [00:40:17] Ashleigh Vogstad: Hmm. [00:40:18] Vince Menzione: And you embrace it, which is just, it’s astounding to me that you do that and, um. I look forward to working with you in the future and for years and years to come. So I will ask you one more question though, because we are still at the precipice of these tectonic shifts and we’re still early in 2026. And so for our listeners and our viewers today, what would be the one thing you would tell them that they need to go do now that possibly they haven’t done yet as they prepare for 2026 and beyond? [00:40:52] Ashleigh Vogstad: The generic phrase would be, be curious, but if we want an action, it would be go build an agent. [00:40:59] Vince Menzione: Go build an agent [00:41:00] Ashleigh Vogstad: if, if you haven’t already. Yeah. And, and I’m, yeah. Speaking hopefully to like a business audience, you know, to, to anyone. Yeah. Really, um, find something that is interesting that you’re passionate about. [00:41:12] Ashleigh Vogstad: A, a use case that it doesn’t have to be some big thing. It could be quite mundane, but just something that’s gonna help you in your role. It’s, you know, what is creativity is an interesting question, and I can tell you that sitting down and hands-on keys and actually creating something is, is a beautiful, powerful experience. [00:41:32] Vince Menzione: Yeah. Awesome. All right. We’re all gonna go create agents this weekend, so thank you for listening. Thank you for viewing the Ultimate Guide to partnering on our YouTube channel, ultimate Partner, and on each end of your platforms at the Ultimate Guide to partnering. Thank you for being with us and supporting us all these years. [00:41:50] Vince Menzione: Thank you. Don’t forget, ultimate Partner Live is coming soon, May 11th through the 13th in beautiful Bellevue, Washington. I hope to see you there.

Police Shot At and Investigating Violent Crime: The Truth. In today's nonstop Social Media environment, from Facebook, Instagram, and LinkedIn to YouTube, Apple, and Spotify podcasts, conversations about policing often focus on headlines rather than reality. Viral clips and breaking News stories frequently highlight moments when officers fire their weapons or when suspects are shot. Far less discussed, however, is a critical perspective: what happens psychologically and physically when police are shot at. The Podcast is available and shared for free on the Law Enforcement Talk Radio Show and Podcast website, also on Apple Podcasts, Spotify, YouTube and most major podcast platforms. That is exactly the conversation explored in this Podcast episode featuring retired Texas law enforcement leader Charles “Chuck” Andrews, a former chief of police who spent decades handling violent incidents, including shootings where victims were struck multiple times. The Law Enforcement Talk Radio Show and Podcast social media like their Facebook , Instagram , LinkedIn , Medium and other social media platforms. “The public often sees the final seconds,” Andrews explained. “They see the moment an officer fires. What they don't see is everything leading up to it, especially the reality of being shot at and having to make decisions in fractions of a second.” Supporting articles about this and much more from Law Enforcement Talk Radio Show and Podcast in platforms like Medium , Blogspot and Linkedin . The Reality Officers Face When Bullets Fly Discussions surrounding use of force typically center on policy, legality, and accountability. Andrews says those discussions are necessary, but incomplete. Police Shot At and Investigating Violent Crime: The Truth. “We talk a lot about when officers fire their weapons,” he said. “We also talk about when officers are shot and wounded. But rarely do people talk about what it's actually like when rounds are coming toward you.” According to Andrews, the experience is both physiological and psychological. Officers must process threat recognition, environmental awareness, and survival instincts simultaneously while protecting others nearby. Available for free on the Law Enforcement Talk Radio Show and Podcast website, also on Apple Podcasts, Spotify, Youtube and most major Podcast networks. “When you're being shot at, your brain is processing danger faster than conscious thought,” he said. “Training takes over because there isn't time for debate.” The Science Behind Being Shot Understanding shootings requires understanding what a bullet actually does to the human body, a topic often misunderstood in movies and online debates. Police Shot At and Investigating Violent Crime: The Truth. A gunshot wound involves a rapid transfer of kinetic energy from a projectile into human tissue. The damage is determined largely by velocity, not simply size. Energy Transfer: Because velocity is squared in physics calculations, faster rounds deliver exponentially greater destructive potential. Permanent vs. Temporary Cavities: A bullet crushes tissue along its direct path while also creating a temporary cavity, a shockwave that stretches surrounding tissue. High-velocity rounds can cause severe internal damage far beyond the visible wound. The Momentum Myth: Contrary to Hollywood portrayals, bullets do not knock people backward. The momentum transfer is minimal compared to body mass, meaning individuals typically collapse due to physiological failure, not impact force. “People expect dramatic knockdowns,” Andrews said. “In reality, incapacitation usually comes from blood loss, nervous system disruption, or organ damage, not from being thrown backward.” Look for The Law Enforcement Talk Radio Show and Podcast on social media like their Facebook , Instagram , LinkedIn , Medium and other social media platforms. Different tissues respond differently to ballistic trauma. Elastic tissues such as muscle may stretch and recover, while organs like the liver or brain are far more vulnerable to catastrophic damage. Bone impacts frequently result in fragmentation, creating secondary projectiles inside the body. Police Shot At and Investigating Violent Crime: The Truth. Bullets may also yaw or fragment after entering tissue, increasing injury severity. Supersonic Reality: Why You May Never Hear the Shot One of the lesser-known truths Andrews discusses involves sound and perception during shootings. Most modern rifle rounds, and many handgun rounds, travel faster than the speed of sound. These supersonic projectiles create a sonic crack as they break the sound barrier. Available for free on their website and streaming on Apple Podcasts, Spotify, Youtube and other podcast platforms. “If a round is supersonic, it hits before you hear the gunshot,” Andrews explained. “That surprises people, but physics doesn't wait for perception.” Rifle rounds commonly travel thousands of feet per second, well beyond the speed of sound. Many handgun rounds, including common 9mm ammunition, are also supersonic. Subsonic ammunition travels slower than sound, meaning the gunshot may be heard before impact. Police Shot At and Investigating Violent Crime: The Truth. Because of this, officers under fire often react to impacts, debris, or instinct, not sound. “That's part of why these encounters are so chaotic,” Andrews said. “Your senses don't behave the way people expect.” Investigating Violent Crime: Complexity Behind the Scenes Beyond the moment of force, Andrews emphasized the intricate and often misunderstood process of investigating violent crime. It is discussed across News platforms and shared on Facebook, Instagram, LinkedIn, Apple, and Spotify, where true crime audiences continue to get their content. Every officer-involved shooting triggers layers of examination, forensic analysis, witness interviews, ballistic reconstruction, and policy review. “The Truth is investigations are extremely detailed,” he said. “Every movement, every decision, every angle gets analyzed. It's not quick, and it shouldn't be.” He noted that investigators must balance objectivity with the realities of human performance under extreme stress. Police Shot At and Investigating Violent Crime: The Truth. “You're analyzing decisions made in milliseconds with the benefit of months of hindsight,” Andrews said. “That's why experience matters.” From Policing to Influence: A Career Beyond the Badge Today, Andrews applies his law enforcement and security expertise globally as a security strategist and influencer. His Book, Yes S.I.R.: The Security Influencer's Guide to Success Using Strategy, Intelligence, and Relationships, outlines how professionals can build careers through networking, leadership, and collaboration. The book has earned praise across the security and law enforcement communities, with industry leaders describing Andrews as a pioneer and connector within the profession. “Relationships are everything,” Andrews said. “Whether you're investigating crime or building a career, success comes from strategy, intelligence, and trust.” Changing the Conversation As discussions about policing continue across digital platforms and Social Media, Andrews believes education is key to bridging public understanding. Police Shot At and Investigating Violent Crime: The Truth. You can find the show on Facebook, Instagram, Pinterest, X (formerly Twitter), and LinkedIn, as well as read companion articles and updates on Medium, Blogspot, YouTube, and even IMDB. “People deserve transparency,” he said. “But they also deserve context, the science, the psychology, and the reality officers face.” In an era where viral clips can shape public perception within minutes, deeper conversations, through podcasts, long-form discussions, and educational content, may help audiences better understand the complexities behind deadly force encounters. “The goal isn't to justify or criticize,” Andrews added. “It's to understand. Because understanding is where better conversations begin.” Charles is also heavily involved with a 5019(c3) charity that helps children of Law Enforcement Officers and Military. It is called Gratitude Initiative. Established in 2013 they honor the sacrifices of our Military and Law Enforcement families by helping their children succeed in college, their career, and life.  His message is available across The Law Enforcement Talk Radio Show and Podcast website, their facebook, Instagram, and LinkedIn, where professionals related to his honest discussions. You can contact John J. “Jay” Wiley by email at Jay@letradio.com , or learn more about him on their website . Find a wide variety of great podcasts online at The Podcast Zone Facebook Page , look for the one with the bright green logo. Be sure to check out our website . Be sure to follow us on X , Instagram , Facebook, Pinterest, Linkedin and other social media platforms for the latest episodes and news. Background song Hurricane is used with permission from the band Dark Horse Flyer. Police Shot At and Investigating Violent Crime: The Truth. Attributions Gratitude Initiative Amazon Google Facebook Facebook Group   Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Send a textRecorded 12/30/25In Part 2, the conversation dives deeper into elastic speed, force production, and long-term athlete development. Steven and Brandon break down how true speed is built through the integration of acceleration mechanics, plyometrics, and strength training — not just weight room numbers.They discuss how to identify whether an athlete is elastic-dominant or strength-dominant, how to program accordingly, and why broad jumps, resisted sprints, and intent-driven lifting matter more than traditional metrics.The episode also explores the evolution of sport performance, the dangers of over-coaching, and how developing adaptable, resilient athletes is the future of training.https://youtube.com/@platesandpancakes4593https://instagram.com/voodoo4power?igshid=YmMyMTA2M2Y=https://voodoo4ranch.com/To possibly be a guest or support the show email Voodoo4ranch@gmail.comhttps://www.paypal.com/paypalme/voodoo4ranch

Connect to John Gilroy on LinkedIn   https://www.linkedin.com/in/john-gilroy/ Want to listen to other episodes? www.Federaltechpodcast.com Way back in 2011, one of the goals of FedRAMP was to eliminate software redundancy. The federal government had evolved to the point where one agency would spend millions of dollars on the same application program that the agency in the same zip code had just invested heavily in. The theory proposed by luminaries like Vivek Kundra was to move to the cloud to share services. Reducing cost and improving resilience. FedRAMP was the initiative that established a safe environment for federal cloud use. Companies can comply with regulations outlined in an Authorization to Operate (ATO). Well, fifteen years later, and we are seeing the same duplication not in the application programs, but in the process to get the ATO itself. For example, FedRAMP, RMF, and agency internal policies may require specific artifacts to satisfy one or the other. During the interview, Travis Howerton paints the legacy model—static documentation, annual/3-year audits, spreadsheets. His solution is to have AI assist with documentation, which will drastically reduce compliance time; he cites an example of reducing a process from 52 weeks to 356 weeks. RegScale uses OSCAL (XML/YAML/JSON) to auto-generate RMF artifacts and integrate with SIEMs (Splunk, Elastic), Axonius, ServiceNow, and APIs. Howerton understands the limitations of many automated systems and suggests that a human is a key component after the machine language has assembled the data to make the decision.    

Join host Nick Schutt on Robots and Red Tape as he chats with Darryl Peek, VP of Partnerships for US Public Sector at Elastic. Darryl shares his journey from engineering at Lockheed Martin to leading in cybersecurity and AI-driven solutions.They dive into Elastic's role in search, observability, and security, exploring Retrieval Augmented Generation (RAG), data governance, and the challenges of AI in regulated industries. Discover how Elastic helps unify siloed data, enhance security, and measure AI's impact on productivity—all while navigating public sector priorities.*Key insights on RAG: Grounding AI with organizational data to avoid hallucinations and ensure accuracy.*Tackling data silos: Harmonizing structured and unstructured data for better insights without perfection.*Federal SOC bottlenecks: Prioritizing alerts, context, and triage to reduce analyst overload.*AI ethics and accountability: The need for audits, human-in-the-loop, and guardrails in agentic AI.*Modernization across administrations: Consolidating tools to build recession-proof missions focused on security and observability.Subscribe to @RobotsandRedTapeAI for more episodes on AI and public sector tech.

#337: Time series databases have become essential infrastructure for the physical AI revolution. As automation extends into manufacturing, autonomous vehicles, and robotics, the demand for high-resolution, low-latency data has shifted from milliseconds to nanoseconds. The difference between a general-purpose database and a specialized time series solution is the difference between a minivan and an F1 car - both will get around the track, but only one is built for the demands of real-time operational workloads. The open source business model continues to evolve in unexpected ways. While companies like Elastic and Redis have seen hyperscalers fork their projects, a new partnership paradigm is emerging. Amazon Web Services now pays to license InfluxDB and offers it as a managed service, signaling a shift toward collaboration rather than competition. This approach benefits everyone: vendors maintain development velocity, cloud providers get workloads on their platforms, and customers receive better-supported products. Evan Kaplan, CEO of InfluxData, joins Darin and Viktor to discuss the trajectory from observability metrics to physical world instrumentation, why deterministic models matter more than probabilistic ones when your robot might run over your cat, and what it takes to build a sustainable open source company over a decade-plus journey.   Evan's contact information: X: https://x.com/evankaplan LinkedIn: https://www.linkedin.com/in/kaplanevan/   YouTube channel: https://youtube.com/devopsparadox   Review the podcast on Apple Podcasts: https://www.devopsparadox.com/review-podcast/   Slack: https://www.devopsparadox.com/slack/   Connect with us at: https://www.devopsparadox.com/contact/

This conversation follows a simple insistence: if physics describes the world, it should also describe what is physically moving. Dr. Robert Close lays out a material, elastic picture of reality where quantum spin, torsion, and angular momentum emerge from deformations of an elastic substrate. Light, charge, and gravity follow as natural consequences. Rather than treating equations as final answers, the discussion asks what atomic-scale landscape could make those equations true. It's an attempt to return physics to mechanism, material, and the courage to hypothesize on what the math and experiments actually mean.PATREON https://www.patreon.com/c/demystifysciPARADOX LOST PRE-SALE: https://buy.stripe.com/7sY7sKdoN5d29eUdYddEs0bHOMEBREW MUSIC - Check out our new album!Hard Copies (Vinyl): FREE SHIPPING https://demystifysci-shop.fourthwall.com/products/vinyl-lp-secretary-of-nature-everything-is-so-good-hereStreaming:https://secretaryofnature.bandcamp.com/album/everything-is-so-good-herePARADIGM DRIFThttps://demystifysci.com/paradigm-drift-showROBERT CLOSE'S WEBSITE: https://classicalmatter.org/00:00 Go! Why physics still lacks physical models00:04:04 Discovering gaps in fundamental physics00:05:54 Angular momentum as the root of energy00:13:15 Coupled oscillators and quantized motion00:18:15 Elastic systems and light as deformation00:20:48 From aether to electromagnetism00:24:27 Gravitational waves as shear waves00:31:38 One medium for light, matter, and gravity00:39:57 Chirality, spin, and electric charge00:47:00 Particles as standing wave structures00:55:11 Atoms as unified wave systems01:00:00 Gravity from torsion in an elastic substrate01:08:47 Classical waves behind quantum behavior#physics, #howthingswork, #light, #gravity, #quantum, #energy, #waves, #space, #understanding, #thinking , #discovery, #longform, #podcast #physicspodcast, #philosophypodcast MERCH: Rock some DemystifySci gear : https://demystifysci-shop.fourthwall.com/AMAZON: Do your shopping through this link: https://amzn.to/3YyoT98DONATE: https://bit.ly/3wkPqaDSUBSTACK: https://substack.com/@UCqV4_7i9h1_V7hY48eZZSLw@demystifysci RSS: https://anchor.fm/s/2be66934/podcast/rssMAILING LIST: https://bit.ly/3v3kz2S SOCIAL: - Discord: https://discord.gg/MJzKT8CQub- Facebook: https://www.facebook.com/groups/DemystifySci- Instagram: https://www.instagram.com/DemystifySci/- Twitter: https://twitter.com/DemystifySciMUSIC: -Shilo Delay: https://g.co/kgs/oty671

We speak with ‘Roads & Kingdoms’ co-founder Nathan Thornburgh. Plus: in conversation with the founders of ‘Souvenir’, Augusta Sagnelli and Kyle Berlin, and Hillary Brenhouse from ‘Elastic’, a magazine dedicated to psychedelic art and literature.See omnystudio.com/listener for privacy information.

Mikey & Jeremy watch S7E13 of Smallville, "Hero". They discuss the long lasting flavor of Stride gum, the return of Pete Ross, and the lack of explanation regarding Kara's lost memory. 

Today's guest is Martin Bingisser. Martin is the founder of HMMR Media, one of the most trusted independent voices in throws and track & field education. A former competitive hammer thrower, Martin blends firsthand experience with deep historical and technical insight to analyze training methods, athlete development, and coaching culture. Through articles, videos, and interviews, his work bridges elite practice and practical coaching, earning him respect from coaches and performance professionals around the world. In a world of rapid-information delivery and short attention spans, the wisdom of master coaches is becoming increasingly rare. Martin has spent substantial time with two legends in the coaching world, Anatoliy Bondarchuk and Vern Gambetta. Spending time discussing the work of the past, and wisdom through the present is a critical practice in forming an effective coaching viewpoint. On today's episode I chat with Martin in a wide-ranging conversation in coaching lessons on efficiency, adaptability, and performing under pressure (two throws, no warmups, huge crowds). We transition into Bondarchuk's training philosophy: exercise classification, consistency, “strength” as sport-specific force production, and why weight-room PRs can distract from performance. The episode closes with motor-learning insights on rhythm, holistic cues, and how Vern Gambetta's “general” work complements specificity. Today's episode is brought to you by Hammer Strength and the Just Fly Sports Online Courses 30-50% off all courses until December 1, 2025. (https://justflysports.thinkific.com) Use code “justfly10” for 10% off the Vert Trainer Use code “justfly20” for 20% off of LILA Exogen Wearable resistance gear at www.lilateam.com View more podcast episodes at the podcast homepage. (https://www.just-fly-sports.com/podcast-home/) Timestamps 0:00 – Martin's background and training lens 7:05 – Why eccentric strength matters 15:40 – Isometric intent and force expression 24:30 – Tendons, stiffness, and elastic qualities 33:50 – Managing fatigue in strength training 42:15 – Applying eccentric and isometric work 51:20 – Athlete readiness and daily adjustment 1:00:10 – Long term development and durability Actionable Takeaways 7:05 – Eccentric strength underpins many performance qualities Martin explains that eccentric capacity sets the foundation for braking, deceleration, and re acceleration. Stronger eccentric abilities allow athletes to tolerate higher forces with less breakdown. Use controlled eccentric work to improve robustness without chasing constant intensity. 15:40 – Isometrics depend on intent, not just position Holding a position is not enough to drive adaptation. Martin emphasizes producing force into the immovable position to create meaningful stimulus. Cue effort and intent during isometrics instead of passively holding time. 24:30 – Tendon stiffness supports speed and efficiency Tendons transmit force, they do not just store it. Training should respect gradual loading to avoid disrupting tendon health. Elastic qualities improve when stiffness and timing are trained together. 33:50 – Fatigue management shapes training quality Not all fatigue is productive. Martin highlights watching bar speed, coordination, and effort quality to guide decisions. End sets when movement quality degrades rather than chasing prescribed numbers. 42:15 – Match training tools to the desired adaptation Eccentrics, isometrics, and dynamics all serve different purposes. Martin stresses selecting methods based on the adaptation you want, not trends. Blend methods thoughtfully instead of stacking stressors blindly. 51:20 – Daily readiness should influence loading Athletes do not arrive the same every day. Use simple readiness cues like bar speed and coordination to adjust training. Flexibility in programming helps preserve long term progress. 1:00:10 – Durability is built over time, not rushed Long term development requires patience and consistency. Martin reinforces gradual progression to protect connective tissue. not short term peaks. Quotes from Martin Bingisser “Eccentric strength is what allows athletes to absorb and redirect force safely.” “An isometric only works if there is intent behind it.” “Tendons are not passive structures, they are active contributors to performance.” “Fatigue is not the enemy, but unmanaged fatigue is.” “You have to choose training tools based on what you want to adapt.” “Readiness is not about feelings, it is about what you observe.” “Durability comes from respecting time and progression.” About Martin Bingisser Martin Bingisser is the founder of HMMR Media, one of the most respected independent platforms covering throws, strength training, and track & field performance. A former competitive hammer thrower, Martin combines firsthand athletic experience with a sharp analytical eye to break down training theory, competition trends, and athlete development across all levels of the sport. Through HMMR Media, he produces in-depth articles, interviews, videos, and educational resources that bridge the gap between elite coaching practice and accessible learning. His work is known for its clarity, historical context, and willingness to challenge oversimplified narratives in modern training. Martin has collaborated with coaches, athletes, and federations worldwide, and his content is widely used by throws coaches, sport scientists, and performance professionals seeking thoughtful, evidence-informed perspectives. His approach emphasizes long-term athlete development, technical mastery, and the craft of coaching; making him a trusted voice in the global track and field community.

Welcome back to the Ultimate Guide to Partnering® Podcast. AI agents are your next customers. Subscribe to our Newsletter: https://theultimatepartner.com/ebook-subscribe/ Check Out UPX:https://theultimatepartner.com/experience/ In this exclusive interview, Vince Menzione sits down with Darryl Peek, Vice President for Partner Sales (Public Sector) at Elastic, to decode how Elastic achieved the rare “triple crown”—winning Partner of the Year across Microsoft, Amazon, and Google Cloud simultaneously. Darryl breaks down the engineering-first approach that makes Elastic sticky with hyperscalers, reveals the rigorous metrics behind their partner health scorecard, and shares his personal “one-page strategy” for aligning mission, vision, and execution. From leveraging generative AI for cleaner sales hygiene to the timeless lesson of the “Acre of Diamonds,” this conversation offers a masterclass in building high-performance partner ecosystems in the public sector and beyond. https://youtu.be/__GE0r2fPuk Key Takeaways Elastic achieved “Pinnacle” status by aligning engineering roadmaps directly with hyperscaler innovations to become essential infrastructure. Successful public sector sales require a dual approach: leveraging resellers for contract access while driving domain-specific co-sell motions. Partner relationships outperform contracts; consistency in communication is more valuable than only showing up for renewals. Effective partner organizations track “influence” revenue just as rigorously as direct bookings to capture the full value of SI relationships. Generative AI can automate sales hygiene, turning scattered meeting notes into actionable CRM data and reducing friction for sales teams. The “Acre of Diamonds” philosophy reminds leaders that the greatest opportunities often lie within their current ecosystem, not in distant new markets. If you're ready to lead through change, elevate your business, and achieve extraordinary outcomes through the power of partnership—this is your community. At Ultimate Partner® we want leaders like you to join us in the Ultimate Partner Experience – where transformation begins. Keywords: Elastic, Darryl Peek, public sector sales, hyperscaler partnership, Microsoft Partner of the Year, AWS Partner of the Year, Google Cloud Partner, partner ecosystem strategy, co-sell motion, partner metrics, channel sales, government contracting, Carahsoft, generative AI in sales, sales hygiene, Russell Conwell, Acre of Diamonds, open source search, observability, security SIM, vector search, retrieval augmented generation, LLM agnostic, partner enablement, influence revenue, channel booking, SI relationships, strategic alliances. Transcript: Darryl Peek Audio Episode [00:00:00] Darryl Peek: I say, I tell my team from time to time, the difference between contacts and contracts is the R and that’s the relationship. So if you’re not building the relationship, then how do you expect that partner to want to lean in? Don’t just show up when you have a contract. Don’t just show up when you have a renewal. [00:00:13] Darryl Peek: Make sure that you are reaching out and letting them know what is happening. Don’t just talk to me when you need a renewal, right? When you’re at end of quarter and you want me to bring a deal forward, [00:00:23] Vince Menzione: welcome to the Ultimate Guide to Partnering. I’m Vince Menzi. Own your host, and my mission is to help leaders like you achieve your greatest results through successful partnering. [00:00:34] Vince Menzione: We just came off Ultimate Partner live at Caresoft Training Center in Reston, Virginia. Over two days, we gathered top leaders to tackle the real shifts shaping our industry. If you weren’t in the room, this episode brings you right to the edge of what’s next. Let’s dive in. So we have another privilege, an incredible partner, another like we call these, if you’ve heard our term, pinnacle. [00:01:00] Vince Menzione: I think it’s a term that’s not widely used, but we refer to Pinnacle as the partners that have achieved the top rung. They’ve become partners of the year. And our next presenter, our next interview is going to be with an organization. And a person that represents an organization that has been a pinnacle partner actually for all three Hyperscalers, which is really unusual. [00:01:24] Vince Menzione: Elastic has been partner of the Year award winner across Microsoft, Amazon, and Google Cloud, so very interesting. And Darrell Peak, who is the leader for the public sector organization, he’s here in the Washington DC area, was kind enough. Elastic is a sponsor event, and Darryl’s been kind enough to join me for a discussion about what it takes to be a Pinnacle partner. [00:01:47] Vince Menzione: So incredibly well. Excited to welcome you, Darryl. Thank you, sir. Good to have you. I love you. I love your smile, man. You got an incredible smile. Thank you. Thank you, Vince. Thank you. So Darryl, I probably didn’t do it any justice, but I was hoping you could take us through your role and responsibilities at Elastic, which is an incredible organization. [00:02:08] Vince Menzione: Alright. Yeah, [00:02:09] Darryl Peek: absolutely. So Darrell Peak vice President for partner sales for the US public sector at Elastic. I’ve been there about two and a half years. Responsible for our partner relationships across all partner types, whether that’s the system integrators, resellers, MSPs, OEMs, distribution Hyperscalers, and our Technology Alliance partners. [00:02:26] Darryl Peek: And those are partners that aren’t built on the Elastic platform. In regards to how my partner team interacts with our team. Our ecosystem. We are essentially looking to further and lean in with our partners in order for them to, one, understand what Elastic does since we’re such a diverse tool, but also work with our field to understand what are their priorities and how do they identify the right partners for the right requirements. [00:02:50] Darryl Peek: In regards to what Elastic is and what it does elastic is a solution that is actually founded on search and we’re an open source company. And one of the things that I actually did when I left the government, so I worked for the government for a number of years. I left, went and worked for Salesforce, then worked for Google ran their federal partner team and then came over to Elastic because I wanted to. [00:03:11] Darryl Peek: Understand what it meant to be at an open source company. Being at an open source company is quite interesting ’cause you’re competing against yourself. [00:03:17] Vince Menzione: Yeah, that’s true. [00:03:18] Darryl Peek: So it’s pretty interesting. But elastic was founded in 2012 as a search company. So when you talk about search, we are the second most used platform behind Google. [00:03:28] Darryl Peek: So many of you have already used Elastic. Maybe on your way here, if you use Uber and Lyft, that is elastic. That is helping you get here. Oh, that is interesting. If you use Netflix, if you use wikipedia.com, booking.com, eBay, home Depot, all of those are search capabilities. That Elastic is happening to power in regards to what else we do. [00:03:47] Darryl Peek: We also do observability, which is really around application monitoring, logging, tracing, and metrics. So we are helping your operations team. Pepsi is a customer as well as Cisco. Wow. And then the last thing that we do is security when we’re a SIM solution. So when we talk about sim, we are really looking to protect networks. [00:04:03] Darryl Peek: So we all, we think that it’s a data problem. So with that data problem, what we’re trying to do is not only understand what is happening in the network, but also we are helping with threat intelligence, endpoint and cloud security. So all those elements together is what Elastic does. And we only do it two ways. [00:04:18] Darryl Peek: We’re one platform and we can be deployed OnPrem and in the cloud. So that’s a little bit about me and the company. Hopefully it was clear, [00:04:24] Vince Menzione: I’ve had elastic people on stage. You’ve done, that’s the best answer I’ve had. What does Elastic do? I used to hear all this hyperbole and what? [00:04:32] Vince Menzione: What? Now I really understand what you do is an organiz. And the name of the company was Elasticsearch. [00:04:36] Darryl Peek: It was [00:04:37] Vince Menzione: elastic at one time when I first. Worked with you. It was Elasticsearch. [00:04:40] Darryl Peek: Absolutely. Yeah. So many moons ago used to be called the Elk Stack and it stood for three things. E was the Elasticsearch which is a search capability. [00:04:48] Darryl Peek: L is Logstash, which is our logging capability. And Cabana is essentially our visualization capability. So it was called Elk. But since we’ve acquired so many companies and built so much capability into the platform, we can now call it the elastic. Platform. [00:05:00] Vince Menzione: So talk to me about your engagement with the hyperscalers. [00:05:02] Vince Menzione: You’ve been partner of the Year award winner with all three, right? I mentioned that, and you were, you worked for Google for a period of time. Yes. So tell us about, like, how does that work? What does that engagement look like? And why do you get chosen as partner of the year? What are the things that stand out when you’re working with these hyperscalers [00:05:19] Darryl Peek: and with that we are very fortunate to be recognized. [00:05:23] Darryl Peek: So many of the organizations that are out there are doing some of the same capabilities that we do, but they can’t claim that they won a part of the year for all three hyperscalers in the same year. We are able to do that because we believe in the power of partnership, not only from a technology perspective, but also from a sales perspective. [00:05:39] Darryl Peek: So we definitely lean in with our partnerships, so having our engineers talk, having our product teams talk, and making sure that we’re building capabilities that actually integrate within the cloud service providers. And also consistently building a roadmap that aligns with the innovation that the cloud service providers are also building towards. [00:05:56] Darryl Peek: And then making sure that we’re a topic of discussion. So elastic. From a search capability, we do semantic search, vector search, but also retrieval augmented generation, which actually is LLM Agnostic. So when you say LLM Agnostic, whether you want to use Gemini, Claude or even Chad, GBT, those things are something that Elastic can integrate in, but it actually helps reduce the likelihood of hallucination. [00:06:18] Darryl Peek: So when we’re building that kind of solution, the cloud service provider’s you’re making it easy for us, and when you make it easy, you become very attractive and therefore you’re. Likely gonna come. So it becomes [00:06:28] Vince Menzione: sticky in that regard. Very sticky. So it sounds like very much an engineer, a lot of emphasis on the engineering aspects of the business. [00:06:35] Vince Menzione: I know you’re an engineer by background too, right? So the engineering aspects of the business means that you’re having alignment with the engineering organizations of those companies at a very deep level. [00:06:44] Darryl Peek: Absolutely. So I’m [00:06:45] Vince Menzione: here. [00:06:45] Darryl Peek: Yeah. And being at Elastic has been pretty amazing. So coming from Google, we had so many different solutions, so many different SKUs, but Elastic releases every eight weeks. [00:06:54] Darryl Peek: So right before you start to understand the last release, the next release is coming out and we’re already at 9.2 and we just released 9.0 in May. So it’s really blazing fast on the capability that we’re really pushing the market, but it’s really hard to make sure that we get it in front of our partners. [00:07:10] Darryl Peek: So when we talk about our partner enablement strategy, we’re just trying to make sure that we get the right information in front of the right partners at the right time, so this way they can best service their customers. [00:07:19] Vince Menzione: So let’s talk about partner strategy. Alyssa Fitzpatrick was on stage with me at our last event, and she Alyssa’s fantastic. [00:07:25] Vince Menzione: She is incredible. Yes, she is. She was a former colleague at Microsoft Days. Yes. And then she, we had a really interesting conversation. About what it takes, like being in, in a company and then working with the partners in general. And you have, I’m sure you have a lot of the similarities in how you have to engage with these organizations. [00:07:42] Vince Menzione: You’re working across the hyperscalers, you’re also working with the ecosystem too. Yes. ’cause the delivery, you have delivery partners as well. Absolutely. So tell us more about that. [00:07:50] Darryl Peek: So we kinda look at it from a two, two ways from the pre-sales motion and then the post-sales. From the pre-sales side. [00:07:56] Darryl Peek: What we’re trying to do is really maximize our, not only working with partners, because within public sector, you need to get access to customers through contract vehicles. So if you want to get access to some, for instance, the VA or through GSA or others, you have to make sure you’re aligned with the right partners who have access to. [00:08:12] Darryl Peek: That particular agency, but also you want domain expertise. So as you’re working with those system integrators, you wanna make sure that they have capability that aligns. So whether it is a security requirement, you wanna work with someone who specializes in security, observability and search. So that’s the way that we really look at our partner ecosystem, but those who are interested in working with us. [00:08:30] Darryl Peek: Because everybody doesn’t necessarily have a emphasis on working with a new technology partner, [00:08:36] Vince Menzione: right? [00:08:36] Darryl Peek: So what we’re trying to do is saying how do we build programs, incentives and sales plays that really does align and strike the interest of that particular partner? So when we talk about it I tell my team, you have to, my grandfather to say, plan your work and work your plan. And if you fail a plan, you plan to fail. So being able to not only have a strong plan in place, but then execute against that plan, check against that plan as you go through the fiscal year, and then see how you come out at the end of the fiscal year to see are we making that progress? [00:09:01] Darryl Peek: But on the other side of it, and what I get stressed about with my sales team and saying what does partners bring to us? So where are those partner deal registrations? What is the partner source numbers? How are we creating more pipeline? And that is where we’re now saying, okay, how can we navigate and how can we make it easier? [00:09:17] Darryl Peek: And how can we reduce friction in order for the partner to say, okay, elastic’s easy to work with. I can see value in, oh, by the way, I can make some money with. [00:09:25] Vince Menzione: So take us through, have there been examples of areas where you’ve had to like, break through to this other side in terms of growing the partner ecosystem? [00:09:33] Vince Menzione: What’s worked, what hasn’t worked? Yes, I’d love to learn more about that. [00:09:36] Darryl Peek: I’ll say that and I tell my team one, you partner program is essential, right? If you don’t have an attractive partner program in regards to how they come on board, how they’re incentivized the right amount of margin, they won’t even look at you. [00:09:49] Darryl Peek: The second thing is really how do you engage? So a lot of things start with relationships. I think partnerships are really about relationships. I say I tell my team from time to time, the difference between contacts and contracts is the R and that’s the relationship. So if you’re not building the relationship, then how do you expect that partner to want to lean in? [00:10:07] Darryl Peek: Don’t just show up when you have a contract. Don’t just show up when you have a renewal. Make sure that you are reaching out and letting them know what is happening. I like the what Matt brought up in saying, okay, talk to me when you have a win. Talk to me when you have something to talk about. [00:10:22] Darryl Peek: Don’t just talk to me when you need a renewal. When you’re at end the quarter and you want me to bring a deal forward, that doesn’t help ab absolutely. [00:10:28] Vince Menzione: So engineering organizations, sales organizations, what are, what does a healthy partnership look like for you? [00:10:35] Darryl Peek: So I look at metrics a lot and we use a number of tools and I know folks are using tools out there. [00:10:41] Darryl Peek: I won’t name any tools for branding purposes, but in regards to how we look at tools. So some things that we measure closely. Of course it’s our partner source numbers, so partner source, bookings, and pipeline. We look at our partner attached numbers and pipeline as well as the amount or percentage of partner attached business that we have in regards to our overall a CV number. [00:11:00] Darryl Peek: We also look at co-sell numbers, so therefore we are looking at not only how. A partner is coming to us, but how is a partner helping us in closing the deal even though they didn’t bring us the deal? We’re also looking at our cloud numbers and saying what amount of deals and how much business are we doing with our cloud service providers? [00:11:15] Darryl Peek: Because of course we wanna see that number go up year over year. We wanna actually help with that consumption number because not only are we looking at it from a SaaS perspective, but also if the customer has to commit we can help burn that down as well. We also look at influence numbers. [00:11:27] Darryl Peek: Now, one of the harder things to do within a technology business is. Capturing all that si goodness. And saying how do I reflect the SI if they’re not bringing me the deal? And I can’t attribute that amount of deal to that particular partner, right? And the way that we do that is we just tag them to the influence. [00:11:44] Darryl Peek: So we’re able to now track influence. And also the M-S-P-O-E-M work that we are also tracking and also we’re tracking the royalties. And lastly is the professional service work that we do with those partners. So we’re looking to go up into the right where we start them out at our select level, we go to our premier level and then our elite level. [00:12:00] Darryl Peek: But left and to the right, I say you gotta go from zero to one, one to five, five to 10, and then 10 to 25. So if we can actually see that progression. That is where we’re really starting to see health in the partnership, but also the executive alignment is really important. So when our CEO is able to meet with the fellow CEO of the co partner company that is really showing how we are progressing, but also our VPs and others that are engaged. [00:12:20] Darryl Peek: So those are things that we really do measure. We do have a health score card and also, we track accreditations, we track certifications as well as training outcomes based on our sales place. [00:12:30] Vince Menzione: Wow. There’s a lot of metrics there. Yeah. So you didn’t bring, you didn’t bring any slides with that out? [00:12:35] Darryl Peek: Oh, no. I’m not looking at slides, by the way. [00:12:40] Vince Menzione: Let’s talk about marketplace. [00:12:42] Darryl Peek: All right? [00:12:42] Vince Menzione: Because we’ve had a lot of conversations about marketplace. We’ve got both vendors up here talking about marketplace and the importance of marketplace, right? You’ve been a Marketplace Award winner. We haven’t really talked about that, like that motion per se. [00:12:55] Vince Menzione: I’d love to s I’d love to hear from you like how you, a, what you had to overcome to get to marketplace, what the marketplace motion looks like for your organization, what a marketplace first motion looks like. ’cause a lot of your cut a. Are all your customers requiring a lot of direct selling effort or is it some of it through Marketplace? [00:13:14] Vince Menzione: Like how does it, how does that work for you? [00:13:15] Darryl Peek: So Elastic is a global organization. Yeah. So we’re, 40 different countries. So it depends on where we’re talking. So if we talk about our international business, which is our A PJ and EMEA business we are seeing a lot more marketplace and we’re seeing that those direct deals with customers. [00:13:28] Darryl Peek: Okay. And we’re talking about our mirror business. A significant amount goes through marketplace and where our customers are transacting with the marketplace and are listing. On the marketplace within public sector, it’s more of a resell motion. Okay. So we are working with our resellers. [00:13:39] Darryl Peek: So we work our primary distribution partner is Carahsoft. So you heard from Craig earlier. Yes. We have a strong relationship with Carahsoft and definitely a big fan of this organization. But in regards to how we do that and how we track it we are looking at better ways to, track that orchestration and consumption numbers in order to see not only what customers we’re working with, but how can we really accelerate that motion and really get those leads and transactions going. [00:14:03] Vince Menzione: Very cool. Very cool. And I think part of the reason why in, in the government or public sector space it has a lot to do with the commitments are different. Absolutely. So it’s not government agencies aren’t able to make the same level of commitments that, private sector organizations were able to make, so they were able to the Mac or Microsoft parlance and also a AWS’s parlance. [00:14:23] Vince Menzione: Yeah, [00:14:24] Darryl Peek: definitely a different dynamic. Yeah. And especially within the public sector. ’cause we have Gov Cloud to work with, right? That’s right. So we’re working with Microsoft or we’re working with AWS, they have their Gov cloud and then we Google, they don’t have a Gov cloud, but we still have to work with them differently. [00:14:35] Darryl Peek: Yeah. Within that space. That’s [00:14:36] Vince Menzione: right. That’s right. So it makes the motion a little bit differently there. So I think we talked through some of this. I just wanna make sure we cover our points [00:14:43] Darryl Peek: here. One thing I’ll do an aside, you talked about the acre of diamonds. I’m a big fan of that story. [00:14:47] Vince Menzione: Yeah, let’s talk about Russ Con. Yeah, [00:14:49] Darryl Peek: let’s talk about it. Do you all know about the Acre Diamonds? Have you all heard that story before? No. You have some those in the audience. [00:14:55] Vince Menzione: I, you know what, let’s talk about it. All [00:14:56] Darryl Peek: See, I’m from Philadelphia. [00:14:57] Vince Menzione: I didn’t know you were a family. My daughter went to Temple University. [00:14:59] Vince Menzione: Ah, [00:15:00] Darryl Peek: okay. That’s all I know. So Russell Conwell. So he was, a gentleman out of the Philadelphia area and he went around town to raise money and he wanted to raise money because he believed that there was a promise within a specific area. And as he continued to raise this money, he would tell a story. [00:15:14] Darryl Peek: And basically it was a story about a farmer in Africa. And the farmer in Africa, to make it really short was essentially looking to be become very wealthy. And because he wanted to become very wealthy, he believed that selling his farm and going off to a long distant land was the primary way for him to find diamonds. [00:15:28] Darryl Peek: And this farmer didn’t sold us. Sold his place, then went off to to this foreign land, and he ended up dying. And people thought that was the end of the story, but there was another farmer who bought that land and one time this big, and they called him the ot, came to the door and said you mind if I have some tea with you? [00:15:43] Darryl Peek: He said, all right, come on in. Have a drink. And as he had the drink, he looked upon the mantle and his mouth dropped. And then the farmer said what’s wrong? What do you say? He says, do you know what that is? No. He said no. Do you know what that is? He says, no. He said, that’s the biggest diamond I’ve ever seen, and the farmer goes. [00:16:01] Darryl Peek: That’s weird because there’s a bunch right in the back where I go grab my fruits and crops every day. So the idea of the acre diamonds and sometimes that you don’t need to go off to a far off land. It is actually sometimes right under your feet, and that is a story that helped fund the starting of Temple University. [00:16:16] Vince Menzione: I’m gonna need to take you at every single event so you can tell this story again. That’s an awesome job. Oh, I love it. And yeah, they founded a Temple University. Yeah. Which has become an incredible university. My daughter, like I said, my daughter’s a graduate, so we’re Temple fan. That’s great story. [00:16:31] Vince Menzione: That is a very cool, I didn’t realize you were a Philadelphia guy too, so that is awesome. Go birds. Go birds. All right, good. So let’s talk, I think we talked a little bit about your ecosystem approach, but maybe just a little bit more on this, like you said, like a lot of data, a lot of metrics but also a lot of these organizations also have to under understand the engineering side of things. [00:16:53] Vince Menzione: Oh, yeah. There’s a tremendous amount to become. Not everybody could just show up one day and become an elastic partner [00:16:58] Darryl Peek: absolutely. Absolutely. So take us [00:16:59] Vince Menzione: through that process. [00:17:00] Darryl Peek: Yeah. So one of the things that we are trying to mature and we have matured is our partner go to market. [00:17:06] Darryl Peek: So in order to join our partner ecosystem, you have to sign ’em through our partner portal. You have to sign our indirect reseller agreement. ’cause we do sell primarily within the public sector through distribution. And we only go direct if it is by exception. So you have to get justification through myself as well as our VP for public sector. [00:17:21] Darryl Peek: But we really do try to make sure that we can aggregate this because one thing that we have to monitor is terms and conditions. ’cause of course, working with the government, there’s a lot of terms and conditions. So we try to alleviate that by having it go through caresoft, they’re able to absorb some, so this way we can actually transact with the government. [00:17:36] Darryl Peek: In regards to the team though we try to really work closely with our solution architecture team. So this way we can develop clear enablement strategies with our partners so this way they know what it is we do, but also how to properly bring us up in a conversation. Also handle objections and also what are we doing to implement our solutions within other markets. [00:17:55] Darryl Peek: So those are things that we are doing as well as partner marketing. Top of funnel activity is really important, so we’re trying to differentiate what we’re doing with the field and field marketing. So you’re doing the leads and m qls and things of that nature also with partner marketing. So our partner marketing actually is driven by leads, but also we’re trying to transact. [00:18:10] Darryl Peek: And get Ps of which our partner deal registration. So that is how we align our partner go to market. And that is actually translating into our partner source outcomes. [00:18:18] Vince Menzione: And I think we have a slide that talks a little bit about your public sector partner strategy. [00:18:23] Darryl Peek: Oh yeah. Oh, I share that. So I thought maybe we could spin it. [00:18:25] Darryl Peek: Absolutely. [00:18:25] Vince Menzione: I know you we can’t see it, but they can. Oh, they can. Okay. Great. [00:18:29] Darryl Peek: There it’s there. [00:18:30] Vince Menzione: It’s career. [00:18:31] Darryl Peek: One thing, I think this was Einstein has said, if you can’t explain it simply, you don’t understand it well enough. So that was the one thing. So I always was a big fan of creating a one page strategy. [00:18:39] Darryl Peek: And based on this one page strategy one of the things when I worked at Salesforce it was really about a couple things and the saying, okay, what are your bookings? And if you don’t have bookings, what does your pipeline look like? If you don’t have pipeline, what does your prospecting look like? [00:18:51] Darryl Peek: Yeah. If you don’t have prospecting what does your account plan look like? And if you don’t have an account plan, why are you here? Why are you here? Exactly. So those are the things that I really talk to my team about is just really a, it’s about bookings. It’s about pipeline. It’s about planning, enablement and execution. [00:19:05] Darryl Peek: It’s about marketing, branding and evangelism, and also about operational excellence and how to execute. Very cool. So being able to do that and also I, since I came from Salesforce, I talk to my team a lot about Salesforce hygiene. So we really talk about that a lot. So make, making sure we’re making proper use of chatter, but also as we talk about utilizing ai, we just try to. [00:19:21] Darryl Peek: How do we simplify that, right? So if we’re using Zoom or we’re using Google, how do we make sure that we’re capturing those meeting minutes, translating that, putting that into the system, so therefore we have a record of that engagement with that partner. So this is a continuous threat. So this way I don’t have to call my partner manager the entire time. [00:19:36] Darryl Peek: I can look back, see what actions, see what was discussed, and say, okay, how can we keep this conversation going? Because we shouldn’t have to have those conversations every time. I shouldn’t have to text you to say, give me the download on every partner. Every time. How do we automate that? And that’s really where you’re creating this context window with your Genive ai. [00:19:53] Darryl Peek: I think they said what 75% of organizations are using one AI tool. And I think 1% are mature in that. But also a number of organizations, it’s 90% of organizations are using generative AI tools to some degree. So we are using gen to bi. We do use a number of them. We have elastic GPT. Nice little brand there. [00:20:11] Darryl Peek: But yeah, we use that for not only understanding what’s in our our repositories and data lakes and data warehouses, but also what are some answers that we can have in regards to proposal responses, RP responses, RFI, responses and the like. [00:20:23] Vince Menzione: And you’re reaching out to the other LLMs through your tool? [00:20:26] Darryl Peek: We can actually interact with any LLM. So we are a LLM Agnostic. [00:20:29] Vince Menzione: Got it. Yep. That’s fantastic. And this slide is we’ll make this available if you don’t have a, yeah, have a chance. We’ll share it. I [00:20:36] Darryl Peek: am happy to share, yeah. And obviously happy to talk, reach out about it. Of, of course. I simplified it in order to account for you, but one of the things that I talk about is mission, vision of values. [00:20:45] Darryl Peek: And as we start with that is what is your mission now? How is anybody from Pittsburgh, anybody steal a fan? Oh wow. No, there’s a steel fan over [00:20:54] Vince Menzione: here. There’s one here. There’s a couple of ’em are out here. So I feel bad. [00:20:57] Darryl Peek: The reason why I put immaculate in there is for the immaculate reception, actually. [00:21:00] Darryl Peek: Yes. And basically saying that if you ever seen that play, it was not pretty at all. It was a very discombobulated play. Yeah. And I usually say that’s the way that you work with partners too, because when that deal doesn’t come in, when you gotta make a call, when you’re texting somebody at 11 o’clock at night, when you’re trying to get that at, right before quarter end. [00:21:17] Darryl Peek: Yeah. Before the end of it. It really is difficult, but it’s really creating that immaculate experience. You want that partner to come back. I know it’s challenging, but I appreciate how you leaned in with us. Yes, absolutely. I appreciate how you work with us. I appreciate how you held our hand through the process, and that’s what I tell my team, that we have to create that partner experience. [00:21:32] Darryl Peek: And maybe that’s a carryover from Salesforce, Dave. I don’t know. But also when we talk about enhancing or accelerating our partner. Our public sector outcomes that is really working with the customer, right? So customer experience has to be part of it. Like all of us have to be focused on that North star, and that is really how do we service the customer, and that’s what we choose to do. [00:21:48] Darryl Peek: But also the internal part. So I used to survey my team many moves ago, and I said, if we don’t get 80% satisfaction rate from our employees how do we get 60% satisfaction rate from our customers? Yeah. So really focus on that employee success and employee satisfaction. It’s so important, is very important. [00:22:03] Darryl Peek: So being able to understand what are the needs of your employees? Are you really addressing their concerns and are you really driving them forward? Are you challenging them? Are you creating pathways for progression? So those are things that I definitely try to do with my team. As well as just really encouraging, inspiring, yeah. [00:22:19] Darryl Peek: And just making sure that they’re having fun at the same time. [00:22:21] Vince Menzione: It shows up in such, I, there’s an airline I don’t fly any longer, and it was a million mile member of and I know it’s because of the way they treat their employees. [00:22:29] Vince Menzione: Because it cascades Right? [00:22:30] Darryl Peek: It does. Culture is important. [00:22:32] Vince Menzione: Yeah. Absolutely. [00:22:32] Darryl Peek: What is it? What Anderson Howard they say what col. Mark Andresen culture eat strategy for [00:22:37] Vince Menzione: breakfast. He strategy for breakfast? Yes. Very much this has been insightful. I really enjoyed having you here today. Really a great, you’re a lot of fun. You’re a lot of fun. [00:22:43] Vince Menzione: Darry, isn’t you? Amazing. So thank you for joining us. Thank you all. Thank And you’re gonna be, you’re gonna be sticking around for a little while today. I’m sticking around for a little while. I’ll be back in little later. I think people are gonna just en enjoy having a conversation with you, a little sidebar. [00:22:55] Darryl Peek: Absolutely. I’m looking forward to it. Thank you all for having me. Glad to be here. And thank you for giving the time today. [00:23:01] Vince Menzione: Thank you Darryl, so much. So appreciate it. And you’re gonna have to come join me on this Story Diamond tool. Yeah, absolutely. Thanks for tuning into this episode of Ultimate Guide to Partnering. [00:23:12] Vince Menzione: We’re bringing these episodes to you to help you level up your strategy. If you haven’t yet, now’s the time to take action and think about joining our community. We created a unique place, UPX or Ultimate partner experience. It’s more than a community. It’s your competitive edge with insider insights, real-time education, and direct access to people who are driving the ecosystem forward. [00:23:38] Vince Menzione: UPX helps you get results, and we’re just getting started as we’re taking this studio. And we’ll be hosting live stream and digital events here, including our January live stream, the Boca Winter Retreat, and more to come. So visit our website, the ultimate partner.com to learn more and join us. Now’s the time to take your partnerships to the next level.

Today's guest is Dustin Oranchuk, Ph.D. Dustin is a sport scientist focused on sprinting biomechanics, speed development, and force production. Known for blending research with practical coaching insight, his work explores how isometrics, elasticity, and coordination shape high-performance sprinting and athletic movement. Isometric training is one of the “original” forms of strength training, and in the modern day has become one of the most popular areas of discussion and training methodology. Although the practice has exploded, it often lacks an understanding of physiology of adaptation with various methods. In this episode, Dustin explores the evolving world of isometric training, including the origins of isometrics. We discuss differences between pushing and holding contractions, tendon and neural adaptations, and modern applications in performance, rehab, and longevity. The conversation also dives into eccentric quasi-isometrics (EQIs), motivation and measurement challenges, and how coaches can intelligently integrate isometrics alongside plyometrics and traditional strength work. Today's episode is brought to you by Hammer Strength. Use the code “justfly20” for 20% off any Lila Exogen wearable resistance training, including the popular Exogen Calf Sleeves. For this offer, head to Lilateam.com Use code “justfly10” for 10% off the Vert Trainer View more podcast episodes at the podcast homepage. (https://www.just-fly-sports.com/podcast-home/) Timestamps 0:11 – Strength Training Beginnings 5:38 – Evolution of Isometric Training 8:38 – Modern Applications of Isometrics 9:52 – Neural vs. Morphological Adaptations 15:45 – The Importance of Long Holds 19:42 – Combining Isometrics and Plyometrics 39:22 – Exploring Eccentric Quasi-Isometrics 47:10 – Periodization and Isometric Training 1:05:48 – Future Research Directions 1:13:00 – Closing Thoughts and Reflections Actionable Takeaways 5:38 Evolution of Isometric Training Overcoming isometrics originated as a way to target sticking points with high force. Early isometric systems emphasized position specific strength over movement. Modern usage has expanded beyond barbell sports into rehab and longevity. 8:38 Modern Applications of Isometrics Isometrics are now widely used to “own positions” across joint angles. Longer duration holds are frequently used for tissue health and rehab. Training intent has shifted from peak strength toward durability and resilience. 9:52 Neural vs. Morphological Adaptations Short range, position specific isometrics bias neural intent and coordination. Long muscle length isometrics bias hypertrophy and tendon adaptation. Choose isometric type based on whether the goal is performance transfer or tissue change. 15:45 The Importance of Long Holds Tendons require relatively high intensity to meaningfully adapt. Long holds help reveal side to side asymmetries and control deficits. Extended holds build tolerance and confidence in vulnerable joint positions. 19:42 Combining Isometrics and Plyometrics Pairing isometrics and plyometrics can produce modest additive benefits. Combining methods may reduce fatigue compared to doing each alone. The interaction may enhance effort quality rather than purely physiological output. 39:22 Exploring Eccentric Quasi Isometrics EQIs combine a maximal hold followed by forced eccentric lengthening. They accumulate large time under tension and eccentric impulse. EQIs are powerful but mentally taxing and difficult to sustain long term. 47:10 Periodization and Isometric Training Use longer, lower intensity holds earlier in the offseason. Progress toward shorter, higher intensity, position specific isometrics near competition. Post game isometrics can support recovery without additional joint stress. 1:05:48 Future Research Directions Measurement technology has driven the resurgence of isometrics. Push versus hold distinctions are becoming a key research focus. Future work aims to clarify muscle and tendon behavior during isometric intent. 1:13:00 Closing Thoughts and Reflections Consistency with foundational exercises drives long term progress. Isometrics are tools, not replacements for dynamic training. Coaches should match the method to the goal, not the trend. Quotes from Dustin Oranchuk “Tendons tend to need a certain threshold of intensity to get meaningful adaptations.” “The maximal amount of force you can push is almost always more than what you can hold.” “Isometrics let you own positions rather than just pass through them.” “Long holds are a great diagnostic tool for finding asymmetries.” “EQIs are effective, but they are very hard to push hard and regularly.” “Use the best tool for the job rather than trying to blend everything together.” “Consistency beats constantly reinventing your training approach.” “Isometrics compress joint motion so other systems can recover and adapt.” “Intent matters just as much as the muscle action itself.” “You do not need complexity to get strong adaptations over time.” About Dustin Oranchuk Dustin Oranchuk, PhD, is a sport scientist specializing in speed development, biomechanics, and force production in sprinting and jumping. He holds a doctorate in sport science and has worked extensively with elite athletes across track and field, team sports, and high-performance environments. Dustin is widely known for his research-informed yet practical approach to sprint mechanics, isometric training, and elastic performance, bridging laboratory insights with real-world coaching application. Through consulting, research, and education, he helps coaches and athletes better understand how force, stiffness, and coordination influence maximal speed and performance.

On today's episode, I talk to musician Amy Oelsner AKA Amy O. Originally from Fayetteville, Arkansas, Amy has been recording and releasing albums since 2004. In 2017, she began releasing albums on Winspear with the wonderful Elastic, which was followed up two years later by Shell and then 2024's brilliant Mirror, Reflect. Alongside her musical career, in 2019 Amy founded Girls Rock Bloomington, a music and mentorship nonprofit for girls, trans and non-binary youth that teaches positive self-esteem and self-expression through many events as well as an annual rock n' roll summer camp. This is the website for Beginnings, subscribe on Apple Podcasts, follow me on Twitter. Check out my free philosophy Substack where I write essays every couple months here and my old casiopop band's lost album here! And the comedy podcast I do with my wife Naomi Couples Therapy can be found here! Theme song by the fantastic Savoir Adore! Second theme by the brilliant Mike Pace! Closing theme by the delightful Gregory Brothers! Podcast art by the inimitable Beano Gee!  

Today's guest is Reinis Krēgers, a former champion decathlete turned track and physical education coach. Reinis is dedicated to building complete movers: fast, coordinated, confident athletes who understand their bodies. His training blends classical sprint development with exploratory tasks, helping athletes develop physical literacy and long-term adaptability. In sports performance, we often fixate on exercises, cues, and optimizing micro-qualities in the moment. What we discuss far less, yet what often separates the elite, is the role of play, creativity, and culture. By looking closely at events like the pole vault and hurdles, we can see how a developmental, curiosity-driven approach benefits athletes of every sport. In this episode, Reinis shares the remarkable story of losing a finger, training exclusively with his non-dominant hand, and still setting a shot put PR. This opens the door to a rich discussion on cross-education, novelty, and how the brain actually learns movement. We explore play-based coaching, pole vault as a developmental super-tool, contrasts between Eastern and American coaching philosophies, youth sport creativity, and sustainable tendon development. It's a conversation full of insight, storytelling, and reminders of what truly anchors a lifelong athletic journey: curiosity, joy, and the art of falling in love with movement. Today's episode is brought to you by Hammer Strength and LILA Exogen wearable resistance. Use the code “justfly20” for 20% off any Lila Exogen wearable resistance training, including the popular Exogen Calf Sleeves. For this offer, head to Lilateam.com Use code “justfly10” for 10% off the Vert Trainer View more podcast episodes at the podcast homepage. (https://www.just-fly-sports.com/podcast-home/) 0:00 – Early upbringing in Latvia and falling in love with movement 6:18 – Play, curiosity, and environment driven athlete development 14:50 – Injuries, setbacks, and choosing to continue competing 23:40 – Czech training experience and constraints based coaching 33:05 – European versus American development and long term athlete philosophy 45:10 – Games, novelty, and bringing play back into training 59:47 – Specialization mistakes and the importance of multi sport development 1:11:48 – Plyometrics, bounding, and gradual tissue adaptation 1:22:40 – Injury lessons, tendon health, and the value of long term gradual loading Actionable Takeaways 6:18 – Play, curiosity, and environment driven development Reinis explains that his athletic foundation came from unstructured exploration, not early specialization. Let athletes solve problems rather than repeat fixed patterns. Encourage outdoor play and varied surfaces to build natural coordination. Curiosity creates better movers than rigid instruction. 14:50 – Navigating injuries and staying in the sport Reinis shares how setbacks led him to rethink training instead of quitting. Use injuries as a signal to adjust training rather than push through blindly. Keep a competitive outlet during rehab to maintain identity and motivation. Return with smarter progression instead of trying to reclaim old numbers immediately. 23:40 – Constraints based learning from Czech training Reinis describes how training environments shaped movement without heavy cueing. Change the environment before changing the athlete. Use simple tasks and small boundaries to create automatic technical improvements. Let athletes feel solutions instead of chasing perfect positions. 33:05 – European versus American development Reinis contrasts long term models focused on movement quality rather than short term output. Early years should build durability, not just speed and strength metrics. Avoid rushing physical qualities before coordination and play are established. Development is a process of layering, not skipping steps. 45:10 – Bringing games and novelty back into training Reinis highlights how playful constraints improve responsiveness and decision making. Add game based movement to keep athletes adaptive under changing conditions. Use novelty sparingly to reawaken coordination and intent. Reduce scripted drills when athletes stop learning from them. 59:47 – Multi sport value and avoiding early specialization Reinis explains why single sport paths can limit long term performance. Multiple sports expand movement bandwidth and reduce overuse. Delay specialization until athletes have broad coordination skills. Early success does not guarantee long term development. 1:11:48 – Plyometrics and gradual tissue progression Reinis stresses that bounding and plyos require patience and slow tissue adaptation. Progress volume and intensity over seasons, not weeks. Start with low amplitude contacts before higher velocity work. Tendons adapt slower than muscles, so loading must reflect that timeline. 1:22:40 – Tendon health and long term loading approach Reinis shares what he learned from repeated injury cycles. Small, consistent loading beats aggressive spikes in volume. Build tolerance through frequency and controlled exposure. The goal is to stay in the game long enough for development to compound. Quotes from Reinis Krēgers "Good coaching has some mystery because we are not robots" "Kids should fall in love with the movement and the sport before anything else" "Constraints are the key word in my training method and philosophy" "Track and field without play is a dry and bad solution for long term success" "There is no such thing as a training methodology, it is the relationship between the coach and the athlete" "Sudden increases in load were always the trigger for my Achilles problems" "You want gradual and consistent work if you want the tissues to adapt" "Sleep enough and rest after good training, that is one of the most important things I tell young athletes" About Reinis Krēgers Reinis Krēgers is a Latvian track and physical preparation coach known for blending classical sprint mechanics with modern movement ecology. With a background in athletics and physical education, Reinis has built a reputation for developing athletes who are not only fast, but exceptionally coordinated, elastic, and adaptable across environments. Drawing from European sprint traditions, plyometric culture, and cutting-edge motor-learning principles, Reinis emphasizes rhythm, posture, and natural force expression before “numbers.” His training sessions regularly weave together technical sprint development, multi-planar strength, and exploratory movement tasks, giving athletes the bandwidth to become resilient movers rather than rigid specialists. Reinis works across youth, club, and competitive settings, helping sprinters, jumpers, and team-sport athletes gain speed, power, and physical literacy. His coaching is marked by clarity, intentionality, and an ability to meet athletes where they are, building them from foundational movement quality toward high-performance execution. Whether on the track or in the PE hall, Reinis' mission is the same: develop confident, capable movers who understand their bodies, enjoy the process, and carry a lifelong relationship with athleticism.