Podcasts about ServiceNow

Jason and Jeff tackle the current wave of market chaos—from oil price spikes and tariffs to the "AI is killing software" narrative. They dive into how they're personally navigating the noise, sharing recent portfolio additions such as Phinia (PHIN) and Clearway Energy that appear insulated from the macroeconomic volatility. They also unpack the AI software scare with deep dives into Toast, ServiceNow, and Procore, and Jason issues a warning about the hidden risks lurking in the booming private credit market.01:19 AI Tariffs Oil Backdrop03:38 Housekeeping Mailbag Plug04:42 Staying the Course07:18 Markets Recover Before Clarity12:04 Stock Pick PHIN19:01 Renewables Reality Check20:54 Clearway Energy Buy24:50 Energy Security and Oil Flows26:36 Oil And Geopolitics27:29 Krugman On Price Spikes30:33 Toast Stock Breakdown35:44 ServiceNow AI Strategy37:35 Procore Construction Software42:17 Private Credit Risks47:38 Staying Invested In Chaos49:19 Process Over HeadlinesCompanies mentioned: BAM, BEP, BX, CPNG, CWEN, DASH, ENPH, FOUR, KKR, NOW, ORCL, OWL, PCOR, PHIN, PYPL, SHOP, SQ, TOSTFind where to listen & subscribe,  portfolio contests, and contact information at https://investingunscripted.com*****************************************To get 15% off any paid plan at fiscal.ai, visit https://fiscal.ai/unscriptedListen to the Chit Chat Stocks Podcast for discussions on stocks, financial markets, super investors, and more. Follow the show on Spotify, Apple Podcasts, or YouTube*****************************************Join our PatreonSubscribe to our portfolio on Savvy Trader

Today's guest is David Shake, Director, ServiceNow PMO - North America at Crossfuze. Founded in 2000, Crossfuze is a global consulting and services firm specializing in the ServiceNow platform. As a 2025 ServiceNow Partner of the Year, Crossfuze helps organizations accelerate digital transformation through advisory, implementation and managed services. The company focuses on optimizing workflows, improving service delivery and enabling customers to maximize the value of their ServiceNow investments.David is a focused and innovative professional with strong leadership, management, and communication skills. He excels in balancing competing priorities while building collaborative teams and strong client relationships. As a Client Lead at Crossfuze, David directs complex projects involving process and system design, resource management, and global service delivery. Passionate about customer success, David leverages his ServiceNow expertise to deliver operational excellence and help clients achieve their business goals.In the episode, David talks about:0:00 His journey from Xerox sales intern to service delivery leader5:47 Crossfuze as an elite ServiceNow partner offering implementations and support6:59 Delivering ServiceNow reveals gaps between vision and reality10:13 The need to be honest, realistic and solution-focused in implementations13:45 Seeing growing demand in SecOps and risk management16:00 How Crossfuze's small size cultivates a collaborative, expert-driven culture18:14 Why Crossfuze's reputation and expert breadth drive industry differentiationTo find out more about all the great work happening at Crossfuze, check out the website www.crossfuze.com

The first half of ServiceNow's (NOW) trading month is characterized by a "head and shoulders" pattern forming in the chart, says Rachel Dashiell with Charles Schwab. She highlights key support and resistance levels in the 20-day and one-year stock activity. ======== Schwab Network ========Empowering every investor and trader, every market day.Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – / schwabnetwork Follow us on Facebook – / schwabnetwork Follow us on LinkedIn - / schwab-network About Schwab Network - https://schwabnetwork.com/about

A busy 24 hours between DC headlines and PCE data... Carl Quintanilla, Sara Eisen, and Michael Santoli kicked off the hour with the latest on both fronts, before discussing the implications for markets, traders, and the Federal Reserve. Plus: hear ServiceNow CEO Bill McDermott's huge warning when it comes to AI and youth unemployment, along with more on how Iran is changing the business of cybersecurity with the CEO of one beneficiary (Rubrik).    Elsewhere in the hour: former Defense Secretary Mark Esper joined the team with his expectations when it comes to possible escalation ahead.    Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

This week I discuss the AI, HR Tech, and consumer AI market in front of announcements next week at the Unleash Conference in Vegas. I discuss how HR Tech is now becoming “Life Tech” (not just Work Tech) and the dynamics of big players like Microsoft, Oracle, Workday, SAP, ServiceNow, Anthropic, OpenAI, Google, and smaller vendors like Cornerstone, Findem, Lightcast, Maki People, Eightfold, WorkHuman and others who are vying for attention with their AI offerings. Next week I'll detail many of these announcements in my keynote and I hope to see many of you in Vegas at Unleash and the following week at Transform. So much to absorb and understand: we are here to help you sort it all out. Additional Information Layoffs at Atlassian, Block, Amazon are Misleading. AI Alone Is Not The Story. The World of Corporate Training Lurches Toward Enablement Oracle's Earnings Prove That AI Infrastructure Is Eating Enterprise Software Enterprise AI Architecture: Imperatives for 2026 Webinar: Watch a replay of Josh's walkthrough of the 11 essential imperatives HR & business leaders need to know for success and progress in 2026. Galileo Learn: Complete The Superworker Organization: AI Goes Enterprise learning program, and discover the hands-on skills required to navigate the redefinition of work, HR teams, and organizations in the era of superworkers and superagents. Get Galileo: The Enterprise AI Agent for HR  Chapters (00:00:00) - All the HR Technology Announcements(00:07:29) - Oracle's strategy for growth(00:10:37) - Microsoft's Copilot, and More

Enterprise leaders are investing heavily in AI, but many struggle to generate measurable business value. In this episode of Technovation, Peter High speaks with Kellie Romack of ServiceNow about how the company is scaling AI across its operations to produce real, quantifiable results. ServiceNow has already generated $355 million in AI-driven value internally, with automation resolving many service requests instantly and improving operational efficiency across the enterprise. Key topics include: How ServiceNow runs its own platform internally as Customer Zero Examples of AI resolving 90% of some IT service requests on first touch Why AI governance and oversight are essential at enterprise scale How automation transforms the workforce rather than replacing it Lessons for CIOs seeking real ROI from AI investments

Realities Remixed, formerly know as Cloud Realities, launches a new season exploring the intersection of people, culture, industry and tech.After years of remote‑first work built on swift trust, companies are asking a harder question: what does a organization really stand for when people rarely show up together? As AI accelerates change, leaders are rethinking presence, team design, and collaboration to fuel trust, innovation, and growth. This week, Dave, Esmee, and Rob are joined by Dr. Tim Currie, disruptor, author, innovator, and advisor, to examine transformation versus trust, the role of AI, and whether organisations can truly build culture without deeper human connection. TLDR00:42– Introduction01:10 –  Hang out: New film releases07:17 – Dig in: The trust gap in remote work17:57 – Conversation with Dr. Tim Currie54:07 – The Wizard of Oz at the Sphere in Las Vegas and staying connected GuestDr. Tim Currie: https://www.linkedin.com/in/dr-tim-currie-37756a/Book Swift Trust: https://swifttrustbook.com/HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

The dominant structural mechanism highlighted is the industry-wide shift toward liability transfer and governance gaps in AI procurement, deployment, and incident response. According to Dave Sobel, both vendors and organizations are accelerating AI adoption without corresponding investments in oversight, training, or clear accountability structures. This is reflected across multiple sectors, from software vendors such as Grammarly, Eightfold.ai, Cohesity, and Rubrik, to business leaders and policymakers, where risk is systematically deferred downstream rather than managed at the point of adoption. The most consequential evidence is the quantitative disconnect between stated AI priorities and functional oversight. Research cited by Dave Sobel from Economist Impact and HR Dive found that while 38% of organizations budget for AI and 86% of executives rate AI as essential, only 16% offer internal training and over half of department-level AI initiatives lack formal oversight (Ernst & Young). Additionally, 88% of AI vendors limit their liability, and only 17% align with regulatory compliance, per cited surveys, leaving substantial legal and operational risk for end users and service providers. Supporting this trend, Dave Sobel points to Grammarly's opt-out identity usage in new features and a class action lawsuit against Eightfold.ai regarding AI-driven employment decisions. Vendors such as Cohesity, Rubrik, ServiceNow, and Datadog are responding by building tools focused on remediation and recovery from AI-driven incidents, underscoring a shift from preventive governance to reactive containment. Policy moves—such as expanded operational cyber roles for the private sector—further offload accountability without addressing contractual and insurance exposure. For MSPs and technology leaders, these developments create practical risks: unclear service scope around AI tool usage in contracts, increased exposure to billable incidents and legal action, and rising labor costs for incident recovery. Service providers must audit agreements for AI-specific language, distinguish AI-related incidents from standard SLAs, and treat AI governance as a managed risk service. The pressure will increasingly fall on MSPs to account for training gaps, audit trails, compliance attestations, and recovery procedures—not simply the technology itself. Three things to know today 00:00 ROI Reality Check 02:12 Governance Gap Widens 03:14 Cleanup Economy Rises 05:45 Why Do We Care?  Supported by:  CometBackup 

In today's Cloud Wars Minute, I look at ServiceNow's new Autonomous Workforce and what it means for the future of the digital workforce. Highlights 00:03 — As companies become more familiar with the scope and capabilities of agentic AI, they're seeking more efficient ways to integrate these features into their workflows. And in line with this trend, ServiceNow has launched the Autonomous Workforce: teams of AI specialists that will enhance teams with domain-specific AI knowledge. 00:29 — So how does the Autonomous Workforce operate in practice? Well, the AI specialists deployed by the system have defined roles and work alongside human team members. ServiceNow explains that this shift represents a move away from AI agents that complete individual tasks to teams of AI specialists that take on specific roles. 00:57 — These specialists execute entire workflows from start to finish autonomously. Teams can onboard pre-skilled AI specialists with just a few clicks. These specialists are familiar with their roles, permissions, and, crucially, the historical enterprise context. Companies can scale the scope of the specialists on demand to match spikes in activity. 01:20 — The first out-of-the-box specialist is theLevel 1 Service Desk AI Specialist which can autonomously diagnose and resolve typical IT support requests like password resets or network troubleshooting. Proof of concept for this new system lies with ServiceNow, where the Autonomous Workforce is already handling over 90% of employee IT requests. 02:01 — What's truly remarkable is the redefinition of the work of the digital workforce. Having a context-aware, independent worker for specific tasks is a really outstanding achievement and development. It embodies the futuristic vision of a robotic worker and, in reality, is somewhat more streamlined than many of the widely dispersed agentic systems that I've come across today. Visit Cloud Wars for more.

Larry Stefanki has coached them all: John McEnroe, Marcelo Rios, Tim Henman, Fernando Gonzalez, and of course, Andy Roddick. Today, Larry joins Andy and Jon Wertheim to pull back the curtain on the world of elite coaching, why Carlos Alcaraz is the closest thing to Bjorn Borg, and some funny stories from coaching Andy. From winning Indian Wells in 1985 as a wildcard to managing the biggest "psychos" in tennis history, Larry breaks down the mental discipline required to reach World No. 1. Read here for more on Larry Stefanki: https://www.palmspringslife.com/history/the-wild-card-larry-stefankis-1985-la-quinta-win-that-launched-a-no-1-tennis-coaching-career/

Charles is joined by Winthrop Capital Management CIO Adam Coons to discuss why AI and an aging population create long-term deflationary risks, how a "K-shaped" economy supports luxury retail names,, and why software leaders like Intuit and ServiceNow are attractive long-term plays as AI acts as a business model enhancer. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Join Kyle, Nader, Vibhu, and swyx live at NVIDIA GTC next week!Now that AIE Europe tix are ~sold out, our attention turns to Miami and World's Fair!The definitive AI Accelerator chip company has more than 10xed this AI Summer:And is now a $4.4 trillion megacorp… that is somehow still moving like a startup. We are blessed to have a unique relationship with our first ever NVIDIA guests: Kyle Kranen who gave a great inference keynote at the first World's Fair and is one of the leading architects of NVIDIA Dynamo (a Datacenter scale inference framework supporting SGLang, TRT-LLM, vLLM), and Nader Khalil, a friend of swyx from our days in Celo in The Arena, who has been drawing developers at GTC since before they were even a glimmer in the eye of NVIDIA:Nader discusses how NVIDIA Brev has drastically reduced the barriers to entry for developers to get a top of the line GPU up and running, and Kyle explains NVIDIA Dynamo as a data center scale inference engine that optimizes serving by scaling out, leveraging techniques like prefill/decode disaggregation, scheduling, and Kubernetes-based orchestration, framed around cost, latency, and quality tradeoffs. We also dive into Jensen's “SOL” (Speed of Light) first-principles urgency concept, long-context limits and model/hardware co-design, internal model APIs (https://build.nvidia.com), and upcoming Dynamo and agent sessions at GTC.Full Video pod on YouTubeTimestamps00:00 Agent Security Basics00:39 Podcast Welcome and Guests07:19 Acquisition and DevEx Shift13:48 SOL Culture and Dynamo Setup27:38 Why Scale Out Wins29:02 Scale Up Limits Explained30:24 From Laptop to Multi Node33:07 Cost Quality Latency Tradeoffs38:42 Disaggregation Prefill vs Decode41:05 Kubernetes Scaling with Grove43:20 Context Length and Co Design57:34 Security Meets Agents58:01 Agent Permissions Model59:10 Build Nvidia Inference Gateway01:01:52 Hackathons And Autonomy Dreams01:10:26 Local GPUs And Scaling Inference01:15:31 Long Running Agents And SF ReflectionsTranscriptAgent Security BasicsNader: Agents can do three things. They can access your files, they can access the internet, and then now they can write custom code and execute it. You literally only let an agent do two of those three things. If you can access your files and you can write custom code, you don't want internet access because that's one to see full vulnerability, right?If you have access to internet and your file system, you should know the full scope of what that agent's capable of doing. Otherwise, now we can get injected or something that can happen. And so that's a lot of what we've been thinking about is like, you know, how do we both enable this because it's clearly the future.But then also, you know, what, what are these enforcement points that we can start to like protect?swyx: All right.Podcast Welcome and Guestsswyx: Welcome to the Lean Space podcast in the Chromo studio. Welcome to all the guests here. Uh, we are back with our guest host Viu. Welcome. Good to have you back. And our friends, uh, Netter and Kyle from Nvidia. Welcome.Kyle: Yeah, thanks for having us.swyx: Yeah, thank you. Actually, I don't even know your titles.Uh, I know you're like architect something of Dynamo.Kyle: Yeah. I, I'm one of the engineering leaders [00:01:00] and a architects of Dynamo.swyx: And you're director of something and developers, developer tech.Nader: Yeah.swyx: You're the developers, developers, developers guy at nvidia,Nader: open source agent marketing, brev,swyx: and likeNader: Devrel tools and stuff.swyx: Yeah. BeenNader: the focus.swyx: And we're, we're kind of recording this ahead of Nvidia, GTC, which is coming to town, uh, again, uh, or taking over town, uh, which, uh, which we'll all be at. Um, and we'll talk a little bit about your sessions and stuff. Yeah.Nader: We're super excited for it.GTC Booth Stunt Storiesswyx: One of my favorite memories for Nader, like you always do like marketing stunts and like while you were at Rev, you like had this surfboard that you like, went down to GTC with and like, NA Nvidia apparently, like did so much that they bought you.Like what, what was that like? What was that?Nader: Yeah. Yeah, we, we, um. Our logo was a chaka. We, we, uh, we were always just kind of like trying to keep true to who we were. I think, you know, some stuff, startups, you're like trying to pretend that you're a bigger, more mature company than you are. And it was actually Evan Conrad from SF Compute who was just like, you guys are like previousswyx: guest.Yeah.Nader: Amazing. Oh, really? Amazing. Yeah. He was just like, guys, you're two dudes in the room. Why are you [00:02:00] pretending that you're not? Uh, and so then we were like, okay, let's make the logo a shaka. We brought surfboards to our booth to GTC and the energy was great. Yeah. Some palm trees too. They,Kyle: they actually poked out over like the, the walls so you could, you could see the bread booth.Oh, that's so funny. AndNader: no one else,Kyle: just from very far away.Nader: Oh, so you remember it backKyle: then? Yeah I remember it pre-acquisition. I was like, oh, those guys look cool,Nader: dude. That makes sense. ‘cause uh, we, so we signed up really last minute, and so we had the last booth. It was all the way in the corner. And so I was, I was worried that no one was gonna come.So that's why we had like the palm trees. We really came in with the surfboards. We even had one of our investors bring her dog and then she was just like walking the dog around to try to like, bring energy towards our booth. Yeah.swyx: Steph.Kyle: Yeah. Yeah, she's the best,swyx: you know, as a conference organizer, I love that.Right? Like, it's like everyone who sponsors a conference comes, does their booth. They're like, we are changing the future of ai or something, some generic b******t and like, no, like actually try to stand out, make it fun, right? And people still remember it after three years.Nader: Yeah. Yeah. You know what's so funny?I'll, I'll send, I'll give you this clip if you wanna, if you wanna add it [00:03:00] in, but, uh, my wife was at the time fiance, she was in medical school and she came to help us. ‘cause it was like a big moment for us. And so we, we bought this cricket, it's like a vinyl, like a vinyl, uh, printer. ‘cause like, how else are we gonna label the surfboard?So, we got a surfboard, luckily was able to purchase that on the company card. We got a cricket and it was just like fine tuning for enterprises or something like that, that we put on the. On the surfboard and it's 1:00 AM the day before we go to GTC. She's helping me put these like vinyl stickers on.And she goes, you son of, she's like, if you pull this off, you son of a b***h. And so, uh, right. Pretty much after the acquisition, I stitched that with the mag music acquisition. I sent it to our family group chat. Ohswyx: Yeah. No, well, she, she made a good choice there. Was that like basically the origin story for Launchable is that we, it was, and maybe we should explain what Brev is andNader: Yeah.Yeah. Uh, I mean, brev is just, it's a developer tool that makes it really easy to get a GPU. So we connect a bunch of different GPU sources. So the basics of it is like, how quickly can we SSH you into a G, into a GPU and whenever we would talk to users, they wanted A GPU. They wanted an A 100. And if you go to like any cloud [00:04:00] provisioning page, usually it's like three pages of forms or in the forms somewhere there's a dropdown.And in the dropdown there's some weird code that you know to translate to an A 100. And I remember just thinking like. Every time someone says they want an A 100, like the piece of text that they're telling me that they want is like, stuffed away in the corner. Yeah. And so we were like, what if the biggest piece of text was what the user's asking for?And so when you go to Brev, it's just big GPU chips with the type that you want withswyx: beautiful animations that you worked on pre, like pre you can, like, now you can just prompt it. But back in the day. Yeah. Yeah. Those were handcraft, handcrafted artisanal code.Nader: Yeah. I was actually really proud of that because, uh, it was an, i I made it in Figma.Yeah. And then I found, I was like really struggling to figure out how to turn it from like Figma to react. So what it actually is, is just an SVG and I, I have all the styles and so when you change the chip, whether it's like active or not it changes the SVG code and that somehow like renders like, looks like it's animating, but it, we just had the transition slow, but it's just like the, a JavaScript function to change the like underlying SVG.Yeah. And that was how I ended up like figuring out how to move it from from Figma. But yeah, that's Art Artisan. [00:05:00]Kyle: Speaking of marketing stunts though, he actually used those SVGs. Or kind of use those SVGs to make these cards.Nader: Oh yeah. LikeKyle: a GPU gift card Yes. That he handed out everywhere. That was actually my first impression of thatNader: one.Yeah,swyx: yeah, yeah.Nader: Yeah.swyx: I think I still have one of them.Nader: They look great.Kyle: Yeah.Nader: I have a ton of them still actually in our garage, which just, they don't have labels. We should honestly like bring, bring them back. But, um, I found this old printing press here, actually just around the corner on Ven ness. And it's a third generation San Francisco shop.And so I come in an excited startup founder trying to like, and they just have this crazy old machinery and I'm in awe. ‘cause the the whole building is so physical. Like you're seeing these machines, they have like pedals to like move these saws and whatever. I don't know what this machinery is, but I saw all three generations.Like there's like the grandpa, the father and the son, and the son was like, around my age. Well,swyx: it's like a holy, holy trinity.Nader: It's funny because we, so I just took the same SVG and we just like printed it and it's foil printing, so they make a a, a mold. That's like an inverse of like the A 100 and then they put the foil on it [00:06:00] and then they press it into the paper.And I remember once we got them, he was like, Hey, don't forget about us. You know, I guess like early Apple and Cisco's first business cards were all made there. And so he was like, yeah, we, we get like the startup businesses but then as they mature, they kind of go somewhere else. And so I actually, I think we were talking with marketing about like using them for some, we should go back and make some cards.swyx: Yeah, yeah, yeah. You know, I remember, you know, as a very, very small breadth investor, I was like, why are we spending time like, doing these like stunts for GPUs? Like, you know, I think like as a, you know, typical like cloud hard hardware person, you go into an AWS you pick like T five X xl, whatever, and it's just like from a list and you look at the specs like, why animate this GP?And, and I, I do think like it just shows the level of care that goes throughout birth and Yeah. And now, and also the, and,Nader: and Nvidia. I think that's what the, the thing that struck me most when we first came in was like the amount of passion that everyone has. Like, I think, um, you know, you talk to, you talk to Kyle, you talk to, like, every VP that I've met at Nvidia goes so close to the metal.Like, I remember it was almost a year ago, and like my VP asked me, he's like, Hey, [00:07:00] what's cursor? And like, are you using it? And if so, why? Surprised at this, and he downloaded Cursor and he was asking me to help him like, use it. And I thought that was, uh, or like, just show him what he, you know, why we were using it.And so, the amount of care that I think everyone has and the passion, appreciate, passion and appreciation for the moment. Right. This is a very unique time. So it's really cool to see everyone really like, uh, appreciate that.swyx: Yeah.Acquisition and DevEx Shiftswyx: One thing I wanted to do before we move over to sort of like research topics and, uh, the, the stuff that Kyle's working on is just tell the story of the acquisition, right?Like, not many people have been, been through an acquisition with Nvidia. What's it like? Uh, what, yeah, just anything you'd like to say.Nader: It's a crazy experience. I think, uh, you know, we were the thing that was the most exciting for us was. Our goal was just to make it easier for developers.We wanted to find access to GPUs, make it easier to do that. And then all, oh, actually your question about launchable. So launchable was just make one click exper, like one click deploys for any software on top of the GPU. Mm-hmm. And so what we really liked about Nvidia was that it felt like we just got a lot more resources to do all of that.I think, uh, you [00:08:00] know, NVIDIA's goal is to make things as easy for developers as possible. So there was a really nice like synergy there. I think that, you know, when it comes to like an acquisition, I think the amount that the soul of the products align, I think is gonna be. Is going speak to the success of the acquisition.Yeah. And so it in many ways feels like we're home. This is a really great outcome for us. Like we you know, I love brev.nvidia.com. Like you should, you should use it's, it's theKyle: front page for GPUs.Nader: Yeah. Yeah. If you want GP views,Kyle: you go there, getswyx: it there, and it's like internally is growing very quickly.I, I don't remember You said some stats there.Nader: Yeah, yeah, yeah. It's, uh, I, I wish I had the exact numbers, but like internally, externally, it's been growing really quickly. We've been working with a bunch of partners with a bunch of different customers and ISVs, if you have a solution that you want someone that runs on the GPU and you want people to use it quickly, we can bundle it up, uh, in a launchable and make it a one click run.If you're doing things and you want just like a sandbox or something to run on, right. Like open claw. Huge moment. Super exciting. Our, uh, and we'll talk into it more, but. You know, internally, people wanna run this, and you, we know we have to be really careful from the security implications. Do we let this run on the corporate network?Security's guidance was, Hey, [00:09:00] run this on breath, it's in, you know, it's, it's, it's a vm, it's sitting in the cloud, it's off the corporate network. It's isolated. And so that's been our stance internally and externally about how to even run something like open call while we figure out how to run these things securely.But yeah,swyx: I think there's also like, you almost like we're the right team at the right time when Nvidia is starting to invest a lot more in developer experience or whatever you call it. Yeah. Uh, UX or I don't know what you call it, like software. Like obviously NVIDIA is always invested in software, but like, there's like, this is like a different audience.Yeah. It's aNader: widerKyle: developer base.swyx: Yeah. Right.Nader: Yeah. Yeah. You know, it's funny, it's like, it's not, uh,swyx: so like, what, what is it called internally? What, what is this that people should be aware that is going on there?Nader: Uh, what, like developer experienceswyx: or, yeah, yeah. Is it's called just developer experience or is there like a broader strategy hereNader: in Nvidia?Um, Nvidia always wants to make a good developer experience. The thing is and a lot of the technology is just really complicated. Like, it's not, it's uh, you know, I think, um. The thing that's been really growing or the AI's growing is having a huge moment, not [00:10:00] because like, let's say data scientists in 2018, were quiet then and are much louder now.The pie is com, right? There's a whole bunch of new audiences. My mom's wondering what she's doing. My sister's learned, like taught herself how to code. Like the, um, you know, I, I actually think just generally AI's a big equalizer and you're seeing a more like technologically literate society, I guess.Like everyone's, everyone's learning how to code. Uh, there isn't really an excuse for that. And so building a good UX means that you really understand who your end user is. And when your end user becomes such a wide, uh, variety of people, then you have to almost like reinvent the practice, right? Yeah. You haveKyle: to, and actually build more developer ux, right?Because the, there are tiers of developer base that were added. You know, the, the hackers that are building on top of open claw, right? For example, have never used gpu. They don't know what kuda is. They, they, they just want to run something.Nader: Yeah.Kyle: You need new UX that is not just. Hey, you know, how do you program something in Cuda and run it?And then, and then we built, you know, like when Deep Learning was getting big, we built, we built Torch and, and, but so recently the amount of like [00:11:00] layers that are added to that developer stack has just exploded because AI has become ubiquitous. Everyone's using it in different ways. Yeah. It'sNader: moving fast in every direction.Vertical, horizontal.Vibhu: Yeah. You guys, you even take it down to hardware, like the DGX Spark, you know, it's, it's basically the same system as just throwing it up on big GPU cluster.Nader: Yeah, yeah, yeah. It's amazing. Blackwell.swyx: Yeah. Uh, we saw the preview at the last year's GTC and that was one of the better performing, uh, videos so far, and video coverage so far.Awesome. This will beat it. Um,Nader: that wasswyx: actually, we have fingersNader: crossed. Yeah.DGX Spark and Remote AccessNader: Even when Grace Blackwell or when, um, uh, DGX Spark was first coming out getting to be involved in that from the beginning of the developer experience. And it just comes back to what youswyx: were involved.Nader: Yeah. St. St.swyx: Mars.Nader: Yeah. Yeah. I mean from, it was just like, I, I got an email, we just got thrown into the loop and suddenly yeah, I, it was actually really funny ‘cause I'm still pretty fresh from the acquisition and I'm, I'm getting an email from a bunch of the engineering VPs about like, the new hardware, GPU chip, like we're, or not chip, but just GPU system that we're putting out.And I'm like, okay, cool. Matters. Now involved with this for the ux, I'm like. What am I gonna do [00:12:00] here? So, I remember the first meeting, I was just like kind of quiet as I was hearing engineering VPs talk about what this box could be, what it could do, how we should use it. And I remember, uh, one of the first ideas that people were idea was like, oh, the first thing that it was like, I think a quote was like, the first thing someone's gonna wanna do with this is get two of them and run a Kubernetes cluster on top of them.And I was like, oh, I think I know why I'm here. I was like, the first thing we're doing is easy. SSH into the machine. And then, and you know, just kind of like scoping it down of like, once you can do that every, you, like the person who wants to run a Kubernetes cluster onto Sparks has a higher propensity for pain, then, then you know someone who buys it and wants to run open Claw right now, right?If you can make sure that that's as effortless as possible, then the rest becomes easy. So there's a tool called Nvidia Sync. It just makes the SSH connection really simple. So, you know, if you think about it like. If you have a Mac, uh, or a PC or whatever, if you have a laptop and you buy this GPU and you want to use it, you should be able to use it like it's A-A-G-P-U in the cloud, right?Um, but there's all this friction of like, how do you actually get into that? That's part of [00:13:00] Revs value proposition is just, you know, there's a CLI that wraps SSH and makes it simple. And so our goal is just get you into that machine really easily. And one thing we just launched at CES, it's in, it's still in like early access.We're ironing out some kinks, but it should be ready by GTC. You can register your spark on Brev. And so now if youswyx: like remote managed yeah, local hardware. Single pane of glass. Yeah. Yeah. Because Brev can already manage other clouds anyway, right?Vibhu: Yeah, yeah. And you use the spark on Brev as well, right?Nader: Yeah. But yeah, exactly. So, so you, you, so you, you set it up at home you can run the command on it, and then it gets it's essentially it'll appear in your Brev account, and then you can take your laptop to a Starbucks or to a cafe, and you'll continue to use your, you can continue use your spark just like any other cloud node on Brev.Yeah. Yeah. And it's just like a pre-provisioned centerswyx: in yourNader: home. Yeah, exactly.swyx: Yeah. Yeah.Vibhu: Tiny little data center.Nader: Tiny little, the size ofVibhu: your phone.SOL Culture and Dynamo Setupswyx: One more thing before we move on to Kyle. Just have so many Jensen stories and I just love, love mining Jensen stories. Uh, my favorite so far is SOL. Uh, what is, yeah, what is S-O-L-S-O-LNader: is actually, i, I think [00:14:00] of all the lessons I've learned, that one's definitely my favorite.Kyle: It'll always stick with you.Nader: Yeah. Yeah. I, you know, in your startup, everything's existential, right? Like we've, we've run out of money. We were like, on the risk of, of losing payroll, we've had to contract our team because we l ran outta money. And so like, um, because of that you're really always forcing yourself to I to like understand the root cause of everything.If you get a date, if you get a timeline, you know exactly why that date or timeline is there. You're, you're pushing every boundary and like, you're not just say, you're not just accepting like a, a no. Just because. And so as you start to introduce more layers, as you start to become a much larger organization, SOL is is essentially like what is the physics, right?The speed of light moves at a certain speed. So if flight's moving some slower, then you know something's in the way. So before trying to like layer reality back in of like, why can't this be delivered at some date? Let's just understand the physics. What is the theoretical limit to like, uh, how fast this can go?And then start to tell me why. ‘cause otherwise people will start telling you why something can't be done. But actually I think any great leader's goal is just to create urgency. Yeah. [00:15:00] There's an infiniteKyle: create compelling events, right?Nader: Yeah.Kyle: Yeah. So l is a term video is used to instigate a compelling event.You say this is done. How do we get there? What is the minimum? As much as necessary, as little as possible thing that it takes for us to get exactly here and. It helps you just break through a bunch of noise.swyx: Yeah.Kyle: Instantly.swyx: One thing I'm unclear about is, can only Jensen use the SOL card? Like, oh, no, no, no.Not everyone get the b******t out because obviously it's Jensen, but like, can someone else be like, no, likeKyle: frontline engineers use it.Nader: Yeah. Every, I think it's not so much about like, get the b******t out. It's like, it's like, give me the root understanding, right? Like, if you tell me something takes three weeks, it like, well, what's the first principles?Yeah, the first principles. It's like, what's the, what? Like why is it three weeks? What is the actual yeah. What's the actual limit of why this is gonna take three weeks? If you're gonna, if you, if let's say you wanted to buy a new computer and someone told you it's gonna be here in five days, what's the SOL?Well, like the SOL is like, I could walk into a Best Buy and pick it up for you. Right? So then anything that's like beyond that is, and is that practical? Is that how we're gonna, you know, let's say give everyone in the [00:16:00] company a laptop, like obviously not. So then like that's the SOL and then it's like, okay, well if we have to get more than 10, suddenly there might be some, right?And so now we can kind of piece the reality back.swyx: So, so this is the. Paul Graham do things that don't scale. Yeah. And this is also the, what people would now call behi agency. Yeah.Kyle: It's actually really interesting because there's a, there's a second hardware angle to SOL that like doesn't come up for all the org sol is used like culturally at aswyx: media for everything.I'm also mining for like, I think that can be annoying sometimes. And like someone keeps going IOO you and you're like, guys, like we have to be stable. We have to, we to f*****g plan. Yeah.Kyle: It's an interesting balance.Nader: Yeah. I encounter that with like, actually just with, with Alec, right? ‘cause we, we have a new conference so we need to launch, we have, we have goals of what we wanna launch by, uh, by the conference and like, yeah.At the end of the day, where isswyx: this GTC?Nader: Um, well this is like, so we, I mean we did it for CES, we did for GT CDC before that we're doing it for GTC San Jose. So I mean, like every, you know, we have a new moment. Um, and we want to launch something. Yeah. And we want to do so at SOL and that does mean that some, there's some level of prioritization that needs [00:17:00] to happen.And so it, it is difficult, right? I think, um, you have to be careful with what you're pushing. You know, stability is important and that should be factored into S-O-L-S-O-L isn't just like, build everything and let it break, you know, that, that's part of the conversation. So as you're laying, layering in all the details, one of them might be, Hey, we could build this, but then it's not gonna be stable for X, y, z reasons.And so that was like, one of our conversations for CES was, you know, hey, like we, we can get this into early access registering your spark with brev. But there are a lot of things that we need to do in order to feel really comfortable from a security perspective, right? There's a lot of networking involved before we deliver that to users.So it's like, okay. Let's get this to a point where we can at least let people experiment with it. We had it in a booth, we had it in Jensen's keynote, and then let's go iron out all the networking kinks. And that's not easy. And so, uh, that can come later. And so that was the way that we layered that back in.Yeah. ButKyle: It's not really about saying like, you don't have to do the, the maintenance or operational work. It's more about saying, you know, it's kind of like [00:18:00] highlights how progress is incremental, right? Like, what is the minimum thing that we can get to. And then there's SOL for like every component after that.But there's the SOL to get you, get you to the, the starting line. And that, that's usually how it's asked. Yeah. On the other side, you know, like SOL came out of like hardware at Nvidia. Right. So SOL is like literally if we ran the accelerator or the GPU with like at basically full speed with like no other constraints, like how FAST would be able to make a program go.swyx: Yeah. Yeah. Right.Kyle: Soswyx: in, in training that like, you know, then you work back to like some percentage of like MFU for example.Kyle: Yeah, that's a, that's a great example. So like, there's an, there's an S-O-L-M-F-U, and then there's like, you know, what's practically achievable.swyx: Cool. Should we move on to sort of, uh, Kyle's side?Uh, Kyle, you're coming more from the data science world. And, uh, I, I mean I always, whenever, whenever I meet someone who's done working in tabular stuff, graph neural networks, time series, these are basically when I go to new reps, I go to ICML, I walk the back halls. There's always like a small group of graph people.Yes. Absolute small group of tabular people. [00:19:00] And like, there's no one there. And like, it's very like, you know what I mean? Like, yeah, no, like it's, it's important interesting work if you care about solving the problems that they solve.Kyle: Yeah.swyx: But everyone else is just LMS all the time.Kyle: Yeah. I mean it's like, it's like the black hole, right?Has the event horizon reached this yet in nerves? Um,swyx: but like, you know, those are, those are transformers too. Yeah. And, and those are also like interesting things. Anyway, uh, I just wanted to spend a little bit of time on, on those, that background before we go into Dynamo, uh, proper.Kyle: Yeah, sure. I took a different path to Nvidia than that, or I joined six years ago, seven, if you count, when I was an intern.So I joined Nvidia, like right outta college. And the first thing I jumped into was not what I'd done in, during internship, which was like, you know, like some stuff for autonomous vehicles, like heavyweight object detection. I jumped into like, you know, something, I'm like, recommenders, this is popular. Andswyx: yeah, he did RexiKyle: as well.Yeah, Rexi. Yeah. I mean that, that was the taboo data at the time, right? You have tables of like, audience qualities and item qualities, and you're trying to figure out like which member of [00:20:00] the audience matches which item or, or more practically which item matches which member of the audience. And at the time, really it was like we were trying to enable.Uh, recommender, which had historically been like a little bit of a CP based workflow into something that like, ran really well in GPUs. And it's since been done. Like there are a bunch of libraries for Axis that run on GPUs. Uh, the common models like Deeplearning recommendation model, which came outta meta and the wide and deep model, which was used or was released by Google were very accelerated by GPUs using, you know, the fast HBM on the chips, especially to do, you know, vector lookups.But it was very interesting at the time and super, super relevant because like we were starting to get like. This explosion of feeds and things that required rec recommenders to just actively be on all the time. And sort of transitioned that a little bit towards graph neural networks when I discovered them because I was like, okay, you can actually use graphical neural networks to represent like, relationships between people, items, concepts, and that, that interested me.So I jumped into that at [00:21:00] Nvidia and, and got really involved for like two-ish years.swyx: Yeah. Uh, and something I learned from Brian Zaro Yeah. Is that you can just kind of choose your own path in Nvidia.Kyle: Oh my God. Yeah.swyx: Which is not a normal big Corp thing. Yeah. Like you, you have a lane, you stay in your lane.Nader: I think probably the reason why I enjoy being in a, a big company, the mission is the boss probably from a startup guy. Yeah. The missionswyx: is the boss.Nader: Yeah. Uh, it feels like a big game of pickup basketball. Like, you know, if you play one, if you wanna play basketball, you just go up to the court and you're like, Hey look, we're gonna play this game and we need three.Yeah. And you just like find your three. That's honestly for every new initiative that's what it feels like. Yeah.Vibhu: It also like shows, right? Like Nvidia. Just releasing state-of-the-art stuff in every domain. Yeah. Like, okay, you expect foundation models with Nemo tron voice just randomly parakeet.Call parakeet just comes out another one, uh, voice. TheKyle: video voice team has always been producing.Vibhu: Yeah. There's always just every other domain of paper that comes out, dataset that comes out. It's like, I mean, it also stems back to what Nvidia has to do, right? You have to make chips years before they're actually produced.Right? So you need to know, you need to really [00:22:00] focus. TheKyle: design process starts likeVibhu: exactlyKyle: three to five years before the chip gets to the market.Vibhu: Yeah. I, I'm curious more about what that's like, right? So like, you have specialist teams. Is it just like, you know, people find an interest, you go in, you go deep on whatever, and that kind of feeds back into, you know, okay, we, we expect predictions.Like the internals at Nvidia must be crazy. Right? You know? Yeah. Yeah. You know, you, you must. Not even without selling to people, you have your own predictions of where things are going. Yeah. And they're very based, very grounded. Right?Kyle: Yeah. It, it, it's really interesting. So there's like two things that I think that Amed does, which are quite interesting.Uh, one is like, we really index into passion. There's a big. Sort of organizational top sound push to like ensure that people are working on the things that they're passionate about. So if someone proposes something that's interesting, many times they can just email someone like way up the chain that they would find this relevant and say like, Hey, can I go work on this?Nader: It's actually like I worked at a, a big company for a couple years before, uh, starting on my startup journey and like, it felt very weird if you were to like email out of chain, if that makes [00:23:00] sense. Yeah. The emails at Nvidia are like mosh pitsswyx: shoot,Nader: and it's just like 60 people, just whatever. And like they're, there's this,swyx: they got messy like, reply all you,Nader: oh, it's in, it's insane.It's insane. They justKyle: help. You know, Maxim,Nader: the context. But, but that's actually like, I've actually, so this is a weird thing where I used to be like, why would we send emails? We have Slack. I am the entire, I'm the exact opposite. I feel so bad for anyone who's like messaging me on Slack ‘cause I'm so unresponsive.swyx: Your emailNader: Maxi, email Maxim. I'm email maxing Now email is a different, email is perfect because man, we can't work together. I'm email is great, right? Because important threads get bumped back up, right? Yeah, yeah. Um, and so Slack doesn't do that. So I just have like this casino going off on the right or on the left and like, I don't know which thread was from where or what, but like the threads get And then also just like the subject, so you can have like working threads.I think what's difficult is like when you're small, if you're just not 40,000 people I think Slack will work fine, but there's, I don't know what the inflection point is. There is gonna be a point where that becomes really messy and you'll actually prefer having email. ‘cause you can have working threads.You can cc more than nine people in a thread.Kyle: You can fork stuff.Nader: You can [00:24:00] fork stuff, which is super nice and just like y Yeah. And so, but that is part of where you can propose a plan. You can also just. Start, honestly, momentum's the only authority, right? So like, if you can just start, start to make a little bit of progress and show someone something, and then they can try it.That's, I think what's been, you know, I think the most effective way to push anything for forward. And that's both at Nvidia and I think just generally.Kyle: Yeah, there's, there's the other concept that like is explored a lot at Nvidia, which is this idea of a zero billion dollar business. Like market creation is a big thing at Nvidia.Like,swyx: oh, you want to go and start a zero billion dollar business?Kyle: Jensen says, we are completely happy investing in zero billion dollar markets. We don't care if this creates revenue. It's important for us to know about this market. We think it will be important in the future. It can be zero billion dollars for a while.I'm probably minging as words here for, but like, you know, like, I'll give an example. NVIDIA's been working on autonomous driving for a a long time,swyx: like an Nvidia car.Kyle: No, they, they'veVibhu: used the Mercedes, right? They're around the HQ and I think it finally just got licensed out. Now they're starting to be used quite a [00:25:00] bit.For 10 years you've been seeing Mercedes with Nvidia logos driving.Kyle: If you're in like the South San Santa Clara, it's, it's actually from South. Yeah. So, um. Zero billion dollar markets are, are a thing like, you know, Jensen,swyx: I mean, okay, look, cars are not a zero billion dollar market. But yeah, that's a bad example.Nader: I think, I think he's, he's messaging, uh, zero today, but, or even like internally, right? Like, like it's like, uh, an org doesn't have to ruthlessly find revenue very quickly to justify their existence. Right. Like a lot of the important research, a lot of the important technology being developed that, that's kind ofKyle: where research, research is very ide ideologically free at Nvidia.Yeah. Like they can pursue things that they wereswyx: Were you research officially?Kyle: I was never in research. Officially. I was always in engineering. Yeah. We in, I'm in an org called Deep Warning Algorithms, which is basically just how do we make things that are relevant to deep warning go fast.swyx: That sounds freaking cool.Vibhu: And I think a lot of that is underappreciated, right? Like time series. This week Google put out time. FF paper. Yeah. A new time series, paper res. Uh, Symantec, ID [00:26:00] started applying Transformers LMS to Yes. Rec system. Yes. And when you think the scale of companies deploying these right. Amazon recommendations, Google web search, it's like, it's huge scale andKyle: Yeah.Vibhu: You want fast?Kyle: Yeah. Yeah. Yeah. Actually it's, it, I, there's a fun moment that brought me like full circle. Like, uh, Amazon Ads recently gave a talk where they talked about using Dynamo for generative recommendation, which was like super, like weirdly cathartic for me. I'm like, oh my God. I've, I've supplanted what I was working on.Like, I, you're using LMS now to do what I was doing five years ago.swyx: Yeah. Amazing. And let's go right into Dynamo. Uh, maybe introduce Yeah, sure. To the top down and Yeah.Kyle: I think at this point a lot of people are familiar with the term of inference. Like funnily enough, like I went from, you know, inference being like a really niche topic to being something that's like discussed on like normal people's Twitter feeds.It's,Nader: it's on billboardsKyle: here now. Yeah. Very, very strange. Driving, driving, seeing just an inference ad on 1 0 1 inference at scale is becoming a lot more important. Uh, we have these moments like, you know, open claw where you have these [00:27:00] agents that take lots and lots of tokens, but produce, incredible results.There are many different aspects of test time scaling so that, you know, you can use more inference to generate a better result than if you were to use like a short amount of inference. There's reasoning, there's quiring, there's, adding agency to the model, allowing it to call tools and use skills.Dyno sort came about at Nvidia. Because myself and a couple others were, were sort of talking about the, these concepts that like, you know, you have inference engines like VLMS, shelan, tenor, TLM and they have like one single copy. They, they, they sort of think about like things as like one single copy, like one replica, right?Why Scale Out WinsKyle: Like one version of the model. But when you're actually serving things at scale, you can't just scale up that replica because you end up with like performance problems. There's a scaling limit to scaling up replicas. So you actually have to scale out to use a, maybe some Kubernetes type terminology.We kind of realized that there was like. A lot of potential optimization that we could do in scaling out and building systems for data [00:28:00] center scale inference. So Dynamo is this data center scale inference engine that sits on top of the frameworks like VLM Shilling and 10 T lm and just makes things go faster because you can leverage the economy of scale.The fact that you have KV cash, which we can define a little bit later, uh, in all these machines that is like unique and you wanna figure out like the ways to maximize your cash hits or you want to employ new techniques in inference like disaggregation, which Dynamo had introduced to the world in, in, in March, not introduced, it was a academic talk, but beforehand.But we are, you know, one of the first frameworks to start, supporting it. And we wanna like, sort of combine all these techniques into sort of a modular framework that allows you to. Accelerate your inference at scale.Nader: By the way, Kyle and I became friends on my first date, Nvidia, and I always loved, ‘cause like he always teaches meswyx: new things.Yeah. By the way, this is why I wanted to put two of you together. I was like, yeah, this is, this is gonna beKyle: good. It's very, it's very different, you know, like we've, we, we've, we've talked to each other a bunch [00:29:00] actually, you asked like, why, why can't we scale up?Nader: Yeah.Scale Up Limits ExplainedNader: model, you said model replicas.Kyle: Yeah. So you, so scale up means assigning moreswyx: heavier?Kyle: Yeah, heavier. Like making things heavier. Yeah, adding more GPUs. Adding more CPUs. Scale out is just like having a barrier saying, I'm gonna duplicate my representation of the model or a representation of this microservice or something, and I'm gonna like, replicate it Many times.Handle, load. And the reason that you can't scale, scale up, uh, past some points is like, you know, there, there, there are sort of hardware bounds and algorithmic bounds on, on that type of scaling. So I'll give you a good example that's like very trivial. Let's say you're on an H 100. The Maxim ENV link domain for H 100, for most Ds H one hundreds is heus, right?So if you scaled up past that, you're gonna have to figure out ways to handle the fact that now for the GPUs to communicate, you have to do it over Infin band, which is still very fast, but is not as fast as ENV link.swyx: Is it like one order of magnitude, like hundreds or,Kyle: it's about an order of magnitude?Yeah. Okay. Um, soswyx: not terrible.Kyle: [00:30:00] Yeah. I, I need to, I need to remember the, the data sheet here, like, I think it's like about 500 gigabytes. Uh, a second unidirectional for ENV link, and about 50 gigabytes a second unidirectional for Infin Band. I, it, it depends on the, the generation.swyx: I just wanna set this up for people who are not familiar with these kinds of like layers and the trash speedVibhu: and all that.Of course.From Laptop to Multi NodeVibhu: Also, maybe even just going like a few steps back before that, like most people are very familiar with. You see a, you know, you can use on your laptop, whatever these steel viol, lm you can just run inference there. All, there's all, you can, youcan run it on thatVibhu: laptop. You can run on laptop.Then you get to, okay, uh, models got pretty big, right? JLM five, they doubled the size, so mm-hmm. Uh, what do you do when you have to go from, okay, I can get 128 gigs of memory. I can run it on a spark. Then you have to go multi GPU. Yeah. Okay. Multi GPU, there's some support there. Now, if I'm a company and I don't have like.I'm not hiring the best researchers for this. Right. But I need to go [00:31:00] multi-node, right? I have a lot of servers. Okay, now there's efficiency problems, right? You can have multiple eight H 100 nodes, but, you know, is that as a, like, how do you do that efficiently?Kyle: Yeah. How do you like represent them? How do you choose how to represent the model?Yeah, exactly right. That's a, that's like a hard question. Everyone asks, how do you size oh, I wanna run GLM five, which just came out new model. There have been like four of them in the past week, by the way, like a bunch of new models.swyx: You know why? Right? Deep seek.Kyle: No comment. Oh. Yeah, but Ggl, LM five, right?We, we have this, new model. It's, it's like a large size, and you have to figure out how to both scale up and scale out, right? Because you have to find the right representation that you care about. Everyone does this differently. Let's be very clear. Everyone figures this out in their own path.Nader: I feel like a lot of AI or ML even is like, is like this. I think people think, you know, I, I was, there was some tweet a few months ago that was like, why hasn't fine tuning as a service taken off? You know, that might be me. It might have been you. Yeah. But people want it to be such an easy recipe to follow.But even like if you look at an ML model and specificKyle: to you Yeah,Nader: yeah.Kyle: And the [00:32:00] model,Nader: the situation, and there's just so much tinkering, right? Like when you see a model that has however many experts in the ME model, it's like, why that many experts? I don't, they, you know, they tried a bunch of things and that one seemed to do better.I think when it comes to how you're serving inference, you know, you have a bunch of decisions to make and there you can always argue that you can take something and make it more optimal. But I think it's this internal calibration and appetite for continued calibration.Vibhu: Yeah. And that doesn't mean like, you know, people aren't taking a shot at this, like tinker from thinking machines, you know?Yeah. RL as a service. Yeah, totally. It's, it also gets even harder when you try to do big model training, right? We're not the best at training Moes, uh, when they're pre-trained. Like we saw this with LAMA three, right? They're trained in such a sparse way that meta knows there's gonna be a bunch of inference done on these, right?They'll open source it, but it's very trained for what meta infrastructure wants, right? They wanna, they wanna inference it a lot. Now the question to basically think about is, okay, say you wanna serve a chat application, a coding copilot, right? You're doing a layer of rl, you're serving a model for X amount of people.Is it a chat model, a coding model? Dynamo, you know, back to that,Kyle: it's [00:33:00] like, yeah, sorry. So you we, we sort of like jumped off of, you know, jumped, uh, on that topic. Everyone has like, their own, own journey.Cost Quality Latency TradeoffsKyle: And I, I like to think of it as defined by like, what is the model you need? What is the accuracy you need?Actually I talked to NA about this earlier. There's three axes you care about. What is the quality that you're able to produce? So like, are you accurate enough or can you complete the task with enough, performance, high enough performance. Yeah, yeah. Uh, there's cost. Can you serve the model or serve your workflow?Because it's not just the model anymore, it's the workflow. It's the multi turn with an agent cheaply enough. And then can you serve it fast enough? And we're seeing all three of these, like, play out, like we saw, we saw new models from OpenAI that you know, are faster. You have like these new fast versions of models.You can change the amount of thinking to change the amount of quality, right? Produce more tokens, but at a higher cost in a, in a higher latency. And really like when you start this journey of like trying to figure out how you wanna host a model, you, you, you think about three things. What is the model I need to serve?How many times do I need to call it? What is the input sequence link was [00:34:00] the, what does the workflow look like on top of it? What is the SLA, what is the latency SLA that I need to achieve? Because there's usually some, this is usually like a constant, you, you know, the SLA that you need to hit and then like you try and find the lowest cost version that hits all of these constraints.Usually, you know, you, you start with those things and you say you, you kind of do like a bit of experimentation across some common configurations. You change the tensor parallel size, which is a form of parallelismVibhu: I take, it goes even deeper first. Gotta think what model.Kyle: Yes, course,ofKyle: course. It's like, it's like a multi-step design process because as you said, you can, you can choose a smaller model and then do more test time scaling and it'll equate the quality of a larger model because you're doing the test time scaling or you're adding a harness or something.So yes, it, it goes way deeper than that. But from the performance perspective, like once you get to the model you need, you need to host, you look at that and you say, Hey. I have this model, I need to serve it at the speed. What is the right configuration for that?Nader: You guys see the recent, uh, there was a paper I just saw like a few days ago that, uh, if you run [00:35:00] the same prompt twice, you're getting like double Just try itagain.Nader: Yeah, exactly.Vibhu: And you get a lot. Yeah. But the, the key thing there is you give the context of the failed try, right? Yeah. So it takes a shot. And this has been like, you know, basic guidance for quite a while. Just try again. ‘cause you know, trying, just try again. Did you try again? All adviceNader: in life.Vibhu: Just, it's a paper from Google, if I'm not mistaken, right?Yeah,Vibhu: yeah. I think it, it's like a seven bas little short paper. Yeah. Yeah. The title's very cute. And it's just like, yeah, just try again. Give it ask context,Kyle: multi-shot. You just like, say like, hey, like, you know, like take, take a little bit more, take a little bit more information, try and fail. Fail.Vibhu: And that basic concept has gone pretty deep.There's like, um, self distillation, rl where you, you do self distillation, you do rl and you have past failure and you know, that gives some signal so people take, try it again. Not strong enough.swyx: Uh, for, for listeners, uh, who listen to here, uh, vivo actually, and I, and we run a second YouTube channel for our paper club where, oh, that's awesome.Vivo just covered this. Yeah. Awesome. Self desolation and all that's, that's why he, to speed [00:36:00] on it.Nader: I'll to check it out.swyx: Yeah. It, it's just a good practice, like everyone needs, like a paper club where like you just read papers together and the social pressure just kind of forces you to just,Nader: we, we,there'sNader: like a big inference.Kyle: ReadingNader: group at a video. I feel so bad every time. I I, he put it on like, on our, he shared it.swyx: One, one ofNader: your guys,swyx: uh, is, is big in that, I forget es han Yeah, yeah,Kyle: es Han's on my team. Actually. Funny. There's a, there's a, there's a employee transfer between us. Han worked for Nater at Brev, and now he, he's on my team.He wasNader: our head of ai. And then, yeah, once we got in, andswyx: because I'm always looking for like, okay, can, can I start at another podcast that only does that thing? Yeah. And, uh, Esan was like, I was trying to like nudge Esan into like, is there something here? I mean, I don't think there's, there's new infant techniques every day.So it's like, it's likeKyle: you would, you would actually be surprised, um, the amount of blog posts you see. And ifswyx: there's a period where it was like, Medusa hydra, what Eagle, like, youKyle: know, now we have new forms of decode, uh, we have new forms of specula, of decoding or new,swyx: what,Kyle: what are youVibhu: excited? And it's exciting when you guys put out something like Tron.‘cause I remember the paper on this Tron three, [00:37:00] uh, the amount of like post train, the on tokens that the GPU rich can just train on. And it, it was a hybrid state space model, right? Yeah.Kyle: It's co-designed for the hardware.Vibhu: Yeah, go design for the hardware. And one of the things was always, you know, the state space models don't scale as well when you do a conversion or whatever the performance.And you guys are like, no, just keep draining. And Nitron shows a lot of that. Yeah.Nader: Also, something cool about Nitron it was released in layers, if you will, very similar to Dynamo. It's, it's, it's essentially it was released as you can, the pre-training, post-training data sets are released. Yeah. The recipes on how to do it are released.The model itself is released. It's full model. You just benefit from us turning on the GPUs. But there are companies like, uh, ServiceNow took the dataset and they trained their own model and we were super excited and like, you know, celebrated that work.ZoomVibhu: different. Zoom is, zoom is CGI, I think, uh, you know, also just to add like a lot of models don't put out based models and if there's that, why is fine tuning not taken off?You know, you can do your own training. Yeah,Kyle: sure.Vibhu: You guys put out based model, I think you put out everything.Nader: I believe I know [00:38:00]swyx: about base. BasicallyVibhu: without baseswyx: basic can be cancelable.Vibhu: Yeah. Base can be cancelable.swyx: Yeah.Vibhu: Safety training.swyx: Did we get a full picture of dymo? I, I don't know if we, what,Nader: what I'd love is you, you mentioned the three axes like break it down of like, you know, what's prefilled decode and like what are the optimizations that we can get with Dynamo?Kyle: Yeah. That, that's, that's, that's a great point. So to summarize on that three axis problem, right, there are three things that determine whether or not something can be done with inference, cost, quality, latency, right? Dynamo is supposed to be there to provide you like the runtime that allows you to pull levers to, you know, mix it up and move around the parade of frontier or the preto surface that determines is this actually possible with inference And AI todayNader: gives you the knobs.Kyle: Yeah, exactly. It gives you the knobs.Disaggregation Prefill vs DecodeKyle: Uh, and one thing that like we, we use a lot in contemporary inference and is, you know, starting to like pick up from, you know, in, in general knowledge is this co concept of disaggregation. So historically. Models would be hosted with a single inference engine. And that inference engine [00:39:00] would ping pong between two phases.There's prefill where you're reading the sequence generating KV cache, which is basically just a set of vectors that represent the sequence. And then using that KV cache to generate new tokens, which is called Decode. And some brilliant researchers across multiple different papers essentially made the realization that if you separate these two phases, you actually gain some benefits.Those benefits are basically a you don't have to worry about step synchronous scheduling. So the way that an inference engine works is you do one step and then you finish it, and then you schedule, you start scheduling the next step there. It's not like fully asynchronous. And the problem with that is you would have, uh, essentially pre-fill and decode are, are actually very different in terms of both their resource requirements and their sometimes their runtime.So you would have like prefill that would like block decode steps because you, you'd still be pre-filing and you couldn't schedule because you know the step has to end. So you remove that scheduling issue and then you also allow you, or you yourself, to like [00:40:00] split the work into two different ki types of pools.So pre-fill typically, and, and this changes as, as model architecture changes. Pre-fill is, right now, compute bound most of the time with the sequence is sufficiently long. It's compute bound. On the decode side because you're doing a full Passover, all the weights and the entire sequence, every time you do a decode step and you're, you don't have the quadratic computation of KV cache, it's usually memory bound because you're retrieving a linear amount of memory and you're doing a linear amount of compute as opposed to prefill where you retrieve a linear amount of memory and then use a quadratic.You know,Nader: it's funny, someone exo Labs did a really cool demo where for the DGX Spark, which has a lot more compute, you can do the pre the compute hungry prefill on a DG X spark and then do the decode on a, on a Mac. Yeah. And soVibhu: that's faster.Nader: Yeah. Yeah.Kyle: So you could, you can do that. You can do machine strat stratification.Nader: Yeah.Kyle: And like with our future generation generations of hardware, we actually announced, like with Reuben, this [00:41:00] new accelerator that is prefilled specific. It's called Reuben, CPX. SoKubernetes Scaling with GroveNader: I have a question when you do the scale out. Yeah. Is scaling out easier with Dynamo? Because when you need a new node, you can dedicate it to either the Prefill or, uh, decode.Kyle: Yeah. So Dynamo actually has like a, a Kubernetes component in it called Grove that allows you to, to do this like crazy scaling specialization. It has like this hot, it's a representation that, I don't wanna go too deep into Kubernetes here, but there was a previous way that you would like launch multi-node work.Uh, it's called Leader Worker Set. It's in the Kubernetes standard, and Leader worker set is great. It served a lot of people super well for a long period of time. But one of the things that it's struggles with is representing a set of cases where you have a multi-node replica that has a pair, right?You know, prefill and decode, or it's not paired, but it has like a second stage that has a ratio that changes over time. And prefill and decode are like two different things as your workload changes, right? The amount of prefill you'll need to do may change. [00:42:00] The amount of decode that you, you'll need to do might change, right?Like, let's say you start getting like insanely long queries, right? That probably means that your prefill scales like harder because you're hitting these, this quadratic scaling growth.swyx: Yeah.And then for listeners, like prefill will be long input. Decode would be long output, for example, right?Kyle: Yeah. So like decode, decode scale. I mean, decode is funny because the amount of tokens that you produce scales with the output length, but the amount of work that you do per step scales with the amount of tokens in the context.swyx: Yes.Kyle: So both scales with the input and the output.swyx: That's true.Kyle: But on the pre-fold view code side, like if.Suddenly, like the amount of work you're doing on the decode side stays about the same or like scales a little bit, and then the prefilled side like jumps up a lot. You actually don't want that ratio to be the same. You want it to change over time. So Dynamo has a set of components that A, tell you how to scale.It tells you how many prefilled workers and decoded workers you, it thinks you should have, and also provides a scheduling API for Kubernetes that allows you to actually represent and affect this scheduling on, on, on your actual [00:43:00] hardware, on your compute infrastructure.Nader: Not gonna lie. I feel a little embarrassed for being proud of my SVG function earlier.swyx: No, itNader: wasreallyKyle: cute. I, Iswyx: likeNader: it's all,swyx: it's all engineering. It's all engineering. Um, that's where I'mKyle: technical.swyx: One thing I'm, I'm kind of just curious about with all with you see at a systems level, everything going on here. Mm-hmm. And we, you know, we're scaling it up in, in multi, in distributed systems.Context Length and Co Designswyx: Um, I think one thing that's like kind of, of the moment right now is people are asking, is there any SOL sort of upper bounds. In terms of like, let's call, just call it context length for one for of a better word, but you can break it down however you like.Nader: Yeah.swyx: I just think like, well, yeah, I mean, like clearly you can engage in hybrid architectures and throw in some state space models in there.All, all you want, but it looks, still looks very attention heavy.Kyle: Yes. Uh, yeah. Long context is attention heavy. I mean, we have these hybrid models, um,swyx: to take and most, most models like cap out at a million contexts and that's it. Yeah. Like for the last two years has been it.Kyle: Yeah. The model hardware context co-design thing that we're seeing these days is actually super [00:44:00] interesting.It's like my, my passion, like my secret side passion. We see models like Kimmy or G-P-T-O-S-S. I'm use these because I, I know specific things about these models. So Kimmy two comes out, right? And it's an interesting model. It's like, like a deep seek style architecture is MLA. It's basically deep seek, scaled like a little bit differently, um, and obviously trained differently as well.But they, they talked about, why they made the design choices for context. Kimmy has more experts, but fewer attention heads, and I believe a slightly smaller attention, uh, like dimension. But I need to remember, I need to check that. Uh, it doesn't matter. But they discussed this actually at length in a blog post on ji, which is like our pu which is like credit puswyx: Yeah.Kyle: Um, in, in China. Chinese red.swyx: Yeah.Kyle: It's, yeah. So it, it's, it's actually an incredible blog post. Uh, like all the mls people in, in, in that, I've seen that on GPU are like very brilliant, but they, they talk about like the creators of Kimi K two [00:45:00] actually like, talked about it on, on, on there in the blog post.And they say, we, we actually did an experiment, right? Attention scales with the number of heads, obviously. Like if you have 64 heads versus 32 heads, you do half the work of attention. You still scale quadratic, but you do half the work. And they made a, a very specific like. Sort of barter in their system, in their architecture, they basically said, Hey, what if we gave it more experts, so we're gonna use more memory capacity.But we keep the amount of activated experts the same. We increase the expert sparsity, so we have fewer experts act. The ratio to of experts activated to number of experts is smaller, and we decrease the number of attention heads.Vibhu: And kind of for context, what the, what we had been seeing was you make models sparser instead.So no one was really touching heads. You're just having, uh,Kyle: well, they, they did, they implicitly made it sparser.Vibhu: Yeah, yeah. For, for Kimmy. They did,Kyle: yes.Vibhu: They also made it sparser. But basically what we were seeing was people were at the level of, okay, there's a sparsity ratio. You want more total parameters, less active, and that's sparsity.[00:46:00]But what you see from papers, like, the labs like moonshot deep seek, they go to the level of, okay, outside of just number of experts, you can also change how many attention heads and less attention layers. More attention. Layers. Layers, yeah. Yes, yes. So, and that's all basically coming back to, just tied together is like hardware model, co-design, which isKyle: hardware model, co model, context, co-design.Vibhu: Yeah.Kyle: Right. Like if you were training a, a model that was like. Really, really short context, uh, or like really is good at super short context tasks. You may like design it in a way such that like you don't care about attention scaling because it hasn't hit that, like the turning point where like the quadratic curve takes over.Nader: How do you consider attention or context as a separate part of the co-design? Like I would imagine hardware or just how I would've thought of it is like hardware model. Co-design would be hardware model context co-designKyle: because the harness and the context that is produced by the harness is a part of the model.Once it's trained in,Vibhu: like even though towards the end you'll do long context, you're not changing architecture through I see. Training. Yeah.Kyle: I mean you can try.swyx: You're saying [00:47:00] everyone's training the harness into the model.Kyle: I would say to some degree, orswyx: there's co-design for harness. I know there's a small amount, but I feel like not everyone has like gone full send on this.Kyle: I think, I think I think it's important to internalize the harness that you think the model will be running. Running into the model.swyx: Yeah. Interesting. Okay. Bash is like the universal harness,Kyle: right? Like I'll, I'll give. An example here, right? I mean, or just like a, like a, it's easy proof, right? If you can train against a harness and you're using that harness for everything, wouldn't you just train with the harness to ensure that you get the best possible quality out of,swyx: Well, the, uh, I, I can provide a counter argument.Yeah, sure. Which is what you wanna provide a generally useful model for other people to plug into their harnesses, right? So if youKyle: Yeah. Harnesses can be open, open source, right?swyx: Yeah. So I mean, that's, that's effectively what's happening with Codex.Kyle: Yeah.swyx: And, but like you may want like a different search tool and then you may have to name it differently or,Nader: I don't know how much people have pushed on this, but can you.Train a model, would it be, have you have people compared training a model for the for the harness versus [00:48:00] like post training forswyx: I think it's the same thing. It's the same thing. It's okay. Just extra post training. INader: see.swyx: And so, I mean, cognition does this course, it does this where you, you just have to like, if your tool is slightly different, um, either force your tool to be like the tool that they train for.Hmm. Or undo their training for their tool and then Oh, that's re retrain. Yeah. It's, it's really annoying and like,Kyle: I would hope that eventually we hit like a certain level of generality with respect to training newswyx: tools. This is not a GI like, it's, this is a really stupid like. Learn my tool b***h.Like, I don't know if, I don't know if I can say that, but like, you know, um, I think what my point kind of is, is that there's, like, I look at slopes of the scaling laws and like, this slope is not working, man. We, we are at a million token con

Realities Remixed, formerly know as Cloud Realities, launches a new season exploring the intersection of people, culture, industry and tech.Business messaging is transforming customer engagement by enabling brands to move conversations into familiar, always‑on messaging platforms. The result for customers is greater convenience, quicker resolutions, and more meaningful, personalized interactions. This week, Dave, Esmee, and Rob are joined by Kathleen Tandy, Global Director and Head of Business Messaging Marketing and WhatsApp for Business at Meta , to explore how companies are using messaging platforms to engage customers, what customers expect from these experiences, and the challenges of scaling messaging in tech.TLDR00:35 – Introduction01:00 –  Hang out: The new Remarkable05:25 – Dig in: Using messaging to enhance customer experiences20:49 – Conversation with Kathleen Tandy55:26 – The passion for college football and championship weekend!GuestKathleen Tandy: https://www.linkedin.com/in/kptandy/HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/ SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:  https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

The Human in the Loop | Ethical AI with Di Le ServicveNow Insights Podcast - hosted By Bobby Brill What does it actually mean to build AI responsibly? Not the buzzword version. The real version. In our latest episode, I sat down with Di Le — AI Ethicist and Human-Centered AI Strategist at ServiceNow — and she broke it down in a way I hadn't heard before. Most people use Ethical AI, Responsible AI, and Human-Centered AI interchangeably, and Di breaks down exactly where each one lives and how they apply to building AI that aligns with our societal values. Fairness. Transparency. Bias. Beyond evaluation and technical talking points, these are also design decisions with real consequences for real people — and operationalizing them is harder than most organizations want to admit. One line from Di that stopped me: "People have crossed oceans and built monuments in honor of our capability to think. And I just want people to preserve that and not surrender it so freely." That's the episode in one sentence. To learn more about Ethical AI and reseatch from Di Le and more - https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1020&context=sighci2025 https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1025&context=sighci2024 https://www.youtube.com/watch?v=QhVY-85A-Wk&t=5s ServiceNow Insights Podcast

The Human in the Loop | Ethical AI with Di Le ServicveNow Insights Podcast - hosted By Bobby Brill What does it actually mean to build AI responsibly? Not the buzzword version. The real version. In our latest episode, I sat down with Di Le — AI Ethicist and Human-Centered AI Strategist at ServiceNow — and she broke it down in a way I hadn't heard before. Most people use Ethical AI, Responsible AI, and Human-Centered AI interchangeably, and Di breaks down exactly where each one lives and how they apply to building AI that aligns with our societal values. Fairness. Transparency. Bias. Beyond evaluation and technical talking points, these are also design decisions with real consequences for real people — and operationalizing them is harder than most organizations want to admit. One line from Di that stopped me: "People have crossed oceans and built monuments in honor of our capability to think. And I just want people to preserve that and not surrender it so freely." That's the episode in one sentence. To learn more about Ethical AI and reseatch from Di Le and more - https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1020&context=sighci2025 https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1025&context=sighci2024 https://www.youtube.com/watch?v=QhVY-85A-Wk&t=5s ServiceNow Insights Podcast

Send a textIn the first episode of Season 16 Karen and Jack chat to the rather fabulous Adrienne Fitzgerald.  An energetic, focussed, determined Strategic Account Manager for CORT Events.   With a degree in fabrics, listen in and experience her journey from fashion to furniture.  In her current role, Adrienne's responsibilities include managing the Midwest territory, Exhibit House programming, General Contractor partnerships and Large Corporate events for Gartner, Service NOW and TwitchCON.  Her role is all about building and understanding client relationships, and developing lasting partnerships. Adrienne has been in the event industry for over 20+ years, prior to joining CORT in 2017 she was managing major Golf industry events and working directly with the USGA and PGA of America. Adrienne strongly believes in the value of networking - if you invest in these relationships, you will have a strong dependable community.  She is on the Board of Women in Experiential and Midwest Chapter of IAEE.  She also supports the EDPA Midwest and Upper Midwest Chapters.   Adrienne is an avid snow skier, learned to wake surf when she turned 50 and is a cardio junkie working out 5 days a week. Adrienne currently lives in Chicago, IL. See more about our Season Sponsor – Electric Cat https://www.electriccat.co/ Find out more about our Shoutout Sponsor Church House Westminster https://churchhouseconf.co.uk/ Our Season Quickfire round Sponsor is the The Lewis Foundation https://www.thelewisfoundation.co.uk/ Our partnership with Standout Magazine is also worth following; https://standoutmagazine.co.uk/ Music Credits go to;Artist: Cathrine RannusTitle: The Events Insight Theme MusicMusic from #Uppbeat:Forever - Sega Williamshttps://uppbeat.io/t/sega-williams/foreverLicense code: 7F5KY293FYDFNVEVhttps://uppbeat.io/t/moire/summerLicense code: WNFODRXZ1ITXJS3HFly Away - Mountaineerhttps://uppbeat.io/t/mountaineer/fly-awayLicense code: EKN0IYNUKGUXMCTWClarity - Zoohttps://uppbeat.io/track/zoo/clarity License code: GL25RXVDXIBQWSWL 

Andy Roddick and Jon Wertheim dive into a heavy week on the ATP tour, ranging from historic statistical milestones to the serious situation in Dubai. We start with a Racket Rundown talking through the victories of Daniil Medvedev, Flavio Cobolli, and Peyton Stearns. Then we dive into breaking news out of Dubai, where over 40 ATP players and staff—including Daniil Medvedev and Andrey Rublev—found themselves hunkered down in a hotel waiting for airspace to open. Then, we transition to a lighthearted interview with 21-year-old American star Alex Michelsen. From his childhood bedroom, Alex talks about his transition from an "average junior" to a Top 50 pro, his decision to play right-handed despite being a natural lefty, and the experience of playing for Andre Agassi at the Laver Cup TAKE OUR SURVEY: https://survey.alchemer.com/s3/8634892/Served-Research Learn more about ServiceNow here: https://www.servicenow.com/?campid=271869&cid=pc:brd:brnd:served:26q1:paitwfp_audioredirect_PAITW2_GAI_PAITWFP_HostRead_:none:br_ams:awa&utm_medium=podcasts&utm_source=served

Send a textThis cluster of enterprise software announcements highlights how vendors are rapidly embedding AI, expanding ecosystem integrations, and strengthening vertical depth to drive measurable operational outcomes. From Camunda's integrations with ServiceNow to Pipefy's launch of next-generation AI agents and Coupa's introduction of agentic AI capabilities, the focus is shifting toward autonomous execution layers that can orchestrate workflows, enforce policies, and improve decision speed. At the same time, platform expansions such as ECI's NET1 Commerce Suite, HighByte's Intelligence Hub updates, and Deltek's platform enhancements demonstrate continued investment in unified operational and data architectures to support increasingly complex digital environments. Strategic moves—including Rootstock's acquisition of Praxis Solutions and Provus' partnership with Kantata—underscore how vendors are closing functional gaps through targeted acquisitions and alliances rather than rebuilding entire platforms. Finally, initiatives such as Sage's AI Trust Label and Flowfinity's AI service expansion reflect a growing emphasis on governance, transparency, and trust as AI becomes embedded infrastructure across the enterprise stack.In today's episode, we invited a panel of industry analysts for a live discussion on LinkedIn to analyze current enterprise software stories. We covered many grounds, including the direction and roadmaps of each enterprise software vendor. Finally, we analyzed future trends and how they might shape the enterprise software industry.Video: https://www.youtube.com/watch?v=Yzfdn7jJiVgQuestions for Panelists?

Bhavin Shah, senior vice president and general manager of ServiceNow (NOW), joins to talk about the company adding Moveworks to its Autonomous Workforce AI platform that the company aims to use in the enterprise space. He walks investors through the process its AI agents take to enhance and speed up workflows for customers. Bhavin later explains how it intertwines the tech with clients like CVS Health (CVS). ======== Schwab Network ========Empowering every investor and trader, every market day.Options involve risks and are not suitable for all investors. Before trading, read the Options Disclosure Document. http://bit.ly/2v9tH6DSubscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/About Schwab Network - https://schwabnetwork.com/about

In this episode of Futures Edge, Jim Iuorio, Bobby Iaccino, and Michael Arnold break down the current state of the markets as geopolitical tensions ripple across asset classes.The discussion focuses on crude oil, gold, silver, and Bitcoin, examining how military conflicts and global instability are influencing inflation expectations, interest rates, and investor sentiment.They also analyze key stock performances, including Nvidia, Tesla, and Oracle, and explain how shifting macro conditions are impacting equities. Throughout the episode, they emphasize the critical role of technical analysis in navigating volatile markets and managing risk during uncertain times.Timestamps:00:00 Introduction and Context of the Discussion01:33 Crude Oil Market Dynamics06:36 Geopolitical Implications on Oil Prices11:25 Military Perspectives and Market Reactions13:41 Gold Market Analysis19:25 Silver Market Insights25:11 Bitcoin's Role in Current Market Conditions27:43 Copper Market Trends and Analysis29:35 Interest Rates and Market Dynamics32:03 Inflation and Yield Movements34:23 Analyzing General Motors37:06 Market Indexes and Key Levels41:07 Stock Analysis: Nvidia and Others47:05 Evaluating Tesla and Oracle53:57 ServiceNow and Market StrategiesImportant Links to Follow:Newsletter: https://app.slice-app.io/p/traders/tGOrEACVVwS0e3WhgPUb4o9v2sX2 Shopify Podcast: open.spotify.com/show/60zQnUdSfZC43ZNoUJjTVp 

In this special UK edition of GlideChat, meet a couple of members of the GlideFast UK team to hear about their roles and what it's like working at GlideFast. Nicki Tones (Senior Business Process Consultant), Shane Rodgers (Lead Technical Consultant), and Roustan Kinioko (Senior Technical Consultant) discuss how they ended up in the ServiceNow world and what a day-to-day work life is like. They also talk about how the UK team is closely connected to the wider global GlideFast organization and what sets GlideFast apart.

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.

Send a textKourtney Cross is a RiseUp with ServiceNow Graduate and Business Analyst at Leidos. With a background in accounting and operations, Kourtney saw a shift happening in the enterprise tech landscape and decided he wouldn't be left behind. He immersed himself in a new ecosystem, earned multiple certifications through the RiseUp program, and built his own hands-on projects to prove his skills to skeptics.But his story isn't just about learning new software. It's about the grit it takes to pivot your career in public. Kourtney joins Dan Turchin to share what it really looks like to go from "credentials on paper" to delivering value in the AI economy, and why he believes compounded effort always yields success.In this conversation, they discuss:Why Kourtney saw a market shift and decided to dive in headfirst, and how that decision became a pivotal career inflection point.How RiseUp with ServiceNow program enables ambitious early-career professionals to obtain certifications, build real skills, and pivot into future-proof tech roles.What certifications actually do, and don't do, in the job market, and how Kourtney differentiated himself by building and showcasing a hands-on project.How to proactively leverage AI as a business analyst, from writing user stories to tightening requirements, instead of fearing job displacement.Where AI should accelerate productivity and where clear human boundaries still matter, especially in high-stakes areas like healthcare and admissions decisions.Why patience, resilience, and what Kourtney calls “compounded effort” matter more than credentials alone when breaking into tech and building long-term career momentum.Resources:Subscribe to the AI & The Future of Work NewsletterAI @ Work – Level One Leaders certificationConnect with Kourtney on LinkedInAI fun fact articleOn how AI can unleash human potentialExplore more about RiseUp with ServiceNow

Anthropic's refusal to remove safeguards against mass domestic surveillance and fully autonomous weapons in its interactions with the Department of Defense establishes an explicit boundary on the use of AI in federal contracts. The company cited specific civic and legal risks, emphasizing that current AI systems are not reliable enough for autonomous weapon deployment and warning that government pressure on vendors to bypass statutory constraints poses broader accountability issues. This underscores a shift in liability for MSPs and IT providers—any weakening of safeguards under contract does not eliminate risk but instead transfers possible exposure down the technology supply chain. This position is reinforced by the lack of unconditional trust in military oversight, as highlighted by the Pentagon CTO's remarks, and by clear legal challenges, including violations of the Fourth Amendment and Department of Defense Directive 3000.09. Dave Sobel asserts that professional liability and cyber policies do not typically cover actions undertaken solely at government request where legal limits are breached. This increases the necessity for MSPs and IT leaders to verify that contract language explicitly defines acceptable AI use and to ensure written documentation before government or enterprise client demands arise. Additional analysis includes operational deployments of AI in service and workplace environments. Burger King's AI chatbot, Patty, and ServiceNow's autonomous request resolution underscore the friction between efficiency claims and trust gaps, as evidenced by a YouGov survey that found 68% of consumers lack confidence in AI customer service. Dave Sobel notes that MSP benchmarks tied to vendor ticket closure rates may not reflect real client satisfaction or risk, especially when legal requirements for monitoring and consent are not met. The episode further covers market reactions to speculative reports on AI-driven job displacement, studies demonstrating AI's failure to maintain human-like restraint in conflict scenarios, and IBM's valuation drop due to AI modernization tools. For MSPs and IT decision-makers, the practical takeaway is the need for documented governance, explicit contractual safeguards, and ongoing risk assessments when deploying or recommending AI solutions—particularly in environments where trust, human oversight, and insurability are not yet aligned with technical capability. Three things to know today: 00:00 Anthropic Refuses Pentagon Demands on Surveillance and Autonomous Weapons, Risks Contract 03:40 AI Hits the Human Layer — and Governance, Consent, and Trust Infrastructure Aren't Ready 07:37 AI Moves Markets, Escalates Wars, and Splits Partner Ecosystems — In One Week   This is the Business of Tech.    Supported by:  IT Service Provider University

ServiceNow, the AI control tower for business reinvention, today launched Autonomous Workforce, AI specialists that can execute jobs with the scope, authority, and governance required for enterprise work – freeing people to focus on strategic problem solving and personalised service. Just two months after the Moveworks acquisition close, the company also introduced ServiceNow EmployeeWorks, which combines Moveworks' conversational AI and enterprise search with ServiceNow's unified portal and autonomous workflows to turn natural language requests into governed, end-to-end execution for nearly 200 million employees. As enterprises evaluate AI platforms, two competing paradigms have emerged: feature-function AI bolted onto disconnected SaaS apps, and unified platforms that execute work through proven enterprise workflows with AI built in. The difference is fundamental: the feature approach requires enterprises to maintain, integrate, and manage the complexity themselves. ServiceNow eliminates the complexity by unifying conversational AI, workflows, enterprise data, security, and governance on a platform purpose-built for mission-critical operations. "Businesses don't need more pilots or promises. They need AI that gets work done," said Amit Zavery, president, chief product officer, and chief operating officer, ServiceNow. "The leaders realising value from AI are investing in platforms where intelligence, execution, and trust work as one system. Our platform was purpose-built for this moment. Autonomous Workforce augments human teams with AI specialists that operate with the scope, authority, and governance enterprise work demands. This is a new era of productivity and ROI, at scale." Autonomous Workforce: AI teammates execute jobs in partnership with people ServiceNow's Autonomous Workforce deploys AI specialists with defined roles to augment teams. Unlike AI agents that complete individual tasks, the ServiceNow Autonomous Workforce orchestrates teams of AI specialists with roles such as a Level 1 Service Desk AI Specialist, Employee Service Agent, or Security Operations Analyst to execute work from start to finish. They work alongside humans, follow established processes and policies set by the organisation, learn from outcomes and employee feedback, and importantly, improve over time. Today, ServiceNow is introducing the first AI specialist available out-of-the-box for customers, a Level 1 Service Desk AI Specialist. This AI specialist autonomously diagnoses and resolves common IT support requests end-to-end — password resets, software access provisioning, network troubleshooting — using enterprise knowledge bases, historical incident data, and proactive remediation workflows. It is designed to operate 24/7 with assignments aligned to specific skillsets and deliverables and escalate issues when human intervention is needed. ServiceNow's Autonomous Workforce is handling 90%+ of employee IT requests. Early results show our newest AI specialist, the L1 Service Desk AI Specialist, is already resolving assigned IT cases autonomously, and it's 99% faster than when these cases are handled by human agents. AI models without workflows are probabilistic — they see patterns, form ideas, and give different answers for the same questions. The enterprise, however, needs deterministic outcomes — governance, security, auditability, and operations that don't hallucinate. Because ServiceNow combines probabilistic intelligence with deterministic workflow orchestration, AI specialists can interpret a request, decide the right action using business context, and execute autonomously across systems with governance built in through the ServiceNow AI Control Tower. Every action is traceable and governed by policies embedded in the workflow layer itself. ServiceNow EmployeeWorks: Consumer AI experiences meet enterprise-grade execution ServiceNow is bringing the power of Moveworks to the ServiceNow AI Platform and delivering immediate value to custome...

Realities Remixed, formerly know as Cloud Realities, launches a new season exploring the intersection of people, culture, industry, and tech. Energy transportation is a deeply local business, safely delivering gas and electricity, more and more from renewable sources, directly to the communities it serves. Technology and AI help make that possible by strengthening safety, bringing companies closer to customers, and enabling teams to build the future together. This week, Dave, Esmee, and Rob are joined by John Koerwer, CIO of UGI Corporation, to explore explore why “the business” and tech still struggle to speak the same language, nd what helps close the gap.TLDR00:35 – Introduction01:17 – Hang out: new toys and coffee07:55 – Dig in: the business - tech divide21:07 – Conversation with John Koerwer59:40 – The amazing AI technology in The Sphere's version of The Wizard of OzGuestJohn Koerwer: https://www.linkedin.com/in/john-koerwer-46102127/HostsDave Chapman: https://www.linkedin.com/in/chapmandr/Esmee van de Giessen: https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan: https://www.linkedin.com/in/rob-kernahan/ProductionMarcel van der Burg: https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman: https://www.linkedin.com/in/chapmandr/ SoundBen Corbett: https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:  https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

What does autonomous IT really look like when you move beyond the slideware and start wiring systems together in the real world? At Dynatrace Perform in Las Vegas, I sat down with Pablo Stern, EVP and GM of Technology Workflow Products at ServiceNow, to unpack exactly that. Pablo leads the teams focused on CIOs and CISOs, building the workflows and security products that sit at the heart of modern IT organizations. From service desks and command centers to risk and asset management, his remit is clear: enable AI to work for people, not the other way around. We began with ServiceNow's deepening multi-year partnership with Dynatrace. While the announcement made headlines, Pablo was quick to point out that the real story starts with customers. This collaboration is rooted in a shared goal of helping joint customers reduce outages, improve SLA adherence, and shrink mean time to resolution. The vision of autonomous IT operations is not about hype. It is about connecting observability data with deterministic workflows so that insight can evolve into coordinated, system-level action. Pablo walked me through the maturity curve he sees emerging. First came AI-powered insight, summarizing data and surfacing signals from noise. Then came task automation, drafting knowledge articles, paging teams, triggering predefined playbooks. The next step, and the one that excites him most, is orchestrated autonomy. That means stitching together skills, agents, and workflows into systems that can drive end-to-end outcomes. It is a journey measured in years, not months, and it depends as much on digitizing process and building trust as it does on technology. We also explored root cause analysis, still one of the biggest time drains in IT. By combining Dynatrace's AI-driven observability with ServiceNow's workflow engine, enterprises can automate forensic steps, correlate events faster, and shorten the time spent on major incident bridges where teams debate ownership. Even incremental improvements in accuracy can save hours when incidents strike. Trust, of course, remains central. Pablo was candid that full self-healing systems are still some distance away. What we will see first is relief automation, controlled failovers, scripted actions suggested by machines but approved by humans. Over time, as confidence grows and processes become fully digitized, the balance will shift. Beyond the technology, a consistent theme ran through our conversation. Outcomes have not changed. Enterprises still want higher availability, faster resolution, better employee experiences. What is changing is the how. ServiceNow is reimagining its platform to deliver those outcomes at a much higher standard, not through incremental tweaks, but through rethinking workflows for an AI-first world. From design partnerships with banks building pre-flight change checks, to internal teams acting as the toughest customers, this was a grounded, practical conversation about where autonomous operations are headed and what it will take to get there. If you are a CIO, CISO, or IT leader wondering how to move from theory to execution, this episode offers a clear-eyed look behind the curtain.      

We open the February 2026 mailbag to answer your questions on how to handle the psychological toll of the "SaaS apocalypse" and when it actually makes sense to buy the dip. We also discuss how to assess relative risk in a portfolio, dive deep into the differences between SentinelOne and CrowdStrike (including thoughts on stock-based compensation), and reveal the "falling knife" software stocks we are most tempted to buy right now, including ServiceNow and Salesforce.00:51 First Friday Update02:03 Mailbag Fear in Downturns03:56 DCA and SaaS Selloff06:15 Deploying Cash Rules08:43 Add to Winners Not Losers15:49 Risk in Portfolios20:31 Position Sizing Examples23:28 SentinelOne Profitability Debate28:35 SentinelOne vs CrowdStrike30:44 Cybersecurity Basket Strategy31:42 M&A and Buyout Odds33:12 CareTrust REIT Update35:00 Discord Falling Knife Picks35:35 ServiceNow Case37:44 PayPal Options and CEO Risk38:33 Salesforce AI and Valuation42:50 How We Add Positions47:28 Enphase and Gut Conviction50:19 Secular Trends and EV Lesson52:05 QuantumScape Battery Bet52:37 Wrap Up and Where to AskCompanies mentioned: ASML, CRM, CRWD, CTRE, ENPH, NOW, PYPL, QS, S, TSLA, TSMFind where to listen & subscribe,  portfolio contests, and contact information at https://investingunscripted.com*****************************************To get 15% off any paid plan at fiscal.ai, visit https://fiscal.ai/unscriptedListen to the Chit Chat Stocks Podcast for discussions on stocks, financial markets, super investors, and more. Follow the show on Spotify, Apple Podcasts, or YouTube*****************************************Join our PatreonSubscribe to our portfolio on Savvy Trader

Andy Roddick and Chris Eubanks discuss the Greatest Servers of All Time on the ATP Tour. From Pete Sampras to Boris Becker, to John Isner and Roger Federer: how they are all different yet so effective. They dive into legends like Goran Ivanisevic, Ivo Karlovic, Wayne Arthurs, & More.  They also cover the latest tour results: Alcaraz defeating Fils, Korda beating Paul, and Pegula winning over Svitolina. They also talk about Serena Williams possible comeback, Craig Tiley taking the CEO position at the USTA, and Andy signing a deal with ESPN to help commentate during Wimbledon and US Open.  COMMENT BELOW: Who has the best serve of all time? TAKE OUR SURVEY: https://survey.alchemer.com/s3/8634892/Served-Research Learn more about ServiceNow here: https://www.servicenow.com/?campid=271869&cid=pc:brd:brnd:served:26q1:paitwfp_audioredirect_PAITW2_GAI_PAITWFP_HostRead_:none:br_ams:awa&utm_medium=podcasts&utm_source=served

OpenAI korrigiert seine Umsatzerwartungen erneut nach oben: $284 Mrd. bis 2030, davon $150 Mrd. aus dem Consumer-Geschäft . Anthropic meldet massive Destillationsangriffe chinesischer Modellbetreiber mit bis zu 24.000 Fake-Accounts, während DeepSeek laut Reuters auf Nvidias Blackwell-Chips trainiert – angeblich in Data Centern in der Mongolei. Bernie Sanders fordert nach Gesprächen mit KI-CEOs ein Moratorium. Der virale Citrini-Research-Artikel "The 2028 Global Intelligence Crisis" beschreibt ein Doom-Szenario für SaaS und löst einen realen Kursrutsch bei ServiceNow, DoorDash und Cloudflare aus. Das DHS baut eine behördenübergreifende biometrische Datenbank. OpenAI-Mitarbeiter erkannten Warnsignale in der Chat-Historie einer kanadischen Amokläuferin, meldeten sie aber nicht an Behörden. Open-Source-Projekte kämpfen mit AI-Slop-Commits, Cerebras wagt einen zweiten IPO-Anlauf. Trump bedroht Netflix wegen Board-Mitglied Susan Rice, Musks Super PAC verstößt gegen das Wahlrecht in Georgia. Das Pentagon arbeitet mit Google, OpenAI und XAI ohne Guardrails. Unterstütze unseren Podcast und entdecke die Angebote unserer Werbepartner auf ⁠⁠⁠⁠⁠⁠doppelgaenger.io/werbung⁠⁠⁠⁠⁠⁠. Vielen Dank!  Philipp Glöckler und Philipp Klöckner sprechen heute über: (00:00:00) Intro (00:09:15) OpenAI Umsatzziel Anpassung (00:23:15) China destilliert Claude mit 24.000 Fake-Accounts (00:35:13) Citrini Research: The 2028 Global Intelligence Crisis (00:57:40) LinkedIn-Verifizierung: Was Persona mit deinen Daten macht (01:04:20) DHS baut biometrische Mega-Datenbank (01:08:50) OpenAI: Warnsignale vor Amoklauf nicht gemeldet (01:13:30) AI-Slop in Open Source und Cerebras IPO (01:19:07) Trump droht Netflix und Musks Wahlrechtsverstoß in Georgia (01:25:00) Waymo vs. Tesla und Pentagon ohne Guardrails (01:30:30) Trump-Regierung gegen europäische NGOs und DMA (01:32:57) Binance: $1,7 Mrd. Iran-Transaktionen, Whistleblower gefeuert (01:37:37) Steven Bartlett und Christian Angermayer (01:44:04) DJI-Saugroboter-Hack Shownotes OpenAI resets spending expectations, tells investors compute target is around $600 billion by 2030 - cnbc.com Anthropic beschuldigt chinesische Firmen, Daten von Claude zu stehlen. - wsj.com China nutzte Nvidia-Chip für KI-Modell trotz US-Verbot. - reuters.com Sanders warnt vor unkontrollierter Geschwindigkeit der KI-Revolution. - theguardian.com Post von pitdesi - x.com LinkedIn-Identität verifiziert - thelocalstack.eu DHS Search Engine - wired OpenAI-Mitarbeiter warnten Monate zuvor vor Kanadaschützen. - wsj.com Für Open-Source-Programme sind KI-Codierungswerkzeuge ein zweischneidiges Schwert. - techcrunch.com Cerebras Files Confidentially For a U.S. IPO - theinformation.com Trump droht Netflix wegen Rice im Vorstand Konsequenzen an. - bloomberg.com Trump sagt, Netflix wird 'Konsequenzen tragen', wenn Susan Rice bleibt. - theverge.com Georgia sagt, Elon Musks America PAC verletzte Wahlgesetz. - theverge.com Tesla Waymo - wired Musks xAI und Pentagon vereinbaren Nutzung von Grok in Geheimdiensten - axios.com Trump-Verbündete zielen auf europäische NGOs wegen Big-Tech-Regeln. - ftm.eu Binance Employees Find $1.7 Billion in Crypto Was Sent to Iranian Entities - nytimes.com Von Dragons' Den zu Disney: Steven Bartlett sammelt achtstellige Summe. - eu-startups.com Meta-Direktorin für KI-Sicherheit gab OpenClaw-Bot vollen Zugriff. - x.com DJI Romo mit Xbox-Controller. - x.com

Tata Consultancy Services (TCS), a global leader in IT services, consulting, and business solutions, and ServiceNow, the AI control tower for business reinvention, have signed a multi-year partnership to help enterprises speed up AI adoption across their businesses and functions. Enterprises are increasingly looking for experts who can reimagine how work is transformed with AI, especially in back-office functions like human resources, finance, supply chain, procurement, and employee services. As part of this partnership, TCS, who operate a global service delivery centre in Ireland, will develop solutions on the ServiceNow platform that will use trusted AI and a unified governance model to make enterprise workflows more efficient, proactive, and insight-driven. These solutions will be offered through TCS's AI-led, autonomous global business solutions portfolio. Amit Zavery, President, Chief Operating Officer and Chief Product Officer, ServiceNow, said, "As global enterprises rethink operating models for growth and efficiency, they are looking for partners that can deliver innovation, execution, and governance at scale. Together with TCS, we are helping enterprises move beyond isolated AI experiments by building agentic AI natively into workflows, modernising legacy environments, and driving measurable business outcomes." Aarthi Subramanian, Executive Director – President and Chief Operating Officer, TCS, said, "Today, enterprises are ready to move beyond AI pilots to scaled, business-wide transformation. Our partnership with ServiceNow brings together trusted AI, modern workflows, and deep industry knowledge that will help customers reimagine workflows for the AI era using TCS's five-stage AI Autonomy Framework. This collaboration will help clients embed intelligence across their IT, business operations, and customer functions, driving speed, efficiency, and sustained competitive advantage." The new offerings will break down silos between corporate functions and business units, transform the flow of work using agentic AI, and enable clients to get a holistic, insights-driven view of their organisations. For example, HR operations could shift from fragmented services to a unified, experience-led hire-to-retire lifecycle that increases employee productivity, engagement, and retention. In addition, customer order processing could change from a slow, multi-step order cycle to a high-velocity revenue engine that improves cash flow and revenue predictability, unlocking capital for growth. Currently, TCS is the largest user of ServiceNow's IT Asset Management, deploying the offering across thousands of devices used by TCS's workforce over a period of three months. This highlights a strong foundation that not only validates the partnership but also affirms the credibility of the solutions that both organisations aim to deliver for their clients. The two companies will also invest in co-innovation labs, solution showcases, and integrated go-to-market programs for clients. The TCS partnership with ServiceNow will play a central role in supporting TCS's aspiration to become the world's largest AI-led technology services company.

In this Dialogue episode of The Synopsis, we discuss the recent sell off of software names, Constellation Software, and introduce the idea of "Point of Monetization" to analyze why Dating Apps are such a bad business.  Five Minute Money Newsletter Free Sign Up Watch the ServiceNow Video here, or the Constellation Software Video Here, the Adobe Video Here.  ~*~ You can also get a free trial to AlphaSense to read 200k+ expert calls through this link.  ~*~ For full access to all of our updates and in-depth research reports become a Speedwell Member here. Please reach out to info@speedwellresearch.com if you need help getting us to become an approved research vendor in order to expense it. -*-*-*-*-*-*-*-*-*-*-*-*-*-*- Show Notes (0:00)  — Intro (3:48)  — ServiceNow Business Overview (13:00)  — Risks to ServiceNow (21:32)  — AI Control Tower (24:14)  — Competitive Dynamics (32:10)  — Valuation (35:18)  — Mature Margin Diatribe (42:39)  — AI Risk Rebuttal (46:16)  — ServiceNow Blue Sky Scenario (47:38)  —  Intuit Disrupted? (50:46)  — Will Margins Collapse for SaaS? (52:54)  — Difference Between SMB vs Enterprise SaaS -*-*-*-*-*-*-*-*-*-*-*-*-*-*- For full access to all of our updates and in-depth research reports, become a Speedwell Member here. Please reach out to info@speedwellresearch.com if you need help getting us to become an approved research vendor in order to expense it. *-*-*- Follow Us: Twitter: @Speedwell_LLC Threads: @speedwell_research Email us at info@speedwellresearch.com for any questions, comments, or feedback. -*-*-*-*-*-*-*-*-*-*- Disclaimer Nothing in this podcast is investment advice nor should be construed as such. Contributors to the podcast may own securities discussed. Furthermore, accounts contributors advise on may also have positions in companies discussed. This may change without notice. Please see our full disclaimers here:  https://speedwellresearch.com/disclaimer/

Today's guest is Amber Robertson, Senior Manager, Application Services (ServiceNow) at Activision Blizzard. Founded in 2008, Activision Blizzard is a global leader in interactive entertainment, creating epic experiences across console, PC and mobile. Home to iconic franchises like Call of Duty®, World of Warcraft®, Overwatch®, Diablo® and Candy Crush™, the company builds vibrant communities, pushes innovation in gaming and esports, and connects players worldwide through immersive, memorable experiences.Amber is a senior technology leader with 20 years' experience building and operating enterprise service platforms in complex global environments. She currently leads the ServiceNow platform across Activision Blizzard, Blizzard Entertainment and King, focusing on scalable strategy, service delivery excellence, and user-centered design. She partners with cross-functional teams to modernize service experiences, establish governance, responsibly leverage AI and create intuitive, human-centered platforms.In the episode, Amber talks about:0:00 Career journey from fine art to IT, building service desks and ServiceNow5:20 Leading ServiceNow consolidation across Activision Blizzard and King9:25 Expanding ServiceNow with HR, legal, events and finance tools company-wide10:47 How ServiceNow became the self-sufficient, gamified hub for company workflows13:24 Currently scaling ServiceNow with Employee Center, AI and lifecycle management15:45 Leading ServiceNow with two engineers plus long-term vendor support16:56 Staying at Activision Blizzard for supportive, positive work environment18:43 ServiceNow work remains project-based, relying on consultants for support20:31 How the company supports side projects, letting her create art and ServiceNow apps

AI momentum is accelerating, but real-world constraints are tightening. From hyperscaler infrastructure lock-ins and sovereign AI expansion to RAM shortages and enterprise AI pivots, Ep. 293 examines what truly determines leadership in the next phase of AI.   The handpicked topics for this week are: Meta & NVIDIA's Long-Term AI Infrastructure Partnership: Meta confirmed a deep infrastructure expansion across NVIDIA Blackwell and Rubin GPUs, Grace CPUs, and advanced networking. Pat & Dan discuss hyperscaler AI factories, overflow capacity strategies, and long-term compute commitments. Microsoft's Global South and Sovereign AI Expansion: As Microsoft continues major investment across India and emerging markets, the hosts explore sovereign cloud strategy, geopolitical positioning, and how global AI infrastructure buildouts shape long-term competitiveness. California AI Oversight and Regulatory Fragmentation Risk: State-level AI oversight initiatives raise concerns about a patchwork regulatory environment that could slow U.S. innovation relative to centralized global competitors. The HBM Memory Crunch and Long-Term Supply Constraints: High-Bandwidth Memory shortages continue to shape AI deployment timelines. Relief may not arrive until late this decade, with downstream impacts on data centers, PCs, and consumer devices. Infosys & Anthropic GSI Pivot to Enterprise AI Agents: Infosys partners with Anthropic to accelerate enterprise AI agent deployment. Hosts examine whether global systems integrators can pivot fast enough in an agent-driven economy. The Flip – Models vs Infrastructure Leadership: Is AI dominance determined by model quality or infrastructure scale? Pat & Dan debate whether gigawatts or algorithmic efficiency define long-term advantage. Bulls & Bears – Cyber, Power, EDA, SaaS & AI Infrastructure Plays: Earnings and market signals across Palo Alto Networks, Analog Devices, Cadence, ServiceNow, Dell, and Marvell highlight how execution, supply chains, and capital discipline matter in this cycle. Be sure to subscribe to The Six Five Pod so you never miss an episode.

Realities Remixed, formerly know as Cloud Realities, launches a new season exploring the intersection of people, culture, technology, and society. Hosts Dave Chapman, Esmee van de Giessen, and Rob Kernahan unpack 2026's defining trends, from AI and sovereignty to adaptability and automation, offering fresh insight, candid reflections, and forward‑looking conversations shaping the year ahead. TLDR00:20 – Introduction of Realities Remixed02:30 – Why the show evolved?04:50 – Dig in with the team: Predictions for 202606:40 – Macro trends13:00 – Sovereignty 17:40 – Agentic AI22:17 – Human–AI interaction26:06 – Cloud trends30:42 – AI scaling, domain‑specific models35:03 – Adoption lag39:34 – Physical AI43:47 – Quantum computing48:21 – Hardware acceleration50:30 – Cybersecurity52:38 – Season outlook HostsDave Chapman:  https://www.linkedin.com/in/chapmandr/Esmee van de Giessen:  https://www.linkedin.com/in/esmeevandegiessen/Rob Kernahan:  https://www.linkedin.com/in/rob-kernahan/ProductionMarcel van der Burg:  https://www.linkedin.com/in/marcel-vd-burg/Dave Chapman:  https://www.linkedin.com/in/chapmandr/ SoundBen Corbett:  https://www.linkedin.com/in/ben-corbett-3b6a11135/Louis Corbett:   https://www.linkedin.com/in/louis-corbett-087250264/ 'Realities Remixed' is an original podcast from Capgemini

AI is transforming how businesses operate and how early-career talent grows. In this episode, UTG Unlocked, Mark Stockford (GVP, Global Cloud Operations) and Alyssa Gerhart (former intern, now full-time employee) share how AI is reshaping work at ServiceNow—from strategic impact to day-to-day execution. Our guest hosts Jorden Shelton and Cynthia Mathenge guide the conversation and explore real AI use cases like Unity, RAG-based duplicate detection, and intent detection, while emphasizing the importance of critical thinking and strong fundamentals. In this episode, designed not just for recent interns, you’ll learn how AI is expanding career paths, how teams like Global Cloud Services power innovation behind the scenes, and what interns and early-career professionals can do now to grow: stay curious, use AI intentionally, seek mentors, and don’t just consume—contribute. UTG is the engine behind the scenes here at ServiceNow — enabling innovation, maintaining production environments, supporting internal teams, and driving operational excellence. It connects strategy to execution by combining engineering, cloud operations, and technology operations to deliver stable, high-performing systems that allow the business and customers to succeed. For more information about the Early Careers program visit - https://careers.servicenow.com/early-careers/ 00:00 Welcome & What ‘UTG Unlocked’ Is All About  02:50 Meet the Panel: Mark, Alyssa, Jorden & Cynthia  04:29 Segment 1: How AI Is Impacting the Business (Customers vs. Employees)  06:26 Skills That Matter in an AI-Powered Workplace  09:52 Real AI Use Cases: Unity, Agents, and Faster Ops  13:57 AI and Career Growth: New Roles, New Paths, Partnering with AI  18:56 Advice for Early-Career Talent: Stay Curious, Build, Contribute  20:41 Segment 2 Kickoff: Rapid-Fire Fun28:50 Pulling Back the Curtain: What is GCS 30:37 GCS as a Superhero: Operating in the Shadows Like Batman  31:35 The Hidden Work: Solving Customer-Created Problems & Root-Cause Hunting  33:37 Alyssa’s Journey: Intern to FTE, Mentorship, and Scaling Developer Productivity  35:38 What’s Next: Emerging Tech on the Radar (AI to Quantum Computing)  37:15 Closing Takeaways: Keep Learning, Use AI Wisely, Ask Questions, and Give Back  40:12 Final Words & Where to Learn More See omnystudio.com/listener for privacy information.

This household name could surge 50% this year. Plus, why software stocks are getting rerated… Bullish moves from ServiceNow (NOW) insiders… Key takeaways from the Trumps' World Liberty Forum… And 13Fs from Buffett, Tepper & Druckenmiller. In this episode: The Olympic curling cheating scandal [1:46] This megacap stock could surge 50% this year [7:41] The Palo Alto Networks CEO is dead wrong on AI [14:53] Why software stocks are getting rerated [17:35] The latest moves from ServiceNow insiders are great for the stock [27:01] Key takeaways from the Trumps' World Liberty Forum [36:35] 13F moves that caught our eye: Buffett, Tepper & Druckenmiller [47:24] One of the best private placement opportunities of my career [58:01] Did you like this episode? Get more Wall Street Unplugged FREE each week in your inbox. Sign up here: https://curzio.me/syn_wsu Find Wall Street Unplugged podcast… --Curzio Research App: https://curzio.me/syn_app --iTunes: https://curzio.me/syn_wsu_i --Stitcher: https://curzio.me/syn_wsu_s --Website: https://curzio.me/syn_wsu_cat Follow Frank… X: https://curzio.me/syn_twt Facebook: https://curzio.me/syn_fb LinkedIn: https://curzio.me/syn_li

In today's Cloud Wars Minute, I explore why Bill McDermott says ServiceNow is not a SaaS company and why SaaS is “on the menu.”Highlights00:03 — Welcome back to Cloud Wars Minute. The big thing is ServiceNow. As Bill McDermott says, ServiceNow is hungry and SaaS is on the menu. He went to great lengths in ServiceNow's recent Q4 earnings call, and also in a follow-up interview with Jim Cramer of Mad Money, to say that ServiceNow is doing great. We hit and exceeded all our numbers. We are not a SaaS company now.00:34 — One of the reasons McDermott wants to emphasize this separation from the SaaS community is because the SaaS business has been getting ravaged by Wall Street analysts who are thinking that AI, generative AI is going to completely gut the whole SaaS model. So they have knocked anywhere from 50, 60, 70% off the market caps of some leading SaaS companies.01:09 — He said AI, generative AI, and workflows and data are going to be the new model, the old model of traditional SaaS applications, or of what McDermott referred to repeatedly as features and functions. He said those are things of the past. We are the AI platform on which a lot of these SaaS apps will work and they'll operate.02:03 — Hyperscale is a nice name, but it doesn't really describe all that they do. Some of them offer applications, application development. They all offer databases. You've now got SaaS companies that got caught up in just features and functions that don't drive value and don't get companies better prepared for the AI Economy. They're all rolled together now.03:05 — "Our stock price and our valuation have taken a huge hit because we are being misinterpreted as being part of the SaaS world." We are not in the SaaS neighborhood. We are not a SaaS company. SaaS is on the menu. We're hungry. AI and ServiceNow are going to eat a lot of these, devour a lot of these feature and function application companies. Visit Cloud Wars for more.

Andy Roddick and Chris Eubanks debate the Greatest Backhands of All Time on the ATP Tour. From Jimmy Connors' simple mechanics to Novak Djokovic and Andy Murray's sliding, elastic defense, they break down how the shot evolved. They dive into legends like David Nalbandian, Marat Safin, and Lleyton Hewitt, plus Chris explains how modern giants like Zverev and Medvedev reshaped the backhand game. They also cover the latest tour results: Ben Shelton capturing the Nexo Dallas Open title, Karolína Muchová winning her first title in seven years, Francisco Cerúndolo taking the title in Buenos Aires, and Aryna Sabalenka and Iga Swiatek withdrawing from Dubai. COMMENT BELOW: Who has the best backhand of all time? TAKE OUR SURVEY: https://survey.alchemer.com/s3/863489... Learn more about ServiceNow here: https://www.servicenow.com/?campid=27...

Send a textThis week's enterprise software developments underscore a widening gap between rapid AI-driven platform innovation and the unresolved execution risks embedded in large-scale ERP programs. On one side of the ledger, Mendix and OutSystems both advanced their agentic AI roadmaps with new releases aimed at operationalizing autonomous workflows, while ServiceNow's unveiling of its AI Experience, Sprinklr's new AI capabilities, and Braze's product enhancements at Forge 2025 reinforce how aggressively vendors across ITSM, CX, and marketing automation are repositioning around AI-first interaction layers. Salesforce's latest Slack updates and Upstream Works' enhanced agent desktop further extend this trend into collaboration and contact center operations, signaling that AI augmentation is now table stakes across front-office and service environments. In parallel, Plex's expanded connected worker integrations highlight how these same concepts are being pushed into manufacturing execution and workforce enablement, while Cleo's invoice payment and financing solution reflects growing pressure to modernize B2B financial operations. Yet this innovation narrative is tempered by Daedong USA's loss of an injunction in its ERP dispute—placing its $11.4 billion suit in jeopardy—which serves as a reminder that beneath the AI acceleration, legacy implementation failures, legal exposure, and governance breakdowns continue to create material risk for enterprises betting on large transformation programs.In today's episode, we invited a panel of industry analysts for a live discussion on LinkedIn to analyze current enterprise software stories. We covered many grounds including the direction and roadmaps of each enterprise software vendors. Finally, we analyzed future trends and how they might shape the enterprise software industry.Video: https://www.youtube.com/watch?v=_Arr9GjwOBsQuestions for Panelists?

In today's Cloud Wars Minute, I break down ServiceNow's latest AI expansion with Anthropic and what it means for enterprise workflows.Highlights00:04 — I recently reported on ServiceNow's expanded collaboration with OpenAI. That agreement makes OpenAI's models the go-to solution for companies running upwards of 80 billion annual workflows on the ServiceNow platform.00:17 — Now, ServiceNow has announced that Anthropic's Claude models will be integrated into core ServiceNow workflows for tasks like app development, with Claude serving as the default model powering the ServiceNow Build Agent — the company's tool for easy development of agentic workflows.00:37 — This is what ServiceNow Chairman and CEO Bill McDermott had to say about the announcement: “ServiceNow and Anthropic are turning intelligence into action through AI-native workflows for the world's largest enterprises ... Together, we are proving that deeply integrated platforms with an open ecosystem are how the future is built.”01:12 — In addition to Build Agent, ServiceNow is integrating Claude alongside purpose-built solutions throughout the implementation lifecycle, with the aim of achieving a 50% reduction in the time it takes customers to deploy solutions built on the ServiceNow AI platform.01:31 — ServiceNow and Anthropic are also building agent-based workflows for specific industries, including healthcare and life sciences, for tasks such as research and analysis. Just as it has done with OpenAI, ServiceNow is integrating Claude directly into workflows — and it's this integration that can lead to much better outcomes for AI initiatives.02:03 — By making these model choices the default, ServiceNow removes the guesswork from customer decision-making and enables customers to rely on the company's expertise to achieve the best results. Visit Cloud Wars for more.

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.    

Today's guest is Laurie Wheeler, Chief Operating Officer – IS&T at MultiCare Health System. Founded in 1882, MultiCare is a locally governed, nonprofit health system serving communities across the Pacific Northwest. Today, it operates 13 hospitals and more than 300 primary, urgent, paediatric and specialty care locations in Washington, Idaho and Oregon. With over 20,000 team members, MultiCare remains dedicated to improving health, expanding access to care and supporting the wellbeing of the communities it serves.Laurie is an accomplished executive leader with more than 20 years of experience driving strategy and delivering results. She is known for turning vision into action through collaboration and strong partnerships, and for successfully advancing complex initiatives within matrixed organizations. Recognized as a decisive executor, Laurie effectively aligns executive teams and C-suite stakeholders across functions - including Finance, Legal, HR, IT and Clinical - to achieve critical organizational objectives.In the episode, Laurie talks about:0:00 An insight into her 25+ year career working in Healthcare and IT2:35 MultiCare's offerings with 13 hospitals, 300+ clinics and full healthcare services3:23 Her role in IT culture, processes and optimizing the ServiceNow platform4:57 Building a robust knowledge base to optimize ServiceNow6:48 Focus on automation, ROI, and scalable IT support systems9:06 How they successfully integrated Overlake Hospital's service desk into ServiceNow11:14 Excitement to expand ServiceNow, automate processes and scale efficiently13:24 How strong governance and structured roadmap ensure successful ServiceNow outcomesTo find out more about all the great work happening at MultiCare Health System, check out the website www.multicare.org

Perform 2026 felt like a turning point for Dynatrace, and when Steve Tack joined me for his fourth appearance on the show, it was clear this was not business as usual.  We began with a little Perform nostalgia, from Dave Anderson's unforgettable "Full Stack Baby" moment to the debut of AI Rick on the keynote stage. But the humor quickly gave way to substance. Because beneath the spectacle, Dynatrace introduced something that signals a broader shift in observability: Dynatrace Intelligence. Steve was candid about the problem they set out to solve. Too much focus on ingesting data. Too much time spent stitching tools together. Too many dashboards. Too many alerts. The real opportunity, he argued, is turning telemetry into trusted, automated action. And that means blending deterministic AI with agentic systems in a way enterprises can actually trust. We unpacked what that looks like in practice. From United Airlines using a digital cockpit to improve operational performance, to TELUS and Vodafone demonstrating measurable ROI on stage, the emphasis at Perform was firmly on production outcomes rather than pilot projects. As Steve put it, the industry has spent long enough in "pilot purgatory." The next phase demands real-world deployment and real return. A big part of that confidence comes from the foundations Dynatrace has laid with Grail and Smartscape. By combining unified telemetry in its data lakehouse with real-time topology mapping and causal AI, Dynatrace is positioning itself as the engine behind explainable, trustworthy automation. When hyperscaler agents from AWS, Azure, or Google Cloud call Dynatrace Intelligence, they are expected to receive answers grounded in causal context rather than probabilistic guesswork. We also explored what this means for developers, who often carry the burden of alert fatigue and fragmented tooling. New integrations into VS Code, Slack, Atlassian, and ServiceNow aim to bring observability directly into the developer workflow. The goal is simple in theory and complex in execution: keep engineers in their flow, reduce toil, and amplify human decision-making rather than replace it. Of course, autonomy raises questions about risk. Steve acknowledged that for now, humans remain firmly in the loop, with most agentic interactions still requiring checkpoints. But as trust grows, so will the willingness to let systems self-optimize, self-heal, and remediate issues automatically. We closed by zooming out. In a market saturated with AI claims, Steve encouraged listeners to bet on change rather than cling to the status quo. There will be hype. There will be agent washing. But there is also real value emerging for those prepared to experiment, learn, and scale responsibly. If you want to understand where AI observability is heading, and how deterministic and agentic intelligence can coexist inside enterprise operations, this episode offers a grounded, practical perspective straight from the Perform show floor.

With a career spanning the US Navy, executive leadership positions at PetSmart and Banfield Pet Hospital, and pioneering online training, Don brings unique insights into building and scaling businesses across industries. Throughout the conversation, Avanish and Don discuss OpenSesame's evolution from an online learning marketplace to an AI-powered platform that serves enterprises, learning management systems, and content publishers. They explore the "Intel Inside" ecosystem strategy, the Simon AI tool that democratizes course creation and enables instant translation into 70 languages, and how organizations can successfully navigate workforce reinvention in the AI era while meeting customers where they are.In this episode, Avanish and Don discuss:OpenSesame's dual-sided platform strategy: Partnering with 200+ LMS/HRIS systems on the delivery side while aggregating 50,000 courses from 200+ publishers, providing distribution for small publishers to reach enterprise customers and enabling large publishers like Harvard Business Publishing to access mid-market and SMB segments.The Simon AI course creation tool: Democratizing content development by enabling subject matter experts to create high-quality courses without instructional designers, with built-in translation capabilities across 70 languages for voiceover and text—expanding global reach for multinational organizations.Workforce reinvention as strategic imperative: Positioning OpenSesame at the center of organizational AI transformation by providing not just technology but comprehensive change management roadmaps, helping HR and learning leaders guide their teams through adoption with curated content and use cases.The "meet them where they are" philosophy: Balancing long-term product vision with practical customer adoption paths, especially during transformational periods like AI implementation, by understanding customer needs deeply before prescribing solutions and allowing products to flex without compromising the ultimate vision.The 1% better daily improvement mindset: Embracing continuous learning and incremental progress as the foundation for breakthrough innovation, recognizing that overnight successes are built on consistent dedication and discipline over time.About Don Spear:Don Spear is CEO of OpenSesame. Before his current role, he founded BlueVolt.com, held executive leadership positions at Banfield Pet Hospital and PetSmart, and served as a submarine officer aboard the USS Tunny (SSN 682).About OpenSesameOpenSesame, the leading provider of online business training, is the choice for L&D professionals wanting to drive learning initiatives forward with innovation, agility, and care. We offer the world's most comprehensive digital learning catalog, with regularly updated content from expert publishers in a variety of formats and languages. By providing comprehensive learning resources and innovative tools like Simon, OpenSesame empowers L&D professionals to exceed their goals and champion learning across their entire organization.Host Avanish SahaiAvanish Sahai is a Tidemark Fellow and served as a Board Member of Hubspot from 2018 to 2023; he currently serves on the boards of Birdie.ai, Flywl.com and Meta.com.br as well as a few non-profits and educational boards. Previously, Avanish served as the vice president, ISV and Apps partner ecosystem of Google from 2019 until 2021. From 2016 to 2019, he served as the global vice president, ISV and Technology alliances at ServiceNow.  From 2014 to 2015, he was the senior vice president and chief product officer at Demandbase.  Prior to Demandbase, Avanish built and led the Appexchange platform ecosystem team at Salesforce, and was an executive at Oracle and McKinsey & Company, as well as various early to mid-stage startups in Silicon Valley.About TidemarkTidemark is a venture capital firm, foundation, and community built to serve category-leading technology companies as they scale.  Tidemark was founded in 2021 by David Yuan, who has been investing, advising, and building technology companies for over 20 years.  Learn more at www.tidemarkcap.com.LinksFollow our host, Avanish SahaiLearn more about Tidemark

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM  Amelia Hernandez Osorio explores practical ways organisations can build lasting Copilot habits, strengthen internal communities and drive effective AI adoption. Amelia shares her journey through web technologies, SharePoint, cloud transformation and Microsoft 365 adoption, offering guidance on behaviour change, team enablement and identifying meaningful Copilot use cases that improve daily work. 

Andy Roddick and Chris Eubanks talk the Greatest Forehands OF ALL TIME from the ATP Tour. They talk how Rafa Nadal changed the forehand and the more incredible forehands from players like Andre Agassi, Jannik Sinner, Roger Federer, Carlos Alcaraz, etc.  We also discuss Serena Williams seems to be back in the training room?Andy Roddick and John Wertheim break down their thoughts on the Winter Olympics, Super Bowl, and much more. COMMENT BELOW: Who has the best forehand of all time? TAKE OUR SURVEY: https://survey.alchemer.com/s3/8634892/Served-Research Learn more about ServiceNow here: https://www.servicenow.com/?campid=271869&cid=pc:brd:brnd:served:26q1:paitwfp_audioredirect_PAITW2_GAI_PAITWFP_HostRead_:none:br_ams:awa&utm_medium=podcasts&utm_source=served

Send a textThis week's enterprise software headlines highlight a market simultaneously accelerating into agentic AI while still wrestling with the structural and legal fallout of past transformation failures. On the innovation front, Genstore's $10M seed round, Tray.ai's launch of the Tray Agent Hub, and new agentic releases from Mendix and OutSystems underscore how aggressively vendors are repositioning around autonomous workflows and AI-first orchestration layers. ServiceNow's unveiling of its AI Experience and Plex's connected worker integration push the same narrative into IT service management and manufacturing operations, signaling that agentic concepts are no longer confined to experimental edges of the stack. At the same time, a parallel storyline of governance and execution risk is playing out, with Zimmer Biomet's $172M ERP lawsuit against Deloitte, Europe's continued delays fixing a troubled Oracle system, Daedong USA's faltering ERP injunction, and the EU Commission's investigation into SAP's practices reinforcing how fragile large-scale enterprise transformations remain. Together, these developments paint a bifurcated 2026 landscape: rapid platform innovation driven by AI ambition on one side, and unresolved accountability, regulatory scrutiny, and implementation risk on the other.In today's episode, we invited a panel of industry analysts for a live discussion on LinkedIn to analyze current enterprise software stories. We covered many grounds including the direction and roadmaps of each enterprise software vendors. Finally, we analyzed future trends and how they might shape the enterprise software industry.Video: https://www.youtube.com/watch?v=m3VmbEsy5uQQuestions for Panelists?

Feb 5, 2026: Are software vendors in trouble? Why are employees suddenly complying with return-to-office mandates? And what happens when leaders are afraid to ask their own teams for feedback? In today's episode of Future-Ready Today, we unpack five stories that together reveal a major reset happening inside organizations: Why Workday is cutting jobs — and what falling enterprise software stocks (including ServiceNow) signal about how AI is disrupting traditional SaaS business models. New data showing workers backing down on return-to-office demands as employers reclaim leverage. A leadership study revealing that senior executives want feedback — but fear appearing weak if they ask. Layoffs surging to the highest January level since 2009, driven in part by restructuring at UPS following shifts in volume from Amazon. And research from Bain & Company showing a massive disconnect between leaders who think change is working and employees who say it isn't.  

As the Patriots will face the Seahawks this Sunday, we will have a little fun with the famous "Super Bowl Indicator" and analyze the record-breaking $8 million cost for a 30-second ad spot.Today's Stocks & Topics: Lincoln Electric Holdings, Inc. (LECO), Market Wrap, VanEck Gold Miners ETF (GDX), Etsy, Inc. (ETSY), The Super Bowl Indicator, ServiceNow, Inc. (NOW), High Yield Savings Account vs. Money Market Fund, Copart, Inc. (CPRT), US Manufacturing and Tariffs, Adobe Inc. (ADBE), Expedia Group, Inc. (EXPE), ResMed Inc. (RMD).Our Sponsors:* Check out Quince: https://quince.com/INVESTAdvertising Inquiries: https://redcircle.com/brands