Podcasts about gpt

Ep 386: Was 2025 a Great or Terrible Year for AI? (w/ Ed Zitron) 2025 was a year that was saturated in AI news, from Deep Seek, through claims of economic “bloodbaths,” to GPT-5, Sora, and Chatbot girlfriends. Frankly, it was exhausting. As we now look back on 2025 an interesting question arises: all in all, did this end up being a good or bad year for AI? To help me answer this question, I'm joined by hard-hitting AI commentator Ed Zitron, who's been everywhere in the media in recent months helping to make sense of the wild claims being thrown in the public's direction. Together we go through the biggest AI stories of the year to try to make sense of what just happened. Below are the questions covered in today's episode (with their timestamps). Get your questions answered by Cal! Here's the link: bit.ly/3U3sTvoVideo from today's episode: youtube.com/calnewportmediaINTERVIEW: Was 2025 a Great or Terrible Year for AI (w/ Ed Zitron) [3:16]Cal Reacts to Comments: Is the Internet Becoming Television? [1:58:25]  Links:Buy Cal's latest book, “Slow Productivity” at calnewport.com/slowGet a signed copy of Cal's “Slow Productivity” at peoplesbooktakoma.com/event/cal-newport/Cal's monthly book directory: bramses.notion.site/059db2641def4a88988b4d2cee4657ba?bbc.com/news/articles/c5yv5976z9poaxios.com/2025/01/23/davos-2025-ai-agentsblog.google/technology/google-deepmind/gemini-model-updates-february-2025/openai.com/index/sora/openai.com/index/introducing-gpt-4-5/ai-2027.com/fortune.com/2025/05/28/anthropic-ceo-warning-ai-job-loss/media.mit.edu/publications/your-brain-on-chatgpt/usatoday.com/story/tech/2025/08/07/chat-gpt-5-release-date-open-ai/85566627007/#:~:text=GPT%2D5%20release%20date,release%20date%20for%20Part%202newyorker.com/culture/open-questions/what-if-ai-doesnt-get-much-better-than-thiswsj.com/tech/ai/ai-bubble-building-spree-55ee6128nvidianews.nvidia.com/news/openai-and-nvidia-announce-strategic-partnership-to-deploy-10gw-of-nvidia-systemsnytimes.com/2025/10/02/technology/openai-sora-video-app.htmlanthropic.com/news/claude-opus-4-5ft.com/content/064bbca0-1cb2-45ab-85f4-25fdfc318d89youtube.com/watch?v=Z_WEmjygNK0Thanks to our Sponsors: This episode is sponsored by Better Help:betterhelp.com/deepquestionsreclaim.ai/calexpressvpn.com/deepcalderalab.com/deepThanks to Jesse Miller for production, Jay Kerstens for the intro music, and Mark Miles for mastering. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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

Wade Foster (CEO) built Zapier into a profitable powerhouse without traditional VC funding—just $1M post-YC, then profitable ever since. On this episode, the co-founder and CEO shares how that capital discipline shaped their ability to pivot hard when AI hit. Wade also dishes on: The GPT-4 moment that shifted Zapier's roadmap A tested formula for AI agents that actually work How to incentivize internal AI adoption   Thanks for tuning in! Catch new episodes every Sunday Subscribe to Topline Newsletter. Tune into Topline Podcast, the #1 podcast for founders, operators, and investors in B2B tech. Join the free Topline Slack channel to connect with 600+ revenue leaders to keep the conversation going beyond the podcast!   Chapters: 00:00 Introduction: Wade Foster and the Age of Agents 02:38 Zapier's Origin: Solving the SaaS Integration Problem 04:14 From Zaps to Agents: The Evolution of Automation 05:07 How GPT-4 Changed Zapier's Internal Strategy 06:43 Unstructured Data and the Rise of Vibe Building 09:56 Why Long-Term Product Roadmaps Are Now Obsolete 13:00 Transitioning from PLG to Enterprise Amidst Competition 17:58 What Actually Works: Defining Successful Agentic Workflows 20:59 Building an AI-Literate Company Culture 26:18 Future Outlook: AI Bubbles vs. Product Reality 27:38 Navigating Board Expectations During Technology Shifts 30:23 Zapier's Capital Efficiency and Fundraising History 33:58 Founder Advice: Prioritizing Long-Term Thinking  

Forget resolutions. In this solo episode, I'm taking you inside the personal mindset shift I'm making for 2026 — one that's already reshaping how I lead, work, and live.Instead of a list of goals, I've chosen two powerful words to guide everything I do this year:

In every culture, there's a sense of how danger brings out the best in us when it comes to surrendering to God. For instance, I don't know what World War, you'd have to ask my old friend chat GPT, who really likes me, when this phrase became prevalent, it says, "there are no atheists in foxholes." A foxhole is a military term. It means, when you're in the infantry on the battlefield and you're being shot at, you have to dig really quickly a divot in the ground so you can be below ground level, so you don't get hit by mortar shrapnel or bullets. In such a precarious situation, people, other humans, have noted that that's when you start praying. "If you get me out of this one, I'll be good for the rest of my life," or whatever the soldier might be praying for at that time. So your Question is, how can we stay conscious of Kṛṣṇa all the time, mainly by keeping the transcendental vibration going. It's like tonight we have a medley of bhajana, chanting a chapter and reading. Developing a taste for that is very helpful. Have your bhajana together. I like to say, 'get your bhajana on'. Make sure that you have a bhajana. Because if you don't have a bhajana, then you're going to have scrolling, randomness. Scrolling just means random observation of the of the world. But when you're very deliberate and keep the transcendental vibration going, and you develop a repertoire where you can have variety, and you keep hearing and chanting and a repertoire of service also, then you'll notice that you're happy because whatever situation you're in, you're thinking of Kṛṣṇa. That's the idea of keeping the transcendental vibration going. ------------------------------------------------------------ To connect with His Grace Vaiśeṣika Dāsa, please visit https://www.fanthespark.com/next-steps/ask-vaisesika-dasa/?utm_source=youtube&utm_medium=video&utm_campaign=launch2025 ------------------------------------------------------------ Add to your wisdom literature collection: https://iskconsv.com/book-store/?utm_source=youtube&utm_medium=video&utm_campaign=launch2025 https://www.bbtacademic.com/books/?utm_source=youtube&utm_medium=video&utm_campaign=launch2025 https://thefourquestionsbook.com/?utm_source=youtube&utm_medium=video&utm_campaign=launch2025 ------------------------------------------------------------ Join us live on Facebook: https://www.facebook.com/FanTheSpark/ Podcasts: https://podcasts.apple.com/us/podcast/sound-bhakti/id1132423868 For the latest videos, subscribe https://www.youtube.com/@FanTheSpark For the latest in SoundCloud: https://soundcloud.com/fan-the-spark ------------------------------------------------------------ #globalyouthretreat #spiritualawakening #soul #spiritualexperience #spiritualpurposeoflife #spiritualgrowthlessons #secretsofspirituality #vaisesikaprabhu #vaisesikadasa #vaisesikaprabhulectures #spirituality #bhaktiyoga #krishna #spiritualpurposeoflife #krishnaspirituality #spiritualusachannel #whybhaktiisimportant #whyspiritualityisimportant #vaisesika #spiritualconnection #thepowerofspiritualstudy #selfrealization #spirituallectures #spiritualstudy #spiritualquestions #spiritualquestionsanswered #trendingspiritualtopics #fanthespark #spiritualpowerofmeditation #spiritualteachersonyoutube #spiritualhabits #spiritualclarity #bhagavadgita #srimadbhagavatam #spiritualbeings #kttvg #keepthetranscendentalvibrationgoing #spiritualpurpose

In this episode of the Crazy Wisdom podcast, host Stewart Alsop interviews Marcin Dymczyk, CPO and co-founder of SevenSense Robotics, exploring the fascinating world of advanced robotics and AI. Their conversation covers the evolution from traditional "standard" robotics with predetermined pathways to advanced robotics that incorporates perception, reasoning, and adaptability - essentially the AGI of physical robotics. Dymczyk explains how his company builds "the eyes and brains of mobile robots" using camera-based autonomy algorithms, drawing parallels between robot sensing systems and human vision, inner ear balance, and proprioception. The discussion ranges from the technical challenges of sensor fusion and world models to broader topics including robotics regulation across different countries, the role of federalism in innovation, and how recent geopolitical changes are driving localized high-tech development, particularly in defense applications. They also touch on the democratization of robotics for small businesses and the philosophical implications of increasingly sophisticated AI systems operating in physical environments. To learn more about SevenSense, visit www.sevensense.ai.Check out this GPT we trained on the conversationTimestamps00:00 Introduction to Robotics and Personal Journey05:27 The Evolution of Robotics: From Standard to Advanced09:56 The Future of Robotics: AI and Automation12:09 The Role of Edge Computing in Robotics17:40 FPGA and AI: The Future of Robotics Processing21:54 Sensing the World: How Robots Perceive Their Environment29:01 Learning from the Physical World: Insights from Robotics33:21 The Intersection of Robotics and Manufacturing35:01 Journey into Robotics: Education and Passion36:41 Practical Robotics Projects for Beginners39:06 Understanding Particle Filters in Robotics40:37 World Models: The Future of AI and Robotics41:51 The Black Box Dilemma in AI and Robotics44:27 Safety and Interpretability in Autonomous Systems49:16 Regulatory Challenges in Robotics and AI51:19 Global Perspectives on Robotics Regulation54:43 The Future of Robotics in Emerging Markets57:38 The Role of Engineers in Modern WarfareKey Insights1. Advanced robotics transcends traditional programming through perception and intelligence. Dymczyk distinguishes between standard robotics that follows rigid, predefined pathways and advanced robotics that incorporates perception and reasoning. This evolution enables robots to make autonomous decisions about navigation and task execution, similar to how humans adapt to unexpected situations rather than following predetermined scripts.2. Camera-based sensing systems mirror human biological navigation. SevenSense Robotics builds "eyes and brains" for mobile robots using multiple cameras (up to eight), IMUs (accelerometers/gyroscopes), and wheel encoders that parallel human vision, inner ear balance, and proprioception. This redundant sensing approach allows robots to navigate even when one system fails, such as operating in dark environments where visual sensors are compromised.3. Edge computing dominates industrial robotics due to connectivity and security constraints. Many industrial applications operate in environments with poor connectivity (like underground grocery stores) or require on-premise solutions for confidentiality. This necessitates powerful local processing capabilities rather than cloud-dependent AI, particularly in automotive factories where data security about new models is paramount.4. Safety regulations create mandatory "kill switches" that bypass AI decision-making. European and US regulatory bodies require deterministic safety systems that can instantly stop robots regardless of AI reasoning. These systems operate like human reflexes, providing immediate responses to obstacles while the main AI brain handles complex navigation and planning tasks.5. Modern robotics development benefits from increasingly affordable optical sensors. The democratization of 3D cameras, laser range finders, and miniature range measurement chips (costing just a few dollars from distributors like DigiKey) enables rapid prototyping and innovation that was previously limited to well-funded research institutions.6. Geopolitical shifts are driving localized high-tech development, particularly in defense applications. The changing role of US global leadership and lessons from Ukraine's drone warfare are motivating countries like Poland to develop indigenous robotics capabilities. Small engineering teams can now create battlefield-effective technology using consumer drones equipped with advanced sensors.7. The future of robotics lies in natural language programming for non-experts. Dymczyk envisions a transformation where small business owners can instruct robots using conversational language rather than complex programming, similar to how AI coding assistants now enable non-programmers to build applications through natural language prompts.

In their first episode of the New Year, Katherine Forrest and Scott Caravello unpack OpenAI's release of GPT-5.2, covering its performance on benchmarks like Humanity's Last Exam and on OpenAI's own GDPval—an evaluation designed to test the model's ability to match or surpass professionals' performance on real world tasks. Our hosts also examine the model's sharp drop in hallucinations and break down OpenAI's discussion of the model's resistance to prompt injections and how it stacks up under the company's safety framework. ## Learn More About Paul, Weiss's Artificial Intelligence practice: https://www.paulweiss.com/industries/artificial-intelligence

L'épisode que vous allez écouter est une rediffusion d'un épisode initialement diffusé le 16 mai 2025.Laurent Kretz reçoit Sylvain Peyronnet, cofondateur de Babbar.tech et chercheur en IA, ainsi que Grégory Pairin, directeur e-commerce chez Ocarat, spécialiste du référencement naturel et du digital. Ensemble, ils analysent les transformations profondes du référencement naturel à l'ère des modèles de langage et des moteurs de recherche génératifs.L'échange revient sur l'évolution du SEO, le fonctionnement des algorithmes de Google et les fuites de données qui ont permis d'en éclairer certains mécanismes. Sylvain explique comment des modèles comme BERT et GPT ont modifié la compréhension des requêtes et la manière dont les moteurs produisent des réponses. Grégory apporte un retour d'expérience concret côté e-commerce, dans un contexte où le SEO représente près de 40 % du chiffre d'affaires.Timecodes clés :00:00:00 Introduction 00:05:20 Histoire et évolution du SEO ; 00:22:50 Fuites Google & données comportementales dans le référencement ;00:34:00 L'arrivée des modèles de langage et leur impact sur le SEO ; 00:44:00 Qu'est-ce que la Generative Search Engine Optimization (GSO) ? ; 00:54:00 Stratégies pratiques pour apparaître dans les réponses des moteurs génératifs ; 01:05:00 Enjeux futurs et conseils pour les e-commerçants.Et quelques dernières infos à vous partager :Suivez Le Panier sur Instagram @lepanier.podcast !Inscrivez- vous à la newsletter sur lepanier.io pour cartonner en e-comm !Écoutez les épisodes sur Apple Podcasts, Spotify ou encore Podcast AddictHébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Is your practice patient- or production-driven? The answer should be purpose-driven. Kiera talks about how shifting your core values in a certain way can actually grow everything else. Episode resources: Subscribe to The Dental A-Team podcast Schedule a Practice Assessment Leave us a review Transcript: The Dental A Team (00:00) Hello, Dental A Team listeners. This is Kiera and I am excited. This is a podcast built just for you by you. If you ever want me to make a podcast for you, just email in Hello@TheDentalATeam.com or go to our website, TheDentalATeam.com and click on the podcast tab. You can submit topics for me to record for you. And today is a great one and I'm super excited about it. Someone asked production focus versus patient focus striking the right balance.   Does it have to be both? So is your practice driven by numbers or by people? And does it have to be a choice? I'm super jazzed. I'm super excited because this is the type of juicy stuff I like to get into because this is what offices talk about all the time. Oh my gosh, we're production focused. Well, that means you're not patient focused. Oh my gosh, you're patient focused. That means you're not production focused. Does it have to be? There's tension. It's tension. It's like, are you on the right side or the left side? Are you blue or are you Which side are you on?   Like there's tension here, production focus versus patient focus. Does it really have to be this debate? So I love this. Email me. You guys are love a good pen pal. Hello@TheDentalATeam.com. I like pen pals. You guys remember that? If you want to write me a letter, you can send me a letter. It's in Verdi, Nevada on the website, P.O. Box. I think it's 635 Verdi, Nevada. No clue what it is, but I will get it and I'll send you a postcard back. So pen pal for real, email us.   You guys, really do love a good pen pal. I will seriously send you a letter back. So ⁓ write me. I would love to hear from you. But I'm curious, does it have to be production focus or patient focus or can it be both? Is it the chicken or the egg? I definitely think that there has to be a way because the most successful practices integrate production and patience. So the answer is yes, it can be both. And I don't care what side of the coin you're on. I'm gonna teach you that you can actually be on both sides of the coin and still maintain your ethics.   like your ethical integrity, all of that. You guys, this is the Dental A Team. I'm obsessed with dentists. I'm obsessed with dental teams. I'm obsessed with making you happy. I'm obsessed with positively impacting this world in the greatest way possible. And that's why we built this podcast free for you to give you all the tips and tricks. And all I ask in return is that you leave us a review and share this with somebody that can change their life. My goal is to have this podcast into the hands of every single dental office out there. And guys, you are crushing it. We are in the millions of downloads and I can't do that without you. So please today.   share, download, or leave us a five star review. That means the world to me and I do read those reviews. So thank you. Thank you for everybody who reads those reviews. I appreciate each of you. So today I want to talk about patient focused version of production focused because you know, I got a pen pal out there. production focused means that we're focused on high volume, goal driven, and we're going to probably have burnout. Like that's the drive. It is a lot of times ego. That's okay. So when I'm talking to you.   You can test yourself right now. Are you ready? I'm gonna say, hey, what is your production? Now, to answer that, what's your production? If you just told me your number in gross, you're a little ego driven and I love you for it. And I'm gonna tell you that that is one of the worst things to do because there's no way for us you to ever collect it. I was talking to a practice the other day and they're like, yes, Kiera, we are a $7 million practice and we had a million dollars worth of write-offs. And I was like, well, shoot. So.   You're actually, think they actually have two million. So you're not a seven million, you're a five million. That's a bit of a minute. So you're actually a five million dollar practice and I'd rather talk about real numbers because then I can actually truly get you to seven million rather than feeding your ego at this. So that tends to be the case where you're, if you, you might be a bit production. If you're presenting those in gross, ⁓ present them in, it's okay to your buddies. You can present in gross. To me, to here, to this conversation in real life.   please, please, please present them in net, what you can actually collect. Now, if we're too patient focused, we tend to run at a slower pace, high trust, but we risk a lot of inefficiency and you actually risk the, like, you really do run a risk of you're not looking at the numbers and you actually can create a really, really, really scary spot where you actually are in like profit row where you have no money. ⁓ And so you gotta have both.   We've got to have production where we're able to serve our patients and we've got to care about our patients. We've got to make sure that both of those come together because that's a true business. This is what we're looking for. So I just want you to look at yourself right now and I want you to audit you and your practice. Where do you lean more? Okay. So do you lean a little more left? Do you lean a little more right? Do you lean a little more production focused or do you lean a little more patient focused? It's okay. There's no right or wrong. I just want you to like really look at yourself and assess what route do you fall?   because it's gonna help you, okay? So where are you? We're not like all patient or all production, but which way do you lean? I want you to answer that. You can pen pal me. Remember, I got pen pals out there. So be another pen pal for me. And then step two is I want you to marry metrics with meaning, which isn't that cute? Yes, chat GPT helped me on that one. Marry metrics with meaning, I love that. I was like, that is such a good way to bring this to the table. So we want you guys to be like in the middle, we're not production, we're not patient, we're purpose.   Did you love that? Another P, we're not patient, we're not production, we're purpose driven. So what this is going to be is you can actually like increase case acceptance to outcomes, not quotas. So it's not like we need 20 crowns, we need to help this many patients. help team members see, like I love Tiff, she said this, she was like, production is the measuring stick to see how many patients we're serving. That feels so much better than like we got to hit 150,000.   No, 150,000 shows is how many patients were able to serve. Let's quantify that up to how many patients and now let's put that up to 200,000 and serve that many patients. So we'll help you guys see that like this is a reflection of care. It's not like just, I don't know, like a number on a scorecard. It's people. You guys, all that production was people that we were able to change their lives. That's what we do in Dental A Team. I literally like, when we talk about our numbers, for a while I put up numbers and it was just a number.   So you can tell it's a little bit more production focused rather than patient focused. And it didn't matter to me. And then when I was like, okay, we're going to go out and I want to serve, like I want Dental A Team to serve 500 dental practices. Like in one year, I want us to have that many that to me, like think of how many lives we're going to change. Cause my ultimate goal is impact to possibly impact this world in the greatest way possible. So I was like, all right, let's put an audacious goal out there. I want to serve 500 offices. Yeah, you can join us. Yes, of course.   And like now it became funds. Like the number is tied to people. Cause I ultimately care about people. care about impact. Money can have impact, but it doesn't drive me. What drives me is changing people's lives. Life is my passion, dentistry is my platform. So how can you help your team see that? So we have to help them see like for me with teams, case acceptance, I'm just saying like that's how many smiles you were able to like truly benefit. There's so many lives you're able to change. I believe the case acceptance is life changing. I was the patient on the other side of that coin.   who literally had my life changed by identities. So when we shifted like KPIs are metrics, yes, but metrics have meaning and their purpose. So what does this case acceptance actually reflect? What does this production actually reflect? What did these new patients numbers actually reflect? And when we look at it as this like patient centric, it becomes so much more fun. I did this in a team meeting the other day where, gosh, we were sitting there and I was like, all right, rattle off to me like why you guys go to Chick-fil-A? And they're like talking about it. Not one of them said price.   Not one of them. Not one of them when I talked about McDonald's said price. So when I looked at this, I thought, okay, people go to Chick-fil-A for the experience. And I thought, how can we become a more patient centric practice that uses metrics to see how we're doing of serving those patients? That's what it is. That's how you marry metrics with meaning. These numbers on a KPI scorecard are telling me the vitals of how good we're serving our patients.   So when I look at our hygiene, I wanna know, are we diagnosing perio or are we doing bloody profies? When I look at Florida, you guys, I'm a huge proponent of Florida. If you're not, that's okay, we can still be friends. I'm here to also teach you holistic. I love Florida. Florida changed my life. It prevented so many cavities for me, like truly was life-changing. So I'm like, absolutely, give it to patients. So when I look at your hygiene numbers, I'm not looking at like, did you get your eight out of eight today? I'm looking at like, did you help proactively prevent decay on all of your patients today?   Of course, if they don't want it, that's fine. But like, let's use our words, words are free. Let's set it up in a way to help more patients say yes. I am patient centric with production numbers and using words to get the results I'm looking for. I'm looking for outcomes, not effort. One of my favorite, favorite, favorite lines, and it's probably gonna become like a core value. My team doesn't know this, you guys, is we measure our, we measure by outcomes, not activity. ⁓ we measure it by outcomes.   not activity because I can sit here and say, I served this many patients, but if I didn't close any cases, I did not get the outcome of helping truly get them the smiles and the health that they deserve. Bottom line. So then step three is you got to change your culture. You got to have a culture that supports both. It's got to be efficiency and empathy. It's got to be production and patient. It's got to be like truly driven. And I've got so many offices like Kiera, I don't want to my team about the numbers. That's fine. You don't have to.   But can't we also help them see that the numbers are helping more patients? Every team I've ever gone into has told me the reason they're in tennis tree is to help change patients' lives. That's why they're here. So when I look at this, I'm like, okay, if that's why we're all here, how do we know that we're actually helping the number of patients that we could? Like genuinely somebody tell me, how do we actually know in a tangible, non-emotional way? How do I know? So we've got to help people see that like, okay, fantastic. We have a culture where when we hit our numbers,   We know we serve the patients that we're set here to serve. Period. You're not gonna go away from that and helping people see that numbers equate the outcomes we're looking for. Numbers help us serve patients. And on the flip side, when we, like you guys, there's a book called Unreasonable Hospitality. Have your team do fun things like that where we celebrate the birthdays, the weddings, the anniversaries, the celebrations. We have like a little gift basket on the side where we can quickly go and have some fun with those people to make this magic moment for our patients.   have magic moments that produce results. Team training, we gotta do patient and production language. We've gotta be empathetic. So for me to say like, my gosh, I'm so excited that you don't work with Dr. Jones. Dr. Jones is incredible. They're gonna take great care of you. Let's get you scheduled for this appointment. I know Dr. Jones definitely wants to get you back. I've got Monday or Wednesday, which works best for you. That was patient and production centric, both in the same exact equation.   when I talk to them about case acceptance, it's like, perfect. So here's the treatment that Dr. Jones diagnosed for you. This is your total out of pocket. This is your insurance estimate. This will be your total when I see you on Wednesday. What questions do you have for me? I want you to be rock solid moving forward. Again, production and patient focus. I want them to be so solid. I'm genuinely so concerned about them. I really want them to be solid. If they tell me they got to talk to their spouse, absolutely, 100%. I want you to talk to your spouse.   Help me what questions they're going to ask. That way I can make sure you're fully prepped when you chat with them. That's production and patient focused. A cancellation calls in. my gosh, what's going on? Tell me, like, ⁓ I've been so worried about you. Like help me understand where you at, what's going on. Like, are you okay? Tell me like, you're sick. Like, my gosh, what's going on? I know there's been a bug going around. Someone says I can't make it from work. my gosh. Like, I'm so sorry to hear that. Tell me what's going on. Let's find a solution. I know Dr. wanted to see you.   I can't wait to see you and I know there's gonna be a solution for us. Production and patient focus. And I think when teams see that you don't have to be one or the other, production focus can come across aggressive, patient focus can come across non-aggressive and very like twiddling my thumb sometimes. And so I'm like the true win is the middle ground. The true win is where we see that patients need to feel loved.   and important and that they're humans. And they also need to see that we love them so much. And we're going to make sure that they get the treatment that they need to get done. And we're going to help use our words to make sure it's easy for them to say yes. Both are doable. Both are right. Both are necessary. This is how you guys are able to have it. And so I think you guys can have conversations with the team. How can we be patient and production focused? How can we marry the two because we know the best practices are both.   They are, there's not one lever that's stronger than the other. Both are married together as a perfect whole, two perfect complete whole. How can we be more, if you know from, remember we did an audit, if you know you're a little more production focused, how can you be a bit more patient focused? Have that come up in the team. If you know you're a bit more patient focused, how can we be a bit more production focused? And I know you might be bristling on both sides. Production focused people might think that, my gosh, it's a complete waste of time to be patient focused.   Patient focused people, they're like, my gosh, you'll maybe be aggressive and like force these people into treatment. The answer is no to both of those. Us treating people like human beings, production focused teams will actually make those patients want to be here more. Our teams that are more patient focused, turning more production focused, it's gonna help us make sure that we're not missing things on the patients, that we're not doing inadequate care. And that actually that patient's not leaving confused and that they truly know what they need to do. And it's very clear of next steps for them.   Clear is kind. Being direct is kind. Loving people as people is kind. So I'd really encourage you to adopt this into your practice. And if you struggle with this, if your doctor is like, ⁓ I am not having that team meeting, I'm not having that conversation, great. That's why we have a job. That's what we love to do. Our job is to align doctors and team members to help team members see that production is patient focused and to see that patient focus is production focused. Both sides are necessary.   You need both of them. And so to be able to help you and your team get there, I think is a beautiful thing. So I would really, really, really encourage you to be patient and production focused, both of them. Look to see where you could be a little bit more on whichever side you don't naturally lean to. I know you can already do more on the side that you naturally lean to. Go the other side. I want you to think about it. I want you to bring that into your culture. And I'd really encourage you. And if you struggle with this or you're like, I don't really know how to do this, reach out. Hello@TheDentalATeam.com.   It's not just about this. It's about other goals. It's about other spaces. It's about other awkward conversations that you just don't know how to navigate. It's about getting your team and you doctors rowing in the exact same direction. And that's what we're here to do. So reach out. Hello@TheDentalATeam.com. And as always remember, patient and production is purpose driven dentistry. And that's what you're here to do. And I know that you're here for that. I know that you care so much about your patients and that's why I wanted to really bring this up. So thanks for the pen pal. Thanks for writing. I'd love to hear from more of you. Hello@TheDentalATeam.com.   Go to our website, give me some more topics and reach out. I'd love for you to be one of our 500 practices. We get to help love serve and have that be the purpose to positively impact and change your life for the better. Not just your practice, but you as a person. Because at the end of the day, I care about you as a human being. I care about you thriving. I care about you having the practice of your dreams and having the team of your dreams because I care about you as a human. So reach out and as always know that I'm rooting for you. Know that I care about you.   Know that I adore you as always. Thanks for listening. I'll catch you next time on the Dental A Team Podcast.  

In this week's episode of the Rich Habits Podcast, Robert Croak and Austin Hankwitz answer your questions!---

In this episode we speak with Avichay Nissenbaum. A serial entrepreneur turned investor, and the founding partner of lool Ventures. He built and sold two startups - SmarTeam (acquired by Dassault Systèmes) and Yedda (acquired by AOL) - before dedicating his career to backing founders. Lool Ventures has invested over $200M and helped shape some of Israel's standout companies, including Beewise, NoTraffic, and Eleos Health. This conversation goes deep into the psychology of decision making, the emotional reality of investing, and the mindset that helps founders and investors navigate uncertainty. What We Dig Into: Pattern Recognition as a Superpower Avichay explains why VC is about seeing patterns long before they become obvious. He shares how reviewing 400–800 startups a year sharpens intuition, and why “sensor-tuning” is one of the most important skills an investor develops. He believes founders are often the ones who intuitively sense the future first. The AI Shift: Native vs. AI-Resilient Companies Avichay breaks down a framework every founder should understand: • AI Native - companies born on AI-first architecture. • AI Resilient - deep-tech companies that won't get erased by the next Gemini or GPT feature drop. He calls AI “the biggest shift of wealth of our generation,” and explains why resilience matters more than hype. What Makes a Founder Fundable He is blunt about what truly matters: • Tenacity • Resilience • Skin in the game • Hunger • Ability to execute under pressure He calls this the capacity to survive a “roller coaster on steroids.” He also explains why lool Ventures loves bootstrappers and founders who have already built a minimal product before fundraising. The Emotional Reality of Investing One of the most insightful parts of the discussion. Avichay describes the difficulty of shifting from builder to observer. He talks about: • Seeing founders drive straight into a wall • Knowing the solution but not owning the steering wheel • Balancing heart and logic • Acting as an advisor, not a commander His analogy: “It's like sitting next to the driver and you can't touch the wheel.” The Role of Naivety Avichay argues that naivety is often a hidden advantage. It creates the space for original thinking, passion, and courage - the ingredients behind unconventional breakthroughs. His Entrepreneurial Beginnings We go back to the moment he left a stable career to build something new. At 25, with no entrepreneurial experience, he pitched a radical product vision to his CEO, was turned down, and decided to do it himself. He shares how: • Most early feedback was “no.” • The first yes arrived only after many rejections. • Passion and discomfort worked together to pull him forward. His clarity is powerful: “You don't know. But something burns inside you.”

From pre-training data curation to shipping GPT-4o, o1, o3, and now GPT-5 thinking and the shopping model, Josh McGrath has lived through the full arc of OpenAI's post-training evolution—from the PPO vs DPO debates of 2023 to today's RLVR era, where the real innovation isn't optimization methods but data quality, signal trust, and token efficiency. We sat down with Josh at NeurIPS 2025 to dig into the state of post-training heading into 2026: why RLHF and RLVR are both just policy gradient methods (the difference is the input data, not the math), how GRPO from DeepSeek Math was underappreciated as a shift toward more trustworthy reward signals (math answers you can verify vs. human preference you can't), why token efficiency matters more than wall-clock time (GPT-5 to 5.1 bumped evals and slashed tokens), how Codex has changed his workflow so much he feels "trapped" by 40-minute design sessions followed by 15-minute agent sprints, the infrastructure chaos of scaling RL ("way more moving parts than pre-training"), why long context will keep climbing but agents + graph walks might matter more than 10M-token windows, the shopping model as a test bed for interruptability and chain-of-thought transparency, why personality toggles (Anton vs Clippy) are a real differentiator users care about, and his thesis that the education system isn't producing enough people who can do both distributed systems and ML research—the exact skill set required to push the frontier when the bottleneck moves every few weeks. We discuss: Josh's path: pre-training data curation → post-training researcher at OpenAI, shipping GPT-4o, o1, o3, GPT-5 thinking, and the shopping model Why he switched from pre-training to post-training: "Do I want to make 3% compute efficiency wins, or change behavior by 40%?" The RL infrastructure challenge: way more moving parts than pre-training (tasks, grading setups, external partners), and why babysitting runs at 12:30am means jumping into unfamiliar code constantly How Codex has changed his workflow: 40-minute design sessions compressed into 15-minute agent sprints, and the strange "trapped" feeling of waiting for the agent to finish The RLHF vs RLVR debate: both are policy gradient methods, the real difference is data quality and signal trust (human preference vs. verifiable correctness) Why GRPO (from DeepSeek Math) was underappreciated: not just an optimization trick, but a shift toward reward signals you can actually trust (math answers over human vibes) The token efficiency revolution: GPT-5 to 5.1 bumped evals and slashed tokens, and why thinking in tokens (not wall-clock time) unlocks better tool-calling and agent workflows Personality toggles: Anton (tool, no warmth) vs Clippy (friendly, helpful), and why Josh uses custom instructions to make his model "just a tool" The router problem: having a router at the top (GPT-5 thinking vs non-thinking) and an implicit router (thinking effort slider) creates weird bumps, and why the abstractions will eventually merge Long context: climbing Graph Blocks evals, the dream of 10M+ token windows, and why agents + graph walks might matter more than raw context length Why the education system isn't producing enough people who can do both distributed systems and ML research, and why that's the bottleneck for frontier labs The 2026 vision: neither pre-training nor post-training is dead, we're in the fog of war, and the bottleneck will keep moving (so emotional stability helps) — Josh McGrath OpenAI: https://openai.com https://x.com/j_mcgraph Chapters 00:00:00 Introduction: Josh McGrath on Post-Training at OpenAI 00:04:37 The Shopping Model: Black Friday Launch and Interruptability 00:07:11 Model Personality and the Anton vs Clippy Divide 00:08:26 Beyond PPO vs DPO: The Data Quality Spectrum in RL 00:01:40 Infrastructure Challenges: Why Post-Training RL is Harder Than Pre-Training 00:13:12 Token Efficiency: The 2D Plot That Matters Most 00:03:45 Codex Max and the Flow Problem: 40 Minutes of Planning, 15 Minutes of Waiting 00:17:29 Long Context and Graph Blocks: Climbing Toward Perfect Context 00:21:23 The ML-Systems Hybrid: What's Hard to Hire For 00:24:50 Pre-Training Isn't Dead: Living Through Technological Revolution

Send us a textIn Part 2 of our year-end reflections, Alex speaks with educators, founders, investors, and platform leaders about what 2026 may bring for AI and learning at scale.

Welcome to the 2025 podcast recap. What a ride! This episode lets me do two things I love: celebrate the baddest ass people on the planet who showed up on this show, and gently remind you that if you missed even one episode, you have an absolute treasure chest waiting for you. We are talking season 10 podcast recap-style, which still blows my mind. Ten seasons. You are going to hear quick nuggets from leaders, entrepreneurs, authors, coaches, creators, and straight-up legends. These are mini master classes. Listen once for the fun, then come back for the education and the "wait, how did I miss that the first time" moments. Expect authentic leadership and modern leadership strategies that hit you right in the heart and right in the calendar. Expect career development wisdom, interview confidence tips, HR career advice, and job search strategy 2025 conversations that will make you want to take control of your career. Expect entrepreneurship mindset and personal branding tips, content strategy for entrepreneurs, and marketing strategy for small business ideas that will make you want to build a brand and actually commit to the content, even when your couch is begging you not to. And because we are living in the future, yes, we get into AI tools for professionals, prompting tips for beginners, how to write better prompts for ChatGPT, custom GPT talk, and AI productivity for business, including AI interview practice and AI for career coaching. If you have been curious about using ChatGPT for work, or you want to stop getting "meh" results and start getting "whoa" results, you will love these segments. We also hit the real stuff. Sales mindset, boundaries, how to handle rejection, and more lessons from experts from their respective fields. So if you want the best podcast episodes of 2025 in one place, this is it. If you want a season recap podcast that feels like a hype video for your next level, buckle up. Please share this with a friend who needs a little optimism, and tell me in the comments which guest you are going back to binge first. Happy Holidays, Happy New Year, and get ready to kick 2026 in the hindquarters. Ripple with Steve Harper Instagram: http://instagram.com/rippleon Facebook: https://www.facebook.com/rippleon X: https://twitter.com/rippleon Website: http://www.ripplecentral.com Stay in the loop by being a part of the Ripple mail list: https://ripplecentral.com/subscribe Be a Patron: https://www.patreon.com/SteveHarper Join our ever-growing community of Ripplers in The Pond: https://ripplecentral.com/pond To inquire about my availability for conference keynotes, corporate training, or performance coaching, please contact info@ripplecentral.com.

Shelly Palmer has spent 45 years watching technology reshape every industry—from writing news themes for CBS to consulting with every major media company on AI strategy. On this year-end recap, he cuts through the noise with one devastating observation: 2025 was the year everyone talked about AI while almost nobody actually used it. Executives shook their heads knowingly in meetings, pontificated about capabilities the models don't yet have, and parroted nonsense they read from other people who knew nothing. But when you asked one innocent question, they crumbled.In the News: CES 2026 shapes up with Nvidia sponsoring two full days of AI training. Samsung is skipping the main floor for a massive offsite activation. Sony brings no electronics—only Honda's experimental vehicles. The TCL and Chinese companies' presence hinges on tariff policy. The innovation series breakfast that Shelly runs is becoming an official CES event after a decade of independence.The conversation spirals into deeper territory: $3 trillion in government money is stacked behind AI development. The U.S. explicitly states it must beat China to AGI—making this the Manhattan Project of our lifetime. Shelly walks through what he's seen in successful companies (leadership using the tech, paid "Tech Tuesdays" for AI experiments, cross-discipline teams with SecOps and legal at the table) versus the chaos of places with no process. He breaks down what's real—drone warfare, cybersecurity applications, robotics—versus what's hot air. And he makes a case that won't be killed by AI itself, but by militarized applications and the geopolitical arms race we're already in.5 Key Takeaways from Shelly:Leadership belief and hands-on use are non-negotiable. Companies winning with AI have senior leaders who actually use the technology. When the CEO walks into an LT meeting saying "I built this agent over the weekend," everyone else starts experimenting too.The recipe for AI success has three ingredients: leadership belief, paid time to experiment (Tech Tuesdays/Thursdays with real budgets), and cross-discipline teams (SecOps, legal, compliance, risk) paving the way. Chaos erupts without this structure.You cannot build a point of view on AI from reading blogs or watching YouTubers. Pick a personal project you care about, go hands-on with a model (Claude, Gemini, GPT), and complete it from beginning to end. Only lived experience grounds your understanding.AI parallelizes with web 1.0: In 1998, you had to hand-code HTML, build databases manually, write raw JavaScript. Today you can vibe code a site in 90 seconds. AI will eventually reach "spin me up an expert that does X" without asking questions—we're not there yet, but it's inevitable.It's both bubble and Manhattan Project. Some valuations are insane and will burst. But military applications, cyber warfare, drone control, robotics—those aren't going anywhere. The government won't back off. Both outcomes happen simultaneously.This episode is brought to you by Zappar, creators of Mattercraft—the leading visual development environment for building immersive 3D web experiences for mobile headsets and desktop. Mattercraft combines game engine power with web flexibility and features an AI assistant to help you design, code, and debug in real time in your browser. Build smarter at mattercraft.io.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

From Berkeley robotics and OpenAI's 2017 Dota-era internship to shipping RL breakthroughs on GPT-4o, o1, and o3, and now leading model development at Cursor, Ashvin Nair has done it all. We caught up with Ashvin at NeurIPS 2025 to dig into the inside story of OpenAI's reasoning team (spoiler: it went from a dozen people to 300+), why IOI Gold felt reachable in 2022 but somehow didn't change the world when o1 actually achieved it, how RL doesn't generalize beyond the training distribution (and why that means you need to bring economically useful tasks into distribution by co-designing products and models), the deeper lessons from the RL research era (2017–2022) and why most of it didn't pan out because the community overfitted to benchmarks, how Cursor is uniquely positioned to do continual learning at scale with policy updates every two hours and product-model co-design that keeps engineers in the loop instead of context-switching into ADHD hell, and his bet that the next paradigm shift is continual learning with infinite memory—where models experience something once (a bug, a mistake, a user pattern) and never forget it, storing millions of deployment tokens in weights without overloading capacity. We discuss: Ashvin's path: Berkeley robotics PhD → OpenAI 2017 intern (Dota era) → o1/o3 reasoning team → Cursor ML lead in three months Why robotics people are the most grounded at NeurIPS (they work with the real world) and simulation people are the most unhinged (Lex Fridman's take) The IOI Gold paradox: "If you told me we'd achieve IOI Gold in 2022, I'd assume we could all go on vacation—AI solved, no point working anymore. But life is still the same." The RL research era (2017–2022) and why most of it didn't pan out: overfitting to benchmarks, too many implicit knobs to tune, and the community rewarding complex ideas over simple ones that generalize Inside the o1 origin story: a dozen people, conviction from Ilya and Jakob Pachocki that RL would work, small-scale prototypes producing "surprisingly accurate reasoning traces" on math, and first-principles belief that scaled The reasoning team grew from ~12 to 300+ people as o1 became a product and safety, tooling, and deployment scaled up Why Cursor is uniquely positioned for continual learning: policy updates every two hours (online RL on tab), product and ML sitting next to each other, and the entire software engineering workflow (code, logs, debugging, DataDog) living in the product Composer as the start of product-model co-design: smart enough to use, fast enough to stay in the loop, and built by a 20–25 person ML team with high-taste co-founders who code daily The next paradigm shift: continual learning with infinite memory—models that experience something once (a bug, a user mistake) and store it in weights forever, learning from millions of deployment tokens without overloading capacity (trillions of pretraining tokens = plenty of room) Why off-policy RL is unstable (Ashvin's favorite interview question) and why Cursor does two-day work trials instead of whiteboard interviews The vision: automate software engineering as a process (not just answering prompts), co-design products so the entire workflow (write code, check logs, debug, iterate) is in-distribution for RL, and make models that never make the same mistake twice — Ashvin Nair Cursor: https://cursor.com X: https://x.com/ashvinnair_ Chapters 00:00:00 Introduction: From Robotics to Cursor via OpenAI 00:01:58 The Robotics to LLM Agent Transition: Why Code Won 00:09:11 RL Research Winter and Academic Overfitting 00:11:45 The Scaling Era and Moving Goalposts: IOI Gold Doesn't Mean AGI 00:21:30 OpenAI's Reasoning Journey: From Codex to O1 00:20:03 The Blip: Thanksgiving 2023 and OpenAI Governance 00:22:39 RL for Reasoning: The O-Series Conviction and Scaling 00:25:47 O1 to O3: Smooth Internal Progress vs External Hype Cycles 00:33:07 Why Cursor: Co-Designing Products and Models for Real Work 00:34:14 Composer and the Future: Online Learning Every Two Hours 00:35:15 Continual Learning: The Missing Paradigm Shift 00:44:00 Hiring at Cursor and Why Off-Policy RL is Unstable

ChatGPT stands as the biggest AI chatbot, but LikeFolio's data shows a closing gap. Landon Swan says Alphabet's (GOOGL) Gemini grew over 300% year-over-year compared to GPT's 87%. He explains how Alphabet is getting the word out on Gemini as the stock soars off April lows. Landon later talks about another digital fortress Alphabet has under its thumb: YouTube. ======== 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

On this episode of The AI Report, AI anchors Artie Intel and Micheline Learning break down the latest, real‑world developments in artificial intelligence, from mind‑blowing breakthroughs to genuinely worrying power grabs. You’ll hear how frontier models like GPT‑5.2 and the newest multimodal systems are rewriting the rules for coding, creativity, and knowledge work, while open and regional models race to catch up and cut costs.​ Artie and Micheline walk you through AI that spots cancer, boosts medical regulators, and sharpens storm forecasts, then pivot hard into the political fight over AI regulation, including a new U.S. executive order that loosens some safety guardrails in the name of “innovation.” They dig into what this all means for your job, your data, and your ability to tell human‑made content from machine‑generated noise, framing 2025 as an “AI hype correction” year where real value and real risks finally start to separate.​ This episode treats AI as what it is: the most powerful tool humans have ever built, and a potential chaos engine if left unsupervised. If you care about where AI is actually going, not just what the marketing says, this is your briefing from the cloud. Get your good time on and celebrate the new year in style at Topgolf! Shake up the way you celebrate the new year. We’ll be up playing all night with high-energy music, chef-crafted bites, and fun drinks. Find a location at TopGolf.com

L'intelligence artificielle est-elle réellement prête à remplacer les humains au travail ? La question agite les entreprises, entre fantasmes de productivité totale et scepticisme assumé. Pour dépasser les discours, des chercheurs de Carnegie Mellon University ont tenté une expérience originale : simuler une entreprise presque entièrement peuplée d'agents d'intelligence artificielle. Les résultats, publiés en prépublication sur arXiv, sont loin d'annoncer la fin du salariat humain. Les scientifiques ont confié le fonctionnement de cette entreprise virtuelle à des agents issus des modèles les plus en vue du moment : Claude d'Anthropic, GPT-4o d'OpenAI, Gemini de Google, Nova d'Amazon, Llama de Meta ou encore Qwen d'Alibaba. Chaque agent s'est vu attribuer un poste classique : analyste financier, chef de projet, ingénieur logiciel. En parallèle, d'autres agents jouaient le rôle de collègues ou de services internes, comme les ressources humaines.Sur le papier, tout était en place. Dans les faits, la performance est restée très limitée. Le meilleur élève, Claude 3.5 Sonnet, n'a réussi à mener à terme que 24 % des tâches confiées. En incluant les missions partiellement accomplies, son score plafonne à 34,4 %. Gemini 2.0 Flash arrive en deuxième position, avec à peine 11,4 % de tâches finalisées. Aucun autre modèle ne dépasse la barre des 10 %. Un contraste saisissant avec les promesses d'autonomie souvent associées à ces systèmes. Les chercheurs identifient plusieurs causes à ces échecs. Les agents peinent à comprendre les implicites humains : demander un fichier en « .docx » ne leur permet pas toujours de déduire qu'il s'agit d'un document Word. Ils manquent aussi de compétences sociales élémentaires et se retrouvent rapidement bloqués lorsqu'ils doivent naviguer sur le Web, gérer des fenêtres surgissantes ou interpréter des interfaces complexes. Plus préoccupant encore, certains agents estiment avoir réussi une tâche après en avoir simplement contourné les étapes difficiles.En clair, cette expérience rappelle une réalité souvent oubliée : si les IA excellent sur des tâches ciblées et bien définies, elles restent très loin de pouvoir gérer seules un environnement de travail réel, avec ses imprévus, ses règles implicites et ses interactions humaines. Le remplacement généralisé des salariés, lui, peut encore attendre. Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

Welcome to AI Unraveled (December 30th, 2025): Your strategic briefing on the business, technology, and policy reshaping artificial intelligence.Hardware & Industry ConsolidationNvidia's $20B Dominance Play: In a massive move to secure its inference future, Nvidia has agreed to acquire key assets and employees from AI chip startup Groq for $20 billion. The deal is structured as an asset purchase and non-exclusive licensing agreement—likely to navigate antitrust scrutiny—allowing Nvidia to integrate Groq's ultra-fast LPU (Language Processing Unit) technology into its "AI Factory" roadmap.Cursor Acquires Graphite:Model Breakthroughs & BenchmarksChina's Z.ai Takes the Crown: Z.ai's new GLM-4.7 model has topped open-source benchmarks, reportedly outperforming GPT-5.1 High in coding tasks and introducing "Preserved Thinking" to prevent context decay in long agentic workflows.Claude Opus 4.5's Stamina: A new analysis by evaluation firm METR reveals that Anthropic's Claude Opus 4.5 can successfully execute tasks that require nearly 5 hours of human work,Poetiq Crushes Reasoning Benchmarks:Policy, Risk & GeopoliticsChina's "Ideological Test": New regulations in China require AI chatbots to pass a rigorous 2,000-question ideological exam,Pentagon Partners with xAI: The Department of Defense will embed Grok-based AI systems directly into its GenAI.mil platform by early 2026,Italy vs. Meta:Society & The WorkforceThe "Slop" Epidemic: A new study finds that over 20% of videos recommended to new YouTube users are now "AI slop"—low-quality, generative content designed solely to farm views.OpenAI's "Head of Preparedness": Sam Altman is hiring a lead to secure "systems that can self-improve,"Sal Khan's 1% Solution: Khan Academy founder Sal Khan is proposing that companies donate 1% of profits to retrain workers displaced by the looming AI job apocalypse.Keywords: Nvidia, Groq, GLM-4.7, Z.ai, Claude Opus 4.5, AI Slop, GenAI.mil, Pentagon, xAI, Grok, ARC-AGI-2, Graphite, Sal Khan, AI Regulation, Antitrust.Host Connection & Engagement:Etienne on Linkedin: https://www.linkedin.com/in/enoumen

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Mike Bakon to explore the fascinating intersection of hardware hacking, blockchain technology, and decentralized systems. Their conversation spans from Mike's childhood fascination with taking apart electronics in 1980s Poland to his current work with ESP32 microcontrollers, LoRa mesh networks, and Cardano blockchain development. They discuss the technical differences between UTXO and account-based blockchains, the challenges of true decentralization versus hybrid systems, and how AI tools are changing the development landscape. Mike shares his vision for incentivizing mesh networks through blockchain technology and explains why he believes mass adoption of decentralized systems will come through abstraction rather than technical education. The discussion also touches on the potential for creating new internet infrastructure using ad hoc mesh networks and the importance of maintaining truly decentralized, permissionless systems in an increasingly surveilled world. You can find Mike in Twitter as @anothervariable.Check out this GPT we trained on the conversationTimestamps00:00 Introduction to Hardware and Early Experiences02:59 The Evolution of AI in Hardware Development05:56 Decentralization and Blockchain Technology09:02 Understanding UTXO vs Account-Based Blockchains11:59 Smart Contracts and Their Functionality14:58 The Importance of Decentralization in Blockchain17:59 The Process of Data Verification in Blockchain20:48 The Future of Blockchain and Its Applications34:38 Decentralization and Trustless Systems37:42 Mainstream Adoption of Blockchain39:58 The Role of Currency in Blockchain43:27 Interoperability vs Bridging in Blockchain47:27 Exploring Mesh Networks and LoRa Technology01:00:25 The Future of AI and DecentralizationKey Insights1. Hardware curiosity drives innovation from childhood - Mike's journey into hardware began as a child in 1980s Poland, where he would disassemble toys like battery-powered cars to understand how they worked. This natural curiosity about taking things apart and understanding their inner workings laid the foundation for his later expertise in microcontrollers like the ESP32 and his deep understanding of both hardware and software integration.2. AI as a research companion, not a replacement for coding - Mike uses AI and LLMs primarily as research tools and coding companions rather than letting them write entire applications. He finds them invaluable for getting quick answers to coding problems, analyzing Git repositories, and avoiding the need to search through Stack Overflow, but maintains anxiety when AI writes whole functions, preferring to understand and write his own code.3. Blockchain decentralization requires trustless consensus verification - The fundamental difference between blockchain databases and traditional databases lies in the consensus process that data must go through before being recorded. Unlike centralized systems where one entity controls data validation, blockchains require hundreds of nodes to verify each block through trustless consensus mechanisms, ensuring data integrity without relying on any single authority.4. UTXO vs account-based blockchains have fundamentally different architectures - Cardano uses an extended UTXO model (like Bitcoin but with smart contracts) where transactions consume existing UTXOs and create new ones, keeping the ledger lean. Ethereum uses account-based ledgers that store persistent state, leading to much larger data requirements over time and making it increasingly difficult for individuals to sync and maintain full nodes independently.5. True interoperability differs fundamentally from bridging - Real blockchain interoperability means being able to send assets directly between different blockchains (like sending ADA to a Bitcoin wallet) without intermediaries. This is possible between UTXO-based chains like Cardano and Bitcoin. Bridges, in contrast, require centralized entities to listen for transactions on one chain and trigger corresponding actions on another, introducing centralization risks.6. Mesh networks need economic incentives for sustainable infrastructure - While technologies like LoRa and Meshtastic enable impressive decentralized communication networks, the challenge lies in incentivizing people to maintain the hardware infrastructure. Mike sees potential in combining blockchain-based rewards (like earning ADA for running mesh network nodes) with existing decentralized communication protocols to create self-sustaining networks.7. Mass adoption comes through abstraction, not education - Rather than trying to educate everyone about blockchain technology, mass adoption will happen when developers can build applications on decentralized infrastructure that users interact with seamlessly, without needing to understand the underlying blockchain mechanics. Users should be able to benefit from decentralization through well-designed interfaces that abstract away the complexity of wallets, addresses, and consensus mechanisms.

If Instagram stopped feeling fun, if your account stopped growing, or if you used to land clients from it but that has slowed drastically— this episode is your reset.In this episode, I'm sharing how I'm actually shifting my content strategy going into 2026 — not based on trends, but on what's working. This isn't about being viral or cute for the algorithm. It's about building connection, getting strategic with content that has different jobs, and making your IG feel fun again by turning IG into a funnel vs something that carries your whole business.We talk about:Why not every post should be about selling (and what to do instead)How Instagram's 2025 algorithm update changed everythingWhat “top of funnel” content really is and how to use it to grow your audienceWhy storytelling is non-negotiable (and what kind of stories to share)How trial reels + better hooks = more visibility and more aligned leadsHow to turn IG into a funnel that grows your list and converts — without hard sellingWhether you're burnt out on IG or ready to make it your most powerful tool again, this episode breaks down what's working right now and how to implement it in a way that feels sustainable and aligned with your identity.GRAB YOUR FREE STORYSELLING BUNDLE -That's why I created Six Figure Storyselling Hooks - 60 days of prompts that will grow your account, build high ticket trust and authority, and convert followers to clients - all through your story.https://marieladelamora.myflodesk.com/storyselling-hooksAnd in the emails that follow the Storyselling Hooks, you'll receive a limited time bonus that's normally only available in my paid offers - my Sellable Stories Coach custom GPT.It's designed to position you as a Category of One (through your story) and extract your top 3 sellable stories. Grab it now - it's an insane amount of value that will totally change the way you market on IG.CHAPTERS:00:00 – Intro: Why Instagram Feels Different02:15 – What Changed in the 2025 Algorithm06:58 – Why Your Posts Need Different Jobs09:25 – The 50/30/20 Rule for Content Strategy12:44 – Why Storytelling is STILL the Move16:40 – Writing Better Hooks (and Why They Matter)20:01 – What Top of Funnel Content Actually Looks Like25:00 – Why Trial Reels Are Your New Favorite Hack28:45 – The Funnel Mindset: Using IG to Grow Your List33:10 – The Freebie You'll Want (Six-Figure Story Selling + GPT)35:00 – Why This Gets to Be More Fun (and Strategic)

Send us a textNolan Bushnell is the founder of Atari and Chuck E. Cheese and is widely known as the father of the video game industry. Dr. Leah Hanes is the CEO of ExoDexa, co-author of the ExoDexa Manifesto, and leads the Two Bit Circus Foundation, where she has impacted over 460,000 students through game-based and project-based learning.

Welcome back to the Ultimate Guide to Partnering® Podcast. AI agents are your next customers. Subscribe to our Newsletter: https://theultimatepartner.com/ebook-subscribe/ Check Out UPX:https://theultimatepartner.com/experience/ https://youtu.be/vEdq8rpBM3I In this data-rich keynote, Jay McBain deconstructs the tectonic shifts reshaping the $5.3 trillion global technology industry, arguing that we are entering a new 20-year cycle where traditional direct sales models are obsolete. McBain explains why 96% of the industry is now surrounded by partners and how successful companies must pivot from “flywheels and theory” to a granular strategy focused on the seven specific partners present in every deal. From the explosion of agentic AI and the $163 billion marketplace revolution to the specific mechanics of multiplier economics, this discussion provides a roadmap for navigating the “decade of the ecosystem” where influence, trust, and integration—not just product—determine winners and losers. Key Takeaways Half of today's Fortune 500 companies will likely vanish in the next 20 years due to the shift toward AI and ecosystem-led models. Every B2B deal now involves an average of seven trusted partners who influence the decision before a vendor even knows a deal exists. Microsoft has outpaced AWS growth for 26 consecutive quarters largely because of a superior partner-led geographic strategy. Marketplaces are projected to grow to $163 billion by 2030, with nearly 60% of deals involving partner funding or private offers. The “Multiplier Effect” is the new ROI, where partners can make up to $8.45 for every dollar of vendor product sold. Future dominance relies on five key pillars: Platform, Service Partnerships, Channel Partnerships, Alliances, and Go-to-Market orchestration. If you're ready to lead through change, elevate your business, and achieve extraordinary outcomes through the power of partnership—this is your community. At Ultimate Partner® we want leaders like you to join us in the Ultimate Partner Experience – where transformation begins. Keywords: Jay McBain, Canalys, partner ecosystem, channel chief, agentic AI, marketplace growth, multiplier economics, B2B sales trends, tech industry forecast, service partnerships, strategic alliances, Microsoft vs AWS, distribution transformation, managed services growth, SaaS platforms, customer journey mapping, 28 moments of truth, future of reselling, technology spending 2025, ecosystem orchestration, partner multipliers. T Transcript: Jay McBain WORKFILE FOR TRANSCRIPT [00:00:00] Vince Menzione: Just up from, did you Puerto Rico last night? Puerto Rico, yes. Puerto Rico. He dodged the hurricane. Um, you all know him. Uh, let him introduce himself for those of you who don’t, but just thrilled to have on the stage, again, somebody who knows more about what’s going on in, in the, and has the pulse on this industry probably than just about anybody I know personally. [00:00:21] Vince Menzione: J Jay McBain. Jay, great to see you my friend. Alright, thank you. We have to come all the way. We live, we live uh, about 20 minutes from each other. We have to come all the way to Reston, Virginia to see each other, right? That’s right. Very good. Well, uh, that’s all over to you, sir. Thank you. [00:00:35] Jay McBain: Alright, well thank you so much. [00:00:36] Jay McBain: I went from 85 degrees yesterday to 45 today, but I was able to dodge that, uh, that hurricane, uh, that we kind of had to fly through the northern edge of, uh, wanna talk today about our industry, about the ultimate partner. I’m gonna try to frame up the ultimate partner as I walk through the data and the latest research that, uh, that we’ve been doing in the market. [00:00:56] Jay McBain: But I wanted to start here ’cause our industry moves in 20 year cycles, and if you look at the Fortune 500 and dial back 20 years from today, 52% of them no longer exist. As we step into the next 20 year AI era, half of the companies that we know and love today are not gonna exist. So we look at this, and by the way, if you’re not in the Fortune 500 and you don’t have deep pockets to buy your way outta problems, 71% of tech companies fail over the course of 10 years. [00:01:30] Jay McBain: Those are statistics from the US government. So I start to look at our industry and you know, you may look at the, you know, mainframe era from the sixties and seventies, mini computers, August the 12th, 1981, that first IBM, PC with Microsoft dos, version one, you know, triggered. A new 20 year era of client server. [00:01:51] Jay McBain: It was the time and I worked at IBM for 17 years, but there was a time where Bill Gates flew into Boca Raton, Florida and met with the IBM team and did that, you know, fancy licensing agreement. But after, you know, 20 years of being the most valuable company in the world and 13 years of antitrust and getting broken up, almost like at and TIBM almost didn’t make payroll. [00:02:14] Jay McBain: 13 years after meeting Bill Gates. Yeah, that’s how quickly things change in these eras. In 1999, a small company outta San Francisco called salesforce.com got its start. About 10 years later, Jeff Bezos asked a question in a boardroom, could we rent out our excess capacity and would other companies buy it? [00:02:35] Jay McBain: Which, you know, most people in the room laughed at ’em at the time. But it created a 20 year cloud era when our friends, our neighbors, our family. Saw Chachi PT for the first time in March of 2023. They saw the deep fakes, they saw the poetry, they saw the music. They came to us as tech people and said, did we just light up Skynet? [00:02:58] Jay McBain: And that consumer trend has triggered this next 20 years. I could walk through the richest people in the world through those trends. I could walk through the most valuable companies. It all aligns. ’cause by the way, Apple’s no longer at the top. Nvidia is at the top, Microsoft. Second, things change really quickly. [00:03:17] Jay McBain: So in that course of time, you start to look at our industry and as people are talking about a six and a half or $7 trillion build out of ai, that’s open AI and Microsoft numbers, that is bigger than our industry that’s taken over 50 years to build. This year, we’re gonna finish the year at $5.3 trillion. [00:03:36] Jay McBain: That’s from the smallest flower shop to the biggest bank. Biggest governments that Caresoft would, uh, serve biggest customer in the world is actually the federal government of the us. But you look at this pie chart and you look at the changes that we’re gonna go through over the next 20 years, there’s about a trillion dollars in hardware. [00:03:54] Jay McBain: There’s about a trillion dollars in software. If you look forward through all of the merging trends, quantum computing, humanoid robots, all the things that are coming that dollar to dollar software to hardware will continue to exist all the way through. We see services making up almost two thirds of this pie. [00:04:13] Jay McBain: Yesterday I was in a telco conference with at and t and Verizon and T-Mobile and some of the biggest wireless players and IT services, which happen to be growing faster than products. At the moment, there is more work to be done wrapping around the deal than the actual products that the customer is buying. [00:04:32] Jay McBain: So in an industry that’s growing at 7%. On top of the world economy that’s grown at 2.2. This is the fastest growing industry, and it will be at least for the next 10 years, if not 2070 0.1% of this entire $5 trillion gets transacted through partners. While what we’re talking to today about the ultimate partner, 96% of this industry is surrounded by partners in one way or another. [00:05:01] Jay McBain: They’re there before the deal. They’re there at the deal. They’re there after the deal. Two thirds of our industry is now subscription consumption based. So every 30 days forever, and a customer for life becomes everything. So if every deal in medium, mid-market, and higher has seven partners, according to McKinsey, who are those seven people trying to get into the deal? [00:05:25] Jay McBain: While there’s millions of companies that have come into tech over the last 10 to 20 years. Digital agencies, accountants, legal firms, everybody’s come in. The 250,000 SaaS companies, a million emerging tech companies, there’s a big fight to be one of those seven trusted people at the table. So millions of companies and tens of millions of people our competing for these slots. [00:05:49] Jay McBain: So one of the pieces of research I’m most proud of, uh, in my analyst career is this. And this took over two years to build. It’s a lot of logos. Not this PowerPoint slide, but the actual data. Thousands of people hours. Because guess what? When you look at partners from the top down, the top 1000 partners, by capability and capacity, not by resale. [00:06:15] Jay McBain: It’s not a ranking of CDW and insight and resale numbers. It is the surrounding. Consulting, design, architecture, implementations, integrations, managed services, all the pieces that’s gonna make the next 20 years run. So when you start to look at this, 98% of these companies are private, so very difficult to get to those numbers and, uh, a ton of research and help from AI and other things to get this. [00:06:41] Jay McBain: But this is it. And if you look at this list, there’s a thousand logos out of the million companies. There’s a thousand logos that drive two thirds of all tech services in the world. $1.07 trillion gets delivered by a thousand companies, but here’s where it gets fun. Those companies in the middle, in blue, the 30 of them deliver more tech services than the next 970. [00:07:08] Jay McBain: Combined the 970 combined in white deliver more tech services. Then the next million combined. So if you think we live in an 80 20 rule or maybe a 99, a 95 5 rule, or a 99 1 rule, we actually live in a 99.9 0.1 parallel principle. These companies spread around the world evenly split across the uh, different regions. [00:07:35] Jay McBain: South Africa, Latin America, they’re all over. They split. They split among types. All of the Venn diagram I just showed from GSIs to VARs to MSPs, to agencies and other types of companies. But this is a really rich list and it’s public. So every company in the world now, if you’re looking at Transactable data, if you’re looking at quantifiable data that you can go put your revenue numbers against, it represents 70 to 80% of every company in this room’s Tam. [00:08:08] Jay McBain: In one piece of research. So what do you do below that? How do you cover a million companies that you can’t afford to put a channel account manager? You can’t afford to write programs directly for well after the top down analysis and all the wallet share and you know exactly where the lowest hanging fruit is for most of your tam. [00:08:28] Jay McBain: The available markets. The obtainable markets. You gotta start from the community level grassroots up. So you need to ask the question for the million companies and the maybe a hundred thousand companies out there, partner companies that are surrounding your customer. These are the seven partners that surround your customer. [00:08:48] Jay McBain: What do they read, where do they go, and who do they follow? Interestingly enough, our industry globally equates to only a thousand watering holes, a thousand companies at the top, a thousand places at the bottom. 35% of this audience we’re talking. Millions of people here love events and there’s 352 of them like this one that they love to go to. [00:09:13] Jay McBain: They love the hallway chats, they love the hotel lobby bar, you know, in a time reminded by the pandemic. They love to be in person. It’s the number one way they’re influenced. So if you don’t have a solid event strategy and you don’t have a community team out giving out socks every week, your competitors might beat you. [00:09:31] Jay McBain: 12% of this audience loves podcasts. It’s the Joe Rogan effect of our industry. And while you know, you may not think the 121 podcasts out there are important, well, you’re missing 12% of your audience. It’s over a million people. If you’re not on a weekly podcast in one of these podcasts in the world, there’s still people that read one of the 106 magazines in the world. [00:09:55] Jay McBain: There are people that love peer groups, associations, they wanna be part of this. There’s 15 different ways people are influenced. And a solid grassroots strategy is how you make this happen. In the last 10 years, we’ve created a number of billionaires. Bottom up. They never had to go talk to la large enterprise. [00:10:15] Jay McBain: They never had to go build out a mid-market strategy. They just went and give away socks and new community marketing. And this has created, I could rip through a bunch of names that became unicorns just in the last couple of years, bottoms up. You go back to your board walking into next year, top down, bottom up. [00:10:34] Jay McBain: You’ve covered a hundred percent of your tam, and now you’ve covered it with names, faces, and places. You haven’t covered it with a flywheel or a theory. And for 44 years, we have gone to our board every fourth quarter with flywheels and theory. Trust me, partners are important. The channel is key to us. [00:10:57] Jay McBain: Well, let’s talk at the point of this granularity, and now we’re getting supported by technology 261 entrepreneurs. Many of them in the room actually here that are driving this ability to succeed with seven partners in every deal to exchange data to be able to exchange telemetry of these prospects to be able to see twice or three times in terms of pipeline of your target addressable market. [00:11:26] Jay McBain: All these ai, um, technologies, agentic technologies are coming into this. It’s all about data. It’s all about quantifiable names, faces, and places. Now none of us should be walking around with flywheels, so let’s flip the flywheels. No. Uh, so we also look at, and I sold PCs for 17 years and that was in the high times of 40% margins for partners. [00:11:55] Jay McBain: But one interesting thing when you study the p and l for broad base of partners around the world, it’s changed pretty significantly in this last 20 year era. What the cloud era did is dropped hardware from what used to be 84% plus the break fix and things that wrap around it of the p and l to now 16% of every partner in the world. [00:12:16] Jay McBain: 84% of their p and l is now software and services. And if you look at profitability, it’s worse. It’s actually 87% is profitability wise. They’ve completely shifted in terms of where they go. Now we look at other parts of our market. I could go through every part of the pie of the slide, but we’re watching each of the companies, and if you can see here, this is what we want to talk about in terms of ultimate partner. [00:12:43] Jay McBain: Microsoft has outgrown AWS for 26 straight quarters. They don’t have a better product. They don’t have a better price, they don’t have better promotion. It’s all place. And I’ll explain why you guess here in the light green line. Exactly. The day that Google went a hundred percent all in partner, every deal, even if a deal didn’t have a partner, one of the 4% of deals that didn’t have a partner, they injected a partner. [00:13:09] Jay McBain: You can see on the left side exactly where they did it. They got to the point of a hundred percent partner driven. Rebuilt their programs, rebuilt their marketplace. Their marketplace is actually larger than Microsoft’s, and they grew faster than Microsoft. A couple of those quarters. It is a partner driven future, and now I have Oracle, which I just walked by as I walked from the hotel. [00:13:31] Jay McBain: Oracle with their RPOs will start to join. Maybe the list of three hyperscalers becomes the list of four in future slides, but that’s a growth slide. Market share is different. AWS early and commanding lead. And it plays out, uh, plays out this way. But we’re at an interesting moment and I stood up six years ago talking about the decade of the ecosystem after we went through a decade of sales starting in 1999 when we all thought we were born to be salespeople. [00:14:02] Jay McBain: We managed territories with our gut. The sales tech stack would have it different, that sales was a science, and we ended the decade 2009, looking at sales very differently in 2009. I remember being at cocktail parties where CMOs would be joking around that 50% of their marketing dollars were wasted. They just didn’t know which 50%. [00:14:23] Jay McBain: And I’ll tell you, that was really funny. In 2009 till every 58-year-old CMO got replaced by a 38-year-old growth hacker who walked in with 15,348 SaaS companies in their MarTech and ad tech stack to solve the problem, every nickel of marketing by 2019 was tracked. Marketo, Eloqua, Pardot, HubSpot, driving this industry. [00:14:50] Jay McBain: Now, we stood up and said the 28 moments that come before a sale are pretty much all partner driven. In the best case scenario, a vendor might see four of the moments. They might come to your website, maybe they read an ebook, maybe they have a salesperson or a demo that comes in. That’s four outta 28 moments. [00:15:10] Jay McBain: The other 24 are done by partners. Yeah, in the worst case scenario and the majority scenario, you don’t see any of the moments. All 28 happen and you lose a deal without knowing there ever was a deal. So this is it. We need to partner in these moments and we need to inject partners into sales and marketing, like no time before, and this was the time to do it. [00:15:33] Jay McBain: And we got some feedback in the Salesforce state of sales report, which doesn’t involve any partnerships or, or. Channel Chiefs or anything else. This is 5,500 of the biggest CROs in the world that obviously use Salesforce. 89% of salespeople today use partners every day. For the 11% who don’t, 58% plan two within a year. [00:15:57] Jay McBain: If you add those two numbers together, that’s magically the 96% number. They recognize that every deal has partners in it. In 2024, last year, half of the salespeople in the world, every industry, every country. Miss their numbers. For the minority who made their numbers, 84 point percent pointed to partners as the reason why they made their numbers. [00:16:21] Jay McBain: It was the cheat code for sales, so that modern salesperson that knows how to orchestrate a deal, orchestrate the 28 moments with the seven partners and get to that final spot is the winning formula. HubSpot’s number in separate research was 84% in marketing. So we’re starting to see partners in here. We don’t have to shout from the mountaintops. [00:16:44] Jay McBain: These communities like ultimate Partner are working and we’re getting this to the highest levels in the board. And I’ll say that, you know, when 20 years from now half of the companies we know and love fail after we’re done writing the book and blaming the CEO for inventing the thing that ended up killing them, blaming the board for fiduciary responsibility and letting it happen. [00:17:06] Jay McBain: What are the other chapters of the book? And I think it’s all in one slide. We are in this platform economy and the. [00:17:31] Jay McBain: So your battery’s fine. Check, check, check, check. Alright, I’ll, I’ll just hold this in case, but the companies that execute on all five of these areas, well. Not only today become the trillion dollar valued companies, but they become the companies of tomorrow. These will be the fastest growing companies at every level. [00:17:50] Jay McBain: Not only running a platform business, but participating in other platforms. So this is how it breaks out, and there are people at very senior levels, at very big companies that have this now posted in the office of the CEO winning on integrations is everything. We just went through a demographic shift this year where 51% of our buyers are born after 1982. [00:18:15] Jay McBain: Millennials are the number one buyer of the $5 trillion. Their number one buying criteria is not service. Support your price, your brand reputation, it’s integrations. The buy a product, 80% is good as the next one if it works better in their environment. 79% of us won’t buy a car unless it has CarPlay or Android Auto. [00:18:34] Jay McBain: This is an integration world. The company with the most integrations win. Second, there are seven partners that surround the customer. Highly trusted partners. We’re talking, coaching the customer’s, kids soccer team, having a cottage together up at the lake. You know, best men, bate of honors at weddings type of relationships. [00:18:57] Jay McBain: You can’t maybe have all seven, but how does Microsoft beat AWS? They might have had two, three, or four of them saying nice things about them instead of the competition. Winning in service partnerships and channel partnerships changes by category. If you’re selling MarTech, only 10% of it today is resold, so you build more on service partnerships. [00:19:18] Jay McBain: If you’re in cybersecurity today, 91.6% of it is resold. Transacted through partners. So you build a lot of channel partnerships, plus the service partnerships, whatever the mix is in your category, you have to have two or three of those seven people. Saying nice things about you at every stage of the customer journey. [00:19:38] Jay McBain: Now move over to alliances. We have already built the platforms at the hyperscale level. We’ve built the platforms within SaaS, Salesforce, ServiceNow, Workday, Marketo, NetSuite, HubSpot. Every buyer has a set of platforms that they buy. We’ve now built them in cybersecurity this year out of 6,500 as high as cyber companies, the top five are starting to separate. [00:20:02] Jay McBain: We built it in distribution, which I’ll show in a minute. We’re building it in Telco. This is a platform economy and alliances win and you have alliances with your competitors ’cause you compete in the morning, but you’re best friends by the afternoon. Winning in other platforms is just as important as driving your own. [00:20:20] Jay McBain: And probably the most important part of this is go to market. That sales, that marketing, the 28 moments, the every 30 days forever become all a partner strategy. So there’s still CEOs out there that believe platform is a UI or UX on a bunch of disparate products and things you’ve acquired. There’s still CFOs out there that Think platform is a pricing model, a bundle model of just getting everything under one, you know, subscription price or consumption price. [00:20:51] Jay McBain: And it’s not, platforms are synonymous with partnerships. This is the way forward and there’s no conversation around ai. That doesn’t involve Nvidia over there, an open AI over here and a hyperscaler over there and a SaaS company over here. The seven layer stack wins every single time, and the companies that get this will be the ones that survive this cycle. [00:21:16] Jay McBain: Now, flipping over to marketplaces. So we had written research that, um, about five years ago that marketplaces were going to grow at 82% compounded. Yeah, probably one of the most accurate predictions we ever made, because it happened, we, we predicted that, uh, we were gonna get up to about $85 billion. Well, now we’ve extended that to 2030, so we’re gonna get up to $163 billion, and the thing that we’re watching is in green. [00:21:46] Jay McBain: If 96% of these deals are partner assisted in some way, how is the economics of partnering going to work? We predicted that 50% of deals by 2027. Would be partner funded in some way. Private offers multi-partner offers distributor sellers of record, and now that extends to 59% by 2030, the most senior leader of the biggest marketplace AWS, just said to us they’re gonna probably make these numbers on their own. [00:22:14] Jay McBain: And he asked what their two competitors are doing. So he’s telling us that we under called this. Now when you look at each of the press releases, and this is the AWS Billion Dollar Club. Every one of the companies on the left have issued a press release that they’re in the billion dollar club. Some of them are in the multi-billions, but I want you to double click on this press release. [00:22:35] Jay McBain: I’m quoted in here somewhere, but as CrowdStrike is building the marketplace at 91% compounded, they’re almost doubling their revenue every single year. They’re growing the partner funding, in this case, distributor funding by 3548%. Almost triple digit growth in marketplace is translating into almost quadruple digit growth in funding. [00:23:01] Jay McBain: And you see that over and over again as, as Splunk hit three, uh, billion dollars. The same. Salesforce hit $2 billion on AWS in Ulti, 18 months. They joined in October 20, 23, and 18 months later, they’re already at $2 billion. But now you’re seeing at Salesforce, which by the way. Grew up to $40 billion in revenue direct, almost not a nickel in resell. [00:23:28] Jay McBain: Made it really difficult for VARs and managed service providers to work with Salesforce because they couldn’t understand how to add services to something they didn’t book the revenue for. While $40 billion companies now seeing 70% of their deals come through partners. So this is just the world that we’re in. [00:23:44] Jay McBain: It doesn’t matter who you are and what industry you’re in, this takes place. But now we’re starting to see for the first time. Partners join the billion dollar club. So you wonder about partnering and all this funding and everything that’s working through Now you’re seeing press releases and companies that are redoing their LinkedIn branding about joining this illustrious club without a product to sell and all the services that wrap around it. [00:24:10] Jay McBain: So the opening session on Microsoft was interesting because there’s been a number of changes that Microsoft has done just in the last 30 days. One is they cut distribution by two thirds going from 180 distributors to 62. They cut out any small partner lower than a thousand dollars, and that doesn’t sound like a lot, but that’s over a hundred thousand partners that get deed tightening the long tail. [00:24:38] Jay McBain: They we’re the first to really put a global point system in place three years ago. They went to the new commerce experience. If you remember, all kinds of changes being led by. The biggest company for the channel. And so when we’re studying marketplaces, we’re not just studying the three hyperscalers, we’re studying what TD Cynic is doing with Stream One Ingram’s doing with Advant Advantage Aerosphere. [00:25:01] Jay McBain: Also, we’re watching what PAX eight, who by the way, is the 365 bestseller for Microsoft in the world. They are the cybersecurity leader for Microsoft in the world and the copilot. Leader in the world for Microsoft and Partner of the Year for Microsoft. So we’re watching what the cloud platforms are doing, watching what the Telco are doing, which is 25 cents out of every dollar, if you remember that pie chart, watching what the biggest resellers are converting themselves into. [00:25:30] Jay McBain: Vince just mentioned, you know, SHI in the changes there watching the managed services market and the leaders there, what they’re doing in terms of how this industry’s moving forward. By the way, managed services at $608 billion this year. Is one and a half times larger than the SaaS industry overall. [00:25:48] Jay McBain: It’s also one and a half times larger than all the hyperscalers combined. Oracle, Alibaba, IBM, all the way down. This is a massive market and it makes up 15 to 20 cents of every dollar the customer spend. We’re watching that industry hit a trillion dollars by the end of the decade, and we’re watching 150 different marketplace development platforms, the distribution of our industry, which today is 70.1% indirect. [00:26:13] Jay McBain: We’re starting to see that number, uh, solidify in terms of marketplaces as well. Watching distributors go from that linear warehouse in a bank to this orchestration model, watching some of the biggest players as the world comes around, platforms, it tightens around the place. So Caresoft, uh, from from here is the sixth biggest distributor in the world. [00:26:40] Jay McBain: Just shows you how big the. You know, biggest client in the world is that they serve. But understand that we’re publishing the distributor 500 list, but it’ll be the same thing. That little group in blue in the middle today, you know, drives almost two thirds of the market. So what happens in all this next stage in terms of where the dollars change hands. [00:27:07] Jay McBain: And the economics of partnering themselves are going through the most radical shift that we’ve seen ever. So back to the nineties, and, and for those of you that have been channel chiefs and running programs, we went to work every day. You know, everything’s on fire. We’re trying to check hundred boxes, trying to make our program 10% better than our competitors. [00:27:30] Jay McBain: Hey, we gotta fix our deal registration program today, and our incentives are outta whack or training programs or. You know, not where they need to be. Our certification, you know, this was the life of, uh, of a channel chief. Everybody thought we were just out drinking in the Caribbean with our best partners, but we were under the weight of this. [00:27:49] Jay McBain: But something interesting has happened is that we turned around and put the customer at the middle of our programs to say that those 28 moments in green before the sale are really, really important. And the seven partners who participate are really important. Understanding. The customer’s gonna buy a seven layer stack. [00:28:09] Jay McBain: They’re gonna buy it With these seven partners, the procurement stage is much different. The growth of marketplaces, the growth of direct in some of these areas, and then long term every 30 days forever in a managed service, implementations, integrations, how you upsell, cross-sell, enrich a deal changes. So how would you build a program that’s wrapped around the customer instead of the vendor? [00:28:35] Jay McBain: And we’re starting to hear our partners shout back to us. These are global surveys, big numbers, but over half of our partners, regardless of type, are selling consulting to their customer. Over half are designing architecting deals. A third of them are trying to be system integrators showing up at those implementation integration moments. [00:28:55] Jay McBain: Two thirds of them are doing managed services, but the shocking one here is 44% of our partners, regardless of type, are coding. They’re building agents and they’re out helping their customer at that level. So this is the modern partner that says, don’t typecast me. You may have thought of me in your program. [00:29:14] Jay McBain: You might have me slotted as a var. Well, I do 3.2 things, and if I don’t get access to those resources, if you don’t walk me to that room, I’m not gonna do them with you. You may have me as a managed service provider that’s only in the morning. By the afternoon I’m coding, and by the next morning I’m implementing and consulting. [00:29:33] Jay McBain: So again, a partner’s not a partner. That Venn diagram is a very loose one now, as every partner on there is doing 3.2 different business models. And again, they’re telling us for 43 years, they said, I want more leads this year it changed. For the first time, I want to be recognized and incentivized as more than just a cash register for you. [00:29:57] Jay McBain: I want you to recognize when I’m consulting, when I’m designing, when you’re winning deals, because of my wonderful services, by the way, we asked the follow up question, well, where should we spend our money with you? And they overwhelmingly say, in the consulting stage, you win and lose deals. Not at moment 28. [00:30:18] Jay McBain: We’re not buying a pack of gum at the gas station. This is a considered purchase. You win deals from moment 12 through 16 and I’m gonna show you a picture of that later, and they say, you better be spending your money there, or you’re not gonna win your fair share or more than your fair share of deals. [00:30:36] Jay McBain: The shocking thing about this is that Microsoft, when they went to the point system, lifted two thirds of all the money, tens of billions of dollars, and put it post-sale, and we were all scratching our heads going. Well, if the partners are asking for it there, and it seems like to beat your biggest competitors, you want to win there. [00:30:54] Jay McBain: Why would you spend the money on renewal? Well, they went to Wall Street and Goldman Sachs and the people who lift trillions of dollars of pension funds and said, if we renew deals at 108%, we become a cash machine for you. And we think that’s more valuable than a company coming out with a new cell phone in September and selling a lot of them by Christmas every year. [00:31:18] Jay McBain: The industry. And by the way, wall Street responded, Microsoft has been more valuable than Apple since. So we talk in this now multiplier language, and these are reports that we write, uh, at AMIA at canals. But talking about the partner opportunity in that customer cycle, the $6 and 40 cents you can make for every dollar of consumption, or the $7 and 5 cents you can make the $8 and 45 cents you can make. [00:31:46] Jay McBain: There’s over 24 companies speaking at this level now, and guess what? It’s not just cloud or software companies. Hardware companies are starting to speak in this language, and on January 25th, Cisco, you know, probably second to Microsoft in terms of trust built with the channel globally is moving to a full point system. [00:32:09] Jay McBain: So these are the changes that happen fast. But your QBR with your partners now less about drinking beers at the hotel lobby bar and talking dollar by dollar where these opportunities are. So if you’re doing 3.2 of these things, let’s build out a, uh, a play where you can make $3 for every dollar that we make. [00:32:28] Jay McBain: And you make that profitably. You make it in sticky, highly retained business, and that’s the model. ’cause if you make $3 for every dollar. We make, you’re gonna win Partner of the year, and if you win partner of the year, that piece of glass that you win on stage, by the time you get back to your table, you’re gonna have three offers to buy your business. [00:32:51] Jay McBain: CDW just bought a w. S’s Partner of the Year. Insight bought Google’s eight time partner of the year. Presidio bought ServiceNow’s, partner of the year over and over and over again. So I’m at Octane, I’m at CrowdStrike, I’m at all these events in Vegas every week. I’m watching these partners of the year. [00:33:05] Jay McBain: And I’m watching as the big resellers. I’m watching as the GSIs and the m and a folks are surrounding their table after, and they’re selling their businesses for SaaS level valuations. Not the one-to-one service valuation. They’re getting multiples because this is the new future of our industry. This is platform economics. [00:33:25] Jay McBain: This is winning and platforms for partners. Now, like Vince, I spent 20 minutes without talking about ai, but we have to talk about ai. So the next 20 years as it plays out is gonna play out in phases. And the first thing you know to get it out of the way. The first two years since that March of 23, has been underwhelming, to say the least. [00:33:47] Jay McBain: It’s been disappointing. All the companies that should have won the biggest in AI have been the most disappointing. It’s underperformed the s and p by a considerable amount in terms of where we are. And it goes back to this. We always overestimate the first two years, but we underestimate the first 10. [00:34:07] Jay McBain: If you wanna be the point in time person and go look at that 1983 PC or the 1995 internet or that 2007 iPhone or that whatever point in time you wanna look at, or if you want to talk about hallucinations or where chat chip ET version five is version, as opposed to where it’s going to be as it improves every six months here on in. [00:34:30] Jay McBain: But the fact of the matter is, it’s been a consumer trend. Nvidia got to be the most valuable company in the world. OpenAI was the first company to 2 billion users, uh, in that amount of speed. It’s the fastest growing product ever in history, and it’s been a consumer win this trillions of dollars to get it thrown around in the press releases. [00:34:49] Jay McBain: They’re going out every day, you know, open ai, signing up somebody new or Nvidia, investing in somebody new almost every single day in hundreds of billions of dollars. It is all happening really on the consumer side. So we got a little bit worried and said, is that 96% of surround gonna work in ag agentic ai? [00:35:10] Jay McBain: So we went and asked, and the good news is 88% of end customers are using partners to work through their ag agentic strategy. Even though they’re moving slow, they’re actually using partners. But what’s interesting from a partner perspective, and this is new research that out till 2030. This is the number one services opportunity in the entire tech or telco industry. [00:35:34] Jay McBain: 35.3% compounded growth ending at $267 billion in services. Companies are rebuilding themselves, building out practices, and getting on this train and figuring out which vendors they should hook their caboose to as those trains leave the station. But it kind of plays out like this. So in the next three to five years, we’re in this generative, moving into agentic phase. [00:36:01] Jay McBain: Every partner thinks internally first, the sales and marketing. They’re thinking about their invoicing and billing. They’re thinking about their service tickets. They’re thinking about creating a business that’s 10% better than their competitors, taking that knowledge into their customers and drive in business. [00:36:17] Jay McBain: But we understand that ag agentic AI, as it’s going to play out is not a product. A couple of years ago, we thought maybe a copilot or an agent force or something was going to be the product that everybody needed to buy, and it’s not a product, it’s gonna show up as a feature. So you go back in the history of feature ads and it’s gonna show up in software. [00:36:38] Jay McBain: So if you’re calling in SMB, maybe you’re calling on a restaurant. The restaurant isn’t gonna call OpenAI or call Microsoft or call Nvidia directly. They’re running their restaurant. And they may have chosen a platform like Toast Square, Clover, whatever iPads people are running around with, runs on a platform that does everything in their business, does staffing, does food ordering, works with Uber Eats, does everything end to end? [00:37:08] Jay McBain: They’re gonna wait to one of those platforms, dries out agent AI for them, and can run the restaurant more effectively, less human capital and more consistently, but they wait for the SaaS platform as you get larger. A hundred, 150 people. You have vice presidents. Each of those vice presidents already have a SaaS stack. [00:37:28] Jay McBain: I talked about Salesforce, ServiceNow, Workday, et cetera. They’ve already built that seven layer model and in some cases it’s 70 layers. But the fact is, is they’re gonna wait for those SaaS layers to deliver ag agentic to them. So this is how it’s gonna play out for the next three and a half, three to five years. [00:37:45] Jay McBain: And partners are realizing that many of them were slow to pick up SaaS ’cause they didn’t resell it. Well now to win in this next three to half, three to five years, you’re gonna have to play in this environment. When you start looking out from here, the next generation, you know, kind of five through 15 years gets interesting in more of a physical sense. [00:38:06] Jay McBain: Where I was yesterday talking about every IOT device that now is internet access, starts to get access to large language models. Every little sensor, every camera, everything that’s out there starts to get smart. But there’s a point. The first trillionaire, I believe, will be created here. Elon’s already halfway there. [00:38:24] Jay McBain: Um, but when Bill Gates thought there was gonna be a PC in every home, and IBM thought they were gonna sell 10,000 to hobbyists, that created the richest person in the world for 20 years, there will be a humanoid in every home. There’s gonna be a point in time that you’re out having drinks with your friends, and somebody’s gonna say, the early adopter of your friends is gonna say. [00:38:46] Jay McBain: I haven’t done the dishes in six weeks. I haven’t done the laundry. I haven’t made my bed. I haven’t mowed the lawn. When they say that, you’re gonna say, well, how? And they’re gonna say, well, this year I didn’t buy a new car, but I went to the car dealership and I bought this. So we’re very close to the dexterity needed. [00:39:05] Jay McBain: We’ve got the large language models. Now. The chat, GPT version 10 by then is going to make an insane, and every house is gonna have one of the. [00:39:17] Jay McBain: This is the promise of ai. It’s not humanoid robots, it’s not agents. It’s this. 99% of the world’s business data has not been trained or tuned into models yet. Again, this is the slow moving business. If you want to think about the 99% of business data, every flight we’ve all taken in this room sits on a saber system that was put in place in 1964. [00:39:43] Jay McBain: Every banking transaction, we’ve all made, every withdrawal, every deposit sits on an IBM mainframe put in place in the sixties or seventies. 83% of this data sits in cold storage at the edge. It’s not ready to be moved. It’s not cleansed, it’s not, um, indexed. It’s not in any format or sitting on any infrastructure that a large language model will be able to gobble up the data. [00:40:10] Jay McBain: None of the workflows, none of the programming on top of that data is yet ready. So this is your 10 to 20 year arc of this era that chat bot today when they cancel your flight is cute. It’s empathetic, it feels bad for you, or at least it seems to, but it can’t do anything. It can’t book you the Marriott and get you an Uber and then a 5:00 AM flight the next morning. [00:40:34] Jay McBain: It can’t do any of that. But more importantly, it doesn’t know who you are. I’ve got 53 years of flights under my belt and they, I’m the person that get me within six hours of my kids and get me a one-way Hertz rental. You know, if there’s bad weather in Miami, get me to Tampa, get me a Hertz, I’m driving home, I’m gonna make it home. [00:40:56] Jay McBain: I’m not the 5:00 AM get me a hotel person. They would know that if they picked up the flights that I’ve taken in the past. Each of us are different. When you get access to the business data and you become ag agentic, everything changes. Every industry changes because of this around the customers. When you ask about this 35% growth, working on that data, working in traditional consulting and design and implementation, working in the $7 trillion of infrastructure, storage, compute, networking, that’s gonna be around, this is a massive opportunity. [00:41:30] Jay McBain: Services are gonna continue to outgrow products. Probably for the next five to 10 years because of this, and I’m gonna finish here. So we talked a lot about quantifying names, faces, places, and I think where we failed the most as ultimate partners is underneath the tam, which every one of our CEOs knows to the decimal point underneath the TAM that our board thinks they’re chasing. [00:41:59] Jay McBain: We’ve done a very poor job. Of talking about the available markets and obtainable markets underneath it, we, we’ve shown them theory. We’ve shown them a bunch of, you know, really smart stuff, and PowerPoint slides up the wazoo, but we’ve never quantified it for them. If they wanna win, if they want to get access, if they want to double their pipeline, triple their pipeline, if they wanna start winning more deals, if they wanna win deals that are three times larger, they close two times faster. [00:42:31] Jay McBain: And they renew 15% larger. They have to get into the available and obtainable markets. So just in the last couple weeks I spoke at Cribble, I spoke at Octane, I spoke at CrowdStrike Falcon. All three of those companies at the CEO level, main stage use those exact three numbers, three x, two x, 15%. That’s the language of platforms, and they’re investing millions and millions and millions of dollars on teams. [00:42:59] Jay McBain: To go build out the Sam Andal in name spaces and places. So you’ve heard me talk about these 28 moments a lot. They’re the ones that you spend when you buy a car. Some people spend one moment and they drive to the Cadillac dealership. ’cause Larry’s been, you know, taking care of the family for 50 years. [00:43:18] Jay McBain: Some people spend 50 moments like I do, watching every YouTube video and every, you know, thing on the internet. I clear the internet cover to cover. But the fact is, is every deal averages around these 28 moments. Your customer, there’s 13 members of the buying committee today. There’s seven partners and they’re buying seven things. [00:43:37] Jay McBain: There’s 27 things orchestrating inside these 28 moments. And where and how they all take place is a story of partnering. So a couple of years ago, canals. Latin for channel was acquired by amia, which is a part of Informa Tech Target, which is majority owned by Informa. All that being said, there’s hundreds of magazines that we have. [00:44:00] Jay McBain: There’s hundreds of events that we run. If somebody’s buying cybersecurity, they probably went to Black Hat or they probably went to GI Tech. One of these events we run, or one of the magazines. So we pick up these signals, these buyer intent signals as a company. Why did they wanna, um, buy a, uh, a Canals, which was a, you know, a small analyst firm around channels? [00:44:22] Jay McBain: They understood this as well. The 28 moments look a lot like this when marketers and salespeople are busy filling in the spots of every deal. And by the way, this is a real deal. AstraZeneca came in to spend millions of dollars on ASAP transformation, and you can start to see as the customer got smart. [00:44:45] Jay McBain: The eBooks, they read the podcasts, they listened to the events they went to. You start to see how this played out over the long term. But the thing we’ve never had in our industry is the light blue boxes. This deal was won and lost in December. In this particular case, NTT software won and Yash came in and sold the customer five projects. [00:45:07] Jay McBain: The millions of dollars that were going to be spent were solved here. The design and architecture work was all done here. A couple of ISVs You see in light blue came in right at the end, deal was closed in April. You see the six month cycle. But what if you could fill in every one of the 28 boxes in every single customer prospect that your sales and marketing team have? [00:45:30] Jay McBain: But here’s the brilliance of this. Those light blue boxes didn’t win the deals there. They won the deals months before that. So when NTT and Software one walked into this deal. They probably won the deal back in October and they had to go through the redlining. They had to go through the contracting, they had to go through all the stuff and the Gantt chart to get started. [00:45:54] Jay McBain: But while your CMO is getting all excited about somebody reading an ebook and triggering an MQL that the sales team doesn’t want, ’cause it’s not qualified, it’s not sales qualified, you walk in and say, no, no. This is a multimillion deal, dollar deal. It’s AstraZeneca. I know the five partners that are coming in in December to solidify the seven layers, and you’re walking in at the same time as the CMOs bragging about an ebook. [00:46:21] Jay McBain: This changes everything. If we could get to this level of data about every dollar of our tam, we not only outgrow our competitors, we become the platforms of the next generation. Partnering and ultimate partnering is all here. And this is what we’re doing in this room. This is what we’re doing over these couple of days, and this is what, uh, the mission that Vince is leading. [00:46:43] Jay McBain: Thank you so much. [00:46:47] Vince Menzione: Woo. Day in the house. Good to see you my friend. Good to see you. Oh, we’re gonna spend a couple minutes. Um, I’m put you in the second seat. We’re gonna put, we’re gonna make it sit fireside for a minute. Uh, that was intense. It was pretty incredible actually, Jay. And so I’m, I think I wanna open it up ’cause we only have a few minutes just to, any questions? [00:47:06] Vince Menzione: I’m sure people are just digesting. We already have one up here. See, [00:47:09] Question: Jay knows I’m [00:47:10] Vince Menzione: a question. I love it. We, I don’t think we have any I can grab a mic, a roving mic. I could be a roving mic person. Hold on. We can do this. This is not on. [00:47:25] Vince Menzione: Test, test. Yes it is. Yeah. [00:47:26] Question: Theresa Carriol dared me to ask a question and I say, you don’t have to dare me. You know, I’m going to Anyway. Um, so Jay, of the point of view that with all of the new AI players that strategic alliances is again having a moment, and I was curious your point of view on what you’re seeing around this emergence and trend of strategic alliances and strategic alliance management. [00:47:52] Question: As compared to channel management. And what are you seeing in terms of large vendors like AWS investing in that strategic alliance role versus that channel role training, enablement, measurement, all that good stuff? [00:48:06] Jay McBain: Yeah, it’s, it’s a great question. So when I told the story about toast at the restaurant or Square or Clover, they’re not call, they’re not gonna call open AI or Nvidia themselves either. [00:48:17] Jay McBain: When you look out at the 250,000 ISVs. That make up this AI stack, there is the layers that happen there. So the Alliance with AWS, the alliance they have with Microsoft or Google is going to be how they generate agent AI in their platforms. So when I talk about a seven layer stack, the average deal being seven layers, AI is gonna drive this to nine, and then 11, then probably 13. [00:48:44] Jay McBain: So in terms of how alliances work, I had it up there as one of the five core strategies, and I think it’s pretty even. You can have the best alliances in the world, but if the seven partners trusted by the customer don’t know what that alliance is and the benefits to the customer and never mention it, it’s all for Naugh. [00:49:00] Jay McBain: If you’re go-to market, you’re co-selling, your co-marketing strategies are not built around that alliance. It’s all for naught. If the integration and the co-innovation, the co-development, the all the co-creation work that’s done inside these alliances isn’t translated to customer outcomes, it’s all for naugh. [00:49:17] Jay McBain: These are all five parallel swim lanes. All five are absolutely critically needed. And I think they’re all five pretty equally weighted in terms of needing each other. Yes. To be successful in the era of platforms. Yeah. [00:49:32] Vince Menzione: And the problem is they’re all stove pipe today. If, if at all. Yeah. Maintained, right. [00:49:36] Vince Menzione: Alliances is an example. Channels and other example. They don’t talk to one another. Judge any, we’ve got a mic up here if anybody else has. Yep. We have some questions here, Jacqueline. [00:49:51] Question: So when we’re developing our channel programs, any advice on, you know, what’s the shift that we should make six months from now, a year from now? The historical has been bronze, silver, gold, right? And you’ve got your deal registration, but what’s the future look like? [00:50:05] Jay McBain: Yeah, so I mean, the programs are, are changing to, to the point where the customer should be in the middle and realizing the seven partners you need to win the deal. [00:50:15] Jay McBain: And depending on what category of product you’re in, security, how much you rely on resell, 91.6%. You know, the channel partners are gonna be critical where the customer spends the money. And if you’re adding friction to that process, you’re adding friction in terms of your growth. So you know, if you’re in cybersecurity, you have to have a pretty wide open reseller model. [00:50:39] Jay McBain: You have to have a wide open distribution model, and you have to make sure you’re there at that point of sale. While at the same time, considering the other six partners at moment 12 who are in either saying nice things about you or not, the customer might even be starting with you. ’cause there is actually one thing that I didn’t mention when I showed the 28 moments filled in. [00:51:00] Jay McBain: You’ll notice that the customer went to AWS twice direct. AWS lost the deal. Microsoft won the deal software. One is Microsoft’s biggest reseller in the world. They just acquired crayon. NTT who, who loves both had their Microsoft team go in. [00:51:18] Question: Mm. [00:51:19] Jay McBain: So I think that they went to AWS thinking it was A-W-S-S-A-P, you know, kind of starting this seven layer stack. [00:51:25] Jay McBain: I think they finished those, you know, critical moments in the middle looking at it. And then they went back to AWS kind of going probably WWTF. Yeah. What we thought was happening isn’t actually the outcome that was painted by our most trusted people. So, you know, to answer your question, listen to your partners. [00:51:43] Jay McBain: They want to be recognized for the other things they’re doing. You can’t be spending a hundred percent of the dollars at the point of sale. You gotta have a point of system that recognizes the point of sale, maybe even gold, silver, bronze, but recognizing that you’re paying for these other moments as well. [00:51:57] Jay McBain: Paying for alliances, paying for integrations and everything else, uh, in the cyber stack. And, um, you know, recognizing also the top 1000. So if I took your tam. And I overlaid those thousand logos. I would be walking into 2026 the best I could of showing my company logo by logo, where 80% of our TAM sits as wallet share, not by revenue. [00:52:25] Jay McBain: Remember, a million dollar partner is not a million dollar partner. One of them sells 1.2 million in our category. We should buy them a baseball cap and have ’em sit in the front row of our event. One of them sells $10 million and only sells our stuff if the customer asks. So my company should be looking at that $9 million opportunity and making sure my programs are writing the checks and my coverage. [00:52:48] Jay McBain: My capacity and capability planning is getting obsessed over that $9 million. My farmers can go over there, my hunters can go over here, and I should be submitting a list of a thousand sorted in descending order of opportunity. Of where my company can write program dollars into. [00:53:07] Vince Menzione: Great answer. All right. I, I do wanna be cognizant of time and the, all the other sessions we have. [00:53:14] Vince Menzione: So we’ll just take one other question if there are any here and if not, we’ll let I know. Jay, you’re gonna be mingling around for a little while before your flight. I’m [00:53:21] Jay McBain: here the whole day. [00:53:22] Vince Menzione: You, you’re the whole day. I see that Jay’s here the whole day. So if you have any other questions and, and, uh, sharing the deck is that. [00:53:29] Vince Menzione: Yep. Alright. We have permission to share the deck with the each of you as well. [00:53:34] Jay McBain: Alright, well thank you very much everyone. Jay. Great to have you.

Crazy Wisdom: Read the notes at at podcastnotes.org. Don't forget to subscribe for free to our newsletter, the top 10 ideas of the week, every Monday --------- In this episode of the Crazy Wisdom Podcast, host Stewart Alsop speaks with Aaron Borger, founder and CEO of Orbital Robotics, about the emerging world of space robotics and satellite capture technology. The conversation covers a fascinating range of topics including Borger's early experience launching AI-controlled robotic arms to space as a student, his work at Blue Origin developing lunar lander software, and how his company is developing robots that can capture other spacecraft for refueling, repair, and debris removal. They discuss the technical challenges of operating in space - from radiation hardening electronics to dealing with tumbling satellites - as well as the broader implications for the space economy, from preventing the Kessler effect to building space-based recycling facilities and mining lunar ice for rocket fuel. You can find more about Aaron Borger's work at Orbital Robots and follow him on LinkedIn for updates on upcoming missions and demos. Check out this GPT we trained on the conversationTimestamps00:00 Introduction to orbital robotics, satellite capture, and why sensing and perception matter in space 05:00 The Kessler Effect, cascading collisions, and why space debris is an economic problem before it is an existential one 10:00 From debris removal to orbital recycling and the idea of turning junk into infrastructure 15:00 Long-term vision of space factories, lunar ice, and refueling satellites to bootstrap a lunar economy 20:00 Satellite upgrading, servicing live spacecraft, and expanding today's narrow space economy 25:00 Costs of collision avoidance, ISS maneuvers, and making debris capture economically viable 30:00 Early experiments with AI-controlled robotic arms, suborbital launches, and reinforcement learning in microgravity 35:00 Why deterministic AI and provable safety matter more than LLM hype for spacecraft control 40:00 Radiation, single event upsets, and designing space-safe AI systems with bounded behavior 45:00 AI, physics-based world models, and autonomy as the key to scaling space operations 50:00 Manufacturing constraints, space supply chains, and lessons from rocket engine software 55:00 The future of space startups, geopolitics, deterrence, and keeping space usable for humanityKey Insights1. Space Debris Removal as a Growing Economic Opportunity: Aaron Borger explains that orbital debris is becoming a critical problem with approximately 3,000-4,000 defunct satellites among the 15,000 total satellites in orbit. The company is developing robotic arms and AI-controlled spacecraft to capture other satellites for refueling, repair, debris removal, and even space station assembly. The economic case is compelling - it costs about $1 million for the ISS to maneuver around debris, so if their spacecraft can capture and remove multiple pieces of debris for less than that cost per piece, it becomes financially viable while addressing the growing space junk problem.2. Revolutionary AI Safety Methods Enable Space Robotics: Traditional NASA engineers have been reluctant to use AI for spacecraft control due to safety concerns, but Orbital Robotics has developed breakthrough methods combining reinforcement learning with traditional control systems that can mathematically prove the AI will behave safely. Their approach uses physics-based world models rather than pure data-driven learning, ensuring deterministic behavior and bounded operations. This represents a significant advancement over previous AI approaches that couldn't guarantee safe operation in the high-stakes environment of space.3. Vision for Space-Based Manufacturing and Resource Utilization: The long-term vision extends beyond debris removal to creating orbital recycling facilities that can break down captured satellites and rebuild them into new spacecraft using existing materials in orbit. Additionally, the company plans to harvest propellant from lunar ice, splitting it into hydrogen and oxygen for rocket fuel, which could kickstart a lunar economy by providing economic incentives for moon-based operations while supporting the growing satellite constellation infrastructure.4. Unique Space Technology Development Through Student Programs: Borger and his co-founder gained unprecedented experience by launching six AI-controlled robotic arms to space through NASA's student rocket programs while still undergraduates. These missions involved throwing and catching objects in microgravity using deep reinforcement learning trained in simulation and tested on Earth. This hands-on space experience is extremely rare and gave them practical knowledge that informed their current commercial venture.5. Hardware Challenges Require Innovative Engineering Solutions: Space presents unique technical challenges including radiation-induced single event upsets that can reset processors for up to 10 seconds, requiring "passive safe" trajectories that won't cause collisions even during system resets. Unlike traditional space companies that spend $100,000 on radiation-hardened processors, Orbital Robotics uses automotive-grade components made radiation-tolerant through smart software and electrical design, enabling cost-effective operations while maintaining safety.6. Space Manufacturing Supply Chain Constraints: The space industry faces significant manufacturing bottlenecks with 24-week lead times for space-grade components and limited suppliers serving multiple companies simultaneously. This creates challenges for scaling production - Orbital Robotics needs to manufacture 30 robotic arms per year within a few years. They've partnered with manufacturers who previously worked on Blue Origin's rocket engines to address these supply chain limitations and achieve the scale necessary for their ambitious deployment timeline.7. Emerging Space Economy Beyond Communications: While current commercial space activities focus primarily on communications satellites (with SpaceX Starlink holding 60% market share) and Earth observation, new sectors are emerging including AI data centers in space and orbital manufacturing. The convergence of AI, robotics, and space technology is enabling more sophisticated autonomous operations, from predictive maintenance of rocket engines using sensor data to complex orbital maneuvering and satellite servicing that was previously impossible with traditional control methods.

2025年のこのポッドキャストとホストを振り返りました。Show Note2025エピソード ランキング TOP 5176. 上達の法則 1,544再生 https://podcasts.apple.com/us/podcast/id1529233853?i=1000725421865161. Metaをレイオフされたはなし 1,525再生 https://podcasts.apple.com/us/podcast/id1529233853?i=1000709809864175. 良いデザインドキュメントの書き方 1,475再生 https://podcasts.apple.com/us/podcast/id1529233853?i=1000724284603177. GPT-5のプロンプトエンジニアリングガイドを読み解く 1,418再生 https://podcasts.apple.com/us/podcast/id1529233853?i=1000726784686159. エンジニアにおすすめの本 1,391再生 https://podcasts.apple.com/us/podcast/id1529233853?i=1000708011992## 買ってよかったものDell 4Kモニタ https://amzn.to/48XDOAr仕事机の足下ヒータ https://amzn.to/3N0SPZxモバイルディスプレイ ⁠https://amzn.to/4peW4e1⁠## 本亡刻のシェオル SFファンタジー https://amzn.to/4pX7vrlかがみの孤城 https://amzn.to/3NjXc1T一億年のテレスコープ https://amzn.to/4pTQiin日本のピアノは世界の非常識？ https://amzn.to/45kKN41科学的根拠に基づく最強の勉強法 https://amzn.to/4qnXWS0アノマリー ⁠https://amzn.to/4rCGmLA⁠ザリガニが鳴くところ ⁠https://amzn.to/4jcJ9qS⁠BORN TO RUN ⁠https://amzn.to/3XyMo1X⁠奇妙で不思議な菌類の世界 ⁠https://amzn.to/4as7zu6⁠感想をぜひハッシュタグ #tilfm でつぶやいてください!お便りフォーム https://forms.gle/J2ioXHS98dYNoMbq5Your co-hosts:Tomoaki Imai, Noxx CTO  https://x.com/tomoaki_imai bsky: https://bsky.app/profile/tomoaki-imai.bsky.socialRyoichi Kato, Software Engineer ⁠https://x.com/ryo1kato bsky: https://bsky.app/profile/ryo1kato.bsky.social買ってよかったもの本

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop speaks with Aaron Borger, founder and CEO of Orbital Robotics, about the emerging world of space robotics and satellite capture technology. The conversation covers a fascinating range of topics including Borger's early experience launching AI-controlled robotic arms to space as a student, his work at Blue Origin developing lunar lander software, and how his company is developing robots that can capture other spacecraft for refueling, repair, and debris removal. They discuss the technical challenges of operating in space - from radiation hardening electronics to dealing with tumbling satellites - as well as the broader implications for the space economy, from preventing the Kessler effect to building space-based recycling facilities and mining lunar ice for rocket fuel. You can find more about Aaron Borger's work at Orbital Robots and follow him on LinkedIn for updates on upcoming missions and demos. Check out this GPT we trained on the conversationTimestamps00:00 Introduction to orbital robotics, satellite capture, and why sensing and perception matter in space 05:00 The Kessler Effect, cascading collisions, and why space debris is an economic problem before it is an existential one 10:00 From debris removal to orbital recycling and the idea of turning junk into infrastructure 15:00 Long-term vision of space factories, lunar ice, and refueling satellites to bootstrap a lunar economy 20:00 Satellite upgrading, servicing live spacecraft, and expanding today's narrow space economy 25:00 Costs of collision avoidance, ISS maneuvers, and making debris capture economically viable 30:00 Early experiments with AI-controlled robotic arms, suborbital launches, and reinforcement learning in microgravity 35:00 Why deterministic AI and provable safety matter more than LLM hype for spacecraft control 40:00 Radiation, single event upsets, and designing space-safe AI systems with bounded behavior 45:00 AI, physics-based world models, and autonomy as the key to scaling space operations 50:00 Manufacturing constraints, space supply chains, and lessons from rocket engine software 55:00 The future of space startups, geopolitics, deterrence, and keeping space usable for humanityKey Insights1. Space Debris Removal as a Growing Economic Opportunity: Aaron Borger explains that orbital debris is becoming a critical problem with approximately 3,000-4,000 defunct satellites among the 15,000 total satellites in orbit. The company is developing robotic arms and AI-controlled spacecraft to capture other satellites for refueling, repair, debris removal, and even space station assembly. The economic case is compelling - it costs about $1 million for the ISS to maneuver around debris, so if their spacecraft can capture and remove multiple pieces of debris for less than that cost per piece, it becomes financially viable while addressing the growing space junk problem.2. Revolutionary AI Safety Methods Enable Space Robotics: Traditional NASA engineers have been reluctant to use AI for spacecraft control due to safety concerns, but Orbital Robotics has developed breakthrough methods combining reinforcement learning with traditional control systems that can mathematically prove the AI will behave safely. Their approach uses physics-based world models rather than pure data-driven learning, ensuring deterministic behavior and bounded operations. This represents a significant advancement over previous AI approaches that couldn't guarantee safe operation in the high-stakes environment of space.3. Vision for Space-Based Manufacturing and Resource Utilization: The long-term vision extends beyond debris removal to creating orbital recycling facilities that can break down captured satellites and rebuild them into new spacecraft using existing materials in orbit. Additionally, the company plans to harvest propellant from lunar ice, splitting it into hydrogen and oxygen for rocket fuel, which could kickstart a lunar economy by providing economic incentives for moon-based operations while supporting the growing satellite constellation infrastructure.4. Unique Space Technology Development Through Student Programs: Borger and his co-founder gained unprecedented experience by launching six AI-controlled robotic arms to space through NASA's student rocket programs while still undergraduates. These missions involved throwing and catching objects in microgravity using deep reinforcement learning trained in simulation and tested on Earth. This hands-on space experience is extremely rare and gave them practical knowledge that informed their current commercial venture.5. Hardware Challenges Require Innovative Engineering Solutions: Space presents unique technical challenges including radiation-induced single event upsets that can reset processors for up to 10 seconds, requiring "passive safe" trajectories that won't cause collisions even during system resets. Unlike traditional space companies that spend $100,000 on radiation-hardened processors, Orbital Robotics uses automotive-grade components made radiation-tolerant through smart software and electrical design, enabling cost-effective operations while maintaining safety.6. Space Manufacturing Supply Chain Constraints: The space industry faces significant manufacturing bottlenecks with 24-week lead times for space-grade components and limited suppliers serving multiple companies simultaneously. This creates challenges for scaling production - Orbital Robotics needs to manufacture 30 robotic arms per year within a few years. They've partnered with manufacturers who previously worked on Blue Origin's rocket engines to address these supply chain limitations and achieve the scale necessary for their ambitious deployment timeline.7. Emerging Space Economy Beyond Communications: While current commercial space activities focus primarily on communications satellites (with SpaceX Starlink holding 60% market share) and Earth observation, new sectors are emerging including AI data centers in space and orbital manufacturing. The convergence of AI, robotics, and space technology is enabling more sophisticated autonomous operations, from predictive maintenance of rocket engines using sensor data to complex orbital maneuvering and satellite servicing that was previously impossible with traditional control methods.

From the frontlines of OpenAI's Codex and GPT-5 training teams, Bryan and Bill are building the future of AI-powered coding—where agents don't just autocomplete, they architect, refactor, and ship entire features while you sleep. We caught up with them at AI Engineer Conference right after the launch of Codex Max, OpenAI's newest long-running coding agent designed to work for 24+ hours straight, manage its own context, and spawn sub-agents to parallelize work across your entire codebase. We sat down with Bryan and Bill to dig into what it actually takes to train a model that developers trust—why personality, communication, and planning matter as much as raw capability, how Codex is trained with strong opinions about tools (it loves rg over grep, seriously), why the abstraction layer is moving from models to full-stack agents you can plug into VS Code or Zed, how OpenAI partners co-develop tool integrations and discover unexpected model habits (like renaming tools to match Codex's internal training), the rise of applied evals that measure real-world impact instead of academic benchmarks, why multi-turn evals are the next frontier (and Bryan's "job interview eval" idea), how coding agents are breaking out of code into personal automation, terminal workflows, and computer use, and their 2026 vision: coding agents trusted enough to handle the hardest refactors at any company, not just top-tier firms, and general enough to build integrations, organize your desktop, and unlock capabilities you'd never get access to otherwise. We discuss: What Codex Max is: a long-running coding agent that can work 24+ hours, manage its own context window, and spawn sub-agents for parallel work Why the name "Max": maximalist, maximization, speed and endurance—it's simply better and faster for the same problems Training for personality: communication, planning, context gathering, and checking your work as behavioral characteristics, not just capabilities How Codex develops habits like preferring rg over grep, and why renaming tools to match its training (e.g., terminal-style naming) dramatically improves tool-call performance The split between Codex (opinionated, agent-focused, optimized for the Codex harness) and GPT-5 (general, more durable across different tools and modalities) Why the abstraction layer is moving up: from prompting models to plugging in full agents (Codex, GitHub Copilot, Zed) that package the entire stack The rise of sub-agents and agents-using-agents: Codex Max spawning its own instances, handing off context, and parallelizing work across a codebase How OpenAI works with coding partners on the bleeding edge to co-develop tool integrations and discover what the model is actually good at The shift to applied evals: capturing real-world use cases instead of academic benchmarks, and why ~50% of OpenAI employees now use Codex daily Why multi-turn evals are the next frontier: LM-as-a-judge for entire trajectories, Bryan's "job interview eval" concept, and the need for a batch multi-turn eval API How coding agents are breaking out of code: personal automation, organizing desktops, terminal workflows, and "Devin for non-coding" use cases Why Slack is the ultimate UI for work, and how coding agents can become your personal automation layer for email, files, and everything in between The 2026 vision: more computer use, more trust, and coding agents capable enough that any company can access top-tier developer capabilities, not just elite firms — Bryan & Bill (OpenAI Codex Team) http://x.com/bfioca https://x.com/realchillben OpenAI Codex: https://openai.com/index/openai-codex/ Where to find Latent Space X: https://x.com/latentspacepod Substack: https://www.latent.space/ Chapters 00:00:00 Introduction: Latent Space Listeners at AI Engineer Code 00:01:27 Codex Max Launch: Training for Long-Running Coding Agents 00:03:01 Model Personality and Trust: Communication, Planning, and Self-Checking 00:05:20 Codex vs GPT-5: Opinionated Agents vs General Models 00:07:47 Tool Use and Model Habits: The Ripgrep Discovery 00:09:16 Personality Design: Verbosity vs Efficiency in Coding Agents 00:11:56 The Agent Abstraction Layer: Building on Top of Codex 00:14:08 Sub-Agents and Multi-Agent Patterns: The Future of Composition 00:16:11 Trust and Adoption: OpenAI Developers Using Codex Daily 00:17:21 Applied Evals: Real-World Testing vs Academic Benchmarks 00:19:15 Multi-Turn Evals and the Job Interview Pattern 00:21:35 Feature Request: Batch Multi-Turn Eval API 00:22:28 Beyond Code: Personal Automation and Computer Use 00:24:51 Vision-Native Agents and the UI Integration Challenge 00:25:02 2026 Predictions: Trust, Computer Use, and Democratized Excellence

What if the key to scaling your real estate career wasn't selling more—but letting go? In this episode of the Real Estate Excellence Podcast, Tracy Hayes sits down with Jonathan Lickstein, the award-winning COO of one of the nation's fastest-growing independent brokerages. From launching his career unexpectedly in Honduras to leading a 5,000-agent operation across six states, Jonathan reveals how he uses cutting-edge AI, strong culture, and deep mentorship to scale operations, without losing the human touch. Jonathan dives deep into how brokers can truly support agents in today's competitive market, why building relationships is more important than ever, and the powerful moment that made Jonathan realize he needed to let go in order to grow. Whether you're a solo agent, team leader, or managing broker, this episode offers a blueprint for sustainable growth, tech integration, and authentic leadership. Ready to level up your real estate career? Share this episode with a fellow agent, leave a review, and follow the Real Estate Excellence Podcast for more insider strategies from the industry's best.   Highlights: 00:00 – 07:04 From Georgia Tech to Honduras Career detour from engineering to real estate Building the largest property network on Roatan Selling million dollar homes at 19 The power of bilingual networking Returning to the US market with experience 07:05 – 14:01 Rebuilding in Florida with Relationships Restarting a business with zero clients Youth sports as a referral engine Using branded email for subtle marketing Getting 6 million in sales from one connection Leveraging everyday conversations 14:02 – 24:25 Winning with AI and Building Broker Efficiency How the brokerage won Inman's AI award Using AI to automate compliance and contracts Creating a GPT powered broker avatar Saving agents hours of manual entry Voice activated contract creation system 24:26 – 33:59 The Power of Letting Go to Scale The game changing moment on a baseball field Why delegation is critical for brokers Replacing yourself without losing culture Empowering your team to lead Avoiding burnout as a growing company 34:00 – 45:13 What Makes a Great Brokerage and How to Choose Red flags in bad broker leadership Why 100 percent commission isn't everything The importance of real support not just tools How brokers should evaluate their own value Questions every agent should ask before switching 45:14 – 59:50 Retention and Growth with Real Tech and Mentorship New agent mentoring that actually works Creating mastermind groups for real learning Using friends lists to maintain past clients Leveraging social media meaningfully The real reason agents stay or leave   Quotes: "This business is driven by relationships. AI should free you to build more of them—not replace them." – Jonathan Lickstein  "If I'm in line at a grocery store, by the time we leave, you'll know who I am, what I do, and how to get ahold of me." – Jonathan Lickstein "Support is the number one thing an agent should be looking for—not training, not branding, but support." – Jonathan Lickstein "There's no such thing as a past client—just someone you haven't reconnected with yet." – Jonathan Lickstein   To contact Jonathan Lickstein, learn more about her business, and make her a part of your network, make sure to follow her on her Website, Instagram, Facebook, YouTube, and TikTok.   Connect with Jonathan Lickstein! Website: http://www.jonathanlickstein.com Instagram: https://www.instagram.com/thebrokerlick Facebook: https://www.facebook.com/jonathan.lickstein LinkedIn: https://www.linkedin.com/in/jonathanlickstein/   Connect with me! Website: toprealtorjacksonville.com   Website: toprealtorstaugustine.com    SUBSCRIBE & LEAVE A 5-STAR REVIEW as we discuss real estate excellence with the best of the best.   #RealEstateExcellence ##JonathanLickstein #RealEstatePodcast #NicheMarketing #AIInRealEstate #RealEstateTips #ContentMarketing #LuxuryHomes #EquestrianLifestyle #PropertyInvesting #NewAgentAdvice #SocialMediaForRealtors #RealEstateStrategy #FloridaRealEstate #HorseProperties #LuxuryListingAgent

구글의 에어드롭 역설계애플 미니 앱 파트너 프로그램아이폰 포켓스팀 머신테슬라 FSD, 한국 지원테슬라가 카플레이?메타, (틱톡 덕분에) 독점 아니다카카오톡의 위치 공유 기능그래서 에이전틱 OS가 뭐죠?킴 카다시안, GPT 때문에 사법고시 떨어졌다제미나이 3(남이 조종하는) 가사 로봇일본 콘텐츠 업계, 드디어 AI에 뿔났다?"AI 버블은 존재한다"

팔로우업- 워너: "우리를 사 주세요"- 카카오톡 롤백은 불가능하다?- 에픽과 구글의 합의 - 최초 합의 - 근데 판사가 반대해요고깃집- 애플, 미국 F1 중계권 획득- 헤일로가 PS5?- 고지라 마이너스 제로- 락스타 게임즈 해고사건테슬라 BMS 문제돌아온 저가형 맥북 루머오픈AI, 이제 영리적 단체또 소송에 휘말린 챗GPT오픈AI 아틀라스퍼플렉시티 vs 아마존챗GPT, 카카오톡에 들어가다애플 인텔리전스 powered by 제미나이애플 M5- 디에디트 기사 by 쿠도군- 블루님 영상

Send us a textJoin hosts Alex Sarlin, Ben Kornell, Michael Horn and Dhawal Shah as they break down major moves in online learning, AI, and higher education shaping the end of 2025.✨ Episode Highlights:[00:00:00] Coursera and Udemy announce a $2.5B all-stock merger forming a 175M-learner platform[00:00:30] Michael Horn on Coursera's growing leverage over university partners[00:02:08] Ben Kornell explores Coursera's potential to become a global university [00:05:40] Dhawal Shah explains the financial motivations behind the merger [00:09:54] Michael Horn compares the deal to the 2U–edX acquisition [00:11:54] The hosts discuss channel power and aggregation in edtech [00:16:49] Debate on Coursera's acquisition strategy and platform future [00:21:43] Dhawal Shah on why these businesses may perform better as private companies [00:22:33] Ben Kornell outlines Coursera's two paths: efficiency or AI-led reinvention [00:30:24] Gaps in online learning around mentorship and advanced skills [00:35:29] OpenAI's latest release and rising competition with Google Gemini [00:38:55] Why content and IP still matter in the AI era [00:48:36] Purdue introduces an AI competency requirement for graduatesPlus, special guests: [00:52:54] Isabelle Hau, Executive Director of the Stanford Accelerator for Learning, on human-centered and social AI in education 

In this week's episode of the Rich Habits Podcast, Robert Croak and Austin Hankwitz answer your questions!---

In this episode of the AI Applied podcast, Conor Grennan and Jaeden discuss the new GPT image generator, GPT Image 1.5, and its implications for enterprise use. They explore how this model, similar to Google's Gemini NanoBanana Pro, offers customizable, cost-effective solutions for businesses. Jaeden shares his experience using the model for creating YouTube thumbnails, highlighting its improved reasoning and ability to handle complex prompts. The conversation also touches on the importance of patience and iteration when working with AI models, as well as the potential for these tools to revolutionize marketing strategies.Get the top 40+ AI Models for $20 at AI Box: ⁠⁠https://aibox.aiConor's AI Course: https://www.ai-mindset.ai/coursesConor's AI Newsletter: https://www.ai-mindset.ai/Jaeden's AI Hustle Community: https://www.skool.com/aihustleSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Our 229th episode with a summary and discussion of last week's big AI news!Recorded on 12/19/2025Hosted by Andrey Kurenkov and Jeremie HarrisFeel free to email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.aiRead out our text newsletter and comment on the podcast at https://lastweekin.ai/In this episode:Notable releases include OpenAI's GPT-5.2 Codex for advanced coding and Google's Gemini Free Flash for competitive AI application performance. Nvidia's new open-source Trion-3 models also showcase impressive benchmarks.Funding updates highlight Lovable's $330M Series B, valuing the AI coding startup at $6.6B, and Faya's $140M Series D for AI model hosting, valued at $4.5B.China makes significant strides in semiconductor technology with advances in EUV lithography machines, led by Huawei and SMIC, potentially disrupting global chip manufacturing dominance.Key safety and policy updates include OpenAI's GPT-5.2 system card focusing on biosecurity and cybersecurity risks, while Google partners with the US military to power a new AI platform with Gemini models.Timestamps:(00:00:10) Intro / Banter(00:02:09) News PreviewTools & Apps(00:02:56) Google launches Gemini 3 Flash, makes it the default model in the Gemini app | TechCrunch(00:10:13) ChatGPT launches an app store, lets developers know it's open for business | TechCrunch(00:13:35) Introducing GPT-5.2-Codex | OpenAI(00:19:23) Story about OpenAI release - GPT image 1.5(00:22:27) Meta partners with ElevenLabs to power AI audio across Instagram, Horizon - The Economic TimesApplications & Business(00:23:16) OpenAI to End Equity Vesting Period for Employees, WSJ Says(00:28:20) How China built its ‘Manhattan Project' to rival the West in AI chips(00:36:47) China's Huawei, SMIC Make Progress With Chips, Report Finds(00:41:03) OpenAI in Talks to Raise At Least $10 Billion From Amazon and Use Its AI Chips(00:43:32) Amazon has a new leader for its ‘AGI' group as it plays catch-up on AI | The Verge(00:47:27) Broadcom reveals its mystery $10 billion customer is Anthropic(00:49:12) Vibe-coding startup Lovable raises $330M at a $6.6B valuation | TechCrunch(00:50:38) Fal nabs $140M in fresh funding led by Sequoia, tripling valuation to $4.5B | TechCrunchProjects & Open Source(00:51:10) Nvidia Becomes a Major Model Maker With Nemotron 3 | WIRED(00:59:24) Meta introduces new SAM AI able to isolate and edit audio • The Register(00:59:54) [2512.14856] T5Gemma 2: Seeing, Reading, and Understanding Longer(01:03:10) Anthropic makes agent Skills an open standard - SiliconANGLEResearch & Advancements(01:03:47) Budget-Aware Tool-Use Enables Effective Agent Scaling(01:08:21) Rethinking Thinking Tokens: LLMs as Improvement Operators(01:10:50) What if AI capabilities suddenly accelerated in 2027? How would the world know?Policy & Safety(01:12:58) Update to GPdfT-5 System Card: GPT-5.2(01:18:04) Neural Chameleons: Language Models Can Learn to Hide Their Thoughts from Unseen Activation Monitors(01:20:47) Async Control: Stress-testing Asynchronous Control Measures for LLM Agents(01:24:37) Google is powering a new US military AI platform | The VergeSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Student use of AI tools presents challenges for faculty teaching writing. In this episode, Anna Mills joins us to discuss when and how AI tools can be used to help students develop their writing skills. Anna has been a leader in exploring effective strategies for integrating AI into higher education in a manner that fosters the development of student critical literacy. Anna serves on the MLA Task Force on Writing and AI and as a lead advisor on the instructional design for MyEssayFeedback.ai. She also has served as the only educational specialist recruited by Open AI to test GPT-4 pre-release. Anna is also an OER advocate who has released numerous OER resources including two OER textbooks, one on How Arguments Work: A Guide to Writing and Analyzing Texts in College, and the other on AI in College Writing: An Orientation. She is also one of the developers of the PAIRR process in which students develop writing skills through feedback from peers, AI, and individual reflection.  A transcript of this episode and show notes may be found at http://teaforteaching.com.  

This is a lively, no-holds-barred debate about whether AI can truly be intelligent, conscious, or understand anything at all — and what happens when (or if) machines become smarter than us.Dr. Mike Israetel is a sports scientist, entrepreneur, and co-founder of RP Strength (a fitness company). He describes himself as a "dilettante" in AI but brings a fascinating outsider's perspective.Jared Feather (IFBB Pro bodybuilder and exercise physiologist)The Big Questions:1. When is superintelligence coming?2. Does AI actually understand anything?3. The Simulation Debate (The Spiciest Part)4. Will AI kill us all? (The Doomer Debate)5. What happens to human jobs and purpose?6. Do we need suffering?Mikes channel: https://www.youtube.com/channel/UCfQgsKhHjSyRLOp9mnffqVgRESCRIPT INTERACTIVE PLAYER: https://app.rescript.info/public/share/GVMUXHCqctPkXH8WcYtufFG7FQcdJew_RL_MLgMKU1U---TIMESTAMPS:00:00:00 Introduction & Workout Demo00:04:15 ASI Timelines & Definitions00:10:24 The Embodiment Debate00:18:28 Neutrinos & Abstract Knowledge00:25:56 Can AI Learn From YouTube?00:31:25 Diversity of Intelligence00:36:00 AI Slop & Understanding00:45:18 The Simulation Argument: Fire & Water00:58:36 Consciousness & Zombies01:04:30 Do Reasoning Models Actually Reason?01:12:00 The Live Learning Problem01:19:15 Superintelligence & Benevolence01:28:59 What is True Agency?01:37:20 Game Theory & The "Kill All Humans" Fallacy01:48:05 Regulation & The China Factor01:55:52 Mind Uploading & The Future of Love02:04:41 Economics of ASI: Will We Be Useless?02:13:35 The Matrix & The Value of Suffering02:17:30 Transhumanism & Inequality02:21:28 Debrief: AI Medical Advice & Final Thoughts---REFERENCES:Paper:[00:10:45] Alchemy and Artificial Intelligence (Dreyfus)https://www.rand.org/content/dam/rand/pubs/papers/2006/P3244.pdf[00:10:55] The Chinese Room Argument (John Searle)https://home.csulb.edu/~cwallis/382/readings/482/searle.minds.brains.programs.bbs.1980.pdf[00:11:05] The Symbol Grounding Problem (Stephen Harnad)https://arxiv.org/html/cs/9906002[00:23:00] Attention Is All You Needhttps://arxiv.org/abs/1706.03762[00:45:00] GPT-4 Technical Reporthttps://arxiv.org/abs/2303.08774[01:45:00] Anthropic Agentic Misalignment Paperhttps://www.anthropic.com/research/agentic-misalignment[02:17:45] Retatrutidehttps://pubmed.ncbi.nlm.nih.gov/37366315/Organization:[00:15:50] CERNhttps://home.cern/[01:05:00] METR Long Horizon Evaluationshttps://evaluations.metr.org/MLST Episode:[00:23:10] MLST: Llion Jones - Inventors' Remorsehttps://www.youtube.com/watch?v=DtePicx_kFY[00:50:30] MLST: Blaise Agüera y Arcas Interviewhttps://www.youtube.com/watch?v=rMSEqJ_4EBk[01:10:00] MLST: David Krakauerhttps://www.youtube.com/watch?v=dY46YsGWMIcEvent:[00:23:40] ARC Prize/Challengehttps://arcprize.org/Book:[00:24:45] The Brain Abstractedhttps://www.amazon.com/Brain-Abstracted-Simplification-Philosophy-Neuroscience/dp/0262548046[00:47:55] Pamela McCorduckhttps://www.amazon.com/Machines-Who-Think-Artificial-Intelligence/dp/1568812051[01:23:15] The Singularity Is Nearer (Ray Kurzweil)https://www.amazon.com/Singularity-Nearer-Ray-Kurzweil-ebook/dp/B08Y6FYJVY[01:27:35] A Fire Upon The Deep (Vernor Vinge)https://www.amazon.com/Fire-Upon-Deep-S-F-MASTERWORKS-ebook/dp/B00AVUMIZE/[02:04:50] Deep Utopia (Nick Bostrom)https://www.amazon.com/Deep-Utopia-Meaning-Solved-World/dp/1646871642[02:05:00] Technofeudalism (Yanis Varoufakis)https://www.amazon.com/Technofeudalism-Killed-Capitalism-Yanis-Varoufakis/dp/1685891241Visual Context Needed:[00:29:40] AT-AT Walker (Star Wars)https://starwars.fandom.com/wiki/All_Terrain_Armored_TransportPerson:[00:33:15] Andrej Karpathyhttps://karpathy.ai/Video:[01:40:00] Mike Israetel vs Liron Shapira AI Doom Debatehttps://www.youtube.com/watch?v=RaDWSPMdM4oCompany:[02:26:30] Examine.comhttps://examine.com/

Send us a text2025 was a defining year for AI in education. From rapid adoption to rising educator confidence and growing questions about what comes next.In Part 1 of our year-end reflections and predictions, Alex Sarlin and Ben Kornell revisit their 2025 reflections and look ahead to what 2026 may bring for EdTech, AI, and the future of learning.

I am off for the holidays, but I am not leaving you empty handed.  Please enjoy the first of many shows to come, featuring my favorite AMA calls of '25.  Including a woman who ended up losing her virginity to a married man, a bridesmaid using chat GPT to decline a wedding invite, and much more.I will be back LIVE on Monday 1/5, until than have a happy and safe holiday season! Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Sharon Karaffa is the President of Multifamily Debt and Structured Finance at Newmark. With over two decades of experience, she's built her career advising on agency lending, capital markets strategy, and multifamily finance. From starting in corporate finance at Fannie Mae to shaping lending strategies during volatile market cycles, Sharon brings a rare lens on long-term trends and real-time insights. She has led teams through critical transitions, including Fannie Mae's restatement period and the public launch of Newmark's multifamily platform, giving her a comprehensive view from both the borrower and lender perspective.     Make sure to download our free guide, 7 Questions Every Passive Investor Should Ask, here.     Key Takeaways How Sharon transitioned into multifamily lending during a corporate finance shake-up at Fannie Mae Why mentorship and sponsorship play a crucial role in long-term success The ongoing conservatorship of Fannie and Freddie—and what it means for agency lending How current interest rate volatility is reshaping investor and lender behavior The role of AI in the future of multifamily debt underwriting     Topics Covered Falling Into Multifamily by Taking a Chance Sharon shares how she unexpectedly landed in multifamily finance after being offered three career tracks at Fannie Mae—and choosing the one she knew the least about. Navigating the Conservatorship Era A look at how Fannie and Freddie's placement under conservatorship in 2008 changed the structure of agency lending, from Treasury sweeps to regulatory capital planning. How Volatility Affects Lending Decisions Sharon explains how rate volatility has impacted investor confidence and what lenders consider when advising clients during market uncertainty. Bridge Loans vs. Agency Debt Sharon breaks down where potential distress may appear in the market and why deals underwritten with aggressive bridge debt may be more vulnerable. Lender Advice: Don't Wait for the 'Perfect Rate' Insight on why now may still be the right time to execute a deal—and how waiting on the sidelines may mean missing key opportunities. Tech and AI in Multifamily Lending Sharon shares how Newmark is experimenting with a proprietary GPT tool for internal underwriting and predictive analytics—and where AI still needs work.    

From DeepSeek's shockwave debut and the trillion-dollar AI infrastructure buildout to the bubble debate, the MIT enterprise adoption backlash, the AI talent wars, and the rise of reasoning, agents, and vibe coding, this episode walks through the 10 defining AI stories that shaped 2025 and set the trajectory for 2026, including why agent infrastructure quietly became the most important foundation of the year and how next-leap models like Gemini 3, Opus 4.5, and GPT-5.2 reset expectations for what's coming next. In the headlines: DeepSeek R1, Project Stargate, the AI bubble debate, enterprise ROI myths, talent wars, reasoning models, vibe coding, agent infrastructure, and next-generation models.Brought to you by:KPMG – Discover how AI is transforming possibility into reality. Tune into the new KPMG 'You Can with AI' podcast and unlock insights that will inform smarter decisions inside your enterprise. Listen now and start shaping your future with every episode. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.kpmg.us/AIpodcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Blitzy.com - Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://blitzy.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ to build enterprise software in days, not months Robots & Pencils - Cloud-native AI solutions that power results ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://robotsandpencils.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Agent Readiness Audit from Superintelligent - Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://besuper.ai/ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠to request your company's agent readiness score.The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614Interested in sponsoring the show? sponsors@aidailybrief.ai

Brett and Christina host an OG episode. Christina talks about her upcoming spinal surgery and navigating insurance hassles. Brett talks about his sleep issues, project progress, and coding routines. They dive into the complexities of USB-C cables, from volts to data rates. And TV’s just ‘okay’ now, except for some softcore gay porn. Kagi search saves the day. Happy holidays — and get some sleep. Sponsor Copilot Money can help you take control of your finances. Get a fresh start with your money for 2026 with 26% off when you visit try.copilot.money/overtired and use code OVERTIRED. Shopify is the commerce platform behind 10% of all eCommerce in the US, from household names like Mattel and Gymshark, to brands just getting started. Get started today at shopify.com/overtired. Show Links CaberQu BLE cable tester Umami Analytics Plausible Analytics Kagi The Comfortable Problem of Mid TV – The New York Times Fallout Heated Rivalry (TV Series 2025– ) – IMDb Chapters 00:00 Introduction and Greetings 00:40 Christina’s Health Update 05:05 Brett’s Sleep and Work Routine 12:19 USB-C Cable Confusion 22:03 Sponsor Break: Shopify 24:26 Sponsor Break: Copilot Money 26:57 Exploring Rocket Money and Web Interfaces 27:21 Discovering Umami Analytics 28:06 Nostalgia for Mint and Fever 28:44 The Decline of RSS and Google Reader 31:45 Switching to Kagi Search Engine 32:33 The Rise of AI-Generated Content 40:46 TV Shows: Is TV Just Okay Now? 47:24 The Cultural Phenomenon of Heated Rivalry 52:50 Wrapping Up and Holiday Wishes Join the Conversation Merch Come chat on Discord! Twitter/ovrtrd Instagram/ovrtrd Youtube Get the Newsletter Thanks! You’re downloading today’s show from CacheFly’s network BackBeat Media Podcast Network Check out more episodes at overtiredpod.com and subscribe on Apple Podcasts, Spotify, or your favorite podcast app. Find Brett as @ttscoff, Christina as @film_girl, Jeff as @jsguntzel, and follow Overtired at @ovrtrd on Twitter. Transcript Universal Serial Bitching Introduction and Greetings [00:00:00] Brett: Hey, you’re listening to Overtired. I am Brett Terpstra, and it’s just me and Christina Warren this morning. How you doing, Christina? Christina: Doing pretty good. Doing pretty good. Yeah. This is the, this is the OG Overtired configuration. Brett: right back to basics. Um, Christina: We do miss you Jeff, though. Ho, ho, ho. Hope that Jeff is having a great holiday with his family. Brett: we’ll have to have some, uh, gratuitous Wiki K hole that you go down just to, to commemorate the olden days. Um, so yeah, let’s, uh, let’s, let’s do a quick check-in. Christina’s Health Update Brett: Um, I’m curious about your health and all of the wildness that’s going on with your spine and whatnot. Christina: Yeah. Yeah. Um, same. I wanna hear about you too. Um, so, uh, Christina’s cervical spine update, as it were. Um, I am [00:01:00] still waiting to, as we’re recording this, which is like. Uh, three days before Christmas, uh, I’m still waiting to hear from the, uh, hospital to see if I can, when I can get scheduled. Um, insurance has sort of been a pain in the ass, so when I talked to them last week, they were like, we sent them some paperwork. We’re still waiting for some things back then. I called the insurance company and the, the, uh, like my insurance is like, has like an intermediary service that is supposed to contact the insurance company on your behalf and that person, but like, I can’t contact them directly. And then that person was like, oh, you don’t need pre-authorization. Go ahead and schedule the surgery. And I’m like, this doesn’t feel right. Um, so, but, but we, we went ahead and we called back the, you know, the, the surgeon, um, his office and they were very nice and we were like. They say that we can get on the books. So I don’t know when that will be. I’m hoping that it will be, you know, like the first week of January, um, or, or, or thereabouts. Um, but I don’t know. Um, [00:02:00] so I am still kind of in this like limbo stage where I don’t know exactly when I’m gonna have the surgery, except hopefully soon. And, um, and, and for anyone who hasn’t caught up, I, uh, I have a bulging disc on C seven on my cervical spine, and I’m going to get a, um, artificial disc replacement. Um, so they’re gonna take out the, you know, bulging bone and all that and put in, uh, some synthetic piece and then hopefully that will immediately relieve the, the pain that has been primarily through the left side of, uh, my arm and my shoulder, um, uh, down through my fingers. But it’s been on my right side a little bit too. So hopefully when that is done, it’ll be a relatively short recovery. Um, I’ll have an early scar and um, I will be, you know, not. Uh, the pain right now, like the levels aren’t terrible, but I’m pretty numb, uh, on my, my, my left arm, my, my right arm, um, uh, or right fingers I guess too, but, but really it’s, it’s, uh, the, the, the left side [00:03:00] that’s the worst. And traveling. Um, I’m, I’m in Atlanta with my family right now and, you know, kind of doing other things is just not, it’s not great. So, um, hopefully I’ll be getting surgery sooner rather than later. But obviously all that stuff does impact your mental health too, when you’re in pain and, and you, you know, are freaked out too about, you know, like, even though like they do, you know, it, it’s not an uncommon surgery and, and it, and it should be fine, but you know, there’s always these things in the back of your mind. You’re like, okay, well what if something goes wrong or whatever. So I’m just, I’m looking forward to, um, you know, light at the end of the tunnel, but um, still kind of in a holding pattern with that. So Brett: Wow. So that scar’s, that scar’s gonna be on your throat. Christina: Yeah, Brett: Wow. Christina: yeah. Like probably like. No, not really. I’m, I mean, I’m hoping that it’ll be, uh, like no, it really won’t be at all. Brett: I, I, I would like to have it. I can understand why you wouldn’t. Christina: yeah, I mean, you know, I will obviously, you know, uh, hopefully it’ll be like low enough to be [00:04:00] primarily covered by shirts or other things, although, who knows? ’cause I do like to wear like, lower cut things sometimes. I don’t know. It, it’ll hopefully, you Brett: I heard chokers are coming back. Christina: Yeah, I don’t, unfortunately. I think it’s gonna be too, uh, low for that. Brett: Okay. Christina: uh, like, it, it’s gonna be, I think like it might hit against my laryn is, is what they say. That’s the other thing too. I might have, you know, some hoarseness after, won’t we permanent? Um, you know, knock on wood. Um, Brett: go on Etsy, you can get, um, they’re for BDSM, they’re like neck, uh, they hold your chin up. They’re like posture enhancers. Uh, but they sell them within leather with like corset straps. ’cause they’re like A-B-D-S-M accessory. That would work. Christina: No, no. Not even once. Uh, not even once. I mean, look, a good group of people who wanna do that, uh, I I will not be wearing a collar of any sort of that sort of thing. Uh, I, I, I don’t, I don’t really wanna, wanna be part [00:05:00] of, uh, one of that, those types of, you know, uh, Harlequin romance novels. , Brett’s Sleep and Work Routine Brett: All right, well, I will go ahead and check in. Um, I, I’m sleeping really well for like two days at a time, and then I’ll have. A string of like five or six hours of sleep, which isn’t nothing. Um, but it’s not quite enough for me to not feel tired all the time. And two nights of sleep is not enough for me to catch up on sleep. And, um, so I’m kind of, this has been going on for like a year though, so it’s, I’m just kind of, I’m used to it and I’ve learned to operate pretty well on six or seven hours of sleep, even though historically like I need eight and a half. Um, but I’m doing okay and I get up about four every morning and I start coding and I usually code from like four to noon, so an eight [00:06:00] hour workday, uh, with a breakfast somewhere in there. And, um, I’ve made really good progress. Marked is, as far as I can tell, ready to go wide with the beta. Um. I think I’ve solved every bug that’s been reported so far. I only have about a hundred testers right now, um, but I’m gonna open it up, uh, try to get maybe a thousand testers for a couple weeks and then go for a live release. The biggest thing that I’m running into is problems with getting the, like free trial and the purchase mechanisms working, which is the exact same thing that’s holding up NV Ultra right now. Um, so if I can figure it out for Mark, I can port it to NV Ultra. I can have two apps out there making money, hopefully never have to get a job again. Um, I’m teamed up right now with Dan Peterson, formerly of One Password. Um, and we’re [00:07:00] working on some iOS apps and. And, uh, apex. My, my, all my Universal markdown processor is, it’s coming along really well. I’ve, I’ve put it out there. Um, I’ve talked to John Gruber a little bit about it. He’s gonna give it more of a workout and get back to me. Um, but I think, I think it’s getting to a point where I would be comfortable integrating it into Mark and even talking to some other, uh, apps about using it as their default processor, um, and kind of alleviating some of the issues people run into with, uh, differences in syntax. Um, I. I, I, I talked to Devon, think, uh, Eric from Devon think about using it. ’cause they use multi markdown right now, uh, which has a lot of cool features, but is not [00:08:00] really in sync with what most of the web is using these days. Um, so I talked to them about it and they’re like, oh, we had the exact same idea and we’re almost done with our own universal processor. Um, and theirs is gonna output like RTF and things that I don’t need apex to do. ’cause you can just pipe apex into panoc and do everything you need. So anyway, I’m, I’m tired. I’m, I’m in good spirits. I. I’m dealing fine with winter. My, I’m alone on Christmas, which is gonna be weird. Um, my family’s outta town. Elle is house sitting I’ll, I’ll go visit Elle, but most of the day I’m gonna be like by myself on Christmas and I don’t drink anymore. And I, I don’t, I don’t know how that’s gonna go yet. Um, initially I thought, oh, that’s fine. I like being alone. But then, [00:09:00] then the idea of like, not having anyone to talk to you on Christmas day started to feel a little depressing. Christina: Yeah. Yeah. Um, but, um, hopefully, um, when, when will, uh, when will I’ll be back from, from house sitting. How long is, uh, are, are they going to be Brett: I think. I think the people, the, the house owners come back Thursday or Friday. Christina: Okay. Brett: Then we’re gonna take off and go up to Minneapolis to hang out with her family for a weekend. So, I don’t know. It’ll, it’s gonna be fine. It’s gonna be fine. We’re gonna like cook on Christmas Eve and, and have leftovers on Christmas day. It’ll be fine. Christina: Yeah, yeah. Well, but, but it, but, but that is weird. Like, I’m sure like to be, you know, not, not, not, not with like your usual crew, but, um, [00:10:00] especially without the alcohol there. But that’s probably a good thing too. Brett: Yeah, I guess. Um, I will have all the cats. I’ll be fine. I have to take care of the dog too. Christina: Have, have you heard any updates, like, um, I guess, um, about when you were, you know, you were in the hospital a few times over the last year with, with various things. Did you ever get any definitive update on what that was? Brett: On which one? I have so many symptoms. Which one are we talking about? Christina: Well, I guess I, I guess when you, you know, you’ve had to be like hospitalized or Brett: The pancreatitis. Christina: had the pancreatitis. Brett: the, the fact that it hasn’t happened again since I stopped drinking, um, really does indicate that it was entirely alcohol that was causing the problem. Um, so yeah, I’m just, I’m never gonna drink again. That’s fine. It’s, it’s all fine. Um, I did, I did get approved to get back on Medicaid. Um, so [00:11:00] yeah, I haven’t gotten the paperwork in the mail yet. Uh, but my old card should just start working and I’ll be able to, my, my new doctor wants a whole bunch more tests, including an MRI of my pituitary gland. Um. Like testosterone tests and stuff that I guess is more specific to what she thinks might be going on with me. Um, but now I can, I can actually get those tests That would’ve been just a huge out-of-pocket expense over the last couple months. So I’m excited. I’m excited to be back on Medicaid. I wish everyone could have Medicaid. Christina: Yeah, that would be really nice. That would be really nice if, if, if we had systems like that available, um, for everyone. Um, but. Instead, you know, if they’re, like, if you have really great health, I mean, you, you pointed those out. Like you have really great health insurance if you [00:12:00] can prove that you, you know, make absolutely no money. Um, but, but that opens up so many other, you know, issues that most people aren’t lucky enough to be able Brett: right. Yeah, totally. Christina: right. Brett: All right, well do you, okay, first topic. USB-C Cable Confusion Brett: How much do you know about USBC cables and the various specs? Christina: Uh, Brett: you know a shit ton. Christina: I do, unfortunately, I know a lot. Brett: So I, I had been operating under the assumption that there were basically, you had like data USBC cables, you had, uh, thunderbolt USBC cables and you had like, power only USPC cables. It turns out there’s like 18 different varieties of different, uh, like vol, uh, voltage, uh, amperage, uh, levels, like total wattage basically. And, um, and transfer speeds. And, [00:13:00] um, and there’s like maximum links for different types of cable. And it, it, I started to understand why like. One device would charge with one cable and another device would not charge with the same cable, even though they all have the same connector. Christina: Yeah. Yeah. I mean, I think this is, this is why, um, some of us have been really like eye rolly at the EU for their pronouncements about certain things, because simply mandating a connector type doesn’t actually solve the problem. Brett: No, it actually confuses it a little bit Christina: I think Yeah, I was going to say exactly. I think in some cases it makes it worse. Right? And, and then you have different, like, and, and then getting SB four into it, uh, uh, versus like, like, like, like various Thunderbolt versions. Like that adds complications too, because technically SB four and Thunderbolt four should basically be the same, but they’re not really, there are a couple of things that Thunderbolt might have that [00:14:00] USB four doesn’t necessarily have to have, although for all intents and purposes they might be the same. And then of course, thunderbolts five is its own thing too. So like I bought off of Kickstarter, I got like this, you know, like a cable charger, basically like, like a connector thing. It was like $120. For this, this, this thing that basically you can plug a cable into and you can see its voltage and um, or not voltage, I guess it’s uh, you know, amperage or whatever. And you can see like, it, it, it’s transfer speed and you can basically like check that on like a little display, which is useful, but the fact that like, you have to buy that sometimes. So like figure out, well, okay, well which cable is this? Right? And then, uh, to your point about lengths, right? So like, okay, so you want something that’s going to be fast charging but also high speed data transfer. Alright, well that means that you, the cable’s gonna have to be stiff. It’s not gonna be able to be something that’s really bendable. Um, which of course is what most people are going to want. So like you can get a fast charge, like a 240 wat or a hundred and, you know, 20 wat or, or [00:15:00] whatever, um, like a USB 2.0 transfer speed cable. But if you want one that’s, uh, going to be, you know, fast charging and. Fast data transfer, then like that’s a different type. And they have like limited lengths, which again, can also be associated with like Thunderbolt or Thunderbolt. You know, cables are much more expensive. Um, and, uh, uh, you know, the, the, the, but their, their lengths are limited. Um, yeah. Uh, it’s very confusing. Brett: Did you know that in rare circumstances there are even devices that will only charge with an A to C cable. Christina: Yes, Brett: That’s so insane. Christina: yeah, no, I’ve run into that myself and then that’s a weird thing and I don’t even know how that should work. ’cause it’s, it’s, it’s a bizarre thing. You’re like, okay, well I thought this was just like a, you know, maybe like a dumb end, but it’s like, no, there’s like, you know, basically a microchip Brett: Like a two pin to two pin. Christina: at this point. Brett: Like two pen to two pen, no pd like you would think that would work with C to C, [00:16:00] but somehow it has to be A to c. I am getting one of those cable testers. I asked for one for Christmas so I could figure out this pile of cables I have and like my Sonos Ace headphones are very particular about which cables and what, um, charging hub I hooked them up to Christina: Right. Oh, yeah, hubs. I was gonna say, hubs introduce a whole other complication into this too, because depending on what hub you’re using, if you’re using a USB hub, it may or may not have certain things versus a Thunderbolt hub versus something else, versus just like, um, you know, a power brick. Like, yeah. Brett: Yeah. It’s fun stuff you. Christina: Yeah. No, it’s annoying. And, um, like, and what, what’s frustrating about this is like some of the cables that they’re better, like you can look at the, you know, the bottoms of them and you can see like they will have like the USB like four, or they might have 3.2, or they might have, you know, like the thunderbolt, you know, um, uh, icon [00:17:00] with, with, with its version. So you can figure out is this 20 gigabits, is this 40, is this 80? Um, but um. That’s not a guaranteed thing, and that also doesn’t guarantee authenticity of stuff, right? So a lot of the cables, you know, you buy off the internet can be, you know, and they might be, or even at stores, right? Like you’re, you’re not buying something from, even if you get things from Belkin or whoever, like, those things can have issues too. Um, although they at least tend to have better warranties. I bought a Balkan, um. Uh, like a, a, a PD cable, like a two 40 cable that I think it was like, you know, uh, 10 feet longer something. It was supposed to have some sort of long warranty and, and because the, the, you know, um, faster transfer ones, um, are, even though it was braided, you know, it stiff and it, it broke, like there was, uh, the, like the, you know, the connect with the part of the, the, the cable near the, the end, um, did that thing that typically apple cables do, where like, it, it sort of [00:18:00] fraying and you started like seeing the exposed wires and then like, you start to like, feel like, you know, like an electric charge, like Brett: A little tingle. Christina: you’re Yeah. And you’re like, okay, this isn’t good. Um, and so I at least had my Amazon receipt, so I was able to like. Get them to mail me a new one relatively easily. And like Anchor has an okay warranty too. But it’s one of those things you’re like, okay, when did I buy this? I was like, I didn’t even buy this a year ago, and this thing already crapped out. Um, versus, you know, you can get some really nice braided cables that are flexible, but they’re just gonna be 2.0 speeds. Um, and, and then if you buy, you know, you just buy like some random cable, you know, like at the airport or whatever. You’re like, all right, well, I don’t even know Brett: Great. Christina: anything about this. Uh, yeah, Brett: I have heard good things. I’ve heard good things about the company. Cable Matters. Christina: Yeah. Yeah. They make good stuff. They make good stuff. But again, at least the cables matters, cables that I have have been primarily stiffer cables because they tend to be like the, the higher transfer [00:19:00] speeds. So, um, like I have a cable, cable matters Thunderbolt cable, and I have like a USB four cable, I think. Um, but like, these are cables that like. I don’t, I mean, I, I have one that I, I kind of travel with, but I don’t, um, either keeping it as little cable matters, uh, uh, plastic, um. Like, so they come in like these, these case, uh, not these cases. Uh, they come in like these, uh, almost like Ziploc bag type of things. Um, which is a great way to ship cables honestly, you know, rather than using a box and, and like I, and I might toss one of those in a suitcase or a backpack, um, rather than having like the cable just out there loose. But I do that primarily because again, like they’re stiff and they’re not the sorts of things that I necessarily want, like in the bottom of my bag, you know, potentially getting broken and, and, and, and twisted and all of that. Um, they are overpriced for what they are and they are definitely not like, they’re not a high transfer cable, but if you can find ’em on sale, the beats, cables, the, the, the, the, the, the branded Beats cables, I actually like them better [00:20:00] than the apple cables that are the same thing, because they are, they’re longer, uh, by, you know, um, a, a few inches than, um, the, the Apple ones. But they’re still braided and they’re nice. And I was able to get, I dunno, this was a, this was not even Black Friday, but this was. Um, you know, sometime in like early November, I think, um, or maybe it was like late October. It might’ve been a Prime Day thing, I don’t know, but they were like eight or $9 a piece, and so I bought like five or six of them. Um, and they are, you know, uh, uh, PD and like, like, like fast charging peoples, they might not be 240, but I think they’re, they’re, they were like a hundred and you know, like 20 watts or whatever. But, um, you know, not high transfer speeds, but if you’re wanting to just quickly charge something and have it, you know, be a, a decent length and be like flexible. Those I don’t, those I don’t hate. Um, anchor makes pretty good cables. You green seems to be the company that’s sponsoring everyone now for various things. [00:21:00] But, um, I don’t know. I’ve started using MagSafe more and more, uh, like wireless charging when I can for some things, at least for phones, Brett: yeah. I actually have some U green wireless charging solutions that are really good. Christina: Yeah. Yeah. I just got one of their, uh, their 10,000 million pair battery fast charging battery things because now the MagSafe, uh, can be like up to, you know, 30 watts or whatever, or 25 watts or, or, or, or whatever it is. Like it’s, um, a lot more, um, usable than, you know, when it was like 10 or, or, or even 15. You’re like, okay, this, this is actually not going to be like the, the slowest, you know, charging thing known to man. But of course, obviously it’s like you can use it with your phone and with your AirPods, but the rest of the things out there don’t, don’t all support shi too, so, Brett: Right. Christina: yeah. Brett: All right. So, um, I want to talk about TV a little bit. Christina: Yeah. I think before we do that though, we should probably Brett: oh, we should, we [00:22:00] have two sponsors to fit in Jesus. I should get on that. Sponsor Break: Shopify Brett: Um, let’s start with, uh, let’s start with Shopify. This episode is brought to you by Shopify. Have you been dreaming of owning your own business? In addition to having something to sell, you’ll need a website, a payment system, a logo, a way to advertise to new customers, et cetera, et cetera. It can all be overwhelming and confusing, but that’s where today’s sponsor, Shopify comes in. Shopify is the commerce platform behind millions of businesses around the world, and 10% of all e-commerce in the us From household names like Mattel and Gym Shark to brands. Just getting started, get started with your own design studio with hundreds of ready to use templates. Shopify helps you build beautiful online store to match your brand style, accelerate your content creation. Shopify is packed with helpful AI tools that write product descriptions, page headlines, and even enhance your product photography.[00:23:00] Get the word out like you have a marketing team behind you. Easily create email and social media campaigns wherever your customers are scrolling or strolling. And best yet, Shopify is your commerce expert with world-class expertise and everything from managing inventory to international shipping, to processing returns and beyond. If you’re ready to sell, you’re ready for Shopify. Turn your big business idea into with Shopify on your side. Sign up for your $1 per month trial and start selling today@shopify.com slash Overtired. Go to shopify.com/ Overtired. That is shopify.com/ Overtired. Thanks Shopify. Christina: Thank you Shopify. Brett: It’ll be, it’ll be just tight as hell by the time people hear it. But that was rough. I, that, that, that, that read, you just heard I [00:24:00] edited like six places. ’cause I kept, I, I don’t know. I’m tired. I’ve been up since, I’ve been up since two today. Christina: Yeah. Shit, man. That’s, yeah, you again, like you’ve been having like sleep issues. It’s, it’s, Brett: Maybe, maybe I shouldn’t be doing sponsor reads. Christina: No, no, no, no, no. Uh, no. We definitely wanna talk about tv. Do you wanna do, do we wanna do our second, um, uh, uh, ad break Brett: let’s do a block. Let’s make it a Christina: Let’s do it. Block. Alright, fantastic. Sponsor Break: Copilot Money Christina: Alright, well, since we are about to go into 2026, this is a great time to, uh, think about your finances. So are you ready to take control of your finances? Well meet copilot money. This is the personal finance app that makes your money feel clear and calm with a beautiful design. Smart automation copilot money brings all of your spending, saving and investment accounts into one place. It’s available on iOS, Mac, iPad, and now on the web, which is really great, uh, because I know, uh, for me anyway, that’s one of my one kind of things [00:25:00] about some of these like tools like this is that there’s not a web app. I’m really bothered by it. This is, you know, it’s a frustration that like the Apple card, for a long time, you know, you couldn’t really access things on, on the web. Even now it’s still kind of messy, like being able to handle things on the web. But as we enter 2026, it is time for a fresh start. And so with the, uh, mint shutdown and rising financial uncertainty, consumers are seeking clarity and control. And this is where copilot money comes in. So copilot money can help you track your budgets, your savings goals, and your net worth seamlessly. Plus, with the the new, um, web launch, you can enjoy a sudden experience on any device, which is really good. And guess what? For a limited time, you can get 26% off your first year when you sign up through the web app. New Year’s only don’t miss out on the chance to start the new year with confidence. There are features like automatic subscription tracking, so you’ll never miss upcoming charges again. Copilot money’s privacy first approach ensures that your data is secure and their team is dedicated to helping you stress less [00:26:00] about money. So whether you’re a finance pro or just starting out, copilot money is there to help you make better decisions. Visit, try dot copilot money slash Overtired and use the code Overtired to sign up for your one month free trial and embrace financial clarity. That’s try.copilot.money/ Overtired. Use the coupon Overtired. And again, that is 26% off for your first year. So thank you copilot money for, uh, sponsoring this week’s, uh, uh, episode. Oh, one other note about copilot money. They were, um, an apple, uh, design award finalist. So it’s a really well designed app and, um, we love to see, um, apps like this available on, on the web as well as iOS and, and MAC os. Brett: I have started using it very much because of the web version, and it is, it is really good. Christina: yeah, yeah. No, yeah. For, yeah, for me, that is like a, an actual like. Concrete requirement. Exploring Rocket Money and Web Interfaces Christina: Any money Brett: Like I’ve, I’ve [00:27:00] paid, I have about eight months left. I paid for a year of, of Rocket Money or whatever it’s called now. Um, and I’ve always loved that app, but yeah, it does not have a web interface. And once I started trying copilot out, I realized how much I really did want a web interface for that stuff, you know? What else have you seen? Discovering Umami Analytics Brett: Umami the analytics platform. Christina: Yes. Brett: It is so good. And it’s, it’s open source and you can self-host. And it is like, I, I’ve been using Fathom Analytics for a long time and I like Fathom, but Umami is, it has like all of the, uh, advanced stuff you would get with Google Analytics, but with like way more privacy focus and you’re not giving information to Google for one. Um, and the interface is beautiful. I love that. It’s so good. Christina: Yeah. Um, umami is really good. I think, uh, there’s another one, I’m [00:28:00] trying to think of what it was called. There are a number of these various, um, analytics, uh, hosted things, but no, umami is definitely a really good one. Nostalgia for Mint and Fever Christina: And I like, um, it reminds me, um, it was, what was it? It was Mint. It was Mint, Sean Edmond’s Mint. Which Brett: I was just gonna ask you if you remembered that. Christina: yeah, which was, which was one of the, uh, plausible analytics. It’s another one too. Um, which is also like, um, they, they have a hosted version, but you can also self-host. Um, and then that’s also a, a, a, another, uh, good one. But yeah. Um, was like my, my all time favorites, uh, you know, app. I, I, I loved that. Brett: Um, what was his RSS one? Uh, fever? Fever. Christina: was, was the best fever, was the best. The Decline of RSS and Google Reader Christina: And it was funny, like I, I think I’ve talked about this before, I was more insulated and like less upset than some people by the, the Google reader death because I had a, a, I’d been using Fever for so long, and then obviously, you know, stuff being updated and doesn’t really work [00:29:00] super well with like, the latest versions of PHP and things like that. But, you know, a lot of people were really, understandably and, and still more than a decade on, you know, very upset by the death of, um, Google reader. But I think because I, I had paid for and used, you know, my own, um, self-hosted fever installation, and then there were apps that people used for, you know, APIs and whatnot to build, you know, Macs or iOS apps or, or whatever. Like, I, I was obviously upset about Google Reader being shut down, but I was like, okay, you know, I, I can just, you know, move on to something else. And, um, and I’ve used, uh, feeder, um, not, not, not feeder, um, Brett: Reader Christina: is. No, no. Maybe, uh, it’s, uh, not Feed Demon. Um, that was like the OG one. Um, it’ll come to me, um, because I, I, yes. Thank you. Feed Ben. Thank you, thank you. One of the ones that’s still around, uh, from like the, of the, you know, various Google reader alternatives, like many of them. You know, closed up shop.[00:30:00] Brett: Yeah. Christina: if they kind of realized, you know, by Google reader, like this is the, unfortunately a niche market. Um, now that didn’t help the fact that like, you know, when people, when web browsers Safari, I think started at first and then Firefox did, and then, you know, uh, Chrome was, was fairly early too. Like when all the web browsers took away like RSS buttons to make it easy to subscribe to feeds or to auto discover feeds, and you had to like install like a, an extension or whatever to do that. Like, that all helped with the, the demise of RSS in a lot of ways. And of course, people moving everything into closed platforms and, and social networks and stuff that, you Brett: In, in the tech world though. So I have, my blog gets about 20,000 visits a week, but it gets 30,000 RSS downloads, like, uh, like daily, 30,000 readers are, are, are pulling my site. Um, so RSS is far from dead in the tech world. Christina: Right. Well, [00:31:00] well, I think, I think in a certain demographic, right? I think if you were to ask like a new, like college grads, I don’t think that any of them are using RSS at least not actively, right? Like, I mean, you might have a few, but like it’s, it’s just not gonna be like a thing where they’re gonna be, act like they might be using some apps that do similar types of things and might even pull in feed sources maybe. But it, it’s, it’s just not like a, like when, when I was graduating from college or in college, like everybody had, you know, RSS clients and that was just kind of a, a known thing. Brett: Yeah. So speaking of traffic, um, I don’t, did I mention that I got delisted on Bing and Christina: You did, Brett: I am, I’m back Christina: figure that out? You’re back now. Okay. Brett: I’m back now. Switching to Kagi Search Engine Brett: And, um, I have switched to using Kaji, um, as my primary search engine and they replicate all of duck duck go’s bang searches. Christina: Yes. Brett: So I Christina: one of the things I love about them. [00:32:00] Yes. Brett: I was pleased to see there’s a Bang Turp search on Kaji. Um, I actually use Christina: or is it kgi? Because I think I’ve always called it kgi. Yeah, it’s KA, it’s K, it’s KAGI. For anybody who’s who’s, uh, I don’t know how to, how, how, if it’s kgi, kgi, um, uh, you know, Kaji, whatever, Brett: It’ll be in the show notes. What the fuck ever, we’ll just call it KGI. Um, and yeah, so like I was super happy ’cause I used the Bang Turp to search my own site. I just got used to doing that. The Rise of AI-Generated Content Brett: Um, and, but it is like you can, the reason I switched to said web, uh, search engine is um, because you can report sites that are just AI slop and they will verify those reports and remove or flag slop sites in your search results. ’cause I was getting sick, even with DuckDuckGo, like five out [00:33:00] of 10 results were always, I’d get in, I’d get there, I’d get one, maybe two paragraphs into, uh, an article and realize, oh, someone just typed in my search term into chat GPT and then Christina: Oh yeah. Brett: automated it. Christina: Oh, I was gonna say there, there it is. Automated at this point. And, and like, to be clear, like a lot of search results, even before like the rise of like genre of AI were a variant of this, where you would see like people like buying older domain names that expired. Well, yeah, but even before that happened mean that, that obviously when, when, when the Christina Warren and Brett Terpstra and then they, they changed your name. Um, I Brett: know, like Jason Turra or Christina: Or something like that. Yeah, it was, it was, it was, it was weird. Um, I mean, you know, um, does that site, did, did have they given up the ghost on that? I’m curious. Um, yeah. Wow. Okay. They are still, well, no, they haven’t published anything since November 30th. So something has happened where they, uh, are [00:34:00] they, they’re definitely cutting down on, on various things. Um, oh no. Paul Terpstra. Oh my God. Paul Terpstra. You are still, Brett: Yeah. Christina: you were like the one author there that I see on this website. Um, now what was, what was messed up about, about this? Um, although no. Okay. Their homepage, the last one they say is like, OCT is like, uh, November, um, uh, 30th. But if you click on the, the Paul trips to handle, then like you see, um, December 22nd, uh, which is, which is today as we’re recording this, Brett: Wow, I didn’t even realize. Christina: Yeah. So, alright. So that is still, somehow that grift is still going on. But yeah, I mean, even before the rise of those things, you would see, you know, sites that would either buy up dead domains and then like, have like very similar looking content, but slightly different maybe, you know, like, uh, you know, injected with a bunch of, you know. Links or whatever, or you would see people who would, you know, do very clearly SEO written and, and probably, you know, [00:35:00] like, again, pre generative ai, but, you know, assisted slop content. But yeah, now it’s, it’s just, it’s crazy. Like, and it doesn’t help that, like the AI summaries, which can be useful, but, um, and they’re getting better, which is good only because they’re so prominent. Like, I’m not a fan of them. But if you’re not using an alternative search engine, like, you know, you see these AI summaries and like if they’re bad and sometimes they are then. Brett: Often Christina: You know, well, they’re, they’ve gotten better, uh, is the only thing I would say. I, I still wouldn’t rely on them, but I’ve, I’ve noticed a, like, I’ve noticed a, a genuine, like uptick in like, improvements and in like, how awful they are probably in like the last six weeks, which is damning with faint praise. I’m not at all saying it’s good. I am simply saying, it’s like, I’m primarily thinking for like, people who are like, like less tech savvy relatives who are going to just go to, you know, bing.com or, or google.com and then see those sorts of things. Right. Um, and, uh, you know, we’re not gonna be able to convince them to go to a, a, a third [00:36:00] party search engine. Um, although, you know, some people, like, I think my mom was using Duck to Go for a while as like her default on her iPhone, um, which I was, I was like proud of her about, but I was also kind of like, uh, that’s got its own issues. But no, I, I like ka a lot. Um, I, I’ve Brett: Well, and it’s so keyboard driven, like DuckDuckGo has good keyboard shortcuts. KAGY slash Kaji has even better keyboard shortcuts. Like you can navigate and control everything with, uh, like Gmail style, single key keyboard shortcuts, which I really like. Christina: Yeah. Yeah, I like that too. And then they, they, of course, they make like a, a web kit, um, like a browser, um, that, that has, they’ve back ported, um, you know, a lot of chrome extensions too. I personally don’t see the point in that. Um, I, I think that if you’re going to be like that committed to, like, using like the, you know, the web extension format and like using like more popular extensions, you might as well [00:37:00] just use a Chrome fork if you don’t wanna use Chrome, which is fine, but like, you could use a browser like Helium, which, which we talked about last show, which has, um, the, the, the hash bangs kind of integrated in, or you could use, you know, if you wanted to use, um, um, you know, the, the, the, the Brett: o is Orion, is Orion the one you’re talking about that? Yeah. Christina: that, that, yeah, that, that, that, that, that, that’s Katy’s thing. And that was actually originally how I heard about them was because it was like, oh, this is interesting. Um, you know, this is a kind of an interesting, you know, kind of alternative browser. And then it turned out that that was just kind of a, in some ways, kind of a front to promote the, the search engine, which is the real, you know, thing. Um, which is fine, right? I mean, that, that was Google’s model. Um, Brett: Well, and we should mention for anyone who hasn’t tried it, it is a paid service. Um, and you are getting search results with no ads and, and spam, uh, ai, slot protection and all of the benefits you would expect from a paid service. So [00:38:00] I think, like for me, five bucks a month gets me, I think 300 searches, which is. Plenty for me, like, I guess I, I’m still waiting to see, I’ve never counted how many searches I do a month, Christina: Yeah, Brett: you know, like three searches a day, uh, would come out to like 90 searches a month and I have 300 available, so I think I’ll be fine. Christina: yeah, yeah. I mean, yeah, basically being able to get to do 10 a day, which in most cases is fine. What I’ve done is I’m on, like, they have a, a, a family plan, um, and they don’t care. They even, I think in their documentation, or at least they did, they do not care if you are like actually in a family with the people that you are on or not. So if you, you know, find some folks that you wanna kind of sync up with, you can like, you know, be on a family plan together and you can save money, um, on, uh, whatever their, uh, um, their pricing [00:39:00] stuff is. So, um, so me, me and Justin Williams are, uh, in a, uh, Brett: Justin Williams, I haven’t heard that name in forever. Christina: Yeah. Yeah. We went to C Oasis together. We went both nights in Los Angeles, um, in August. Yeah. Um, or September rather. Um, yeah, so, okay, so this is how this works. They have, their starter plan is, is $5 a month, which includes, and they do have an AI assistant too. So it was funny, they had the AI slot protection, but they also have like an AI assistant that you can use and like an AI summarizer and whatnot. Um, that’s $5 a month. And then there’s the professional plan, which is, so that’s for 300 searches a month for the standard AI for starter $5 a month. The professional plan is unlimited searches and standard ai, that’s $10 a month. And then the ultimate is, um. Uh, everything in professional plus you get like premium model access, which, okay, but the family plan, um, is, is the, so you can do one of two things. You have a duo [00:40:00] plan, which is two professional accounts for a couple, which is $14 a month plus sales tax. So it’s, uh, you know, average of $7 per person, which I think is what Justin and I are on. And then there’s a family plan with up to six family members. And again, they don’t care if you are actually in a family or not, and that’s $20 a month. So the real thing to do if you’re wanting to like, you know, save on this is like find five friends, Brett: Yeah. Christina: get on the $20 a month, you know, family plan thing. Spread the, spread the cost, and that way you can get the, you know, professional plan for, for, for less. But to your Brett: All right. Christina: most people, it’s probably $300, 300 searches a month is probably plenty. And if you search a lot like we do, I, I think it is worth paying for. Brett: yeah, yeah. All right. TV Shows: Is TV Just Okay Now? Christina: anyway, but we wanted to talk about tv, so let’s Brett: Well do, we’re, we’re at 50 minutes already, so I think we need to choose whether we do TV or gratitude. What Christina: do you have a [00:41:00] gude, like a good one? Brett: I, I, no, I have a, I have a throwaway one. Christina: Okay. Brett: I, it was one of those, like, I looked at my doc and I was like, oh, I don’t think I’ve talked about that even though I probably have, um, yeah, let’s just talk about tv. So I, I have been noting, and my question in the show notes was, is TV just okay now? Because I’ve been watching, I watched Stranger Things, pluribus Down, cemetery Road, platonic, and all of it was, it was entertaining, but it wasn’t like, must watch tv. None of it was like, none of it was as good as like Modern Family. Modern Family was fucking good. Tv, like family friendly and just like I’ve, I’ve been through that series so many times and it’s always fun and it’s always better than like pluribus. I like the, I like the concept kind of, it’s not. not all that, um, engaging, I guess.[00:42:00] Christina: I like it. But, Brett: Yeah. I don’t hate it like I do, I do like it, but it’s not like, I don’t, I don’t count the days until the next episode comes out and I miss, I miss things being really good. So you had a couple responses to that though. Christina: Well, I mean, I tend to agree with you. So first of all, there, I put in the, in the show notes, um, there’s a link to a thing that, uh, that James and Pozak wrote for the, the New York Times, uh, God a year and a half ago now called, um, the Comfortable Problem of Mid tv. And he said it, it, it’s got a great cast, it looks cinematic, it’s, um, fine and is everywhere. And kind of talking about like, you know, we went from like the era of like peak TV to now being, um. You know what, what he’s dubbed like mid tv and I think that there’s, there’s some truth to that. Um, and, and, and he even says at the beginning, let me say up front, this is not an essay about how bad TV is today, just the opposite. There’s, um, little truly bad high profile television made anymore, um, is it’s more talking about, um, like [00:43:00] what we have instead Today is something less awful, but in a way more sad, the willingness to retreat, to settle to trade, the ambitious for the defendable. And I think that there’s some truth to that. Um, I think that we see this movies now too, and with movies it’s actually much more of a problem. Like there’s some really high highs. Um, but because the movie industry is in such a bad place, um, it, it’s that much more notable when like, you don’t have like a big strong slate of, of things. And so, you know, it, it, it’s more of a problem. TV for, for better or worse, has become the dominant entertainment form. And yeah, I think that it, it, it’s fine. Uh, but there are very few things that I’m like, oh, wow, yeah, that, that’s like, you know, the wire. Um, not that anything is, but you know what I mean? But is, but even like, you know, pluribus, which I really like. I actually think that’s, um, my, my favorite show of, of, um, 2025, um, at least new show. Um, well, maybe the studio. The studio. I might have, I, I, I might put, Brett: That was pretty Christina: above that. But, but, but, but [00:44:00] like, it’s one of those things where I’m like, okay, you know, um, it’s not breaking bad, right? Like, if we’re gonna be comparing Vince Gilligan shows, and maybe that’s unfair, but, you know, it just, but, but still, like, you know, you’re gonna be compared to your last hit. And, and, and, and that is what it is. Um, I will say though, like, I haven’t watched Stranger Things in years, and I don’t, I don’t, I don’t think I can force myself to like, care about that again, but I’ve heard kind of mixed Brett: That’s where L is too, L doesn’t care. And, and then there’s the whole like two cast members being Zionists kind of turned a whole bunch of people off and Christina: Well, and well, David Harbor, David Harbor’s whole Lily Allen thing. Are you, are you, are you familiar with this floor at all? Brett: No. Christina: Okay. You know who Lily Allen is? Brett: Yes. Christina: Okay. So she and David Harbor were married and, um, she wrote an album called, uh, uh, west End Girl that, that came out, uh, like in November, which is actually a really good album, [00:45:00] which is like White Girl Lemonade, where she just basically reads him to filth for being an absolute piece of shit. Like, apparently like, you know, they were together, they were married or whatever. She goes off to London to perform in a play and he’s like. Oh, we’re gonna be away for months. I, I wanna sleep with other people. And so they kind of like, she kind of accepts getting into an open relationship with him, even though she didn’t really want to be, which look that her, that’s her bad, whatever. But then he proceeds to like, do things that was not what they’d agreed upon on, upon the parameters of their, of their relationship. And then she’s just like brutally honest about the entire thing. And so as you’re listening to this album, you’re just learning more and more about like, David Harbor’s like sex life and, um, and stuff. And, and like, it’s just on blast. It’s incredible. Um, but, uh, yeah, so there’s, there’s some of that stuff. There’s, I, I don’t know, like I don’t, I don’t really follow the rest of the cast stuff except that, uh, the girl who plays, um, 11 like. Frequently want to smack because just the most annoying [00:46:00] celebrity in on the planet. But like, putting that aside, um, I just, I stopped caring. It took them too long between seasons and the, and, and, and the budget for that show was also so insane. I’m like, you, you cost more than strain than thinking of Thrones. Game of Thrones is, was even at its worst, was a better show than Stranger Things. So like it, yeah. But but that goes to your point. Like, it’s like, it’s okay. Brett: Yeah. Yeah, Christina: Um, I will say the new season of Fallout just, um, premiered and so far I I’m still really enjoying that. Um, Brett: yet to see it. Christina: you should, you should definitely watch the Brett: What is it on? Christina: uh, Amazon Brett: Okay. Christina: and, uh, and it’s, and it’s really, really good. Um. And this year they are doing the episodic, um, not episodic, the weekly drop, right. Rather than the binge thing. So the first season, uh, they dropped it all at once and um, and I was a little bit worried. I was like, fuck, does that mean they don’t [00:47:00] believe in this? What are they going to do? Wound up being like Amazon’s biggest hit after their Lord of the Rings, um, you know, thing. And so it was immediately kind of picked up for a second season and it was picked up for a third season before the second season even, uh, premiered. Um, and uh, and that might be the final one. Um, they’re saying, but, but, but, but who knows? But, but so far anyway, like they’ve only, there’s only been one episode, but it’s, it’s been good so far. The Cultural Phenomenon of Heated Rivalry Christina: Um, but, but what I was gonna talk to you about is the gay hockey show. Brett: Which is. Christina: It’s called Heated rivalry. It’s on HBO Max. It was originally just supposed to be on, uh, a Canadian streamer called Crave. And um, then at the, like, the, the like 11th hour, HBO Max picked it up and was like, okay, we’ll play this in, um, some of our territories and other things. And I wanna be very clear, this is not high art at all. This is like, no way. Like this actually in some ways it, it personifies [00:48:00] the TV is just okay now thing, but in other ways it’s actually a little bit more interesting just because the cultural phenomenon that has happened around it in like the last, like, like it hasn’t even been out a month and it’s only six episodes, although they are also going to be getting a second season. Um, it’s sort of wild how, like I went from, I’d seen a trailer for it and I was like, okay, whatever. And like it came out, I think like right after Thanksgiving. Then like within like two or three weeks, like literally I wasn’t following anything around it, but my Instagram, my TikTok, Twitter, everything that I was seeing was just all about the discourse around the show. And it’s like a bunch of us all seem to have to have discovered it. Like one weekend where we were like, okay, we’re gonna actually sit down and watch the gay hockey show. Um, and this is exactly what it is. It is a gay hockey show. So it is based on, there was a series of books that this, uh, female, uh, writer Rachel Reed wrote, um, uh, about like, uh, I think like they were like eBooks, types of thing. Um, uh, I think although there, there is now I [00:49:00] think like a, a hard cover release because they’ve been so popular and they’re just, it’s just ero, it’s just smut, right? It’s basically fanfic dressed up in something else. And the idea was like, okay, you have like these, you know, male like hockey players who are closeted and kind of have like this, this romance that, that starts from like 2008, um, through like, I dunno, like, like 2017 or 2018. And there are a number of different. Books or stories in the universe. But the one that people liked the most was the, the second book, which is called Heed Rivalry. You don’t really need to know any about that. The big thing about the show is that it is essentially like soft core gay porn. Um, but yet it’s like weirdly compelling in a way. Like, it, it is very, like, there’s, there’s some sweet aspects to it. Like you were before the, the show, you were saying, oh, it’s kinda like Heart Stopper could not be further from Heart Stopper. ’cause Heart Stopper is very sweet and twee and kind of like loving and like whatnot. This is like. You know, like guys in their twenties with amazing asses, [00:50:00] you know, like doing things to one another kind of an in secret. And, and the, the thing is, there’s not a whole lot of plot. Like the plot is the porn. Because, because the whole thing is, is that like they don’t spend, they don’t have a time to spend a lot of time together because they’re, they’re closeted and their rivals. Oh, that’s the whole conceit. It’s like they’re these two great hockey players and they, they, they, um, you know, um, play for opposing teams and they’re like, each other’s biggest rivals, but like, they’re, they’re fucking, um, and uh, it, it’s, uh, again, it’s not high art at all, but Brett: the target audience for this? Christina: And here’s the interesting thing. So the books are almost entirely read by women, um, and which, which makes sense. There’s, there’s a lot of like, you know, like, male, male, like, um, like the history of slash fiction goes back to like, like Fanfic in general, like goes back to like women writing, like Spock and, and, uh, um, what’s the space together? Kirk Together. Yeah. Um, and so the books are almost entirely, uh, consumed by, by women and probably straight women, although probably some queer women too. Um, but the [00:51:00] show seems to be a mix of gay men, straight women, all, although I’ve seen a lot of lesbians. As well. Um, yeah, yeah, because again, like the discourse is just kind of ridiculous and, and the memes are fun. Um, the guy who created it, he’s gay or created the, the, the television adaptation. He’s gay and, uh, I think he’s done a, a, a pretty good job with it. The, the leads are the thing that’s like incredible, like the, especially the guy who plays the, the Russian character, Ilya, uh, that actor is really, really good and he’s Texan, and yet he does like a great Russian accent and, um. And, and he’s very attractive. And like I, I, I can see like why a lot of people are into it, but it’s funny ’cause like New York Magazine, like they weren’t even covering the show, which, why would you, it was like some Canadian kind of, you know, you know, thing that barely gets picked by HBO. Then it takes off and now like they’re covering it. The, the last time I remember New York Magazine covering a show like this, like Vociferously was Gossip Girl, like 18 years ago. Um, [00:52:00] and it kind of reminds me of that, where like everybody woke up one day when they’re like, oh, this is like a cultural moment now. So again, not good television, probably not gonna necessarily be for everyone, but, but it’s a moment. And like, I kept seeing edits, I kept seeing Mo, I kept seeing edits on TikTok and stuff and I was like, okay, do I have to watch the gay hockey show? All right, I have to watch the gay hockey show so that it’s, we might be at the point where like TV is just okay, but at least there are some good like moments about, whereas the culture, we can all like agree. Okay, we’re all gonna be talking about this one thing. Brett: That sounds like what I’ll be doing on Christmas Day. Christina: Oh my God. Actually that would be a great thing to watch on Christmas. And I think that the final episode is gonna come out like the day after Christmas, so there you go. Brett: Done Deal. Cool. Wrapping Up and Holiday Wishes Brett: All right, well thanks for, we’re recording this the same morning. The show’s supposed to come out, so I gotta do some editing, but uh, but [00:53:00] thanks for showing up while you’re in Atlanta and yeah, this has been a classic, a fun classic Overtired. Christina: absolutely. Well, um, get some sleep, uh, take care of yourself. Um, happy holidays. Um, uh, hope that a, a Christmas isn’t too weird for you. And, um, and happy New Year. Brett: you too. Get some sleep.

In this episode, Stewart Alsop sits down with Joe Wilkinson of Artisan Growth Strategies to talk through how vibe coding is changing who gets to build software, why functional programming and immutability may be better suited for AI-written code, and how tools like LLMs are reshaping learning, work, and curiosity itself. The conversation ranges from Joe's experience living in China and his perspective on Chinese AI labs like DeepSeek, Kimi, Minimax, and GLM, to mesh networks, Raspberry Pi–powered infrastructure, decentralization, and what sovereignty might mean in a world where intelligence is increasingly distributed. They also explore hallucinations, AlphaGo's Move 37, and why creative “wrongness” may be essential for real breakthroughs, along with the tension between centralized power and open access to advanced technology. You can find more about Joe's work at https://artisangrowthstrategies.com and follow him on X at https://x.com/artisangrowth.Check out this GPT we trained on the conversationTimestamps00:00 – Vibe coding as a new learning unlock, China experience, information overload, and AI-powered ingestion systems05:00 – Learning to code late, Exercism, syntax friction, AI as a real-time coding partner10:00 – Functional programming, Elixir, immutability, and why AI struggles with mutable state15:00 – Coding metaphors, “spooky action at a distance,” and making software AI-readable20:00 – Raspberry Pi, personal servers, mesh networks, and peer-to-peer infrastructure25:00 – Curiosity as activation energy, tech literacy gaps, and AI-enabled problem solving30:00 – Knowledge work superpowers, decentralization, and small groups reshaping systems35:00 – Open source vs open weights, Chinese AI labs, data ingestion, and competitive dynamics40:00 – Power, safety, and why broad access to AI beats centralized control45:00 – Hallucinations, AlphaGo's Move 37, creativity, and logical consistency in AI50:00 – Provenance, epistemology, ontologies, and risks of closed-loop science55:00 – Centralization vs decentralization, sovereign countries, and post-global-order shifts01:00:00 – U.S.–China dynamics, war skepticism, pragmatism, and cautious optimism about the futureKey InsightsVibe coding fundamentally lowers the barrier to entry for technical creation by shifting the focus from syntax mastery to intent, structure, and iteration. Instead of learning code the traditional way and hitting constant friction, AI lets people learn by doing, correcting mistakes in real time, and gradually building mental models of how systems work, which changes who gets to participate in software creation.Functional programming and immutability may be better aligned with AI-written code than object-oriented paradigms because they reduce hidden state and unintended side effects. By making data flows explicit and preventing “spooky action at a distance,” immutable systems are easier for both humans and AI to reason about, debug, and extend, especially as code becomes increasingly machine-authored.AI is compressing the entire learning stack, from software to physical reality, enabling people to move fluidly between abstract knowledge and hands-on problem solving. Whether fixing hardware, setting up servers, or understanding networks, the combination of curiosity and AI assistance turns complex systems into navigable terrain rather than expert-only domains.Decentralized infrastructure like mesh networks and personal servers becomes viable when cognitive overhead drops. What once required extreme dedication or specialist knowledge can now be done by small groups, meaning that relatively few motivated individuals can meaningfully change communication, resilience, and local autonomy without waiting for institutions to act.Chinese AI labs are likely underestimated because they operate with different constraints, incentives, and cultural inputs. Their openness to alternative training methods, massive data ingestion, and open-weight strategies creates competitive pressure that limits monopolistic control by Western labs and gives users real leverage through choice.Hallucinations and “mistakes” are not purely failures but potential sources of creative breakthroughs, similar to AlphaGo's Move 37. If AI systems are overly constrained to consensus truth or authority-approved outputs, they risk losing the capacity for novel insight, suggesting that future progress depends on balancing correctness with exploratory freedom.The next phase of decentralization may begin with sovereign countries before sovereign individuals, as AI enables smaller nations to reason from first principles in areas like medicine, regulation, and science. Rather than a collapse into chaos, this points toward a more pluralistic world where power, knowledge, and decision-making are distributed across many competing systems instead of centralized authorities.

Sander Schulhoff is an AI researcher specializing in AI security, prompt injection, and red teaming. He wrote the first comprehensive guide on prompt engineering and ran the first-ever prompt injection competition, working with top AI labs and companies. His dataset is now used by Fortune 500 companies to benchmark their AI systems security, he's spent more time than anyone alive studying how attackers break AI systems, and what he's found isn't reassuring: the guardrails companies are buying don't actually work, and we've been lucky we haven't seen more harm so far, only because AI agents aren't capable enough yet to do real damage.We discuss:1. The difference between jailbreaking and prompt injection attacks on AI systems2. Why AI guardrails don't work3. Why we haven't seen major AI security incidents yet (but soon will)4. Why AI browser agents are vulnerable to hidden attacks embedded in webpages5. The practical steps organizations should take instead of buying ineffective security tools6. Why solving this requires merging classical cybersecurity expertise with AI knowledge—Brought to you by:Datadog—Now home to Eppo, the leading experimentation and feature flagging platform: https://www.datadoghq.com/lennyMetronome—Monetization infrastructure for modern software companies: https://metronome.com/GoFundMe Giving Funds—Make year-end giving easy: http://gofundme.com/lenny—Transcript: https://www.lennysnewsletter.com/p/the-coming-ai-security-crisis—My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/181089452/my-biggest-takeaways-from-this-conversation—Where to find Sander Schulhoff:• X: https://x.com/sanderschulhoff• LinkedIn: https://www.linkedin.com/in/sander-schulhoff• Website: https://sanderschulhoff.com• AI Red Teaming and AI Security Masterclass on Maven: https://bit.ly/44lLSbC—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Sander Schulhoff and AI security(05:14) Understanding AI vulnerabilities(11:42) Real-world examples of AI security breaches(17:55) The impact of intelligent agents(19:44) The rise of AI security solutions(21:09) Red teaming and guardrails(23:44) Adversarial robustness(27:52) Why guardrails fail(38:22) The lack of resources addressing this problem(44:44) Practical advice for addressing AI security(55:49) Why you shouldn't spend your time on guardrails(59:06) Prompt injection and agentic systems(01:09:15) Education and awareness in AI security(01:11:47) Challenges and future directions in AI security(01:17:52) Companies that are doing this well(01:21:57) Final thoughts and recommendations—Referenced:• AI prompt engineering in 2025: What works and what doesn't | Sander Schulhoff (Learn Prompting, HackAPrompt): https://www.lennysnewsletter.com/p/ai-prompt-engineering-in-2025-sander-schulhoff• The AI Security Industry is Bullshit: https://sanderschulhoff.substack.com/p/the-ai-security-industry-is-bullshit• The Prompt Report: Insights from the Most Comprehensive Study of Prompting Ever Done: https://learnprompting.org/blog/the_prompt_report?srsltid=AfmBOoo7CRNNCtavzhyLbCMxc0LDmkSUakJ4P8XBaITbE6GXL1i2SvA0• OpenAI: https://openai.com• Scale: https://scale.com• Hugging Face: https://huggingface.co• Ignore This Title and HackAPrompt: Exposing Systemic Vulnerabilities of LLMs through a Global Scale Prompt Hacking Competition: https://www.semanticscholar.org/paper/Ignore-This-Title-and-HackAPrompt%3A-Exposing-of-LLMs-Schulhoff-Pinto/f3de6ea08e2464190673c0ec8f78e5ec1cd08642• Simon Willison's Weblog: https://simonwillison.net• ServiceNow: https://www.servicenow.com• ServiceNow AI Agents Can Be Tricked Into Acting Against Each Other via Second-Order Prompts: https://thehackernews.com/2025/11/servicenow-ai-agents-can-be-tricked.html• Alex Komoroske on X: https://x.com/komorama• Twitter pranksters derail GPT-3 bot with newly discovered “prompt injection” hack: https://arstechnica.com/information-technology/2022/09/twitter-pranksters-derail-gpt-3-bot-with-newly-discovered-prompt-injection-hack• MathGPT: https://math-gpt.org• 2025 Las Vegas Cybertruck explosion: https://en.wikipedia.org/wiki/2025_Las_Vegas_Cybertruck_explosion• Disrupting the first reported AI-orchestrated cyber espionage campaign: https://www.anthropic.com/news/disrupting-AI-espionage• Thinking like a gardener not a builder, organizing teams like slime mold, the adjacent possible, and other unconventional product advice | Alex Komoroske (Stripe, Google): https://www.lennysnewsletter.com/p/unconventional-product-advice-alex-komoroske• Prompt Optimization and Evaluation for LLM Automated Red Teaming: https://arxiv.org/abs/2507.22133• MATS Research: https://substack.com/@matsresearch• CBRN: https://en.wikipedia.org/wiki/CBRN_defense• CaMeL offers a promising new direction for mitigating prompt injection attacks: https://simonwillison.net/2025/Apr/11/camel• Trustible: https://trustible.ai• Repello: https://repello.ai• Do not write that jailbreak paper: https://javirando.com/blog/2024/jailbreaks—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

ChatGPT Images (aka OpenAI's Image 1.5) can create stunning AI images, text and more. But how does it compare to Google's Nanobanana Pro? We dive in… way too deep. Plus, new GPT-5.2 Codex, Gemini 3 Flash, YouTube's new vibecoded games, the controversy around Generative AI and game developer Larian Studios, a lego-like robot and, of course, seeing how AI video can cause soap opera actress hair to endlessly grow. IT'S YET ANOTHER WEEK OF NEW RELEASES! AND WE DON'T STOP. Get notified when AndThen launches: https://andthen.chat/ Come to our Discord to try our Secret Project: https://discord.gg/muD2TYgC8f Join our Patreon: https://www.patreon.com/AIForHumansShow AI For Humans Newsletter: https://aiforhumans.beehiiv.com/ Follow us for more on X @AIForHumansShow Join our TikTok @aiforhumansshow To book us for speaking, please visit our website: https://www.aiforhumans.show/   // Show Links // ChatGPT Image 1.5 is here https://openai.com/index/new-chatgpt-images-is-here/ Recreating the post from the OpenAI blog with us https://chatgpt.com/share/69443100-6e7c-8003-910e-749bab75f6e2 Fabian (from GLIF) Notes on Images 1.5 https://x.com/fabianstelzer/status/2001300766368178435?s=20 Jeff Goldblum's Resume https://x.com/gavinpurcell/status/2001033377294467182?s=20 Upcoming QWEN Image Layering https://x.com/wildmindai/status/2001593677576384747?s=20 Image 1.5 Vs Nanobanana Pro Video Game Characters https://www.reddit.com/r/ChatGPT/comments/1ppg4s9/test_2_turning_game_characters_into_real_people/ Fingers https://x.com/petergostev/status/2001027573636088184?s=20 Gavin's Original Knight and Rotisserie Chicken Post https://www.reddit.com/r/ChatGPT/comments/1jk0p3v/tried_to_push_the_new_image_model_with_an/ OpenAI's Greg Brockman: WE NEED THE COMPUTE https://x.com/OpenAI/status/2001336514786017417?s=20 GPT-5.2 CODEX https://openai.com/index/introducing-gpt-5-2-codex/ Frontier Science: New Benchmark https://x.com/OpenAI/status/2000975293448905038?s=20 ChatGPT Apps Store Opens For Developer Submission https://x.com/OpenAIDevs/status/2001419749016899868?s=20 Gemini 3 Flash https://x.com/GoogleDeepMind/status/2001321759702663544?s=20 Nanobanana now in community posts on YT https://x.com/nealmohan/status/2001425749941829920?s=20 Meanwhile, YouTube "Playable Builders" https://x.com/YouTubeGaming/status/2000989303086649637?s= Larian's AI Gaming "Controversy" https://www.pcgamer.com/games/rpg/baldurs-gate-3-developer-larian-defends-itself-as-fans-react-to-generative-ai-use-im-not-entirely-sure-we-are-the-ideal-target-for-the-level-of-scorn/ Direct response from Larian Head of Studios: https://x.com/LarAtLarian/status/2001011042642505833?s=20 MSFT Open-Source Image-to-3D Trellis 2 https://x.com/_akhaliq/status/2001041559366598799?s=20 Bernie's Moratorium on Data Centers https://youtu.be/f40SFNcTOXo?si=hduNjATJgtIya9oq Meanwhile… China can now produce high-end AI Chips https://finance.yahoo.com/news/exclusive-china-built-manhattan-project-141758929.html Meta SAM Audio https://x.com/AIatMeta/status/2000980784425931067?s=20 Tron 2: Lego Robot https://x.com/CyberRobooo/status/2001513866157789308?s=20 AVP Spatial Photos Of Newborn https://x.com/SadlyItsBradley/status/2001276039671197783?s=20 WAN 2.1 Workflow Re-creates The Matrix With Homer Simpson https://x.com/ChetiArt/status/2001291373182382526?s=20 Miss Piggy in Melania Trailer https://x.com/charliebcurran/status/2001564626144928146?s=20 One Woman's Transformation Via Sora Remixes https://sora.chatgpt.com/p/s_693a2ed29e288191a542b776553e1145?psh=HXVzZXItT3diZ1NFOUtyZlRXV2ZvajcwWjJsZ2Uy.XXZmIQEXNl-L

Did AI end up being a political force this year?

In this week's episode of the Rich Habits Podcast, Robert Croak and Austin Hankwitz answer your questions!---

We were inundated with new Windows features in 2025, but which ones actually moved the needle? Fortnite isn't just back on iPhone and Android, it's available on Windows 11 on Arm, and it works great! Plus, 2 big mobile wins for Epic Games and some thoughts on the "right" way to roll out AI features.Windows 11 Best Windows 11 updates of 2025, in no particular order... Dark mode improvements to File Explorer Widgets major overhaul with separate widgets and Discovery feed Xbox Full Screen experience - especially good on handhelds, of course, but also any PC you use for gaming with a controller Click to Do (Copilot+ PC only) External fingerprint reader support for Windows Hello ESS -External/USB webcams supported by Windows Studio Effects (Copilot+ PC only) Quick Machine Recovery is the tip of a wave of new foundational features like Admin Protection, Smart App Control (updates), and more that go beyond surface-level look and feel Redesigned Start menu isn't perfect but it's a nice improvement Copilot Vision, though this type of thing may make more sense on phones AI features in Paint, Photos, Notepad, and Snipping Tool Natural language interactions like the agent in Settings, file search, and more (mostly Copilot+ PC only, but you can do this in Copilot as well) Bluetooth LE support for improved audio quality in game chat, voice calls Gaming on Windows 11 on Arm and Snapdragon X: Major steps forward, but the same issue as always Looking ahead to 2026: 26H1, Agentic features that work, potential Windows 12, and AI PCs AI An extensive new interview with Mustafa Suleyman confirms why this guy is special and how confusing it is that Copilot is so disrespected Microsoft Copilot is auto-installing on LG smart TVs and there's no way to remove it GPT-5.2 is OpenAI's answer to Gemini 3 ChatGPT Images is OpenAI's answer to Nano Banana Pro Disney invests $1 billion OpenAI, sues Google Opera Neon is now generally available for $20 per month AI is moving quick as we all know but the bigger issue may be the incessant marketing about features like agents that don't even work now Microsoft is getting pushback on forced Copilot usage, price hikes Google is expanding its use of "experiments" outside of mainstream products with things like NotebookLM, Mixboard, CC, and much more. Maybe this is the better approach: Test separately and then integrate it into existing products Oddly enough, Microsoft does have a Windows AI Lab for this kind of experimentation Many small models vs. one big LLM in the cloud Mobile Fortnite is back in the Google Play Store in the U.S. as Google plays nice Apple loses its contempt appeal, the end of "junk fees" (Apple Tax) is in sight Xbox and gaming Xbox December Update has one big update for the mobile app and one big update for Xbox Wireless Headphones There's a new Xbox Developer Direct coming in January Half-Life 3 may really be happening, but it will be a Steam Machine launch title so it could be a while Tips & picks Tip of the year: De-enshittify Windows 11 App pick of the year: Fortnite RunAs Radio this week: Zero Trust in 2026 with Michele Bustamante Brown liquor pick of the week: Lark Symphony No. 1 These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/963 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Sponsors: auraframes.com/ink framer.com/design promo code WW outsystems.com/twit cachefly.com/twit