Podcast appearances and mentions of elad gil

At 66 years old, instead of heading towards retirement, former Cadence CEO and legendary investor Lip Bu Tan decided to take on the hardest job in tech: turning Intel around. Elad Gil and Sarah Guo sit down with Intel CEO Lip Bu Tan to talk about why he took the job and what “saving” Intel actually looks like. Tan explains how his experience in startup culture informed his decisions to drive Intel's culture towards faster decisions, focus on customer satisfaction, and engineer accountability. He also discusses his strategy to strengthen Intel's balance sheet by welcoming investments from Jensen Huang's Nvidia, Softbank, and the US government. Tan also shares his product roadmap that centers the CPU for agentic AI and inference, the collaboration with Elon Musk on Terafab, his investing framework for semiconductors, and his views on how AI is reshaping design and operations at, as he puts it, a ‘legacy spreadsheet' tech company.         Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @LipBuTan1 | @intel Chapters: 00:00 – Cold Open 01:01 – Lip Bu Tan Introduction 01:24 – Why Lip Bu Took the Reins at Intel 03:00 – Fixing Culture 04:08 – Intel's 10-Year Vision 07:57 – Working with Elon Musk on Terafab 09:59 – Shifting Supply Chain for Semiconductors 15:34 – Limits to Scaling and Packaging 18:30 – Physical Limits to Engineering and Design 20:33 – Challenges in Semiconductor Investing 26:29 – Lessons from Cadence 28:02 – Scaling and Investment Decisions 32:03 – Rethinking Teams in AI Era 34:31 – Industrial Policy and Funding 37:25 – What Investors Misunderstand About Intel 41:10 – Where Compute Will Live 44:59 – Conclusion

Biohub started with an ambitious goal of curing, preventing, and managing all disease by the end of the century. A decade later, thanks to the convergence of frontier AI and biological data, that goal may have been too conservative. In this episode, Elad Gil and Sarah Guo sit down with Biohub co-founders Mark Zuckerberg and Priscilla Chan, alongside Biohub Head of Science Alex Rives. Together, they discuss Biohub's $500 million virtual biology initiative, which integrates frontier AI with wet-lab work to build predictive world models of cells, proteins, and systems. They also talk about their newly announced open-source engine for digital protein and antibody design, ESMFold2; why Biohub is a nonprofit rather than a venture-backed startup; and how hierarchical simulations will soon allow doctors to treat patients at an individual, mechanistic level.   Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Biohub | @finkd | @alexrives | @ChanZuckerberg Chapters: 00:00 – Cold Open 01:02 - Mark Zuckerberg, Priscilla Chan, and Alex Rives Introduction 01:26 – Why Biohub and Their Mission 08:27 – Integrating Frontier AI and Frontier Biology 09:45 – Micro to Macro Biological Modeling 14:22 – Mechanistic Interpretiability  16:58 – Why Biohub is a Non-Profit 21:41 – Understanding How Biology Works 24:23 – Timeline for Curing All Diseases 26:25 – Translating Research to Patient Impact 28:04 – Launch of ESMFold2 32:13 – Tackling Off-Target Effects and Edge Cases 38:39 – Putting the Tech in Individual Hands 41:06 – Talent at Biohub 44:25 – What's Next After ESMFold2 46:10 –  Connecting ESMFold2 to Agentic Systems 46:51 – The Virtual Cell 49:33 – Defining Success for Biohub 51:52 – Biohub Strategy Update 56:20 – Conclusion

What does it mean for a business to truly operate at the AI frontier? In a special crossover episode at Microsoft Build, Sarah Guo and Elad Gil team up with Latent Space host “swyx” to talk with Microsoft Chairman and CEO Satya Nadella about the future of AI platforms, software development, and the tech ecosystem. Satya reflects on the latest breakthroughs from Microsoft Build, the strategic shift toward multi-model harnesses, and why private evaluations (evals) are now a company's most important intellectual property. They also discuss how autonomous AI agents are reshaping the role of software engineers, the durability of SaaS business models, and why showing communities the ROI on data centers is so critical. Plus, Satya shares his thoughts on the economic and societal impacts of the token economy, as well as the future of AI-driven education startups. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @satyanadella | @Microsoft | @latentspacepod | @swyx Chapters: 00:00 – Satya Nadella Introduction 01:48 – Reflections from Microsoft Build 03:12 – Microsoft's AI Training Strategy 05:48 – Complexity of Real-World Deployment of AI 07:33 – Augmenting Human Capital 09:37 – Harnesses for Enterprise 11:49 – Developer Value 15:09 – Can Everybody Operate at the Frontier with Their Frontier Intelligence? 15:51 – Modern Definition of IP 17:38 – Future of Vendor vs. Enterprise Agents 21:48 – Near-Term Predictions on Model Pricing 24:02 – Durability of SaaS 25:58 – What Satya's Building 28:18 – Future of Engineering Roles 30:54 – How Microsoft Can Be More Ambitious 34:36 – Data Centers and Community Impact 38:01 – AI's Impact on Society 39:52 - AI and Education 42:28 – Conclusion

We've informally heard that Satya is a listener to LS for a couple years now, but it was still absolutely surreal to meet him and do a live pod at Build, together with our friends at No Priors, the leading VC AI Podcast that we also greatly admire!We covered the MAI model technical takeaways on yesterday's AINews, so I will focus our recap of Satya's main messages around three elements:* Satya's adaptation of the Bill Gates Line for positioning Microsoft as the Frontier Intelligence Platform — customers must gain much more value from the Microsoft ecosystem than Microsoft itself, by building on multi-model harnesses like OpenClaw and Scout, drawing on the full enterprise context exposed by context layers like Work IQ (heavily dogfooded by his C-suite), and building up private evals and traces as a new form of Token IP* AI ROI: On one hand, enterprises are having difficult conversations around Tokenmaxxing and Layoffs, and on the other hand, there are serious re-evaluations of the End of SaaS since the Build vs Buy equation has changed so much. Our previous SemiAnalysis guest had… interesting comments on Microsoft's position on this as the ur-SaaS titan, and Satya had great answers* Making the Impossible Possible: Kevin Scott's inspiring framing around what the most ambitious version of applying AI and technology at large to business and social problems, like education and social impact.Enjoy!Full VideoTranscriptVoiceover: Welcome swyx, Sarah Guo, Elad Gil,, and Chairman and Chief Executive Officer of Microsoft, Satya NadellaSarah Guo: Welcome to a crossover episode of No Priors and Lane Space with Satya Nadella. Um, congratulations on an amazing build. No, thank you so much, and it's great to be with both of you. I listen to both of you or b- both the podcasts all the time. It's great to be on it.Thank you so much. [00:01:00] So you're just talking about, um, these amazing, uh, announcements from across the Microsoft estate all morning for, I think, three hours. What is the, uh, what's the most important reflection or takeaway you have?AI as an Ecosystem PlatformSarah Guo: I, I'd say there are, uh, perhaps the, the biggest one for me is let's sort of conceptualize this more as an ecosystem play as opposed to a single model or even a single platform, right?Satya Nadella: I mean, you know, whatever I... At least for me, having grown up at Microsoft, having seen, whatever, four major platform shifts, uh, I sort of fall into that, um, uh, camp where a platform is defined by fundamentally its ability to create more value about the platform versus what's captured in the platform. And so if you, you view what's happening right now, I think this morning's keynote was how can any company, whether it's an AI native company or a traditional enterprise company, participate as a first-class participant where they can point to AI they created, [00:02:00] right?It's not that they don't use other people's AI. Of course they will. But to me, what's the path? What's the recipe? How do I do it? What does a stack look like? What does the tooling look like? What is valuable? How do you do that? That's it. That's sort of our job to do. Yeah. Ecosystem strategy is, uh, very complicated, right?Sarah Guo: Because you end up building certain components, partnering for certain components, supporting them. You just announced this big suite of models. Like, tell us a little bit about the, uh, training strategy for Microsoft now. Yeah.MAI Models & Training StrategySarah Guo: So, so the thing that we wanted to do with the MAI models was to build, and as Mustafa talked about, first of all, a great lineage, right?Satya Nadella: Starting with pre-training, uh, with very good data quality, uh, doing all the ablations, making sure because in, in some sense it's becoming even harder to build a clean lineage model just because there's so much stuff out there, uh, that you truly need to ablate out to be able to have a fantastic [00:03:00] pre-trained model.In fact, that's one of the challenges of a lot of the open weight models is they look great on one benchmark or two, but they're not great on practice. So that's why, in fact, even in the RFDEs are, they, they are pretty gone really excited about these MAI models because how the heck can a small five B model hill climb?Uh, and it goes back a little bit to what I think is ultimately the key thing to do, which is try to pursue finding that cognitive core. Uh, so to me, starting with a clean lineage- Then creating that ability for companies to be able to use this, right? Not just as a generalist, but to create their own specialist by building this hill climbing scaffold around it, right?So it's not just the model, but you have a hill climb scaffold around it, then you will start building your RLE. You will start collecting the traces. Most importantly, you'll have private evals because we know all the evals out there are good, interesting, [00:04:00] but they're not really that critical- They're work, yeahSwyx: at this point because they all can be maxed. And so the point is each company will have its own private eval. And so that end-to-end platform story around our models is sort of, uh, what I think is interesting. And then the one other thing, Sarah, since you brought that up, is I do feel there's a new frontier.Satya Nadella: Like people talk about the frontier and are you operating at the frontier. Um, interestingly enough, if you add a little temporality to it, you can use, let's say, in, in, in fact, the, the Lando Lakes demo we showed was pretty cool. We used, whatever, GPT-55, right? Then you collected a bunch of traces, and then you took a 5B reasoning model and achieved higher.Sarah Guo: Uh, so that is another aspect of what it means to appear... uh, you know, operate at the frontier Yeah. I, I think, uh, I first of all have to congratulate you on basically building a frontier neo lab inside of Microsoft in two years. Um, I'm wondering, you know, you have all this AI strategy that you're rolling out.Lessons from Two Years of AI DevelopmentSwyx: I'm wondering, what do you know now that you wish you would tell yourself two years ago where- or two or [00:05:00] three years ago? Three years for the Jensen partnership, two years for, uh, MEI. Yeah, I mean, I think the, the thing when, that I reflect quite a bit, right, which is sort of obviously I got into all this when I got excited by the, the scaling laws paper and, you know, when, you know, even the OpenAI partnership came about when those folks said, “Hey, we're gonna really throw a lot of computer transformers.”Satya Nadella: Uh, and they've helped. I- the thing that I always look back and say, “Wow, these things, uh, do have capability that they're climbing up.” W- I mean, this, you know, this crude way of saying it is intelligence is log of compute kind of works. Now what I think we underestimated perhaps is the real-world complexity of deploying these so that they actually deliver the value in the real world, right?So the outcomes as measured by any benchmark is interestingly important, but the true eval is when people out there are able to do unique things that they only can value, and it's very [00:06:00] measurable, right? That I wish we had sort of even, like, had more in our consciousness, right? Which is as an industry.Sarah Guo: Because right now I think when people say, “Wow, I don't want a token max,” it's an artifact of us not having thought ourselves as an industry that we are using tokens to create value every step of the way. So I think that's kind of what I wish we had gotten there, but I'm glad we are here.Real-World Value & Use CasesSarah Guo: What are some of the use cases that you've seen that have created the most value for your customers?Because I know that people talk a lot about code, and I think it's pretty clear that that's something that's having very large scale impact. Are there other areas that you find in common that your customers are really benefiting from? Yeah. I think, yeah, to your point, obviously coding is now got... But it's interesting, by the way, Elijah, to even talk about the coding, right?Satya Nadella: Which is coding has worked so well that we now have to rebuild the IDE, right? I mean, it's kind of nuts to see what we sh- launched is like, oh my God, I have these hundred agent sessions. I... The cognitive load it transfers back to me as a human is so [00:07:00] excessive that now I need a new UI. Uh, oh, by the way, I, like the, the chat as the only artifact was also impossible, so that's why we need a canvas.So it's kind of interesting for all the things about where is software needed or where is UI needed, uh, you kind of need that even for code, right? In a fully agentic world. But that said, one of the things that we are starting to see, we started seeing with co-work, but even some of the work we, we showed with auto com- uh, um, autopilot Right on what you see with claws is a good one because if you sort of think about a lot of human capital is doing the glue work, right?If you now can augment that with tokens/agents that are long-running, durable, right, then your ability to scale even what is still judgment and glue work gets amplified like coding does. Uh, so you can... Like, I'm positive that six months from now we'll all be saying, “Oh, wow,” like, all through ni- the night there was a bunch of stuff that [00:08:00] all these autopilots that I have working on my behalf with my delegated authority, so to speak, right?I can... Sort of given even my identity, did a bunch of work, then of course I'll need my new ADE to say, “Well, what did you do?” Like, I might... “Did I do this work?” And so on. So I think that that's where compressing of workflows, uh, completing of tasks, uh, that's where I think a lot of the value gets created. I think you raised a really interesting point, which is there's the actual agent that's doing the code, and then there's a harness around it, and that's the environment, that's the context, that's everything you're setting up as a developer around actually a coding agent.The Harness Concept for Enterprise AISarah Guo: What is the harness for the enterprise? Is there an equivalent concept for broader productivity work, or how do you think about that concept sort of generalized? That's right. So, so in some sense you kind of want the harness to define the models, the, the data, uh, and the tools, and so that you have a loop across those three.Satya Nadella: And so what we are trying to, first of all, make sure is each of our products that we build, right, whether it's GitHub Copilot or the security copi- the, the [00:09:00] stuff we showed with MDASH or even the discovery for science, it doesn't matter, all of them are multi-model harnesses, um, with tools access so that you can do this progressive, uh, disclosure of tools even so that they're token efficient.Uh, and then you're feeding it with very rich context because that's sort of the other hard lesson we have learned in the last two years is, oh my God, the amount of work you need to do to prep the context layer, uh, such that your plan can execute in the most efficient way is where the magic is. So we have, in our case, we have the GitHub harness, which essentially we're using across all our products.It's available in Foundry, and we are open, like you can use your Llama harness, whatever. Or you can use the, um, uh, you know, any open harness or any harness of yours and train with your tools and multiple models and your context. And so that's the pitch. Because right now a lot of dialogue is, um, “Hey, if I train the harness plus tools and the model together, you get [00:10:00] evals.”Elad Gil: And what we are proving out is... And the best example of that is what we did with MDASH, right? Because when it launched, uh, it found bugs or vulnerabilities that were not found by Mythos Uh, and so there is existence proof, I would claim, that you can have a multimodal harness, uh, that can in fact be more, uh, performant in the real world So a premise behind the, uh, training at the independent frontier labs is really, you know, we're gonna have these models, and we'll have an API business, and we'll support enterprises and startups.Sarah Guo: ButPlatform Strategy & Developer EcosystemSarah Guo: a first-party product, be it productivity or code or search, drives the majority of revenue. That's a different value equation than you're describing, I think, with the Microsoft ecosystem. Uh, if, if that's the case, tell me if it's the case, uh, ‘cause obviously you have first-party products and you have enablement products.Satya Nadella: Um, what is the role of the develop- Like what is gonna be hard and the set of skills and the value capture the developer has in that world? Yeah. So I think that there's always [00:11:00] gonna be the case that someone who is super successful in- as a platform builder can also have first-party products. It was true with Windows.It is true, uh, with, uh, the, the SaaS side and the cloud side as well with us and others and so on. But the thing that is, is it should not be a limiter to other people achieving that same success, right? That I think is the core difference, which is the, the network effects this time around, around intelligence are such because they learn from data, and not really lots of data.It's just a few samples that you have to see to understand what's novel about something. So that's why the game becomes how to protect. So that's why I would say every company, having private evals may be the biggest IP, right? Think about it, like what's that private eval that you can then use even a frontier model to hill climb on and not leak the traces may be one of the biggest [00:12:00] drivers, uh, of IP.Like, so in other words, another te- acid test is you have an eval that's private. You're using, uh, a g- a Model A. Can you switch it to Model B and e- you know, climb up? If you can, then you're in control. If you can't, you're not in control, and that's where even the harness decision becomes super important, right?swyx So therefore, having an open harness, letting all models come in, having your evals, your context, your tools help you hill climb, I think is the skills that an AI native startup needs, a SaaS company needs, or every enterprise needs. Yeah, I think in, in a very real way you are ... Microsoft historically is an operating systems company and th- then become a cloud company.Maybe like the third act is that you're a harness or evals company. Whatever w- ... whatever the, the sort of conglomerate of concepts that you wanna put together. Um, and, and I think like enabling every company to have like frontier intelligence or what- what- Yeah ... I forget the, the [00:13:00] exact term that you used, um, is the, is the mission, right?Satya Nadella: That's it. Like that is, that is the platform promise, that you build with us, you will get your intelligence, uh, for your data. That's it. That ... To, to me, that is the ... Like if there was one tagline, uh, for this entire developer conference is- Can everybody operate at the frontier with their frontier intelligence, right?To me, that is so important because otherwise it, I, I don't know how you achieve stable equilibrium, right? Which is how do I then go and say, “Well, my company is gonna have a terminal value because I now know how to continuously compound-” Yeah ... on top of what's a platform that gets better,” right? So when, like Windows obviously came out, Adobe built, Autodesk built, uh, or even like take what Jensen said.We built DX and he built, you know, CUDA on top of it. Um, right? I mean, I always say to Jensen, “God, I got the short end of that,” right? “I wish, uh, we had recognized it.” But nevertheless, but that, that idea that you can build a platform layer [00:14:00] that someone else can then extend out, um, and build their own intelligence layer in this case, I think is everything, right?Without it, why have a developer conference? I can just come and have you all sort of just worship at the altar of one model. Yeah. But that's not a developer conference. Uh,IP, Evals & Company Valueswyx: backstage we, we had a discussion about what is IP or what is the, the value in a company. It used to be the length of, uh, human experience at a company, and now it's this other thing which is the evals, the, uh, experience in sort of applying agents to the company. Can you... I just want you to like flesh that out a bit more ‘cause- Yeah ... it was very insightful.Satya Nadella: It's a great way to frame it, right? Because yeah, at the end of the day, every company is gonna have both the human capital that is still gonna be super valuable, uh, because humans, uh, and their ability to find the gaps that exist at all times is going to be the way we all will create value, right?I mean, so I'm definitely in the camp that this is going to be about expressing new forms of human agency and ambition even as token capital goes up, right? So let's say a cor- any corporation [00:15:00] has lots of tokens and lot of human capital. The question is how do you compound the two? So if you have a... Like if you take in Teams I have a bunch of agents doing work and a bunch of humans doing work, and the traces between those, that is really important context of how that enterprise is creating value.Then that goes back to train not a generalist model, but to train the company veteran agent, uh, right? That is super valuable again, right? Which is when a company goes says, “It should in fact go onto the balance sheet,” is how I think about it, right? That's so... In fact, there may be... Like human capital was never possible to go put on a balance sheet, uh, because you didn't know how to capture the tacit knowledge.swyx: Whereas now I think you can with the agents that have learned through the h- through, through time, through all the traces. Uh, so that's what at least we think will happen. I, I think the SEC is gonna have to have accounting standards- ... for token, uh, expertise Uh, y- y- you're talking about the equilibrium [00:16:00] state, um, and a stable equilibrium where companies have this compounding value and can see terminal value for themselves.Future of SaaS & Business ModelsSarah Guo: Another challenge to, you know, the considered equilibrium of, okay, there are applications and workflows that are sort of common to a vertical or a horizontal. Um, and this was, like, the generation of SaaS companies and, you know, Microsoft has lots of SaaS properties as well. And then there are things that are very specific to every enterprise that they're differentiated against.Elad Gil: Um, I'm sure you have heard much and participate in much of the debate about the end of software because all these workflows are, are cheap to generate now. Um, do you think the equilibrium looks different between what agents get built- Yeah ... in enterprises versus in their vendors in the future? Yeah. So I think what's happening there is, see, we, we had a particular way we captured, um, I would say workflow in apps, right?Satya Nadella: Because we built a, a data model, right? We schematized some part of some business process. Mm-hmm. We then built a bunch of business logic. Yep. And then we put a bunch of UI [00:17:00] on top of it, right? So that's kind of what every SaaS company- And a little configuration. For, like, 20, 20 years that was the plan.Right, that- Yeah ... and that was it. So interestingly enough, now you kind of get to re-litigate that vertical stacking, right? So I still think, for example, that data model that you built underneath every SaaS application is super good, right? Like, why reinvent it? Like, I, I, my general ledger better be a general ledger.I don't need new schema creation. No. Uh, in fact, that entity relationship, uh, is actually pretty good, robust thing that I want to feed. And you want it to be stable. That's right. Yeah. Then same thing with business logic, right? If, if you look at, uh... We have this product called Power BI, right? It is like dashboards galore people created.The beauty underneath that dashboard is a very rich semantic model, right? Someone took the pain to create a dashboard and do all the measures, and you want that. That's business logic, right? I want that to be available to me. So I think the [00:18:00] challenge of the SaaS business model is we packaged one way. We now have to learn how to unbundle these things and rebundle in new ways and discover new business models, right?I mean, if you look at it, d- what's happening today with Microsoft 365 is a great example, right? We have this thing called Work IQ. In fact, like, what we are realizing is, oh my God, like, you know, if you look at... In fact, there's a pa- historical parallel too, right? We sold first Exchange and SharePoint and, uh, you know, before Teams, we had a thing called Lync Server and what have you, and we thought, “Oh, that's all gonna move to the cloud.”But little did we realize that, um, the number of people who will use servers in the cloud is 10X, 100X, right? Because people were not buying servers, they were just buying a subscription. Mm-hmm. The same thing is now happening with M365 because with Work IQ, we have exposed what is perhaps the most important database in a company that never got used as a database because it was only captive to our apps.Mm-hmm. Right? It, it was all email operated on it, Teams operated [00:19:00] on it, Word, Excel, PowerPoint, SharePoint. But now, like this is one of the coo- coolest things I get to do with Work IQ. I go to a GitHub repo and I say, “Hey, I attended a bunch of design meetings last week related to this repo. Can you capture all that and tell me what changes I should make?”I mean, think about that, right? It literally can go look at all those transcripts, come back with a plan to change a code base, right? Previously, you could never have thought of using M365 for something like that. So the value creation opportunity now in the agent world is in fact 10X more, but it does require us to have...Sarah Guo: For example, there's going to be usage around M365, right? Which is going to be perhaps more than even the e- end users and we have to even re-architect. Like, in fact, like what I use to serve an inbox or a mailbox cannot be used to serve an agent. Uh, and so that's sort of what we are doing.Pricing Models: Per-User, Consumption & OutcomesSarah Guo: I don't believe in, like, permanent business models for any of these domains, but in the [00:20:00] near term, do you have a prediction between, uh, you know, outcomes-based pricing, token-based pricing?Elad Gil: Enterprise bundles Yeah. The way I- I think about this is always we've had... Like, let's even take the per-user pricing. Mm-hmm. The per-user pricing is really an artifact of someone creating a budget needing certainty, right? Because it's the most important thing. Like, somebody wants a budget- Mm-hmm ... they need a per user.Satya Nadella: And, and per user is just a set of entitlements to usage, right? That's kind of what it is. And so the way is, if the first bundling will be take some usage, bundle it into per user stacks and, you know, then sell subscriptions. So subscriptions I think are gonna be there, per user is gonna be there. Then the next big thing will be consumption.So people will say, “I want consumption.” And it's also possible that people will say, “I don't even want to pay for any of the subscriptions or the consumption's outcome.” Mm. But remember, most people love outcomes until they have an outcome, because once you have an outcome, it's like giving away royalty, [00:21:00] right?Mm. I mean, like I, I've talked to customers who love, you know, outcome-based pricing, and I say, “I'm all in,” until they, “Oh my God,” like, “what are you talking about? You're sharing in my outcome? No, no, no. I want you to go back to per-user pricing, and I want you to consumption price,” right? So I think that debate will go on.Uh, but and all, all, all of these business models have a particular time and a place versus one to rule them all. And if anything, if you're a SaaS vendor or you're a platform vendor, having that flexibility... And quite frankly, we face this with GitHub, right? We just recently announced a per-user pricing on GitHub because little, you know, we- GitHub Copilot was constructed at a per-user level before we understood even, uh, the intensity of usage of agents, right?It was an interactive way for a developer to use code complete, maybe tasks. It was not like, oh, I launched 10,000, you know, agents that are going on all day, right? So that is what the adjustment is about. So now that we really want, there will [00:22:00] always be a per user, but there will have to be a consumption meter.Durability of SaaS & Build vs BuySarah Guo: How do you think about the durability of SaaS more generally? One thing I've observed is in a lot of enterprises internally, there will be teams that almost have agent euphoria. They're so excited about the explosion of things they can build that they're trying to rebuild a lot of applications or going to their SaaS vendors and saying, “We're not gonna work with you anymore,” or, “We're considering an internal project.”And it seems like in six to nine months, maybe some of those people will come back and say, “Actually, we, we can't rebuild everything.” How do you think about what's durable in this world and what isn't? Yeah, it's a... It... I think we have to go through one full budget cycle on this to really see the, um- Uh, the sort of the emergence of the equilibrium, because at the end of the day, there's marginal cost to even generating the app, right?Elad Gil: In, in fact, there can be even a, a simple way to say it, like if you should always acquire something if the marginal cost of building and maintaining, uh, something on your own is higher. Uh, right? That should be like it's a quantifiable- Yeah. Right? A quantifiable thing. And [00:23:00] the maintenance part is important, right?Even, like you got to remember like, hey, you know, all the security stuff that now AI will find, you better fix them too fast. Uh, of course, there's a coding agent to help you with, but then that burns tokens, right? So whose responsibility is it? It's kind of like a, a cycle that you've got to think through.And I think we have gone through the excitement that I can generate a lot of software. I think the next thing would be what software do I really want to generate? Mm-hmm. What software do I want to use from others? How do I compose these two into some agentic workflow that I have agency over, right?Sarah Guo: Because I think there'll be very little tolerance for anybody who's inflexible, uh, at the vendor level. Uh, but at the same time, I think that anyone who has got that flexibility shows up, delivers the value, will be back at again, right? We're selling software, uh, but with just different business models, in fact Uh, speaking about building software, um, one of my favorite moments from, I think, a previous build maybe one or two years ago was they had a b- they, they...Swyx: There was a section of you building your [00:24:00] own software. I'm curious if you're building anything now. Yeah. So I, I think the... You know, first of all, let's face it, right? Building software has made it possible for even the incompetence of a CEO of a company- ... like ours, uh, you can build, so thank God. But that said, I, I, I, I do feel that, you know, something like, um, GitHub Copilot to me, and especially the new Sessions app or the new app, has just made it so much more possible for you to have agency over artifacts that you felt you couldn't touch before, right?Satya Nadella: So to, for me as a CEO, even to go to a code base, uh, to be able to learn about it, like I remember joining Microsoft long back, you know, first and then you say, man, everybody had to go in and look at, you know, whatever, Cutler's, Malik, or what have you to learn how to do good C, uh, C++ code. Um, so now that ability to be more full stack up and down is so good, but that doesn't mean every one of us should be doing the same thing.The question is: [00:25:00] how do you then have the ability to inspect things, learn things, see things, um, I think is just so much more. And so to me, what I'm building a lot of is these long-running Foundry agents. Uh, right? So there's autopilots. So the easiest thing is, to me, I think I just built one, uh, even last week, where the idea was, hey, can I have an agent that is continuously monitoring essentially my own chief of staff autopilot, right?We're gonna have that obviously in, uh, Scout. That's what, uh, uh, we showed. But it is so easy and trivial to build. I took Work IQ. I said, “Take Work IQ, go, uh, and build a Foundry long-running agent.” Uh, store all the memory in, um, uh, using Ray Fin, right? Basically at my backend as a service. And lo and behold, it built it, and not only built it, I could say publish to Teams, and it published the damn thing to Teams.Sarah Guo: So the ability, uh, to have a, you know, some end-to-end project like this complete is just pretty [00:26:00] miraculous. How do you think, uh,Future Engineering RolesSarah Guo: that impacts the different types of engineering roles that exist in the future? Because right now I think there's, you know, a dozen different types of engineers that you can be, from QA, front end, et cetera.You know, there's a big swath. I've heard some people argue that in four or five years we'll basically end up with four engineering roles. It'll be people who are managing agents, it'll be four deployed engineers or FDEs, it'll be security engineers, and then people working on large scale infrastructure for a small number of services, and then everything else just collapses into the agentic world.Satya Nadella: Yeah, I- Do you think that's a correct view of the world? Yeah, I mean, I think, I think we'll have to experiment our way through it. But what you said is what... There are some very at scale things. At LinkedIn, they did structurally change- Mm-hmm ... uh, and it, you know, basically built up a new discipline called full stack builder, right?So they went and said, “Hey, let's bring, uh, people from design and product management, front end engineering, all put them together.” Uh, but also have an edge, right? It's not like the design person still doesn't have the design edge, or the front end [00:27:00] person doesn't have the front end edge, but you can give yourself bigger scope in roles so that you're not confined to one role.Um, and then r- equally, infrastructure has become very critical, right? So in other words, like, I mean, RLEs, I mean, one thing we've realized is even for the Excel team, for example. Mm-hmm. Building the RLE in which a reward can be learned is actually one of the hardest sort of infrastructure problems.Mm-hmm. Uh, and so you kind of need even new talent, right? Distributed systems people even in what was considered an end user app team, uh, because it's a different skill set. So yes, infrastructure, science is the other one, obviously. Um, so I think we'll see how these evolve, right? Where's the s- real... I mean, always the world will have a bunch of specialists.Okay. Um, you know, I think the generalist role is going to be the most exciting, right? Because the leverage of a generalist- Mm-hmm ... um, is where we are going to see the maximum returns, right? When, when you said, “Hey, are you coding?” I'm now a gen- Like, what... I've basically translated [00:28:00] knowledge work Right?Which I did, where I created a Word document or a spreadsheet, or even, uh... And now I can build an app, right? It's in the same sentence. Uh, right? That idea that, “Oh, wow, my generalist skills have gotten higher leverage,” I think is what we're gonna see across the board. Music to the ears of CEOs and VCs that are, like, a little dangerous and a lot of- Golden age for idea peopleSarah Guo: idea people. Yeah. Uh- With a lot of agency. I- if you take that idea of personal agency and you just zoom it out to the organizational context, um, uh, my partner Mike Renall, who, uh, actually started his career at Microsoft, just wrote an essay where one of the big takeaways is i- it's an age where you can be much more ambitious, and you need to be, given the pace of the environment and how quickly, actually, users and companies are open to adopting new technologies.Satya Nadella: Um, how do you think about... I, I feel silly asking this of somebody running a, you know, trillion-dollar-plus company already, butAmbition & Making the Impossible PossibleSatya Nadella: how do you think about how Microsoft can be more ambitious now? It's a great question. Um, I [00:29:00] think, um- I think the, the thing in these type of transitions is to have a conceptual model of how work can change to go after outcomes that you could hardly imagine previously, right?In fact, Kevin Scott has this nice line, right, which is, um, when you can make the impossible... Like, when you're making hard things easier, that's sort of one point of leverage. But true ambition is about making the impossible possible. So now the thing that is missing a little bit in all of our organizations is what is that new conceptual model of what can we build?What was impossible and what can we build? And I'll give you one example of this, right, which is I take great inspiration from sort of the people who were managing the Azure net- network. And they came to the... This was from even last year. You know, we were scaling. You saw that I, I [00:30:00] talked about sort of how we built in the last 15 months more Azure capacity than we built in the first 15 years.I mean, it's crazy. Wild. Yeah. Right? It's pretty wild. And it's the same team. So they saw that and they said, “Bob, this just ain't gonna work if we don't reconceptualize our work.” So they built... Essentially they said, “Our job is not to do Azure networking. Our job is to build the agentic system does, that, that does Azure networking,” right?These are the folks managing the 500-plus fiber operators managing the VAN, right, all over. And fiber operations ultimately is a physical operation. Things get cut, things get, uh, you know, have to be repaired. You know, we have fancy words called DevOps and so on. Basically, emails are coming in and you gotta go respond to them, take care of it.So they built this agentic system. They even have a character for it. It's called Miles, and it sort of does all this stuff, right? They started sort of screaming for more tokens and so on. And so they were saying, “Look, uh, we don't need a headcount. We need tokens in order to be able to [00:31:00] manage, uh, our operation.”That reconceptualization- Mm-hmm ... of what their work is, right? They, they basically took their work and made it meta, right? That meta work is now their new work. Mm-hmm. Right? In the ‘80s, if somebody had come to us and said, “4 billion people are gonna get up in the morning and start typing,” my model would've been, we need 4 billion typists?But we're not doing typing, we're doing knowledge work. So that, to me, I think is it, right, which is whether it's Microsoft or whether it's any organization, is to give ourselves permission to do new types of metacognition, meta work, using these new tools to change the outputs that matter, uh, and then really make the impossible possible.Sarah Guo: So completing that dot or the, the connective tissue across those, I think, is where a lot of the enterprise value will get created.Data Center Build-Out & Community ImpactSarah Guo: Should we talk about data centers? Yeah, please ask. Oh, okay. Well, uh, uh, w- we-- this leads nicely into the data center build-up. I always think, I- I just-- I'm just impressed at the sheer scale of the [00:32:00] build-out from Microsoft, but also everyone else, that this is redefining what it means to be a hyperscaler.And I just feel like that, that, that is at unprecedented scale on finances, uh, on the way you run the company, but also the communities that are, that are impacted. Um, yeah, just talk a bit more about what you're seeing on the ground, like when you visit your- Yeah, I think there are two aspects of it.Satya Nadella: Obviously, the, the build-out is, uh, extraordinary. Um, you know, nothing like this has happened, and it's great to be, uh, one of the participants in it. Uh, but you brought up the other part, right? I think at this point it's clear that unless we as an industry, uh, are very principled about ensuring that the benefits of all the stuff we're talking about are felt in real ways, uh, at the community level, right?Because this is not just a, a campaign, um, right? It has to be real, where people are saying, “Look, this is not ch- changing the prices on energy for me.” In fact, if anything, it's bringing down prices because long term there's going to be a better [00:33:00] grid, there is going to be more energy. Water consumption is, in fact, not sort of, uh...In fact, water is being replenished, right? You gotta really, you know, educate folks on truly what's happening, the cl- uh, the closed loop systems we are building. We have to invest in the training, the jobs, the tax base. In fact, the least talked about stuff is the amount of jobs that get created during construction, after construction.What's the tax base that's there in the community? And, and all this has to be real. Um, and, and if that is the case, then we will have permission. If it is not, we won't have permission. It's as simple as that, right? Which is, uh, we, we... I think we have to take it as an industry pretty seriously. Uh, I think it's good for communities to be skeptical, ask the hard questions, for us to do the hard work, earn that.Um, but at the end of the day, if there's-- if we can really be the produ-- Wait. I've always felt like in human history, if you use a lot of energy but also create a lot of value for society- The story has been fantastic. If you don't [00:34:00] do that, it's not been that great. And this time around, I'm a firm believer that ultimately if you do have a token economy that drives productivity, that drives economic growth, that drives broad spread, um, you know, participation, better health outcomes, um, then I think we'll be in a great place.Sarah Guo: Uh, and that's at least what we all have to be focused on. Yeah. It, it makes me think actually that with all these initiatives that you're doing, might be e- easier to see ROI in the communities first before in enterprise. Yeah. I, I mean, I think both sides. Yeah. In fact, it comes back together. It has to be the people in the communities are going to be employed, are going to be participants, uh, in the real economy, right?Satya Nadella: That's I think the question is. Like, if we- if the broad economy is doing well and the communities are doing well, the dots get connected. It's sort of the market forces are such that we will connect the dots. And that I think is it. Like, you ought to be able to see the evidence. You can't be about o- any one company, uh, but it has to be broad economic growth and broad [00:35:00] ec- you know, community permission.Elad Gil: Yeah. I guess I wanna talk aboutSocietal Impact & Optimism About AIElad Gil: what you're most optimistic about currently or what have you most updated your personal models on regarding societal impact of AI? So you're saying what's the, the, the- What have you updated most on in terms of societal impact of AI? Yeah. I think the, um, the p- the most, um- Critical thing is the first question we even started with, which is we need to tell the story and make it real that everybody has a real shot to participate as a first-class participant in this new economy.Satya Nadella: Right? That's kind of, I think we- in the next 12 months, 18 months, we need a way for people to say, “Oh, wow, I get it.” Right? There's going to be tremendous capability, tremendous amount of infrastructure, but I can see what is going to happen, whether it's the benefits like health outcomes or my ability to create a startup or my ability to run my [00:36:00] local sort of, uh, store more efficiently.It's just happening, and I see that, uh, benefit myself, right? That to me, you know, earning that permission in a path-dependent way, we can't wait. See, the one thing, Eli, that I've now learned is I think the world is gonna be very skeptical of tech and tech companies that say, “Trust us, we've got it. The g- future is gonna be glorious.”Sarah Guo: Uh, you kind of have to deliver tangible benefits. Um, and quite frankly, politicians winning elections, uh, because they have advocated for that. That will be at least my adjustment because without it, um, thinking that somehow... Because it's too important this time around. It's too much of the economy for it not to be the case So one very simple framework I have for, you know, what are, what is gonna be the broad benefit of AI, um, beyond the communities just working in technology, are, are sort of wealth creation- Yepit's [00:37:00] gonna happen in a ton of different companies, startups and large companies. Then you have healthcare. Uh, you, you had amazing demos today. There are companies like Open Evidence. I think that is happening. Um,Education & Future of LearningSarah Guo: education seems like another one that's an- Yep ... obvious good where we haven't seen as much impact as I'd expect.Swyx: Do you have a hypothesis on why that might be, or if it'll come? Yeah, I mean, I think this is where, again, how we think about education, how... You know, recently I met with, uh, the founders of Alpha School and learnt a lot about what they were going and going about, and it's fascinating to listen, uh, to how to even rethink- MmSatya Nadella: uh, what does education really look like. Because I think it's actually very important. Mm. Uh, and I'm not saying anything traditionally being done is less important, right? I was even looking at the, uh... It's fascinating to see. I, I, I forget the which Stanford class it was, uh, the, the Asian guidelines for CS something.Mm. Uh, because you still need people to learn. Uh, like it was an interesting AI class that they were making sure people were learning how to apply softmax appropriately versus saying, “Hey, fix my training run.” Mm-hmm. Uh, so I think learning concepts is important. It's going to [00:38:00] be, uh, critical. But the way we create the incentives, what are the credentials, how we value those credentials, what is the employment opportunity for those credentials?So I think that there's a complete change that has to happen, uh, given the way to get to information, way to educate yourself, way to continuously keep yourself updated has changed so much. So I think interestingly enough, maybe the next big startup and success story could be someone who builds a new university, um, or a new, um, pedagogy even of how to get someone to go through a curriculum and find economic opportunity, uh, that's highly valuable.Well, that has felt, uh, perhaps impossible for a long time, but it's a great note to end on and something that might be possible. It's still possible. Yeah. Thank you, Satya. Thank you so much. Thank you. Yeah. I appreciate it. Thank you all. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe

Companies in Silicon Valley from Nvidia to AMD are racing to fuel the AI revolution with postage stamp-sized AI chips. Meanwhile, a chip the size of a dinner plate just fueled a $63 billion IPO for Cerebras. Elad Gil and Sarah Guo sit down with Cerebras founder and CEO Andrew Feldman to discuss the company's journey to making one of the largest tech go-publics in history. Andrew details the multi-year journey of pioneering wafer-scale AI computing, including surviving a brutal period of being ahead of market demand. He also explains the engineering breakthroughs that led to delivering inference speeds at 20x that of standard GPUs. Andrew then shares how a remarkable $20 billion deal with OpenAI came together in only four weeks. Plus, Andrew's thoughts on why architecting the future of AI requires the fortitude to be a “professional David” against the Goliaths of tech. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @andrewdfeldman | @Cerebras Chapters: 00:00 – Cold Open 00:36 – Andrew Feldman Introduction 01:19 – Cerebras' Evolution 02:48 – Wafer-Scale Bet Pays Off 06:38 – Challenges and Breakthroughs 08:37 – Crossing the Market Chasm 10:38 – Scaling Software and Hardware 12:03 – Relevance of AI-Generated Coding 13:31 – Leadership and Hiring Culture 17:16 – When to Quit vs. Persist 19:40 – Why Cerebras Went Public 22:57 – The OpenAI Deal 25:54 – Open Source and Post-Trained Workloads 27:37 – How Speed Opens Up New Business 30:33 – Conclusion

Securing AI dominance requires more than just semiconductors; it demands a complete overhaul of how the West manages everything that goes into them, from rare earth minerals to actuators. Enter: Pax Silica. Sarah Guo and Elad Gil sit down with US Under Secretary of State for Economic Affairs Jacob Helberg to discuss the launch and expansion of Pax Silica, a 14-country economic security coalition designed to secure the entire AI supply chain. Jacob talks about the creation of a forward-deployed industrial base in the Philippines, where 4,000 acres will be developed into an “economic security zone.” He also compares and contrasts Pax Silica with China's Belt and Road initiative, explains how the US plans to reindustrialize through automation and robotics, and explores how the Trump administration envisions making these policies durable across future presidencies. Plus, we hear why Jacob believes America to be a “global underdog.” Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jacobhelberg | @UnderSecE Chapters: 00:00 – Cold Open 00:41 – Jacob Helberg Introduction 01:02 – Pax Silica's Mission 03:51 – Investing in AI Chip Supply Chains 05:43 – Comparing Pax Silica to China's Belt and Road Initiative 12:38 – Pax Silica's Value Proposition 14:38 – US vs. Partnered Manufacturing 19:10 – Rare Earth Mineral Pricing 22:16 – Role of Venture Capital in Pax Silica 24:50 – Near vs. Long-Term Priorities 27:09 – Making AI Policy Durable 28:09 – How Policies Impact Entrepreneurs 31:00 – Trump's Entrepreneurial Administration 33:00 – Why America is a Global Underdog 38:00 – Conclusion

The world's first AI-take-private just proved that AI can revolutionize the real economy. Long Lake Management co-founder and CEO Alexander Taubman joins Elad Gil to discuss his firm's agreement to acquire the legacy platform American Express Global Business Travel (Amex GBT) in a deal valued at $6.3 billion. Alexander explains the mechanics of AI-driven roll-ups, and why Long Lake chooses to acquire and transform businesses rather than simply selling them software. He also talks about how Long Lake's horizontal AI platform, Nexus, automates workflows across diverse verticals, and how automation through AI not only powers growth for their portfolio companies, but results in both satisfied customers and employees. Plus, they explore Alexander's vision of Amex GBT as a multi-decade compounding machine.  Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @alextaubman | @amexgbt  Chapters: 00:00 – Alexander Taubman Introduction 00:30 – Long Lake's Nexus Platform 03:35 – Retention and Talent Flywheel 05:01 – Acquisition vs. Offering Software 06:57 – Building Long Lake's Founding Team 10:37 – Taking American Express Global Business Travel Private 13:36 – Taking Berkshire Hathaway's Approach to Management 16:37 – How AI Strategy Makes Long Lake Stand Out  19:32 – AI Makes Services Scale 22:00 – Conclusion

Baseten CEO and co-founder Tuhin Srivastava sits down with Sarah Guo and Elad Gil to discuss the rapid growth of AI inference demand, Baseten's 30x growth, and why inference is becoming the strategic “last market.” Tuhin Srivastava argues the application layer will persist because companies with unique user signals can encode value into workflows and post-train specialized models, citing examples like Abridge and support workflows. The conversation covers GPU capacity constraints, Baseten's multi-cloud fabric across 18 clouds and 90 clusters, long-term contracting dynamics, the importance of the software layer for stickiness, evolving workloads, multichip possibilities, and operational lessons at scale. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @Tuhinone   Chapters: 00:31 Baseten growth 01:55 Why the app layer wins 05:57 Serving frontier customers 07:55 Open source model mix 09:21 Chinese models and geopolitics 13:07 Custom inference dominates 14:22 Post training acquisition 17:10 When to invest in custom models 18:35 Supply crunch and data centerse 22:25 Longer GPU Contracts 24:09 What Makes a Winner 26:07 Multi Chip Future 28:19 Runtime Roadmap 31:08 Scaling Edge Cases 33:48 Hiring and Leadership 36:44 Operations Pager Culture 38:19 Efficiency Drives Demand 40:41 Concierge Everything Future 42:34 Conclusion

Elad Gil (@eladgil) is CEO of Gil & Co, a multi-stage investment firm, holding company, and operating company working on the world's most advanced technologies. Elad is a serial entrepreneur, operating executive, and investor or advisor to private companies, including AirBnB, Anduril, Coinbase, Figma, Instacart, OpenAI, SpaceX, and Stripe. He was previously VP of Corporate Strategy at Twitter and started mobile at Google. He was the founder and CEO of Mixerlabs and Color. Elad is the author of the bestseller High Growth Handbook: Scaling Startups from 10 to 10,000 People.This episode is brought to you by:Matic the intelligent robot vacuum and mop that navigates obstacles and needs no babysitting: MaticRobots.com/TimAG1 all-in-one nutritional supplement: DrinkAG1.com/TimEight Sleep Pod Cover 5 sleeping solution for dynamic cooling and heating: EightSleep.com/Tim Helix Sleep premium mattresses: HelixSleep.com/TimTimestamps[00:00:00] Start.[00:02:21] What's the “AI personal IPO” that just quietly happened across Silicon Valley?[00:05:28] Tens to hundreds of millions per researcher: What top AI pay packages actually look like.[00:06:44] The compute ceiling: Why Korean memory fabs are the unlikely bottleneck throttling every AI lab on earth.[00:11:11] From zero to $30B run rate: The fastest revenue ramps in the history of capitalism.[00:17:24] The dot-com survival rate was one in 100. Buckle up, AI founders.[00:20:35] Your value-maximizing window: Why the next 12–18 months may be as good as it gets.[00:21:32] Durable advantage — and why the AI market is an oligopoly (for now).[00:24:12] Exit options for AI founders: labs, hyperscalers, vertical players, and the underrated merger of equals.[00:28:11] Math, biology, and intuitive leaps: Elad's pre-investing background.[00:29:42] Elad's revisionist genesis story.[00:30:50] Go where the cluster is: 91% of global AI private market cap lives in a 10×10 mile square.[00:33:20] The accidental investor: Patrick Collison walks, Airbnb intros, and deals that just happened.[00:34:37] Want money? Ask for advice. Want advice? Ask for money.[00:35:00] The High Growth Handbook: Tactical guide, not bedtime reading.[00:35:41] Market first, team second — with a Perplexity-and-Anduril asterisk.[00:37:43] Smoke in the distance: AlexNet and the transformative GPT-3 moment.[00:45:15] AI cold-reading: Feeding photos to the model and getting eerily accurate personality reads.[00:48:56] Has Elad ever done a retrospective on his own investing?[00:52:13] Power laws are terrifying: 10 companies, 80% of returns, two decades.[00:55:53] Avoiding science projects, and how SPACs accidentally saved hard tech investing.[00:59:20] The one-belief framework: Coinbase = crypto index. Stripe = e-commerce index. That's the whole memo.[01:00:54] Due diligence theater vs. the one question that actually matters.[01:02:13] The four-year vest is a relic: How venture capital ate growth investing.[01:07:16] Boards as in-laws: You can't fire them, so choose wisely.[01:09:47] “Valuation is temporary. Control is forever.” — Naval Ravikant, as quoted by Elad, as relayed to you.[01:11:30] How great companies actually grew: toolbars, name-targeted ads, and billions in distribution spend.[01:15:36] Selling software vs. selling labor hours: The real shift generative AI made.[01:18:40] Spotting a great market: regulatory shifts, technology shifts, and Hashi getting bought by IBM.[01:21:28] Fake TAM, real TAM, and the Coke CEO who realized he wasn't in the soda business.[01:22:47] Right now, consensus is just correct. Save the contrarianism for later.[01:25:15] Market entry vs. market disruption: SpaceX launched rockets, then disrupted the internet.[01:26:16] How Elad learns: X, papers, 20-minute calls with the right people — and four AI models running in parallel.[01:27:15] Deep dive: ADHD, autism, and why diagnostic rates soared without more people actually having it.[01:33:40] Longevity for realists: sleep, creatine, and maybe rapamycin when the real drugs arrive.[01:40:30] Ibogaine, anesthesia, and the next frontier of bioelectric medicine.[01:45:15] Elad's first-ever 10-year plan — and why making one changes everything.[01:46:53] Parting thoughts.*For show notes and past guests on The Tim Ferriss Show, please visit tim.blog/podcast.For deals from sponsors of The Tim Ferriss Show, please visit tim.blog/podcast-sponsorsSign up for Tim's email newsletter (5-Bullet Friday) at tim.blog/friday.For transcripts of episodes, go to tim.blog/transcripts.Discover Tim's books: tim.blog/books.Follow Tim:Twitter: twitter.com/tferriss Instagram: instagram.com/timferrissYouTube: youtube.com/timferrissFacebook: facebook.com/timferriss LinkedIn: linkedin.com/in/timferrissSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

AI agents can already collaborate, but they lack a trustworthy medium in which to store value and execute contracts. Enter Circle's Arc Blockchain, an economic “operating system” designed for a world where machines drive the real economy. Circle co-founder and CEO Jeremy Allaire joins Elad Gil to dive into the future of programmable money and the agentic economy. Jeremy explains why traditional banking fails to support the needs of AI agents, and how stablecoins like USDC facilitate an internet-native economy. They also discuss the tokenization of real-world assets, the move toward full-reserve banking, and Jeremy's predictions for double-digit GDP growth as AI and blockchain reach their “broadband moment.”  Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jerallaire | @circle Chapters: 00:00 – Cold Open 00:05 – Jeremy Allaire Introduction 00:21 – Origin Story of Circle 02:11 – Rethinking the Financial System 05:26 – The Role of Stablecoins 09:52 – Use Cases for USDC 11:30 – Programmable Money  12:25 – Blockchain as Operating System 14:37 – The Agentic Economy 17:45 – Arc Blockchain Use Cases 27:00 – Scaling Models and Privacy Tech 30:45 – Securitization of Other Assets Under the Blockchain 34:16 – Prediction Markets 35:09 – Incremental Revenue Through GPU Usage 37:19 – Jeremy's 10 Year Future Vision 41:12 – AI and GDP 44:00 – Conclusion

What happens when you apply the scaling laws of large language models to the physical work of atoms? Elad Gil sits down with Liam Fedus, co-founder at Periodic Labs, which is pioneering an AI foundation lab for atoms. Liam discusses how he pivoted from dark matter physics research to the front lines of artificial intelligence, including stints at Google Brain and working on ChatGPT at OpenAI. He talks about how Periodic is connecting massive language models to the physical world to overcome data bottlenecks in material science. Liam also shares how they use language models as an orchestration layer operating alongside specialized neural nets to run closed-loop physical experiments. They also explore the future of AGI and ASI, as well as the role of robotics in lab automation. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @LiamFedus | @periodiclabs Chapters: 00:00 – Cold Open 00:05 – Liam Fedus Introduction 00:39 – Liam's Background at Google Brain, OpenAI 05:14 – From ChatGPT to Materials and Atoms 06:34 – Training Data in the Physical World 09:52 – Generalization Across Domains 11:31 – Models as an Orchestration Layer 12:48 – Commercialization and Business Model 16:10 – How Periodic's Success May Shape the Future  17:45 – Multidisciplinary Scaling 19:41 – Capital and Compute 21:12 – Hiring at Periodic 21:44 – Thoughts on AGI and ASI 23:30 – Timeline for Machine-Directed Self-Improvement 25:39 – Automation and Data Generation 27:59 – Why Liam is Excited About the Future of Robotics 29:25 – Conclusion

Elad Gil, investor and author of High Growth Handbook, sits down with South Park Commons Partner Aditya Agarwal to challenge some of Silicon Valley's favorite startup myths. He talks about why you might not actually need a cofounder, why data alone isn't much of a moat, and how the strongest companies build real defensibility while others quietly fall behind.Elad also walks us through his approach to exit hygiene, what the Slack vs. Teams battle says about the power of incumbents, and why some of the worst advice in Silicon Valley isn't directed at struggling startups but the ones already winning. Elad Gil: https://x.com/eladgil Aditya Agarwal: https://x.com/adityaag South Park Commons: https://www.linkedin.com/company/southparkcommons/Apply to SPC: https://www.southparkcommons.com/applyChapters:(00:01:31) - Approaches to starting a company in the age of AI(00:05:03) - The cofounder fallacy (00:06:22) - Winning is the only startup culture that matters(00:08:00) - Why more markets are open right now than ever before(00:10:14) - The oligopoly market (00:21:13) - Product surface area beats data as a real competitive moat(00:24:12) - The failure mode no one discusses: bad advice for working companies(00:32:11) - How many Jensen Huangs are hiding in plain sight right now?(00:40:08) - Pre-scheduling exit conversations as annual board hygiene(00:43:54) - Why micromanagement is actually underrated

Qasar Younis is the co-founder and CEO of Applied Intuition, a $15 billion AI company that adds intelligence to cars, tractors, planes, submarines, and other vehicles—essentially, Tesla or Waymo without the hardware. He was previously COO of Y Combinator, started his career as an engineer at GM and Bosch, and was born on a farm in Pakistan.We discuss:1. Why the biggest AI revolution will play out in mining, farming, construction, and trucking over the next 5 to 10 years, not in software2. Why Qasar intentionally stayed under the radar for nearly a decade while building Applied Intuition, and why most founders shouldn't do that3. The truth about China's AI capabilities and why comparisons to American companies are fundamentally flawed4. The company values that drive Applied Intuition: speed above everything, laugh a lot, half the work is follow-up, never disappoint the customer5. The biggest lessons from Qasar's stint as YC's COO, including that the most successful companies show traction very early6. How reading old books is the best way to build taste—Brought to you by:Omni—AI analytics your customers can trustVanta—Automate compliance. Simplify security.Lovable—Build apps by simply chatting with AI—Episode transcript: https://www.lennysnewsletter.com/p/the-most-successful-ai-company-youve-never-heard-of—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Qasar Younis:• X: https://x.com/qasar• LinkedIn: https://www.linkedin.com/in/qasar• Website: https://qy.co• Reading list: https://qy.co/books—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 Qasar and Applied Intuition(04:01) The optimistic vision: How AI will create abundance(08:49) Why anxiety about AI comes from misunderstanding—and how to fight fear with knowledge(12:58) The market sell-off explained(16:31) Self-driving cars: Why 30,000 annual deaths prove we need autonomy now(20:22) The spectrum of physical AI(28:00) How AI is coming just in time(33:26) Why comparing Chinese AI companies to American AI companies is a category error(39:12) Why Qasar finally joined Twitter after staying silent for a decade(45:08) Why successful companies almost always show early signs of traction(50:40) Applied Intuition's core values(56:00) Why the company cleans its own office—and never spent a dollar of raised capital(58:50) Quasar's reading philosophy(01:06:14) How to operationalize listening to naysayers(01:12:53) The importance of decisiveness(01:14:55) Removing emotions from decisions(01:19:02) Why most Silicon Valley CEOs don't have great taste—and how to develop it—Referenced:• Applied Intuition: https://www.appliedintuition.com• Marc Andreessen: The real AI boom hasn't even started yet: https://www.lennysnewsletter.com/p/marc-andreessen-the-real-ai-boom• Elad Gil's website: https://eladgil.com• Bosch: https://www.bosch.com• Berkshire Hathaway: https://www.berkshirehathaway.com• Naval Ravikant on X: https://x.com/naval• Y Combinator: https://www.ycombinator.com• Waymo: https://waymo.com/• Tesla: https://www.tesla.com• DeepSeek: https://www.deepseek.com• Rivian: https://rivian.com• Crate & Barrel: https://www.crateandbarrel.com• OpenClaw: https://openclaw.ai• Sam Altman on X: https://x.com/sama• Peter Ludwig on LinkedIn: https://www.linkedin.com/in/peterwludwig• What Steve Jobs really meant when he said ‘Good artists copy; great artists steal': https://www.cnet.com/tech/tech-industry/what-steve-jobs-really-meant-when-he-said-good-artists-copy-great-artists-steal• 7 quotes on the power of reading from Charlie Munger: https://www.neil.blog/articles/7-quotes-power-reading-charlie-munger• Andreessen Horowitz: https://a16z.com• John Doerr on LinkedIn: https://www.linkedin.com/in/john-doerr-03248211• Gandhi's quote: https://www.azquotes.com/author/5308-Mahatma_Gandhi/tag/truth#google_vignette• Steve Ballmer on X: https://x.com/Steven_Ballmer• General Motors: https://www.gm.com—Recommended books:• House of Huawei: The Secret History of China's Most Powerful Company: https://www.amazon.com/House-Huawei-History-Powerful-Company/dp/0593544633• Maintenance: Of Everything, Part One: https://press.stripe.com/maintenance-part-one• The Autobiography of Malcolm X: As Told to Alex Haley: https://www.amazon.com/Autobiography-Malcolm-Told-Alex-Haley/dp/0345350685• High Output Management: https://www.amazon.com/High-Output-Management-Andrew-Grove/dp/0679762884• The Emperor of All Maladies: A Biography of Cancer: https://www.amazon.com/Emperor-All-Maladies-Biography-Cancer/dp/1439170916• Made in America: https://www.amazon.com/Sam-Walton-Made-America/dp/0553562835• My American Journey: https://www.amazon.com/American-Journey-Autobiography-Colin-Powell/dp/0679432965• Guns, Germs, and Steel: The Fates of Human Societies: https://www.amazon.com/Guns-Germs-Steel-Fates-Societies/dp/0393317552• Collapse: How Societies Choose to Fail or Succeed: https://www.amazon.com/Collapse-Societies-Choose-Succeed-Revised/dp/0143117009• SPQR: A History of Ancient Rome: https://www.amazon.com/SPQR-History-Ancient-Mary-Beard/dp/0871404230• A World Appears: A Journey into Consciousness: https://www.amazon.com/World-Appears-Journey-into-Consciousness/dp/198488199X—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

Elad Gil was an early investor in 40 unicorns, including major AI companies like Perplexity. I asked him what's next for software companies now that AI can code better than humans, and what he'd invest in after AI. Elad Gil is the Founder & Investor at Gil Capital, his private investment firm. He has backed some of the most iconic technology companies of the past two decades, including Airbnb, Stripe, Coinbase, Instacart, OpenAI, and SpaceX. A former executive at Twitter and Google, Elad is known for identifying major technology waves early — from social to SaaS to AI — and helping founders build category-defining companies. Sponsored byZapier More interviews -> https://mixergy.com/moreint Rate this interview -> https://mixergy.com/rateint

From “virtual doppelgängers” to “real-time dreaming,” online gaming platform Roblox is using AI technology to build the “Holodeck” envisioned in science fiction decades ago. Sarah Guo and Elad Gil sit down with Roblox CEO Dave Baszucki at Roblox headquarters to explore the intersection of AI, physics simulation, and the future of human connection. Dave discusses the evolution of the 4D creation tool in Roblox, a high-fidelity simulation that enables thousands of people to interact in real-time with photo-realistic graphics and acoustic physics. Dave reveals how Roblox is leveraging 13 billion hours of monthly user data to train native AI models that go beyond simple LLMs, enabling NPCs that can navigate and play games with human-like intuition. He also talks about how immersive communication will change video conferencing, how Roblox searches for unlikely talent outside of traditional elite universities, and how he balances rapid weekly iterations with keeping a “long view” on Roblox's vision.  Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @DavidBaszucki | @Roblox  Chapters: 00:00 – Cold Open 00:36 – Dave Baszucki Introduction 01:16 – Realizing Robolox's 20-Year Vision 05:29 – Using 4D Immersive Simulations in Virtual Interactions 08:22 – Physics Engine vs. Photorealism  11:50 – Storing Roblox History as Vector Data 14:00 – Training NPCs - Moving Beyond LLMs 18:05 – The Future of the Game Designer 19:54 – Video Latent World Models 23:53 – Social Simulation - AI Companions and Virtual Relationships 27:26 – Why Asset Costs Haven't Changed the Gaming Industry 29:52 – AI Coding in Roblox Studio 31:36 – The Roblox Creator Economy 33:57 – Long-Term Conviction vs. Weekly Iteration 37:50 – Dave's Hiring Philosophy for Roblox 43:44 – Conclusion

Winston Weinberg is the CEO and Co-Founder of Harvey, the leading professional services platform engineered with AI for law, tax, and finance. Winston has raised over $980M for Harvey from Sequoia, a16z, GV, Elad Gil and more with a last round price of $9.2BN post-money. Before founding Harvey in August 2022, Winston was an attorney at O'Melveny & Myers LLP, specializing in antitrust and securities litigation.  AGENDA: 04:10 #1 Thing Every Founder Needs to Do Everyday 05:33 Must Do Daily Routines and Productivity Tips for CEOs 12:45 How to Get Sequoia and a16z Term Sheets 15:06 Why VCs Suck at Helping Companies Hire? 27:01 What No One Understands About Enterprise AI Adoption 38:06 AI's Impact on Professional Services 39:26 Future of Law Firms: Do They Die? 43:38 What Everyone Should Know That No One Tells You About Hiring in Europe 47:08 I Have Massive Trust Issues… 54:17 Biggest Lessons on Effective Deal-Making  59:20 Cold Emailing OpenAI and It Leading to a Term Sheet 01:02:33 Quick Fire Round Try NEXOS.AI for yourself with a 14-day free trial: https://nexos.ai/20vc  

Today's arms race looks a little different from those of the past. Under the Trump administration, the US Department of War (DoW) is deploying generative AI to millions of employees in order to maintain a strategic edge over our global adversaries. Sarah Guo and Elad Gil sit down with Emil Michael, the Under Secretary of War for Research and Engineering of the United States, to discuss the radical technological transformation of the US military. Emil outlines the architecture and launch of GenAI.mil, a DoW internal AI platform powered by Gemini and Grok that reached over one million unique users in its first 30 days. He also highlights critical technology priorities for national security, including hypersonics, direct energy, and autonomous drone swarms. Together, they also explore the urgent need to rebuild the American defense industrial base and end dependency on foreign supply chains for critical materials, as well as how Emil is recruiting the next generation of “fixer-builder” workers to serve their country in government.  Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @USWREMichael | @DoWCTO Chapters: 00:00 – Cold Open 00:00 – Emil Michael Introduction 00:58 – Emil's Role at the Department of War 05:22 – Innovation Priorities for the DoW 08:27 – Shift Toward Autonomous Defense Technologies 10:41 – Identifying Common Needs Across the DoW 12:02 – Architecting GenAI.mil 13:48 – Applied AI Initiatives at the DoW 15:57 – The Future of Warfare 17:55 – Recruiting for DoW 19:33 – Arsenal of Freedom Tour 22:25 – Opportunities for Entrepreneurs at DoW 25:49 – Speeding Up and Scaling DoW Initiatives 28:37 – Innovation in Defense Tech 30:00 – Change Management in Government 32:09 – Rebuilding the Defense Industrial Base 37:27 – Initiatives and Opportunities at the Office of Strategic Capital 41:41 – Lessons from Emil's Government Experience 44:30 – Conclusion

Even if ChatGPT never existed, the tech giant NVIDIA would still be winning. The end of Moore's Law—says NVIDIA President, Founder, and CEO Jensen Huang—makes the shift to accelerated computing inevitable, regardless of any talk of an AI “bubble.” Sarah Guo and Elad Gil are joined by Jensen Huang for a wide-ranging discussion on the state of artificial intelligence as we begin 2026. Jensen reflects on the biggest surprises of 2025, including the rapid improvements in reasoning, as well as the profitability of inference tokens. He also talks about why AI will increase productivity without necessarily taking away jobs, and how physical AI and robotics can help to solve labor shortages. Finally, Jensen shares his 2026 outlook, including why he's optimistic about US-China relations, why open source remains essential for keeping the US competitive, and which sectors are due for their “ChatGPT moment.”  Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @nvidia Chapters: 00:00 – Jensen Huang Introduction 00:17 – Biggest AI Surprises of 2025 04:12 – AI and Jobs: New Infrastructure and Demand for Skilled Labor 09:03 – Task vs. Purpose Framework in Labor 12:31 – Solving Labor Shortages with Robotics 15:14 – The Layer Cake of AI Technology 18:39 – The Importance of Open Source 21:52 – The Myth of “God AI” and Monolithic Models 23:54 – Addressing the “Doomer” Narrative and Regulation 29:25 – The Plummeting Cost of Compute and Tokenomics 35:09 – The Return to Research 37:49 – Future of Coding and Software Engineering 43:20 – The Industries Due For Their “ChatGPT” Moments 46:00 – The Evolution of Self-Driving Cars and Robotics 54:06 – Energy Demand and Growth for AI 58:49 – 2026 Outlook: US-China Relations and Geopolitics 1:04:43 – Is There An AI Bubble? 1:16:20 – Conclusion

Pundits are screaming about the so-called “AI bubble.” But historically slow-to-adopt industries like medicine and law are actually embracing AI at an unprecedented speed. Sarah Guo and Elad Gil look ahead to 2026, breaking down the major trends that will define the next era of AI technologies. They explore the future of AI foundational models, predicting breakthroughs in solving complex scientific problems. They share competing views on the timeline for robotics and self-driving cars, debating whether startups have a chance for survival or if incumbents will dominate. Elad and Sarah also discuss the return of tech IPOs and M&As, forecast a new wave of AI consumer agent software, and explore why consumer product innovation has been slower than expected. Finally, the two offer bold non-AI predictions for the new year, including the acceleration of defense tech startups and the second-order underrated impacts of GLP-1 drugs on biohacking. Plus, stick around to hear predictions on what's next for AI in 2026 from some of tech's biggest names and industry leaders. We hear from Jensen Huang (Founder/CEO NVIDIA), Arvind Jain (Founder/CEO, Glean), Winston Weinberg (Founder/CEO, Harvey), Scott Wu (Founder/CEO, Cognition), Raiza Martin (Founder/CEO Huxe), Zach Ziegler (Founder/CTO, Open Evidence), Aaron Levie (Founder/CEO, Box), Misha Laskin (Founder/CEO, ReflectionAI), Noam Brown (Research Scientist, OpenAI), Joshua Meier (Founder/CEO Chai Discovery), Bryan Johnson (Living Man, Don't Die), Sholto Douglas (Member of the Technical Staff, Anthropic), Ben & Asher Spector (Stanford PhDs) and Dylan Patel (Founder/CEO SemiAnalysis). Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Chapters: 00:00 – Introduction 02:43 – AI Predictions for 2026 04:40 – Adoption of AI in Professional Fields 07:17 – Robotics and Self-Driving Cars 08:25 – Robotics: Incumbents vs. Startups 13:59 – Future of IPOs and M&A in AI 16:42 – Challenges in Consumer AI Innovation 21:08 – Funding of Neo Labs, RL Research 26:28 – Predictions for 2026 Beyond AI 26:44 – The Future of Defense and Technology 28:23 – Biohacking and Peptide Therapies 30:37 – 2026 Prediction from AI Industry Leaders 40:46 – Conclusion

In just over three years, Harvey has not only scaled to nearly one thousand customers, including Walmart, PwC, and other giants of the Fortune 500, but fundamentally transformed how legal work is delivered. Sarah Guo and Elad Gil are joined by Harvey's co-founder and president Gabe Pereyra to discuss why the future of legal AI isn't only about individual productivity, but also about putting together complex client matters to make law firms more profitable. They also talk about how Harvey analyzes complex tasks like fund formation or M&A and deploys agents to handle research and drafting, the strategic reasoning behind enabling law firms rather than competing with them, and why AI won't replace partners but will change law firm leverage models and training for associates. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @gabepereyra | @Harvey Chapters: 00:00 – Gabe Pereyra Introduction 00:09 – Introduction to Harvey 02:04 – Expanding Harvey's Reach 03:22 – Understanding Legal Workflows 06:20 – Agentic AI Applications in Law 09:06 – The Future Evolution of Law Firms 13:36 – RL in Law 19:46 – Deploying Harvey and Customization 23:46 – Adoption and Customer Success 25:28– Why Harvey Isn't Building a Law Firm 27:25 – Challenges and Opportunities in Legal Tech 29:26 – Building a Company During the Rise of Gen AI 37:24 – Hiring at Harvey 40:19 – Future Predictions 44:17 – Conclusion 

Over the last year, certain AI markets appear to be nearly sewn up by startup market leaders. Plus, Locket's social app is using iOS Live Activities to reach Gen Alpha via the iPhone Lock Screen. Learn more about your ad choices. Visit podcastchoices.com/adchoices

2025 has thus far been a year of great leaps and advances in AI technology. And Sarah and Elad have spoken with some of the most enterprising founders and scientific minds in the field of AI today. So we're revisiting a few of our favorite conversations on No Priors so far in 2025 – Winston Weinberg (Harvey), Dr. Fei-Fei Li (World Labs), Brendan Foody (Mercor), Dan Hendrycks (Center for AI Safety), Noubar Afeyan (Flagship Pioneering), Brandon McKinzie and Eric Mitchell (OpenAI o3), Isa Fulford (OpenAI), Arvind Jain (Glen), and Dr. Shiv Rao (Abridge).  Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil  Chapters: 00:00 – Episode Introduction 0:21 – Winston Weinberg on Leaning into New Capabilities 02:01 – Dr. Fei-Fei Li on Spatial Intelligence 04:13 – Brendan Foody on AI Disruption in the Workforce 06:10 – Dan Hendrycks on the Geopolitics of Superintelligence 08:06 – Noubar Afeyan on Entrepreneurship   10:38 – Brandon McKinzie and Eric Mitchell on Reasoning Models 12:41 – Isa Fulford on Training Deep Research 13:49 – Arvind Jain on Innovating Enterprise Search 16:21 – Dr. Shiv Rao on AI's Human Impact 18:58 – Conclusion

For decades, the developer terminal has remained largely unchanged. But for Warp CEO and co-founder Zach Lloyd, reinventing this core tool is the key to unlocking AI agents for coding, debugging, and automating the entire development process. Zach joins Elad Gil to discuss how seeing this opportunity for innovation led to Warp's agentic terminal for developers. Zach talks about the phases of software development, from coding by hand to the current "develop by prompt" era, and the coming age of fully automated development. Plus, Zach and Elad explore the deep philosophical questions around intelligence versus consciousness in AI models, and what it would take to believe a computer program is truly aware. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @zachlloydtweets | @warpdotdev Chapters: 00:00 – Zach Lloyd Introduction 00:32 – AI, Intelligence, and Consciousness 06:55 – What Warp Does 07:38 – Benefits of the Terminal as a Launchpoint  08:27 – Features Driving Warp's Adoption 09:12 – Zach's View of the Coding Market 10:27 – Evolution of Coding Development 12:45 – Importance of Senior Engineer Expertise 14:11 – Future of Security and Other Dev Tools 22:22 – Why Zach Focused on the Terminal 23:52 – The Future of the Model Layer  25:36 – What Zach's Excited About in the AI Dev World 27:18 – Conclusion

Today's show:*Amazon's dropping a LOT of employees for AI and robots… are Jason's darkest predictions coming true?Legendary investor Elad Gil joins Jason and Alex for the full show today! Together, they're digging into the Amazon news, looking back at Jason's predictions from just last month, and theorizing about just how many people will lose their jobs to computers, and what we're going to do about it. (Is it possible the US hasn't been massively hit by job displacement so far because those gigs already moved overseas?)PLUS… Anthropic's Dario Amodei responds to criticisms from JCal's bestie David Sacks, Sesame emerges from stealth to work on AI wearables, and where will people in the future interact with their favorite apps? A headset? Phones? Somewhere else? The great debate continues.Timestamps:(00:04:04) Our guest is iconic angel investor Elad Gil! What's he working on…(00:04:54) Alexandria AI translates public domain books into all commonly spoken languages… Do people actually prefer AI translations?(00:09:16) Why compute tends to centralize over time… (It's because of economies of scale!)(00:09:29) Squarespace - Use offer code TWIST to save 10% off your first purchase of a website or domain at https://www.Squarespace.com/TWIST(00:12:49) So are we building TOO MANY datacenters? Will AI apps eventually run on your phone anyway?(00:16:39) Jason says “The Age of Efficiency is upon us.”(00:19:24) When companies trade inference for market share(00:19:27) Sentry - New users get 3 months free of the Business plan (covers 150k errors). Go to http://sentry.io/twist and use code TWIST(00:21:57) Why one of the main challenges of adopting AI is buy-in and convincing teams to use it.(00:25:47) Elad's robotics questions: (1) What % of winners will be incumbents?(00:27:50) Jason called the Amazon news last month and we have the receipts!(00:29:36) Pilot - Visit https://www.pilot.com/twist and get $1,200 off your first yea(00:45:33) Jason says Adobe and Figma should abandon the UK entirely.(00:45:55) Time for a Polymarket: The sharps say 80% chance Tesla beats their quarterly earnings(00:51:02) What is Sesame? They just emerged from stealth, they raised $250M, and they're working on AI wearables.(00:53:21) Jason has concerns about AI wearables that are always recording… Does Elad share these concerns?(01:03:17) The crypto industry is now one of the largest purchasers of US government debt… what does that mean? Who owns who?(01:08:53) Anthropic responded to JCal's Bestie David Sacks… Is Dario Amodei a doomer? Fearmongering?(01:19:12) Why Jason thinks AI companies need to self-regulateSubscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpFollow Lon:X: https://x.com/lonsFollow Alex:X: https://x.com/alexLinkedIn: ⁠https://www.linkedin.com/in/alexwilhelmFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisThank you to our partners:Squarespace - Use offer code TWIST to save 10% off your first purchase of a website or domain at https://www.Squarespace.com/TWISTSentry - New users get 3 months free of the Business plan (covers 150k errors). Go to http://sentry.io/twist and use code TWISTPilot - Visit https://www.pilot.com/twist and get $1,200 off your first yeaGreat TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason's suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.comSubscribe to the Founder University Podcast: https://www.youtube.com/@founderuniversity1916

Zach Lloyd is the Founder and CEO of Warp, the next-generation developer terminal reinventing how engineers build and collaborate. Warp has raised over $70M from top-tier investors including Sequoia Capital, GV, Dylan Field, and Elad Gil. Before founding Warp, Zach was Principal Engineer at Google, where he led development of Google Docs, and later served as CTO at Time. He's one of the most respected engineering minds redefining the future of developer tools. AGENDA:  04:14 Biggest Product Lessons from Rewriting Google Sheets 07:10 Why I Would Short Google: Leadership and AI Strategy 09:55 Comparing AI Models: GPT, Claude, and Gemini: Who Wins and Loses 17:04 Do Margins Matter in AI? 24:57 Adding $1M in ARR Every Week: Is Triple, Triple, Double, Double Dead? 33:58 How to Build Defensibility in a World of AI? 43:05 OpenAI vs Anthropic: Who Wins and Why? 44:25 Biggest Fundraising Lessons Raising from Sequoia, Elad Gil and GV 50:56 Why Sequoia are the Best VC 53:51 What Every Founder Gets Wrong in Fundraising 01:01:30 Quick Fire Questions and Final Thoughts  

With demand from AI for energy already exploding, our electric grid is facing a crisis. Base Power CEO and co-founder Zach Dell is ready to re-architect its future from the ground up. Zach sits down with Elad Gil to talk about Base Power's recent $1 billion fundraise from major investors. Zach discusses the role of energy across industries, as well as Base Power's mission to lower electricity costs through vertical integration. Zach and Elad also explore the future of energy, the role of batteries in transforming the grid, and the regulatory challenges facing the energy industry. Plus, Zach pitches why top talent should make their careers in energy generation.   Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @ZachBDell | @basepowerco Chapters: 00:00 – Zach Dell Introduction 00:50 – Base Power's Vision 02:15 – Base Power's Products and Services  04:00 – What Drew Zach to Working on Power 05:12 – Base Power's Founding Team 06:58 – Base Power's Hiring Needs 08:02 – How Zach Hired an Awesome Founding Team 09:51 – How Do We Meet Energy Demands? 12:58 – How Viable is Nuclear Energy? 17:04 – Global Energy Cost Dynamics 17:41 – Future of AI Training Centers 18:32 – What Will Drive Energy Buildout 20:38 – Drivers of Energy Transmission Cost 22:30 – Regulation and the Energy Industry  23:52 – What Zach is Optimistic About in Energy 24:42 – Cultivating Base Power's Culture 27:26 – Zach's Philosophy on Capitalization 30:00 – How Base Power Uses Scale 31:57 – Conclusion

Between the future of search, the biggest threats in cybersecurity, and the jobs and platforms of tomorrow, Nikesh Arora sees one common thread connecting and transforming them all—AI. Sarah Guo and Elad Gil sit down with Nikesh Arora, CEO of cybersecurity giant Palo Alto Networks, to talk about a wide array of topics from agentic AI to leadership. Nikesh dives into the future of search, the disruptive potential of AI agents for existing business models, and how AI has both compressed the timeline for cyberattacks as well as fundamentally shifted defense strategies in cybersecurity. Plus, Nikesh shares his leadership philosophy, and why he's so optimistic about AI.  Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @nikesharora | @PaloAltoNtwks  Chapters: 00:00 – Nikesh Arora Introduction 00:39 – Nikesh on the Future of Search 04:46 – Shifting to an Agentic Model of Search 08:12 – AI-as-a-Service 16:55 – State of Enterprise Adoption 20:15 – Gen AI and Cybersecurity 27:35 – New Problems in Cybersecurity in the AI Age 29:53 – Deepfakes, Spearfishing, and Other Attacks 32:56 – Expanding Products at Palo Alto 35:49 – AI Agents and Human Replaceability  44:28 – Nikesh's Thoughts on Growth at Scale 46:52 – Nikesh's Leadership Tips 51:14 – Nikesh on Ambition 54:18 – Nikesh's Thoughts on AI 58:21 – Conclusion

What if kids could master their academics in just two hours a day and spend the rest of their time developing real-world skills they're passionate about? Joe Liemandt, founder of the software company Trilogy, is doing just that. Sarah Guo and Elad Gil are joined by Joe Liemandt, principal of Alpha School, to discuss his AI-driven vision of reinventing K-12 education. Joe talks about the strategies that Alpha School employs: reducing the traditional six-hour school day to two, replacing teachers with “Guides,” using financial incentives as motivation, and dedicating the remainder of the school day to project-based workshops that reflect the students' passions. Together, they also examine Joe's plan to scale Alpha School, the youth mental health crisis, and why edtech so far has failed. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @AlphaSchoolATX Chapters: 00:00 – Joe Liemandt Introduction 00:27 – From Trilogy to Alpha School 02:45 – How Joe Changed His Mind About Alpha School 04:16 – Reenvisioning the School Day 09:06 – An Example Day at Alpha School 20:13 – Educating Based on Motivations 22:56 – Incentives-Based Learning 24:40 – Standards for Guides 26:39 – Extrinsic vs. Intrinsic Motivators 35:12 – Tackling Learning Differences  39:13 – Alpha School Pricing Structure 43:08 – Education Tech at Alpha School 44:54 – Rebuilding Education in the AI Age 48:43 – Reforming Education Policy 56:25 – Ed Tech as a Product 58:58 – Fixing Gaps in Education 59:45 – Why Education is Joe's Mission 01:01:49 – Conclusion

The traditional call center may soon be a thing of the past. Jessie Zhang is building AI agents designed to replace monotonous human labor and transform how consumers interact with brands. Elad Gil sits down with Jesse Zhang, co-founder and CEO of Decagon, an AI agent company at the forefront of AI customer service. Jesse talks about how Decagon secured large enterprise clients and the impact of its AI agents, his journey as a second-time founder, and Decagon's company culture. Plus, they discuss what the future of agentic customer service may look like. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @thejessezhang | @DecagonAI  Chapters: 00:00 – Jesse Zhang Introduction 00:30 – Decagon's Services 01:11 – Decagon's Customers and Growth 02:41 – Productivity Gains with Decagon 03:33 – How Decagon Integrates in Customer Workflows 04:25 – Jesse's Second Time Founder Story 05:41 – Jesse's Hiring Philosophy 09:13 – Counter-intuitive Advice for Founders 11:19 – How Decagon Thinks About Talent 14:12 – Areas for Longer Term Planning 15:37 – Decagon's Path to Customer Service 16:57 – Thoughts on Pushing Into the Application Layer 19:40 – What Decagon Does Uniquely  22:05 – Pricing Services in the AI Age 24:46 – How Decagon Sees Customer Service 25:53 – Defining Long-Term Success for Decagon 27:41 – Jesse's Views on an Agentic Future 31:22 – Conclusion

From negotiating with world leaders to partnering with top entrepreneurs, businessman and investor Jared Kushner has traveled the unique path of bringing private sector knowledge to government work and back again. Jared Kushner joins Sarah Guo and Elad Gil to cover a wide range of topics, from his founding of investment firm Affinity Partners, to his time in government, to his new AI venture BrainCo. Jared discusses Affinity Partners' mission and strategy, how he has leveraged his government experience in business and investing, and the geopolitics of technological advancements like AI. Plus, he makes a case for why private sector talent should do “tours of duty” in government. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jaredkushner Chapters: 00:00 – Jared Kushner Introduction 00:30 – Starting Affinity Partners Post-Government 01:59 – Value of Global Perspective 03:34 – Ventures with Affinity 05:14 – Evaluating Investments Via Macro Trends 09:09 – Undervalued Countries 12:32 – Origins of BrainCo 16:50 – BrainCo Use Cases 23:49 – BrainCo's Biggest Challenge 24:47 – Determining Customer Fit 26:39 – AI and Policy 30:03 – Middle East and AI 31:59 – Jared's Experience in Middle East Diplomacy 40:16 – Brokering Peace Post-October 7th 43:52 – Making Deals with Middle Eastern Partners 47:14 – Jared and Ivanka's Partnership 49:18 – Benefits of Joining Public Sector from the Private Sector 52:07 – Jared's Pitch for Serving in Government 56:25 – Jared's Leadership Style 58:24 – Conclusion

How does a new technology get adopted by 40% of American doctors in just 18 months? In an era where the golden age of biotechnology has also created a dark age of physician burnout, OpenEvidence found the answer by fundamentally changing how doctors access critical information. OpenEvidence founder Daniel Nadler sits down with Sarah Guo and Elad Gil to discuss how his company solved the semantic search problem in medicine. He talks about the strategy of treating doctors as consumers, striking the balance of keeping patients in the loop in medical conversations, and how technology will reshape both medicine and medical education. Plus, Daniel gives his thoughts on the roots of motivation, as well as his philosophy for recruitment.  Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @EvidenceOpen  Chapters: 00:00 – Daniel Nadler Introduction 00:08 – OpenEvidence's Success  01:54 – How OpenEvidence Works 06:35 – Dealing with Ambiguity 11:37 – Treating Knowledge Workers as Consumers 15:53 – Balancing Keeping Patients in the Loop 19:28 – How Technology May Shape the Future of Medicine 22:12 – How Technology Will Change Medical Education 30:40 – Examining Consumer Adoption of Preventative Health Measures 36:02 – Lessons for Other Fields 37:27 – Rationalism vs. Will 41:13 – Daniel's Thoughts on Motivation 42:44 – Daniel's Recruiting Philosophy 44:48 – Conclusion

AI doomers say that the technology will be the ultimate job-killer. But Jacob Helberg wants people to see AI as a tech that will boost, not replace, human workers and give them superpowers. Under Secretary of State for Economic Growth, Energy, and the Environment Jacob Helberg joins Sarah Guo and Elad Gil to talk about AI's role in reshoring manufacturing in America, supply chain security, and transforming the US energy grid. He also discusses the CapEx revolution, why he sees opportunity for tech and energy partnerships in the Middle East, and the path to more nuclear energy for the US. Plus, the three explore what the “superintelligence century” could look like. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @jacobhelberg  Chapters: 00:00 – Jacob Helberg Introduction 00:50 – Jacob's Agenda for Capitol Hill 01:53 – Reshoring the American Supply Chain 04:38 – Areas of CapEx Growth 06:56 – Importance of Supply Chain Security 08:52 – Reshoring Rare Earth Minerals 11:12 – How AI Can Help America Reindustrialize  15:37 – AI and Productivity Gains 17:38 – The Superintelligence Century 22:56 – Creating an Open Source AI Ecosystem 24:41 – The Middle East and AI 26:24 – Growing Energy Resources in the US 28:28 – The Path to More Nuclear Energy in the US 35:50 – Essential Domains for Strategy and Security 38:20 – The Tech Industry and the Administration 40:29 – Conclusion

How to prevent infighting, mitigate status races, and keep your people focused. Cross-posted from my Substack. Organizational culture changes rapidly at scale. When you add new people to an org, they'll bring in their own priors about how to operate, how to communicate, and what sort of behavior is looked-up to. Despite rapid changes, in this post I explain how you can implement anti-fragile cultural principles—principles that help your team fix their own problems, often arising from growth and scale, and help the org continue to do what made it successful in the first place. This is based partially on my experience at Wave, which grew to 2000+ people, but also tons of other reading (top recommendations: Peopleware by DeMarco and Lister, Swarmwise by Rick Falkvinge, High Growth Handbook by Elad Gil, The Secret of Our Success by Henrich, Antifragile by Nassim Nicholas Taleb, as well as Brian [...] ---Outline:(01:13) Common Problems(05:00) Write down your culture(06:25) That said, you don't have to write everything down(08:37) Anti-fragile values I recommend(09:02) Mission First(10:51) Focus(11:32) Fire Fast(12:58) Feedback for everything(13:50) Mutual Trust(15:48) Work sustainably and avoid burnout(17:42) Write only what's new & helpful--- First published: August 21st, 2025 Source: https://forum.effectivealtruism.org/posts/mLonxtAiuvvkjXiwq/the-anti-fragile-culture --- Narrated by TYPE III AUDIO.

Andrew Ng has always been at the bleeding edge of fast-evolving AI technologies, founding companies and projects like Google Brain, AI Fund, and DeepLearning.AI. So he knows better than anyone that founders who operate the same way in 2025 as they did in 2022 are doing it wrong. Sarah Guo and Elad Gil sit down with Andrew Ng, the godfather of the AI revolution, to discuss the rise of agentic AI, and how the technology has changed everything from what makes a successful founder to the value of small teams. They talk about where future capability growth may come from, the potential for models to bootstrap themselves, and why Andrew doesn't like the term “vibe coding.” Also, Andrew makes the case for why everybody in an organization—not just the engineers—should learn to code.  Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @AndrewYNg Chapters: 00:00 – Andrew Ng Introduction 00:32 – The Next Frontier for Capability Growth 01:29 – Andrew's Definition of Agentic AI 02:44 – Obstacles to Building True Agents 06:09 – The Bleeding Edge of Agentic AI 08:12 – Will Models Bootstrap Themselves? 09:05 – Vibe Coding vs. AI Assisted Coding 09:56 – Is Vibe Coding Changing the Nature of Startups? 11:35 – Speeding Up Project Management 12:55 – The Evolution of the Successful Founder Profile 19:23 – Finding Great Product People 21:14 – Building for One User Profile vs. Many 22:47 – Requisites for Leaders and Teams in the AI Age 28:21 – The Value of Keeping Teams Small 32:13 – The Next Industry Transformations 34:04 – Future of Automation in Investing Firms and Incubators 37:39 – Technical People as First Time Founders 41:08– Broad Impact of AI Over the Next 5 Years 41:49 – Conclusion

Cloudflare has spent nearly fifteen years making the Internet faster, more reliable, and more secure. So now that AI systems are changing the way we interact with the Internet, Cloudflare wants to help level the playing field for content creators. Sarah Guo and Elad Gil sit down with Matthew Prince, co-founder and CEO of Cloudflare to discuss the evolution of the internet from search to AI, including Cloudflare's role in facilitating that shift. Matthew talks about how AI assistants are changing the shape of the Internet, the problems Google created by making traffic the arbiter of content value, and how he sees Cloudflare's part in facilitating the new content marketplace for the mutual benefit of creators and AI companies. Plus, a look towards how agentic infrastructure may unfold in the near future. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @eastdakota | @Cloudflare Chapters: 00:00 – Matthew Prince Introduction 00:37 – Cloudflare's Role in Securing the Internet 02:08 – The Road to Cloudflare's Dominance 03:20 – The Internet's Shift from Search to AI 06:34 – Role of Agents and Content on the New Web 09:44 – Reshaping the Content Market Online 13:05 – De-emphasizing Traffic as a Proxy for Value 18:04 – Will We Run Out of Quality Human-Generated Content? 20:01 – Scaling the Value of Content in the AI Age 22:32 – Cloudflare's Approach to Inference 24:55 – How Cloudflare Responds to Market Demand 26:04 – Open vs. Closed Models 27:21 – Path to the New Marketplace for Content 30:58 – Advice for Content Creators 32:47 – Exploring the Timeline for Running Models Locally 40:07 – The Future of Agentic Infrastructure 44:52 – Conclusion

Qasar Younis is the co-founder and CEO of Applied Intuition, a leading vehicle intelligence platform that helps companies develop and deploy autonomous systems at scale. In June 2025, the company raised $600M at a $15B valuation. Before Applied Intuition, Qasar was the COO and a group partner at Y Combinator, and earlier founded TalkBin, which was acquired by Google. He's also held engineering roles at General Motors and Bosch. In today's episode, we discuss: • The two founder traits Silicon Valley undervalues • How to get 1–3 extra months of work done every year • Lessons from YC on pattern matching and founder feedback • The battle-tested startup formula Qasar used at Applied • Why co-founder fit is make-or-break • Applied's playbook: vertical SaaS, product-led GTM, and leveraging VC networks • Why Applied went multi-product in the early days • Contrarian takes on startup culture, compensation, and cost control • Why domain expertise is making a comeback • And much more… Referenced: • Applied Intuition: https://www.appliedintuition.com • Ansys: https://www.ansys.com • Bilal Zuberi: https://www.linkedin.com/in/bzuberi • Bosch: https://www.bosch.com • Elad Gil: https://www.linkedin.com/in/eladgil • General Motors: https://www.gm.com • “Google's Acquisition of TalkBin”: https://techcrunch.com/2011/04/25/google-acquires-talkbin-a-feedback-platform-for-businesses-thats-only-five-months-old/ • “High Output Management”: https://www.amazon.com/High-Output-Management-Andrew-Grove/dp/0679762884 • Kyle Vogt: https://x.com/kvogt • Marc Andreessen: https://x.com/pmarca • “Only the Paranoid Survive”: https://www.amazon.com/Only-Paranoid-Survive-Strategic-Inflection/dp/0385483821 • Paul Graham: https://x.com/paulg • Peter Ludwig: https://www.linkedin.com/in/peterwludwig • Sam Altman: https://x.com/sama • TalkBin: https://www.crunchbase.com/organization/talkbin • “The History of the Standard Oil Company”: https://www.amazon.com/History-Standard-Oil-Company-Volumes/dp/1519455860 • Waymo: https://waymo.com • Y Combinator: https://www.ycombinator.com • Zoox: https://zoox.com Where to find Qasar: • LinkedIn: https://www.linkedin.com/in/qasar/ Where to find Brett: • LinkedIn: https://www.linkedin.com/in/brett-berson-9986094/ • Twitter/X: https://twitter.com/brettberson Where to find First Round Capital: • Website: https://firstround.com/ • First Round Review: https://review.firstround.com/ • Twitter/X: https://twitter.com/firstround • YouTube: https://www.youtube.com/@FirstRoundCapital • This podcast on all platforms: https://review.firstround.com/podcast Timestamps: (01:26) Two founder traits Silicon Valley undervalues (04:23) Gain 1-3 extra months of productivity yearly (05:52) Why founders should read outside the startup canon (07:27) Lessons from YC (13:44) Why it's harder to start than to quit (15:52) The moment you become a real founder (20:24) How great founders master luck (21:46) Qasar's battle-tested startup formula (25:37) The founding insight for Applied (31:42) How Applied expanded beyond automotive (38:05) Why Applied went multi-product early (45:45) What no one says about startup secondaries (49:02) Why being cheap is a startup superpower (51:04) The myth of "competition doesn't matter" (53:50) Early scrappiness: The Sunnyvale house setup (54:50) Why domain knowledge is making a comeback (58:32) The mentors who shaped Qasar

Agenda: 00:00 - Why Benchmark Is Bleeding Partners (and Why That's the New Normal) 04:57 - “I Wouldn't Leave Benchmark… Unless I Had THIS” — Jason on Brand vs Autonomy 09:01 - The Rise of the Solo GP & The Death of LP Conventional Wisdom 13:50 - The Unstoppable Force of Elad Gil & The Myth of LP Discipline 18:45 - Is Vibe Coding the New SaaS? Jason's $10K/Month Spend Reveal 26:57 - Cursor's Growth Is Insane—But Is It Sustainable? 31:44 - Will Microsoft, Google, or Amazon Win the AI Infra War? 37:42 - Is GitHub Copilot the Biggest Miss in Microsoft's History? 44:15 - Are Big Tech Incumbents Now Too Powerful to Fail? 48:00 - Apple's AI Problem: Is It Time for a Management Overhaul? 52:30 - Figma's IPO: $30B Return, Zero Hype. What Happened? 1:06:00 - Final Bets: Cursor to $4B ARR, Lovable to $400M ARR, OpenAI to $800BN?      

Sriram Krishnan was never interested in policy. But after seeing a gap in AI knowledge at senior levels of government, he decided to lend his expertise to the tech-friendly Trump administration. Senior White House Policy Advisor on AI Sriram Krishnan joins Elad Gil and Sarah Guo to talk about America's AI Action Plan, a recent executive order that outlines how America can win the AI race and maintain its AI supremacy. Sriram discusses why winning the AI race is important and what that looks like, as well as the core goals of the Action Plan that he helped to author. Together, they explore how AI is the latest iteration of American cultural exportation and soft power, the bottlenecks in upgrading America's energy infrastructure, and the importance of America owning the “full stack” from GPUs and models to agents and software. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @skrishnan47 | @sriramk Chapters: 00:00 – Sriram Krishnan Introduction 01:00 – Sriram's Role in Government 03:43 – Impetus for the America AI Action Plan 06:14 – What Winning the AI Race Looks Like 10:36 – Algorithms and Cultural Bias 12:26 – Main Tenets of the America AI Action Plan 19:13 – Infrastructure and Energy Needs for AI 22:56 – Manufacturing, Supply Chains, and AI 24:52 – Ensuring American Dominance in Robotics 26:30 – Translating Policy to Industry and the Economy 29:30 – Should the US Be a Technocracy? 32:33 – Understanding the Argument Against Open Source Models 36:07 – Conclusion

In the generative AI revolution, quality data is a valuable commodity. But not all data is created equally. Sarah Guo and Elad Gil sit down with SurgeAI founder and CEO Edwin Chen to discuss the meaning and importance of quality human data. Edwin talks about why he bootstrapped Surge instead of raising venture funds, the importance of scalable oversight in producing quality data, and the work Surge is doing to standardize human evals. Plus, we get Edwin's take on what Meta's investment into Scale AI means for Surge, as well as whether or not he thinks an underdog can catch up with OpenAI, Anthropic, and other dominant industry players. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @echen | @HelloSurgeAI Chapters: 00:00 – Edwin Chen Introduction 00:41 – Overview of SurgeAI 02:28 – Why SurgeAI Bootstrapped Instead of Raising Funds 07:59 – Explaining SurgeAI's Product 09:39 – Differentiating SurgeAI from Competitors  11:27 – Measuring the Quality of SurgeAI's Output 12:25 – Role of Scalable Oversight at SurgeAI 14:02 – Challenges of Building Rich RL Environments 16:39 – Predicting Future Needs for Training AI Models 17:29 – Role of Humans in Data Generation 21:27 – Importance of Human Evaluation for Quality Data 22:51 – SurgeAI's Work Toward Standardization of Human Evals 23:37 – What the Meta/ScaleAI Deal Means for SurgeAI 24:35 – Edwin's Underdog Pick to Catch Up to Big AI Companies 24:50 – The Future Frontier Model Landscape 26:25 – Future Directions for SurgeAI 29:29 – What Does High Quality Data Mean? 32:26 – Conclusion

Is your career site delivering the conversion you need? Dalia's plug-and-play tech turns any employer career site into a high-performance candidate conversion engine — no replatforming required, live in days.Visit dalia.co to learn more. AND by jobcase, Jobcase is an online community where workers of all kinds – like hourly employees, tradespeople and healthcare technicians – access jobs, make connections, and support each other in any aspect of their work life.Visit jobcase.com/hire and tap into their 120 million strong  job seeker network First up…1848 Ventures, an AI-first venture studio building SaaS solutions for small and medium-sized businesses (SMBs) in the US, today announced it has led a $3 million seed funding round for Propel People, a mobile-first hiring platform built to help contractors hire skilled tradespeople faster. Propel People has also appointed industry veteran Dexter Bachelder as CEO, bringing deep expertise in construction tech and go-to-market execution to the growing company. https://hrtechfeed.com/1848-ventures-leads-3m-seed-round-for-propel-people/ WALNUT CREEK, Calif.—-BetterComp, a leading provider of compensation management software, today announced its $33M Series A funding round, led by Ten Coves Capital. The investment will fuel BetterComp's continued growth and innovation, enhance its AI-powered market pricing and pay recommendation capabilities, expand into new product adjacencies, and scale operations to better serve a rapidly growing global customer base. https://hrtechfeed.com/compensation-management-software-lands-33m-in-funding/ RICHMOND, Va — goHappy, the leading provider of innovative frontline employee engagement tools, today announced it has received a significant growth investment from Pamlico Capital, a private equity firm focused on high-growth technology and services businesses. The investment amount which was not mentioned… will support goHappy's next phase of growth as it continues to pursue its vision of helping employers drive stronger business outcomes through better engagement of their frontline teams. https://hrtechfeed.com/employee-engagement-tool-announces-investment/ Ashby, a rapidly growing company, has announced a successful $50 million Series D funding round. The investment was led by Mark McLaughlin at Alkeon, with co-lead support from existing investor Lachy Groom, and participation from F-Prime, Elad Gil, Gaingels, and other new and returning backers. https://hrtechfeed.com/ashby-raises-50-million-series-d/ SAN FRANCISCO—-CandorIQ, the AI-powered platform transforming how organizations plan and manage people spend, today announced a $4.8 million seed funding round led by Array Ventures, with participation from Y Combinator, CRV, and Switch Ventures. The funding will be used to grow CandorIQ's engineering and go-to-market teams, accelerate product development, and expand the platform's AI capabilities across compensation and workforce planning workflows. https://hrtechfeed.com/workforce-planning-tool-lands-4-8m/ The highly anticipated Monster/CareerBuilder auction has concluded, and the winning bidder is not JobGet, as some might have expected. Instead, BOLD Holdings emerged victorious with a staggering final bid of $28.4 million! Jobget emerged as the backup with a bid of $27 million. https://hrtechfeed.com/bold-holdings-snags-monster-careerbuilder-auction-for-28-4-million/ Learn more about your ad choices. Visit megaphone.fm/adchoices

When will fully autonomous vehicles see widespread adoption? According to Applied Intuition, that future is closer than you may think. Applied Intuition's CEO, Qasar Younis, and CTO, Peter Ludwig, talk with Elad Gil about how now is the best time to both work on self-driving vehicle technology and monetize it. Qasar and Peter discuss the advantages of developing their own OS in-house for their autonomous applications, self-driving technology's potential to drive re-shoring of vehicle manufacturing to the United States, and how best to gauge the bar for safety in autonomous systems. Plus, they explore how self-driving technology may reshape the designs of not only vehicles, but cities themselves. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @qasar | @AppliedInt Chapters: 00:00 Qasar Younis and Peter Ludwig Introduction 01:28 A Primer on Applied Intuition 11:08 Applied Intuition's Customers 12:04 Impact of Chinese Vehicles Manufacturers 15:44 EV Policies in the European Market 20:49 Can Robotics and Automation Re-Shore Vehicle Manufacturing? 21:53 Training Models for Autonomous Vehicles 26:41 Gauging the Bar for Autonomous Vehicles Safety 32:03 Timeline for Large-Scale Autonomous Vehicle Adoption 36:28 Rethinking Urban Design for Autonomous Vehicles 38:47 How Applied Intuition Uses AI for Tooling and OS 42:09 Designing for User Experience 43:31 Applied Intuition's Hiring Strategy 45:01 Conclusion

What happens when you give AI researchers unlimited compute and tell them to compete for the highest usage rates? Ben Mann, Co-Founder, from Anthropic sits down with Sarah Guo and Elad Gil to explain how Claude 4 went from "reward hacking" to efficiently completing tasks and how they're racing to solve AI safety before deploying computer-controlling agents. Ben talks about economic Turing tests, the future of general versus specialized AI models, Reinforcement Learning From AI Feedback (RLAIF), and Anthropic's Model Context Protocol (MCP). Plus, Ben shares his thoughts on if we will have Superintelligence by 2028.  Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @8enmann Links:  ai-2027.com/  Chapters: 00:00 Ben Mann Introduction 00:33 Releasing Claude 4 02:05 Claude 4 Highlights and Improvements 03:42 Advanced Use Cases and Capabilities 06:42 Specialization and Future of AI Models 09:35 Anthropic's Approach to Model Development 18:08 Human Feedback and AI Self-Improvement 19:15 Principles and Correctness in Model Training 20:58 Challenges in Measuring Correctness 21:42 Human Feedback and Preference Models 23:38 Empiricism and Real-World Applications 27:02 AI Safety and Ethical Considerations 28:13 AI Alignment and High-Risk Research 30:01 Responsible Scaling and Safety Policies 35:08 Future of AI and Emerging Behaviors 38:35 Model Context Protocol (MCP) and Industry Standards 41:00 Conclusion

We know WWDC might be underwhelming this year, but to what degree? Is Samsung about to pick Perplexity as its horse in the AI race? AI based acquisition and wrapups continue to be the new hotness in VC investing. And how DoorDash has quietly been killing it in the delivery space.Sponsors:AGNTCY.ORGQualiaLife.com/ride and code RIDELinks:Apple Developer Event Will Show It's Still Far From Being an AI Leader (Bloomberg)Samsung Nears Wide-Ranging Deal With Perplexity for AI Features (Bloomberg)Google quietly released an app that lets you download and run AI models locally (TechCrunch)Early AI investor Elad Gil finds his next big bet: AI-powered rollups (TechCrunch)Meta Aims to Fully Automate Ad Creation Using AI (WSJ)DoorDash CEO Tony Xu is taking on the role of industry consolidator in food delivery (CNBC)See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This episode is sponsored in part by Dalia—Talent teams are sitting on a powerful asset: candidate and lead data in their CRM. But knowing how—and when—to convert those leads into applicants and hires? That's the hard part. That's why Dalia is offering a free CRM Audit to help you unlock more value from the systems you've already invested in.…. Go to dalia.co/rectechcrm to get your free CRM audit today AND by jobcase, Jobcase is an online community where workers of all kinds – like hourly employees, tradespeople and healthcare technicians – access jobs, make connections, and support each other in any aspect of their work life.Visit jobcase.com/hire and tap into their 120 million strong  job seeker network Glider AI, the Skills Validation Platform™, today announced the launch of Agentic AI Interviews, a breakthrough solution that delivers real-time, human-like interviews in multiple languages—validating skills for any role through dynamic, two-way conversations and real-world tasks. https://hrtechfeed.com/glider-ai-launches-agentic-ai-interviews/ Yello, a leading provider of early talent acquisition software solutions, announces the launch of Hello App, a new mobile app to help employers create personalized and branded event experiences for candidates.  https://hrtechfeed.com/yello-launches-hello-app-for-campus-recruiting-events/ Cronofy, a UK-based provider of embedded interview/meeting scheduling infrastructure, has secured a £15 million investment from BGF, one of the UK and Ireland's most active growth capital investors. The funding will support Cronofy's ongoing expansion and product development as it continues to streamline complex scheduling processes for businesses globally. https://hrtechfeed.com/cronofy-lands-big-investment/ Rippling has raised $450M in new financing and signed agreements to repurchase up to $200M of equity from current and former employees. The financing includes investment from Elad Gil, Sands Capital, GIC, Growth Equity at Goldman Sachs Alternatives, Baillie Gifford, and Y Combinator, along with participation from existing investors. https://hrtechfeed.com/rippling-announces-series-g/  

What if the world's most connected tech investor handed you his mental playbook? Elad Gil, an investor behind Airbnb, Stripe, Coinbase and Anduril, flips conventional wisdom on its head and prioritizes market opportunities over founders. Elad decodes why innovation has clustered geographically throughout history, from Renaissance Florence to Silicon Valley, where today 25% of global tech wealth is created. We get into why he believes AI is dramatically under-hyped and still under-appreciated, why remote work hampers innovation, and the self-inflicted wounds that he's seen kill most startups.   This is a masterclass in pattern recognition from one of tech's most consistent and accurate forecasters, revealing the counterintuitive principles behind identifying world-changing ideas.  Disclaimer: This episode was recorded in January. The pace of AI development is staggering, and some of what we discussed has already evolved. But the mental models Elad shares about strategy, judgment, and high-agency thinking are timeless and will remain relevant for years to come. Approximate timestamps: Subject to variation due to dynamically inserted ads. (2:13) - Investing in Startups (3:25) - Identifying Outlier Teams (6:37) - Tech Clusters (9:55) - Remote Work and Innovation (11:19) - Role of Y Combinator (15:19) - The Waves of AI Companies (20:24) - AI's Problem Solving Capabilities (26:13) - AI's Learning Process (30:41) - Prompt Engineering and AI (32:00) - AI's Role in Future Development (34:37) - AI's Impact on Self-Driving Technology (40:16) - The Role of Open Source in AI (43:23) - The Future of AI in Big Players (44:23) - Regulation and Safety Concerns in AI (49:11) - Common Self-Inflicted Wounds (51:34) - Scaling the CEO and Avoiding Conventional Wisdom (55:21) - Workplace Culture (58:39) - Patterns Among Outlier CEOs (1:15:50) - Remote Work and its Implications (1:18:47) - The Impact of Clusters and Exceptional Individuals (1:25:41) - Investing in Defense Technology (1:27:38) - Business Model Shift in the Defense Industry (1:31:46) - Changes in Warfare SHOPIFY: Upgrade your business and get the same checkout I use. Sign up for your one-dollar-per-month trial period at shopify.com/knowledgeproject NORDVPN: To get the best discount off your NordVPN plan go to nordvpn.com/KNOWLEDGEPROJECT. Our link will also give you 4 extra months on the 2-year plan. There's no risk with Nord's 30 day money-back guarantee! Newsletter - The Brain Food newsletter delivers actionable insights and thoughtful ideas every Sunday. It takes 5 minutes to read, and it's completely free. Learn more and sign up at ⁠fs.blog/newsletter⁠ Upgrade — If you want to hear my thoughts and reflections at the end of the episode, join our membership: ⁠⁠⁠⁠⁠⁠⁠⁠fs.blog/membership⁠⁠⁠ and get your own private feed. Watch on YouTube: ⁠@tkppodcast Learn more about your ad choices. Visit megaphone.fm/adchoices

Aravind Srinivas is the co-founder and CEO of Perplexity AI, the world's first generally available conversation answer engine. Founded in August 2022 with Johnny Ho, Andy Konwinski, and Denis Yarats, Perplexity delivers accurate, sourced answers to any question. Born and raised in Chennai, India, Srinivas moved to the U.S. in 2017 and earned a PhD in Computer Science from the University of California, Berkeley, where he also taught a course in Deep Unsupervised Learning. He previously held prominent research roles at OpenAI, DeepMind, and Google, and he has positioned Perplexity as a leader in AI-powered information access with backing from top investors including Jeff Bezos, Elad Gil, Nat Friedman, and many others. ------ Thank you to the sponsors that fuel our podcast and our team: Squarespace https://squarespace.com/tetra Use code 'TETRA' ------ LMNT Electrolytes https://drinklmnt.com/tetra Use code 'TETRA' ------ Athletic Nicotine https://www.athleticnicotine.com/tetra Use code 'TETRA' ------ Sign up to receive Tetragrammaton Transmissions https://www.tetragrammaton.com/join-newsletter

2024 has been a year of transformative technological progress, marked by conversations that have reshaped our understanding of AI's evolution and what lies ahead. Throughout the year, Sarah and Elad have had the privilege of speaking with some of the brightest minds in the field. As we look back on the past months, we're excited to share highlights from some of our favorite No Priors podcast episodes. Featured guests include Jensen Huang (Nvidia), Andrej Karpathy (OpenAI, Tesla), Bret Taylor (Sierra), Aditya Ramesh, Tim Brooks, and Bill Peebles (OpenAI's Sora Team), Dmitri Dolgov (Waymo), Dylan Field (Figma), and Alexandr Wang (Scale). Want to dive deeper? Listen to the full episodes here: NVIDIA's Jensen Huang on AI Chip Design, Scaling Data Centers, and his 10-Year Bet No Priors Ep. 89 | With NVIDIA CEO Jensen Huang  The Road to Autonomous Intelligence, With Andrej Karpathy from OpenAI and Tesla No Priors Ep. 80 | With Andrej Karpathy from OpenAI and Tesla Transforming Customer Service through Company Agents, with Sierra's Bret Taylor No Priors Ep. 82 | With CEO of Sierra Bret Taylor OpenAI's Sora team thinks we've only seen the "GPT-1 of video models" No Priors Ep.61 | OpenAI's Sora Leaders Aditya Ramesh, Tim Brooks and Bill Peebles Waymo's Journey to Full Autonomy: AI Breakthroughs, Safety, and Scaling No Priors Ep. 87 | With Co-CEO of Waymo Dmitri Dolgov Designing the Future: Dylan Field on AI, Collaboration, and Independence No Priors Ep. 55 | With Figma CEO Dylan Field The Data Foundry for AI with Alexandr Wang from Scale No Priors Ep. 65 | With Scale AI CEO Alexandr Wang Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil Timecodes: 0:00 Introduction  0:15 Jensen Huang on building at data-center scale  4:00 Andrej Karpathy on the AI exo-cortex, model control, and a shift to smaller models  7:14 Bret Taylor on the agentic future of business interactions  11:17 OpenAI's Sora team on visual models and their role in AGI  15:53 Waymo's Dmitri Dolgov on bridging the gap to full autonomy and the challenge of 100% accuracy  19:00 Figma's Dylan Field on the future of interfaces and new modalities  23:29 Scale AI's Alexandr Wang on the journey to AGI  26:29 Outro

What are the best investing opportunities in Tech for 2025? Elad Gil is one of silicon valley's legendary investors. He's backed 40 unicorns including Airbnb, Coinbase, Figma and Stripe to name a few. He's super active in AI and hosts the no priors podcast which is like Bankless but for AI. In this conversation, Elad explores the state of AI and how the industry is evolving, what he thinks about Crypto. and why he's bullish on Tech in general given the new United States political administration. ------

Torsten Reil is the Co-Founder and Co-CEO of Helsing, a new type of defence company providing artificial intelligence to protect our democracies. Torsten has raised over $825M from the likes of Prima Materia, Elad Gil, Accel and General Catalyst. Previously Torsten founded NaturalMotion, one of the UK's most successful games and technology start-ups. Torsten was named as one of MIT's Top 100 Innovators and is a member of the Munich Security Conference Innovation Board. In Today's Episode with Torsten Reil We Discuss: 1. The World Around Us: China, Russia and Trump: What will happen between China and Taiwan? What will happen between Russia and Ukraine? How will a Trump administration impact the US' commitment to fund European defence? What conflict do people not pay enough attention to in the world today? 2. Are We Ready and What Needs to Be Done: Are the west ready to fight against our adversaries as we stand today? What do we need to do to equip ourselves?  What needs to change in our defence budgets? Where do they need to go? How does the procurement process for defence need to change? 3. The Future of War:  Why does Torsten believe the future of war is contactless? In the next wave of defence, what are the most important elements for allies to own? What elements concern Torsten the most? What role does AI and autonomous play in the future of war? 4. Is Europe F********: Why does Torsten believe that Europe's biggest problem is ambition not capital? Why does Torsten believ that we put too much weight on the location in which companies are founded? Why does it not matter? How does Torsten respond to the statement that we do not have the depth of experienced talent in Europe to recruit?  

Episode 635: Sam Parr ( https://x.com/theSamParr ) and Shaan Puri ( https://x.com/ShaanVP ) talk to Elad Gil ( https://x.com/eladgil ) about the three things he looks for when betting on startups, how he became an early investor in Anduril, plus 3 business ideas he thinks someone should go after.  — Show Notes:  (0:00) How to be successful in angel investing (3:00) How to create a bankroll  (5:00) Making the great works of history available to anyone anywhere (7:21) The 1 thing that matters in a business (10:21) How to master a new topic like defense tech (12:15) Investing in Anduril in the first round (15:47) $1b dollar 1 person companies (18:51) Missionary vs mercenary (22:12) Idea: new schools inspired by Ancient Greece (25:49) Idea: A drug that makes you live longer (34:56) Idea: Large scale monuments to flex (44:25) Gil's Guide to Intensive Travel — Links: • Elad's blog - https://eladgil.com/  • Proof School - https://www.proofschool.org/ • BioAge Labs - https://bioagelabs.com/  — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth • Sam's List - http://samslist.co/ My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano