Podcast appearances and mentions of erik torenberg

Erik Torenberg speaks with tech analyst Benedict Evans about the current state of AI, what has changed over the past year, and which questions remain unanswered. The conversation covers coding agents, foundation models, AI infrastructure spending, software economics, and the tension between today's AI excitement and the long-term realities of technology adoption. Evans discusses why coding has emerged as AI's first breakout use case, how previous platform shifts can help frame the current moment, and why many of the most important questions about AI remain unresolved. Along the way, they explore the future of software, enterprise adoption, consumer behavior, and whether AI models ultimately capture value themselves or become infrastructure for the next generation of applications.   Resources: Follow Benedict Evans on X: https://x.com/benedictevans Follow Erik Torenberg on X: https://x.com/eriktorenberg Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Erik Torenberg speaks with Marc Andreessen about the state of AI, media, and the broader cultural and economic shifts shaping the internet. They discuss how narratives around AI, from fear to hype, are influencing public perception, and why real-world usage tells a very different story. The conversation covers AI's impact on jobs and productivity, the rise of “AI-native” builders, and why increased capability tends to expand work rather than eliminate it. Andreessen also examines how companies are adapting, from restructuring teams to rethinking roles around more generalist “builders.” They also explore the changing media landscape, from the dynamics of influence and information to the breakdown of traditional authority, and what it means for trust, culture, and generational attitudes. Along the way, they touch on topics ranging from institutional power to emerging internet subcultures, offering a wide-ranging look at how technology is reshaping both systems and society.   Resources: Follow Marc Andreessen on X: https://x.com/pmarca Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Sharing the pod I did with the TECH BROS over at Monitoring the Situation. Tried to give some sense of what we discuss over here at HoS, plus engage in the discourse of the day. Topics covered include: * How sports shape the future of X/Twitter * Caitlin Clark, the WNBA, and the business of controversy .* Nike, ideology, and shareholder value* The fragmentation of internet culture* Erik Torenberg's controversial, “Right-wing memes are displacing African-American Vernacular English as the most dynamic source of linguistic innovation” comment House of Strauss is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.houseofstrauss.com/subscribe

Erik Torenberg speaks with Martin Shkreli, American investor and businessman, about how he sees the AI landscape, from OpenAI to Anthropic, and what actually matters beyond the hype. They also talk through the future of computing, the limits of “vibe coding,” and why biotech and pharma remain some of the toughest industries to get right.   Resources: Follow Martin on X: https://x.com/MartinShkreli   Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Erik Torenberg and Theo Jaffee speak with Balaji Srinivasan, angel investor, entrepreneur, and author of The Network State, about how AI is transforming media, eroding trust, and reshaping how information is created and verified. They discuss why systems like hiring, journalism, and online communication are breaking under synthetic content, and what replaces them. The conversation also examines the role of cryptography, on-chain data, and new models of proof in rebuilding trust online.   Resources: Follow Balaji on X: https://x.com/balajis Follow Erik Torenberg on X: https://twitter.com/eriktorenberg Follow Theo Jaffee on X: https://x.com/theojaffee Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Erik Torenberg and Theo Jaffee speak with Marc Andreessen, cofounder and general partner at a16z, about the launch of Monitoring the Situation (MTS), a new, always-on media network on X. They discuss the rise of the “current thing,” how narratives spread in real time, and why internet-native media is reshaping politics, culture, and attention.   Resources: Follow Marc X: https://x.com/pmarca Follow Eric on X: https://x.com/eriktorenberg Follow Theo on X: https://x.com/theojaffee Follow MTS on X: https://x.com/MTSlive Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Erik Torenberg, Steve Sinofsky, and Martin Casado speak to Aaron Levie, CEO at Box, about what happens to enterprise software when agents become the primary users. They discuss why coding agents succeed where other knowledge work agents struggle, what abstraction layers mean for the workforce, and how data access and systems of record must change in an agent-first world. Follow Aaron Levie on X: https://twitter.com/levie Follow Steve Sinofsky on X: https://twitter.com/stevesi Follow Martin Casado on X: https://twitter.com/martin_casado Follow Erik Torenberg on X: https://twitter.com/eriktorenberg Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts. Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The internet already has a bot problem — and it's just getting worse. a16z's Ben Horowitz and Erik Torenberg speak with Alex Blania of Tools for Humanity. World is building the largest real human network, a proof-of-human layer for the AI era. They cover the technical challenge of proving human uniqueness at scale using iris biometrics, the privacy architecture behind World ID, and why platforms from social networks to dating apps to video conferencing will soon require proof of human verification. Timestamps:  0:00—Introduction  4:07—Three Big Ideas People Were Interested In  9:05—The Orb Verification Piece  15:20—Social Media Bots: PSYOPs and Propaganda  29:18—We Had Proof of Personhood for the Longest Time  36:44—Next Year Go-to-Market Is Focused on the US  40:09—Different Levels of Verification Resources:  Follow Alex Blania on X: / alexblania  Follow Ben Horowitz on X: / bhorowitz  Follow Erik Torenberg on X: / eriktorenber Follow a16z crypto for more...  X: https://x.com/a16zcrypto  LinkedIn: https://www.linkedin.com/showcase/a16zcrypto/posts/  YouTube: https://www.youtube.com/@a16zcrypto  Substack: https://a16zcrypto.substack.com/subscribe/   As always, none of the following should be taken as investment, business, legal, or tax advice. Please see a16z.com/disclosures for more important information, including a link to a list of our investments. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Erik Torenberg and Anish Acharya, general partners at a16z, speak with signüll about how technology reshapes culture, relationships, and the products we build. The conversation covers tacit knowledge versus intellectual knowledge, dating apps and their effect on human connection, AI relationships, why Claude feels artisan while other models feel utilitarian, and what consumer founders should actually care about.   Resources: Follow signüll on X: https://twitter.com/signulll Follow Anish Acharya on X: https://twitter.com/illscience Follow Erik Torenberg on X: https://twitter.com/eriktorenberg Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Erik Torenberg, Steve Sinofsky, and Martin Casado speak to Aaron Levie, CEO at Box, about what happens to enterprise software when agents become the primary users. They discuss why coding agents succeed where other knowledge work agents struggle, what abstraction layers mean for the workforce, and how data access and systems of record must change in an agent-first world.   Resources: Follow Aaron Levie on X: https://twitter.com/levie Follow Steve Sinofsky on X: https://twitter.com/stevesi Follow Martin Casado on X: https://twitter.com/martin_casado Follow Erik Torenberg on X: https://twitter.com/eriktorenberg Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

a16z general partner Erik Torenberg speaks with Balaji Srinivasan, angel investor and entrepreneur, about why AI simultaneously reduces the cost of creation and increases the cost of verification, and what that tension means for the shape of the AI economy. They discuss why AI drives companies toward the "trusted tribe" model of the Chinese internet, why physical world tasks are easier to automate than digital ones, why shortcuts only work for experts, and why AI makes everyone a CEO rather than making CEOs obsolete.   Resources: Follow Balaji Srinivasan on X: https://twitter.com/balajis Follow Erik Torenberg on X: https://twitter.com/eriktorenberg Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Fresh off raising a monster $15B, Marc Andreessen has lived through multiple computing platform shifts firsthand, from Mosaic and Netscape to cofounding A16z. In this episode, Marc joins swyx and Alessio in a16z's legendary Sand Hill Road office to argue that AI is not just another hype cycle, but the payoff of an “80-year overnight success”: from neural nets and expert systems to transformers, reasoning models, coding, agents, and recursive self-improvement. He lays out why he thinks this moment is different, why AI is finally escaping the old boom-bust pattern, and why the real bottleneck may be less about models than about the messy institutions, incentives, and social systems that struggle to absorb technological change.This episode was a dream come true for us, and many thanks to Erik Torenberg for the assist in setting this up. Full episode on YouTube!We discuss:* Marc's long view on AI: from the 1980s AI boom and expert systems to AlexNet, transformers, and why he sees today's moment as the culmination of decades of compounding technical progress* Why “this time is different”: the jump from LLMs to reasoning, coding, agents, and recursive self-improvement, and why Marc thinks these breakthroughs make AI real in a way prior cycles were not* AI winters vs. “80-year overnight success”: why the field repeatedly swings between utopianism and doom, and why Marc thinks the underlying researchers were mostly right even when the timelines were wrong* Scaling laws, Moore's Law, and what to build: why he believes AI scaling laws will continue, why the outside world is messier than lab purists assume, and how startups can still create durable value on top of rapidly improving models* The dot-com crash and AI infrastructure risk: Marc's comparison between today's AI capex boom and the fiber/data-center overbuild of 2000, plus why he thinks this cycle is different because the buyers are huge cash-rich incumbents and demand is already here* Why old NVIDIA chips may be getting more valuable: the pace of software progress, chronic capacity shortages, and the idea that even current models are “sandbagged” by supply constraints* Open source, edge inference, and the chip bottleneck: why Marc thinks local models, Apple Silicon, privacy, trust, and economics all point toward a major role for edge AI* American vs. Chinese open source AI: DeepSeek as a “gift to the world,” why open models matter not just because they're free but because they teach the world how things work, and how open source strategies may shift as the market consolidates* Why Pi and OpenClaw matter so much: Marc's claim that the combination of LLM + shell + filesystem + markdown + cron loop is one of the biggest software architecture breakthroughs in decades* Agents as the new “Unix”: how agent state living in files allows portability across models and runtimes, and why self-modifying agents that can extend themselves may redefine what software even is* The future of coding and programming languages: why Marc thinks software becomes abundant, why bots may translate freely across languages, and why “programming language” itself may stop being a salient concept* Browsers, protocols, and human readability: lessons from Mosaic and the web, why text protocols and “view source” mattered, and how similar principles may shape AI-native systems* Real-world OpenClaw use: health dashboards, sleep monitoring, smart homes, rewriting firmware on robot dogs, and why the most aggressive users are discovering both the power and danger of agents first* Proof of human vs. proof of bot: why Marc thinks the internet's bot problem is now unsolvable via detection alone, and why biometric + cryptographic proof of human becomes necessaryTimestamps* 00:00 Marc on AI's “80-Year Overnight Success”* 00:01 A Quick Message From swyx* 01:44 Inside a16z With Marc Andreessen* 02:13 The Truth About a16z's AI Pivot* 03:29 Why This AI Boom Is Not Like 2016* 06:33 Marc on AI Winters, Hype Cycles, and What's Different Now* 10:09 Reasoning, Coding, Agents, and the New AI Breakthroughs* 12:13 What Founders Should Build as Models Keep Improving* 16:33 AI Capex, GPU Shortages, and the Dot-Com Crash Analogy* 24:54 Open Source AI, Edge Inference, and Why It Matters* 33:03 Why OpenClaw and PI Could Change Software Forever* 41:37 Agents, the End of Interfaces, and Software for Bots* 46:47 Do Programming Languages Even Have a Future?* 54:19 AI Agents Need Money: Payments, Crypto, and Stablecoins* 56:59 Proof of Human, Internet Bots, and the Drone Problem* 01:06:12 AI, Management, and the Return of Founder-Led Companies* 01:12:23 Why the Real Economy May Resist AI Longer Than Expected* 01:15:53 Closing ThoughtsTranscriptMarc: Something about AI that causes the people in the field, I would say, to become both excessively utopian and excessively apocalyptic. Having said that, I think what's actually happened is an enormous amount of technical progress that built up over time. And like for, for example, we now know that neural network is the correct architecture.And I, I will tell you like there was a 60 year run where that was like a, you know, or even 70 years where that was controversial. And so, so the way I think about what's happening is basically, I think, I think about basically the, the, the period we're in right now is it's, I call it 80 year overnight success, right?Which is like, it's an overnight success ‘cause it's like bam, you know, chat GPT hits and then, and then oh one hits, and then, you know, open claw hits and like, you know, these are open, these are, these are like overnight, like radical, overnight transformative successes, but they're drawing on an 80 year sort of wellspring backlog, you know, of, of, of, of ideas and thinking it's not just that it's all brand new, it's that it's an unlock of all of these decades of like very serious, hardcore research.If I were 18, like this is a hundred, this is what I would be spending all of my time on. This is like such an incredible conceptual breakthrough.swyx: Before we get into today's episode, I just have a small message for listeners. Thank you. We will not be able to bring you the ai, engineering, science, and entertainment contents that you so clearly want if you didn't choose to also click in and tune into our content.We've been approached by sponsors on an almost daily basis, but fortunately enough of you actually subscribed to us to keep all this sustainable without ads, and we wanna keep it that way. But I just have one favor to ask all of you. The single, most powerful, completely free thing you can do is to click that subscribe button.It's the only thing I'll ever ask of you, and it means absolutely everything to me and my team that works so hard to bring the in space to you each and every week. If you do it, I promise you will never stop working to make the show even better. Now, let's get into it.Alessio: Hey everyone, welcome to the Lidian Space Pockets. This is CIO, founder Kernel Labs, and I'm joined by s Swix, editor of Lidian Space.swyx: Hello. And we're in a 16 Z with a, uh, mark G and welcome.Marc: Yes, yes. A and what, half of 16? Something like that. A one. Exactly,swyx: exactly. Uh, apparently this is the, the final few days in your, your current office.You're moving across the road.Marc: Uh, we're, yeah. We have a, we have some, we have some projects underway, but yeah, this is actually, oh, this is the original. We're in actually the original office. We're in the, we're in the, we're, we're in the whole thing.swyx: It's beautiful. Yeah. Great.Marc: Thank you.swyx: So I have to come out, uh, this is a, you know, I wanted to pick a spicy start in October, 2022.I just made friends with Roone and, uh, I wanted to give him something to sort of be spicy about. And I said, uh. Uh, it'll never not be funny. The A 16 Z was constantly going. The future is where the smart people choose to spend their time and then going deep into crypto and not in ai. And that was in October 22nd, 2022.And Ruen says there was an internal meeting in a 16 Z to reorient around Gen ai. Obviously you have, but was there a meeting? What, what was that?Marc: I mean, I don't, look, I've been doing AI since the late eighties.swyx: Yeah.Marc: So I, I don't know, like all that, as far as I'm concerned, this stuff is all Johnny cum lately.Yeah. You, I mean, look, we've been doing ar entire existence. I mean, we've been doing AI machine learning deep, you know, deeply. We've been doing this stuff way from the beginning. Obviously a AI is just core to computer science. I, I, I actually view them as like quite, uh, quite continuous. Um, you know, Ben and I both have computer science degrees.Um, you know, we, we both, Ben, Ben and I actually both are world enough to remember the actual AI boom in the 1980s. Yeah. There was like a, there was a big AI boom at the time. Um, and there was a, was names like expert systems. Um, and they of like lisp and lisp machines. Uh, I, I coded in lisp. I was coding a lisp in 1989.When that was the, the language of the AI future. Um, yeah. So this is something that we're like completely, you completely comfortable with. I've been doing the whole time and are very enthusiastic aboutswyx: is there a strong, like this time is different because, uh, my closest analog was 20 16 17. It was an AI boom.Mm-hmm. And it petered out very, very quickly. Um, we, it just, it just in terms of investingMarc: sort of, sort of,swyx: yeah. Investment, investment excitement.Marc: Although that's really when the, the, the Nvidia phenomenon really, it was, I would say it was in that period when it was very clear that at, at the time it, the vocabulary was more machine learning, but it, it was very clear at that time that machine learning was hitting some sort of takeoff point.Alessio: Yeah.Marc: Well, and as you guys, you guys have talked about this at length on, on your thing, but, you know, if you really track what happened, I think the real story is, it was, it was the Alex net, uh, basically breakthrough in like 2013. That was the, that was the real knee in the curve. Um, and then it was obviously the transformer breakthrough in 17.Alessio: Yeah.Marc: Um, and then everything that followed. But, but, you know, look, machine learning, you know, there were, you know, look, uh, I mean look, I've been working, you know, I've been working with, uh, one of my, you know, kind of projects working with Facebook since 2004. Um, and on the board since 2007, and of course, you know, they, they started using machine learning very early, um, and, you know, have used it basically, you know, for like 20 years for, you know, content, you know, feed optimization and advertising optimization.And obviously many, you know, financial services. You know, many, many, many companies, many different sectors have been doing this. And so it's like one of these things, it's like, it's not a, it's not a single thing. Like it's, it's like, it's like layers, right? Yeah. Um, and, and the layers arrive at different paces and, but they kind of build up.swyx: Yeah.Marc: Uh, they kind of build up over time and then, and then, yeah. And then look, in retrospect, it was 2017 was kind of the, you know, the key, the key point with the trans transformer and then. And then as you guys know, there was this really weird like four year period where it's like the, the transformer existed and then it was just like,swyx: let's go.Yeah.Marc: Well, but, but it was just, but, but between 2020, but between 2017 and 2021, I mean, that was the era of which like companies like Google had internal chat Botts, but they weren't letting anybody use them.swyx: Yeah.Marc: Right. And then, you know, and then OpenAI developed Chat GT or GPT two, and then they told everybody, this is way too dangerous to deploy.Right. Yeah. You know, we can't possibly let normal people, normal people use this thing. And then you, you guys, I'm sure remember AI Dungeon, um mm-hmm. So the o for, there was like a year where like the only way for a normal person to use GP T three was in, in AI dungeon.Alessio: Yeah.Marc: And so you, you, we would do this, you'd go in there and you'd pretend to play Dungeons and Dragons.In reality, you're just trying to talk to talk to GPT. And so there was this, you know, there was this long, you know, and I, you know, the big, big companies, you know, big companies are cautious and, you know, the big companies were cautious. It, it, by the way, it took open ai. You know, they, they, they talk about this, it took open AI time to actually adjust, you know, kind of re redirect their researchswyx: path.I, I think, uh, let say Rosewood, right? Uh, the, the dinner that founded OpenAI was right there.Marc: Right, right. But that, that dinner would've taken place in 20swyx: 18Marc: 19. The formation of OpenAI Uhhuh as late as 2018.swyx: Uh, uh, sorry. Uh, no, I'm, I'm, I'm, I'm wrong. Probably It should be 20. Yeah. They just celebrated a 10 year anniversary, so it it is 2025.Yeah, so, so 2015?Marc: Yeah. 2015. Yeah. 2015. But then, uh, um, Alec Radford did G PT one in what, probablyswyx: mm-hmm. 17, 18,Marc: yeah. 17, 18. So it, yeah. For, and then, and then they didn't really, and then GPT three was what? 2020? 2020.swyx: 2020.Marc: Because that became copilot immediately. Even open ai, which has been, you know, the leader of, of this thing in the last decade, you know, e even they had to adapt and, and, and lean into the new thing.And so. Um, yeah, I, I think it's just this process of basically sort of wave after wave layer after layer, you know, building on itself. And then you kind of get these catalytic moments where, where the whole thing pops and, and obviously that's what's happening now.swyx: Is it useful to think about will there be any ai, winter?‘cause there's always these patterns. Like, is this, in the summer is something I constantly think about because do I get, do I just like. Just get endlessly hyped and just trust that I will only be early and never wrong or right. Well, are we, will there be a winter?Marc: So there's something about, say the following.There's something about AI that has led to this repeated pattern. Um, and, and, and you guys know this,swyx: it's summer, winter, summer,Marc: winter, summer, winter, summer, winter. And it goes back 80 years. Yeah. 80 years. Uh, so the original neural network paper was 1943. Right. Which is, which is amazing. Uh, that it was, it was far back that long.And then there was you, if you guys have ever talked about this on your show, but there was this, uh, there was a big, uh, there was an a GI conference at Dartmouth University in 1950. 55. 55, yeah. And they got a NSF grant to, uh, for the, all the AI experts at the time to spend the summer together. And they figured if they had 10 weeks together, they could get a GI, uh, at the other end.And they got their, by the way, they got the grant, they got the 10 weeks and then, you know, 1955, you know. No, no. A GI. And like I said, I, I lived through the eighties version of this where there was a big, a big boom and a crash. And so, so there is this thing, and there, there is something about AI that causes the people in the field, I would say, to become both excessively utopian and excessively apocalyptic.Um, and, and it's probably on both sides of like the, the, the boom bus cycle. You, you kind of see that play out. Having said that, I think what's actually happened is like just, and you know, and we now know in retrospect like an enormous amount of technical progress that built up over time. And like for, for example, we now know that neural network is the correct architecture.And I, I will tell you like there was a 60 year run where that was like a, you know, or even 70 years or that was controversial. And, and we now know that that's the case. And so we, we now, you know, everything we're building on today just sort of derives from the original idea in 1943. And so, so in retrospect, we, we now know that like, these, these guys are right.They, they, you know, they would get the timing wrong and they thought, you know, capabilities would arrive faster, or they were, it could be turned into businesses sooner or whatever, but like, they were fundamentally, the, the scientists who worked on this over the course of decades were fundamentally correct about what they were doing.And, and the, and the payoff from, from, from all their work is happening now. And so, so the way I think about what's happening is basically, I think, I think about basically the, the, the period we're in right now is it's, I call it 80 year overnight success, right? Which is like, it's an overnight success.‘cause it's like bam, you know, chat, GPT hits and then, and then oh one hits, and then, you know, open claw hits and like, you know, these are open, these are, these are like overnight, like radical, overnight transformative successes, but they're drawing on an 80 year sort of wellspring backlog, you know, of, of, of, of ideas and thinking it's not just that it's all brand new, it's that it's an unlock of all of these decades of like very serious, hardcore research.Um, and thinking, and look, there were AI researchers who spent their entire lives. They got their PhD. They, they worked for, they've researched for 40 years. They retired in a lot of cases, they passed away and they never actually saw it work.swyx: Yeah. It's all sad.Marc: It is. It is sad. It's sad. Knewswyx: Jeff Hinton was like the last guy.Marc: Yeah. Yeah. Well, there were the guys, uh, was a guy, Alan Newell. I mean, there's tons of John McCarthy. You know, John McCarthy was like one of the inventors in the field. He's one of the guys who organized the Dartmouth Conference and you know, he taught at Stanford for 40 years. Wow. And passed, you know, passed away, I don't know, whatever, 10, 10 years ago or something.Never, never actually go. Got to see it happen. But like, it is amazing in retrospect, like, these guys were incredibly smart and they worked really hard and they were correct. So anyway, so then it's like, okay, you know, say history doesn't repeat, but it rhymes. It's like, okay, does that mean that there's gonna be another, like, you know, basically boom buzz cycle.And I, I will tell you, like, let, like in a sense, like yes, everything goes through cycles and, you know, people get overly enthusiastic and overly depressed and there's, there's a time, there's a timelessness to that. Having said that, there's just no question. Um, so the form, the foremost dangerous words in investing this time are, this time is different.Do you know the 12 most dangerous words investing? No. The four most d foremost dangerous words in investing are this time is different. Yeah. Um, the 12 most dangerous words. And so like, I'll tell you what's different. Like now it's working like, like there's just no, I mean, look, there's just no question.And by the way, I, I'll just give you guys my take. Like L LLMs, like from, from basically the Chad G PT moment through to spring of 25. I think you could still, I think well intention, well, and of. Form skeptics could still say, oh, this is just pattern completion. And oh, these things don't really understand what they're doing.And you know, the hall hallucination rates are way too high. And, you know, this is gonna be great for creative writing and creating, you know, Shakespeare and so sonnets and, you know, as, as rap lyrics or whatever, like, it's gonna be great and all that stuff, but we're not gonna be able to harness this to make this relevant in, you know, coding or in medicine or in law or in, you know, you know, kind of feels that, you know, kind of really, really matter.And I think basically it was the reasoning breakthrough. It, it was oh one and then R one that basically answered that question basically said, oh no, we're gonna be able to actually turn this into something that's gonna work in the real world. And, and then obviously the coding breakthrough over the, over basically the coding breakthrough that kind of catalyzed over the holiday break was kind of the third step in that.Mm-hmm. Where you're just like, alright, if, if, you know, if Linus Tova is saying that the AI coding is no better than he is like. Like, that's, that's never happened before. That's theswyx: benchmark.Marc: Yeah. That's never happened before. And so now we know that it's, it's gonna sweep through coding and, and then, and then we, we know, you know, we know that if it's gonna work in coding, it's gonna work in everything else.Right. It's just then, because that's, that's like, that's like, that's like the hardest in many ways. That's the hardest example. And how everything else is gonna be a, a derivative of that. And then on top of that, we just got the agent breakthrough, you know, with Open Claw, which is fantastic. Which is amazing and incredibly powerful.And then we just got the, the, um, the auto research, uh, you know, the, the self-improvement. You know, we're now into the self-improvement breakthrough. And so the, so the way I think about it is we've had four fundamental breakthroughs in functionality, l OMS reasoning, uh, agents, um, and then, uh, and, and then now RSI, um, and, and they're all actually working.Um, and so I'm, I'm just, as you like, you can tell I'm jumping outta my shoes. Like, like this is, like this is it like this, this is the culmination of 80 years worth of worth of work, and this is the time it's becoming real.Alessio: Yeah.Marc: I, I'm completely convinced.Alessio: I think the anxiety that people feel is like during the transistor era, yet Mors law, and it's like, all right, we understand why these things are getting better.We understand the physics of it. Yeah. With ai, it's. It's so jagged in like the jumps where like, like you said, it's like in three months you have like this huge jump like, and people are like, well this can keep happening. Right? But then it keeps happening,Marc: it'll keep happening.Alessio: And so like how do you think about also timelines of like what's we're building?I think we always have this question with guests, which is like, you know, should you spend time building harness for a model versus like the next model just gonna do it one shot in the lead space. Right. And how does that inform, like how you think about the shape of the technology? You know, you talk about how it's a new computing platform.If you have a computing platform, then like every six months it like drastically changes in what it looks like. It's hard to build companies on top of it.Marc: Yeah. So, so a couple things. So one is like, look, the, the Moore's law was what we now call a scaling law. Like Moore's Law was a scaling law and for your younger viewers, more Moore's Law was every chip chip chips either get twice as powerful or twice as cheap every, every 18 months.And that, and that and that, you know, that it's gotten more complicated in the last few years. But like that, that was like the 50 year trajectory of, of, of the computer industry. And then, and then by the way, and that's what took the mainframe computer from a $25 million current dollar thing into, you know, the phone in your pocket being, you know, a million times more powerful than that.Like that, you know, for, for 500 bucks. And so that, that was a scaling law. And then, and then, and then key to any scaling law, including Moore's Law and the AI scaling laws is, you know, they're not really laws, right? They're, they're, they're, they're predictions, but when they work, they become self-fulfilling predictions because they, they, they, they, they set a benchmark and, and then the entire industry, right?All the smart people in the industry kind of work to make sure that, that, that actually happens. And so they, they kind of motivate the breakthroughs that are required to, to keep that going. And, and in and in chips, that was a 50 year, that was a 50 year run. Right. And it, it was amazing. And it's still happening in, in some areas of, of chips.I think the same thing is happening with the, the core scaling laws. The core scaling laws. In, in, in ai, you know, they're, they're not really laws, but like they, they are basically. There are predictions and then they're motivating catalysts for the research work that is required to be. And, and, and, and by the way, also the investment, uh, dollars, um, uh, you know, required to basically keep, you know, keep the curves going and, and look, it, it is, it's gonna be complicated and it's gonna be variable and they're, you know, there're gonna be walls that are gonna look like they're fast approaching, and then they're gonna be, you know, engineers are gonna get to work and they're gonna figure out a way to punch through the walls.And obviously that's, you know, that's been happening a lot, you know, and then look, there's gonna be times when it looks like the walls have, you know, the, the, the laws have petered out and then they're gonna, they're gonna pick up again and surge and then, and then, and then it, it appears what's happening to the eyes is there's not multiple, you know, multiple scaling laws.Um, there's multiple areas of improvement. And, and I think, you know, I don't know how many more there are already yet to be discovered, but there are probably some more that we don't know about yet. You know, they, like, for example, there's probably some scaling law around, um, world models and robotics that we don't fully understand, you know, kind of acquisition of data at scale in the real world that we don't fully understand yet.So that, that, that one will probably kick in at some point here. There's a bunch of really smart people working on that. Um, and so, yeah, I, I think the expectation is that, that, you know, the, the scaling laws generally are gonna continue. Yeah. The, the pace of improvement will continue to move really fast.Um. To your question on like what to build. So, uh, I'm a complete believer the scaling laws are gonna continue. I'm a complete believer the capabilities are gonna keep getting amazing, um, you know, leaps and bounds. Uh, the part where I kind of part ways a little bit with how, what I would describe as the AI purists, um, you know, which is, which I would characterize as like the people who are.In many ways, the smartest people in the field, but also the people who spend their entire life, like at a lab, um, and have, have, I would say, have very little experience in the outside world. Um, the, the, the nuance I would offer is the outside world of 8 billion people and institutions and governments and companies and economic systems and social systems is really complicated.Um, and, um, and doesn't, you know, it it 8 billion people making collective decisions on planet Earth is not a simple process of like, just like you see this happening now. It's like a bunch of AI CEOs have this thing, which is just like, well, there's just this, they just all have this kind of thing when they talk in public where they're just like, well, there's these, these obvious set of things that so society to do.Alessio: Mm-hmm.Marc: And then they're like, society's not doing any of those things. Right. And it's like, how can society not, you know, what, whatever their theory is, how can society not see x, y, Z? Mm-hmm. And the answer is, well, society is number one. There's no single society, it's like 8 billion people. And they like all have a voice, and they all have a vote, like at the end of the day of how they, they react to change.And then, you know, it just like, it's just human reality is just really complicated and messy. Um, and, and, and so the specific answer to your question is like, as usual, it depends. Um, you know, it, it depends. Look, pe there's no question people are gonna, like, there's no question they're gonna be companies.It's already happening. There are companies that think that they're building value on top of the models and then they're just gonna get blissed by the, by the next model. There's no question that's happening. But I think there's no question also that just the process of adaptation of any technology into the real and into the real messy world of humanity is, is just going to be messy and complicated.It's, it's not going to be simple and straightforward. It's gonna be messy and complicated. And there are gonna be a lot of companies and a lot of products, um, uh, and in, in fact entire industries that are gonna get built to, to, to basically actually help all of this technology actually reach real people.Alessio: The amount of capital going into these companies, I mean, Dario talked about it on the Door Cash podcast and Door Cash was like, why don't you just buy 10 x more GPUs? And he is like, because I'm gonna go bankrupt if the model doesn't exactly hit the, the performance level. How do you think about that?Also as a risk on, you know, you guys are investors, open AI and thinking machines and world apps. It seems like we're leveraging the scaling loss at a pretty high rate, right? Like how comfortable, I guess, do you feel with the downside scenario, like, and say like things Peter out, you think you can kind of like restructure uh, these build outs and uh, you know, capital investments.Marc: Yeah. So should start by saying, so I live through the.com crash, um, and I can tell you stories for hours about the.com crash and it was horrible. No, it was awful. It was, it was, it was apocalyptic by the way. The, a lot of the.com crash was actually at the time, it was actually a telecom crash. It was a bandwidth crash.Like the, the thing that actually crashed, that wiped out all the money with the tele, the telecom companies.swyx: GlobalMarc: crossing. Global, global, yeah.swyx: I'm from Singapore and they, they laid so much cable o over over our oceans.Marc: Actually there was a scaling law in the.com. Era. And it was literally the, the US Commerce Department put out a report in 1996 and they said internet traffic was doubling every quarter.Um, and, and actually in 1995 and 1996, internet traffic actually did double every quarter. And so that became the scaling law. And so what all these telecom entrepreneurs did was they went out and they raised money to build fiber, anticipating that the demand for bandwidth is gonna keep doubling every quarter.Doubling every quarter though is like, you know, grains of chess and the chessboard, like at some point the numbers become extremely large. Right. And, and, and it really, and really what happened was the internet. The internet by the way, continuously kept growing basically since inception. And it's, you know, it's, it's continuously grown.It's never shrunk. And it's grown really fast compared to anything else. Mm-hmm. You know, in, in, in human history. But it wasn't doubling every quarter as of 19 98, 19 99. And so there was this gap in the expectation of what they thought was a scaling law versus reality. And that's actually what caused the.com crash, which was the, it they, they way over companies like global crossing way overbuilt fiber, which is sort of the, and by the way, fiber, telecom equipment, you know, so all the, all the networking gear, you know, and then, and then by the way, the actual physical data centers, like that was the beginning of the, of the, of the data center build and then, and the data center overbuild.And so you had that, but it was, it was literally, I think it was like $2 trillion got wiped out, right? It was like Jesus, it was like a big, it was. And by the way, the other, the other subtlety in it was the internet companies themselves never really had any debt. ‘cause tech, tech companies generally don't run on debt, but the telecom companies run on debt.Physical infrastructure companies run on debt. And so the companies like Global Crossing not just raise a lot of equity, they also raise a lot of debt. So they're highly levered. And so then you just do the thing. It's just like, okay, you have a highly levered thing where you're, you're just over, you're overbuilding capacity.Demand is growing, but not as fast as you hoped. And then boom, bankrupt. Right. And, and then it, and then it's like they say about the hotel industry, which is, it's always the third owner of a hotel that makes money. It has to go bankrupt twice, right? You have to wash out all of the over optimistic exuberance before it gets to actually a stable state.And then it makes money. So by the way, all of those data centers and all of those, all the fiber that they're in use, it's all in use today. Yeah. But 25 years later. But it, it, it took, and actually the elapsed time was, it took 15 years. It took 15 years from 2000 to 2015 to actually fill, fill up all that capacity.The cautionary warning is the, the overbuild can happen. Um, and, and, and, and, you know, you, you get into this thing where basically everybody, everybody who basically has any sort of institutional capital, it's like, wow. It's just, I, I don't know how to invest in these crazy software things. For sure I can put build data centers and for sure I can buy GPUs that I can deploy, you know, compute grids and, and all these things.Um, and so, you know, if you're a pessimist, you could look at this and you could say, wow, this is like really set up to be able to basically replicate, you know, what we went through, what we went through in 2000. Obviously that would be bad. The counter argument, which is the one I I agree with, which is the counter on, on the other side is a couple things.One is the companies that are investing all the, the companies that are investing the money are like the bluest chip of companies. And so back, back, back in the, in the do, like Global Crossing was like a, it was like an entrepreneur. It was like a, a new venture, but like the money that's being deployed now at scale is Microsoft, and, you know, and Amazon and Google, Facebook and Facebook and Nvidia and, you know, these, these, these, and, and now you know, by the way, open ai philanthropic, which are now at like, you know, really serious size, um, you know, as companies with, you know, very serious revenue.These are very large scale companies with like, lots, lots of cash, lots of debt capacity that they've, they've never used. And so th this is institutional in a way that, that really wasn't at the time. And then the other is, at least for now, every dollar that's being put into anything that results in a running GPU is being turned into revenue right away.Like so, and you guys know this, like everybody's starved for capacity, everybody's starved for compute capacity and then, you know, all the associated things, memory and, and, and interconnected and everything else. Um, data center space. And so e every dollar right now that's being put into the ground is turning into revenue.And, and it, and in fact, I actually think there's an interesting thing happening, which is because everybody starve for capacity, the models that we actually have that we can use today are inferior versions of what we would have if not for the supply constraints. That's true. Um, if Right pose a hypothetical universe in which GPUs were 10 times cheaper and 10 times more plentiful mm-hmm.The models would be much better. ‘cause you would just allocate a lot more money to training and you'd just build better models and they would be better. Um, and so we're, we're actually getting the sandbag version of the technology.swyx: Yeah. No. Everything we use is quantized because the, the labs have to keep the, the full versions,Marc: right?swyx: LikeMarc: we're not even getting the good stuff.swyx: Yeah.Marc: But, but getting the good stuff, it's, it's just, even if technical progress stops. Once there's like a much bigger build of like GPU manufacturing capacity and memory, you know, all, all the things that have to happen in the course of the next five or 10 years.Once it happens, even the current technology is gonna get, gonna get much better. And then as you know, like there's just like a million ways to use this stuff. Like there's just like a million use cases for this. Mm-hmm. Like, it, it, you know, this isn't just sending packets across a, a thing, whatever, and hoping that people find something to do with it.This is just like, oh, we apply intelligence into every domain of human activity. And then it works like incredibly well. Yeah. Um. Here's what I know, here's what I know. Um, in the next three or four year, it's like somewhere between three or four years out, basically everything is selling out. So like the, the entire supply chain is, is, is, is sold out or, or, or selling out.And so there, there's no, like, we're just gonna have like chronic supply shortage for, you know, for years to come. Um, there's going to be a response from the market that's gonna result in an enormous, you know, it's happening now. An enormous flood of investment in a new fab capacity and ev you know, every, everything else to be able to do that, at some point the supply chain constraints will unlock, you know, at least to some degree that will be another accelerant to industry growth when that happens.‘cause the products will get better and everything will get cheaper. Um, and so, so I know that's gonna happen. I know that, you know, the deployments, you know, the, the actual use cases are like really compelling. And then, like I said, you know, with reasoning and agents and so forth, like, I know they're just gonna get like much, much better from here.And so I, I, I know the capabilities are like really real and serious. I also know that the technical progress is not going to stop. It. It, it is excel. It is, is accelerating. Like the, the breakthroughs are are tremendous. I mean, even just month over month, the breakthroughs are really dramatic. And so, you know, I think if you were a cynic and there, there are cynics, you can look at 2000, you can find echoes.But I can't even imagine betting it that this is gonna like somehow disappoint and, you know, at least for years to come, I think it would be essentially suicidal to make that bet. Yeah. Um, it was that Michael Burry, uh, uh, that'sswyx: anMarc: interesting guy, huh? We'll pick on a guy. We'll pick, let's pick on one guy.We'll pick. Well ‘cause he did, he he came out with, it was, it was the, heswyx: doesn't mind.Marc: It was the Nvidia short. Right. He came with the Nvidia short. And then if you guys probably talked about this, which is the, the analysis now that like the current models are getting better faster at such a rate that if you are running an Nvidia, if you're running an Nvidia inference chip today, that's three years old, you're making more money on it today than you did three years ago because the pace of improvement of the software is, is faster than the, the, the depreciation cycle, the chip.And then my understanding is Google is running. I don't if they've, I don't know exactly what, uh, these are rumors that I've heard or maybe it's public, but, um, I think Google's running very old TPUs, very profitably. Ference. Yeah. And very profit and very profitably. Yeah. Um, and so, so it actually turns out, as far as I can tell, it's actually the opposite of the Beery thesis is actually.He was actually 180 degrees wrong. It's actually the, the, the, the old Nvidia chips are getting more valuable, which is something that's like literally never happened before. Like it's never been the case that you have an older model chip that becomes more valuable, not less valuable. And that, and again, that's an expression of the just ferocious pace of software progress.Ferocious pace of capability payoff. Yeah. Uh, that you're getting on the other side of this. And so I just, the idea of betting against that, like.swyx: Yeah. Yeah. Well, one ofMarc: my, it seems like an invitation to get your face ripped up.swyx: One of my early hits was like modeling the lifespan of the H 100 and h two hundreds and, and going like, you know, usually they advise like four to seven years and it was, you know, maybe you sort of realistically haircut cut it down to two to three.Yeah. But actually it's going up and not down. Yeah. And, and uh, that's, I mean that's, I think that's the dream. Uh, we are finding utilization and I think utilization solves all problems. Like, you can, you can find use, use cases for even like the poor, like even memory, we're having a shortage. Right. And, and even like the, the shittier versions of, of memory that we do have, we are finding use cases for it.So like That's great.Marc: Yeah.Alessio: How, how important is open source AI and kinda like edge inference in a world in which you have three years of supply crunch. Like, do you think in the, like, you know, if you fast forward like five years, like how do you think about inference, uh, in the data center versus at the edge?Marc: Well, so just to start, yeah. So I think, I think open source is very important for a bunch of reasons. I think edge, edge inference is very important for a bunch of reasons. I, I think just practically speaking, if we're just gonna have fundamental construc, supply crunches for the next, I mean, you, you guys know if you just project forward demand over the next three years, right?Yeah. Relative to supply, one of the, its main predictions you can do is what's gonna, what, what's gonna happen to the cost of, of inference in the core, uh, over the next three years? And like, it may rise dramatically, right? Like, so, so what is, and then is, is, you know, like the, the, the big model competition are subsidizing heavily right now.Right? Right. And so, so what's the, what will be the average person's, you know, per day, per month token cost, you know, three years from now to do all the things that they want to do. And I, I don't know, it's gonna. I mean, I have, you guys probably have friends, I have friends today who are paying a thousand dollars a day for open claw, for claw tokens to run open claw.Right? And so, okay. $30,000 a month. Right? And, and by the way, those, those friends have like a thousand more ideas of the things that they want their claw to do, right? Yeah. And so you, you could imagine there, there's like latent demand of up to, I don't know, five or $10,000 a day of, of, of tokens for a fully deployed, you know, per personal agent.Uh, and obviously consumers can't pay that, right? And so, so, but it gives you a sense of the fu of the fu of the future scope of demand, right? And so, so even, even if there's a 10 x improvement in price performance, that still, you know, goes to a hundred dollars a day, which is still way beyond what people can pay.Mm-hmm. So there's just gonna be like. Ferocious to me, by the way. The agent thing, the other interesting thing is I think the agent thing, so up until now, a lot of the constraints of GGPU constraints, I think the agent thing now also translates into CPU constraints. Mm-hmm. Right?swyx: CPU memory.Marc: Yes. CPU memory, right?And so, like the entire chip ecosystem is just gonna get wait,swyx: wait for network constraints, that that will be the killer.Marc: It's all bottleneck potentially for years. And so, so I, I think that Brad, and, and I think it's actually possible, I mean, generally inference costs are gonna keep coming down, but I think the, let's put it this way, the rate of decline, I think may level out here for a bit because of these supply constraints.And then at some point, maybe the lab stops subsidizing so much and that, that, that again, will be, be an issue. And so there's just gonna be so much more demand for inference than, than can be satisfied. Um, you know, kind of with the centralized model. And then, and then, you know, you guys know this, but like all the, just the dramatic, I mean just the dramatic innovations that have happened in the Apple silicon to be able to do, uh, inferences, it's quite amazing the level of effort being put.Like the open source guys are putting incredible effort into getting, you know, this recurring pattern where the big model will never run on a pc, and then six months later mm-hmm. Oh, it runs in a pc, right? It's like amazing. And there's very smart people working on that. So there's all that. And then look, there's also, you know.There's also like other, there's other motivators. There's other motivators which is just like, okay, how much trust are the big centralized model providers? You know, how much trust are they building in the market versus, you know, how much are, you know, at least for, in certain cases with some people, for certain use cases, people being like, well, I'm not willing to just like, turn everything over.So there, there, there's all the trust issues. Um, by the way, there's also just like straight up price optimization. There's many uses of AI where you don't need Einstein in the cloud. You just need like a, a a, a smart local model. There's also performance issues where you want, you know, you want, you know, you're gonna want your doorknob to have an AI model in it.Right. You know, to be able to, you know, do, um, you know, to be able to do access control. Um, obviously like everything with a chip is gonna have an AI model in it. Mm-hmm. And it, a lot of those are gonna be local. Um, and so, yeah. No, like I think, I think you're gonna have ti and then you're gonna, by the way, also wearable devices, you know, you don't wanna do a complete round trip.You want, you know, you, whatever your smart devices are, you want it to be like super low latency. Yeah.swyx: The question, do we care who makes it? Yeah. One of the biggest news this week was the collapse of AI two, the Allen Institute. Mm-hmm. One of the actual American open source model labs. Yeah. Um, and, uh, I'm not that optimistic on, on American open source.Yeah. Like you, you guys invested in MIS trial and MIS trial's doing extremely well outside of China. That's about it.Marc: Yeah. We'll see. We'll see. I look, I, number one, I do think we care. Uh, I do think we, I do think we care who makes it. Um, I would say this, the, the, the, the previous presidential administration wanted to kill it in the us Oh yeah.They wanted to drown in the bathtub. Um, and so they wanted to kill it. So at least we have a government now that actually like, actually wants it wants it to happen. And youswyx: earned to councilMarc: and Yeah. And the new and the P pcast. Yeah. So the, the, you know, this admin for whatever other political issues people have, which are many, you know, this administration has, I think a very enlightened view and in particular an enlightened view on AI and in particular on open source ai.Uh, and so they're very supportive. Um, my read is the Chi. The Chinese have a very, the various Chinese companies have a very specific reason to do open source, which is, they, they, they don't fundamentally, they don't think they can sell commercial, uh, AI outside of China right now. And or at least specifically not, not in the US for a combination of reasons.And so they, they kind of view, I think, open source AI as a bit of a loss leader against basically domestic, uh, you know, paid, paid services. And then kind of an, you know, kind of an ancillary products. You know, they're, they're very excited about it, by the way. I think it's great. I think it's great that they're doing it.Um, you know, I think Deeps seek was like a gift to the world. Um, I think. The great thing about open source, open source, the, the, the impact of open source is felt two ways. One is you, you get the software for free, but the other is you get to learn how it works, right? And so like the paper, the paper, the paper and, and the code, right?And the code. And so, like, for example, I thought this was amazing. So open comes out with L one and it's an amazing technical breakthrough, and it's just like, absolutely fantastic. But of course they don't explain how it works in detail. And then of course they hide the, they hide the reasoning traces, right?And, and then, and then, and then everybody's like, okay, this is great, but like, who's gonna be able to replicate this? Are other people gonna be able to do this? You know, is their secret sauce in there? And then our one comes out and it's just like, there's the code and there's the paper, and now the whole world knows how to do it.And then, you know, three months later, every other AI model is, is adding reasoning. And so, so you get this kind of double, like even if the Chinese models themselves are not the models that get used, the education that's taken place to the rest of the world, the information diffusion, you know, is incredibly powerful.So that happens and then, I don't know. We'll, we'll see. You know, there are a bunch of American, you know, open source, you know, ai, uh, model companies. I mean, look, there's gonna be tremendous, you know, there already is. There's, you know, there's gonna be tre there's tremendous competition, uh, among the primary model companies.You know, there's, depending on how you count, there's like four or five, you know, big co model companies now that are, you know, kind of neck and neck, uh, in different ways. Um, uh, you know, and, and, and, um, you know, and then obviously Bo Bo both X and then MetAware involved are, you know, both have huge, you know, huge attempts to, you know, kind of, to kind of leapfrog underway.And then you've got, you know, a whole fleet of startups, new companies, including a whole bunch that we're backing, that are, you know, trying to come out with different approaches. And then you've got whatever it is. I don't know how, how many, how many, like main line foundation model companies are there in China at this point?It's probably six. It'sswyx: five Tigers is what they call it. Yeah. Uh, Quinn is in questionable because there's change in leadership,Marc: right?swyx: Yeah.Marc: But that, does that include, that includes like Moonshot,swyx: yes. Can deep seek, uh, uh, ZI, um, Quinn oh one is in there.Marc: Right. And then, um, and by dance and, and then you see,swyx: ance would be like the next tier ance.They weren't as prominent. They weren't, didn't haveMarc: a leading. Yeah. But they, you at least, you know, ance is very inspiring and presumably they have more stuff coming and Tencent probably has more stuff coming and, and so forth. And so, so, so like, look, here, here would be a thing you can anticipate, which is there are not these markets, there are not going to be between the US and China right now, there's like a dozen primary foundation model companies that are like at scale, at, at some level of a critical mass.It's not gonna be a dozen in three years, right? Like, it just because these industries don't bear a dozen, it's, it's gonna be three or you know, there's gonna be three or four big winners or maybe one or two big winners. And so there's gonna be like a whole bunch of those guys that are gonna have to figure out alternate strategies.Um, and I think like open source is one of those strategies. And so I, I think you could see like a whole, i, I, I think the questions like, who's gonna do open source? I think that could change really fast. I, I think that, that, that's a very dynamic thing. I think it's very hard to predict what happens. And, and I think it's very important.swyx: NVIDIA's doing a lot.Marc: Well, I was gonna say. Well, exactly. And then you're got Nvidia and then, and then, you know, just to, again, indu, there's an old thing in business strategy, which is called, uh, commoditize Compliments. Commoditize the compliment. That's right. And so if your Jensen is just kind of obvious, of course, you wanna commoditize the software.Yeah. And he's, and to his enormous credit, he's putting enormous resources behind that. And so maybe it, maybe it's literally Nvidia and I think that would be great.Alessio: Yeah. Uh, narrative violation to European projects, uh, in the, uh, damn.swyx: I'm hosting my, uh, Europe, uh, conference soon. And I got both of them.Alessio: They got us.They got us. MarkMarc: finished. They got us, us. Well, wait a minute. Where was Peter? So where was Steinberger when he did? In AustriaAlessio: was, yeah, yeah, yeah.Marc: He was in what? He was in Vienna. Oh, he was in Vienna. And then where is he now?swyx: Uh, he's moving to sf.Marc: Okay. Okay. Alright. Okay, there we go. And then, yeah, the PI guy, right?The PI guys are European.swyx: Yeah, they're also, they're buddies inAlessio: Australia. Mario's also there. Yeah.Marc: Right. And are they, yeah, they haven't announced yet. Any sort of change changed or have theyAlessio: No, they're, they have a company there.Marc: Okay. Got, okay. Good.Alessio: Good, good,good.Alessio: Um,Marc: yeah, good.swyx: Anyways, I think pie and open cloud very important software things and, and I just wanted you to just go off on what you think.Marc: Yeah. So I think in co the, the combination of the two of them I think is one of the 10 most important softwares. Openswyx: Claw got all the attention, but Right. Talk about pie,Marc: pi pie's, kind of the Yeah. PI's, PI's kind of the architectural breakthrough for those of us who are older. There was this whole thing that was very important in the world of software basically from like 1970 to, I don't know, it still is very important, but like 19, from 1973 to like basically the creation of Linux, which is basically this, this thing used to call like the Unix mindset.Like so, so, ‘cause there were all these different, you know, theories. There are all these different operating systems and mainframes and, and then you know, all these windows and Mac and all these things. And then there was this, but kind of behind it all was this idea of kind of the Unix mindset. And the Unix mindset was this thing where basically you don't have these, like, like in the old days, like, like the operating system that like made the computer industry really work, like in the 1960s mm-hmm.Was this thing called o os 360, which was this big operating system that IBM developed that was supposed to basically run everything. And it was this like giant monolithic architecture in the sky. It was like a, you know, it was like a giant castle. Um, of software. And, and by the way, it worked really well and they were very successful with it.But like, it was this huge castle in the sky, but it was this thing, it was almost unapproachable, which is like, you had to be kind of inside IBM or very close to IBM. And you had to really understand every aspect, how the system worked. And then the, the Unix sky is originally out of at and t and then out out of Berkeley, um, you know, came out and they said, no, let's have a completely different architecture.And the way architecture's gonna work is we're gonna have, we're gonna have a, a prompt and, and a, and a shell. And then, and then we're gonna, all, all the functionality is gonna be in the form of these discreet modules, and then you're gonna be able to chain the modules together. Mm-hmm. Yeah. And so like the, the, the op, it's almost like the operating, operating system itself is gonna be a programming language.Um, and then that led led to the, the, the sort of centrality of the shell. Um, and then that led to sort of, uh, you know, basically chaining together Unix tools. And then that led to the emergence of these, these scripting languages like Pearl, where you, you could basically kind of very easily do this, and then the shells got more sophisticated and then, and then, and then look like, you know, that, that, that number one, that worked and that, that was the world I grew up in.Like I was, I was a Unix guy. You know, sort of from, call it 1988 to, you know, kind of all, all the way through my work and it worked really well. It, it's in the background, um, you know, nor normal people don't need to, didn't need to necessarily know about it, but like, if you were doing like system architecture, application development, you, you, you knew all about it.Um, and then, you know, it's been in the background ever since. And, you know, look, your Mac still has a Unix shell, you know, kind of in there, and your iPhone still has a Unix shell kind of buried in there somewhere. So they're kind of in there. And then, you know, the Windows shell is kind of a, you know, sort of a weird derivative of that.But, um, you know, but look, the inter, the internet runs on Unix, um, and that smartphones, actually, both iOS and Android are Unix derivatives. And so, you know, kind of Unix did end up winning. But, but anyway, and then we just started taking that for granted. And then, and then so, so basically the, the way I think about what happened with Pie and then with Open Claw is basically what those guys figured out is, I always say the, the great breakthroughs are obvious in retrospect, right?Which is the best kind, the best kind. They weren't obvious at the time or somebody else would've done them already. Um, and so there is a, like a real conceptual leap, but then you look at it sort of the backwards looking and you're just like, oh, of course. Mm-hmm. Like the, the, to me those are always the best breakthroughs.Well, actually language models themselves are like that. It's just like, oh, next token completion. Oh, of course.swyx: Yeah. What other objective mattered?Marc: Yeah, exactly. But, but like it, right. But she's even saying it wasn't obvious until somebody actually did it. Right. And so the conceptual breakthrough is real and deep and powerful and, and very important.And so the way I think about pie and olaw is it's basically marrying the, the language model mindset to the un to the Unix, basically shell prompt mindset. And so it's, it's basically this idea that what, what, so what is an agent, right? And as, as, and as you know, like many smart people who have been trying to figure out what an agent is for, for, for decades, and they've had many architectures to build agents and the whole thing.And it turns out what is an agent. So it turns out what we now know is an agent is the following. It's, so it's a language model. And then above that, it's a ba, it's a bash shell. Um, so it's a, it's a Unix shell, and then it's, and then the agent has access, uh, has access to, to the shell. And, you know, hopeful, hopefully in a sandbox, maybe in, maybe in a sandbox.So it's, it's the model. Um, it's the shell. Um, and then it's a fi, it's a file system. Um, and then the state is stored in files. And then, you know, there's the markdown format for the, you know, for, for the files themselves. And then, and then there's basically what in Unix is called Aron job. There's a loop and then there's a heartbeat for the, there's heartbeat and, and the thing basically Wake Wakes up.Wakes up. So it's basically LLM plus shell, plus file system, plus markdown, plus kron. And it turns out that's an agent. And, and, and every part of that, other than the model is something that we already completely know and understand. And in fact, it turns out that like the latent power of the Unix shell is like extraordinary because basically like all, like, there's just like an, there's just enormous latent power in the shell.There's enormous numbers of Unix commands, there's enormous number of command line interfaces into all kinds of things already in the, you know, your entire, I mean your entire, just to start with, your computer runs on a shell. If you're running a Mac or a, or, or a phone, your computer, your computer's running on a shell, uh, already.And so like the full power of your computer is available at the command line level. Um, and then it turns out it's really easy to expose other functions as a command line interface. And so like this whole idea where we need like MCP and these like product mm-hmm. Fancy protocols, whatever, it's like, no, we don't, we just need like a command, command line thing.So that's the architecture. And then it turns out what is your agent? Your agent has a bunch of files starting a file system. And then there's the thing that just like completely blew my mind when I write my head around it as a result of this, which is like, okay. This means your agent is now actually independent of the model that it's running on.Because you can actually swap out a different LLM underneath your agent and your, your agent will change personality somewhat. ‘cause the model is different, but all of the state stored in the files will be retained.swyx: Yeah. Different instruction set, but you just compiledit.Marc: Right, exactly. And it's all right.It's like right. Swapping out a ship and recompiling, but it's, it's still, it's still your agent with all of its memories. Um, and with all of its capabilities. And then by the way, you can also swap out the shell, uh, so you can move it to a different execution environment that is also, is also a b shell, by the way, you can also switch out the file system, right.Uh, and you can, and you can, and you can swap out the, the, the heartbeat for the, the crown framework, the, the loop that the agent framework itself. And so your agent basically is ba basically at the end of the day, it's just. It's just, its files. Um, and then, and then there's of course it a openswyx: call.Marc: Yeah, it's, it's basically, it's, it's just the files.Um, and then by the way, as a consequence of that, the agent and then the agent itself, it turns out a couple important things. So one is it, it's, it, it can migrate itself, right? And so you're, you can instruct your agent, migrate yourself to a different, uh, runtime environment, migrate yourself to a different file system, migrate yourself to a different, you know, swap out the language model.Your agent will do all that stuff for you. And then there's the final thing, which is just amazing, which is the agent is the agent actually has full introspection. It actually, it actually knows about its own files and it could rewrite its own files. Right. Which by the way, is basically no widely deployed software system in history where the, the, the thing that you're using actually has full introspective knowledge of how it itself works and is able to modify itself.Like that, that, I mean, there have been toy systems that have had that, but there, there's never been a widely deployed system that has that capability and then that leads you to the capability. That just like completely blew my mind when I wrap my head around it, which is you can tell the agent to add new functions and features to itself and it can do that.Extend yourself. Yeah. Right? Extend, extend yourself. Like extend yourself. Give yourself a new capability. Right? And so, and so literally it's just like you run into somebody at a party and they're like, oh, I have my open claw, do whatever, connect to my eat, sleep bed, and it gives me better advice and sleep.And you go home at night and you tell your claw, or if they're at the party, by the way, you tell your claw, oh, add this capability to yourself. And your claw will say, oh, okay, no problem. And it'll go out on the internet and it'll figure out whatever it needs and then it'll go out to claw code or whatever.It'll write whatever it needs. And then the next thing you know, it has this new capability. And so you don't even have to, like, you can have it upgrade itself without even having to, without having to do anything other than tell it that you want it to do that. And so anyway, so the, the combination of all this is just, I mean, this is just like a massive, incredible, I mean, it's just incredible.Like if I, if I were, if I were 18, like this is a hundred, this is what I would be spending all of my time on. This is like such an incredible conceptual breakthrough. Yeah. And again, pe people are gonna look at it and they already get this response. People are gonna look at it and they're gonna say, oh, well, where's the breakthrough?‘cause these, the, all of these components were already known before. Mm-hmm. But, but this is the key, the key to the breakthrough was by using all these components that were known before, you get all of the underlying capability of that's buried in there. And so all, and so for example, computer use all of a sudden just kind of falls, trivi, trivial.Of course it's gonna be able to use your computer. It has full access to the shell. Right. And then, and then you just, you, you give it access to a browser, and then you've got the computer and the browser and, and often away it goes. And, and then you've got all the abilities of the browser also. Um, yeah.And so, and so the capability unlock here is profound. My friends who are, you know, deepest into this, are having their claw do like a, like, literally like a thousand things in their lives. They have new ideas every day. They're just like constantly throwing new challenges at the thing. And by the way, it's early and, you know, these are, you know, these are prototypes and there are, you know, as you guys know, there's security issues.Yeah. And, and so, you know, there's a bunch of stuff to be ironed out, but the, the unlock of capability is just incredible.swyx: Yeah.Marc: And I, I have absolutely no doubt that everybody in the world is gonna, is gonna have at least, you know, an agent like this, if not an entire family of agents. And w

In this episode of Live Players, Samo Burja and Erik Torenberg discuss the current Iran conflict, how we got into this situation, and how the US can turn this into a winning moment and reindustrialize. Along the way they discuss rebuilding the US military to win the next war using start ups, the exit options for the current administration, and how to decrease the need for oil. — 00:00 Introduction 00:43 Energy independence and Iran 02:49 A brief history of how we got here 08:27 Oil as THE globalized good 24:26 The Options out of Iran 26:25 China's smart moves 29:04 We are in an energy Crisis 32:09 Startups are needed to win the next wars 38:05 Using this war as a way to reindustrialize the US 40:30 US energy change recommendations — Bismark Analysis: https://www.bismarckanalysis.com/ https://twitter.com/samoburja https://twitter.com/eriktorenberg — Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details, please see https://a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

a16z's Ben Horowitz and Erik Torenberg speak with Alex Blania, cofounder and CEO of Tools for Humanity, World, and cofounder of Merge Labs. World is building the largest real human network, a proof-of-human layer for the AI era. They cover the technical challenge of proving human uniqueness at scale using iris biometrics, the privacy architecture behind World ID, and why platforms from social networks to dating apps to video conferencing will soon require proof of human verification.   Resources: Follow Alex Blania on X: https://twitter.com/alexblania Follow Ben Horowitz on X: https://twitter.com/bhorowitz Follow Erik Torenberg on X: https://twitter.com/eriktorenberg Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

a16z general partners Erin Price-Wright and Erik Torenberg speak with Doug Bernauer, founder and CEO of Radiant, and Drew Baglino, founder and CEO of Heron, about rebuilding American energy infrastructure. They discuss portable micro nuclear reactors, solid state power electronics, why delivery rather than generation is the real bottleneck, the case for modular manufacturing, and whether data centers are actually good for the grid.   Resources: Follow Doug Bernauer on X: https://twitter.com/DougBernauer Follow Drew Baglino on X: https://twitter.com/baglino Follow Erin Price-Wright on X: https://twitter.com/espricewright Follow Erik Torenberg on X: https://twitter.com/eriktorenberg Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Noah Smith joins Erik Torenberg at the 2026 American Dynamism Summit in Washington, D.C. to discuss Anthropic's relationship with Washington, bioterrorism risks stemming from AI, why Noah isn't worried about AI causing job loss, and more. - Timestamps: 00:00 - Intro 00:28 - Anthropic, DOD, & Government Control of AI 04:28 - Sponsor: NetSuite 09:44 - Advice for Dario & Anthropic 12:13 - Partisan Politics vs. Existential Risk 16:06 - Mass Surveillance & AI 17:30 - The Biosecurity Threat 24:21 - Will AI Take Our Jobs? 28:41 - Outro - Sponsor: NetSuite More than 42,000 businesses have already upgraded to NetSuite by Oracle, the #1 cloud financial system bringing accounting, financial management, inventory, HR, into ONE proven platform. Download the CFO's Guide to AI and Machine learning: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://netsuite.com/102 - FOLLOW on X: https://twitter.com/eriktorenberg https://twitter.com/Noahpinion - Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details, please see https://a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Bridgit Mendler, Co-founder and CEO of Northwood, joins a16z's Erik Torenberg to discuss the critical but overlooked bottleneck in space: ground infrastructure. Northwood is building the systems that connect satellites back to Earth, enabling faster, more scalable space missions. They cover Bridgit's unconventional path to founding a space company, why vertical integration matters in hard tech, and how modern ground networks could unlock the next wave of innovation in the space economy, from national security to new commercial applications.   Resources: Follow Bridgit on X: https://x.com/bridgitmendler   Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode of Live Players, Samo Burja and Erik Torenberg discuss talent, immigration, culture, and what AI means for them, including novel talent hunting methods, what Denmark gets right, and more. — 00:00 Introduction 01:55 Economists & the Case for Immigration 07:01 Assimilation & Cultural Transformation 12:17 Democracy & Mass Immigration 16:08 The Denmark Model 20:07 The Skilled Immigration Debate 27:57 Optimal Population Size 33:23 AI, Automation & the Future of Labor 39:09 The Future of Immigration Politics 43:12 Peak Human Talent & the Idiocracy Question — Bismark Analysis: https://www.bismarckanalysis.com/ https://twitter.com/samoburja https://twitter.com/eriktorenebrg — Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details, please see https://a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Erik Torenberg sits down with Jacob Helberg to discuss AI, manufacturing, supply chains, and the new geopolitics of technology. Drawing on themes from Helberg's book The Wires of War, they explore why hardware, industrial capacity, and secure supply chains have become central to both economic strength and national security. They also unpack what it means to “win the AI race” — from model leadership and global adoption to energy, compute, tariffs, and reindustrialization in the U.S.   Resources: Find Jacob Helberg on X: https://x.com/jacobhelberg Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode of Live Players, Samo Burja and Erik Torenberg explore ancient complex human society that likely predates agriculture and written history by thousands of years. They discuss ancient seafarers, violence in prehistory, how archaeology needs to change, how irreplaceable historical evidence is being lost, and more. — Timestamps: 00:00 Introduction & Palladium Issue 19 03:30 Ancient Seafaring & Mariners at the Dawn of History 15:00 Native Americans & Pre-Clovis Settlements 20:37 Genomics & Violence in Prehistory 25:14 The Decay of Historical Knowledge & The Digital Dark Age 35:42 Reforming Archaeology for the Future 46:54 Closing thoughts — Palladium Magazine Issue 19: https://www.palladiummag.com/2025/11/17/palladium-19-long-history/ Bismark Analysis: https://www.bismarckanalysis.com/ x.com/samoburja x.com/eriktorenberg — Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details, please see https://a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Alex Rampell and Erik Torenberg speak with Mike Cannon-Brookes, cofounder and CEO of Atlassian, about how to make sense of the SaaS selloff, why not all software companies face the same AI-driven risks, and how Atlassian is thinking about the shift from records to processes. They also examine the real design challenge of getting everyday users to trust and benefit from AI agents in enterprise workflows.   Resources: Follow Alex Rampell on X:  https://twitter.com/arampell Follow Erik Torenberg on X:   https://twitter.com/eriktorenberg Follow Mike Cannon-Brookes on X: https://twitter.com/mcannonbrookes Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Erik Torenberg, Ben Horowitz, and Marc Andreessen discuss how the media landscape has fundamentally changed and what a16z is doing about it. They cover why offense beats defense, why individuals now matter more than corporate brands, why speed wins in the new media landscape, and the difference between oral and written culture on the internet.   Resources: Follow Erik Torenberg on X: https://twitter.com/eriktorenberg Follow Ben Horowitz on X: https://twitter.com/bhorowitz Follow Marc Andreessen on X: https://twitter.com/bhorowitz Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

a16z general partner Erik Torenberg speaks with Justin Mares, founder and CEO of TrueMed. They discuss why American health outcomes are so poor compared to the rest of the developed world, how crop subsidies created a food system that "systematically outputs unhealthy people," and what it would take to treat the chronic disease crisis as a national security issue. Mares explains how TrueMed allows people to spend tax-free HSA and FSA dollars on lifestyle interventions like gym memberships, sleep aids, and healthier food—and why he believes this could redirect hundreds of billions of dollars toward prevention. They also explore the case for psychedelics as mental health therapy and why peptides could disrupt the pharmaceutical industry. Resources:Follow Justin Mares on X: https://x.com/jwmaresFollow TrueMed on X: https://x.com/truemed Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

a16z cofounders Marc Andreessen and Ben Horowitz join a16z general partner Erik Torenberg and Not Boring founder Packy McCormick for a conversation on how the media and information ecosystem has changed over the past decade. The discussion breaks down the shift toward a more open and decentralized speech environment, the rise of writer- and creator-led platforms like Substack, and the erosion of centralized media gatekeepers. Marc and Ben also tie these dynamics to their investing worldview, outlining how supply-driven markets, major technological step changes, and reputation-driven venture platforms shape outcomes in the AI era.Timecodes: 00:00  Introduction00:46  How the media ecosystem is changing4:20  Why a16z invested in Substack6:28  Supply-driven markets and new content creation8:07  Why writers felt trapped by media companies10:09  Databricks and the 10x cloud multiplier13:58  Long-form podcasting proves demand15:40  What the new fund signals about the future16:24  AI as a universal problem solver18:49  Why market sizing is broken20:45  Go-to-market, policy, and platform power22:37  Turning inventors into confident CEOs25:58  Borrowing power to scale faster27:29  Building dreamers, not killing dreams30:46  Reputation as a core competitive advantage35:57  Taking arrows in public38:56  Avoiding big company failure modes40:39  Autonomous teams inside a16z41:54  Venture capital as the last job46:01  Why intangibles matter more than ever48:17  Original thinkers with charisma50:06  Why Zoomers are differentResources: https://www.notboring.co/p/a16z-the-power-brokershttps://www.a16z.news/p/firm-fundFollow Marc Andreessen on X: https://twitter.com/pmarcaFollow Ben Horowitz on X: https://twitter.com/bhorowitzFollow Erik Torenberg on X: https://twitter.com/eriktorenbergFollow Packy McCormick on X: https://twitter.com/packyM Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://twitter.com/eriktorenberg](https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.  Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Nvidia's $5 billion investment in Intel is one of the biggest surprises in semiconductors in years. Two longtime rivals are now teaming up, and the ripple effects could reshape AI, cloud, and the global chip race.To make sense of it all, Erik Torenberg is joined by Dylan Patel, chief analyst at SemiAnalysis, joins Sarah Wang, general partner at a16z, and Guido Appenzeller, a16z partner and former CTO of Intel's Data Center and AI business unit. Together, they dig into what the deal means for Nvidia, Intel, AMD, ARM, and Huawei; the state of US-China tech bans; Nvidia's moat and Jensen Huang's leadership; and the future of GPUs, mega data centers, and AI infrastructure.Resources: Find Dylan on X: https://x.com/dylan522pFind Sarah on X: https://x.com/sarahdingwangFind Guido on X: https://x.com/appenzLearn more about SemiAnalysis: https://semianalysis.com/dylan-patel/ Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts. Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode of Econ 102, Noah Smith and Erik Torenberg cover Europe's economic future, how internet discourse has changed politics, the rise of identitarian populism on both the right and left in America, and more.-Sponsors:NotionAI meeting notes lives right in Notion, everything you capture, whether that's meetings, podcasts, interviews, conversations, live exactly where you plan, build, and get things done.  Here's an exclusive offer for our listeners. Try one month for free at ⁠https://www.notion.com/lp/econ102. NetSuiteMore than 42,000 businesses have already upgraded to NetSuite by Oracle, the #1 cloud financial system bringing accounting, financial management, inventory, HR, into ONE proven platform. Download the CFO's Guide to AI and Machine learning: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://netsuite.com/102 Found Found provides small business owners tools to track expenses, calculate taxes, manage cashflow, send invoices and more. Open a Found account for free at https://found.com-Shownotes brought to you by Notion AI Meeting Notes - try one month for free at https://www.notion.com/lp/econ102Europe continues to focus more on regulation than innovation, creating challenges for economic growthTraditional European industries like auto manufacturing are struggling with the transition to electric vehiclesChinese companies are producing better and cheaper electric cars that align with Europe's climate goalsThe Gaza deal is viewed positively because it considers Gaza's economic future beyond just stopping violenceAn economically self-sustaining Gaza might be less likely to support groups like HamasGulf Arab countries could potentially assist with Gaza's economic development given their expertiseIsrael has been militarily successful against Hamas, Hezbollah, and Iran but faces global criticismIsrael's approach to international criticism has often relied on projecting strength rather than building alliancesIsrael remains dependent on other countries for military supplies despite its own manufacturing capabilitiesRegular people are disengaging from politics, leaving only the most extreme voices engaged ("evaporative cooling effect")Political discussions on platforms like X (Twitter) have become increasingly extremeYoung political staffers who work for both parties are heavily consuming this extremist contentThe speakers observe parallels to the political unrest of the 1960s-70s, which eventually dissipatedUnlike previous eras, today's extremism remains highly visible online even as the general public tunes outDiscussion of Zohran Mamdani's election in New York as representing a new direction in leftist politicsConcern about the mainstreaming of far-right figures like Nick Fuentes who previously were more fringeThe conversation reflects concern about the polarization between extremes while the majority of people disengageThere's agreement that substantive engagement with ideas is needed rather than simply dismissing opponents-Timestamps:00:00 — Introduction00:24 — Europe and Russia03:02 — China and Electric Cars04:38 — Israel-Gaza Conflict06:43 — American Sentiment Toward Israel09:57 – Sponsors: Notion | Netsuite12:00 — Online Extremism and Political Disengagement22:50 — Staffers and Extremism24:25 – Sponsor: Found25:29 — New York Politics and Mamdani31:47 — The Future of Leftist Politics34:11 — Race and Identity38:06 — Islam and Immigration38:44 — Identitarian Populism41:44 — Closing Thoughts-FOLLOW on X:https://x.com/eriktorenberghttps://x.com/Noahpinion-Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details, please see https://a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

What if America tried to eliminate crime instead of just reacting to it? Not with slogans, but with staffing, technology, and strategy scaled to the problem. In this episode, Erik Torenberg speaks with Garrett Langley, founder and CEO of Flock Safety, and Ben Horowitz, cofounder of a16z, about what is happening in the cities that are trying. Flock now works with over 5,000 communities to detect crime, recover missing children, and close cases faster than ever. Ben has been closely involved in Las Vegas, where Flock technology, drones, and community policing have raised clearance rates while reducing use of force. They outline what a real national crime-reduction strategy could look like: solving the police staffing crisis, using intelligence to make policing safer, understanding why clearance rates have collapsed, and how public–private partnerships are filling gaps cities cannot. They also tackle the hard questions around privacy, criminal justice failures, and the hidden role of organized crime in everyday offenses. Timecodes: 0:00 — Introduction and the Cost of Crime1:09 — Technology, Privacy, and Trust in Policing1:22 — Eliminating Crime: A National Strategy2:54 — People: Staffing, Culture, and Recruitment8:45 — Products: Technology in Modern Policing9:41 — Policy: Accountability and Prosecution20:11 — Community Policing and Clearance Rates25:16 — Case Study: Las Vegas and Public-Private Partnerships32:00 — Criticisms, Privacy, and Trust35:23 — Economic Mobility, Safety, and Social Impact36:44 — Reform, Recidivism, and Alternative Approaches52:14 — Organized Crime and Policy Challenges54:32 — The Future of Policing: Intelligence and Precision57:24 — Success Stories and ConclusionResources: Follow Garrett on X: https://twitter.com/glangley Follow Ben on X: https://twitter.com/bhorowitz Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details, please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Jonathan Swanson has built two rare successes: Thumbtack, the home-services marketplace, and Athena, the fast-growing platform that pairs ambitious people with world-class personal assistants. Today he runs a 4,000-person company, invests on the side, and raises four kids — all by designing his life around leverage.a16z General Partner, Erik Torenberg, sits down with Jonathan to unpack what that actually looks like. They discuss how elite assistant culture shaped his philosophy, why delegation is a skill most founders never truly learn, and how the combination of humans and AI is redefining personal productivity. Jonathan explains why he believes ambition grows with leverage, not the other way around, and breaks down how he delegates everything from scheduling to search processes to entire life systems.They also get into the future of work, the rise of machine-generated delegation, the expanding role of chiefs of staff, and how founders can design their time around the few things that matter most. It's a conversation about work, life, and the systems that allow people to operate at scale. Resources:Follow Jonathan on X: https://x.com/swaaansonFollow our host: https://twitter.com/eriktorenberg Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

a16z General Partners David Haber, Alex Rampell, and Erik Torenberg discuss why 19 out of 20 AI startups building the same thing will die - and why the survivor might charge $20,000 for what used to cost $20.They expose the "janitorial services paradox" (why the most boring software is most defensible), explain why OpenAI won't compete with your orthodontic clinic software despite having 800 million weekly users, and reveal how non-lawyers are building the most successful legal AI companies. Plus: the brutal truth about why momentum isn't a moat, but without it, you're already dead. Resources:Follow David on X: https://x.com/dhaberFollow Alex on X: https://x.com/arampellFollow Erik on X: https://x.com/eriktorenberg Stay Updated:If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

A16z Podcast: Read the notes at at podcastnotes.org. Don't forget to subscribe for free to our newsletter, the top 10 ideas of the week, every Monday --------- Emmett Shear, founder of Twitch and former OpenAI interim CEO, challenges the fundamental assumptions driving AGI development. In this conversation with Erik Torenberg and Séb Krier, Shear argues that the entire "control and steering" paradigm for AI alignment is fatally flawed. Instead, he proposes "organic alignment" - teaching AI systems to genuinely care about humans the way we naturally do. The discussion explores why treating AGI as a tool rather than a potential being could be catastrophic, how current chatbots act as "narcissistic mirrors," and why the only sustainable path forward is creating AI that can say no to harmful requests. Shear shares his technical approach through multi-agent simulations at his new company Softmax, and offers a surprisingly hopeful vision of humans and AI as collaborative teammates - if we can get the alignment right. Resources:Follow Emmett on X: https://x.com/eshearFollow Séb on X: https://x.com/sebkrierFollow Erik on X: https://x.com/eriktorenberg Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.   Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Emmett Shear, founder of Twitch and former OpenAI interim CEO, challenges the fundamental assumptions driving AGI development. In this conversation with Erik Torenberg and Séb Krier, Shear argues that the entire "control and steering" paradigm for AI alignment is fatally flawed. Instead, he proposes "organic alignment" - teaching AI systems to genuinely care about humans the way we naturally do. The discussion explores why treating AGI as a tool rather than a potential being could be catastrophic, how current chatbots act as "narcissistic mirrors," and why the only sustainable path forward is creating AI that can say no to harmful requests. Shear shares his technical approach through multi-agent simulations at his new company Softmax, and offers a surprisingly hopeful vision of humans and AI as collaborative teammates - if we can get the alignment right. Resources:Follow Emmett on X: https://x.com/eshearFollow Séb on X: https://x.com/sebkrierFollow Erik on X: https://x.com/eriktorenberg Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.   Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode of Econ 102, Noah Smith and Erik Torenberg explore AI's effects on productivity, how AI business models will shake out, the US and China's rare earth minerals industries, and China's economic challenges, including demographics, real estate, and involution.-Sponsors:NotionAI meeting notes lives right in Notion, everything you capture, whether that's meetings, podcasts, interviews, conversations, live exactly where you plan, build, and get things done.  Here's an exclusive offer for our listeners. Try one month for free at ⁠https://www.notion.com/lp/econ102⁠NetSuiteMore than 42,000 businesses have already upgraded to NetSuite by Oracle, the #1 cloud financial system bringing accounting, financial management, inventory, HR, into ONE proven platform. Download the CFO's Guide to AI and Machine learning: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://netsuite.com/102⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Found Found provides small business owners tools to track expenses, calculate taxes, manage cashflow, send invoices and more. Open a Found account for free at https://found.com/econ102-Shownotes brought to you by Notion AI Meeting Notes - try one month for free at https://www.notion.com/lp/econ102⁠AI can affect productivity in multiple ways: replacing humans, enhancing human productivity, creating new tasks, and increasing capital productivityAI may follow other essential industries with low profit margins despite creating enormous value:Like farming, solar power, and airlinesCode-related AI applications are seeing particularly strong adoptionVertical AI applications in specific industries (healthcare, legal, real estate) are gaining tractionChina controls the majority of rare earth mining and refiningThe US has sufficient rare earth deposits but faces two challenges:Regulatory barriers to miningLack of solvent extraction technology and know-howChina's fertility rate is lower than Japan and EuropeHowever, a "baby bulge" (ages 7-22) will support the workforce short-term-Timestamps:00:00 — Intro00:52 — AI's impact on productivity02:27 — Debating whether AI will increase productivity03:11 — Historical analogy: Electricity's impact on productivity, lessons for AI07:55 — Sponsors: Notion | Netsuite09:57 — Application layer companies, AI in coding, vertical AI applications12:49 — AI bubble vs. CapEx boom/bust, historical parallels (railroads, telecoms)16:54 — Brand loyalty, price wars, and profitability in AI models22:26 — US-China trade, rare earths, and supply chain challenges32:20 — Sponsor: Found33:33 — China's demographic and economic challenges, over-competition, and deflation54:06 — Recommendations for China's economic policy, rationalizing the economy-FOLLOW on X:https://x.com/eriktorenberghttps://x.com/Noahpinion-Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details, please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Priscilla Chan and Mark Zuckerberg join a16z's Ben Horowitz, Erik Torenberg, and Vineeta Agarwala to share how the Chan Zuckerberg Initiative is building the computational tools that will accelerate the cure, prevention, and management of all disease by century's end. They explain why basic science needs $100 million-scale projects that traditional NIH grants can't fund, how their Cell Atlas became biology's missing periodic table with millions of cells catalogued in open-source format, and why their new virtual cell models will let scientists test high-risk hypotheses in silico before investing in expensive wet lab work. Plus: the organizational shift unifying the Biohub under AI leadership, what happens when biologists and engineers sit side-by-side, and why modern biology labs are expanding compute instead of square footage. Timestamps:4:17 - Building tools to accelerate scientific discovery5:47 - The credible path to funding basic science7:21 - Biohub = Frontier Biology + Frontier AI9:05 - Challenges building on a 10-15 year timeline9:43 - How CZI chooses what to work on11:15 - Making sense of science with LLMs11:31 - Measuring success in the therapeutic realm13:32 - “Most diseases should be thought of as rare diseases”15:39 - Inspiration: building a periodic table for biology19:27 - Why virtual cells?21:17 - The Biohub Master Plan21:51 - How virtual cell models allow more risk taking28:15 - Bringing CZI & Biohub together30:32 - Why Biohub matters33:36 - The importance of interface design in democratizing scientific discovery35:34 - How Biohub encourages cross-functional collaboration40:38 - Looking ahead: the broader impact of AI on biotech Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

As global tensions rise, AI and autonomy are transforming how nations prepare for conflict.In this episode, Horacio Rozanski, CEO of Booz Allen Hamilton and Gary Shield, CEO of Shield AI join Erik Torenberg to discuss how technology, speed, and public–private partnerships are reshaping America's defense strategy.They cover lessons from Ukraine and Taiwan, the rise of autonomous systems, and why the future of warfare will be defined by software, agility, and innovation. Resources:Follow Gary on X: https://x.com/garylsteeleFind Horacio on LinkedIn: https://www.linkedin.com/in/horacio-rozanski-84a2519 Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Erik Torenberg joins to debate whether recent developments suggest AI progress is slowing down or stalling, addressing arguments from Cal Newport and others. Nathan counters this view by highlighting significant qualitative advances, including 100X context window expansion, real-time interactive voice, improved reasoning, vision, and AI's growing contributions to hard sciences. The conversation then covers AI's impact on the labor market, the potential for AI protectionism, and concerns about recursive self-improvement. This episode argues that AI capabilities are not stopping, with frontier developers seeing a clear path for continued rapid progress in the coming years. Sponsors: Tasklet: Tasklet is an AI agent that automates your work 24/7; just describe what you want in plain English and it gets the job done. Try it for free and use code COGREV for 50% off your first month at https://tasklet.ai Linear: Linear is the system for modern product development. Nearly every AI company you've heard of is using Linear to build products. Get 6 months of Linear Business for free at: https://linear.app/tcr Shopify: Shopify powers millions of businesses worldwide, handling 10% of U.S. e-commerce. With hundreds of templates, AI tools for product descriptions, and seamless marketing campaign creation, it's like having a design studio and marketing team in one. Start your $1/month trial today at https://shopify.com/cognitive PRODUCED BY: https://aipodcast.ing CHAPTERS: (00:00) About the Episode (03:49) Is AI Slowing Down? (09:15) Newport's Scaling Law Theory (16:56) The Value of Reasoning (Part 1) (17:17) Sponsors: Tasklet | Linear (19:57) The Value of Reasoning (Part 2) (24:52) Explaining GPT-5's Vibe Shift (31:39) AI's Impact on Jobs (Part 1) (36:50) Sponsor: Shopify (38:47) AI's Impact on Jobs (Part 2) (44:08) Recursive Self-Improvement via Code (49:35) The Future of Engineers (53:24) Economic Pressure vs. Protectionism (58:29) Progress Beyond Language Models (01:07:11) The State of AI Agents (01:19:19) China's Open Source Models (01:29:44) A Positive Vision Forward (01:37:39) Outro SOCIAL LINKS: Website: https://www.cognitiverevolution.ai Twitter (Podcast): https://x.com/cogrev_podcast Twitter (Nathan): https://x.com/labenz LinkedIn: https://linkedin.com/in/nathanlabenz/ Youtube: https://youtube.com/@CognitiveRevolutionPodcast Apple: https://podcasts.apple.com/de/podcast/the-cognitive-revolution-ai-builders-researchers-and/id1669813431 Spotify: https://open.spotify.com/show/6yHyok3M3BjqzR0VB5MSyk

In this episode of Monitoring the Situation, Marc Andreessen, Katherine Boyle, and Erik Torenberg dive into the movies that best explain America, from Once Upon a Time in Hollywood to Tropic Thunder to Fight Club.They explore how Tarantino's revisionist masterpiece reimagines 1969 and the end of America's cultural innocence, why Tropic Thunder was the last truly un-cancellable comedy, and how Fight Club evolved from a left-wing critique of capitalism to a right-wing prophecy about alienation and identity.Along the way, they trace the parallels between the counterculture of the 1960s and the internet culture wars of the 2010s, and debate whether we're living through another great American cultural reset. Resources:Follow Marc on X: https://x.com/pmarcaFollow Katherine on X: https://x.com/KTmBoyle Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Amjad Masad, founder and CEO of Replit, joins a16z's Marc Andreessen and Erik Torenberg to discuss the new world of AI agents, the future of programming, and how software itself is beginning to build software.They trace the history of computing to the rise of AI agents that can now plan, reason, and code for hours without breaking, and explore how Replit is making it possible for anyone to create complex applications in natural language. Amjad explains how RL unlocked reasoning for modern models, why verification loops changed everything, whether LLMs are hitting diminishing returns — and if “good enough” AI might actually block progress toward true general intelligence. Resources:Follow Amjad on X: https://x.com/amasadFollow Marc on X: https://x.com/pmarcaFollow Erik on X: https://x.com/eriktorenberg Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Reid Hoffman has been at the center of every major tech shift, from co-founding LinkedIn and helping build PayPal to investing early in OpenAI. In this conversation, he looks ahead to the next transformation: how artificial intelligence will reshape work, science, and what it means to be human.In this episode, Reid joins Erik Torenberg and Alex Rampell to talk about what AI means for human progress, where Silicon Valley's blind spots lie, and why the biggest breakthroughs will come from outside the obvious productivity apps. They discuss why reasoning still limits today's AI, whether consciousness is required for true intelligence, and how to design systems that augment, not replace, people.Reid also reflects on LinkedIn's durability, the next generation of AI-native companies, and what friendship and purpose mean in an era where machines can simulate almost anything. This is a sweeping, high-level conversation at the intersection of technology, philosophy, and humanity. Resources:Follow Reid on X: ​​x.com/reidhoffmanFollow Alex on X: x.com/arampell Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Hollywood is going through a major cultural and creative reset, and Marc Andreessen thinks it's long overdue.In this episode of Monitoring the Situation, Marc joins Erik Torenberg and Katherine Boyle to dissect the past decade of filmmaking, from the rise of “the message” in every movie to the return of genuine comedy and art. They cover the post-woke shift in Hollywood, the financial collapse of the streaming era, and why AI could spark a renaissance for a new generation of independent filmmakers.Marc also shares his favorite recent films (and the ones he thinks aged terribly), why Edington might be the first true “Capital-A Art” film in years, and how AI could democratize storytelling the way digital cameras did in the 1990s. Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

From politics to technology to real estate, Keith Rabois has bold predictions for America's next decade.In this conversation with Erik Torenberg, Keith breaks down why he believes the U.S. is entering a new economic expansion driven by AI, productivity, and sovereign technology. They discuss how AI could lift GDP growth to 5%, why sovereign AI projects are inevitable, and why America can “grow its way out” of debt.Keith also shares his takes on Trump's second term, the decline of legacy institutions, OpenAI's dominance, the future of Google and Microsoft, and how startups like Ramp and Opendoor are rewriting the rules of fintech and housing. Resources:Follow Keith on X: https://x.com/raboisFollow Alex on X: https://x.com/arampell Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.  Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Nathan Labenz is one of the clearest voices analyzing where AI is headed, pairing sharp technical analysis with his years of work on The Cognitive Revolution.In this episode, Nathan joins a16z's Erik Torenberg to ask a pressing question: is AI progress actually slowing down, or are we just getting used to the breakthroughs? They discuss the debate over GPT-5, the state of reasoning and automation, the future of agents and engineering work, and how we can build a positive vision for where AI goes next. Resources:Follow Nathan on X: https://x.com/labenzListen to the Cognitive Revolution: https://open.spotify.com/show/6yHyok3M3BjqzR0VB5MSykWatch Cognitive Revolution: https://www.youtube.com/@CognitiveRevolutionPodcast Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ben Horowitz founded Loudcloud in the middle of the dot-com bust and sold it for $1.6 billion, then led Andreessen Horowitz from its founding to $46 billion in committed capital. Ali Ghodsi co-founded Databricks, stepped in as CEO during a crisis, and led it to a valuation of over $100 billion.In this episode of “Boss Talk”, Ben and Ali join a16z General Partners Sarah Wang and Erik Torenberg to share founder war stories, how to hire and make deals, how to keep culture intense without burning employees out, and why founders should raise their ambitions even higher. ResourcesFollow Ali on X: https://x.com/alighodsiLearn more about Databricks: https://www.databricks.com/Follow Ben on X: https://x.com/bhorowitzFollow Sarah on X: https://x.com/sarahdingwangFollow Erik on X: https://x.com/eriktorenberg Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Resources:Find a16z on X: https://x.com/a16zSubscribe to a16z on Substack: https://a16z.substack.com/Find a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenberg Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Opendoor is trying to make it easier to buy a home. Kaz Nejatian just joined as CEO to help them succeed.In this episode, a16z General Partners Alex Rampell and Erik Torenberg sit down with Kaz to cover all things real estate and marketplaces. They cover Kaz's vision for Opendoor, the problem with copying the hedge fund model, how to build through economic downturns, and the importance of ambition and long-term thinking. Resources:Follow Kaz on X: https://x.com/CanadaKazFollow Alex on X: https://x.com/arampell Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Resources:Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ben, Marc, and Erik Torenberg are joined by Brian Schimpf, Co-Founder & CEO of Anduril, and Chris Power, Founder & CEO of Hadrian. Together, they dig into America's defense production gap: why the U.S. can out-innovate but not out-produce—and what it will take to turn that around.They discuss why U.S. war games show we run out of munitions in a week, the myth of “exquisite-only” systems, how to rebuild industrial capacity with software-led automation, financing factories like data centers, and what it takes to create real deterrence in a Taiwan scenario. Timecodes: 0:00 Introduction0:27 Technical Superiority vs. Industrial Scale  3:59 The Decline of US Manufacturing  7:23 Challenges in Onshoring & Skilled Labor  13:27 Supply Chains & Rare Earths  15:34 Automation, Software, and Catching Up  17:15 Complexity of Modern Production  23:34 Strategic Policy & Industrial Planning  26:37 Regulatory Barriers & State vs. Federal Roles  35:27 Talent, Data Centers, and Financial Engineering  38:33 China's Industrial Policy & US Response  46:07 US Manufacturing, National Security, and the China Challenge  52:00 Demographics, Long-Term Outlook, and Closing Thoughts   Resources: Find Chris on X: https://x.com/chris_powerFind Brian on LinkedIn: https://www.linkedin.com/in/bschimpf/Marc on X: https://x.com/pmarcaMarc's Substack: https://pmarca.substack.com/Ben on X: https://x.com/bhorowitz Stay Updated: Find us on X:https://x.com/a16zFind us on LinkedIn: https://www.linkedin.com/company/a16zThe views expressed here are those of the individual personnel quoted and are not the views of a16z or its affiliates. This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors and may not under any circumstances be relied upon when making a decision to invest in any a16z funds. PLEASE SEE MORE HERE: https://a16z.com/disclosures/ Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Should the US put a price on H-1B visas, or would that block the flow of new talent? Are AI coding agents actually making teams way more productive, or is it just hype? And in the AI platform shift, will the big winners be incumbents or new AI-native startups?Erik Torenberg is joined by Box co-founder and CEO Aaron Levie, a16z board partner Steven Sinofsky, and a16z general partner Martin Casado to debate the biggest questions in tech. They unpack pricing vs lottery for H-1Bs and what we're actually optimizing for, why Box now ships a third of its code from AI, the shift from writing to reviewing code, and why bottom-up personal AI tools succeed where top-down “AI pilots” struggle. Timecodes: 0:00 Introduction1:07  Latest immigration policy and who benefits1:39  Debating the Price on H-1B Visas2:11  Startups vs. Big Tech: Who Benefits from Policy?2:31  Market Dynamics and Wage Impacts3:44  The Lottery System and Startup Challenges12:25  Labor Markets to Labor Productivity with AIs14:47  Startups Achieving 10x Productivity with AI16:43  Early Adopters, Hype, and Measuring Productivity33:50  AI's Impact on Professional and Creative Work37:56  The Rise of AI-Native Startups40:58  Platform Shifts: Startups vs. Incumbents42:12  Disruption, Incumbents, and New Opportunities53:00  The Future of Work and AI Adoption54:38  Brand Effects and Early Leaders in AI55:22  Will Incumbents or Newcomers Win the AI Race?Resources:Find Aaron on X: https://x.com/levieFind Steven on X: https://x.com/stevesiFind Martin on X: https://x.com/martin_casadoFind Erik on X: https://x.com/eriktorenberg Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Nvidia's $5 billion investment in Intel is one of the biggest surprises in semiconductors in years. Two longtime rivals are now teaming up, and the ripple effects could reshape AI, cloud, and the global chip race.To make sense of it all, Erik Torenberg is joined by Dylan Patel, chief analyst at SemiAnalysis, joins Sarah Wang, general partner at a16z, and Guido Appenzeller, a16z partner and former CTO of Intel's Data Center and AI business unit. Together, they dig into what the deal means for Nvidia, Intel, AMD, ARM, and Huawei; the state of US-China tech bans; Nvidia's moat and Jensen Huang's leadership; and the future of GPUs, mega data centers, and AI infrastructure. Resources: Find Dylan on X: https://x.com/dylan522pFind Sarah on X: https://x.com/sarahdingwangFind Guido on X: https://x.com/appenzLearn more about SemiAnalysis: https://semianalysis.com/dylan-patel/ Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends!Find a16z on X: https://x.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zListen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYXListen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Can we make science as fast as software? In this episode, Erik Torenberg talks with Patrick Hsu (cofounder of Arc Institute) and a16z general partner Jorge Conde about Arc's “virtual cells” moonshot, which uses foundation models to simulate biology and guide experiments. They discuss why research is slow, what an AlphaFold-style moment for cell biology could look like, and how AI might improve drug discovery. The conversation also covers hype versus substance in AI for biology, clinical bottlenecks, capital intensity, and how breakthroughs like GLP-1s show the path from science to major business and health impact. Resources:Find Patrick on X: https://x.com/pdhsuFind Jorge on X: https://x.com/JorgeCondeBio Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

What happens when AI collides with salesmanship, streaming-era sports, and healthcare?In this episode, Erik Torenberg is joined by Mark Cuban, entrepreneur, Dallas Mavericks co-owner, and founder of Cost Plus Drugs.Topics include fiery group chats and how dissent sharpens thinking, the sales playbook of modern politics, and concrete fixes for U.S. healthcare like ending PBM opacity, publishing real prices, and government-backed patient financing. Mark also explains how AI is pushing media from “social” to algorithmic, why he expects millions of models, and why ESOPs are an underrated wealth engine. He shares what he'd build today and weighs in on NBA economics under the new collective bargaining agreement.Timecodes: 00:00 Introduction 00:47 Salesmanship, Politics, and Social Media04:05 AI, Algorithms, and the Future of Media06:29 Fragmentation of Social Platforms09:04 Political Messaging & Economic Populism12:05 Wealth, Equity, and Employee Ownership16:39 AI's Impact on Education and Healthcare21:32 Fixing the US Healthcare System29:39 Entrepreneurship in the Age of AI33:38 Business Success, Sports, and Investments35:32 NBA Economics and Team Building50:44 Personal Priorities & Closing Thoughts Resources: Find Mark on X: https://x.com/mcuban Stay Updated: Let us know what you think: https://ratethispodcast.com/a16zFind a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

What if the future of media isn't controlled by algorithms or legacy institutions—but by independent voices building directly with their audiences?In this episode, Erik Torenberg is joined by Chris Best, cofounder and CEO of Substack, along with a16z general partners Katherine Boyle and Andrew Chen.We trace the origin story of Substack and its cultural impact, including how it reinvented the business model for independent media. We also explore the evolution of blogging, the rebundling of media, and what the future holds as attention becomes the scarcest resource.Timecodes: 00:00 Introduction03:50 Origins of Substack06:29 The Evolution of Blogging & Media Models09:15 Direct Audience Connection & Platform Independence10:57 Vision for Substack & The Role of Algorithms21:06 Business Models: Ads, Subscriptions, and AI26:10 The Scarcity of Attention & Value of Good Content27:45 Unbundling, Rebundling, and the Future of Media Companies37:12 Academia, Books, and Changing Content Formats44:31 Substack's Next Phase & Closing ThoughtsResources: Find Chris on Substack: https://cb.substack.com/Find Chris on X: https://x.com/cjgbestFind Andrew Chen on Substack: https://andrewchen.substack.com/Find Andrew on X: https://x.com/andrewchenFind Katherine on X: https://x.com/KTmBoyleFind Katherine on Substack: https://boyle.substack.com/Stay Updated: Let us know what you think: https://ratethispodcast.com/a16zFind a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

What exactly is an AI agent, and how will agents change the way we work?In this episode, a16z general partners Erik Torenberg and Martin Casado sit down with Aaron Levie (CEO, Box) and Steven Sinofsky (a16z board partner; former Microsoft exec) to unpack one of the hottest debates in AI right now.They cover:Competing definitions of an “agent,” from background tasks to autonomous internsWhy today's agents look less like a single AGI and more like networks of specialized sub-agentsThe technical challenges of long-running, self-improving systemsHow agent-driven workflows could reshape coding, productivity, and enterprise softwareWhat history — from the early PC era to the rise of the internet — tells us about platform shifts like this oneThe conversation moves from deep technical questions to big-picture implications for founders, enterprises, and the future of work. Timecodes: 0:00 Introduction: The Evolution of AI Agents0:36 Defining Agency and Autonomy1:54 Long-Running Agents and Feedback Loops4:49 Specialization and Task Division in AI6:20 Human-AI Collaboration and Productivity6:59 Anthropomorphizing AI and Economic Impact9:10 Predictions, Progress, and Platform Shifts11:31 Recursive Self-Improvement and Technical Challenges13:20 Hallucinations, Verification, and Expert Productivity16:20 The Role of Experts and Tool Adoption22:14 Changing Workflows: Agents Reshaping Work Patterns45:55 Division of Labor, Specialization, and New Roles48:47 Verticalization, Applied AI, and the Future of Agents54:44 Platform Competition and the Application Layer55:29 Closing Thoughts and Takeaways  Resources: Find Aaron on X: https://x.com/levieFind Martin on X: https://x.com/martin_casadoFind Steven on X: https://x.com/stevesi Stay Updated: Let us know what you think: https://ratethispodcast.com/a16zFind a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://x.com/eriktorenbergPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.