TBPN - CitriniPocalypse, Dot Com Lore, Gene-Edited Polo Horses | Alap Shah, Will Brown, Michelle Lee, Mike Annunziata

Episode Date: February 23, 2026

Sign up for TBPN’s daily newsletter at TBPN.com(00:18) - CitriniPocalypse (18:37) - The Durability of Institutional Inertia (30:26) - 𝕏 Timeline Reactions (44:01) - The Dot Com Boom (01:00:21) - Polo's Gene-Edited Horse Clones (01:11:06) - 𝕏 Timeline Reactions (01:29:24) - Alap Shah, co-founder and former CEO of Sentieo, an AI-powered financial research platform, discusses the transformative impact of AI on white-collar employment, highlighting a significant decline in information sector jobs since 2022. He emphasizes the potential for AI to further disrupt the labor market, particularly as corporate adoption accelerates, and underscores the need for proactive measures to address these challenges. (02:00:11) - Will Brown, Research Lead at Prime Intellect, discusses the company's recent release of a training platform designed to simplify reinforcement learning (RL) on open-source models, enabling users to focus on environment design and task specification without hardware concerns. He highlights the platform's accessibility, allowing users to train models effectively by converting existing data into training recipes, and notes the positive reception from the community. Additionally, Brown touches on the evolving landscape of AI, emphasizing the importance of customization and the potential of open-source models to achieve state-of-the-art performance in specialized tasks. (02:23:31) - Michelle Lee is the founder and CEO of Medra, a company developing physical AI scientists to automate laboratory experiments and accelerate drug discovery. In the conversation, she discusses her background in chemical engineering and robotics, the development of intelligent robots capable of autonomously conducting experiments, and Medra's recent $52 million Series A funding to build one of the largest autonomous labs in the United States. (02:30:59) - 𝕏 Timeline Reactions (02:37:36) - Mike Annunziata, Founder and Managing Partner at Also Capital, has a background in venture capital and entrepreneurship, including co-founding Farther Farms and serving as a board member at Varda Space Industries. In the conversation, he discusses his non-traditional path into venture capital, emphasizing the importance of investing in founders who are magnets for top-tier talent and have a clear, pragmatic vision. He also highlights the significance of having fun while playing to win, and announces the launch of Also Capital's second fund, totaling $50 million. (03:00:07) - 𝕏 Timeline Reactions TBPN.com is made possible by:Ramp - https://Ramp.comAppLovin - https://axon.aiCisco - https://www.cisco.comCognition - https://cognition.aiConsole - https://console.comCrowdStrike - https://crowdstrike.comElevenLabs - https://elevenlabs.ioFigma - https://figma.comFin - https://fin.aiGemini - https://gemini.google.comGraphite - https://graphite.comGusto - https://gusto.com/tbpnKalshi - https://kalshi.comLabelbox - https://labelbox.comLambda - https://lambda.aiLinear - https://linear.appMongoDB - https://mongodb.comNYSE - https://nyse.comOkta - https://www.okta.comPhantom - https://phantom.com/cashPlaid - https://plaid.comPublic - https://public.comRailway - https://railway.comRestream - https://restream.ioSentry - https://sentry.ioShopify - https://shopify.com/tbpnTurbopuffer - https://turbopuffer.comVanta - https://vanta.comVibe - https://vibe.coFollow TBPN: https://TBPN.comhttps://x.com/tbpnhttps://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231https://podcasts.apple.com/us/podcast/technology-brothers/id1772360235https://www.youtube.com/@TBPNLive

You're watching TVPN. Today is Monday, February 23rd, 2026. We are live from TVPEN, Oldeastern, the Temple of Technology, the Fortress of Finance, the Capital of Capital. Let me tell you about ramp.com. Time is money, save both. These use corporate cards, bill pay, accounting,

and a whole lot more, all in one place, let's go. Massive sell off in the markets, thanks to friend of the show, Satrini. We have someone from Satrini coming on the show in just a little bit. Lots of crazy reaction, really broke through with something that is framed as sort of fan fiction, low probability.

And it's always interesting when someone post something and they're like, I think there's a 10% chance of this happens, so it's worth talking about. And I'm like, what's the 90% scenario? No one's getting any clicks for the 90% scenario. And it gets completely written out. It's not that exciting. Yeah, and throwing out something like, oh yeah,

like 10% chance that this crazy thing happens, that doesn't, that people don't react to it, like it's a 10% scenario, or whatever percentage you put on, a 20% chance, 30% P-Doom, they only take away from what you said. It's over. Yeah, no, immediately. And it's the same thing with all of the AI Lab CEOs.

When press, they'll be like, well, I do think that there's a 10% chance that humanity dies, or something like that. And that, the headline is predicts humanity dies. Like, as soon as you say, Like something crazy happens with no matter how low the percentages, like that's what you're going to be known for forever. So be careful out there with those predictions. But.

Okay. So Sunday yesterday. Did this say Sunday? Doing a lot of. Okay. Yeah. Yeah. Yeah.

Yeah. Yeah. Really took it off. Yeah. Doing family stuff. Don't really have a bunch of time to like sit down and read something. And the entire day, I'm just seeing people quoting it being like, this is the best essay that I have ever read. So many people that I think are generally pretty smart.

And then by the time I actually, after the kid's bedtime last night, by the time I actually sat down and started reading it, it was every, almost every paragraph I was experiencing some element of gelman's amnesia where like you have like three sentences that are like maybe somewhat coherent and then like a statement that feels like so wrong. Sure, sure, sure. Specifically, I think a lot of people obviously called out the DoorDash thing. The DoorDash comment, which there's so many businesses that you could have chosen in DoorDash's place. But it didn't matter. DoorDash is down 6.8% today. The Citrini selloff is here. Satrini Possible. Despite tracking close to a billion.

Isn't it a billion monthly orders? Something insane. My experience with it was you had mentioned to me that they're like, oh, it's the current thing and I was pretty offline. And then by the time I actually started refreshing the timeline, I was like, oh, I'm like clearly like stuck on some search feature because I'm only seeing Cotrini posts and like posts reacting to it

and reacting to the reaction. And it had done a full news cycle, both a backlash and then a backlash to the backlash and take him's getting in there fighting and people are posting rebuttals and someone posted a fully AI generated, just like turned it up another. not version, which is hilarious. He's like, if that wasn't extreme enough, I got something even more extreme for you. People were having a lot of fun with it. Sunday is for the posters, I guess.

People are having fun. What should we read through of the actual Satrini article? Because it is sort of long, and we do have someone from Satrini coming on the show. So we can maybe go through some of the reactions. I mean, the futures were read last night. The market is down broad. Yeah, and it's interesting. A lot of people were saying, guys, there's no. way that futures are read just because of the Satrini essay that is obviously science fiction. Yeah. And then it turns out Bloomberg this morning came out and actually stated that it's the Satrini sell-off.

Yeah, yeah. But I mean, there were also the tariff things. The tariff news was sort of digested on Friday, Saturday, so there was totally, like that could be possible. There's a lot of other stuff going on. Joe Weisandthal as opposed to the Satrini sell-off. The quote from the terminal, software payment stocks slide after Satrini post on AI risk, DoorDash and American Express led declines in software and payment stocks on Monday.

And we were debating, like, you know, PayPal had gotten beat up, and there was a question about, like, what is the strategy going forward? PayPal has always been an interesting situation because, like, absolutely goaded founding team, but they're all disinterested in jumping back in and turn it. it around. Yeah, or you have Max with a firm who over a long enough time horizon will probably compete in every. Yeah. And it's hard because even if you went back, how do you build a position, how do you get control of that company? But it does seem like there's some value there. There's some stickiness. And it'll be interesting to see, does it go private? Does the new

management come in? I mean, they already have some new management. So I'm not exactly sure where it goes, but it feels like the payment rail thing will be sticky for a while. Young Macro had a take. quote tweeting Satrini. Good and interesting piece but a necessary caveat is that it's essentially a hypothetical conditioned on severe institutional failure rather than some sort of macro inevitability as the piece itself notes one of its two failure modes liquidity stress and capital impairment includes a liquidity component that the Fed can address quickly with liquidity facilities and asset purchases repo lines quality of easing as seen in recent

episodes of banking stress. Losses from impaired assets won't disappear, but can in principle be moved where the broadest shoulders are. It's an odd situation because you're seeing all of this capital evaporate from the public tech markets, but the labs aren't public yet. So they can't fully absorb it, like they sort of can, but it's much more opaque. And it's not like most, the average investor can't just read this piece and be like, okay, I believe it. I am worried about soft software stock, so I'm going to rotate into a basket of anthropic, Open AI, and SpaceX. They don't have that option yet. They might by the end of the year.

You can buy Nvidia, you can buy Google. There's plenty of ways. Yeah, totally, totally. Just look at Leopoldoshenbrenner's allocations and copy trade that, I suppose. Plenty in this hypothetical economy, much more than before, he says. There will be plenty of broad shoulders. Couldn't they just tax anthropic into paying all your pensions in this hypothetical scenario? This would be done through regulatory or fiscal mechanism.

The second failure mode and aggregate demand shortfall for massive unemployment can be addressed through fiscal policy, transfers, wage subsidies, etc. The piece argues that this may be constrained by falling tax revenues, but in a deflationary low inflation environment, the Treasury can run large deficits and the Fed can buy as much of that debt as it needs to, leaving aside that we'd expect the tax structure to change. The political process is unlikely to be as meaningful as a bottleneck as the peace claims, as the hypothetical fiscal hawks pointing to unsustainable deficits would not have much of a point, given the economy in this hypothetical will have much higher potential output. Also, that obviously wouldn't pull well. The first principle's intuition obviously tells you something is awry when we're told that people will want, at least as many real things as before, and the economy will have the means to produce

more real things than before, but the people won't be getting the amount of real things that they want or need. This is because that typically requires major policy slash institutional frictions or delay in translating capacity into purchasing power. If you suddenly have two loaves of bread in your house instead of one in your house and you weren't starving with one, you probably shouldn't starve when there's two, but if by some hypothetical through the complexity of the novel two breadloaf production process, you suddenly get tangled. and can no longer access the covered, then it's quite possible you will starve.

I thought that was a good take. It is interesting how this moved the markets way more than AI 2027. Like it's sort of the same piece, and it has a lot of the same sort of extrapolations based on AI progress, a lot of same applications. But like AI 2027, probably like the market reaction was like invest more in the labs.

Yeah. At the time, because it was kind of aimed for more, more of a West Coast audience in general. Yeah. I just mean, let me. If you had taken AI 2027 and you had just asked, like, I own this basket of public company stocks, what should I be doing? And AI 2027 is your backbone, you would probably sell a lot like you're selling right now. Like the AI 2027, situational awareness, PDFs, like those are the Leopold-Oshend-Brenner philosophy. that is now being reflected in the market,

but he didn't go long any of these stocks. Anyway, sorry, really quickly. I wonder how much that is just because of, like, who is actually writing it? Totally. People are, like, you know, very San Francisco-coded, like vaguely EA, maybe safest people, where this is like, okay, they're like a financial research firm.

And it's written with a financial audience in mind, and it speaks in that language. So it's been somewhat translated. It's interesting that it took almost a year for it to be translated in this way. But then, yes, it's interesting for a couple reasons because it didn't, this was not the takeaway. And I remember in the Vanity Fair piece, I had some funny quote in there being like, like, the market should be moving off of like what happens on the Dorcasch podcast. And it seems sort of silly, but I think that we're now like seeing the downstream, you know, ramifications of that. Yeah.

But I did think it would be helpful to kind of provide a summary of the essay. I think the original essay, it feels like they use quite a lot of AI to write it. I'm going to use AI to summarize it for you. There we go. So anyway, so this scenario, you should have got to this at the beginning. But by late 2025, agentic AI tools become vastly better at coding and complex tasks. Obviously, that was historical. Firms found they could use AI to replicate work normally done by humans, radically cutting labor costs.

Productivity looks great on paper, GDP and productivity metrics soared because AI output counted in the official numbers, but most of that value didn't translate into real consumer spending. So like businesses are spending money, but they're spending it on data centers, and that is not as opposed to labor, where if you give somebody money, they'll buy a house, they'll do home improvement, they'll buy cars, they'll put their kids in school. Consumption. Consumption, right? So they're calling this ghost GDP economic output that doesn't actually circulate in the real economy.

And then they identify an emerging negative feedback loop, which is companies lay off white-collar workers and reinvest savings into more AI. Displace workers have less spending power. Consumer demand weakens, especially for discretionary goods. Companies facing weaker demand invested even more in AI to maintain margins. And this creates a negative feedback loop with no natural break. The next step is market and credit stress. So they talk about private credit, having lent to a bunch of these different SaaS companies. that are now being threatened, defaults, climbing, as this sort of like perceived recurring revenue

ends up not being fully recurring. And next, intermediation and friction collapses. There's a whole segment talking about how like a lot of value capture in the world is actually just humans like not wanting to deal with friction. It's like not switching car insurance, even though you know you're paying more, than you should. It's just kind of a hassle. But if you could have an AI agent go and do that,

then maybe you do that more often, and that pulls out some potential earnings from the system. The other thing they talk about is like all these different tech hubs and how many like prime mortgages there are that might not be so prime if there's a layoff and somebody ends up having to switch, you know, switch career pass or something like that. So generally talking about unemployment surging, consumer spending, collapsing, severe drawdown in the stock market, and then even our sort of normal economic indicators hiding the sort of overall weakness. And anyways, takeaway, AI being great and powerful, may not equal all the markets ripping. Well, two different things.

Market ripping, individual companies. And median income. And median income. Yeah. There are three wildly different things. You can see asset prices rise massively based on future promise of GDP growth. If it's guaranteed that GDP growth is going to happen 10 years from now, the market will price that in today.

And then if all of that GDP growth goes to one person, you're not going to see median incomes rise. You're not going to see like broad prosperity in America. Yeah. I have more on that. But let me tell you about ACTA. ACHTA helps you assign every AI agent a trusted identity so you get the power of AI without the risk, secure every agent, secure any agent.

So it's worth really quickly. Yeah. Oh, sorry. Worth maybe noting like the kind of companies they call out in the piece by name. So poor all these companies, let's check in with service now, which is, which is one of the companies that was most heavily up down for almost four and a half percent today. So they talk about a bunch of the SaaS tools. They call out Monday.com, Asana, Zapier.

Zapier is kind of funny because in some ways, like it was just like work, automation. before work automation was even that cool. I was using Zapier 10 years ago. It does feel like they're kind of in a decent position given that already their core businesses help people automate different workflows. And then DoorDash, we already talked about that. MasterCard and Visa, they talk about suffering revenue pressure

because an AI agent would just opt for stable coins, which feels like, again, something that many people on the show have come on and made the case for why agents will leverage stable coins or prefer stable coins. Seems like a possibility, but unlikely that that will just, you know, all payment volume will shift over there overnight. And then Amex, Amex, they called out specifically because, of their consumer base being just generally weakened by labor displacement.

And then a bunch of others, travel booking insurance, real estate, tax, et cetera. Travel booking, I thought was funny because most travel agents don't actually take fees from the consumer. They take fees from the side of the hotel, the airline, whatever. And so the idea that you'll just immediately get like every AI agent or every individual. just immediately they I didn't fully process that one and anyways back to you I did think that John Lober I wanted to go through his piece yeah because I thought he had one of the better rebuttals yeah I thought that was good I think the the thing that just keeps sticking out to me is like and I was debating with

Sager and Jetti about this as well like he he was telling me like AI is the only thing holding up the economy I was like no I AI is actually doing very little for the economy right now. It's doing a lot for the markets. It's doing a lot for the future. But like, in terms of the actual economic impact of AI, it's very low. And we just know that because you add up the actual AI revenues from the AI labs. And you're talking about like 30, 40 billion dollars.

And okay, maybe there's like a five X multiple on that. And so you're generating $200 billion of GDP on top. of those tokens, but like that's just not that much in the grand scheme of the actual America's GDP. And so there's this disconnect between like the market, which is pricing future GDP, future cash flows, future value creation. Then you have what is actually driving GDP today. And then you have like the actual workforce and what what Americans do. And so there's this there's this odd disconnect. And I keep coming back to the Tyler Cowan like slow takeoff philosophy around like,

What's actually holding up the American economy, it's like healthcare jobs. And there's a lot of jobs that are, they feel very AI resistant, I don't know, maybe something changes, but like it just feels like the number of people that are software developers, less than 1% of America,

the number of people that work at tech companies broadly is less than 10%. And so even if there's some massive reallocation there, and then you go into like, even in like white collar, if everything shifts, like the rest of world is hit. And there's just a lot of other dynamics that feel like you can see crazy gyration in the markets

and you can see really quick reallocation of 10% of capital, billions of dollars flowing around. But that doesn't immediately translate to what is happening in the real economy. There's always this disconnect. I'm laughing a little bit because we've seen so many short seller reports over the last few years where somebody accuses a company of like really, really bad,

potentially illegal behavior and the stock will move down like half a percent. And then somebody writes like kind of a cool piece of science fiction, but easily can poke a million holes in it. And then it every, you know, it sends like all these mega caps like down. Let's go through this piece from John. Before we do, let me tell you about Cisco.

Critical infrastructure for the AI era. Unlock seamless real time experiences and new value with Cisco. John Lober wrote a great piece very quickly after this called Contra Citrini. He says popular markets commentator Satrini recently published a compelling and popular piece of AI doomer fiction, admittedly with some small probability of occurring, but I'm old enough to have seen many cycles of economic doom saying. I want to present a critique of Satrini's work and show a much likely or more positive view of the future. one never underestimate institutional momentum in 2007 people thought the u.s was geopolitically done

under peak oil in 2008 they thought the u.s. dollar was just shy of collapse in 2014 they thought AMD and video were done then came chat chabit and they thought google was done every time existing institutions with momentum have proven themselves far more durable than on liquor's thought when worried about institutional turnover and rapid labor displacement it's very funny that Satrini writes, even places we thought insulated by the value of human relationships prove fragile. Real estate, where buyers had tolerated five to six percent commissions for decades because of information asymmetry between agent and consumer. People have been calling for the end of the real estate broker for 20 years. You don't need super intelligence for this. All you need is Zillow or

Redfin or Open Door. That's exactly, this example actually shows the very opposite of Satrini's point. We have the type of labor that most people consider obsolete, and yet market inertia and regulatory capture have made the real estate broker far more resilient than anyone would have bet a decade ago. My wife and I bought a house a few months back. The transaction required us to have an agent ostensibly for the above reasons. Our buyer's agent made about 50,000 on the deal for about 10 hours of form filling and party coordination that I could have done myself. This market will eventually be efficient in prices labor fairly, but it takes a long time to get there. I know a lot about inertia and change management. I built and sold a company that focused on moving

insurance brokerages from service to software. And the main thing I learned is the iron rule of dealing with human reality. Everything is always more complicated and takes much longer than you think it will, even if you already know about the iron rule. That doesn't mean that a meaningful change in the world won't happen, but that the change will be more gradual, giving us the time to respond and adjust. Second point, software has infinite demand for labor. The software sector has been struggling in recent months as investors fear that companies like Monday, Salesforce, Asana, can now be easily replicated and that the value of their back-end systems is indefensible. So Trini and others talk of AI coding is a spell of the end of jobs at SaaS companies

are one, the products become obsolete, zero margin, and two, the jobs themselves disappear. What everyone seems to be missing is this. These products effing S-U-C-K, that's his opinion. I can say this because I've actually spent hundreds of thousands of dollars on these products. Sure, maybe AI enables competition to replicate their products, but more importantly, AI enables competition to deliver better products. It's no surprise to see the stocks drop,

an uncompetitive sticky lock-in sector filled with another swear word, and coming competitive again. And my own personal call-out here is even, like, until we see a round of layoffs at a company that is 5,000 software engineers at once, it's hard to believe that AI is replacing software engineers versus just making them a lot more productive.

If somebody's a lot more productive, you'll pay at least the equivalent amount to maintain them. Yeah. Yeah, interesting. More generally, it is uncontroversial that virtually all current software is garbage. Everything I use and pay for is littered with bugs. Some software is so broken that I can't even pay for it. I have not been able to send a wire using Citibank's online banking in three years.

This was my pushback against Roon. Roon was like, oh, like, codex is so good. good, like, you know, you can just vibe code everything. It's amazing. And I was like, why is the United App bad? The United App is good. And then he was like, it actually is good, and then I used it, and it's like, not that bad. But the point holds there is some bad software out there. I will die on this hell. But yes, hopefully it's going to get better. Anyways, there's a deep and important truth. Even if we get something like the software singularity, the level of demand for labor here is practically infinite. Famously, it is the last few

percent of completion that take the most work. And by that, at virtually every software product could probably scale up its complexity and features by something like 100X before beginning to saturate demand. Three, this was probably the best point from his response. Reindustrialization. There will be some labor displacement, of course. Driving stands out. Many types of white-collar work, as Satrini suggests, will undergo some gyration as some jobs disappear and others change meaningfully. AI may be the straw that breaks the camel's backs for jobs like the real estate broker where the job had actually already disappeared a long time ago, but the pay was still there. The saving grace here is that in the U.S., we have virtually limitless capacity and need for reindustrialization. You may have heard about bringing back manufacturing, but it's more than that.

We largely no longer know how to create and don't have the facilities for making the core building blocks of modern life, batteries, motors, small semis. The whole electric stack is something we are almost entirely dependent on China and other countries for. We barely make fertilizer. Once you start looking at the physical world, you see a virtually endless scope for work on job-creating nation benefiting fundamental infrastructure work that is politically bipartisan. I like that. Where does he close? He says, in beyond, the outcome of industrial megaprojects is, of course, that we move toward abundance. These abundance build.

America will once again be more independent and make things at large scale and low cost. Transcending material scarcity is the key in the long run if we do lose almost all white color jobs to AI. We have to be able to provide with a continued high quality of life. Part of this will get automatically just because AI taking margins to zero means that those consumer products would become equivalently cheap. This is a deflationary effect. My view is that different parts of the economy will take off varying speeds, and virtually all the areas are slower than a piece like Citrini's might suggest. To be clear, I'm extremely bullish on AI and expect that one day, my labor too will be obsolete, but it's going to take a while. to get there and that time gives us the opportunity to make good policy. On that front, preventing

a market meltdown the way Cotrini imagines is actually pretty easy. And the federal government's response during COVID showed how proactive and aggressive it is willing to be. I'd expect large-cell stimulus to kick in quickly once needed. It slightly irks me to say that it won't be efficient, but that's also not the point. The point is material prosperity for people in the course of their lives. Broad consumer well-being that legitimizes the state and carries forth the social contract, not satisfying the accounting metrics or economic norm. of the past. If we are nimble and responsive to the slow but sure technical revolution, then we will be fine. It's a good, good response.

Rise calls out, out of every example they could have chosen they went with DoorDash, the barrier to entry for launching a delivery app is not and has never been software. It's distribution, restaurant adoption, user adoption, and of course, driver adoption. It would be really funny to be using like the vibe-coded version, where somebody's like, yeah, I just launched a delivery app, and your food will be here in four hours. Yeah, it does feel like... If I was Tony, I'd be flying to find Satrini

having a work face-to-face. Open it up a can of... I know where you're going. Yeah, it feels like, okay, so you built... Like, you vibe code a profit-less, like open source delivery app that anyone can use. And you assume that it would get adoption just because it's more economically efficient.

Like it's cheaper for all parties, so they will join. But DoorDash is actually like a three-party transaction. So you need to market to all three. And it's really, really hard to break through right now. And maybe it would just go viral and everyone would on board. It just feels tough. And then he was saying that like, well, in this future, It's like all three parties are using agents that are perfectly rational and hunting around for the best opportunity.

So things can shift faster. And I believe that to some extent, but it just feels like still a little bit farther away because of adoption and actual. Yeah, DoorDash has modes. That is the big, that is the simple trick that all vibe coders hate. Yes. Yeah, I mean, it's like there's a lot of capital that when he's. into building the network and the app, but also a lot of capital that went into marketing

and onboarding the pool in the marketplace, like the actual liquidity. Yeah, the only scenarios that I can see the sort of like vibe-coded delivery or sharing economy app working, is at a local level? But there's already a bunch of competition there. Like I have a guy that when I want a ride to the airport, I call him, he picks me up.

I don't necessarily use Uber, because I like, having the same guy's my buddy now I like I like going to the airport with him yeah right so yeah I was thinking about Amazon basics and like that hasn't destroyed every company every brand like and why is that like will that is that a good analogy that like okay the big AI labs will have Amazon basics for SaaS but people will probably still want certain brands there will be certain people that are locked in. Okay, yes, I know the Amazon Basics paper towels are cheaper, but I just happen to like this particular brand that's a little bit more tailored for me. But Amazon Basics was like, hey, you buy paper towels from this brand normally. Yeah. We're going to sell you the same product

with our logo. Yes. Yeah. Sometimes. Yeah. And I think the AI disruption that is much more real is like you have entirely new paradigms for software, an entirely new relationship. with software. And it's not just like, oh, you know, somebody built the exact same version of Salesforce. It's like somebody built an app that automatically sets your schedule every day and you're not even thinking about like,

oh, I need to be monitoring this dashboard or whatever. Yeah, no, I agree. I think the Amazon basics of Salesforce probably is not that big of a business opportunity because the whole value prop is that it's lower margin. And so Amazon, basics is not driving Amazon's market cap. Well, yeah, Amazon has solved the distribution. They're like, we have the customer. But when you have a lower margin profile and you don't

have the customer yet, naturally means you can't spend as much money to acquire a customer and build out sales and distribution and all the stuff. That's a very different situation. It's not like people are just going to like the SaaS, you know, supermarket. I think his, I think his pushback would be like they will effectively because they will go to an agent that says like I need to accomplish this job and it will say okay well for that job I need a tool there's a legacy SaaS provider and there's a and there's a neo SaaS provider that's vibe coded and I could actually build my own version too and it will pick the most economically efficient across that frontier and so that's where he's that's where he's coming away with like some downward

pressure which I think is like reasonable it's just again I just keep coming back to timelines here before we move on let me tell you about console console builds AI agents that automates 70% of ITHR and finance support, giving employees instant resolution for access requests and password resets. Let's continue. Very funny post from Dimes Square Holdings. You think this is crazy, but just wait until next weekend when I publish my substack article, you should freak out and kill yourself right now. People are really having fun with this. What was this next one? Wow, Dimes is on a roll. Average 2026 AI macro research now. I am legend.

This may be the most terrifying novel you will ever read. Is that just the zombie apocalypse movie? That might be the most market-moving piece ever written, says Clouseau investments. That seems accurate. I mean, there are other factors going on, but this does really feel like remarkably impactful. And I don't know, maybe it's a buying opportunity, maybe it's a warning to everyone else, but it certainly broke through. through. I mean, these articles is really, really underrated. I've been, I noticed like I heard about something big is happening on a car podcast. I got that forwarded to me in an email. Like,

like these pieces of like AI is a thing that you need to be paying attention to are breaking through in a way that 2027 did not. And like the, you haven't seen Ilya on Dorcas. Like that actually that's a joke because really that did not break through. But something big is, happening did break through to the tune of 100 million views, which actually means like everyone read it beyond. It went, it went, it broke containment. Like it truly, truly went big. And that's, and that's certainly market moving in the Satrini post did too. We can, we can go through his agent of commerce thing, but it's a little wonky. Let's see what venture anthropologist had to say. So Trini is completely wrong about the impact of AI on the economy, but his article does correctly show

that various forms of AI Dumerism will become incredibly popular in 2026. Yeah, people are pushing back. And someone was saying that this is similar to Karl Marx's critique of capitalism. One of the, this is from Mohit, one of the often slept on benefits of attending the University of Chicago is that they make you read Marx as part of the core curriculum, which is why this article gave me flashbacks of taking SOSC 114 as a freshman. Marx writing during the Industrial Revolution predicted capitalism would periodically devour itself. Firms replace labor with machinery to boost profits, but competition diffuses the technology, drives prices to marginal cost, and the gains get competed away.

This was the collapse of profits. Meanwhile, displaced workers lose purchasing power, hollowing out the demand for the whole system depends on. Production rises, but no one can afford to buy what's produce, the contradiction between production and realization. Sotrini's piece describes this exact dynamic, then declares there's no natural break, but it's the most Marxist piece of financial analysis written in years, and it makes the same errors Marx did. Schumpter offered the obvious rebuttal 80 years ago. Creative destruction doesn't just destroy.

It creates industries we can't yet conceive of. Everyone in the replies is already making this point, and I think they're right. But the sharper rebuttal is Hayek's. Prices are the break, Satrini says, doesn't exist. Who funds $200 billion a quarter in CAPEX when equities are down 40%. Private credit marks are in the 50s and consumer demand has collapsed. Cost of capital rises, incremental buildout becomes uneconomical. Capital gets destroyed and reallocated.

Citrini also unknowingly describes Marx's proletarianization of the Petit Bougouzzi. The 180KPM driving Uber is textbook, but the article claims this collapses consumer demand And that's where it breaks. The top decile drives 50 plus percent of their spending and their wealth is in equities, not W2 income. They're long the hyperscalers posting records in Citrini's own model. Blue collar is insulated because AI replaces cognitive labor,

not physical. The professional middle class gets crushed, but aggregate demand doesn't. The spending class is the capital owning class, the case-shaped recovery, they fear actually stabilizes the demand base, they say is collapsing. In the stable aggregate demand, the petty bourgeoisie finds a way to reinvent itself.

I think the Certrini piece is excellent and worth reading, but history has repeatedly shown that periods of transformative productivity gains ultimately accrue to the consumer through lower prices, deflation, more leisure and higher quality of life. Marx's air wasn't diagnosing the disruption. It was underestimating the system's ability to adapt. Very good. Let me tell you about graphite. Code review for the age of AI. Graphite helps teams on GitHub. Ship higher quality software faster.

Really, going heavy on the goat emojis today. I like it. It's Monday. Everyone is reading the latest at Trini piece thinking it's an institutional research piece when in fact what they are reading is a marketing piece of fiction meant to go viral and viral it did go. Lesson, lesson there. I wonder how broadly the article, the article virality, like long form has not been going viral on X or Twitter for a decade. But even before the link ban and stuff, like it was really, really hard for articles and links

to really go big. They did go big when Twitter started because there wasn't that much content. So people would write and then they'd bring that and then they'd discuss that. But I can't remember a really big debate erupting around an article, maybe a little bit. Steve asked, does Tyler clap for each ad reader? Is that a sound bite? It is real. He clapped.

Yeah, I clap for every single one. We'll give you a chance to do it again. fin.AI, the number one AI agent for customer service. If you want AI to handle your customer support, go to fin.a.I. We did get some feedback that the clapping can be a little loud during the ad reads. So, you know, Tyler, constructive criticism there. Anyway, should we continue with the Satrini back and forth? We do have someone from Satrini coming on the show. Yeah, we can keep going. The thing about the street piece is that that is internally inconsistent is where does all the surplus go? okay, we become impoverished and aggregate demand collapses.

What financial asset is spared from that? A lot of people are asking that. And yeah, I mean, the answer is commodities. You want to be in like gold and silicon and whatever is at the bottom of the stack and then whatever has the deepest moat and then you want to be in the AI companies. John says he collapsed as well. Thank you, Sean. Let's switch gears to something that is certainly more important than the Citrini piece.

a street legal modded garbage truck. What? Pratt and Whitney J3 Jet Engine. Okay, let's see it. Is this real? Let's pull this up. You don't even know anymore. Wait, I've seen this Pratt and Whitney before.

Hermes, I think, bought one. I have no idea if that's real, but that's remarkable, if true. Yeah, no, you can, those are expensive, but I do think that they will sell those to you. Feels like a six-foot flame at the end of your vehicle, is not street legal. I would agree. I would agree.

Anyways, horror is coming out of Mexico. Yesterday. Really sad situation. Our very own Joe Wisenthal had been in the Porto Varyarta area and had just left. I think he got out of there an hour,

an hour before the chaos erupted. So very grateful for that. R.S. Marriott on Reddit. Somebody said, Weston, Puerto Vallarda, won't honor late checkout with streets closed. I am Platinum Elite. No way. Over 1,000 lifetime Marriott nights. Wait, I thought that was a joke. I didn't realize somebody

actually posted this. TV is on fire due to the cartel sitting fires and buses, cars and buses on fire all over the city. The airport is closed and Uber's and taxis are not running. I asked for a 4 p.m. checkout, which I'm entitled to based on availability. They won't extend past 2 p.m. and said we would have to use the hospitality. sweet. We're supposed to be leaving for Buceros this afternoon, but that isn't looking very good. Worst Bonvoy property I have ever experienced. I don't think anyone will be checking in today, so there's no reason to at least not extend us to 4 p.m. This is so fascinating. Does this person just not understand the scale of what's happening? Maybe you could break it down for anyone who's

living under your data center. Like what actually happened in Mexico? Because it was not just fires in a few cars. This was like a military operation, correct? Because my wife texted me yesterday afternoon while I'm on X, monitoring. You're monitoring the situation. All the open source intel. You texted me. You texted me. And I was like, oh, what's up a job? Like, wow, I've expected something like this for a long time, given the attention's down there. And then I'm just watching this. My wife texts me, our friends want to go to Mexico in April. Can we go? A long weekend. And I was like, are you, are you joking? Anyways, the really, really sad situation, basically, the leader of the cartel CJNG, which is like

effectively as paramilitary group, any, like if you looked at any photo or video of them over the last 10, 20 years, they look like their special forces. Yeah. I think the story is at many of them actually did train at some point with U.S. Special Forces and then flipped. Or probably the Mexican military. Yeah, no, they were, but the, but the U.S. special forces have trained Mexican military. Okay. Okay. So these guys are like, like they have their own version. Yeah. It's not a LARP. Like, oh, they just like picked up something. They watched like a video on YouTube. Yeah. I mean, I'm sure, I'm sure some of them are not a church. But in general, this is like a paramilitary organization. It's like one of the

largest, like, private armies in the world, probably the largest private army in the world. And so Almencha, their main guy, gets taken out. And then, uh, they respond by, uh, starting to just like blow up like roads. They, they, uh, took over an airport, I guess. Like, they just start causing mass chaos. Yeah. Because they're leader less. And so this person in Porta Vyarta, if you look at any video of Porta Vyarda, if you just went outside yesterday and looked around, there's like fires rising up everywhere it looks like, uh, It literally looks like a war zone. So for somebody to be hitting Reddit at this moment and being frustrated,

it's like, hey, maybe just, you know, the State Department put out, like, almost exactly when this person was posting a security alert due to ongoing security operations and road blockages and criminal activity, U.S. citizens in the following location should shelter in place until further notice. And, like, you're getting a shelter in place warning and you're mad about your Marriott points.

Again, hopefully, hopefully things settle down. I agree. I agree. Well, I want to move on to some nostalgia. We are gonna get Tyler Cosgrove up to speed on what it was like to live in the 90s in the early 2000s. First, I'm gonna tell you about MongoDB.

What's the only thing faster than the AI market? Your business on MongoDB, don't just build AI. Own the data platform that powers that I grew up in an era before MongoDB. I think of my life as pre-MongoDB. It's crazy. Back then, you had to store files and text files now. My sequel existed.

But the 90s and early 2000s were iconic, and we gotta get Tyler Cosgrove up to speed on what it was like during the heyday. These were the vibes, the blockbuster. So much consumer electronics. Like everything had a, you had a, different device for everything. A Walkman, a Game Boy, an Xbox. You can still go see a Monster Truck Rally.

I had an Xbox. You had an Xbox? Yeah, we have Mod Retros right here. Okay, okay. So you're maybe up to speed. Well, there's another one that talks about the liquid metal object design. And I found this real, very informative to show how technology in the digital world actually shaped the physical world. So we can play this. Liquid metal object design. I feel like this is overdue for a comeback.

It's pretty close. It's pretty close. Good music too. Other terms flooding around for blobbism. Blabism. And biomorphic design. Biomorphic design. It's easy to see that industrial designers were trying to push past the

Because everything was really blocky in the 80s. And had a futuristic vision for things like sports wear watches, music players. The clear, clear case. So good. Of when technology influences form. CAD, a modeling software introduced what is called. nerves. NONUMPLINDS.

NONUMPLINDS. What this allowed is for industrial designers to create mathematically smooth curves to be calculated with precision. It enabled people to make these organic worlds. So before you had to just like use blocks basically and like you'd get like a sphere and that was it. You could do like a sphere and a cube, but you couldn't really do whatever shape you And back then and they were rocking this kind of hardware.

Yeah. When they were saying that all retail stores. Yes. Globally will be wiped out. Yes. five to 10 years. Yeah. Yeah. Yeah, I mean, reflecting on the dot-com boom, I think is particularly interesting right now. I mean, I do like the takeaway from the dot-com boom, when most people, when most people pull up the dot-com boom, they're just like, oh, it's a bubble and everything's

going to zero. And like, that's not quite the lesson because the internet was still like actually the most powerful force for economic growth and change. And it did radically change society. It just did so over two decades instead of like one year as was predicted so there's an article in the New York Times that's sort of comparing the dot-com boom to the AI boom and and it's a piece by David Streitfeld at the New York Times he says people loved the dot-com boom the AI boom not so much and I buy that generally like like the the tenor around the dot-com era that yes there was a lot of froth but in general

people were like, oh, this is like sort of interesting and cool. I got to play with this like tinker. They just missed it more as a toy than like true doom. Yes, there was Y2K and people were worried about that, but the stats weren't quite the same. So right now, there was just... Were you like aware of Y2K? Extremely aware. How did you process it? Because my parents were trying to explain to like a five-year-old. Yeah, yeah. No, it was. I was like, I could, I could generally. Yeah, yeah, I remember the turn of the millennium, I was overseas on a vacation. And there was a little bit of fear.

Yeah, you gotta get out. Everything's collapsing. You gotta seek refuge. No, no, there was like a fear that like, okay, like something crazy might happen. But in general, my parents were like dialed in enough that they had been through the boom and bust of like something bad will happen. to actually understand that like, no, the fixes were in place. And there were a bunch of interesting fixes. So if you're not familiar with Y2K, basically the idea was computers were programmed to store

dates as two-digit numbers. So you would just say it's 86, then it's 95, 96, 97, 99. What happens when you get to 2000? It just says zero-zero, and all of a sudden all your interest calculations for your bank account freak out, you have negative money, the whole financial system collapses. anything that's planned, right? All of this was like the fear of what might happen. Tyler?

Yeah, that doesn't make any sense, right? Why? Well, like, didn't they- Easy for you to say, Tyler, you weren't born for- Oh my gosh, the numbers are resetting all of a sudden. Like you can see, it's like a calendar. You had to be there, Tyler. Yes.

You had to be there. Didn't no one have foresight? No. No, no, yeah, yeah. People did have foresight and so they started implementing changes. And the changes cost a ton of money. I think the total bill for Y2K systems updates,

because if you had hard-coded, like, our dates and our systems, we're a bank and we store dates in two digits, you gotta go and change that, and that's a couple days of work. Yeah, they didn't have cloud code back then. And so, yes, it wound up being something like hundreds of billions of dollars were spent

in the lead up to Y2K. To prevent that, hit the gong for the Y2K pay days. A lot of people made a lot of money. But there were also a whole bunch of interesting rules. And you know, a hotshot over here. I'm gonna give him a pop quiz. Do you know how to calculate a leap year? If you get this wrong, there's gonna be consequences.

Okay, okay. No, no, stop, stop, stop. Do you know how to-. Consequences? Do you? No, no. I told you there'd be consequences, Tyler. All right, okay.

That was the most zoomer thing I've ever seen in my life yeah he just has to go easy he's brain dude how to calculate leap year yes like like like what like when do leap years happen I don't know like the actual calculation isn't every four years every four years except every hundred years except every thousand years so they toggle back and forth and so in in in at 1900 was not a leap year and so if you if you didn't know any of the rules you would just think, oh, every four, any of the special rules, you would just be like every four years is a leap year,

it's a leap year, 2000. But if you knew the 100 year rule, you would be like, oh, actually, it's not a leap year. So I need to hard code the system that is not a leap year. And you can fact, you can fact, you can't actually this too, because I'm not sure, I'm just riffing here. It might be wildly wrong. But the thousand cancels out the 100,

and you wind up with just a normal year. And so if you did nothing, you win. Yeah, but, okay, so Greg, The Gregorian calendar goes into place 1582. Yeah. So you have like 400 years to figure this out. Yes, yes. So I-

And we did, but it cost us $100 billion, as is all technological change. But Y2K was like, it was very millinarian. People were dooming about the apocalypse, but these were like fringe sort of cult types. The same thing happened with 2012, I don't know if you remember 2012 apocalypse stuff. Y2K was the same thing.

But it was not widespread. AI Doom is truly widespread. There's a study in U-Gov. More than 30% of Americans are concerned that AI could end human life on Earth. Like that is a wildly high number compared to how many people believed 2012 was going to be the end or 2000 was going to be the end. Like, I would be shocked if either of those dates were single digit percentages. Most people were like, yeah, okay, like, I might need to like print out my bank statements. A lot of people were doing that.

like print out your bank statements before Y2K because like then you'll have a backup and you'll be able to go in and say like no I actually have $10,000 in my bank if I don't have negative $9 million because it's not the year 1,000 right now but you know everyone got through that the other interesting thing is that there's this disconnect between the doom AI is going to kill everyone and then what is the impact of AI there's this new research paper from the National Bureau of Economic Research NBER they pulled a whole bunch of firms in America, a whole bunch of companies, and they said, are you getting a benefit from AI? Tyler, what percent do you think said, yeah, AI is helping out? It's probably pretty low. It's extremely low. 20 percent?

It's exactly 20 percent. Now that. 80 percent said that AI was having no impact on their productivity or employment. We got to get those numbers up, folks. There are clearly good ways to use AI to benefit your company and your people. I mean, it could also be like, those surveys you never know who you never know. Might be somebody who's just not, who's going to answer the survey quickly and they don't realize it. But I mean, just think about it.

Like, like, there are lots of companies where you have to be HIPAA compliant. Maybe they just don't have a HIPAA compliant LLM available to them. And so they're just like, yeah, I literally can't use it. Or like, or like all LLMs are blocked on my local work network because the IT department's still figuring out how we roll it out. Like these things happen all over and it affects like lots and lots of people. I mean, if you're just a cashier at Walmart, Is AI helping you? It's just not, right?

Yeah, but I'm sure there's still, like, they use services that under, you know, like behind a bunch of layers, there actually is AI going on, right? I agree, I agree. So, like, maybe they're not interfacing with LLMs directly, but at some level, like, there are LMs running.

Totally, totally. And even if you zoom out to AI, just being like machine learning, it's like, okay, so the Walmart person of the checkout counter is not seeing a benefit, but, like, Walmart definitely has a recommendation system on their website. Yeah, or like the Walmart software

is being updated faster. than it usually would be. Isn't that alone? That's AI. You believe that that's happening? Could be. You're willing to bet it all on that. You're willing to bet it all on Walmart going through a dramatic digital transformation right now.

You don't think it's slow? You don't think they're still like, let's figure this thing out? I think they're probably running stuff faster than they used to be. You think they're past the pitch deck phase. Maybe, hopefully. Yeah. And we got to talk about, we should talk about Rufus. Do you guys hear about Rufus?

No, what happened with Rufus is going crazy? Okay. While you pull that up, let me tell you about public.com investing for those that take it seriously. Stocks, options, bonds, crypto, treasuries, and more with great customer service. I'm trying to pull up the... I have some more. My takeaway was that the average American believes that they are in Terminator Judgment Day, but they still have to go to CyberDine systems and do their fake email job, just right up until the bombs drop. That's the general tenor around AI. Like the vibes are rough. But if we go back, to the dot-com bubble and try and understand what's different.

There's some interesting stuff that we can learn. So first, there was definitely a vibe around permanent high growth and a new economy. There was this economist, analysts, executives, they were arguing that productivity would permanently accelerate and recessions would largely disappear and the business cycle would be broken by information networks that moved at the speed of light. Before the SaaS apocalypse, there was what you referred to earlier, the retail apocalypse. The most extreme formulation was total physical retail extinction within 10 years. So within 10 years, they predicted by 2009 there would not be a single retail store anywhere

in America. This was the prediction. This was the prediction. This was the prediction. Directionally accurate. Directionally accurate, for sure, for sure. So shopping malls would become obsolete. All brands would be commoditized by cheap online alternatives.

Some of this happened. Amazon Basics is popular. T-Mood flooded America. Shopping malls are struggling. But Walmart's a trillion dollar. company Nike is worth 90 billion and Rick Caruso has seemed you know to sort of figure out a way to make Walt malls work in LA at least there were also a ton of other crazy dot-com proclamations revenue doesn't matter only eyeballs matter all media

will permanently be free because file sharing and products like Napster simply cannot be stopped and so every piece of media will be free forever that obviously didn't happen And offices will disappear entirely. Digital currencies will replace Fiat money. At its core, the most extreme claim was the internet was a civilizational phase change equivalent to the printing press or electricity.

And most importantly, this transformation would happen in five years, not 50 years. And so time compression was the biggest forecasting error here. Not every dot com prediction, like nearly every dot com prediction had some directionally correct element to it. But various breaks were applied either voluntarily or involuntarily and things slowed down. Media companies sued file-sharing companies, for example, financial markets pulled back, companies adjusted their strategies and retreated to internet-proof modes.

And so protests and political movements also had another role to play as a break. There was this really interesting anti-tech protest in the late 90s, the Battle of Seattle. So over four days, 40,000 protesters rallied against the world trade. organization to push back against internet-driven capitalism, there were 600 protesters who were arrested at the Battle of Seattle, and they were arguing that the internet was linked to corporate consolidation, outsourcing, and labor displacement. Like all relatively true things hard to disprove, but the timelines are what matter, of course. And so the Battle of Seattle didn't result in any specific dramatic curtailing of internet

adoption, but it did raise the political salience of international trade relations and was clearly in the back of policymakers' minds when they set sectors targeted tariffs and domestic preference, procurement rules over the next decade. And so I was thinking about this in the context of the New Brunswick Data Center protest. So the actual, this data center that got canceled in New Jersey, by comparison to AI, like it's tiny. It's generous to call it a data center. Yeah. It's more of like a data point. Edge computing. Yeah.

So it's 25,000 square feet. The current meta-large data center campus is 500,000 square feet. So 5% of the size. And so this data center, we don't know who is actually going to buy the capacity, where it was going to go, but you can think of it much more like delivering you Netflix faster than training the next AI model. But like it worked. They got the data center canceled. And so this is going to be a like a data point in the minds of AI policy makers, decision makers, leaders for a long time. And I think that that will affect things. So you know, the internet rollout continued even

during the bubble and the bubble popping and pushback and all sorts of different things. AI will continue as well. But I think it's important to like refocus the conversation on actual impact like the 20% needs to go up and people need to say yes this is helpful and then and then mitigate the negative externalities before they turn into problems like real problems for for average Americans the energy the energy issue was foreseeable like it was predictable and maybe that's what we need to be forecasting like the next vert the next turn of AI 2027 or a AI 2028 should be like here are all the problems that we're gonna bump into

along the way, like let's go mitigate those now, because all the hyperscalers could have been subsidizing electrical buildouts like years ago, for sure. So anyway, let me tell you about Gemini 3.1 Pro. Gemini 3.1 Pro is here with a full, with a more capable baseline. It's great for super complex tasks like visualizing difficult concepts, synthesizing data into a single view, or bringing creative projects to life. We need a moment of silence for international business machines. What happened? Falls over 10% actually 11% now after Anthropic announces that Claude can streamline COBOL code. Oh no. There we go. Wild times. The example that I was talking about earlier about Amazon's Rufus. They're going to say Anthropic announces they're going to

launch an international business machine. We are an international business. Mike Isaac was reporting financial times, he was just commenting, Amazon's internal AI coding assistant decided the engineer's existing code was inadequate so the bot deleted it to start from scratch. That resulted in taking down a part of AWS for 13 hours, and it was not the first time it happened. I love it.

Sometimes the best course of action is to delete and recreate. Delete everything. Sometimes that's what you've got to do. Lots of people are having fun with the data center protest. I think it should be taken seriously. But apparently the New York Times ran an article in 1887 that says peasants destroy a balloon. Is this a real article? 1887.

1887. You can actually find it on the New York Times website, October 25, 1887. The Russian peasantry appear to be sunk in ignorance and superstition. During the recent eclipse of the sun, three famous Russian savants to send. I'm trying to read. This is in the Times machine. It's very, very. Oh, it's actually like, it's a scan, right?

It's not text. Yeah. Incredibly hard to read. But the peasants did destroy the balloon. They destroyed it. They got it. Somebody asked, would you live next to a date center? Not a data center, but a center for dates.

Dates are underrated. Yeah, dates are good. Healthy. Delicious. Anyway, 11 labs. Build intelligent, real-time. conversational agents, reimagine human technology interaction with 11 labs. Let's go over to the horse section of the show.

There's some big horse news going on. The moment you've been waiting for. In the financial times, a horse walks into a lab. Let's see. And it says, peasants destroying a balloon in 1887 is setting a Waymo on fire in 2025. Yes, but, okay, so the interesting thing about the Waymo fires was that we live in L.A. where the Waymo fires happened. And if you were on the internet,

it looked like Los Angeles was burning to the ground. And Tyler went to the Philharmonic, the Philharmonic, which was directly like a block away from where the main protest was. And we were like, whoa, man, like this seems pretty dangerous from what we're seeing online. And it was fine, right?

You just pulled right in. Yeah, I saw someone holding a flag. Yeah. And that was it. I didn't see, I didn't even see the fires at all. And so a lot of the, the scale of these protests is hard to pick up on because things can go really viral and you can have a protest that's that's a couple hundred people and it's if it's in one block

and the photographer is good about lining it up and you're not seeing like a helicopter shot of like tons of people in the street it can actually be sort of small I remember that video of the data center protests where he runs outside and he's like we did it we did it like it seems huge but I actually think there were only like a couple hundred people there and you comp that to the World Trade Center Organization Battle of Seattle. It was 40,000 people. They arrested 600 people. Like that's pretty significant.

And so I guess I'm not saying like we're still early for protest, but it is important to understand like the scale of like what's happening in the real world and the actual impact of that. And you know, you need to be charting this because if they're getting bigger, like they need to be addressed more. And even if they're small, like people have good points. So they should be listened to. and the solution should be brought to the populace

before it gets to a vote. Like if you could tell that New Brunswick debate would go way differently if the hyperscalers were there saying like, hey, good news. Like we've done so much forward thinking here that your energy prices are gonna go down. Like people are like, oh, okay, cool. And we're making it beautiful.

It's gonna be a building a part. And we're building it down, underground. We're putting grass on the roof. Exactly, yeah. There's like five easy tricks to like get you know Dana Center's approved all over the country But everyone's been putting them in the on the low priority pile, but they're certainly going to be more More important over the next couple of years. Yeah, why don't you read us? Yes, a horse walks into a lab It's a December afternoon at the Campo Argento de Polo at Palermo in the northern suburbs of Buenos Aires the sun is shining and in a clear, in a sky of clear Argentine blue.

The jacaranda, this is too noisy, I'm going to put this down. The jaccharondas are in bloom. You're sitting in the stands overlooking an immaculate green lawn six times the size of a football pitch. A military band with brass trumpets and drums, red epaulettes and shiny blackjack boots has just marched away. Argentina's president, Javier Malay, famous for his eldest sideburns and economic chainsaw

has taken his seat above the center. line. Eight players center on to the pitched hand arms, taut muscles, hair curling over the collars of their polo shirts. It's the first semi-final of the Argentine Open, the most prestigious tournament in the polo world, the one the players really want to win. This year, the stakes are higher than usual. It may be the last open for Adolfo Cambacio, the world's number one player for more than two decades, and the sports goat the greatest of all time. Cambasio has changed the way polo works, not only through his skill and tactical genius, but as a result of a bet he made nearly 20 years ago, he bought into the idea of cloning ponies a decade before his rivals. This year, many of the ponies he will ride in the open

will be clones, identical twins of his favorite horses from years gone by. The players line up four against four, the ponies waiting, ears pricked, poised for action. The whistle blows. The game begins. The players streak up the pitch, sticks swinging, using their ponies to ride off. their opponents to block them from getting to the ball. They gallop, turn, stop, turn on a six pence and start speeding in the opposite direction. They bounce on the ball of a small head of the stick. They bounce the ball on the small head of a stick. Hit back hands under the ponies next. If there's a break, they gallop to one end and leap onto a fresh pony before charging back into the fray. You can tell sitting high in the stands, the ponies get the game. They can anticipate what's

going to happen. They're enjoying themselves. That in and of itself is remarkable. In the millennia humans thought to tame the wild horses that roam the steeps and plains. We have bent them to our will for our species. Horses have charged into battle, dragged plows through rocky fields, and carriages through the slop of medieval cities. The real slop problem. Medieval cities. Now, man has taught them that a hard white ball needs to get to the end of a large field and through the gap between two. two poles. In return, we feed them, tend to their shoes and teeth. We give them massages and march them up and down hills to make sure they are fit enough to play. We polish their coats, plate their tails, and bandage their legs, and to the best, give them a chance at life through cloning and another and another. But it seems that isn't enough. Now two men,

a scientist and an entrepreneur, are going beyond making copies of an original. They are engineering polo ponies to make them even faster in the hope that in a game of high stakes and slim margins, it will give them the edge to win. For one pony, Polo Pureza, the circle of life began on an Estancia near the town of Coronel Suarez, a six-and-a-half-hour drive southwest of Buenos Aires. She was born on December 12, 1988,

a slight mare, raised on a diet of weeping lovegrass, the silvery fronds that grow in the red soil of the pompous. It was apparent from an early age that she had what it took to make a great polo pomper, She played in her first open final, aged only five, written by Pepe Hegai, one of four brothers who competed at the highest level. Four brothers, all polo legend. That's elite.

Polo remains a macho sport. The top players are male, though there is an open tournament for women, too. The grooms who canter the spare ponies up the side of the pitch wearing the gaucho's traditional floppy bray, the bonilla, are typically male. The open has only ever had male umpires, but the ponies are usually female. The players favor mares, citing their intelligence and grit. Polo Pueza was one of the great Polo Mayors of her generation. She was a bright bay, the color of autumn conquers, with black legs, a white star between her eyes, and another splash of white on her nose.

She played at the top level for 14 years, winning the cup for Best Pony at the Open, among many other awards. And speaking of ponies, the purple llamas, Vanta, automate compliance and security. Vanta is the leading AI trust management platform. That mayor was a natural polo player. One in a million, he said, the guy said, in a video made to celebrate Polo Poir's induction into the Polo Pony Hall of Fame. She had an impressive part also.

She was a mayor who never got tired. Polo Puerza retired in 2004. Before she died, samples of her DNA were banked in liquid nitrogen in the laboratories of Kirion, a biotechnology company co-founded, by Gabriel Vichera and based in a science park in the town of Pilar, 35 miles northwest of Palermo Polo fields. With his neatly trimmed beard and white lab coat, Vichera, 46, would not be mistaken for a polo player.

When I first emailed him, he apologized for not responding sooner. He was competing in the world indoor archery championships. Whoa. Made sense. His company is named after Chiron, the mythical archer, half man, half horse. It's the morning of the open semifinal and we're sitting around a large table in the cool of the conference room at Kieran, just a few meters away from the vats of nitrogen, housing Polo Pueres' remaining cells.

There are photographs of horses on the wall. Each clone, Vichera was responsible for creating each a genetic replica of a famous Polo Pony. One photograph, the newest is of five bright bay foals covered in baby fluff, their legs still too long for their bodies. These are the gene edited polo puerzas. He says, the ones you are going to meet. I stare at their photos.

There is no clue in the faces of their unusual conception. No way to differentiate them apart from their similarities to each other and to the videos of Polo Puerza that I have watched. What do you think? Would you go to a polo match if all the ponies were genetically modified and cloned? Or do you want a natty league? Natty ponies only? I'm in favor.

Your favorite cloning? Yeah, I mean, why not? Push the sport to the limit. I feel like it's kind of not in the spirit of just like a couple guys getting on horses that they just like found, round them up, you know? It's a... Well, they should have the sort of like wild league where you can just go find a wild horse, go play. This definitely creates an opportunity for the wild league. Yeah.

Sure. This is kind of the... Free range league. What do they call it the... the enhanced games. Yeah. This is the enhanced games for Polo for sure. Yeah. Anyway. Tyler, are you a polo accelerationalist? Sorry. Your business is AI. Their business is securing it. Crowdstrike secures AI and stops breaches. Tyler, are you a polo purist? I think I'm in favor of the cloning. You're a polo accelerationist. Yeah.

Piac, as they say. Yeah. Well, good news for you. There's lots of cloned ponies coming your way to a polo field near you. What did this post say? If you run every day, you'll be ready for any situation that calls for extreme cowardice. Was this deleted? I think so. I think it's hilarious. Probably the running community. Yeah. Zach Pogrob came in and said, you're going to be, you're about to be running for me. Yeah. Let me tell you about app love and profitable advertising made easy with axon.a i get access to over one billion daily active users and grow your business today there is a game called data center on steam which lets you build and manage your own data center this is low-key genius the best way to educate people on a new trait hyper scalers should lean

should learn a thing or two about edutainment edutainment this is fantastic tyler somebody was saying this it's not out yet it's coming out march 31st oh okay mark your calendars yeah i'm I'm going to run this. Productivity is going to fall. Everybody was saying it's like it could easily be an Ender's game scenario where it's just, it's just. Those racks weren't simulated. Those were real NVL-72s, Ender. Yeah, I love that.

This is all a ploy. The humanoids are already deployed. They just need you to wire everything up. This is, this is amazing. And it feels like it's, it's, the, the game mechanics feel just from this video, remark You're not just walking around a data center doing cabling the entire time. You're also deciding tax treatment and what software runs and getting probably Kubernetes installed or something like that. Slurm.

Very, very fun. I love these one-off games. Apparently there's another game just called Insider Trading coming to Steam. If you're good at insider trading, you're going to love this game. Steam has a game called Insider Trade and Get Ready. It's a rogue-like deck builder that lets you literally pump and then crash the market. This is going to be wildly, wildly popular. No, it depends a lot on the actual mechanics of the game, but hilarious and says a lot about the society.

But I think it's, I don't know, I'll give it a try. I wonder if it will have micro-transactions. That's the big question. or if it's pure for the love of the sport, love of the game. But these roguelike deck builders are fantastic. Bellatro went mega viral a couple years ago. Really, really fun game. Just crazy poker, basically.

It's like poker rules, but with a whole bunch of crazy modifications that allow you to just do, like, insane things and sort of turns it into a completely different game. The client says, someone make a TBPN intern simulator. That'd be good. I'm still waiting for showtacking. No. Now that Tyler's like promoted and just you know a real a real deal employee which happened after like two weeks last year

But that kind of would be kind of fun for a whole of us to kind of like relive the days of interned Intern summer yeah whoever has the highest score gets hired yeah I do I do wonder We've seen this I heard the story about like everyone talks about the death of AAA games right now have you heard about this so It used to be, you know, GTA-5, Halo 3, Bioshock. There were these big games that would sell for 50, 60 bucks. They would sell a lot of copies. But then they weren't, what do they call them? Permanent service games, online service games or something perpetual.

Like, Fortnite is a game that has endless updates and monetizes forever. And same thing with Counterstrike, League of Legends, there's a few others. that have wound up generating a ton of money for these companies, because once they get them up, they're like ecosystems, Roblox, great example. Versus, if you're doing like Bioshock and you make a bunch of money, then you have to do Bioshock 2 if you want more money from those customers, and then you have to do Bioshock 3. And at each point, people are like, well, I didn't actually finish Bioshock 1,

so I'm sort of out of the market for Bioshock 2, and your TAM just gets smaller and smaller while your development costs get higher and higher. And there's been a whole spate of AAA perpetual service. Why am I blanking on the term? There's online service games where they've come out and they said, like, okay, we've seen what CounterStrike has done, we've seen what League of Legends has done. We want that for our company.

Free to play? Free to play is the model, but there's something around the word service that's the gaming lingo. But there's been a lot of flops recently, Like a lot of companies have spent a ton of money on these online service games that they hope will become the next League of Legends or the next CounterStrike 2, and then they just flop and they're shut down in like a couple months. And it's a huge loss. At the same time, there's been a whole bunch of developers that have gone sort of the indie route and done really, really well.

Live service games. Thank you, Bobby Cosmic. They're called Live Service Games. Nailed it. And there was this interesting story of this developer. that spent like three years working on this live service game and it like completely flopped. And then like in this free time made like this game

called Peak for in like three months and it went like super viral and did really well. And I'm excited to see like when do we see the actual acceleration in vibe coding. Do we get more of these like meme type games that have like really interesting mechanics? Does it actually free up the developers to come up with not just interesting

viral hooks like data center simulator is funny enough to get us to like yeah click on it but like the mechanic actually has to be good too and a million people will think it's funny yes 10,000 will try it yes how many people actually yeah play for more than 10 minutes and and the key to playing for more than 10 minutes is not like the graphics will be taken care of we already have Unreal Engine the engine the engine will work like you're not going to be falling through the floor it's not gonna be buggy but and you'll be able to generate assets and actually make the thing look like it. But if you can come up with some sort of novel

reward mechanism progression system that's interesting, that shows, okay, I'm learning and I'm having fun, I'm re-engaged, I think that will. Dan says, peak was that developer's peak. Nomin of determinism is again. Yeah, you never want a larger product called peak. Anyway, really quickly, let me tell you about Lambda. Lambda is the superintelligence cloud, building AI super computers for training and inference that scale from one GPU. to hundreds of thousands of seconds. Signal says, serious question, how do you make someone with absolutely zero gaming experience CEO

of a very prominent and important gaming platform? Asha was announced as the new EVP and CEO Microsoft Gaming after a multi-year run over on the Enterprise AI side of the business. A lot of people had opinions on this. Well, I have an opinion. How do you signal's question is how do you make someone with absolutely zero gaming experience? CEO of a very prominent and important gaming platform you make them lock in and spend three months gaming and so that should be the first task It should say okay, you have no meetings

Microsoft Teams is shut down for you clipy's got it Yeah, we're handling everything your job is to speed run every major Xbox game Fable all the Call of Duty series, you're going to play all the Halo games, you're going to get good, you're going to rank and you're going to learn to speed run, and you're going to really, really lock in and establish true credibility that can't be faked, and then we will announce you. That's the hack. People are poor in one out for Phil Spencer, who was at Microsoft for 38 years, and his profile picture is just the Xbox X, because he's a legend,

and Palmer Lucky quoted it and put an F in the chat, because the world you grow up in no longer exists, apparently. What else is going on here? Okay, so someone asked Asha, what's your favorite game? And Smash JT says, okay, I'll play your game, you rogue. Chrono Trigger, Forever Goaded, Final Fantasy 7, Golden I-O-O-7. Chrono Trigger will forever be number one. I never played Chrono Trigger.

I did play Final Fantasy 7 and Golden Eye. And Asha said, great list. I did my top three in another reply, Halo, Valheim, which I believe is newer and has had much less sticking power in 007. It's been a long time since I played Chrono Trigger. Have you done every ending? Thanks for all the detail. I appreciated a ton.

And is the question that... Chrono Trigger doesn't have multiple endings? I actually don't know. Okay, so I don't know what's going on here. But Xbox CEO accused of using AI for replies. Saying she played Chrono Trigger in her reply to Smash, she would have been six years old. You could play it later, which would be a very young age to play, but maybe she'll have JRP cheese and picked it up later. It is a curious thought. She must be a huge gamer, or this is AI. This doesn't read like AI. I don't know.

What does Palmer Lucky say? He says, Crown Trigger is my favorite game of all time. And I was only three when it came out. True. Yeah, good point. Also, I don't know, Chromtrigger, like, I played Final Fantasy seven. I don't actually don't, I think there are multiple endings.

Like, I would not remember. I don't know. Anyway, what else is in the timeline? We should tell everyone about the linear lineup for today because we have four guests joining us. We have Alap from Citrini. We have Will Brown from Prime Intellect, then Michelle's coming.

And Alap is not at Satrini. He just co-authored the piece. He co-authored the piece. And he also wrote a part one that's a very good read that was released before the mega viral essay. And then Mike's coming on from also Capital at 150. So linear, of course, is the system for modern software development. 70% of enterprise workspaces on linear are using agents. And you should be too.

So. Hot take, it doesn't matter if it's. Yeah. Nick says hot take doesn't matter if CEO's gamer. as Strauss-Zelnik has said it's perfectly a CEO's job is to attract, retain, and motivate the best talent in the business, and then get out of their way. Yep. That's a good point.

A new Xbox CEO, Aosha, does need to be a gamer to run a company. She simply needs to do what the CEO's job of running a gaming company is supposed to do, which is to hire talent and allow game studios to make their creative vision come to reality. The thing I think they maybe could have done better with the announcement is, like, talk about what the rest of the management team looks like. Because if you position Asha as this elite operator who's going to like really, like, there's a way like if she's like managing a team of people that are gamers and love gaming and she's like working with them to figure out how to make the platforms better and better, that's more compelling than, you know, bringing somebody in then that. Yeah, I'm trying to think of other industries where the CEO doesn't use. the product. Part of, part of, part of this is like a industries where the CEO doesn't use a product.

I mean, like, think about almost every category of enterprise software. I think they all dog food the product. But not, not, not on a personal level, like their teams might. Yeah, I guess that's right. Yeah, I was, I was trying to think of like, are there, like, like, uh, I mean, it's like Rick Rubin doesn't know how to play instruments, but he does listen to the music. And I feel like most of the big Hollywood agents or power players, like maybe they didn't know how to use a film camera, but they watched movies, I believe. I don't know if there's like someone out there who's just like, yeah, like I've never seen saving Private Ryan, but it made me a lot of money because I green lit it because like I knew it was. Yeah, one thing's for sure. Xbox is not in founder mode. Yep.

And we'll never be. But... Should it be, though? Should it be? I don't know. Xbox is weird. The guy who started Xbox, what is, the guy that's, the guy that's, it's Seamus Blackley is credited with creating and designing the original Xbox?

I think he's now in the chocolate business. Yeah, I mean, I definitely think the CEO of a video game company can just provide a fantastic environment for creative individuals and also I mean Xbox is a hardware company. It's also a live streaming company. It's also a studio that just where you just have studio heads that go in green light projects. It's not all directly related. Handel says Larry Ellison using Oracle on a nice Sunday morning. Let's go. Good job. That's correct. I don't know. He probably does store a lot of data in in Oracle. Who knows? Yeah, Aaron says the C-Earral. necessarily is not in the product daily.

Yeah. Who knows? We'll wait to see. It's, uh, it already happened. Yeah. Well, yeah, I mean, we'll see. Yeah, we're working on, we're, we got in touch with her on Friday. Yeah.

We're going to find a time for her to jump on the show. Yeah. PS6 might be delayed because of the memory stuff. Um, there's also, I don't know. Yeah, they should just delay the next Xbox and let, let, let Asha just game for three months. Like you said. six months. Yeah.

The really interesting thing on the hardware side is a lot of people were freaking out over the weekend playing with chatjimmy.a.i from Talas, we have the founder on the show. He has baked Lama 3-8B onto Silicon. And so it runs at 16,000 tokens per second. So you ask it your typical LLM query, and it just, boom, loads the page. it's all done. There's no token streaming in. You're just at the bottom of the page. It's actually sort of jarring because then you have to scroll back up. But it's clearly like incredible. And this is coming. And we've experienced with Codex 5.3 cerebrus or spark. Is that what they call it?

And there's a few others. And so. And it doesn't have web search. Yeah. Yeah. So there's a lot of If you ask it what is TBPN? It says when butcher's pizza network? We give you a different answer this time. Wow, it's really hallucinating. Anyway, that, I think that the system on a chip, cerebrus, the wafer scale, super fast inference is going to be very amazing for... Yeah, it really is just a next token predictor. Yeah. It says TBPN could also stand for the Black Pine Network. This is not a well-known term or organization, but it could be a fictional or made-up name. It's having fun.

It's having fun. But I think that there's a very interesting play where... the gaming systems basically bake a style transfer diffusion module onto silicon and put it on the chip. This is what Nvidia did with DLSS, dynamic something super sourcing, super sampling. Deep learning super sampling, DLSS. So if you have a Nvidia, what is it, G-T-S-Forse like 40-90, 30-90, there's a section of the chip that's trained to take a 1080p video game and upres it in real time to 4K. And so you can run, if your hardware can only run the game at 720p, 60 frames a second,

it will up res all of those frames. It's not perfect, but it gives you a sharper image. It's basically just AI sharpening that's happening. You could imagine a model that is trained to turn the images that are generated from a video game from Unreal engine into something that's actually photo real, like make it like a movie, that prompt that we've seen happen, and you're like, wow, that's actually looks like a movie. You could run that in real time at 60 frames a second and be playing a video game that looks truly photo real because the actual game engine graphics have totally plateaued and there doesn't really feel like they're just going to jump to cinema quality anytime

soon. But if you use AI to do the last step, I feel like that could be really good. What do you think, Tyler? Yeah, you could also do like a Genie 3 type model. down right so like interactive video oh yeah yeah yeah that's like it's really slow and limited right now but if you bake that down you could play that yeah I still think there's a lot of work to be done on Genie 3 yeah maybe it's like one or two more models yeah like clearly those are like Lama 2 level right now but yes

yes yes I completely agree anyway let me tell you about restream one live stream 30 plus destinations if you want a multi-stream go to restream.com Dan's gaming says my theory is that Phil and Sarah did not want to shove AI into everything at Xbox. They were forced to retire and resign. Microsoft is replacing them with someone with a strong background in AI and no experience in gaming. This is just getting insane. I don't know. I'm completely white-pelled on AI in gaming as I just said. Like, I think AI in gaming can be really, really great. I mean, there's a ton of games where the developer would love to have the NPC dialogue that they

don't have to sit there and write, okay, this townsperson's going to offer you five coins for your sword. Like, no, just like, be an NPC, be, you know, you have coins, act agentically. And then you go up and you're exchanging with the townsperson, your sword for your coins or whatever, and you have like a much more natural interaction. That feels really great. I don't know. There's a million bull cases for AI and gaming, in my opinion. It seems like the hardest, it seems like one of the easiest things to sort of justify.

Well, we have Mr. Shah. So let's tell you about Figma. Ship the best version, not the first one with Figma, including, introducing. introducing Claude Code to Figma, explore more options, and push ideas further. And without further ado, we'll bring in our first guest to the show. Alap, how are you doing?

What's going on? Oh, great. How are you guys? Doing great. Is this your first time triggering a global sell-off? The first time so far, but I'm just the best injure. The way I look at it. We've got a lot of opportunities and a lot of scary things

coming down the pipe. Okay, so yeah, take us through. the thought process, like how long have this been simmering? What was the actual process of putting together this report? And then what do you want people to take away from it? And then maybe we can go into some of the reactions and your reactions to those reactions. Absolutely. The process ultimately is that I've been building in AI for 15 years and I've been an investor for 20. And so especially the last six months, as I've just been using agenetic coding myself and my teams have adopted it, it's just been a step change function and how much we can get done.

And just thinking through, hey, how is this going to, we're early, we're a startup, you know, we're going to be at the leading edge of how people are adopting things, you know, assuming the corporate world is a year or two years away, it's going to be pretty profound. And I think the underlying thing, you know, as sort of an amateur macroeconomist is we're just not producing white-collar jobs to begin with. I hadn't actually seen the extent of that until I kind of looked at, you know, specifically what we call like the information sector, so different parts of kind of technology, those jobs are down

8% from the peak in 2022 already. And so those are the places where people are adopting the most aggressively already. And we know, you know, every week there's firings out of like big tech. And so in that world, what happens when the technology that big tech's been using for a while has gotten a lot better? And now, you know, your average corporate starts using it as well. It can get quite scary. And so, you know, we wanted to kind of think through the implications of that. And, you know, the piece. But how much of those? of those layoffs do you think are, you know, we've talked about a bunch of those

layoffs on the show. They're usually attributed to AI, but if you dig under the hood, it's like they just wanted to kind of resize or get more efficient or they're reprioritizing resources and not actually because they just launched some new agent and suddenly everything's changed. Hey, we don't need these thousand engineers anymore. So I think, you know, those are all great corporate euphemisms. And of course, that's how they're going to say it. But I think the way I would think about this is it's not necessarily like agentic powers happened

and now everyone's going to get fired. You know, agents and LLMs broadly are just sort of on the tech tree as a continuum from software. And so software has been making companies more efficient for decades. And, you know, that has caused a lot of downstream effects. And now that software has just become much more intelligent. And so in that sense, I think, you know, companies that are efficient have been doing a form of this for a really long time. And we think about, you know, the age starting now in 26 is just something that's going to accelerate that. Okay.

So, yeah, what else was, like, key in the thesis or maybe potentially overlooked that you think people should be really focusing on? I think the problem, A, the first thing, the most important thing is just the labor market dynamics. We've just been in a really weak labor market for a while, and that's before these things roll out. But then you put that together with the fact that, you know, we just have a very structural environment where what is the thing that drives our entire economy? It's wages. Most of those wages that are ultimately driving all the discretionary spending is coming from the white-collar worker. And the problem with that is that we're now entering this place where you made all these assumptions on, like, loaning money to all these companies, you know, to mortgages and everything else. like where white collar economy is our economy, if you all of a sudden just take a leg out of that

economy, it has a contagion effect into basically every asset in the world. And so that I think is the part that people haven't thought about because when people were making these loans, no one ever consumed in a world in which, wow, okay, now like white collar jobs are in sort of permanent decline, right? If that's at 2% a year, then I think we can skate through. But if it's at 4% or 5% a year, then we need action a lot more quickly. Is the white-collar economy actually the full economy, or is it more just like the stock market? Because it feels like white-collar workers are disproportionately allocated to assets versus consumption. And you see things like, you know, like there's a lot of health in more blue-collar sectors, health care is growing.

And then you also see dynamics like just, you know, like we've seen like jitters in the, in the, consumer market for a long time and then we just see the health of the American consumer just continuing, continue and continue and it feels like it's maybe driven by something like lower level and there's always this disconnect in my mind between like the economy and the market. It's a great question. I think the issue here is that it's all just one labor market and right now pool collar is doing better because they're not firings there. I don't think you know I think robots are probably 18 like 24 to 36 months behind. Yeah. Other forms of

that are, you know, just diffusing through society. But the problem is, let's just say that it's one labor market ultimately. If there's no more white, if the white collar jobs are going away, let's say, you know, in our scenario, we talk about 5% of folks might get fired in a couple years. Those 5%, if there aren't white collar jobs for them to relocate into, then they're going to have to move into the gig economy and the blue collar labor force. And so that puts pressure on the entire labor market, not just the white collar one. And to answer your other question, healthcare is growing, education is growing. The reason those things are growing ultimately. And we did some work in our piece to try and isolate white color that is not

government-driven. And so the government continues to spend more. That's why health care is growing. They're the biggest payer in health care. They're guaranteeing all the loans in the education industry. And so those sectors continue to grow because government spending grows. But that's, again, it gets very circular if government spending is coming primarily from taxes and primarily payroll taxes because the average worker pays a lot more in taxes per dollar than the average corporate does. And so some corporates make a lot more money. Workers payroll taxes go down more than there is a bit of a contagion effect into bonds as well there too. On Saturday, John and I were going back and forth about some of the really wild predictions around the impact of the Internet that were being made in the 90s.

There was clicks, replace bricks. People were predicting total die off. Flicks did. Well, I mean, to be fair, to be fair, to be. be like I'll just finish they were expecting a total die-off of all brick-and-mortar stores in five to ten years which was like widely widely discussed prediction it was like why would you ever go to a store to buy something if you could just get it online sent to you directly yeah and a couple a couple others so like not as relevant to your piece but people were predicting like permanent high

growth, the end of business cycles. There was the media disintermediation narrative, which was like the Napster era. Everyone was going to get all media for free forever. Newspapers would would die off. Record labels. Aren't you guys the media disintermediation narrative? Yeah, we are. Yeah, it's all about timelines. 20 years later. And CNBC is still a much, much bigger business than all business media. at least in our world. But like newspapers, like magazines, completely gone, right? All of that has moved to the internet.

Totally, totally. It's just like, like, like, 5% employment shock and, you know, unique example. I mean, like a 5% unemployment shock is completely different if it happens over a quarter than if it happens over two decades, right? Like, these are just fundamentally way different things. Yeah. Yeah. The last thing I would say is like there was like this concept of like frictionless capitalism,

meaning that like middlemen would be eliminated because you could just go directly to the source and that would push pricing pressure down. My question, and I know you guys are not writing your piece saying like, you know, this, we believe we will stake our entire reputation on this sort of narrative. But what do you think? What what how much did you pay attention to like the 90s, early 2000s internet predictions? What do you think they got wrong? Why is this time different in terms of how a new technology will diffuse to the economy? I think the difference is if you just plot what's happening to technology, it's all just going exponentials. These are all just continuous timelines of like we have microcomputers, we have the internet, we have mobile phones, and today, you know, we have very powerful AI.

And so I think most of the predictions that you ticked off there, it's kind of interesting. I would, you know, just looking at them today, you know, I would say they couldn't really happen until you had proper AI. Because like if you have the ability to just freely, you know, come up, like have commerce the way you do today, it doesn't work if you still have to do all the work. Ultimately, like, you have to go and you have to log and think about the amount of friction there is in buying a product for most people today. Right? You still have to go to the website. You have to put your credit card in. It's all work. We only have gotten to kind of the tech required for those predictions, I think, this year. And that's why this is the year that I think it really begins, because now it is completely seamless.

And no one's really doing this yet, but it's going to happen, I think, you know, in the next six months, is just tell your agent, you know, tell Gemini, tell Chat, EBT, BT, go buy these things. It has your credit card. And now that world that they were describing is truly going to come to pass. Yeah. What about the Canary and the Coal Mine analogy? I was looking at unemployment statistics in India and the Philippines, and it doesn't seem to be doom and gloom over there. I don't know.

I didn't dig in super far, but would you at least expect that the unemployment rate would spike overseas before it spikes in America, or do you think this all happens simultaneously? It's a tricky question. I think ultimately white-collar work is a lot more of our economy than it is the economy of India and the Philippines. And they are much sort of like more immature economies

that are growing through investment and things like that. But certainly I think we called it out. The consulting sectors in India are certainly going to be challenged in other places as well. But the reality is like the timing, timing is everything in the markets clearly. But the trick here is if you're a corporate and you are hard pressed to get AI into your organization today,

you know, chat DBT and OpenAI, will send you a forward deployed engineer if you have billion dollars in budget, right? If you have a $10 million budget, they're not going to. And so who are those folks turning to? They can't usually do it themselves. And so they are going to the outsource providers, the accentures of the world. And so I think those businesses are likely going to be in a lot of trouble over the medium term, but they probably will have a big bump from people really putting that AI into their organizations first.

And so it's a bit of a tricky timeline there. What modes do you think hold beyond this? because I think a lot of people latched on to like the DoorDash example as something that they thought had a moat and that in the post you sort of underline like how that could maybe not be as durable as a mode as people thought but in the long case like what what moats do exist like do network effects stay do complex coordination intellectual property like what doesn't break down You know, real brand value where people are choosing you over other things because of the brand and the status signaling across brands matters a ton. Network effects are more powerful than ever, I think, in this world. So things like meta really have a lot to sort of gain in that sense. But I think things that look like their network effect businesses, but in fact are just the ones that are doing the hard work of aggregating demand and supply, I think will be more challenged. And so DoorDash is a good example there.

It's not necessarily the biggest risk versus some of the other things. But I just was in a thread with Gavin Baker talking about this. But the problem for DoorDash and Uber and folks like that is right now they're doing two jobs. They're doing the job of aggregating demand and the job of aggregating supply. They're both hard jobs, but the demand side is the harder side. And we think the world of the future, there are lots of folks in, let's say, food delivery, Instacart wants to get a bunch of market share and Grubhub wants to get a bunch of market share

and so let's say the agents are the ones doing the buying. It's 2028 and 40% of the sales are through agents. You just tell Gemini, hey, order me some noodles. In that world, instead of, it's going to go to each and every provider. And right now there are four providers that do that. But now it's very easy. If I'm building a startup in the space, previously I had to get all the drivers on board,

get all the restaurants on board, and acquire customers. Now, Gemini and Chat ChaptiPT are acquiring the customers for me, and all I have to do is get the supply side going. So it makes it much easier for new entrants to come in. And for existing, you know, second, third, fourth tier players can really sort of say, I'm going to like relax my margins, try to get more top line. And so you would think that, you know, whatever the 15% Vig is that Doordash gets today, maybe it's more than that. You know, some of that, I would think Gemini and Chachypte are going to ask for themselves. Wherever I send the traffic, I'm going to get a piece of that.

And then some of that's going to go back to the consumer. Yeah, it feels like, was this the most, like, stretched or controversial prediction? It seems like it was certainly the one that got, you know, that's getting the most chatter. And I think we did it for a reason. We wanted to be a little provocative in thinking it through because, you know, it's an amazing business and they're gaining a market share. But the fundamental idea that you're, because what did the lock in, right? Like, do the drivers have lock-in on DoorDash or on Uber? Not really, right?

They're, you know, most drivers are doing Lyft and Uber, so they're not locked in. The real lock-in, the real business value, the franchise value of an Uber or DoorDash, is the customer lock-in because the customer gets comfortable, they've got everything saved, they want to hit a couple buttons. They don't price shop. Agents are happy to price shop as much as possible. And so if you take that away, then it's a real problem for businesses that, you know, are ultimately built on customer lock-in.

Yeah. Yeah, I don't know. I think the interviews that we've had with. The lifts, I mean, you know, again, take it with a grain of salt. They have a narrative that is important to their business. But like, if you ask these people, what is the greatest challenge? It is managing the supply side. It is not, the demand side is not where they're saying, like, hey, like, this is really what we need to solve.

It's like, hey, as we get more drivers on the platform, revenue naturally, naturally goes up. And so I'm just hard pressed to imagine a world in which, you know, somebody, think about if somebody in my town, which is like 15,000 people, like vibe codes, a delivery app. And I go into chat, CBT or with another agent, and I say, like, I want food. It's like the agent wants to get the best possible service. I would imagine the agent to route to the platform with the supply that is going to be able to deliver in the shortest possible time horizon. And imagining a world where there's like this vibe-coded, small team operating that just happens to aggregate as much supply, which is just increases the likelihood that my order will be delivered on the best possible timeline, which is going to be the number one factor for customer satisfaction.

I just don't see how solving the front end kind of demand piece actually makes a better consumer experience, which I assume the agent would optimize for on behalf of the user. So let's consider what actually happens here, right? You make the order on DoorDash. DoorDash sends it to the restaurant. The restaurant essentially, you know, sometimes they use their own driver, sometimes they send the drivers from DoorDash. But now imagine the agent can take you directly to the restaurant.

restaurant site and place to order directly with the restaurant. And you can keep half the savings and the agent can keep half the savings. But where's the driver? Where's the driver coming from? Because I feel like I understand the customer demand side, like you start with an LLM or an agent who shops around for you. So maybe that's solved. Maybe it'll find you just via SEO and you can just put out like we only take a 5% cut instead of 15%. and the agent picks you. I understand getting all the restaurants on board because you email them and say, hey, it's 5% instead of 15% they're sure, we'll turn it on. But for the drivers, how do you actually reach out to them and get them on the platform and how does AI

lower that cost? Because right now I think about like what was the driver marketing budget over the last decade at Uber or at DoorDash? And it's probably like in the billions of dollars. And so I feel like to generate that much liquidity, I have to invest that much to onboard all those drivers, build awareness. Maybe it just goes viral because they're like, hey, I can make more money here. But that feels hard. I think it's going to take time. But I think there are a bunch of smaller sort of driver aggregation networks that exist today that are not the ones that we know about. For instance, I started a business called Thistle and we do delivery of healthy foods to your door.

We split it between half of them our own employee drivers and the other half, I think we have like 500 or 700 drivers that we just use a third-party service to provide. So I think there are a lot more of these businesses. All those businesses now will also just have huge opportunities to kind of take market share. Ultimately, what we're saying is the friction in doing commerce is going way down, places where there are rents. The prices can go down. But ultimately, this is just an opportunity for more entrepreneurs to kind of build businesses for the new world. Yeah, I think the the it's interesting because we're here like debating like this this like somewhat temporary thing because like self-driving cars, robotics like changes all of that like in a huge way. But but we we use the term slopable for companies that are that can be vibe coded away and clankable for companies that can be disrupted by robotics.

And I've always put the delivery services more in the clankable category than the sloppable category. So I was I was shocked to see what are the but it's reasonable. more time on if you knew you were going to get 50 million views and the markets would react in the way that they have. I would have finished writing the third piece where I talk about solutions, which I have not got free yet. A lot of people are demanding solutions. You just got you just hit me with a ton of problems. That's funny. Do you think that there's any, there's this question about like, in my mind, like, yes, Google and Nvidia are public, but Anthropic, Open AI, and XAI through SpaceX are not public.

There's sort of like this massive, you know, multiple hundred billion dollar sell off in the public markets that sort of should, if you believe your thesis, that should sort of funnel to the labs, I would imagine. When I read it, like there's a lot of doom and gloom about companies that are out there, but it's a lot of bull case for AI labs. And, but that can't happen in one day,

because like rounds happen every once a while, they're private, there's all these different things. But do you think that the world would change when the big labs get out in the public markets? I think it's absolutely gonna change. I have a strong suspicion that Anthropic is gonna go, you know, in the next three to six months. They just have so much momentum

and there's a lot of value of being first. Yeah. Their P&L also just looks a lot better than anyone else. So I would think that gets public and it's gonna be pretty interesting if it happens. Certainly labs are ultimately, they seem like they're very, They're very well positioned to win.

I would wonder over the medium term, like, you know, what happens with some of the Chinese models and whatnot if people actually want just something that's more local and something that they own. But it does seem like the most likely outcome is going to be that the existing incumbents are going to get the most share. And I think Google is particularly well positioned since they already own all those customers today. And they can finance losses from inference a lot longer than everyone else. But I think ultimately, like, there's a world in which the labs are the biggest winners here. There's also a world in which you end up with just a lot more competition and people trade and change. But the thing that seems very clear to me that the absolute, like, there's no way they won't be the hugest winners here is going to be the underlying tech, meaning the semiconductors. So everything and you go even deeper.

You could go into like commodities and like copper and energy and oil and natural gas and stuff. People have. Yes. Did you see the, some of the criticism was that the essay was very Marxist? Oh, yeah. Reheed said, Mark's writing during the Industrial Revolution predicted capitalism would periodically devour itself. Firms replace labor with machinery to boost profits, but competition diffuses the technology, drives prices to marginal costs and the gains get competed away. Meanwhile, displaced workers lose purchasing power, hollowing out the demand the whole system depends on.

Production rises, but no one can afford to buy what's produced, the contradiction between production and realization. Satrini's piece describes this exact dynamic, then declares there's no natural, break. It's the most Marxist piece of financial analysis. Not my word. I don't think you were expecting that critique. And makes the same errors Marx did. Yeah, creative destruction doesn't just destroy. It creates industries we can't yet conceive of everything. Yeah, that's interesting. I mean, maybe that's going in the solutions. Is that going into solutions? So let me address it a few ways. Marks was a really smart dude. He got a lot of things right very early. Marxists can mean communist. Marxist can also mean just understanding how capital and labor interact.

And in that sense, yes, it's Mark, because he was very insightful. But I think the thing that we're missing here is that it's, there's, there's the economic layer, but ultimately it's the political layer that matters. And, you know, we're in a world where we've had two parties. And both parties, you know, economically have a little bit of difference, but not a huge amount of difference. And so we kind of bicker. But in a world in which jobs are going away really fast, I think,

there's going to be a much stronger alignment for, you know, just a laboring class overall to say, hey, we need to fix this problem. It's a very fixable problem. What I'm, what we're actually expounding here is that GDP, if done properly, will absolutely explode, right? We're getting way more efficient. We have, you know, we've built a machine dot. We build machine intelligence. But we have to structure our society such that as those things happen very, you know, hopefully very slowly, you know, we, we do the right thing from a taxation perspective to say the winners should win, but if that's what's causing the displacement, let's sort of make the pie a little bit bigger for everyone.

And that I think ultimately should be something that appeals to a lot of folks in the AI complex. Because if we don't, then something like this is likely to happen. And, you know, AI progress will slow down because we'll have an economic crisis and we're not going to go to finance nearly as much of it as we otherwise would. So do you think the future is what Anthropics head of sales position in France? The company will be spending $530,000 euros per year. the government will get 340,000 euros, and the employee will get 190,000. Is that the level of taxation?

Do you think we're headed for? I think when we're at, you know, France's level of government spending, then, you know, the math probably means roughly that. I would say that, you know, government spending would be at France's level, I'm guessing, like, you know, five or seven years from now if this, if this scenario kind of comes to pass. And so I think we'll head there over time, but I think it's less a question of the percent of spending and how much goes to the employee versus goes to the government. And ultimately, what is the size of the total pie? So the bet here is that the pie, if done properly, can just increase multiples of what it is today.

And thus, you know, it's just a win-win. One question. I mean, it sounds like you're working on potential solutions post, which I'm very excited to read. Thank you. I'm interested to know your reflection on the messaging that's coming from the leader of the AI labs because they've outlined many sort of low probability but you know potentially negative scenarios you know we have the white color work number we've had many of these comments from lab leaders but I rarely hear them follow it up

with and the answer is print print print or interest rates will be will save us or unemployment insurance or UBI like all of those like solutions that I think people it's funny because people are quoting your post being like this is easily solved with this solution it's like okay well that's great if we all agree um and i think you might with some of the some of the quotes people are all over the place um but i'm wondering about your reflection on like the the the like the messaging from the labs around solutions versus pure focus on problems i think it's a really interesting question and very interesting setup in that the labs are on the one hand you know want to get the word out there and so you know dario especially has

been the loudest here. There's a really good Axios article from last May where he's kind of sound of the alarm bells. People aren't really, he's like saying people are not listening. Obviously a lot has changed since then. But they can't go so far as to say like, hey, if you put the pieces together, then this is how it's going to play out. I think it's too sort of damaging to sort of their reputations and like, you know, their ability to fundraise and things like that. And so I think it's other folks like ourselves that kind of have that duty to go and really start thinking that through. It seems like Anthropic is pretty engaged. Should that conversation really start happening? I think this is the year it needs to really start happening. And so I think

they all kind of get it. And so it's just a question of like how do we as a society start moving in that direction? Yeah. I think, you know, obviously there's, I'm still processing part of the piece. I agree with some of it. I disagree with some of it. But what's really underrated is just like how useful this process of writing an article for a particular audience is. Like I disagree with a lot of, you know, something big is happening, but it hit with a very different audience than machines of loving grace or the adolescence of AI or of machine intelligence. And there's pieces that are written for like, you know, AI, insiders, leaders, researchers. Then there's like the broader tech community. Then there's like everyday people.

and you clearly hit the nail on the head with like speaking to the financial community. And we see that in the market's not amazing results, but maybe it's maybe it's worthwhile because we will get really great solutions and a better conversation around it. So I think in due time this discussion needed to be had. So thank you. What's it, what's an industry or job of the future that you could see emerging? I think, again, if we solve this, like everything related to sort of leisure is going to absolutely zoom and that those are going to be the biggest growth industries of the future, right? Like what do humans want to do? Total chess.

Watch polo. Exactly. Like a cloned horse play polo for sure. Yeah. So, you know, imagine humans have like the entire day to just enjoy themselves instead of having to work. Now, that is something I've been promised for 100 years. So I'm a deeply skeptical. But this time is different. I wanted to be different. Let's bring on the leisure.

Boom. I'm here for it. I'm here. Anything in your solutions, Doc, around reindustrialization? I mean, the frustration that so many people in tech that have been building in kind of hardware in the real world or trying to recruit people that are getting offers from social media companies or now labs or SaaS companies, you know, one of the problems of, the problems of America in the last 20 years was that if you just wanted to make $100 million,

you probably were much more likely to do that building enterprise software than building critical infrastructure or anything in the real world. So is that kind of new infrastructure and re-industrialization, like a potential landing point for people that had the 180K a year PM job that might be going away? It's a great question. I think there's certainly going to be a lot more opportunity in those sectors, and I think we've done some pretty smart policy things that are moving us in that direction. But we're also, you know, just in a lot of ways so far behind China there, and doesn't AI affect kind of those jobs both for, you know, on the reindustrialization side just like it does for writing code. And so that's where I think it will get trickier. I think over as a country, we're going to spend an awful lot more on that.

I think we're going to catch up. But we're not, it's not clear that's going to be. be through just creating a bunch of additional jobs versus, you know, the ultimate thing we're seeing with AI period is just high agency people who really know how to reuse the tools can just do the work of many, many people. And I think that trend applies in every industry to some extent. Yeah. What an exciting time. Thank you so much for taking the time. When's the next piece dropping? Hopefully by the end of the week, but don't hold me to that. When you know that it could be hard for the fall-up to get as much reach as this one. That's kind of the way these things go.

But now the pressure's on to really pay attention. Just don't have any sequel anxiety. You'll be fine. We're excited to read it. And we'll talk to you soon. Yeah, great to meet you. Have a great rest of your day. Thanks so much.

Let me tell you about turbopuffer, serverless vector in full-tech search, built from first principles on object storage, fast, 10x cheaper, and extremely scalable. And I'm also going to tell you about gusto, the unified platform for payroll benefits and HR built to evolve with small and medium-sized businesses. And without further ado, we have Will Brown from Prime Intellect in the TVP. How's it going? Welcome to the show, Will. How are you doing? It's been too long.

I'm doing great. I'm doing great. It's great to be back. I think this is the fourth. Something with that. I looked at there was a list at some point of the record. And some people have been on something like 18 times. on something like 18 times.

I'm looking forward to the 400th. It's great. It's been a lot of fun. What are your old buddies at Morgan Stanley thinking about the current thing in tech, the 2028 intelligence crisis? Have you gotten any messages? That's a great question.

I have not had the full deep-tadmast. They're too busy hitting the sell button. No, everyone in Morgan Stanley is too quickly, too busy setting up Mac minis to run open claw. That's what's happening. because they all just read something big is happening. Right. And so like I think there's definitely a lot of opinions on all sides.

And I feel like that, to me, the piece was pretty cool. I don't necessarily like agree with it, but I think it was effective at getting people to have more interesting conversations than, for example, recent other, maybe viral pieces about how everything's going crazy. And it seems like the conversation ended up getting like into the weeds of monetary policy

and like how people are going to react and like, how hard is it to vibe put a DoorDash clone? And these sorts of things I think are actually like the sorts of conversations that are good for more people to be having, like whether or not a certain prediction is right. I think like it's just generally, like, as stuff is getting crazier, I feel like this is the sort of stuff that allows the rest of the world to kind of like hear about from their friends,

like a little more grounded discussion about what could happen. Yeah. Well, give us an update from Prime Intellect. What's going on in your world? Yeah, yeah. So there's a few things that I think are interesting as well as I want to talk about just today, given some other stuff that's happening on the timeline. But so a couple weeks ago, we released a training platform to make it really easy for people to do RL on top of leading open source models with their own environments.

And we've tried to really make it an agent native experience where you're kind of like, there's a, some model people have been kind of tweeting out their experiences. The term people have been using is vibe RL, which is we're kind of now at the point where the infra to manage the training is kind of in place. and you can do it without thinking about the hardware and the GPUs where the models still kind of struggle, but you can really focus on like the environment and designing your tasks and specifying what you want and having turning existing data that you already have into kind of training recipes.

And so we're kind of at the point now where like, this is pretty accessible for people to kind of go train models. And it's been pretty cool kind of seeing people have fun with it. Yeah, concretize some of the actual applications. I imagine this works best if everything, flows through text, flows through CLI tools. Because when I think like, okay, great, I'm gonna set up an RL environment

and automate one of my workflows and I'm like, well, I'll need to open Adobe Premiere, which has a license and then I'll need to go to YouTube and download some videos. I'm just thinking about like editing a short video that we have. Of course, yes. Some of that stuff definitely,

like there's definitely a range of like simple to complicated. Yeah. But I think there is a lot of sweet spots where it's like the coding tool use and interacting with kind of app simulators, which are the sweet spots of a lot of these, like, focuses for people doing training in the labs anyways, rather than, like, full-fledged Photoshop.

There's a great tweet actually from the ramp guys, from ramp labs showing off how they had been using it for some stuff. It was the team behind ramp sheets, and so you could kind of imagine, like, the sorts of things there where, like, you don't actually have to build the whole thing, but you can, like, and this is where I think the coding agent stuff is really useful. There's a lot of ways you can kind of have the right simulation of the application that is like, it isn't necessarily the full back end,

but it's enough to be able to capture the task. Yeah. And the coding agents are good enough that with human in the loop, using, like, it's all CLI data. So you go into your terminal, we have our CLI, the Prime CLI, and you use that to kind of like set up your skills and get your coding agent configured and your agents MD. And so we've tried to like make that really smooth,

but then you just start kind of like talking to your agent about, hey, my data's here, my app code's over here, let's put it all in the right place and kick off and runs. Yeah. Where are we on the path to personalized RL? I'm thinking back to like the RL that went into RLHF around. Right, right. Chat, GPT, GPD4.

And I remember it was like they had maybe tens of thousands of contractors sort of grading responses, giving thumbs up, thumbs down, giving feedback, varying levels, like a really large scale, generalized process. If I'm running a medium-sized company, is this something that I can pull from logs of what's happening in the business? Should I be firing up a data labeling company to help me generate more data? Because in the long term, I would love just a screen recorder, watch me what I do, and then it's RLing, and then it's getting better, and all of a sudden it can just do what I do with just like one prompt. Yeah, it's pretty close. It's definitely

it's not that sci-fi. Like if you have stuff, especially let's focus, if we focus on like text or image input, full screen recording gets a little tricky. But if it's like text or image input that kind of comes from like agent logs and it's like human inputs, text, and images to an agent log and you have these logs

and you're trying to synthesize these logs, I think the trickiest part is refining criteria about like what counts as good for like rescoring another tribe, but a lot of times the criteria are like either pretty general across tasks or you can infer a lot of them from a user's response or just from the initial prompt. And from what we've seen, it's especially for a lot of very concrete problem solving

use cases more so than, let's say, like, creative writing. But for things where it's like there's a right answer and it's not too hard to see if the model got the right answer from doing an agent trace, either from the human's response or let's say that if companies want to have their humans like label as part of using the product by default. Yeah, this is doable. And the RL recipes are kind of stable and scalable enough that like it kind of like it doesn't always work, but it works reliably enough that it, I think the barrier to entry and the cost are just like at a point where it, it's cool to see that this is now a thing people can go do. Yeah. And we're seeing a lot of people like have success with it. Yeah. How are you thinking about the debate

between MCP and CLI? Uh, Peter was going back and forth. And it, it was something that I was wondering even when MCB came out, it seemed really cool, but at the same time, it felt like, well, the front end, and I remember going to the front end and inspect element and see what's coming across and, oh, there's a HTML request right there. Let's reverse engineer that. Yeah, it's all kind of the same thing. It's sending requests. And so I think people realize models were good enough at coding that the skills are essentially doing the same thing, but it's just you have more flexibility to, like, I think the area where MCP makes the most sense

is when you really want fine-grained, like, off stuff going on where there's, like, kind of credentials and you want to be able to kind of notice that it's being done and have the user, like, approve certain requests or not approve others. That's where, like, the formalism of, like, the tool call is really useful as opposed to it just being code that has an API token.

Yeah. But from the productive capabilities, like, skills are nice. MCP has its areas where it makes sense, But it's really just models using computers, whether it's MCP or code or skill files and reading docs. It's like models are pretty good at reading stuff. And if it has instructions on how to do the thing, they can kind of just do the thing. And they can do that for a while enough that it's useful. Yeah.

How intermediated do you think this product will be? And what I mean is that like, let's just use some toy example, like, you know, widgets company. would benefit from a custom fine-tuned model or RL model. But they don't go to you. There's actually a company that's an intermediary that is providing like a SaaS product that then is fine-tuned on like anonymized industry data or they went and generated URL or they'll even come to the company and say, hey, well, Hansel, well Prime, CLI, you're not going to have to know what that is.

You just give us the data and we'll act as like your customer. How do you think that plays out in the market? I mean, it's definitely going to happen across the spectrum. I think the people who we work the most directly with are the ones who are a little more like AI native and the ones who are going to work with kind of, because I think we're really like building for developers as our kind of target audience, but not necessarily researchers. So I think like the people who are like following the benchmarks and reading about the new model releases

and building with cloud code and the agent frameworks, that's really like our target audience, people who like think about e-vals and prompting versus people who like don't think about that. So we do actually work with a lot of the big data companies where there's like, I think maybe the one interesting story is like there's a lot of market demand for, because everyone's like building environments and selling them into the labs. But you can see a lot of these companies want to like know that their environments are good. And so like using RL as part of this process is the way that you evaluate the quality and be able to prove like, hey, we've got we got the good stuff. Because it actually like improves capabilities. And so there is this whole economy of companies that really specialize on building environments and working with data.

And I imagine this does become a big part of like the way that this stuff is consumed by end companies is through people with that kind of expertise at the data level. Talk about what the Chinese labs are up to. I was going to ask the exact same thing. In terms of stealing American models, how, how talk about kind of the scale. I've seen some rave reviews. I've genuinely. I've genuinely seen some rave reviews of Kimmy K2, and then at the same time I've also seen like, hey, it kind of fell flat on his face when I pushed it beyond a toy example. So yeah, what's real and what are you experiencing? Yeah, so I think they're definitely a couple months behind.

Like they're not at the 4.6 at the Codex 5.3 level. They're pretty close to what we had before that. And I think that's kind of where it's been and it feels like this is tightening. But I think at least where I get much excited is like they're good enough that going the extra mile with customization is a different theater, where you can take a model that's already almost frontier and make it the best model in the world at your thing pretty easily and pretty quickly. And so I think that is, even if you have to do this every three months, like, there's, it's always a capabilities race. But I think if this pipeline, it's this process of, like, taking your data and improving the latest model becomes really easy and repeatable, then it's like you can get a lot of value out of doing that. And I think that's the sort of thing that's going to be in a lot of people's toolkits.

In terms of like the open source models generally, I think, like, there was some interesting debate on the timeline today that I dove into for a little bit around anthropic and deep sea. and in the, uh, doing distillation. And I think like, it feels like there's, there's kind of two things. There's the kind of geopolitical element. Um, there's the kind of like terms of service of like, oh, they're doing bot farms, they're scraping, like, that's not allowed. And there's also like the idea of like distillation more broadly of like, is it? And the two I totally get, the first two.

But I think the thing where I was kind of like trying to push back a bit was like, I mean, everything on GitHub is someone typing a prompt to Claude and submitting it to Claude code and then they're going to review the PR, then they're going to merge it. And this is like perfect training data. And so the internet is just getting flooded with perfect cloud distillation training data. Interesting. Yeah. And there's not much you can do about that. And so it's like, is distillation really the hill we want to die on?

Okay. Yeah. I guess the secondary question is like put all of that aside and then just ask the question of like, of like, is there some, you know, ticking time bomb? with using a distilled model where you run into some wall or you have some problem in performance down the road. And so, yeah, you're doing well in benchmarks, but that is less effective? And is that, like, actually problematic from a business perspective? Or is it just like, okay, yeah, like, I'm getting three months behind, but it's three times cheaper,

so I'm fine with that tradeoff versus, like, I thought I was using something great and then it blew up on me. Right. So it depends a lot on your application. So they think there's certain things for like the models are already like more than good enough. And these are like kind of more commodity like extraction or summarization or labeling use cases where like you kind of just want to optimize for cost. In some cases you want to optimize for speed. If you want to optimize for performance, then if like cost isn't a concern and you really just care about top-wide performance, then customization is really where the open source models become interesting, which is that like you can do more to the open source models than you can do to Claw. And you can have a lot more fine green control of like saying, hey,

This is my e-val. This is how I'm measuring performance. We are just going to hill climb this. And then it's up to you as a business to define your business logic, say, hey, this is what I actually care about. This is what performance means. And I think we'll see a lot of companies realizing that, like, that is a useful knob to be able to turn, to be able to like.

And I think concretely what it'll look like for a lot of cases is there'll be these multi-agent products that have their main orchestrator agent that's, like, one of the frontier models with lots of specialized. sub-agents for things that are related to the business and specific workflows, which are then fine-tuned models. I think that's kind of what we see currently as, like, the most, like, dominant paradigm for mix and matching between the proprietary models and the fine-tuned open models. If you had told someone a year ago that there were going to be like probably millions of people running agents locally with custom setups and dot MD files for various skills,

they'd probably be like, wow, that's pretty aggressive. Do you think that we'll be in a world in like a year or two where at least, you know, people on X will be talking about like my fine tune. I got the, I did, but I did RL on my Pacific problem. My personalized agent is like even better now because I did the RL. I mean, so we see it today already with this a little bit where it's like, I mean, there's people who are showing, You can get these models to beat any of the closed source models on sufficiently well-scoped tasks pretty quickly.

It's not rocket science. You can basically vibe code it. You have to know, you have to like be clear that you have a goal in mind, but if you can define the goal and you can spell this out in English and you can do the same sort of prompting that everyone's doing for coding, then yeah, you can just kind of plug it in and get trained to work. But I think it'll become more like a lot of it is still very much like these kind of of more proof of concept or narrow research cases. But it does seem like it's quickly, especially like code becomes cheap. And the more the cheaper that code gets, the more complex you can make here in environments. And I think like a year ago, we saw like flood codes about a year old. It came out, I think, February last year.

And at the time, it was like, wasn't actually that useful yet. But I remember playing with it and feeling like, oh, this isn't actually something I want to use that heavily today because it's kind of slop. It's very chaotic. It just makes a mess. and I went back to Curser for a while because it was much more controlled. But it was like, oh, this form factor feels like it could eventually work.

And I think there are other form factors today that don't actually work yet. In some ways, like it's the open claw thing where it's like, open claw like kind of works, but there's also a lot of trouble it gets into. Same with like, if you saw like the Gastown thing or these like crazy multi-agent systems where it's like they aren't actually excellent yet for shipping quality production code. But the thing we had a year ago now is at the level where, like, Claude Code is used for, like, most production code. But by the heavy adopters or codex. And so, like, it feels like it is a matter of time until these things stabilize.

And, like, the goals of having that system kind of end back up in the models, the people training for it. But, like, the recipes of how to train these models, they've become, like, robust enough over the past year. that it does seem to be like a good idea in all of these cases to optimize your models for the structure you want them to be in. And if that structure is this crazy multi-agent system thing, it's like, yeah, why not? Yeah. What are you, are you expecting real tangible breakthroughs in the next, in the first half of this year? I mean, our intern keeps saying that he's close to cracking continual learning. Oh, yeah, junior learning is going to fall pretty quickly, I think. Do you think it'll be less of a big thing than...

I mean, I think it's more of an engineering problem. Okay, explain. No one's actually trying. No one's actually trying. Why not? Like, no one, like opening eye and Anthropic don't want to continuously train their models for each user. It's expensive and annoying and hard to serve at scale.

But like from a research perspective, like we do continue learning with the model learns news. They just keep training the model more, and it knows more stuff because they put more internet in it. Sure. And, yeah. Yeah. Yeah. Yeah. Yeah. I think it's a problem.

Un-economical right now, but, yeah. But not for a product like Frontier, I could imagine that that would be a selling point if you're McKinsey and you're going to a big institution. So, yeah, if you hypothetically, like, I don't know, you're a law firm and there's some crazy case update, like, yeah, the model retrains on that, like the day that the Supreme Court

completely changes the way the law works, and then everything else is, like, interpreted from that. Yeah, makes a ton of sense. Yeah, and there's enough kind of tricks. I think there's a lot of experimentation around like exactly the recipe that's going to be the most reliable. But we kind of have a grab bag of like six or seven tricks that kind of work. Or they work in different ways and you can mix and mash them. And it's just going to be like whatever's the best combination of these tricks.

People are going to experiment with it and find the versions that work the best. And there doesn't seem to be any like big wall inside that prevents that from like being practical. That's cool. What are you tracking on the silicon side? We were playing around with chat jimmy.ai. Oh, yeah, that was sick. Jimmy's quick, but is he smart? Maybe too fast.

You have to like scroll up once you get the answer. Yeah, I was trying to see how many tokens I could get it to print so that I could actually see it go. And I was like, give me every number between one and like 10,000. But like Lama just won't do that. No matter how you prompted, it'll always stop after like a few thousand tokens. So you can't actually get to feel it like blitzing past. Whoa, interesting. Yeah. Yeah, yeah, yeah. It was like sort of a throwback experiencing Lama 3A8B because I remember where that model came out and there was a lot of hype because open source developers just love open source stuff and it was exciting and it was cool. It was like, wow, they really did train a big model and they just put it out there. And I remember some people being like, yeah, like if you actually go talk to it, like it hallucinates a fair amount. Like I don't know that this is like actually at the frontier. It might have done okay on some benchmarks, but it's not quite there. And it was a little bit of a throwback. But, but it was a little bit of a throwback. But. You can just imagine baking any of the current frontier back there, giving it access to tools,

giving it a reasoning loop. Like, yeah, it's going to be, even if it's only 10 times as fast, like, that's still so much faster than, like, okay, got to close the app and come back after 20 minutes because my thing is running now. It's going to be a completely different. And I think it'll be a big, like, step change for, like, people that are like, oh, yeah, AI, like, hallucinates. And, like, I need to check that out.

It'll be like, no, like, it's, like, totally, you can just have it right there. and it's perfect and it works a ton very fast. It's going to be a really cool moment. Will you be buying an AI lamp? I want the one that goes over your bed and folds your clothes. Oh, okay. Have you seen that one? Yeah, yeah, yeah, yeah.

It looks like it looks like it might dismember you if it doesn't like you. It's a little bit horrific, but I do agree if it folds your laundry, like that's pretty, pretty amazing. I don't care if there's a one in a 10,000 chance that it goes crazy. I don't care if there's like a one in 10. chance of me just being dismembered in the middle of my night because it gets mad at me as I was trying to it prompt injected or something. No, I am excited for hardware. It feels like it feels like even even the first-gen hardware like the Humane AI pin, the Rabbit R1,

all that stuff with like frontier models starts to get interesting. I really hope we get a solid next iteration there, even though it's obviously very much outside of your core competency, but maybe some hardware developers will be coming to you looking to fine-tune a model, RL model. Do you want local on device for something? Yeah. Because yeah, you can, I think, especially for like these narrow things, like if the R, the rabbit, whatever, and this is also Apple strategy.

It seems like is Apple's like they like keeping stuff on device. The whole privacy thing is part of their whole pitch. And so I think part of the reason why Apple's been slow on the AI stuff is they're shipping a feature once they can do it on device with a sufficient reliability. Yeah. And so that means they're slower in there rolling out of features. but it means that like the stuff like the summarization and the image search, like they can do this locally now because the hardware is good enough and the model are good enough at that scale. Yeah, yeah. You have to imagine that the same talus principle of like baking the model down to silicon.

Well, it feels like they're doing something maybe like wafer scale, like not iPhone scale. So like maybe that's another couple of years. And then you need another couple of years to get it to, okay, it's now frontier on a chip that's the size of your phone. fits in your phone, doesn't suck your battery down. But you play that out and you get to something like really, really fun and interesting. I'm excited. Future is bright. I think the, yeah, definitely exciting.

I think the people always said the internet was gonna run out of data. But I think what we're, like, we're getting more data, but it's better data because it's just from the last generation of models. Oh, interesting. And so you can kind of like, you kind of get this flywheel of like, there's just more data to learn from and it's all getting better as the models get better. And you do more on top of that to boost beyond where you were from the old data.

And that's where the RL and the filtering comes in and the human data. But like it seems like you just have a pretty clear path of models getting better as you put more data into them and we have the data. Well, thank you for coming on the show and producing a bunch more data. That's helpful. It goes on to YouTube. It's an honor to produce data with you. It's an honor to join the training set with you. Yeah, that's the goal.

That is the goal. And thank you to everyone in the chat who's also providing data for the internet. It's God's work. Thanks for having. We'll talk to you soon. Talk soon. Have a good fun. Let me tell you about Plaid. Plad powers the apps you use to spend, save, borrow, and invest securely connecting bank accounts to move money, fight fraud, and improve lending now with AI.

And speaking of data, let me tell you about label box, RL environments, voice, robotics, evals, and expert human data. Labelbox is the data factory behind the world's leading AI teams. And I believe we have our next guest already in the Restream waiting room. Five minutes ahead of schedule, Michelle Lee from Medra is in. What's going on? The TVVN-LGID. Welcome to the show. Hey, guys.

Hey. Excited to be here. Thank you so much for hopping on. Great to have you and your robots. Punctuality. Oh, yes. What is behind you? Wow.

There's a robot that's actually working. Explain. Introduce yourself. That's right. Absolutely. So I'm Michelle. I'm the founder of Medra and a little bit about me. Yeah.

I come, I study chemical engineering and undergrad. Was there a typical chemistry, life science nerd. And then I did an internship at state. and was just really excited about like, what if we can build in the physical world? Yeah. Right? Like I wanted to build in the physical world. I want to build real things with real impact. Yeah.

I ended up doing my PhD at Stanford at the Stanford AI lab in robotics, building robotics foundation models. I worked with Jeanette Bogue and also with Faye-Fei Lee. Shout out World Labs. Yeah, right. Say-Shah. And I ended up, when I finished my PhD, decided I wanted to, I wanted to do. decided I wanted to combine life sciences, robotics, AI, and I started Medra. And we are building physical AI scientists, which we think that is necessary to eradicate disease.

How narrow do you want to go to start? I mean, it feels like there's pipetting, there's centrifuging, there's different stuff going on behind you. But like medicine, bio, these are massive terms can be animal studies, mice models, you can have monkeys in there. There's a million things that you could do. But I feel like you probably want to pick a beachhead, but you tell me what the strategy is. Definitely. Look, like one day we will have Medra robots doing animal studies, like Mark by Words, right? But you're right. We have to start somewhere. And we're starting with early discovery and development. We have physical AI robots at Medra that can do experiments at scale. We can and work with instruments that humans already can use.

And most importantly, we truly have intelligent robotics. This is not just lab automation, where you program things and they do it exactly like you tell it to do. This is actually physical AI autonomy that is intelligent, that's constantly sensing, making corrections. And more importantly, we also have an AI scientist that can actually reason about the science itself. So what is an example in the

the lab where you actually do want some probabilistic reasoning or some stochastic result as opposed to something deterministic because if I'm if I'm vibe coding a website like I don't want it to guess what an HTML tag is I wanted to just use a div every time it does a great job at that but so I imagine there's some things where you know the pipette always needs to go in the same place so it's okay to stand on the shoulders of giants and puppeteer that where does the variability come in Definitely. I think like if you think about the best scientist, right? The best scientists are the ones who are reading all the papers. They have all the scientific knowledge, but they're also the ones going into lab and running the experiments. They can like sense what's happening. They can smell it. They can like visualize what's going on and they can make changes as they see things start happening inside the experiments. That's what we're trying to capture, right? The ability to be really flexible. to actually reason about the science as it is happening. And also taking into account all of the knowledge that's come before us,

all the scientific papers, all the different results, all the past experiments you run. That's actually what enables good science. So tell me about the distribution business model. I could imagine a world where you're basically doing drug discovery, going through the FDA process at the same time, you could sort of sell a lab in a box to a pharmaceutical company. There's a lot of different ways I could see this taking shape.

Where do you think this goes? Yeah, we are building the infrastructure layer. We want to be the TSM for drug discovery. So we are partnering closely with pharma companies biotech such as Genentech, where we are, they can either work with us by using our system, our physical AI scientists in their own lab, or we're actually about to open our our own lab, our own fully autonomous lab, one of the largest autonomous lab in the United States in in 2026. Talk to us about the fundraising. I think we missed you on the day you announced your series A,

but I still want to ring the gong. What happened? Who's in? How much did you raise? Yeah, we raised $52 million for series a day. Yeah, Scott. Thank you. Amazing. Who did you raise it from? Yeah, human capital led. They came in and precede and seed and they tripled down on us for Series A really preempted the raise. We also have Lux, who is also a repeat investor, also Menlo Ventures, Catalia, great investors, joining in for a very ambitious mission and very ambitious journey of eradicating disease. And 52 million Series A, that feels like a lot of money.

Congratulations, but I could imagine spending it on a training run for a foundation, model or buying a bunch of robots like that stuff behind you doesn't look too cheap where do you see the money going what does it unlock well actually the hardware that we use at medra is all off the shelf um robots right now especially their hardware is fairly commoditized and we use this off-the-shelf hardware so we can build AI on top of it so we can actually reason about the science and actually be able to use our uh what we have trained ourselves which is the vision language lab action model to be able to autonomously run experiments. And a lot of what we have raised our series A for is actually to open our own lab right in San Francisco

to be able to scale up data generation. Because ultimately, what we want to do is to be a data foundry for life sciences, to be like a mercure or research, but for biological and life science and chemical chemistry data. So that our partners can train foundation models in biology. Yeah, because there's probably not a lot of really clean data out there on GitHub or out on the open internet.

And so you have to sort of generate it yourself. Is that generally correct? That's right. That's right. I mean, if you think about in biology, like the largest biology foundation models are still about three orders of magnitude, trying out three orders of magnitude less data than like,

you know, even like 01. Yeah, yeah. Yeah, I think Google launched one that was, showed really impressive results and the scaling laws were there, but it was much smaller than what you see elsewhere. So yeah, very interesting. Very same.

Jordy, anything else? No, this is super exciting. Congratulations. And I'm sure we'll have you back on the show soon. Have a great rest of your day. Great to me, Imshel. We'll talk to you soon. Let me tell you about Shopify.

Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents. And we got a little bit of time, I think. We do, that's great. Our next one. Well, then I'll tell people about the New York Stock Exchange.

Want to change the world. Raise Capital at the New York Stock Exchange. And let's pull up this post from Gucci. Gucci. What did Gucci do? Not the kind of account we pull up every day. They say primavera, February 27, 2 PM, CET, and this picture is created with AI. They hit this, they drop this on Maine, and the photo looks.

I've not seen any hallucinations. It looks complete. It looks quite dialed. It looks like it could have been. out of a catalog, any catalog over the last 20 years. I'm sure it's a really peaceful over there at the Gucci offices now. Yeah, I'm sure. I'm sure this wasn't controversial at all.

But they're going. This is, this does feel like a more tasteful dipping your toe in the AI boom than say the Svadka ad, where everyone was kind of like, this just, it's not polished enough. It's still in the uncanny valley. And I feel like we're gonna go through the same thing as CGI, where like there are some terrible movies out there that are CGI based.

There's this one that takes place in like Greek mythology that's like notoriously terrible. There's one with the rock and Scorpion King where he comes out and like it's very clear that they just didn't give the 3D artists long enough to make it look good. And so it just like looks really awkward. Like this shit, didn't age well.

But then some CGI from like the original Star Wars in 1979, you see the green screens and you're like, wow, that stuff. still looks amazing, it holds up. And so you gotta know when, when to actually go in, dip your toe in. There's been another turn of events in the Warner Brothers Takeover.

Have you seen this on Kalshi? It's been going back and forth, neck and neck. Now Paramount is in the lead, 54% chance that Netflix takes over, or that Paramount takes over Warner Brothers. Netflix is at 36%. And I believe the final offers need to be, the final offers need to be submitted

by tonight or tomorrow night, I forget exactly, but Warner, Paramount's revised offer for Warner Brothers will likely come in at $32 per share. Let's pull up this video. Ted Sarandos having a chat. While we pull that up, let me tell you about Century. Century shows developers, what's broken and helps them fix it fast. That's why 150,000 organizations use to keep their apps working. And let's go over to deadline. I like you. You asked that question. We've been working hard on this transaction to acquire Warner Brothers and HBO, and we're deep in that deal every day.

Would you prevail? Yes, absolutely. There's no reason for not to. Right now, our deal is the best deal. It was determined by the Warner Brothers board. It was reiterated to suggest it to their shareholders who were going to vote on March 20th. and that there's no rational reason to block the deal. It is, you know, we're 9% market share growing to 10,

so there's really no concentration risk in our deal. And what's exciting, I think, is we'll be able to have this 100-year legacy of great storytelling. Finally, in the hands of the company for the balance sheet to celebrate it and to make sure and invest in it and grow it. Surrenders.

The Trump language kind of comes, it works its way in, because you're hanging out with your frown. you start doing some Trump impressions and then it just comes out it just comes out sometimes it's just one of the greatest impressions ever so you just got to do it every once in a while the year before the year before it's going to look like that next year in the year after in the year after the year after the year after it's going the greatest acquisition that the world is ever seen traditional 45-day windows theatrical exclusivity you should be like didn't you read the satrini piece everything's going to zero does it matter

Does it matter of two companies that are zero combined? No, just let it happen. So we're excited to be in there. We want to help them win. He's lapel maxing. They've opened nine number one films in a row. That's amazing. That's the kind of track record. We're excited about it. All right, we can pause it. Over the weekend, there is some new reporting from Bloomberg, the Justice Department's investigation of Netflix's proposed takeover. Warner Brothers includes a scrutiny of whether the streaming giant's behavior wields anti-competitive leverage over creators. He talked about it going from 9 to 10% market share

streaming. But the issue is it's taking the buyers from like a handful of buyers down to one. It's more real. And I hadn't considered that. Well, and that's what we were talking about with Ashley Vance. Hey, you sell documentaries. Yeah. You're excited to have one less buyer. Literally no one to play offers against each other. Just kind of here's the price, take it or leave it. Yeah. Well, Netflix for a while has had co-CEOs. Maybe you can mommy-daddy them. Go to one. Oh, the other one said he was going to buy it for $500 million.

He's like, he didn't say that. I just texting with him. What do you want to say, Tyler? At some point, the big labs are going to be buying these documentaries, right? If you have very high-quality training data, you can sell straight to Open AI. Sure, sure. Yeah, that makes sense. Yeah.

I mean, honestly, like a SORA deal wouldn't be out of the question for Warner Brothers. I wonder if the Disney deal is exclusive in that they will not be on another AI generation app, but is it exclusive the other way in the sense that Sora will not add Superman or Batman, and they will only have Spider-Man? Because it does feel like never the two shall meet, like we're not going to see Captain America and Superman fighting and anything other than a Chinese model that's getting a cease and desist. But in theory, SORA could go and do a deal with Warner Brothers in addition to Disney, but that might have been stipulated as like, no, we want to be the exclusive provider of superheroes. We don't want anyone to out-slop us.

Yes. Let me tell you about Railway. Railway is the all-in-one intelligent cloud provider. Use your favorite agent to deploy web apps, servers, databases, and more while Railway to automatically takes care of scaling, monitoring, and security. So I get you off. I think it's going to be a big moment when Disney IP. Oh, yes. But also when this concludes, I mean, it's going to be, it is neck and neck, as we've seen in the Kalshi chart. And then also it's, it's, there's a lot at stake, like the breakup fees and the billions, I think.

Like, it's a, you know, political story. There's so many different things going on. Well, anyway, I think it's time. Well, while we bring him in, let me tell you about cognition. They're the makers of Devon, the AI Software Engineer. Crush your backlog with your personal AI engineering team. Come on to the TB pin Ultrodome. Mike, good to meet you.

How you doing? While he's sitting down, let me tell you about vibe.co. We're D2C brands, B2B startups, and AI companies advertise on streaming TV, pick channels, target audiences, and measure sales just like what's going on. How you doing? What's up, gentlemen? What's up? Please introduce yourself first time on the show.

Sure. first time on the show. Happy to be here. A long time watching. Nice hat. Thank you. Thank you. Thank you. We actually talking earlier. Oh, yeah. How long have you been watching the show? And you're like, I can't remember the hotel room, but I remember the printed tweets. Oh, yeah. I was like that long. We have a lot of paper today. We always stack up a ton of papers on Monday because we get the weekend edition and the Monday edition. And then we print some other stuff. We got to bring back the printed tweet for like the best tweet of the day. But honestly, the printer was like a major rate block rate limiter for us like because we'd be like we're going live and and we used to

just like start the show around 11 we'd be like uh we're 30 minutes late you know because we would just do RSS now that we're live at 11 it's like the printer's got to work and we were print like hundreds of pages yeah because we'd be printing whole article anyway sorry I introduced I interrupted your no no no worries uh so Mike and unziata founder and managing partner at also capital and we're early stage HardTech Fund, investigating inception, pre-seed seed. Yeah. How did you get into VC?

How did I get into VC? Had a bit of an interesting path, a little bit non-traditional. Stanford? Stanford. Yeah, Stanford. Did you actually go to Stanford? No. Okay.

I started at Harker, and then that was good. Okay. No, no, no. So I've been doing venture for a little bit more than a decade, but actually... Overnight success. Overnight success. So a little bit more than a decade. I started my went to Cornell for undergrad which is still Ivy League

so I got him you got you guys you're right exactly have you ever heard of it though yeah I yeah yeah yeah yeah corner undergrad did the family office thing for a few years actually worked at the Cornell endowment so I've been an LP so I've been on that side of the table and then business school and then started a hard tech company back in 2016 okay okay so founder yeah founder yeah you know same same year andrell started cool um we're worth a fraction less than six billion right now but you know what were you doing uh we're doing food technology development so okay oh cool around the same time you're doing soil and John so I'm sure we're doing food manufacturing technology

kind of from scratch me to co-founder in a lab through series B companies still going built out a big facility so I've been doing our tech manufacturing yeah for quite a quite a bit um to give us a history of also then history of also so you know it's funny also started as Will Brewery Mike and Enzziata and Colin Smith's backyard angel investing adventure adventure in 2019. So- He was on the show on Friday.

Yeah, he was on the show on Friday. I saw it. So I did Dorman Fund when I was in business school. So I've been a DRF partner for a number of years, non-alum, started writing angel checks in 2019, kind of scaled up through SPVs, and then raised our first fund in 2023. So that was a $22 million fund. And through that journey, you know, we wrote the first check into Radiant Nuclear. You know, Varda followed shortly after that, and I've been on the board of Varta since inception.

Yeah, we did K2 as a year. Yeah, we did K2 at Seed as well. Any Signal and a software-dhine radios. We raised our first fund in 23 that I mentioned and then wrote the first check into Northwood. So it's been a bunch of- Was that post-ZERP ending the crash? Yeah, so it was post-ZERP, you know,

kind of hard time to raise a fund one as a new manager. But you're not saying, I'm just gonna go into crypto and like the frothy stuff, you're in the stuff that's on in the next boom. Well, you know, I think, well, you should talk a lot more about this, But I think, you know, our thing from the beginning is, you know, who are smartest friends and how do you believe in them before others do. And then I think the hardtick thing candidly grew outside of that, a group from that. When, how many checks had you written into gondo companies or gondo adjacent companies before John went?

Oh, yeah. Put it on the map with that video. Yeah, I don't know. We did like six or seven before the gondo bus and your thing. So the pre-bus and bus. Yeah. The bus is really the defining line. You know, VC, it's freebuss.

Yes, I mean, we did a bunch of it. We did Varda, Radiant, K2, any signal, that kind of crew of folks. And then since then did Northwood first check there. You guys had mesh on the show. We did that one recently as well. No way. Basically, every company. Yeah.

So we've been very fortunate. They let like the non-engineer guy somehow cosplay as an engineer VC, which is a lot of fun sometimes. but I'm not afraid to make myself look silly every once in a while to try to learn something new. So what is your non-technical, so what is your process for underwriting some of these companies where at Precede, they can often actually seem like a science project. And that's like the, I've probably made that mistake once or twice across 60-some vets where I invest. You know, I'm not a professional investor, but accidentally invest in a science project.

that was being positioned as like a commercial opportunity, but the ones you listed off, you know, started as kind of like far out ideas and now have very real commercial opportunities. Yeah. Look, I think the unique lens that I kind of bring to this fact that I ran a company doing hard tech stuff for seven years across, you know, engineering, built the whole team, kind of know what a good engineer sounds like and how they execute, you know, product, go-to-market operations, all that vertically integrated.

We, for the most part, are investing in people that have done these kinds of things before. And if you look, by example, the Varda team, a lot of those guys are doing Dragon at SpaceX, right? They miniaturized it and turned it into Winnebago. If you look at the mesh optical team, they're doing lasers at SpaceX, they're doing lasers now. If you look at any signal, right, doing radios, a lot of the Northwood team, you know, doing ground stations, right? They're doing the thing they were doing before, but with a different market opportunity.

So the common thread is like, these are serious people building serious companies, and that's, you can kind of see that once you've lived it for 70, you're, you're years is you know I didn't you know it's great that more people are coming in and wanting to be excited about investing in this category putting more capital to work in the category I think marking you out need that exactly I'm really excited about it yeah broader yeah exactly Valley community you're coming in and mark me up five times ten times sure yeah I got an on cap note for you if you're if you're really excited about one of these things it was in the cover of

the Walser Journal business and finance section today investors go heavy on AI immune assets explain to us what Halo is, what it stands for or what it means? Yes, so heavy assets, low obsolescence, which is a term that I just learned a week or so ago. So thank you, J.P. Morgan, are they a sponsor yet? Not yet.

Do we want them to be? Depends on what the product is. We love J.P.M. We love JPMorgan. Yeah, I think this heavy assets, low obsolescence is these things that are very difficult to replicate. You build a chemical plant or you build an aerospace production capacity,

capacity, these kinds of things are much more resilient than your traditional B2B SaaS product that may be able to be replicated by cloud code, for example, or open claw, something like that. This was Delian's bit when we had them on for the slop versus steel debate. Debating of, you know, what would be, yeah, it was a pay-per-view. What would be most resilient? But unpack that a little bit, because heavy assets, high assets, What does that actually mean in the defense tech context? Because there still is a lot of R&D that's happening.

And then low obsolescence, I want to know more about the curve of what can be obsolesed. Because there are some companies when I think about like, you know, a lot of people have been saying like, oh, like buy raw materials, like go long gold. And it's like that is fungible. So there's no real moat there. If you just own some gold, you just, it's a commodity. How do you think about non-commodity, non-commodity products? So two things. Like, any great venture business at the core is a company that has the potential to generate high return on capital in the long term.

Like, you have to account for the assets that it takes to generate the revenue, and then how durable is the revenue over the long term. That can come from Dow Chemical, which has just such massive scale that is very difficult to replicate that scale, and they have a very durable business, low obsolescence. We're not going to remake all those chemical plants. Or it could come from something like a radiate nuclear who is building very complex nuclear reactors in a shipping container equivalent and They're going to scale up not just the design of that but the manufacturing the supply chain the regulatory And that gets to the second piece that we always talk about which is we love companies that are novel in the aggregate Right we're not looking to your point on how do you underwrite a science or engineering Jordie? It's like it's not one specific thing we're trying to understand It's what are the 32 things that have to come together. Why is this the right moment right now?

for this thing to happen. And if it does, now all of a sudden we've got a moat. Because it's not impossible for somebody else to get a reentry capsule like a Varda. Right? It's not impossible for somebody to build ground stations like in Northwood. But the dynamism of these companies

is in the ability to execute and move with speed and integrate these complex systems that become low ass, absolescence, but they are heavy asset. Yeah, it's like the factory is the product. I've always heard that thrown around. It's like, and I always read it as like, the real challenge is manufacturing at scale,

But I think there's another cut on the factory as the product, which is probably something like, like you actually would be very reticent to invest in a hard tech company like Varda. If they were like, yeah, we have a third party manufacturer that produces the capsules. We just send them a CAD file. Yeah, I think it really depends, right? Like I love the, I love the theory behind the factories of the product, but I also think there's some pretty strong, you know, strategy that that needs to be built on. you know, why should we build a factory?

And if you look, SpaceX is a good canonical example of this. Why should they build a factory? It was because they were creating a lot of the demand at the same time as they were trying to deliver it at a given unit price to unlock a bigger economic opportunity. And there was no third party even available. Yep. So they had to do it themselves.

So they couldn't meet a spec. So they had to do it themselves. And I think that's the different dynamic where you should not, and I post about this a lot because it definitely is a thing I believe pretty strongly. You should not vertically integrate just for vertical integration's sake. Yeah. No car.

It's a poor use of capital to take a bunch of equity and shove it into a commodity machine, which you could not do, for example. But if you look at like a VARTA, for example, Cadence is everything for that business. So if cadence is everything, you've got to be able to turn fast. So they have a lot of capabilities they've built in-house to be able to do that. Same kind of thing with the Northwood, right? In-house, as much as they possibly can because they have to turn fast to move with speed. Speed's really the advantage, but it is built on a foundation of the ability to deliver at rate.

And that's kind of the core. When you say factories the product, I agree with that. But where are you pointing that advantage? Where are you pointing that? Because it is an investment that you're making as a company. And it's something that even in day zero investments, like all of our stuff is pretty much inception, precede. We're thinking like, if you're gonna build a factory

in three years, you need to be thinking about it now. So why are you building that factory? Why are you doing that? Like what competitive advantages give you? And I think that's how, you know, the people that we backed have really had a good sound, like head on their shoulders of how to think about those tradeoffs

of my build decisions. How did you react to the general intelligence crisis of 2028, the viral essay that nuked the markets. I saw this guy, John Lober, had a pretty kind of a response to it, breaking it down. He was in some part saying, like, institutions have a lot of momentum. They can carry that momentum and adapt to these new market forces. He also suggested that reindustrialization could, it seems obvious that if a lot of our jobs can be just automated with a computer. Maybe they weren't that real in the first place,

but there's a lot of work that needs to be done in the physical world. There's America needs to figure out how to make stuff again, not just kind of push paper around. And so are you optimistic that this could shift talent from, you know, making the 50th, like vertical CRM to making stuff? Do you think this could be a... Look, like, I'll say this. I don't think we need to send our boys back to the coal mines.

The children... You're in for the mines. The children. No, just kidding. You know, my kids, if you're watching, which I think you are. Yeah. Get off my... Get off my...

It's light blue collars. Yeah, it's... Well, I think it's, you know, what are we doing next, right? So if you go back to horse and carriage, right, it's, hey, Ford has a job for you on the production line. Like, go learn how to do that. And I think the opportunity is in the companies that develop recurring education, rework as processes or capabilities as part of their normal operating cadence. So a lot of our best companies, they will get seed funded and they will immediately start an internship

program. And that internship program will become a funnel for new talent to come in after they graduate. For example, and I think institutionalizing that around these companies that are moving fast in new areas, whether it's lasers or nuclear or space, right? I think we could bring back that retraining, but inside the corporate entity, as it's the responsibility of the corporation is really our company's problem,

that there's a talent shortage, so we should take that on. He had someone who was working basically a blue-collar job and just wanted to get like a forklift certification, and he brought him on, and then pretty quickly he was like writing CAM, CAD automation software, computer-aided. manufacturing and like sort of became a cam programmer like almost and that was like a lot longer path a long time ago and so the upskilling thing is definitely real at these companies look I think the

we could get into like this whole different thing around like the student debt crisis is definitely a big bottleneck to people being able to do this upskilling oh sure where they may be constrained financially that they just have to kind of keep keep working to be able to make their student debt payments for example so I think that's a big thing that people yeah I was I was I was having a conversation with Tyler, we've had a number of interns, all of which have been always paid, but I was thinking if I didn't have the opportunity to just work for free for people in college, where at the time I was like working a job at a hotel, like grinding, but then in my free time, I didn't have a lot of skills. And so I would just tell entrepreneurs

like, hey, let me just pick up little things to do and ultimately learned a number of things that allowed me to start my first business and all that stuff. And going back, it is, you know, It feels like the sort of like unpaid intern is like completely like no-go now. Like it's a negative signal if a company is doing it. But it might have to come back. And it actually, if people really want it, it's like, yeah, you can work a job that is very low-skill so that and then spend all the rest of your time like reskilling yourself. Yeah.

I don't know. I think it might have to come back, although I'm sure there's a million reasons why somebody would hate that idea. Yeah. Look, I think it's just really important. So one of the things that's most inspiring to me about this moment in time

is it feels like not only are there are people spinning off of like the SpaceX's of the world that are now continued to take on really big challenges, they're doing two things. They're doing things that are really meaningful that when you get at the root of them and there's an authentic drive behind a lot of what they're doing,

but they're also willing to tell the stories that inspire other people to be better. If you look at Jared Isaacman coming as NASA administrator, he is an inspiring human being. Right? That I think we need more people like a Jared who's 30, 40 years old, whatever it is, like young person's a vision for the future, he's been to space.

He's been to space. He's processed payments. Every time I get a shift, shift payment, check out, I just go. Yeah. Talk about debt. What is a reasonable debt low? for a series A hard tech company.

Yeah. In software, venture debt is seen as cancer. Like you do not want to go near it with a 10-foot pole. Paul Graham said it blows up companies left and right. It's very scary. Yeah. I think a lot of entrepreneurs over time, they get comfortable, they learn how to use it effectively, but then it's always just like,

well, I have this money sloshing around anyway. It's all one big pool. It's not like the dollars get allocated one place or another. How are you talking to founders in your portfolio about debt? Yeah. Like I could get hyper-technical about this, but I won't for this audience. No, get technical. Get technical.

Get hyper-technical. The right amount of debt at Series A is zero. Okay. The right way to use debt in companies is in two places. Says the guy who sells equity. Says the guy who sells equity. He's like, no one should ever read that debt. Just come to me for another check.

Come to pop up. At the right time and the right place, it makes a lot of sense. When does it make sense? When does it start to? You can take me out to series D. I don't care. But where, for sure.

Because there are a lot of companies that we've talked to where it's hard tech, and they wind up buying a ton of machines in a big warehouse. And it just feels like the liability side of the business is very different than a couple programmers in a bedroom or in a garage, right? Yeah. So in a past life, when I mentioned,

I worked at the Cornell Endowment. I also got my CFA while I was there. And then went and got my. NBA. So probably, such a non-traditional background. How did you wind up in finance with just a CFA and an MBA? Yeah. But, you know, Revenge of the Balance Sheets is kind of what I have about what we're investing in now. Okay. But look, I think you're using debt for a couple situations. Number one, to buy long-lived assets. Yep. But the caveat is they need to be tied to actual contracts. Okay. That will be pushing out real revenue and cash flow. Yeah.

If you are buying, if you are using debt to speculably invest in capacity, you are taking a lot of existential risk into the business until you have contracted revenue that has significant bookings and backlog. All right. So if you've got two years of backlog and you want to take on, you know, an interest rate of 7% while your equity is 30% and you think you can get to a revenue milestone that blows out your equity multiple, that's actually a really good use, right? Or if you have, you know, there's a canonical example I always think of when I was working at the endowment,

we looked at a venture debt fund. And it was super interested, like 2015. This was 2015. And they had a very good use case of using venture debt. And they were lending to Pandora. And so for sharing. Just Pandora. Cheers to Pandora.

So they were lending. The music service, not the makeup place. Yeah, yes, exactly. Not the jeweler. The streaming service. They were lending to Pandora. And Pandora basically had like a cash flow timing issue where they needed to buy.

servers to be able to store the music and stream it and there would be revenue that would come off of the streams so the revenue would lag the cash investments in the servers sure but as they were growing streams their multiple on the revenue was growing oh interesting so you actually could use the venture debt to bridge to a higher revenue multiple when you went to raise more equity and reduce the cost of equity so even if you were paying 18% implied cost of equity IRA on the venture debt including the warrant it was still cheaper because the cost of equity was declining as you hit milestones.

So it was episodic use where you knew you could raise equity as you hit a specific milestone to pay it down. Or it was part of the permanent capital structure that was tied specifically to cash flow. The trap is when you use debt to try to extend runway. Yep. So even in that Pandora example, like maybe it's not an asset back loan, but it's like almost asset back because you are just taking the money and buying assets. Correct. That probably have some resale values.

And you know the revenue is going to come. And you know streams are going to go up. And then you'll be able to refinance it because equity investors say, you know, you're at 10 million streams. I need you to be at 15 million streams. And like, how do you get there? Well, at the time, like this was one way you could get there

and buy the fiscal asset. So I think understanding where did the slope change of your multiple effectively, like those inflection points or permanent capital. That's very cool. George, anything else? No, what founders in what categories do you want to meet? What founders and what categories?

Like what kinds of founders, not specific? What kinds of founders? Good question. Look, our big thing is founders that have fun. Have fun, but they play to win. We talk about that a lot. Like, have fun, play to win. There's like plenty of research that if you're having fun.

That's when you do your best work. You see that with the Varta team all the time. See that with the Varta team all the time. The thing Winnebago is funny. Yeah. Clearly they're having a good time. They did the LK99 thing. Yeah, totally.

Night side project. Very fun. Totally. Yeah, it's like, are you building these little cultural things that people have a good time? I think that's really, really important. But also the playing to win side, too, because I think you can over index on let's have too much fun and realize, like, hey, you're competing out here. So that's really what we're looking for is, you know it. You guys have a ton of fun here, right?

Like, I think this cultural vibe is definitely what we look for in founders, is that they having fun. That's how you kind of get to the hard stuff. Let's put the hard tech to work. Tell us about. Why don't you hit the gong? Yeah, you hit the gong. You hit the gong. All right.

Can tell us the announcement of 50 million? All right. Our second fund, 50 million. Woo. There we go. Go smash that. Thank you so much for coming on down to the TV P&LTRA down.

This is great. Have a good rest of your day. And we will talk to you soon. And lastly, but not least, I will tell you about Phantom Cash, fund your wallet without exchanges or middlemen, and spend with the Phantom card.

Mike really backed at least, 50% of the breakout hard tech companies of the last five years at the earliest stage. Really wild. I like this deep dive from Teo Berga who says reading a 2005 Paul Graham essay, Gasp. He used the forbidden sentence structure. And it says, writing doesn't just communicate ideas. It generates them in 2005. I think that it seems obvious that

this point that PG's blog and Sam's blog are both like deep in the training yeah core core to the to the anyways we got a bunch of timeline here let's let's rip let's rip through it take me through it what you chairlift capital says opening eye killing application software to then try to rebuild application software is the funniest timeline still opportunities in the We've got to have somebody on from McKinsey or one of these big consulting firms to hear how they're positioning it to customers. I think it's a deck. Moving on, where are we, Jim Kramer, underrated poster.

He this morning at 3.33 a.m. was outside. The guy doesn't sleep. The guy doesn't sleep. Saying cold, early, dot, dot, dot. I am not worried. Anthropic has a solution. I read it in a report. What? Vag post?

Incredible. I mean, yeah, of course, sent IBM down 11%. Going to work. Dolly Bali says, investors simultaneously think AI is overinvested and AI will take over industries. Yep. It's a funny moment right now. This last one.

SAS is dead. OpenClaw replaced all my subscriptions. I went from $480 a month on tools to $1,2,244.4.4.4. $45 a month on API costs and 15 hours a week fixing YAML files. Adaptor be left behind. Hope's revenge says, woke up to Claudebot running its claw through my wife's hair. I had explicitly asked it not to do that. Stop, stop, stop.

There was a, there was a post about some meta researcher, alignment researcher, got all of her emails deleted by OpenClaw or something. Yeah, that was. That feels like a crazy thing to. I think she needed to stress that my sense is that she like set up a new device with a new email. Yeah. It was not just like running OpenClaught on her main meta email, but I think people read it. Yeah.

Yeah. On her main account, which seems crazy. People were saying like, oh, it's bearish. Like she's literally an alignment researcher. It's like, I actually might make her better at her job, though. Well, she was at scale too before. It wasn't like in, you know, in the less wrong, like, grinding through, like, EA stuff. Yeah, an EA would never be caught getting their emails deleted. No way. Just all of less wrong gets deleted by open call by accident.

Palantir is launching Valley Forge Grants, $10,000 awards for high schoolers to solve the problem that most inspires them using our software. Ditch, the coffee runs, and fake intern projects. Whoa, shots fire at Tyler. Claude with ads was incredibly real. We'll pay you up front. Uh, We'll pay you to confront the challenge you care most about. At Valley Forge, Washington soldiers endured a brutal winner, turned the tide, and won the revolution. Their fortitude has carried America to its 250th birthday. We're looking for pioneers to lead America to its 500th. I like the sound of that.

Very, very cool opportunity. Based on our audience data, we have very, very few high school students in the audience. But you're listening to this. Go apply. Feel free to DM us if you do apply and we will try to Nudge what happened with this F1 race someone smashed someone crashed yeah who in the chat was actually at this demo because San Francisco I've never seen San Francisco go this extreme. Let's pull up this video first of the truck actually jumping over one of the hills John. I want you to see this. Okay, let's play this. Wow This is San Francisco.

This is the best part. This is the best part about San Francisco. They close down roads for crazy stuff all the time. There's beta breakers. Halloween is a whole scene. There's a million other events that happened throughout San Francisco. Honestly, I used to do something like that with my clutch when I would be driving my manual. Jumping over an F1 car.

Wow. I used to. Driving manual as a high schooler in San Francisco made me into a man. Yeah. You're really facing death on every hill. And then let's pull up this, one of the cars did a burnout. People were thinking this was Yuki Sonoda, but apparently it was one of the other drivers.

This is the Red Bull? Wait, why is it on fire? At one point it caught on fire. I thought it just had some minor bumper damage. This was a wild, this was a wild demo. I think, I think, Oracle and Red Bull really wanted to make a statement. We're spinning around here, okay, and then they go forward and smash into the wall. Like, that feels like the easiest crash to prevent.

When I was watching this, I was like, while you're spinning around, that's the point where you're going to go crazy. But then it's just smoothly going forward and smashing. Front wing. No brakes. No brakes. No brakes. And then at another point, the car caught on fire. 10 out of 10 demo.

Red Bull knows how to entertain. They know how to entertain. Like, they... Yeah, this was on purpose. Actually, in the Apple Vision Pro update, I watched a Red Bull video in immersive video. It was a skier video about 15 minutes, and they take you backcountry skiing, heli skiing, with these skiers, and they have the Applevision Pro thing. And it is amazing.

It's like one of the greatest experiences. Because realistically, I'm never actually going to go heli skiing, backcountry alone. But this like just you feel the scale and everything. It's so good. I called you at like 10 or 1030 on Friday. You up? Yeah, no. I didn't even call you. I just said it, you up, question mark. And John sends me back a picture of him in a selfie in the Apple Vision Pro. You know you're you were probably the only active user. Yeah. Well, you know what? I use I got a Mac Mini hooked up to my Apple Vision Pro now. Because I got an I got a I got a capture card that can take in an HDMI input. So I hooked the PS5 up to the Mac Mini and then mirror that to the Apple Vision Pro so I can play PSS.

in Apple Vision Pro with way too much latency and it actually doesn't work well at all. But it was a fun experiment and an obvious feature that they should have launched two years ago, but they didn't figure out how to do it. Just put the HDMI cable on the actual power brick and just let you plug in anything and you'd have a massive audience of people that just want to play all sorts of stuff that's HTML. Anyway, very, very now. If you are in the market for a Western

sort of vintage Gulfstream. Greg's got you covered. It's a 1994 Gulfstream GIVSP. The latest ask was only 3.75 million. This is beautiful. We don't know how to make jets like this anymore.

Everything about this is amazing. It's so good, so opinionated. Look at the bathroom. I love it. The bathroom, they went full of Crazy steampunk, yeah. Yeah, Star Wars mode.

Yeah. Cantina. Yeah. Should we watch this latest video from Sea Dance? Let's do it. It starts by saying, Hollywood is cooked. Hollywood is cooked based on the new Seedance AI video model. It's showing Transformers.

But let's actually track what's going on here. Starts out as a jet, a combat aircraft. He gets out of the jet. Turns in around. Now it's a transformer. Okay. When he gets in another cockpit, now it's a helicopter. And it has a gun on it, okay?

He's shooting it, that's useful. You need to be in helicopter mode, but now you gotta get back in the transformer again. So he gets back in the transformer. Oh, turns out the transformer can run like a human and walk, but it turns back into a plane. Back into a plane. Then what do you wanna do when you're a plane?

You wanna land on the freeway, on the highway, on the street. You land, you get back out, then you get back into your transformer to get in the front cockpit. highly realistic. And now you're back in human mode, humanoid mode, and then you blast off. You would not be criticizing this. And then you turn into a plane and you fly backwards.

John, if this was an actual scene in Transformers, you would just be watching it being like, that's tight. Okay. So I agree. I would be saying that's tight. And it is incredible visual fidelity, incredible visual fidelity and just an amazing video and entertaining to watch. And that's why four million people enjoy.

it and it only has one community note and the community note is just AI slop engagement farm. Yeah, obviously this is not cooking Hollywood today. It's a tool, it's cool, but really impressive considering that this truly is the most expensive shot you can do in Hollywood. Like it is so, so complicated to animate all of those different rigid bodies as they interact with each other and they don't and they tuck inside. It's so difficult. It's the Mount Everest of motion graphics and CGI. Tyler could do it if we get 10 minutes, but I see your point. And the

last and the final step in any of these, like you can actually go and animate the rigid bodies in Cinema 40 or Houdini or something, rig all this up. But the final texturing, the color grading, blending everything in, that's another major step. And it just nails all of this. The lens flares, the reflections on the glass, all of that's like another step. Because you create the jet, and then it just looks like, you know, a 3D render of a jet. So you have to blend it in, you have to make sure the colors match, make sure it matches the background.

This stuff is so time consuming. And having a tool that at least allows you to do some previs, animate and interpolate, do a bunch of different things. Obviously it would require a lot more art direction to get that to a place where it's amazing and it makes sense because a lot of the, A lot of the CGI that happens in transformers, I know some of the transformers clips are silly,

but a lot of it's very motivated. Like it shows you how things move in it, there's a decision driving one transformation to another. It's not just randomly switching from a plane to a car to a plane and back and forth. And it's usually meant for like dramatic weight and there's some weight and timing and there's art direction that sits on top

of the actual CGI. Anyway. Apparently open claw fueled ordering, Frenzy creates Apple Mac shortage. Delivery for high unified memory units now ranges from six days to six weeks. I called it. It's happening. I did call it.

You did. We did the math a couple weeks ago. And it seemed obvious that if the frenzy kept up, there would eventually be some shortages. I mean, demand for AI is continuing unabated. People are using this stuff. Martin Screlli shared the NVIDIA demand check on Lambda. Lots of things are out of capacity right now. People are using stuff.

If you need to hop on Lambda, hit us up, and we'll introduce you. But people were pretty triggered by Gary Tan and the YC crew jumping on a podcast dresses, lobsters. And I was triggered by people's reaction to it because we have done similar gesture maxing many, many times. I think they were just having, they were just having a little fun. I don't have fun. but apparently fun fun is illegal but is illegal hunter wise you have to pack it up we got it we got to

talk about our secret plan oh yeah we're leaving how we're leaving california not because of any taxes those don't apply to us but um because there is an entire main village with a church in multiple homes that's on the market for six million dollars and we're going to move everyone there i'm hearing some claps i think people are in they're down we're going to build up the whole crew. It's a 40-acre village and it was first listed for 5.5 million. You get the whole town. What actually qualifies as a village though? Well, it has 21 structures, 21 structures and this is where it gets funny. So we were saying let's move the whole team there. There's 21 structures. We're a small team. We got like 10 people. That's enough. There's not 21 houses,

George there's 21 structures so it's entirely likely that Tyler over there will have to live in a barn or shed or perhaps the church fitting in the stable but other properties found on you on the unique compound included Greek Revival style Dwelling antique barns and multi-bay garages would you go if you had just had to stay in a multi-bay garage you can sleep in a Gt3RS you can also sleep in a multi-bay garage if you get some cloned horses clone ponies let's do it everything a homeowner needs to build their own thriving community or set up one-of-a-kind rental venue. Very fun option if you have a need for 21 structures. Head over to Maine and pick this up.

Hunter Weiss shares one of the best product ads ever. I agree. It's the I run, the iPod shuffle. We don't know how to make ads like this anymore. Really good. Simple. Really, really, tells you exactly what's going to do, run around. Really, really, really good. Bring it back. Will DePue says, whoever builds Gmail app shirt, search should be burned at the stake. Every time I use this app, I want a KMS. He searched proof. 75 likes. Proof of insurance.

And it's just pulling up a bunch of Delta Airlines receipts. This is actually extremely annoying. I don't know how the search got so fuzzy, but you can search for exactly the term. And it'll just be like, there's this one cookie that's buried in white text that sort of matches it. And it just shows it to you. They got to do something here. I think it's a big app, so there's probably some overhead to fully rewriting this.

But search is tough, search is hard, even in the AI apps. I find that they generate so much text now that if I search for one keyword and I have it in my mind, it's like, well, that word came up the last 50 chats. Like, it comes up all the time. And so it's been very hard, but I do think, I do think it'll get better, but certainly an opportunity.

Dylan Field was having a little fun. He says, nothing to see here. Sometimes the chairwoman of the task force on the declassification of federal secrets just likes posting pretty pictures. Please continue talking about the Olympics. And Anna Luna sharing an image of what looks like a wormhole. And just vague posting now. We got Congresswoman vague posting.

Now, I love it. I love it. Let's keep it up. You got a vague post everyone so long. A bone. Any other big post to go through? Last one says, my culture is not your costume, Brian Johnson. Because Brian said he decided to live life on Friday.

He was spotted. Just playing some video games, having some Taco Bell, some pizza, some Dr. Pepper, having a lot of fun looking, not his, not his usual self, but locked in on the big game or something like that. Okay. Plant the bomb. I have some water. words of inspiration for the listeners.

Wait, no, we have to, we have to say this last one. That's my words of inspiration after you play. No, and then I actually have a few more last one. Okay, read this one off. Let's see here. Excuse me. Neil Renick says, everyone you meet is fighting a battle you know nothing about.

Send them a team's meeting link and finish them off. I love it. Last thing we'll cover today. Anthropic posted earlier, we've identified industrial scale distillation attacks on our models by deep seek moonshot and mini max. Wow. These labs created over 24,000 fraudulent accounts and generated over 16 million exchanges with Claude extracting its capabilities to train and improve their own models.

People were having a lot of fun with this. They said, no crying in the copyright casino in all caps. Or Daniel, Luke brought up a vintage growing Daniel post. Oh, did someone take your hard work and use it to train a model to mimic your expert? without compensation. Oh, yeah. Pot-culling, middle-black, potentially. Another person says,

I can't believe someone would just steal from Anthropic like this. The millions of man-hours, Anthropics spent handwriting code, text, art, books, etc. To generate enough data for training must be taken into consideration here. Where is the respect for IP?

Wild. Fun times. And here's where we'll end. Neat says, reading one LinkedIn post is equivalent to unreading five books and that is a good time to remind you to leave us five stars yeah follow our LinkedIn we're on LinkedIn we're on LinkedIn we're posting regularly now we got a bunch of fun stuff little clips from the show rewritten little takeaways little things that are on our mind we really would appreciate a follow over on LinkedIn computer leave us five stars

make sure everyone in the audience has the best evening of their life and sign up for the tbPN newsletter at tbpn.com. Goodbye. Nice work, brothers. I'll see you on the next one.