🟠 YC Demo Day, Paul Graham Joins, Will AWS Buy TPUs From Google? | Harj Taggar, Paul Graham & Jessica Livingston, Richard Wang, Philip Ho, Ali Attar, Kurush Dubash & More

28:15Barron made interesting points about this in a recent blog post. When we see frontier models improving at various benchmarks, we should think not just of increased scale and clever ML research ideas, but billions of dollars spent paying PhDs, MDs, and other experts to write questions and provide example answers and reasoning targets. Let's give it up for the experts. These precise capabilities. In a way, this is like a large-scale reprise of the expert systems era, where instead of paying experts to directly program their thinking as code, They provide numerous examples of their reasoning and process formalized and tracked, and then we distill them into models through behavioral cloning.

28:55This has updated me slightly towards longer AI timelines since given we need such effort to design extremely high quality human trajectories and environments for frontier systems implies that they still lack the critical core of learning that an actual AGI must possess. This tension seems especially vivid in robotics. In some fundamental sense, robotics is an algorithms problem, not a hardware or data problem. With very little training, a human can learn how to tele-operate current hardware to do useful work. So if we had a human-like learner, robotics would in large part be solved. But the fact that we don't have such a learner makes it necessary to go out into thousands of different homes and factories and learn how to pick up dishes or fold laundry.

29:41One counter-argument I've heard from the take off within five years crew is that we have to do this clue GRL in service of building a superhuman AI researcher. And then the million copies of automated ILLIA can go figure out how to solve robust and efficient learning from experience. This gives the vibes of we're losing money on every sale, but we'll make it up in volume. This automated researcher is somehow going to figure out the algorithm for AGI, something humans have been banging their heads against for the better part of a century while not having the basic learning capabilities that children have?

30:16That seems super implausible to me. Besides, even if that's what you believe, it clearly doesn't describe how the labs are approaching RLVR. You don't need to pre-bake the consultant's skills at crafting PowerPoint slides in order to automate ILIA. So clearly, the lab's actions hint at a worldview where these models will continue to fare poorly at generalizing and on-the-job learning, thus making it necessary to build in the skills that they hope will be economically valuable beforehand. I want to go to the section on economic diffusion, but first I'm going to tell you about Privy. Privy makes it easy to build on crypto rail, securely spin up light-label wallets, signed transactions, integrate on-chain infrastructure, all through one simple API.

31:01So you've been asking about economic diffusion, what is the rate that we're diffusing. Let's see what Dwarkesh has to say about economic diffusion. He says that economic diffusion lag is cope for missing capabilities. And so this is also seems informed by the Tyler Cowen take that AGI is here. The models are good, but it just takes time to adopt them. And I'm very sympathetic to this because when I go to the doctor's office and they hand me a piece of paper, I know that a web form is good enough. Like the capabilities of the digital form are complete. It's not that the form is lacking in something or it's not reliable enough.

31:47It's not like, they're like, oh yes, like the website goes down 20 % of the time. And so paper makes more sense still in this case. It's like, no, it's just a diffusion problem. There's just someone who runs that doctor's office is like, I like doing it the old way, right? And that's the economic diffusion lag problem that I think is real in a lot of scenarios. But - The missing capabilities thing, I mean, just to give a pretty concrete example, right now, AI is great at generating text, right? It's great at kind of analyzing a piece of content and then generating text based on that. And yet we still have multiple people on the team at TBPN whose job is to find interesting moments of the show and then create captions around that and share it to x and instagram and youtube and other platforms and drorke shins too where he was trying to find the most interesting pieces of a full podcast uh with one big gemini prompt and he was trying all the different models and couldn't get it to actually find like the most salient and viral points yeah so one of the the the other thing that stands out is like one of the uh seeming missing capabilities is is like uh ability to like identify humor or even something like it's almost emotional so ilia and dwarkesh talked about this where i think ilia was giving the example of scientists studied people who had had various brain injuries that limited their ability to experience emotion yep and uh when you they took out emotion it took them it would it can take somebody two hours to figure out which pair of socks to choose yeah they were kind of like stunned And like, it's just a pair of socks.

33:25Like, you know, like, you know what's going on in your day. Why do you need emotion in order to make that kind of decision? And so it seems like at least in AI, a missing capability is like, okay, finding out like what's an interesting moment of a podcast in Varkesh's case, right? Is it something that makes the audience member feel something, right? I mean, there's just so much to pull through. Like I remember during the Carpathia interview, I was watching it and Tyler was watching it. And there's this moment where Carpathia says, like, the coding models are amazing and they're magical. But what they produce is slop.

34:01And it's like that word slop is so, it's like the word of the year or maybe the word of last year. Like it's a huge word. It has a huge amount of weight. Coming from him, it's crazy. It's crazy that rage bait beat out slop for the word of the year. Slop is probably the 2024 word of the year or something like that. But anyway, the point was like, when I heard that, when Tyler heard that word, Carpathic calling it slop, everyone was like, whoa. And I was like, we should clip that. And we looked and it had already been clipped by a human. Like someone on the timeline had also identified that it was like, that was the crazy moment that we should be like reacting to and taking in.

34:40Yeah, it's crazy. See, the other thing that's notable is like on WAP, one of the best, one of like the top jobs that people do on WAP or way they make their first dollar online is just like clipping for various content creators and media companies. And some of the clips that they make are so sloppy. Like it's literally just like a random segment of the show and they're blasting it out from like 20 different accounts. And the fact that we're still paying humans to do that still, I mean, it just feels notable. Yeah. Yeah. Well, let's read Dwarakash's take on economic diffusion lag being cope for missing capabilities.

35:18It says, sometimes... Copium would be a beautiful name for an AI chip, by the way. It would. It would. You got Tranium. Maybe they need Copium. Sometimes people will say that the reason that AIs aren't more widely deployed across firms and already providing lots of value outside of coding is that technology takes a long time to diffuse. Dworkash thinks this is cope. He says, people are using this cope to gloss over the fact that these models just lack the capabilities necessary for broad economic value. Stephen Burns has an excellent post on this and many other points. He says, new technologies take a long time to integrate into the economy.

35:58Well, ask yourself, how do highly skilled, experienced, and entrepreneurial immigrant humans manage to integrate into the economy immediately? Once you've answered that question, note that AGI will be able to do those things too. Dwarkesh says, if these models were actually like humans on a server, they'd diffuse incredibly quickly. In fact, they'd be so much easier to integrate and onboard than a normal human employee. They could read your entire Slack and drive in minutes and immediately distill all the skills that your other AI employees have. Plus, the hiring market is very much like a lemons market where it's hard to tell who the good people are beforehand and hiring someone bad is quite costly.

36:41This is a dynamic that you wouldn't have to worry about when you just want to spin up another instance of a vetted AGI model. For these reasons, I expect it's going to be much easier to diffuse AI labor into firms than it is to hire a person. And companies hire lots of people all the time. If the capabilities were actually at AGI level, people would be willing to spend trillions of dollars a year buying tokens, knowledge workers. Yeah, think about that. We hire someone, like we hire an AI or we're leveraging an AI, and they've listened to every single minute of TVPN ever and watched every clip.

37:15Yeah. And right now, you'd have to fine-tune that into the model or whatever. You don't just get that out of the gate. Yeah, and I'm just saying, like, we do end up hiring a lot of people that are, like, previously just listeners. Yeah. but getting somebody that knows every single moment that has ever happened on the show would be super powerful. But again, there's just like a missing capability set that doesn't allow agents to deliver a lot of value internally. The reason that lab revenues are four orders of magnitude off right now is that models are just nowhere near as capable as human knowledge workers.

37:51Yeah, I agree with that. The one thing that I don't necessarily agree with here, he says, Well, ask yourself this quote from Stephen Burns. How do highly skilled, experienced, and entrepreneurial immigrant humans manage to integrate into the economy immediately? I mean, they do sort of integrate into the economy immediately, but the immigration flow is a slow process. It doesn't just happen immediately. It's not just the amount of immigration went from zero to, I don't know, a million people or something. It's like people move around. There is a bit of a drag. But I understand what he's saying here.

38:26It does make sense. Anyway, let me tell you about public.com. Investing for those who take it seriously. They got multi-asset investing. They're trusted by millions. The Verge is trying to get in on the action, trying to attack David Sachs with a headline. It's so funny that the New York Times went after David Sachs and then The Verge was like, we want to go after him too. We want to get some of the hate. Wait, wait, wait. Let us cook. Let us cook. We heard everybody in tech hates this article. I do think. That's one that'll hate, too. Well, I don't agree with this journalistic approach. It is a pretty funny headline.

39:07Yeah. Oh, yeah. It's hilarious. The headline is Silicon Valley is rallying behind a guy who sucks. It's like, what does that mean? Just pure. Pure, like, qualitative, like, just name calling. they're just like, we don't like this guy. Pure ad hominem. But, you know, go off if your fans like it, if that's what your audience wants. It's rage bait. It's going to go hard. It already got a thousand likes on a linked article. The Verge is not putting up a thousand likes per link, so this is outperformance. And it's heavily paywalled. You cannot learn how David Sachs sucks without subscribing to that thing.

39:49They did a good job. You gotta pay. You gotta pay. know why he sucks uh i didn't you pay i don't know why he sucks but uh that'd be really funny if behind the paywall is like we're just kidding he's actually awesome we think the new york times missed on this one who knows uh paul graham yeah on the timeline he says a startup told me that one of their investors didn't like that they were selling to newly founded startups and wanted them to sell to bigger companies who have more money if investors tell you this write them off as idiots. Selling to startups is the best thing you can do. I'm sure many of the companies we're talking with today will be selling to other companies in the batch.

40:29A lot of people, a lot of people like say that's bad. They try to say like YC is a circular economy, but you have to ignore the hundreds of, you know, very real businesses that have, you know, been created through YC and gone on to work with every kind of company in the world. Yeah. Yeah. It certainly seems at this point, startups tend to be smarter, less bureaucratic, more representative to future trends. Like even if there's some sort of insular circular economy in the startup ecosystem, like there's a pretty immense amount of pressure to actually deliver something that's valuable because every dollar is precious.

41:13Yeah. And these are every founder. Yeah, they're being rational. It's not like, I'm sure there's been small instances where companies were actually, you know, had somewhat bad behavior. But in general, it's like, if I'm going to pay for the SaaS tool or the beta that you're running, it has to be good. Yeah. It has to work. Did you see Stuart Brand, he says, so there's a$1.5 billion judgment against Anthropic for including 480 ,000 books in training their AIs. Five of my books are among them. Word is there might be a$1 ,500 payout per book, according to my agent, Max Brockman. That's a good name.

41:57He said, I wrote to my agent, Max, the following. If any payment comes to me, please send it back to Anthropic with my thanks for including my books in their AIs. The judgment website offers a way to opt out of the payment, but I found it cumbersome. So I didn't. I'm principled, but too lazy to be highly principled. I really like this. He's the co-founder of the Long Now Foundation, which takes no sides. In this forum, as a private person, I do take sides occasionally. So I thought that was a funny thing. There is secondary market fraud going on left and right. But first, let me tell you about graphite.dev.

42:32Code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster. Take us through this. Yeah, reading through this, Matt Grimm says, secondary markets are rife with fraud and bad actors, and it pains me to see these bottom feeders profiting off of Anderle's growth while fleecing retail investors through unreasonable or opaque fee structures. In this week's episode of Nonsense Ignite VC, a fund we've never taken a meeting with or had any contact with whatsoever, founded by Brian, who we've never met, is soliciting investors via public Google Doc to invest in an SPV that will in turn invest in another SPV that will in turn potentially enter into a forward contract with a supposedly, though unnamed, early-end role employee.

43:12A few problems here. First off, so-called forward contracts are notoriously hard to settle in private companies, and counterparty risk is extremely real. What about the many complicating corner cases like acquisitions where shares don't trade or marriages, divorces, or deaths where ownership of the underlying shares is complicated? Just generally a risky structure to close that I don't think most folks actually understand. So yeah, if you enter into a forward contract and you basically buy the right to the future value of some shares, and then somebody gets, you know, again, married or divorced or passes away or bankruptcy is another situation where you might not be actually able to collect, even if your investment should have generated some return.

43:55Matt says, second, this deal memo includes basically no details about Anderle's performance, no revenue figures whatsoever, no product specifics. I guess that's good, right? Like if they were just floating around information that they had acquired. But anyways, continuing, almost as if it's soliciting investors to invest on hype and momentum and not fundamentals. Generally, I'd advise folks to be skeptical of any deal memo lacking basic details. Third, forward contracts are explicitly disallowed by Anderil stock plan and bylaws, which means that Anderil will never consent to Team Ignite's SPV actually taking possession of these shares while we are privately held.

44:32Zero chance. And finally, the memo spends most of its time talking about the structure and fees, which are insane. A double-layered SPV with all legal and admin costs passed through, in addition to an 8 % upfront fee, 3 % annual fee for two years, 20 % carried interest, and the craziest part, an implied price per share that is completely insane. In this case, the implied PPS is 115 % higher than the most recent preferred raise from nine months ago. Flattered, I suppose, but also puts these investors in an almost absurd position by paying more than double the price per share of our most recent transaction.

45:07As stated at the top, I don't know Brian or Team Ignite at all. Maybe they're kind of wholesome people, and this is all a big misunderstanding. But if I were an investor looking at this, quote, opportunity, quote, I'd run for the hills. and I believe the founder the founder replied and said appreciate the heads up the document reference was an internal draft prepared for discussion with an existing LP and was not intended for public circulation it appears someone shared it without authorization and we're looking into how that happened but do you see what there's like seven people that share a screenshot of like a direct email they got with this exact memo okay and the other thing is they say not soliciting investment for any Andrel related vehicle Matt says really?

45:48the draft was written by your founder and managing partner. I literally watched him edit the doc in real time. And he has a screenshot of like the, the, the founder's name in Google docs. Like, you know, basically anyways, well, don't do this. Don't do it. Instead. Why don't you start a company and apply to Y Combinator build an actual business instead of going around hustling SPVs and companies that don't want to sell shares. But we are moving on to our Y Combinator coverage. We have Harsh Taggar here in the Restream Waiting Room. Let's bring him into the TV panel. Harsh, thank you so much for taking the time on a busy Y Combinator demo day to come talk to us.

46:33How are you doing? I'm doing good. Thanks for having me. Fantastic. Take us through how's the day going? What is the schedule like? And then I'd love to dig into some of the trends that you're seeing, some of the standout companies. I'm sure we're going to be talking to a lot of them. But what's the run of the show today? And where are we in the course of the process of graduating these companies? So we got started like almost a couple of hours ago, 10 in the morning. And so the founders kind of – investors all gather together. They get into the main room here at the YC office. And then the founders start giving presentations, talking about like the progress, what they've built themselves, themselves, their background, the pretty quick-fire presentations, one minute each.

47:21And then there's sort of like a break in between sort of blocks of presentations where the investors can hang out and talk to some of the founders and get to meet them and, you know, obviously, hopefully invest in a bunch of them. So that's kind of, we're like, we're just about approaching lunch. So it's kind of like that part of the day where people have like listened to a bunch of companies, probably got like a sense of some of the stuff that they're interested in. I see people right now, like just hanging out, doing deals. So it's kind of like a fun vibe. It's like live. It's the best party rounds.

47:46We love it. I wish we could be there. Are there any like hero metrics or stats that the YC team shared this year to kick off demo day? How are you sharing like the shape of YC these days? Yeah, I mean, we didn't go too stats heavy this time around. I think, I mean, at a high level, it's just the continuation of the theme we've seen this whole year, which is just like the companies during the batch are just getting faster revenue growth, assigning like contracts with like big companies. In some cases, like even like government, defense tech, like the dollar value contracts that startups can close in like the first few months of their life are just bigger than anything we've ever seen.

48:32And that's all very directly from AI. So it's just exciting. Yeah, and it's a very interesting kind of approach. You can sign one big contract and generate enough revenue to go on the stage at demo day and feel confident in your pitch and have something that's compelling. Or you can go and sign up a bunch of startups to something, you know, smaller plans. But both approaches work. And you see that even post-demo day. There's companies that keep growing. In the SaaS world, you were used to just a consistent month-over-month growth. and now in sort of AI world, you're used to like big step function growth and it might be flat for a month, but then you sign like another contract and it just like leaps, leapfrogs again.

49:08Interesting. Yeah. Help me square sort of the shape of revenue with some of the YC batch that we might talk to you today because Paul Graham was on the timeline sort of defending this idea of selling to startups. We were in complete agreement with that, that selling to startups can be so much better in a bunch of different ways, but it does feel like we're entering an era where maybe it's AI, maybe it's just the maturity of the ecosystem. Like it's also been easier than ever to sell to the government or to sell to Fortune 500. And so are both happening in, are there specific companies that are really great at one or the other?

49:43Is there, is there any advice that you've given founders on how to decide between those two paths? Yeah, it's really, it really depends, I think, on like the type of product you're building. So I think like the, the bull case for selling to startups as your customers is like the stripe or the aws case and like it's like you get them all early i mean you could put gusto rippling deal into that bucket as well it's like if you get the startups early and you can grow with them that is one of the most powerful business models you can have right like the stripe team could go on vacation for like two years and they would just like keep growing because like the cohorts would just keep going up and to the right right so like i don't think they're going to do that anytime soon but they they could if they wanted.

50:24I think if you have a product like that, where you can grow with the startups, and you can get in early, and they will just like, those startups in the future will become your enterprise customers. That's like fantastic. That's absolutely what you want to do. I just think like with AI, what's new is, you didn't even have the option of selling to a big customer until you sold to startups. And you'd build up like, Oh, hey, like, we don't have an enterprise customer yet. But we got like 1000 startups. And like, in aggregate, we're processing like, x or like we're reliable we're not going to shut down i think now with um ai and the fact that the incumbents can't actually build the products because the engineers that work at these bigger companies don't even believe in ai so like startups in the batch are able to go to a big company and actually get them as a customer because they're the only ones that can actually deliver the product i think that's just new so like we still give the advice it's very dependent on the company and the product and like will you be able to scale with startups or not but like in general there's just more options as a founder for how you do sales than there's ever been.

51:22Let's talk about themes in the batch. Two batches ago, I felt like a lot of the companies were, at least the ones that we talked to, were various infrastructure. It was like infrastructure for building agents. Last batch really felt like much more applied. It was like applying AI to very specific industries and opportunities. I'm curious. I'm sure you're seeing both of those kind of types of companies, but looking at the list of guests that we have today, a bunch of super exciting companies, but curious to know kind of like broad themes across the batch. I mean, I think you say, right. I think what we've seen is that like maybe a year ago, just a year ago, it was like infrastructure, infrastructure to build agents, like you're saying, like laying the foundation.

52:08Then it's like vertical agents just take off like customer support, logistics, like name any, like healthcare, like all these verticals, and they're just like taking off. And primarily what they were doing is selling these agents to the companies in those verticals to make their operations more efficient. I think what seems to be a theme coming out of this batch, you'll notice, is like the companies are going the next step and they're not actually selling the agents to the like incumbents. They're going like AI native full stack. They're just actually doing the thing. So you have like, um, Fernstone being like an AI native insurance brokerage, like they're just, they, they, they are insurance brokerage and they're just going to use AI to be the best one.

52:49Um, Sava is doing that with trust. It's like a company that sets up trust, but it's doing it with AI. So I think that, um, that seems to be the new trend is going like AI native and not just selling your agents, but using them to build the company doing all the stuff. Yeah. We, uh, yeah, we've talked to a couple of like law firms that have done that. and also like investment banks, just people who have said, okay, we actually need to go do the core thing. I'm always reminded of Justin Kahn's company because it feels like Atrium was like just a little bit early to that model and now everyone's working on it and it's starting to maybe work and we'll see.

53:24Yeah, I think if you go bad, do you remember it was, I mean, it was like a decade ago now, but it was Balaji that started this whole thing with like the full stack startup. He had this blog post and like, I don't know if you guys were in San Francisco at the time, but like there was this moment where there was doordash which was delivering food and then you had spoon rocket and sprig which were like the full stack version because what they did is they had these kitchens like these bands which had little kitchens driving around san francisco cooking the food right so i think like back in that era was like it was seen as being the most ambitious thing to be a full stack startup you didn't just sell your software you did the whole thing yeah ultimately those companies didn't it turned out that being a marketplace or selling software was just a better scalable business in that era.

54:05But now with AI, like, I think the promises were kind of going back to the full stack startup idea. But this time, like, you know, we're all hoping and kind of seems like these things will actually scale because you don't need to hire like 1000 people to do the work. You just keep improving your agents. Yeah, yeah. I mean, the food example is interesting, because it feels like Travis Kalanick is maybe dipping his toe in like, Oh, what if I did the full stack thing? Yeah, yeah, he's got picnic. And I think it's otter. And he has cloud kitchens. So maybe at his scale, maybe it's a scale thing. I don't know, but it is more complicated financially.

54:38I think if you have Travis's access to capital and his background operating, you can do that. How are companies or founders grappling with what's happening at the largest foundation model labs? I remember there was some Sam Altman interview where he said, here's how not to get steamrolled. If your entire business is just predicated on the model not getting better, you're going to have a bad time. But if you're doing something completely separate with the model, you're probably good. How are people thinking about it in the more modern context? I think the framework people have on this stuff is that they expect, you know, Sam and the big lab companies, I mean, OpenEye in particular, to go after probably like maybe more of like the sexy consumer ideas that capture the public's imagination.

55:37And it is going to be hard to compete with them on that. But there are like the startups in the batch in particular focus on just like the unsexy verticals, like building an audit firm, building a legal firm, building insurance broker. Like the bet they're making is that like the best people at OpenAI or Anthropic are not going to be thrilled to build like auditing software or auditing agents, you know? Or actually sell the end service, right? Yeah, exactly. Like doing it, like going like all the way and like learning what that customer wants and how to do it really well and like iterating on it a thousand times to get that.

56:10Yeah, this is the whole thing with Google versus Amazon. Like Google did wind up building a shopping product, but they never really had that in them to be like, we're going and doing warehouses and we're going to compete with Amazon. Even though we want e-commerce, it's like, we don't really want it that badly. That sounds actually sort of miserable. And it's just not the data. It's the best people who don't want to do it, right? Like the best engineers at Google don't want to build a shopping product. They are like, back in the day, they wanted to work on search quality. Now they probably want to work on Gemini.

56:36Totally. Yeah. And there's, and there's also just cultural, I feel like culturally there are certain companies where like, if you're like, we do 80 % gross margin work and you show up and you're like, I'm the guy who does 30 % gross margin work. They're like, you can leave the company actually. Like we don't like you at all. So yeah, yeah. You know, your margin is my opportunity, both directions sometimes. Yeah. What, uh, what are, what are some companies from previous batches that you really feel like are hitting their stride now. We had Kaushii on yesterday for their$11 billion round. I don't think a lot of people are even aware that they went through YZ because it was so long ago, right?

57:15Yeah, that was 2019, I think. So, yeah, I mean, obviously, Kaushii is like the prime example of a company that just made a bet on a space early and had to just wait for the market to actually exist for it. And those founders super tenacious went for it. But I think more recently, there's a company that announced it around doing customer support called Giga, which I think is a really exciting one. They're competing with Sierra and Dekacorn, superstar founders of those companies, tons of capital raised. But they've been able to beat them on head-to-heads with customers like DoorDash through technology, really.

57:51So I think Giga seems to be really growing. I mean, another one, like non-AI, that's what, like PostHog, is actually a little bit more under the radar. but they are sort of like taking the rippling approach of. Yeah, they're launching a new product like every week it feels like. Yeah, it's like really interesting to see. They've done that from day one and it seems to actually be compounding and working the way that it has for rippling. So I'm curious to see if you start seeing more of that, just like startups trying to build multiple products from day one and have like the compound startup effect.

58:21I like animal themed companies. I like post hog. I like the hog themed. when we did our first demo day stream we talked to a company called Pig and we really liked Pig and it stuck with me and so I'm rooting all the swine themed startups I hope they all do very well but thank you so much for taking the time to kick this off with us congratulations on the big day great to have you on for the first time we gotta do this more often I would love to thanks for having me have a good one See you guys. Goodbye. Our first guest will be Clad Labs, makers of the Chad IDE. First, let me tell you about Julius AI, the AI data analyst that works for you.

59:08Join millions who use Julius to connect their data, ask questions, and get insights in seconds. We have Clad Labs. While we wait, I have some other names for if you're launching a startup and you want a pig themes name, a swine theme name. You could have Wilbur, Babe, Hamlet, Daisy, Peanut, and Cookie. Okay. I like that. Ham Solo. I like Babe. I think Babe works. Mud Pie. Okay. So we have the founder of Clad Labs in the Restream waiting room. Let's bring him into the TVP in Ultradome. What's going on? Look at this shirt. They look fantastic. Incredible. Incredible shirt. You know, you're winning me over already.

59:51Break it down first. Introduce yourself. Tell us what you're building. Good to meet you. How's it going, guys? Yeah. I'm Richard, the CEO of Cloud Labs. We're building Chad IDE, the world's first brain rot IDE. Okay. Why? So great. So we exchanged some comments and wanted you to come on the show. I think you get the TBPN award for the best rage bait at the product level of the year. And I thought your response to the essay that I did was amazing. You were like, cool essay. Unfortunately, it doesn't apply to us. Yeah, so why doesn't it apply? What are you actually building? Why BrainRot? Is it just for fun or is there something meaningful here?

1:00:32Do you think this turns into a real business? What's the plan? Yeah, the general thesis is that we're able to subsidize the generation of code with affiliates and provide these state-of-the-art models for much, much cheaper, mostly for free, actually, to most developers. And so that's why you're putting... So you're acting as a funnel to any affiliate. So it could just be ads, but you picked specifically the most controversial ones, the gambling and the subway surfers, like the stuff that feels more brain-rotty, because that would get a reaction. Was that the plan? Yeah.

1:01:12Yeah, I think Jordi touched on this earlier. There is a difference between the marketing and the product. We actually started out with affiliates on these very normal sites, and a lot of our users actually requested saying, hey, we actually score on RainBet. We actually go to stake during our generation time. We're like, okay, we'll integrate that feature, and then we'll use that as our marketing campaign. Okay, it's incredible. I mean, the debate was, are you making something people want? Is this in keeping with the Y Combinator thesis and the values of the organization? Yeah, I guess so break down what's actually happening.

1:01:44like you have the IDE and then you have this other column, which you can basically fill with anything. You could fill with an ad, you could fill it with videos or rainbed or whatever. What are some of the most common ways that developers are using the product today? And what do you think really scales and becomes the most popular? Yeah, the greatest thing about AI Native is that it completely changes the ad unit. So we have these AI Native ads that are in context and it's really great for code generation. Here, let me give you an example. So I say I code a website. Code me a website. Right now, Cloud Code has this multi-stage planning, right?

1:02:21It says, well, what do you want to code? Like, how do you want to use a backend? If I say, well, maybe I want to use a, like, Superbase. Say, yes, Superbase. That's a Superbase conversion right there. So the ad is actually in the context, in the application layer. So we have multiple ad placements, but I think the most exciting one is how does ads scale at AI Native? Yeah, we had a, What was the name of the company that we had on? There's another company that's doing this and actually integrating the ad so that you see an ad. You're like, yes, I want this functionality. You press a button and the AI actually implements the product for you.

1:02:57And I can just see that converting at a really high level and companies being willing to pay quite a lot to get in front of people at the right time. I mean, yeah, it makes a ton of sense to me on that level. a little bit less on the stake gambling while you're waiting. That feels like that would actually reduce developer productivity. Do you have any plans to actually assess whether or not this is a good decision? Because most developers are not solo entrepreneurs. They're employed by someone. And if I'm running an organization, do I really want my most valuable resource, my most valuable human capital, tuning out every other second while they're waiting for the generation to come back.

1:03:41Well, one of those engineers might say, well, because I'm betting on RainBet with my personal dollars, you're paying less for the IDE. I'm saving the company money, John. But don't you think that it would be better to show educational videos than something like that? Oh, we have that as well. Yeah, so we have educational videos, learn about the code that you're actually writing. But I think our thesis is basically that we follow the YC advice, talk to your user, and the user wanted the gambling integration, so we made it for them. And if at some point the user doesn't want it anymore, we'll take it away.

1:04:16So it's all about, I think, for BSC, being close to the user, iterating close to the user, and serving what they want. Have you been banned at any companies yet? Actually, the opposite. we had quite a few companies reach out to us and say, hey, we actually really want you to integrate our Notion, our Jira board, the whole productivity workflow into the generation time. And we're serving consumer right now. But I mean, there's infinite possibilities here to scale at various business levels. How has the traction been to date? It's been great. Yeah, I think I'd thank you guys for that as well, helping us go viral.

1:04:52So we have a great waitlist of 11K now. 11 ,000 people on the waitlist. Successfully baited. Has anyone used it yet? Have you built it? Is it in the wild? Is it a VS Code fork? Yeah, what were the metrics that you shared at Demo Day? Yeah, so the metrics I shared at Demo Day were 11K on the wait list, 30K in revenue from ads. We have people using right now in beta, and we're going to give out codes today at Demo Day. So anybody who comes up to us in Demo Day, we're giving you a code. It's going really great. Amazing. Find Tyler. I know he's probably in the same room. let's get Tyler on on Clad Labs or Chad IDE we should hit the gong yeah we should and how's the round going?

1:05:38it's going great yeah we filled half the round we have a lot of allocation to give out to people who are interested awesome, alright well great to meet you Richard thanks for coming on and breaking it down appreciate it, we'll talk to you soon have a good one let me tell you about Figma think bigger, build faster Figma helps design and development teams build great products together you can get started for free we have our next guest coming into the ultra dome this next company is absurd really? oh wait, it is absurd that's the name of the company they will be joining in just a minute here we might need to pop back to the timeline while we wait for them to sit down And, Jordy, you can take a view here.

1:06:22This is a live view into YC Demanday. So if we jump ahead of the schedule, we can always check in there. But we have the founder of Absurd in the Restream waiting room. Let's bring Tim into the TVP and Ultrodome. How are you doing? What's happening? Thank you so much for taking the time to talk to us. Of course. I'm doing good. How are you guys doing? I know you guys are only taking on a couple companies today. So thanks for having me on. We appreciate you coming on. I love you. Please introduce yourself. Tell us what you're building. Yeah. My name is Philip. I'm CEO of Absurd. Absurd makes AI marketing videos.

1:06:58An ad that we've made, you've probably seen it on your feed, is a Kyle Sheehy's Mamdani versus Cuomo 1v1 basketball match, which we did right before the elections. We like to joke that we influence the New York City elections. Amazing. So walk me through the product. It sounds like you're more using the foundation models, using Sora Vio 3 than training your own. But what are you building? How do you fit into the stack? Are you more of like a creative agency that I hire and pay a lot of money for an ad and you go out and use all the tools? Or are you trying to build software as a service or train a foundation model?

1:07:34Where do you sit in the stack? The way we're seeing how we fit into the stack is that we handle everything for a company in terms of AI native distribution. And the reason why we're doing it in that route instead of making an editor that anyone could use is because we can charge exponentially higher for that. So do you want to ultimately productize this? This is what Harge was talking about. Basically, instead of building an AI-native accounting firm or an AI-native law firm, you're effectively building an AI-native creative ad agency where somebody comes and says, I want one launch video, please.

1:08:14and you say, sure, here's the fixed price. And then you guys use your internal tooling and whatever models you have access to to generate the best possible output and you deliver that end product. Exactly. And what are you charging on like a per video basis today? So a lot of that's confidential, but I can say we charge upwards of 30 grand per video. Oh. So in the same line. You're effectively charging the same, somewhat similar to like what somebody would pay for like a full day shoot. Totally. You're in like the proper video production realm, at least in terms of price. What are the secrets to using the video models appropriately to actually go viral?

1:08:59What do you hire for? What are you focused on making sure that the video that you deliver is actually hitting upwards of$30 ,000 of value? so in terms of the value we deliver every video we've posted has gone viral i mean we average 300 000 organic views for every company we work with regardless of whether you have 200 followers on twitter or you have like a million um second thing in terms of what we're prioritizing um what we're really thinking about internally is just how many videos per person per week like what's that throughput looking like and then how do you drastically increase that week over week so three weeks ago that was one video per person per week today it's 10 super bowl quality ads per person per week made in parallel next week it's going to be 50 following week it's going to be a thousand i mean there was a company that came to us i can't say their name but um they said they won 1500 of our kalshi super bowl ads in a month and that's the type of quantity we're talking about here like this is just this is a lot of money that we turned down 200 000 dollars in the past three days because we just you know in terms of our bottleneck we just had this huge technical bottleneck and we couldn't get it out in time yeah like you turn that you turn that revenue down a few days ago why don't you just go back and say hey we have the capability that we have the capacity now you just said because we still don't have capacity now we are we could literally so how many thirty thousand dollar videos have you sold did you did you create did you find an infinite money glitch here or something there's not even a thousand there's not even a thousand you know venture-backed startup launches uh you know a week yeah so the way we're seeing things right now sure we start out with launch videos that we charge 30 40 grand for but now we're going towards more of like a retainer right so now we're striking deals with companies like kalshi replit wop and we're telling them you know we'll do a bundle deal 10 videos a month for x price sure right and eventually it's going to go to 50 then 100 and 200 a lot of this is going to be used in ads um because the more you spend on ads the more you have to switch out ad copy because you've had you know fatigue and then we're going to go up and we're going to actually connect the orchestration layer to the actual metrics dashboard of all these ads um and then eventually we're gonna get to a point where like we have this huge compounding data mode and our ad just get better and better and you can think of an ad i think for the first time in history as like you can create a thousand different variations with one click of a button.

1:11:35Because if you think about the ad, an AI ad, it's literally just like images and you're animating them. And as long as you have an agent that edits the images and changes the prompt slightly, you can create a thousand different variations and then test multiple things at once. Will we see any absurd commercials during the Super Bowl this year? I can't say.

1:12:00You think maybe? That's a good answer. You should make it happen. He can't, you know, people are going to look up his customers. What do you think about the role of taste, of craft? A lot of what's previously gone viral in the age, in the pre-AI age, has been someone coming up with a really unique concept, a really unique spin. And AI hasn't really been able to deliver those unique ideas. It's really good at reconstituting what's already out there and coming up with existing ideas. Yeah. Historically, the best creative agencies have been the agencies with the best ideas. Yeah. Right? Totally. You pay to work with somebody that has a track record of generating great pain concepts.

1:12:52And then they'll oftentimes just outsource the work to people that are good at the execution layer but not at the idea side. do you feel like you guys need to develop like a like internal like taste yeah just just ability to like generate a high volume of good ideas now that the actual execution yeah in terms of like creative production is like so much faster uh with ai yeah i think um we think of like creativity not as a monolith but really in terms of two parties exactly how you put it so there's a taste layer, then there's an execution layer. Our job here is we want to remove that bottleneck between an idea and a finished product.

1:13:33So internally, what we're doing to solve that is like, sure, we're not going to replace human creativity. We're going to automate human labor. We're going to make it so easy for like a comedian or a script writer or someone who just wants a part-time job. And we're going to pay them like a really high salary, really easy for them to like create the seed of an idea that we can spin off tens and thousands of ads for. How much are you guys actually spending on the model side or within any of the applications that you're using to generate this content? Well, for like a 30-second to 60-second video, really it's like 300, 400 bucks.

1:14:16We have an internal orchestration layer that picks the best models to use for all these specific use cases. it's paired with like a 50 page doc that has all our learnings that isn't available anywhere online. And we're able to use these models really effectively. So our margins, like beyond just human labor, because we're the ones making the videos and spending all these things up, we don't know how to price that, is like close to like 98%. But if you add in human labor, I think it's still like above 90. How many different models are you using on an average 30 second video? Do you feel like it's worthwhile to stick to one model because you get more of a consistent look?

1:14:51or are you jumping around? How do you think about the different models, what they're good at? Well, it's extremely obvious that some models are just really good at some stuff and really bad at another thing. C-Dream is good at specific use cases. Nano Banana is good at specific use cases. Kling, Wan all have their own unique use cases that we use. Something that's interesting beyond just the models is just in terms of workflow orchestration. Before Nano Banana Pro came out, I'll give this as an example. If you wanted to swap someone else's face, like you would put in, you know, I put in John's face and I say, I want to put Kanye on that.

1:15:29And that wouldn't work. So the way you do it is you'd actually tell Nano Banana to cut off John's head and then get that like headless image and put Kanye's head on top. And that's how we swap faces before Nano Banana Pro. So there are all these like little workflow things that we've learned just by experimenting and playing around with these models, which play a huge role in making all our ads like the creation of our ads really effective have we entered a post slop era will we enter a post slop era what what is your post slop timelines i was speaking to jess lee actually about this uh she was talking about how photography used to be seen as slop um and because you know it used they used to say that photography was this way that artists were actually painting something.

1:16:19But photography allowed people to realize that, allowed people to capture like a smile really quickly through slow motion. And something will emerge from this AI era where you can do something with AI video to capture some essence of human that you wouldn't be able to do otherwise. And we don't know what that is, but I'm pretty sure we'll be the first to figure that out, especially if we're pushing all these videos every month. How big is the team today and how's the fundraise going? It's just me and my two co-founders, Daniel and Damon. In terms of the round, we closed. I can't announce how much, but we closed a week and a half ago.

1:17:00Incredible. John, hit that gong. I will. For Phillip and the absurd team. Thanks for coming on, breaking it down. I'm actually surprised there's not more companies trying to do this exact sort of playbook. But it's cool to hear how you're thinking about this and excited to see more of the work that you guys put out. Of course. Yeah. And by the way, before I go, I'd love to make a launch video for you guys. Okay. Let's talk. I would love that. I want to see what you can do. We have a benchmark here, BezelBench, where it involves a lot of watches on arms. We like to put this to the test with a lot of different AI video generators.

1:17:44It's a particularly hard shot to get right. But we can come up with a bunch of different ideas. Let's do it. It would be fantastic. Let's do it. Perfect. Well, have a great rest of your demo day. Dylan is an angel investor. He'll be in contact. Thank you guys for having me. Talk to you soon. Cheers. Goodbye. Hi. Before we bring in our next guest, let me tell you about Adio, the AI native CRM. Adio builds, scales, and grows your company to the next level. Up next, we have Lightberry with Ali Attar. I like Lightberry. Social brains for robots. Social brains for robots. Let's bring in Ali. I like the sound of that.

1:18:19Lightberry. Yes. Very interesting to see what robots we're talking about, but we have him here in the studio. Welcome to the show. Hello, how are you? What's happening? Lightberry owning yellow, verticalizing yellow. I love it. I love it. You know, we have to wear something different. Everyone's wearing like gray and blue and black and like, we need to stand up. So yellow it is. Underrated color. Underrated color. It is. It's awesome. Great to have you on the show. Why don't you introduce yourself, give some quick background, what you're doing before starting Lightberry. Yeah, of course. So yeah.

1:18:53Hi, everyone. I'm Ali. I'm one of the founders of Lightberry. We're effectively just building the operating system for all robots so that any person can use a robot. Before this, I ran a browser company called Sigma OS. I was running product and design there, and I went through YC in summer 21. Very cool. Yeah, so that's me. Very cool. Talk more about that. This feels like a very big opportunity, but I'm not using a lot of robots in my day-to-day life today. I assume that I will be much more in the future. But yeah, talk about what the business and the product looks like today and where you see the kind of category going.

1:19:35Yeah, so we literally have a humanoid robot upstairs right now emceeing the entire event for Demo Day. And he's fully autonomous. He talks. We give him some instructions about how he should behave for the day. And he's just acting like a part of the event staff. Now, you can go out there right now and just buy a humanoid robot from at least 50 different manufacturers. But if you do that... Who did you buy yours from? So ours is from Unitree. It's a Unitree robot. Did you buy it on Walmart.com? No, no, we didn't. I know they sell Unitree robots. No, no, no, no, not at all. No, no, we actually work directly with Unitree.

1:20:10And so if you buy a robot from them or any of the 50 others, it literally doesn't do anything. It can't talk. You can't teach it anything. The only way to interact with it is by writing code. We thought that's insane. And so we're building a software layer that allows literally anyone to use a robot by just talking to it.

1:20:29What does adoption kind of look like with this? Like, how are you actually selling it? Is this something that you want Unitree to kind of encourage their customers to adopt? Because again, I'm sure any manufacturer of robots doesn't want to just sell to developer hacker types that happen to want to go through all the different hoops in order to actually get value out of a humanoid. I mean, that's exactly it. You hit the nail on the head. We're working directly with the manufacturers. There's over 50 of them. We actually just last week closed a deal with Unitree. They correspond to 90 % of market share in the world.

1:21:06I'm giving you the air horn, but I have encouraged various government officials to ban Unitree from the United States. Oh, no! Well, look, you know, the truth is like they're the only ones shipping. Like we want to work with the American companies too. We want to work with literally everyone. But Unitree's shipping. They have market share. So it just makes sense to ship on them. We're going to be selling Lightberry powered robots with them all over the US. But we're also working with other companies, some European ones, some American ones. Yeah, what's happening? So I would imagine OneX has no interest in partnering with external providers.

1:21:40That would be my sense. Maybe that changes in the future, but I know they're trying to really verticalize, and I'm sure they want to create personality and some of the same feature set. But what about other players in the U.S., Figure, Optimus, et cetera? I mean, the truth is, like, they're just not shipping yet. And when they want to start shipping, and right now they currently don't have any software that allows you to interact with the robot. There's nothing that works in a public space. I heard that Figure's deal with OpenAI just fell through. I don't know if that's true, but, like, that's the rumor.

1:22:13We'd love to help all of those companies get to market faster. It's just a race right now. So it's like whoever needs software so that you can interact with the robot, we're here to help. What do you think the most dominant form factor for robotics in daily life will be in just maybe like two or three years? Do you think we're going to go through like a wheeled robot phase or, you know, one robotic arm on Roomba phase? Like, how do you see, because the self-driving cars are sort of here, the Roombas are sort of here, the full humanoid robot, that feels a little bit farther out. But is there going to be more of a transitionary phase in your mind?

1:22:56I mean, if you look at sci-fi as an indicator of what people want, we don't just want humanoids. There'll be different kinds of robots. You're going to have some, like, small bipedal droids that, you know, we work with a few companies that do that. You're going to have wheeled robots for, like, delivery that's just more practical. In homes, I actually don't think you'll have humanoids because, like, why do you need locomotion in those cases? Humanoids are going to be the first, like, general purpose form factor that's going to make it, in my opinion, just because, you know, they look like us. And the reason why we're building humanoids is because they look like people.

1:23:27And so we'll just be deploying them in people-facing roles. So, like, shop assistants, manning booths at events, emceeing at demo day, right? Like, we have done this before. we deployed a fully functional autonomous humanoid at the 11 lab summit three weeks ago, and it was just working there for 10 and a half hours fully autonomously alongside the staff. So yeah, that's what we do, and we think that there's going to be tons of different form factors. It's going to be like a Cambrian explosion of robots. What are the compute constraints like? Do you think on-device inference is going to be really important?

1:23:59So we run a hybrid pipeline. We rely heavily on the cloud because that's where the best models are, and people prioritize the quality of interaction. more than the reliability of it. Now, we also run it, as I said, hybrid. So we have an offline version that's also running in the same time. So if connection drops or anything, the robot will still talk to you. It'll still understand. It'll be less smart, but it'll know about it. Yeah. Have you had any luck? I mean, how do you think about like personality development? And I've been very fascinated by the fact that pretty much no lab has been able to hammer out of the model.

1:24:34Like the, it's not this, it's that. They all have this specific LLM flavor to them that I don't think most humans, maybe I run into one out of a million people that talk like that, but all the robots talk like robots. And I'm wondering if you have any thoughts about where that all goes. I think prompting is just, I mean, these models are getting more and more steerable and they're better at following instructions. So as long as you do a great job of spending time on designing those interactions, you'll be able to get these robots to behave less like robots. Now, we're not trying to make robots that, you know, behave just like people.

1:25:09Like, people love C-3PO, but C-3PO is very obviously a robot. It has a robotic voice. It's a bit awkward in the way it speaks. And, like, that's the inspiration. It should just be, like, smart enough, but it should still, like, behave and follow our social norms. Like, the robot should look at you when you're speaking to it. The robot should be wearing the outfit of, like, the staff members that it's representing if it's at an event. And that's what we're here to do. Like, we're just here to make that easier for all of those manufacturers because they're racing on hardware. They don't have time to think about the software and the interactions.

1:25:37Are you excited about robot pets as a category? I know dogs are substantially cheaper, and that feels like something that a robot pet doesn't need to necessarily add any value outside of companionship, and so it feels like potentially an area where we could see a lot of growth in the near term. So we actually have a little pet droid in our office. It's like a bipedal that kind of looks like R2-D2. We brought a bunch of little robots to the event too. There's like six of them in the demo for anyone who's here. Yeah, I think robot pets are going to be really big. It's just we started working mostly with Humanoids just because the price point is so much higher that we could just focus on quality rather than like trying to optimize for cost.

1:26:23Obviously, as these robots get smaller, the cost gets lower. And so, you know, for us, we just care about quality. The models are going to get cheaper too. So we'll be able to deliver on toys, pets in the near future. Yeah, the toy market seems really, really interesting. Yeah, our first customer was a toy company, actually. It's very funny. It's just so much lower stakes, in my opinion. What about security? I feel like there's a potential use case for humanoids just having a human-shaped thing just moving around. So literally the landlord of our building, when he saw that we moved in, he stepped into our office.

1:26:59and on day one he just asked us like oh so these things can talk and they can walk around they can map the world it's like yeah and he was like you know what i would love to deploy them for security how much does it cost and i told him it's gonna be like around 60 to 70k it's like i want four i was like okay deal so like he he already pre-ordered them like people want this for security not because it can fight not because it can harm people these things can't just about they're like it's about presence yeah it's just it's the best deterrent and like you know it can literally talk to weird people in the evenings like who are you and like run facial recognition like are you meant to be here and then just alert like whoever's on like on guard at staff and just call them and ask for help like that's how it should work right yeah robust to help people not not to replace them yeah i do think it's interesting that a lot of these humanoid companies are focused on the hardest possible thing which is replacing like a house a housekeeper sure who is already not the highest comps person doing the most like intricate, specialized tasks where somebody that's a security guard, their primary job is to just stand there and look like they're paying attention.

1:28:03And that's like the job. And they make like the same amount as a housekeeper. We don't think the chat GPT moment for robotics is going to be the day that your robot will know how to fold your laundry. We think it's going to be the day you start seeing robots everywhere in the street or like in shops, in coffee shops, in events, like talking to people. And that's just really soon. It's going to be fun. Very cool. How big is the team? We're just a small team of three people. We have a few people that we're working with that are helping out on top of it, obviously. But yeah, it's just a core team of three founders.

1:28:39Amazing. And how's the round going? It's been very fun. I mean, we managed to close it pretty early. There's a lot of, there's some interest now because, you know, with the Unitary deal, we're pretty close to our Series A milestone, so we're trying to discuss that. There we go. Series A time. Love it. Let's go. Really great to meet you. We'll talk to you soon. Thank you for coming on. Pleasure to meet you guys. Take care. Have a good one. Cheers. Bye. Yep. Up next, we have Dome, a unified API for prediction markets. This should be fun. It's trying to sit on top of... Pick a favorite. Pick a favorite.

1:29:15Call us for your polymarket. Well, there is a lot of arbitrage to be done on the topic of robots. I'm super excited about the lamps that are happening. Have you seen that there's two robotic lamp companies now? They're expanded. One of them was just CGI, right? I don't know. Maybe both of them were CGI. Isn't Apple making their own robotic? It just feels like something that can be done, whereas if it's full humanoid tomorrow for this much money, that feels like a taller order. It's going to be a couple years away. But the lamp I feel like we can do today, the lamp can talk to you. It's going to be funny.

1:29:49It's going to be awesome. I'm excited. I'm really bullish on the lamps. But I'm also bullish on a unified API for prediction markets. So we'll bring in the founder of Dome. Welcome to the show. What's going on? Welcome to the TBP and Ultra Dome. You're in the Ultra Dome. I love it. And your company is Dome. Please introduce yourself and your company. What do you do? Hi, my name is Karush. We're basically Dome. So Dome is a unified API for prediction markets. In a nutshell, what that means is we allow users and developers to trade and analyze across multiple platforms at once. Okay. Who's the customer?

1:30:20Are you talking hedge funds or like the most advanced traders? Yeah, honestly, it's all of the above. A lot of our current customers are folks building applications in prediction markets. So these are folks building like prediction market skins or markets themselves or copy trading. And agentic trading is like really popular right now. We talk to a lot of sports books and hedge funds as well. They're getting interested in high-frequency trading. and also like platforms like, you know, things, sweepstakes apps, folks who are trying to like price internal parlays. So there's a lot of applications currently being built right now.

1:30:49It's crazy. Very cool. Who's your favorite, Polymarket or Kalshi? I'm just kidding. I'm just kidding. I won't make you answer that. I was about to say that's the million-dollar question. Yeah, yeah. No, no. I mean, it's unfortunate that the timeline is just so incredibly toxic right now. But I feel like you're able to kind of like sit back and be hopefully like Switzerland and support a variety of different exchanges. How do you think this market actually shapes out? Right. I think the big news from last week is that Robin Hood is getting into the game themselves. They actually want to not just be a broker.

1:31:29They want to be the exchange. But how does this how does this evolve? Yeah, I mean, we're supporting currently Polymarket and Kalshi. They're both great. Obviously, we don't pick a winner in the fight. We want everyone to do well. And what we're currently seeing is there are a bunch of new platforms launching, different regions, different specific verticals. Some folks are just like only sports. Some are doing crypto, mentioned markets. So what we're actually seeing is there's going to be a lot of players coming in, each trying to find their specific wedge, find their little market, their community there.

1:31:57And so in addition, you'll have Kalshi, Polymarket, you'll have Robinhood and a bunch of other big players that are probably launching soon. But you'll also have a lot of these smaller players in different specific regions and verticals. And so we're excited to see the whole world basically start adopting this. Do you have a reference point for how cross-market transactions – is there a public markets equivalent to you or some sort of layer that's not necessarily a hedge fund? I remember reading Flash Boys. and in there they're talking about trading on the commodity markets in Chicago and then also the stock exchanges in New York and that but it's done this is all done by the hedge funds there's not some sort of intermediary why do we need an intermediary here in this markets particularly yeah I mean that's a great question for what it's with my flash boys is my co-founder's favorite book so you hit it on the nail but yeah absolutely so one as you get a lot more providers in right now a lot of the liquidity is fragmented okay so if you actually look at just calcium polymarket themselves, about like 80 % of their markets, their underlying contracts are the same event.

1:33:03So you actually have a good amount of overlap there. But you also hit it on the nail as well as like there are other markets you can match against. Like sports books are obviously very, very clear. There's a lot of prediction market overlap there. Crypto prices, perps, and all these things. So by kind of taking all this data in, creating that centralized source, it really helps out the hedge funds and those other professional traders who are trying to trade across multiple platforms because everything's in one spot. Is some of your volume people just arbing markets on the different, basically seeing like, okay, what are the odds on Kalshi?

1:33:34What are the odds on Polymarket? And trying to find alpha through that. Yeah, I mean, arbitrage is a very common request from a lot of our customers, right? We actually had a customer that charted using our APIs, like the different prices across the platforms. And it's a really cool visual because you can see the gaps over time of free arbitrage. And so arbitrage is a very common platform. One thing that we do really well is we make sure like when we are matching markets across platforms, we tell them like, hey, this is for sure a one-to-one market versus like a maybe one-to-one market. Because personally, the way we got started was we were trading ourselves and got burned as well when two markets look similar, but they're not perfectly similar and you lose a lot of money.

1:34:12And so that's something we're very – Oh, because you think you're hedging. You think you're just squeezing like 1%. Here's the issue is you can have the same event and like different criteria in the market based on the platform and where – what exchange it's hosted on. A lot of people have been seeing the rounds coming together for the different prediction market platforms and having flashbacks to like OpenSea in 2021 and 2022. Why do you think NFTs, which also saw explosive growth and volume, are kind of not the right comp for this industry? Yeah, great question. Biggest answer is like, we've kind of seen this exact playbook before.

1:34:51Both my co-founder and I, we were founding engineers at a company called Alchemy. So they're the blockchain infrastructure layer for anything you're doing in Web3. They did extraordinarily well. And prior to them, the only really big businesses in crypto was exchanges. After they came and solved the infrastructure problem, you saw a bunch of companies build on top of them, including OpenSea and Polymarket. So we've seen this wave. We've built a lot of the similar technology, the infrastructure layer at these previous companies. What you typically see is there's a huge hype and boom cycle. Everyone's excited.

1:35:20and then like interest kind of fades away, but people keep building. And then the next hype cycle, you realize, wow, the floor is raised. And so with prediction markets, you saw this during the 2024 election. Everyone was super excited. They thought this was the future. The election ended. Everyone's like, oh, this is fine. We'll see you in 2028. But people kept building. And then the first week of the NFL Sunday, they did more volume than they did during the 2024 election. And so that's just more proof to say like, yes, there will be boom and bust as far as interest, but the overall market will continue to grow.

1:35:50So are you actually routing trades on behalf of clients or just providing the data layer? Because I imagine it could get quite difficult when some exchanges are using digital asset, you know, stable coins. Others are using traditional fiat rails. I'm sure you would need to integrate both. What can you say there? Yeah. So first things we start off with is you got to solve the read layer. You got to give developers the tools they need to build, right? So that was the first version of product is just give them data, give them prices, APIs, tools, whatever they need to display on their application so that they can build applications.

1:36:27The next part of our plan was then, okay, let's actually start doing order routing and routing these requests to these different platforms. And we actually just recently launched our order router as of last week. And so we will be doing, we first are starting off on the crypto angle, like processing orders through on-chain portions. And then eventually we'll also do off-chain and traditional fiat as well. uh do you think it's interesting that a lot of the sports books are uh funding lawsuits against the prediction markets while also starting prediction markets uh products themselves i think it's super interesting i think i think a lot of these sports books and sports companies are also very smart and aware they understand they kind of see the writing on the wall there's so many more advantages to having a pure prediction market a p2p experience it's a lot better for the and consumer as well.

1:37:14So I think they kind of see the writing on the wall. I think while the lawsuits are like the equivalent of like maybe the taxi industry suing Uber back in the day, I think eventually most of this industry will move towards prediction markets. How's the round going? Round's been good. We actually closed up yesterday. And so super, super excited. We're excited to get back to building. I had a feeling. I had a feeling. I appreciate that. Yeah, I appreciate the excitement. It's been an exciting journey so far. Well, thank you so much for coming on the show. Yeah, great to meet you. Congratulations for writing domes Yes, we appreciate it We'll talk to you soon Cheers Have a good one Before bringing our next guest Let me tell you about none other than Turbo Puffer Serverless Vector and Fault Dex Search Built from first principles and object storage Fast, 10x cheaper Extremely scalable The Forbes 30 Under 30 came out today And liquidity is having some fun Because one of the guys who made it he performed 150 % equity growth since 2019, but the S &P is up over 172 % over the same period.

1:38:18He made money for his investors. Well, the thing, he might have taken less risk. And so if he took less risk and made almost the same amount of money, then that's good, you know? So there is a steel man for this particular person making the 440. It's always a steel man. But there's some good folks on the 30 under 30. We'll have to take you through them at some point. But until later, we will go head over to Source, and we're going to talk to David, who's building Tinder for Jobs. David, good to meet you. Welcome to the show. Thanks so much for taking the time. Introduce yourself. Introduce the company.

1:38:52Yeah, thanks for having me, guys. My name is David. I am one of the founders of Source. Source is like Tinder, but for jobs. So you just upload your resume, swipe right, and AI will apply on the company's website for you. Okay. How is AI actually helping there? Because I'm still doing the swiping myself if I'm looking for a job. The AI is just doing the application. Is that correct? Yeah, yeah. So you basically fill out one job application when you first set up the app. And then when you swipe, then we have browser agents that will actually fill out the applications. Got it. So it just saves the filling out form time.

1:39:28How's the traction? What is it? Are people using it already? Can you talk about the state of the hiring market? because I feel like the number one complaint that candidates and people that are applying for jobs have is that seemingly nobody reads, nobody actually looks at job applications, and a lot of roles don't actually end up getting hired based on traditional job boards. But yeah, what can you say about kind of what you're seeing in the market? Yeah, I guess it very much depends on the company and the role in the sector, but in general people definitely still get interviews from just inbound applications a lot of it is automated and recruiters do kind of like sift through the applicants applications but i think the number one meta point is that it's definitely a field that's like ripe for disruption like you are applying with many many other people and there's typically other ways to get in like a lot of people email them themselves into a job or a lot of people refer their way into a job but But the inbound is definitely still something that companies use because when you're hiring people at scale, there's just no other way to do it.

1:40:37Like if you're a company that's hiring like 200, 300 people a month, it's impossible to do it through inbound. What kind of like jobs and markets have you been focused on? Because maybe it's not like, you know, other companies in a YC batch. Maybe that's incorrect. But where's the focus been? Yeah. Yeah, I guess a misconception about Source is that we're not very directly working with these companies. We're just a traditional job board like an Indeed or a LinkedIn. So we directly scrape the ATSs. So right now there's like a million and a half jobs on the app. And those are scraped from ATSs like Workday or Greenhouse or Ashby.

1:41:13So if your company uses that system as an ATS, then we've probably scraped your job and you're on Source. Are they okay with that? Is that fine to just scrape these? Because I know LinkedIn used to be amazing for scraping. I'm assuming yes, because they're like, you're going to get more candidates. Yeah, so the ATSs themselves aren't like advertising or marketing. Like they're just SaaS, right? So there's kind of a contract in this industry to the ATSs are there to be scraped. Like 80 % of the jobs on Indeed are scraped. Most of the jobs on LinkedIn are scraped. Sure. Job boards themselves obviously don't want to be scraped.

1:41:44Like we wouldn't want to get scraped. But the ATS themselves, obviously, they are just like sending out emails to candidates and managing that whole pipeline. so yeah that's completely fine and as for how the companies are reacting to it to answer someone's question um like we've helped get over 25 000 interviews in the past year and those range from those range from thank you that's fantastic from like i guess there's a very wide range of companies We've helped somebody get a software engineering role at Anduril a couple months ago. But then very often you'll see someone get a line cook job. But it's really just the universal fact is that filling out the form is very, very pointless.

1:42:32How do you do top of funnel? How do you get people to be aware of your app, actually install it, download it? How are you driving attention on that side? Yeah, we've gotten very good at going viral and getting views. I think over the past year, we've done over 100 million views on social media, mostly on TikTok and Instagram. And that, again, is mostly just like me and my co-founder making videos on TikTok and Instagram. We have like, I think like 72K on Instagram right now. And that's just from us pulling out the camera and telling people about what we're doing and people like it. That's very cool.

1:43:06How are you going to make money? Are you making money already? So we actually launched this while we were in school. I just graduated in May, but we launched this at the beginning of the fall semester. And we used to make money by charging people for more swipes. We recently have gone very, very free. You really don't need to pay to apply to a lot of jobs anymore. But yeah, we used to make money from that. Since we've taken that down, we don't really make money from that anymore. And in the future, obviously, we plan to take the traditional job board route and work directly with employers, just faster matches, get more applicants, et cetera.

1:43:42But right now, we're very much just product-focused, and we're kind of willfully ignoring revenue. Yeah. How's the round going? Round is basically done. I think my co-founder is talking to investors, but it's really just for fun. We're not planning on raising any more money. Tell them to get back in the grind. You don't need to be talking to your investors if you close the round. Uh, yeah. Small recommendation. Small. I, I, I don't like Tinder for X. Oh, sure. Uh, I'm sure that that actually resonates really well with consumers, but, uh, but, uh, the, the, the, the product experience makes it, makes a ton of sense.

1:44:22Um, people think swiping, they know swiping. They know swiping. They know swiping. They're not getting away for that. Um, makes sense. But, uh, but anyways, very, very, very cool. Congrats on, on all the traction. and hopefully we find some people on source at that point. Yeah, that'd be great. Yeah, absolutely. Thanks so much. We'll talk to you soon. Have a good rest of your day. Let me tell you about Gemini 3 Pro, Google's most intelligent model yet, state-of-the-art reasoning, next-level vibe coding, and deep multimodal understanding. Before we go to the next guest, Drew Rowe in the chat says, I don't know if anyone said it, but the Ryzen X3D is the only way to go for your racing sim setup.

1:45:03Ooh, that's an AMD chip. That's an AMD chip. We might have to do AMD. I had a thread ripper years ago. Give us some. We've been talking. I think we're dealing with an expert here. An expert. We need to trust the experts. We've been talking to our friend Paul, who's a racing enthusiast, getting some recommendations there, but putting together some rigs for the team. Yeah. Well, up next we have Matorial with Kareem, the integration layer for AI agents. Welcome to the show. How are you doing, Kareem? Thanks for joining us. Finally, somebody that is integrating agents. Great to have you. Almost. Almost correct.

1:45:39Okay. Thank you, Kareem. What are you doing? So we basically give your AI agents, so your LMs, access to these apps and data sources. So anything from your Gmail to your SAP to your Salesforce. Okay. I was just, we were just talking to somebody. Oh, Jason Fried, right? He was saying that OpenAI just wound up building a Basecamp integration out of nowhere one day. They just kind of told him, hey, it's live now. You didn't have to do anything. Is that not happening fast enough? Like, in what scenario would I need your service if all of the – it feels like there's a massive war going on between the LLMs.

1:46:13They all want to do the integrations as fast as possible. How is this going to play out? I mean, actually, one of the OpenAI members of technical staff reached out to us for our product. Okay, okay, this makes sense. There's that. But basically, one way to think about this is, right, first of all, OpenAI, won't give you AI integrations for the other providers. People still want to be using Gemini. They want to be using Anthropic or any of these others. So we basically provide you with the developer tooling to use any LLM model with any AI integration. And it's not just integrations. It's also these things like access control, right?

1:46:46Because these Fortune 500s can't just unleash an LLM with access to whatever your Salesforce SAP to all the members in their organization. They need to think very concretely about who has secure access to which models and which data sources. Yeah, that makes a ton of sense. What were you doing before this? So I just graduated from NYU Abu Dhabi in May, and before that I ran a different Abu Dhabi-based ticketing startup for around three and a half years. Oh, that's cool. Very, very cool. What's Traction been like? You said a member of the technical staff at OpenAI reached out. I am. That's a development from yesterday, so not too many updates on that.

1:47:24But we are open source with over 3 ,600 GitHub stars. And we have close to 1 ,000 weekly active users just since launching around five weeks ago. And then we're also in final stage discussions with some Fortune 500s and unicorns who will deploy this across the organization. Good sound effects across the organizations of 80 ,000, 100 ,000 members. Is MCP complementary, competitive, substitutive? How does MCP fit into this? So here's how we think about it. So LLMs, 10 years from now, will still need access to apps and data sources with access control. Right now, the standard for that is MCP. So we basically have this middleware layer translating between our platform and MCP.

1:48:09But if the standard changes a year from now, we just switch to the new standard, right? Because the long-term bet here is not an MCP. I think that's what a lot of these other companies are getting wrong, where they're building 100 % on top of MCP. but they don't actually think about what these companies need. They're just kind of following the hype train of, oh, MCP is the next cool big thing, which we are not fully in agreement with. Can you take me through sort of like the top five agent categories that are interesting to you? I imagine coding agents are probably at the top, maybe knowledge retrieval, deep research agents, maybe customer support agents.

1:48:42Yeah, we don't actually think about that. Okay. We are completely unopinionated about how you build your agent. We just provide you with the integrations. because every agent will need to do read and write operations on these apps and data sources. And if you can take a text on that, you figure out how big the market is. Yeah. Is there, I mean, I guess to flip the question around, just what agentic capabilities are you excited to see out in the world in 2026? Honestly, I really like seeing all these new verticals where basically people just, what do they call them? those full stack AI native firms where free people go in there, use these LM capabilities, and these, for example, legal agents or healthcare agents to compete with unicorns or large established players.

1:49:30I think that's really exciting. You kind of got this golly of story there. Okay. So walk me through that. If I'm a lawyer and I'm leaving my firm to start an AI native law firm, I might buy some AI legal SaaS, but I also might need to integrate with some more niche tools or some more legacy tools. Are you the firm that I would go to to do those integrations for me? Yeah, we basically want to become the substrate for your integrations. So really long-term, we want to have a sort of Oracle story here. Similar to how Oracle became the substrate for enterprise databases and then sold those extra things like enterprise Java, et cetera, on top.

1:50:10We want to be the substrate for the integration layer and the access control layer and then add these additional things like the workflow builders or also hosting your agents, right? So that's kind of the long-term vision here. I always like to take the temperature on YC folks on what's breaking out in their supply chain. What's a tool or company or service or technology that you are leveraging to build this company that you're particularly thankful for? See, this might surprise you, but kind of compared to a lot of other people, we are very OG software engineers. What I mean by that is my co-founder and I have had formal computer science education for over 11 years.

1:50:55So we met in Austrian technical high school at 14 years old for basically computer science. And that really allows us to think about first principles. So in terms of building out our entire infrastructure ourselves, thinking about the API designer from scratch. And we don't really use that many tools that are available out of the market right now. because what we find is that they speed up the process a little bit, but we have been doing it for so long that we can just do it better ourselves. So really, we invented a lot of new things here as well, which kind of the other competitors who are mostly only wipe coding can't even do with their...

1:51:30You need to get an organic certification on the website. You know, like, this is organic code. You can get the Austrian Armagüter Siegel. Yeah, I love it. Let me guess, the round's already done. Yes, very fast. Actually wrapped up in around five days. Five days. I knew it. I knew it. Oh. I knew it. Congratulations. Thank you. Yeah, I loved hearing how you're thinking about the opportunity and how opinionated you are. So congrats on all the progress. Excited to follow on. Appreciate it. I'm sure you'll be back on the show soon. We'll talk to you soon. Thank you so much. Have a good rest of your day.

1:52:10Before bringing our next guest, let me tell you about Fin.ai. the number one AI agent for customer service. Automate the most complex customer service queries on every channel with Fin.ai. And we have Phillip from Crunched. What a great name for an AI analyst, for an AI Excel analyst, for Excel power users. Just for power users. Have you ever been an Excel power user? No. You always had to have one hand on the mouse? You were never just on the keyboards, guy? Always had one hand. Very soft, very soft. I can hear Andrew Reid losing respect from you all the way from here. He's getting cooked. All the way from the valley.

1:52:50Indeed. Well, he is in the Restream waiting room. Let's bring in Philip from Crunch to the TBP and Ultradome. Philip, welcome to the show. What's happening? Thanks for joining us. Please introduce yourself and the company. Hey, guys. Pleasure to be on. Great to meet you. Michael, actually, from Crunch, will do the last minute switch here. Oh, okay. Good to see you, Michael. The co-founder as well, CEO of Crunched. Fantastic. Maybe I'll give you a two-second description of Crunched then. Crunched is your Excel AI analyst built by and for power users. So it's like this side panel chat in Excel, basically cursor for the world's most popular programming language.

1:53:26And then you just chat with the natural language, and it makes modeling for you. Makes a ton of sense. Very clear value prop. I think everyone who uses Excel wants a co-pilot, but there is a company that's trying to build Copilot and they happen to own Excel. How are you imagining this plays out? Are you going to live in plug-in world? Are you going to live at the OS level and be screen scraping? Are you worried about sharp elbows for Microsoft? How are you dealing with all that? That's a great question. I think Microsoft is for sure going to build a great product. They're building a Copilot for 2 billion Excel users and they're in competition with Google Sheets, right?

1:54:05I think we're building a tool specifically for the top 1 % finance professionals, investment bankers, private equity associates, management consultants of the world who use Excel in a very specific way. So this is more of the 5 million of the Excel users, the top 1%. So that's a bit of the difference. A lot of big, big market, big opportunity. If you build a great product, there's tons of people that will happily pay for it. There's also tons of startups as well going after this opportunity. What do you think they're getting wrong? Or is this just going to come down to actual product quality and working super closely with these power users to make something that actually integrates into their everyday Excel life?

1:54:52Yeah, absolutely. So I think we have plenty of startups going after this opportunity. We don't think about competition too much, but out of the big ones with the most traction, we're the only one with a team that has 10 ,000 plus real life Excel hours in our previous jobs. Me and my co-founder, Philip, in McKinsey and another finance gigs. And I think that really shines through in the product. I think also Crunched is modeling more like a real life analyst and performing more of the real tasks that you do on the analyst floor versus some of the artificial benchmarks you see around. So, for example, Crunch scan, detect mistakes in workbooks, plenty of time is spent in private equity firms and actually reviewing Excel and making sure they are correct.

1:55:37As much time as modeling from scratch, right? And then these professionals typically work with templates, right? And they need Crunch to fill out and augment their templates, not build basic announcements from scratch. We can do that as well, but we're great at working with large models and these sorts of things. How do you think about the enterprise flywheel here? It seems like one of Cursor's main advantages is that they have a really solid data flywheel now from open source developers and developers who are not in an enterprise level contract. I imagine that the top 1 % of investment bankers, consultants, like on day one, they're going to not want you to train on their data because it's going to be not just some code that builds a front end website, but like extremely critical financial information, private information.

1:56:32Like it is probably a higher bar to not letting that leak into a training run. So how do you get a data flywheel going? How do you improve the product iteratively?

1:57:12It's a good question, right? concerned about their security, right? And do live public deals, right? All of this stuff. And so, like, in principle, we do not train on the data of our customers, and we cannot see what they prompt or do, right? At the same time, what we want to do now, and just in record time, closed our fundraise, we want to make sure that we tailor Crunch to every single firm. That's great.

1:58:05we link that into their specific LBO template and then transfer that from like the simple LBO to the advanced LBO and these sorts of custom. What's the biggest deal Crunch has supported? The biggest deal we have supported? That's a good question. I can tell you about the most impactful. You don't need to name the company. Yeah, you don't need to name the company. It was a$500 billion company. They were doing a$1.4 trillion deal. They were doing about$20 billion in revenue. I'm not going to say who it was. Exactly, exactly. No, but I can tell you a real story about the mistake we caught, though.

1:58:38Crunch has this error detection system. Okay. And on a live deal for an associate at one of our private equity clients in London, used the sort of crunch mistake detection system to identify or scan one of his previous models on a real transaction and identified a mistake in the working capital that overvalued the deal by 10 million pounds. Wow. Whoa. You saved his job. Send him an invoice for$5 million right now. You just saved him 10. Give me 50 % of that. That's your seed round right there. Exactly, exactly. Well, congratulations on a fantastic demo day. Thank you so much. Yeah, great to meet you, Michael.

1:59:17We'd love to talk to you more. I live for Excel agents. I'm so excited about this category. It just feels like there's not a... I would love to. Thank you. Well, have a great rest of your day. We will talk to you soon. Great hanging, Michael. Goodbye. All right. Thanks, guys. Numeral.com. What$500 billion company could that be? Numeral.com, compliance handled. Numeral worries about sales tax and VAT compliance so you can focus on growth. Speaking of growth, there's some folks putting Menlo Ventures in the truth zone. Enterprise large language model API market share has been falling for OpenAI.

2:00:00It's been climbing amongst Anthropic, according to Menlo Ventures. Ev Randall puts it in the truth zone over at Benchmark, multi-time TBPN guest Ev Randall. He says, people are quoting this Menlo Ventures chart and extrapolating from it like it's official data from the Federal Reserve or something. It's a small sample survey conducted by an investor in Anthropic. Please calm down. I like that he's pouring some cold water on this. This is from November 3rd. Yes. So at the same time, does, is it possible that open AI's enterprise, large language model, API market shares falling? Sure. You know, they were the only game in town when they launched.

2:00:42And so you would expect their market share to fall a little bit over time. Will be interesting to see. We'll get more data on this. All these companies are going to be public in a couple of years. And so we'll know exactly how it's breaking down. Can't wait. Until, until that happens, We will return to our coverage of YC Demo Day 2025. We have Sava, the AI-powered trust company. Welcome to the show. How are you doing? What's going on? Hey, I'm doing great. How are you? We're fantastic. Please introduce yourself. Introduce the company. Tell us what you're building. Great. Yeah, I'm Nimit Maru. We're building Sava.

2:01:19We're building a new modern agentic trust company that administers advanced trusts. So is this specifically like will and trust? Yeah, so it's trust like will and trust. Yeah, exactly. Yeah, because people would say a trust company could be somebody that makes sure your password doesn't get leaked or something. But this is specifically for agent trusts. How old were you when you realized you wanted to use AI to spin up trust? I'm just kidding. What were you doing before this? uh well my my previous company was actually uh in john's um oh no way batch uh summer 12 batch no way no way what company yeah and uh we so at the time we were building yelthy which was a um we're like you know like the front-facing camera had come out on the iphone so we wanted to build like a telemedicine but we pivoted to being an early uh code education and like tech education company.

2:02:12And that's how we kind of built that. Um, and then sold it in, uh, like, uh, 10 years later. If you, if you hadn't pivoted, you could have been selling math at scale, like some of the other, uh, telemedicine companies, but I'm glad you did. Um, very cool. Did you say selling, did you say selling meth? No, no, I'm just, I'm just, I'm just joking because there were some, there were some, there were some telemedicine companies that went a little bit too far. And, uh, one of The founders is in jail now. They're like, check if the patient's breathing. If they are, give them Adderall. That was going on.

2:02:47No, more seriously, talk about what's, are these Nevada trusts? Like what's happening at the actual like entity layer? Sure, yeah. So we're not drafting the trusts. We will basically like an attorney or like a fintech or legal tech that uses LLM to draft trust. So they would create the trust document. And then once they need someone to administer the trust to be an independent trustee, that's when we would take over. We're getting our charter in Nevada. So we're going to be chartered in Nevada. Maybe eventually we'll go to other states, but that's where we're going to be right now. And yeah, we work directly with attorneys, wealth managers, fintechs to serve as the trust administration there.

2:03:36So do you have no consumer-facing brand, essentially? It's purely B2B at that point? Well, I mean, it is consumer-facing in the sense that the people who will be using it are also the families who have these trusts. But the reason I say we work with attorneys is because generally the families are taking advice from the attorney or the wealth manager about which trust company to choose. Because, I mean, how would a family know even what a trust company is? or so. So we think of them as the ICP. Sure. Are trusts underrated? Yeah, I think they're underrated and they're underutilized. And also right now they're very annoying and expensive to create and manage.

2:04:18And so I think people don't use the power of trusts enough. And that's not to say like, you know, every American or every person can be using them, but definitely a big slab of people, you know, kind of below where right now they're being utilized. Yeah. Do you have a ballpark cost figure for, you know, doing a trust? Like what scale does it start to make sense for customers to even participate in the market to even consider a trust? So I think creating a revocable trust that, you know, owns your house or other assets that's applicable at, you know, at like reasonably, you know, like almost any level like when someone would own some property.

2:05:04Just as soon as you own those. Makes sense. Yeah. But then using something like Sava today, it's generally people who are trying to make irrevocable trusts. And so they would tend to have, you know, like some millions, like, you know, maybe like low single digits, but or maybe mid single digits millions in assets before they start utilizing that. I think that as tech makes it, A, a lot easier and cheaper to create trust in a good way, and also people like us can make it a lot more friendly and modern to administer trust, I think more people will be able to use them. It should just get way cheaper.

2:05:45I mean, if you think about just the YC story of how much it cost to set up a corporation and raise a seed round in 2005 or something, you were looking at like$20 ,000, maybe$50 ,000 in total fees across everything. Now it's like Stripe Atlas, one click, they charge you, what, 200 bucks or something? 500 bucks. 500 bucks. And then the safe is like one second and, you know, administered by a bunch of folks. And like, it's like really, really low, low cost. And that's obviously led to just more entrepreneurship. You would imagine that something similar happens. When the infrastructure gets better, like usage goes up.

2:06:29And even the safe, like I was talking to my co-founder the other day, like the safe is an incredible invention that makes this early stage of fundraising so much smoother. Back when we did it in the Summer 12 batch, it was all convertible notes. And even that, a lot of investors wanted price rounds. At this stage, it's a pretty difficult thing. So yeah, I think when the infrastructure gets better, more people utilize it and more people can take advantage. Well, congratulations on the progress. Thanks so much for coming on the show. Yeah, excited to check the product out. And we'll talk to you soon.

2:07:02Have a good rest of your day. Thank you. Goodbye. Thank you, guys. Let me tell you about Profound. Get your brand mentioned in ChatGPT. Reach millions of consumers who use AI to discover new products and brands. I want to pull up this chart of the day from Code 2. They say, hey, look, there's no Code Red here. It's all Baja Blast because ChatGPT traffic historically dips this time of year. And it's a fascinating chart if you actually zoom in on this Gemini 3 launch day. It looks like people stop using LLMs around Christmas. The turkey's going around. The tryptophan is coursing through their blood.

2:07:41They're getting a little sleepy. They're getting a little sleepy. They're having an extra bottle of wine, and they're taking time off from their chat app, specifically from ChatGPT. This is bizarre that this chart tracks so much with when people do work. You can see that ChatGPT grows in the spring every year up until summer. Then it completely flatlines during summer. Then it peaks when school year starts again and work starts back up. Then it crashes on Black Friday. It's almost like it's a tool used by students and people with jobs. Students and workers, people with jobs. That's everyone. That's everyone.

2:08:15Come on. That's everyone. What about the unemployed? Oh, yes. I don't know. Well, they're the ones that are holding it up. They're holding it down during Black Friday. They're like, I'm still grinding. But clearly, folks did not get the great lock-in memo because the whole point was that you We were supposed to continue to use all the AI apps. Anyway, it's a fascinating chart. I'm sure we'll be digging into it more, reading the tea leaves. But up next, we have Ben from SF Tensor. It's Marcel for GPUs. Welcome to the show. Thank you so much. Please introduce yourself and the company. Great to have you.

2:08:47Hi. Yeah, thanks. I'm Ben. We're building the infrastructure layer for AI researchers. So basically from training models from small experiments all the way up to large-scale frontier training runs, We basically deal with infrastructure to allow you to do all your training runs. Okay, so there's a bunch of different layers going down to somebody that owns the ground, somebody that builds the data center, somebody that racks the GPUs, and then there's the NeoClouds. Are you interfacing with multiple NeoClouds? Are you a NeoCloud? How are you positioning yourself? Yeah, so we work with all sorts of NeoClouds and hyperscalers, and we basically just say we're building above all of them, And so our customers should only be worrying about what they want to be researching or training and not like how the actual technology, like the underlying stuff works.

2:09:34And so we deal with, you know, finding GPU allocations, optimizing for different GPUs. So we also allow you to work with TPUs or AMD GPUs or any of this stuff to allow you to train your models. Okay, so this is specifically for research and training runs and less focus on like actually inferencing on the product side. Yeah, so we focus exclusively on the training side. There's great companies, even from LastBatch, for example, there's Luminal. They do great things for inference. We focus just on training because we think training is a problem that's not been solved by anyone. And there needs to be way more training happening.

2:10:12What are your clients, like, what's the shape of them? I guess there's a lot of focus when people think training, they think OpenAI, Anthropic, Google, DeepMind, right? But take me through the variety, the landscape of folks that you talk to who are actually doing training runs. Who are these folks? You don't have to give exact names, but tell me the shape of their workloads, what problems they're trying to solve, the scale of their training runs. Take me on a little tour. Yeah. So there's a huge variety. I mean, you have on the one hand, you obviously have like the academic or researchers at home who are training like small models.

2:10:50And then you have, you know, larger scale academic research happening. But then you also have startups that have raised maybe, you know, call it$10 million. You know, there's some companies from YC as well who are training models for super niche use cases. And then there's also, you know, companies that have raised hundreds of millions or, you know, up to a billion dollars. There's a bunch of labs actually in that like area who are doing, who are training their own models. You don't just have anthropic. I mean, like the text-based models like LLMs, there's not an awful lot of competition going on there anymore.

2:11:21Things have sort of converged at the top there. But for everything else, like, you know, drug discovery or, you know, protein folding, all of these things are still problems that have not been solved by anyone. Is it correct to say that SF Tensor is a bet that there will be millions of smaller models for specific use cases or one day billions? I wouldn't say billions, but definitely a lot more than there is today, especially just in the modalities that haven't been explored today. I mean, we're all focusing on text, and text is great for a lot of things. But I can't really use a text-based model to do things like, you know, text-to-speech, for example, is another type of model.

2:12:01Or we have protein-folding models. Or all of these things can't really be solved with text. We need models that are specialized in those topics. What about, I mean, we were talking to the CEO of AWS yesterday, and he was saying that AWS launched a product that is actually a checkpoint 80 % of the way done on an actual foundation model. And then a company can come in and add their own data to the pre-train. And then they can do everything else with it. And that felt like an interesting proposition when you think about if you do want a text-based model and you want it to really know your company's data at the core in the pre-train, really know it, not just drop it in the prompt, not just fine-tune on it, actually bake it in.

2:12:45That feels like we're going to see a Cambrian explosion of every company wants their own trained model earlier. They're going to want training workloads for that. Is that something that you think you can play in? Are there already other companies that are working there? How do you think about that? So it's a very unexplored area so far. The idea of basically saying you have like 80 % of the way the model can already form coherent sentences, have basic reasoning abilities, and then I add my own information. I think that's going to be very important in the future just because it allows me to take a base model and then not just do post-training, but sort of continuous pre-training almost, continuing the pre-training.

2:13:28I think there's going to be a lot of use cases that come out of that, and I think we can help there. I mean, we don't really care what you're training on the hardware. If it's an AI training, we can help with that. So, you know, that's definitely something we're looking into. Do you want to ask about progress? Yeah. What kind of metrics were you sharing today during demo day? Yeah. So the metric we're sharing is we launched like two weeks ago and we did$41 ,000 in usage-based revenue since then. There we go. Love it. And how's the round going? We closed the first day of fundraising. I knew it.

2:14:09First day of fundraising. There we go. There you go. I'm not going to dox, but a friend of ours. We got a text message about you. We got a text message about you. A friend of ours just backed one company this batch, and he's known for backing great companies, and he just backed you. So I'm excited for you guys to announce the round soon and come back on and do it on TBPN. Thank you so much. Awesome. Great to meet you, man. We'll talk to you soon. Cheers. Great to meet you. Good to meet you. Let me tell you about GetBezil.com. Shop over 26 ,500 luxury watches. Super intelligence for your wrist.

2:14:43Fully authenticated in-house by Bezel's team of experts. Brad Gerstner on Trump accounts. POTUS was elected on a Main Street agenda to get the rest of America into the game. And that's exactly what this does. Bill Gurley showing him some respect. And we didn't cover it yesterday, but Michael Dell donated$6.5 billion to these Trump accounts. the accounts where children get them, they can't be touched. They're invested, and they compound over 20 years. $250 for a bunch of individuals. And there was some pushback. Some people were saying, well, if you compound at the S &P, even if you compound at 10 % for 20 years, it's only$1 ,000 or a couple thousand bucks.

2:15:26It's not that much money. It's not life-changing. But it's like a piece of one. That's just Dell's contribution. There's going to be other people that are contributing, corporations. There's$1 ,000 from America. Yeah, and there's a whole bunch of other ways to add money to the account over time at birthdays and Christmas and stuff. It's like targeted donations. And the most important thing is that it's a lockbox. It's psychologically a lockbox. So I still stand with the Gerstner accounts. It's incredible. But we have our next guest in the Restream Waiting Room from Locus, Payment Infrastructure for Agents.

2:16:00How are you doing? Welcome to the show. Please introduce yourself and tell us what you're building. First tie-dye shirt ever on the show. I like it. On TBPN, we've done over a thousand interviews. I don't think we've ever seen one. This is unique. I like it. It's a first. It's a first. Thank you. And they, you know, thank you. And so they actually switched me up with the other guy. Oh, I'm Icarus. Sorry. Icarus. Great. Well, Henry Tie-Dye, welcome to the show. Yes, sir. Henry from Icarus, please introduce yourself and tell us what you're building. Yeah. So I'm Henry, founder and CEO at Icarus.

2:16:29My background, aerospace engineer at Georgia Tech. Build drones for NASA and satellites at Orbital. Icarus were building solar-powered autonomous drones that fly at 60 ,000 feet for weeks at a time. Close to the sun. Close to the sun. Not the closest, but out there. Not the closest. And in fact, if we flew any higher, we'd actually fall out of the sky. So we want to stay at 60 ,000 feet. You're like, but we're going to try flying a little higher. Okay. How many hard tech companies were in this batch? I believe five or 10. Yeah. That seems about right. And so I feel like it's been like steadily at five to 10 for forever, basically.

2:17:11Take me through the bear case for stratospheric drones. What I've heard is, you know, people always refer to the SR-71. It's such an amazing plane. It flies, I think, around 60 ,000 feet. The SR-71 Blackbird, it's this amazing Lockheed Martin plane built at Skunk Works. Flies super fast. We can't build planes like that anymore. We don't have it in us. And when I talk to folks, we're like, yeah, it kind of sucks. We can't build that because it's really cool. But we have satellites now. And satellites go way higher and way faster. And so if you need to put a camera over something, we usually just use a satellite.

2:17:49So why not satellites for this use case? Yeah, from first principles, you're 20 times closer than low-Earth orbit. And you can stay fixed over an area. So just from an engineering perspective, it makes a lot of sense. The bare case is pretty much like none of this is new, even what I'm doing, the solar-powered version. It's all been done. It's just been too expensive. So the question is like, can you get the cost down? Can you? How are you doing that? Is it just like being a startup? Are you using cheaper materials? Are you standing on the shoulders of giants? Like what are you leveraging to actually make it?

2:18:28Yeah, we'll talk about the form factor first because I'm on the website, and this thing just looks like a massive, really skinny bird. Yes. It's very unique. It's Icarus1.com. Icarus. Or sorry, Icarus.1. Icarus.1, correct. Yeah, to your point, John, it's about getting the right product specifications for the first go-to-market. Oh, wow. And so, yeah, our first product, it's a 20-foot solar-powered bird. Sure. flies for weeks at a time. Yep. The bird noise is perfect. So it's effectively like a loitering drone that's just sitting at 60 ,000 feet, and I'm assuming it's incredibly light. It's solar.

2:19:14It has a battery, but it can generate solar power on the fly to increase the battery life effectively. Like it's not sufficient to hold it in the air forever yet, but it can stay up over a specific area. So is this primarily like defense applications early on? Who are you trying to sell this to? Yeah, Act One, it's all defense. I do think this is much bigger than a defense company. I do see the stratosphere as a category. And once you kind of are able to make the stratosphere affordable, then there's many things you can do. So one easy example, like, yeah, today you can't really carry very heavy payloads.

2:20:00You can't carry and deliver a lot of power. But what the future looks like, and there's like no laws of physics that says you can't do this, you can essentially take like a Starlink satellite and have that in the stratosphere. And imagine if you had this Starlink satellite that's 20 times closer and fixed open area. So then that's like, that's the future. And what you can do from that, it's, I don't know, it's anyone's imagination. Near term, there's a lot of clear, direct line of sight towards defense and a market there. Again, it's really difficult. It's not a category yet today. There's no real markets, but with defense, there's a clear need.

2:20:40Very cool. How do you actually get the drone up? Is this something that you launch like a rocket, and then it sort of spreads its wings at some point? How do you actually get a 20-foot drone, 60 ,000? in the air. Into the air. Yeah, so we use a balloon. Do you eat it? Oh, use a balloon. Okay. Okay, that seems less violent than yeeting a 20-foot drone in the air. Some drones are yeeted, I believe. This is a real thing. So you use effectively like a weather balloon to take it up. Are you a beneficiary of Starlink? Are we a competitor? No, no, no. A beneficiary. Oh, a beneficiary? Like, can you use Starlink effectively as the backbone for communications?

2:21:21Yeah, that is our beyond line of sight method. Sure. So we have Starlink on it as an option. Yeah, that's very cool. Yeah, fascinating. So how close are you to actually getting this up in the air? Have you flown? Yes. Is it just test at this point? Are you actually going to sell these things? We are selling them today to the Army. Okay. And, yeah, we've done over 30 successful stratospheric flights, successful demos with Special Ops Command, SOCOM, and the Army as well. and we have, oh, there you go. There you go. There you go. Yeah, super impressive traction. I noticed, is it Ronak on your team?

2:21:58Was that Red Bull Racing before this? Oh, no way. How cracked is Ronak? That's awesome. He is very, very hardcore. I imagine if you want to make something that's ultra light, ultra durable, he's your guy. That's right. That's correct. Yeah, so a third of our team is SpaceX Tesla. Ronix worked at Tesla before Red Bull Racing and also SpaceX as well but he's definitely character yeah awesome well great to meet you I'm excited to to follow along how the round already done how's it going yes raised a lot of money um there you go hit the gong again John There we go. Yeah, buddy. Yeah, buddy. Yeah. Just coming on.

2:22:47Absolute legend. You're a TVPN legend. Yeah, thank you. We might have to make a TVPN tie-dye shirt in your honor. Yeah. Let's do it. I love it. Thank you, Todd. Very cool. Well, have a good rest of Demo Day. Congratulations on all the progress. Very excited to see these up in the stratosphere. Just don't fly them too high. Yep, exactly. Perfect. All right, Jordy, John, thanks so much. Have a good rest of your day. Goodbye. What a legend. I need to know from you if we have some breaking news that we can share right now. It sounds like we might have some surprise guests join the stream, so stay with us.

2:23:27I will also tell you about adquick.com, out-of-home advertising made easy and measurable. Plan, buy, and measure out of home with precision. um also uh people are calling for google to make glasses now because uh google glass doing this they did this 20 years ago practically google glass uh and they're working they're still working yes yes yes yes but through partners through partners so so uh they've done the google pixel they've done they've done a variety of of hardware devices and they're and they are working on uh some augmented reality glasses again but they're certainly not making as much of a you know big push, media push as they did with the original Google Glass, which was like it dominated the news.

2:24:12And it was like the future is here. And then the product didn't really get to escape velocity and is sort of remembered as a failure. But it wasn't a failure. They were just early. They were just early. And that's the important thing to remember. But we have our next guest here in the Restream Waiting Room. Let's bring him in from Locus. Welcome to the show. Thank you so much for taking the time to join us. Please introduce yourself and tell us what you're building. Yeah, for sure. So I'm Cole Dermott. I'm the CEO and co-founder of Locus. We build payment infrastructure for AI agents. Okay. MCP currently doesn't have payment infrastructure.

2:24:44That's why you exist. Is that what's going on? Yeah, basically. Plus trust. Trust is a huge part of it. Okay. Interesting. Are people actually solving this manually right now? Are there agent-to-agent payments that are happening right now? Or is this something where we're thinking in the future, they will all be flowing stable coins to each other in the future? I think agent to agent isn't really adopted yet. What we're looking at right now is more so developer use cases of, if you're familiar with X402, paying for API endpoints on a pay-per-use basis or potentially doing payouts to people. The way I like to explain it is, historically, payment automation has been deeply rooted in conditional automation, a series of ifs, ends, ors, et cetera.

2:25:29Now with agentic payments, you open up this new frontier of contextual automation, right? And that's a pretty huge evolution. How do you imagine the first adoption of agent-to-agent payments or even just payments for agents broadly playing out? Me and Jordi have been talking about this with the agent-to-commerce stuff. We're using ChatGPT. We're using Gemini. There's all these times when I run into a paywall and I can tell it's running into a paywall. It's like, oh, I actually can't tell you about what's going on on that website. And I'm like, oh, you actually could if I gave you my credit card.

2:26:05I know you could, but they can't. And it seems like that's something you could potentially help with. But how do you see the first early adopters using your service? I see the first ones as really developers building these autonomous agents, right? Being able to essentially pay for services as they do their workload in the wild and discover those services autonomously, right? In terms of like the more commerce side, I think that'll be an industry that evolves over the next few years as trust is really developed. Because frankly, on a wide scale consumer basis, that's really the biggest barrier right now is trust rather than tech.

2:26:38Yeah. What kind of numbers did you share during your pitch or are you planning to share? Yeah, so we processed around 3 ,500 transactions and have around 80 projects built using Locust so far. Amazing. That's amazing. What were you doing before this? John's got the gong for you. Do I ring? Hit it, hit it. What were you doing before this? Yeah, so I interned at Coinbase. I was one of the people who helped build Coinbase business over there. My co-founder was one of the six software engineering interns at ScaleAI. Studied CS at Waterloo. Business at Wilfrid Laurier. Was the finance athlete at Waterloo Blockchain.

2:27:13Waterloo mentioned. Fantastic. Well, thank you so much for coming on the show. Congratulations. Yeah, great to meet you. No problem. And I'm sure we'll be seeing you soon. Follow along. Have a good rest of your day. Thank you. We'll talk to you soon. Thank you for having me. Let me tell you about Wander.com, Book of Wander with inspiring views, hotel-grade amenities, dreamy beds, top-tier cleaning, and 24-7 concierge service. It's a vacation home, but better. And we have some surprise guests, I believe, joining in just a second. We will have them in. Jessica and Paul, you may know them. They started a small startup accelerator called Y Combinator.

2:27:48Yes, that's right. And it's Jessica's second time on the show. We had a fantastic conversation with her the last time she was on the show. We talked about the get-your-bag culture and the carpetbaggers and just all the cultural ebbs and flows of Silicon Valley and where we are culturally. So I'm very excited to bring in Jessica and Paul, the founders of Y Combinator. They are living legends. Living legends. There they are. You're live now. Welcome to the show. Welcome to the show. Thank you so much for taking the time to talk to us. Hi, guys. Hi. Good to see you. This is so fun with you guys here at Demo Day.

2:28:27It is. It is. It's always great. This is our fourth Demo Day live stream talking to tons of founders. It's always fun picking out. I can't wait for the 400th. I got a ways to go, but I'm excited. A hundred more years. We'll make it. Great to have you guys on. What's it been like today? It's been crowded. It's buzzing. And by the way, this is our first demo day that we've been to in a few years because we're in England and can't manage to come back for it. It is just buzzing. The energy here is just kind of like what I remember in the early days of YC and the investors are all excited to be here.

2:29:05It's magical. I'm on a high. Incredible. There's a lot of stuff happening. Yeah. Yeah. How are you thinking about, there was this moment a few years ago where I think in tech, maybe we were afraid to admit it, but it felt like a lot of founders and a lot of entrepreneurs were sort of grappling with this idea that OpenAI might just build every startup and there might be no more ideas. And people were a little bit nervous about that. Of course, they went and built companies, but it feels like now things have calmed down a little bit. And the founders that we talk to are building with more confidence.

2:29:40Have you noticed anything in the founders that you talk to in an ebb and flow of just the confidence with which they view the future right now? No. Founders weren't really worried that OpenAI was going to eat them. I mean, maybe they were in denial, but whatever reason, they weren't worried about it. They're too busy working on their companies. They're making their thing. They're trying to get users, OpenAI eating them in some theoretical future three years from now. They're not thinking about anything three years from now. We had another, we were talking to Harj about this, this idea that potentially, I don't know, we're just in a new era where it has become easier for a small team of scrappy entrepreneurs to sell to Fortune 500 companies, to sell to the government even.

2:30:30Do you feel like something has materially changed and go to market for YC companies? Well, if you're an AI company, all these big organizations now have some bureaucrat who's been told, you're supposed to AI-ify our organization, right? And he's thinking, damn, I have no idea what to do. And so some startup shows up and says, will AI-ify your organization? He's like, great, come in here. Very different from the way it used to be. I mean, if you show up with other products for the big company, they'll still tell you to talk to the hand. But nobody's coming to them with AI things except startups, so they have no choice but to talk to startups.

2:31:10What about this tweet that you put out just recently? We were sort of debating it earlier, this idea of the circular economy selling to other startups. There are a ton of benefits, obviously. Startups are very discerning. If you mess up and don't deliver the product that they're buying from you, you might hear about it publicly. they'll churn, they'll talk to you, they'll talk to their friends. But are there any risks from that that you caution entrepreneurs on if they are going to be selling to a lot of startups? Do they have to message anything differently? Is there anything that they need to be doing?

2:31:45Well, you have to not suck because startups are discerning. You can't like have some bullshit product and sell it based on a bunch of hype. It's got to actually work because they don't have time to mess around with things that don't work. And they're very sharp observers of technology. They're run by the founders themselves usually at that point. So you got to actually be good. I'd love to reflect on how marketing and launching startups has changed over the last few decades. Jordy, we had Clad Labs on, which we had a really fun time talking to them, but they sort of went viral for the wrong reasons.

2:32:21They were offending people. Well, in their view is the right reason. Yeah, in their view is the right reason. They were offending people by putting gambling in your IDE. So the software engineer can be gambling while they're coding, I guess. Yeah, and it felt like this year, the concept of using rage bait both at the marketing level and the product level kind of exploded. I guess the question is, has intentionally pissing people off been something that YC founders have utilized across the eras to get attention? Is it really new? And that sort of technique sounds like the technique that would be popular with someone you'd describe as a bit of a scammer.

2:33:03And the thing about these scammers is they don't make the giant companies. They don't have a long-term focus. They're not earnestly doing engineering. They're thinking about what's some gimmick I can use to get ahead, right? And so long-term, they don't matter. You can skip the companies that do random shit like that because they're never going to be that big. And of course, I haven't heard of the term rage baiting either. It's the Oxford word of the year. So you can go look at their definition. It's so interesting. It's getting attention by making people mad. I know what it means. Yeah, and I had written an article, and Gary and I had a nice back and forth where I basically said, like, in startups, you need to build a coalition of people that want you to win.

2:33:54This is like talent, the media, investors, customers, et cetera. You don't even have to do that, actually. All you have to do is make something really good and find the people who want it. You don't even need a coalition. You think like when Facebook was taking off at Harvard, there was some coalition of investors and media that wanted it to take off. All that mattered was that Zuck had this thing and everybody at Harvard wanted to use it. That's all that matters. That's small, intense fire, right? were when Apple was getting started and the users were like the people at the homebrew computer club, right?

2:34:26The media didn't know about that. There was no coalition. Zuck did a little rage baiting early on. You are an epiphenomenon. Zuck kind of did a little rage baiting. He kind of did rage bait with the Hot or Not app. That definitely enraged a lot of people who didn't want to be raiding. Yeah, but he didn't do it deliberately. No, exactly, exactly. And I was thinking about the Airbnb example, like the whole Obama owes and Captain McCain's crunch, like those cereals that they made. That was sort of a side quest for them. That was simply to get attention from the press. Interesting. That's all. And make, no, actually it was to make money.

2:34:59It was to make money. That was before YC. They didn't have any money, remember? They were dying. Yeah. They needed to make money. They went and got these like off-brand Cheerios and they glued together the boxes themselves just to make money. I don't think they knew they were going to make money. Eh? We're going to have to consult Chesky. I'm pretty sure that was mainly to make money. What's it like being back in San Francisco? Sunny. It's fabulous. The energy is so great here. I'm just so happy to be back and so happy to be around startups right now. I'm having a great day, if you can't tell.

2:35:35It gets better every time we come back. Like Daniel Lurie is really cleaning up the city. Every time we show up, it's like a little better. That's great news. I was asking, like, how far back have we gone? Have we gone all the way back to when Ed Lee died? Not yet. We're like, but we've turned the clock back to maybe two years into London Breed. Oh, that's good. Okay. Yeah, that's great. I have one more. I want to think through this concept that's been sort of lightly bandied about in the startup discussion ecosystem. system, this idea of the deals guy era that you can actually build a business now by being more of the business person, the more of the deals guy and less of the, of what I remember about the, the Y Combinator promise, which was, uh, just the earnest hacker, the earnest hacker.

2:36:29And it feels like there's a lot of people that are saying, yeah, but there's actually a way to go and get this person just marshal the Capitol and, you know, do something that's just been forgotten, and not necessarily discover something new. And I was wondering if you have any reactions to this idea that increasingly there are entrepreneurs that sort of get really big. Who knows if they win, but they seem to win on the back of just raw deal-making talent as opposed to raw engineering leadership. Maybe in enterprise more. You know, like enterprise, you like sell crap to CTOs instead of selling good stuff to programmers.

2:37:13So salesmanship has always mattered more in enterprise. I have one observation from this morning session of demo day. Everyone, most everyone that presented this morning is an earnest hacker. I said to the person next to me, they're all nerds this time, like 100%. I love it. Yeah, you know, if anything, YC drifted too far away from funding earnest hackers. And so YC for the last few years has been focusing more on like getting back to the essentials, back to the roots. And so if anything, I would say YC batches are more like a higher percentage earnest hackers now. Yeah. You know, honestly, I would still bet on earnest hackers.

2:37:55Yeah, I agree with you. Do you think that that is what the essential skill set of YC leadership needs to be? Because I don't want to discredit all the hard work you did in the early days, but you didn't have to fight the fact that there were people out there writing blog posts of how to reverse engineer and make it look like you're an earnest hacker when in fact you are the carpetbagger. And now there's a whole industrial complex for how to fake your way and make it appear that you're an earnest hacker when in fact you're not. If the YC partners are themselves hackers, you can sniff out a faker like that.

2:38:31It's not even a problem. Yeah, yeah, yeah. But that seems like the main way that YC creates value these days. We'll just be continuing to hold that line, essentially. What do you think is your most? Yeah, I think here's something that will reassure you. If you think, okay, is the earnest hacker thing, did that just work for a while and now maybe it's over? Isaac Newton was an earnest hacker. right it's way older than startups yes this is this is what wins uh what do you think is your most underappreciated essay because a lot of them are sufficiently appreciated the thing is i don't know how much people appreciate them i don't know how much people appreciate different ones so it's hard to say um how to do great work is pretty good but I think people like that one.

2:39:22Yeah. Right? I read Life is Short at least once a year, but people like that one too. Yeah. I don't know. I don't know. That's a weird question. You'd probably have to look at inverse page views, which gets the least page views historically over the past year, let's say. Yeah, if I was looking at a list of page views, I could tell you. Okay, well, maybe we'll have to follow up and get some breaking news. Yeah, that's very funny. Do you have anything else, Rory? What else? Paul, are we in a bubble? No. No, everybody is always saying we're in a bubble. Like every year people say we're in a bubble.

2:40:00Every year people say, like, the valuations at DemoDye, they're too high now. I mean, they were saying this back in like 2010 when the valuations were like$4 million. And now they're like, what,$30 or something typically. So people are always saying stuff like that. And I don't know. I don't think so. I think I'll tell you. I think like AI is very highly priced, but it might not be overpriced. That's the interesting thing. Is it as big a deal as prices seem to suggest? It could be maybe even bigger. It's definitely real. It's not hype. The AI is real. Are foundation models good at writing Lisp?

2:40:50I think they would be good at writing Lisp. Yes, yes. Because they're good at writing things that have a lot of training data out there. There's a lot of Lisp source code. So I think they'd be fine at writing Lisp. How are you using AI in your life? I just use it like ordinary people do. I ask you questions. Sure, sure. Very boring answer. That's a good answer. It's not like, oh, I stringed. I'm training my own model to do a better Google search. No, no, no. I haven't actually written anything using AI. You know, I feel bad. I really should write an LLM because you can't really understand this stuff unless you've written one.

2:41:31I should write an LLM, but I haven't done it. Yeah, didn't Carpathie publish a whole chat GPT from first principles type of thing? It's a really fun project. To teach himself. You know that's why he did it. Well, he has a new company that's an education technology company. And I believe that the main course will be teaching yourself to build an LLM, teaching yourself to build a chatbot effectively, which would be very cool. That's what I tell high school kids. I get all these emails from high school kids say, I'm working on a startup to introduce founders to VCs or some crap like that. And I say, don't start a startup.

2:42:03Get good at technology. Write an LLM. Then you can start a startup. Do you think, reflecting on the history of YC, do you think it's fair to try and create a concept of eras around what the key insight was? I remember a lot of people saying one of the first key insights was just this idea that you could take someone fresh out of college and actually give them money and they could go and build a business. They didn't need$10 million. They didn't need 10 years of experience in the enterprise. Or an MBA. Or an MBA. And then maybe the second era was thinking that maybe the same rules applied internationally.

2:42:43And that was like a second wave of entrepreneurial energy that was unlocked by the YC ecosystem. We always had international. We understand countries aren't all that good. But do you think there are any other underappreciated aspects of the YC strategy? Or is it really just as simple as fun? Well, there were things we didn't appreciate in the beginning. Yes. So, for example, we didn't understand that as a byproduct of funding all these companies, we would create this alumni network. We had no idea. But the alumni network is enormously important. It's out there now. All these alumni are investors.

2:43:21Yes. It's staggering how many are investors now, actually. Yeah. It's amazing. It's like taking over Silicon Valley and we never had any idea that was going to happen. Okay. On the alumni network, is it fair to characterize YC as a bit of a union against venture capitalists? Yeah. It's a lot like a union. A nice union. Yeah, because if you attack one individual, one founder, if you fire the founder after investing, you get board control from them and you oust them, that might make its way into the rest of the YC community. And it overall raises the level of founder friendliness. Is that correct?

2:44:01You know what, though? It's not simply one-sided because if founders screw over investors, if they do a handshake deal and then refuse to go through with it, we would tell them not to do that too. We want everybody to play by the rules. Yeah, and behave well. Because the big wins don't come from breaking the rules. The big wins don't come from little cheats that get you 2x multiples in a world of 1 ,000x returns, right? It's for the same reason people in Silicon Valley don't focus a lot on tax evasion. Because what's tax evasion going to get you? 2x returns in a world where getting the right startups will get you 1 ,000x returns.

2:44:38Yeah. You know? don't. Do you think that the process of founding a company, raising money is at the end of history in terms of efficiency? Like the safe is the most efficient document we will ever have, or do we need to speed things up even further? Well, C. Levy, Carolyn Levy, invented the safe, and she also invented the convertible note that everybody used before it. So she has twice rewritten the rules. She's twice recreated the chessboard that the game is played on. If she thought there was a better thing than the safe, she probably would have created it. Maybe she has a third one in her. We should ask.

2:45:20We'll ask her. It's a trilogy. Trilogy's a very popular. Oh, yeah. Okay. Yeah. And you could ask her that, John, when you come on our podcast. We'd love to. I'd love to. Is there anything wrong with the safe? And if there is, why hasn't she fixed it already? So probably not, because C. Levy's not slack. If there was anything missing, she would have made a new version. Yeah. I mean, from my perspective, it seems like it's worked. What problem in the world did you think a YC startup would have fixed by now? Think like housing affordability or any of these sort of major - You know, we don't have any grand strategic vision for what the startups do because the founders know that, not us, right?

2:46:02That would be like asking a publisher, what novel do you think, would you have expected someone to write? Good publishers, they let the novelists write the novels. So we just try and find good people. What do they do? Whatever these good people are interested in, any preconceptions we had about what they should do would just be adding noise to that. How do you think about coaching folks through pivots? It feels like we're in an era where there's a lot of companies that are still finding product market fit. Pivots are probably just as common as they always have been, but everyone has an order of magnitude more money.

2:46:40If anything, more common. Yeah. Yeah. I think that it's more common. You talk about new ideas with startups all the time in your office hours. This is one of my specialties. Yeah. When people are just dead in the water and they need to get a new idea, they often get sent to talk to me and we cook up something. Has the advice changed if someone comes in and says, hey, I have$200 ,000 raised and I I have me and my co-founder are living in an apartment together and we need to pivot versus I come in and I say, hey, look, I got five million bucks and I got 20 employees already or something like that.

2:47:1620 employees. I don't know. It's happening, right? You do see this, right? Well, no. Usually they don't have 20 employees. Okay.

2:47:27Usually, I mean, that would be alarming. That would be very alarming because they're probably not. But it feels like there's so many companies that just employees so much. Those 20 employees constrain the idea you're going to have. If you just have the founders, you could do anything. If you already have 20 people, you either have to fire them or do something that those 20 people can do, right? Which really constrains your options. So the problem with the 20 employees is not the cost. It's that they limit what you can think of, you know, which is why you shouldn't hire. Just don't hire. What kind of guidance do you give to founders that are feeling a pressure to go from zero to$100 million in ARR in like three years or whatever?

2:48:06like the new gold standard is? What I tell startups over and over and over is all that matters is growth rate, not the absolute numbers. Because mathematically, you'll see if you try simulating it. If your growth rate is high enough, it doesn't matter what the absolute numbers are. You'll get there. And so you just get a really good growth rate. And so the great thing about focusing on growth rate means you can focus on startups. You can sell stuff to startups for cheap instead of having to go and do these big deals at big companies that take a long time and make your products stupider, right?

2:48:38You can sell things to these quick, quick deciding early adopters. And then you just get more and more of them and your company grows by several percent a week. Eventually it's going to be huge. Are you still recommending to folks who ask for advice for kids that they should learn to code? Yeah. Oh yeah, yeah, yeah. I still tell people that. Or at least learn technology. It doesn't have to be coding specifically. You could learn how to make rockets or drones or work with lasers or gene editing or something like that. But you should do the stuff and not just like play house pretending to start fake startups in some business plan competition.

2:49:20I tell everyone who says they might want to start a startup someday to learn to code because it's the most important thing you could do. That and save your money. Yeah. That's really good advice. And no one likes to hear that, by the way, but I tell them anyway. Yeah. No, no. We give a lot of advice. People come and they want advice. It's like if you went to the doctor and you said, doctor, what can I need to be healthier? And the doctor says, eat less and exercise more. And you're like, oh, I was hoping you'd say something else. Right? Well, that's what it's like when they come to me. They come to me for advice and I say the startup equivalent of eat less, exercise more.

2:49:56And they're like, oh, isn't there some trick I could use to get virality? Couldn't I get virality instead? Just do the startup equivalent of eat less and get more exercise, which is build stuff and talk to users, understand your users and be good at building. That's the recipe. It was in 2005 and it's just as much the recipe now. Yeah. How many startups do you think YC will have per batch? decade from now because I think in a perfect world we have a lot more earnest hackers and they can apply to YC and and if they meet them I know you're not setting targets and there's not like a specific you know acceptance rate that you're trying to track but we we feel like YC is one of the most important institutions in the world and ideally it can be bigger but but maybe there's some...

2:50:55No, no, no. They will be bigger. They will inevitably be bigger because there's this secular trend of more people starting startups. Yeah, do you think we're early in this trend? I mean, it feels like there's so much... It's now you can create a startup. You can create a C-Corp in a few minutes, right? There's all this sort of underlying infrastructure that's been built that is reducing friction to starting companies. You can ask ChatGPT, how do I start a business? And it'll give you a good playbook and that maybe helps somebody that hasn't found the YC blog yet figure out how to get going. We're the training data, even if they don't know it.

2:51:32Yeah. So will more people start startups? Yes. If you talk to like ambitious 15 year olds, they all want to go start startups. Nobody wants to go work for some company and work their way up to the corporate ladder anymore. The whole idea sounds so like sounds so like 1980s um and there's a lot of earnest hackers the limit and the limit you think like what's the limit so the limit is what people want right that's what startups do they make something people want what are what are people's people's wants they're limitless not literally limitless because eventually you run out of atoms in the universe but for all practical purposes in the near term, people's wants are infinite.

2:52:16And so there's infinite demand for good stuff you could make. Well, that's a great place to end it. We have to catch a flight. Thank you so much for taking the time to talk to us. Yeah, thank you for everything you guys have done for the industry and the world through YC. It's an honor to cover every batch and it's been great having you guys on. Yeah. Nice to meet you. Thanks for having us. I love you guys. Yes, we love you too. Thank you so much. Have fun in SF. Have a great rest of your trip. We'll talk to you soon. Thanks. Goodbye. We have to hop on a flight. Did you hear that, John? I hear it.

2:52:52Yes, I hear the goat noise, the sound cue. That one's a little bit subtle. I think that there's a lot of people that might not pick up on why they're hearing this random goat noise. If you know, you know. But if you know, you know. And also, if you want exceptional sleep without exception, you go to 8sleep.com. You fall asleep faster. You sleep deeper. You wake up energized and we should close out. There's a lot of stuff going on. Deal book summits going on. There are debates raging on the timeline, but we will have to cover them tomorrow. We will close out with a congratulations to Ed Elson, the co-host of the Prof G Markets podcast.

2:53:30I love his bio because he says he's not Prof G's son, even though they look somewhat similar. He had a viral post yesterday because he got into Forbes 30 under 30 and he said, I'll see you guys in prison. He said, woke up to learn I made Forbes 30 under 30. Congrats to the other winners. Can we play this before we jump? Can we play this? Oh, Gary Tan's in the chat. Ollie's in the chat. Gary, we hope you feel better. Tana's in the chat. Gary, feel better. Welcome to the show. Thank you so much for making this happen. We're very sorry we couldn't be there in person, but we had a blast. we went on a whirlwind tour.

2:54:07We talked to tons of YC founders and the state of YC is healthier than ever, stronger than ever. Gary's got elementary school or preschool. It's so rough. I've been there, man. I've been there. It's very rough. Well, we hope you get well soon. Team, we need to definitely send some soup or some flowers to Gary Tan as soon as possible. and we will see you all tomorrow. Thank you for tuning in. Thank you to Y Combinator for hosting us and all the founders. It was a whirlwind tour and I'm very excited about a lot of these companies. Yes, we will talk to you later. Cheers. Goodbye.