TBPN - 🟠 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

Starting point is 00:00:00 You're watching TVPN. We are live from the TBPN Ultramm. It's Wednesday, December 3rd, 2025. You probably thought we were at YC Demo Day in San Francisco. We got to go to New York City tomorrow. We're interviewing Jim Kramer, a bunch of other folks. Today, actually, yeah. We're traveling today.

Starting point is 00:00:16 We are traveling today. So we couldn't, we unfortunately couldn't be in San Francisco at the Palace of Party rounds. But we still have a ton of YC Demo Day content lined up for you, folks. We got Harsh Tagar coming. on at 1145. Then we got Clad Labs, the makers of Chad IDE, the company that

Starting point is 00:00:38 yeah, the company that sparked, they buy their own by their own definition. They call themselves the brain rot IDE. We're getting to the bottom of that story. And then we're talking to probably 10 or 20 other founders. Going to be asking them how they're building their

Starting point is 00:00:53 businesses, what they're building, what they're seeing. It's always a fun time to check in with the good folks over at, at W. And of course we will be telling you about ramp.com. Time is money. Save both. Easy use corporate cards, bill pay,

Starting point is 00:01:06 accounting and a whole lot more. Aye, aye. And I will also be telling you about fall, the generative media platform for developers. Develop and fine-tune models with serverless GPUs and on-demand clusters. So today I wrote about will AWS buy TPUs from Google? In the front page of the Wall Street Journal's business and finance section, they're singing the Traneum chips praises.

Starting point is 00:01:35 Amazon chips. Amazon's chips pose risk to Nvidia. The whole week we've been talking to people. Is that clickbait? I don't know. What we're going to find out. We'll see. It certainly doesn't seem, you know, good to have more competition in the market.

Starting point is 00:01:52 And Tay Kim came on the show yesterday to talk about how Nvidia was strong and really was not. going to face significant headwinds from the TPU threat. Of course, Dylan Patel over at semi-analysis wrote a 10,000 word piece all about how the TPUV-7 was pretty good, and Anthropic was going to be buying some, and they were also going be leasing some, and they maybe had some really, and that sparked a lot of backlash from Nvidia Bulls. And also folks who are really tied to AMD, they're upset about it. There's a lot of losers if Google winds up winning with TPU.

Starting point is 00:02:32 And so the losers came out to fight, apparently. But let's read through. Let's just get the facts down from Amazon's Traneum 3 launch. We, of course, had the CEO of AWS on the show yesterday. And I asked him about this question. Will Amazon be buying TPU? I think that's an interesting question. But first, let's see what Amazon's actually planning with their own

Starting point is 00:02:57 AI accelerator. He did, no cliffhanger here. He did not say yes or no. He just kind of. I think you can read between the tea leaves and understand how the decision will be made, even though the decision has not been made yet. But we'll go through that. So Amazon.com is the latest big tech company to muscle in on NVIDIA's turf.

Starting point is 00:03:17 Give me a sound cue from the fall sound. How about this? There we go. That's right. On Tuesday, Amazon Web Services announced the public launch of its training three. custom AI chip, which it says is four times as fast as its previous generation of artificial intelligence chips. 4X speedup.

Starting point is 00:03:35 That's actually very significant. That's great. The company said Traneum 3 produced by AWS's Anapurna Labs, fascinating company, acquired a decade ago for around 350 billion, so it's pretty small acquisition, actually, 350 million. In AI, you never know. But back then, you start a custom silicon company. you could barely clear nine figures on the way out the door. But Inapurna Labs has been working on custom silicon for Amazon for a long time.

Starting point is 00:04:05 They actually do have a custom CPU at AWS to accelerate CPU-based workloads. Then for the last few years, they've been working on GPUs or A6 for accelerated workloads. And so this custom chip design business, Anapurna Labs, can reduce the cost of terms. and operating AI models by up to 50% compared with systems that use equivalent GPUs. The chips are meant to provide a stronger backbone of computing power for software developers like Dean Leiterz, Lydersorf, the co-founder and co- and executive, chief executive officer of the startup, Descartes, who we had on the show. And Descartes is valued now at $3.1 billion. Let's go. So if you don't remember Descartes came on, and Dean was doing live AI video generation while he was doing the interview with us. It was really crazy.

Starting point is 00:05:02 Yeah, he basically, yeah, it was real time. He looked like he was in a video game, but it was happening with little to no delay, really, really cool demo. Yeah. Before we move on, let me tell you about Restream. One live stream 30 plus destinations. If you want to multistream, go to Restream. So he said his company had a breakthrough. enabled by a Traneum 3 chip, by the Traneum 3 chip, after trying out several other competitor

Starting point is 00:05:28 chips, including Nvidia's processors. Dozens of programmers and AI researchers from his San Francisco-based company had been trying four months to train a version of Descartes flagship AI-powered video generation application known as Lucy, that would be able to render footage in real-time without bugs or hiccups. ADBS gave Descartes early access to Traneum 3 after meeting. with the startup and being impressed with the founders. The company was two weeks into a marathon coding session in a rented house in Silicon Valley,

Starting point is 00:05:58 which I think he took us on a tour of while he was in wizard land and AI-generated sci-fi world. It was very fun. That a few of his employees were celebrating wildly behind him. Wait. Well, that's like a reference, I think that's a reference to the actual call

Starting point is 00:06:14 that I'm referring to. Weird. This is very weird reading the journal. Oh, yeah, I've experienced this. The moment that I saw it worked, I saw four people just start jumping up and down, said Dean. The next question was how fast can we get it to market and start changing industries with it? The launch of Traneum 3 is the latest broad side against Nvidia, which dominates the GPU market. A flurry of deals in recent months have caught the attention of investors indicating that more AI firms are seeking to diversify their suppliers by buying chips and other hardware from,

Starting point is 00:06:49 companies other than Nvidia. So meta platforms is in talk with Google to buy billions of dollars worth of advanced AI processors known as TPUs. And OpenAI has struck deals with Nvidia rival AMD as well as Broadcom. And so very exciting that Descartes got good results out of the Traneum chip. That's awesome, obviously. I'm sure everyone over at Amazon has been working very hard on that. At the same time, we've heard that Anthropic maybe didn't have that great of an experience with Traneum, and that's why maybe they're moving over to TPU a little bit more. Even though Amazon remains a major shareholder in Anthropic. And so my question is, will AWS buy TPU from Google?

Starting point is 00:07:30 I asked Matt Garman that question. You asked me that question. Yes. I said they will be mocked. They would be mocked. Which is ridiculous. And we'll get to why that's ridiculous. I mean, first off, it's just, it's funny to mock anyone for something like, you know,

Starting point is 00:07:48 related to their semiconductor supply chain and what they rack in their massive data centers. AWS is a massive business. Where I just like, please, please my arch rival, can I please get some chips for my data center to compete with your data center? Okay. Well, let's actually go to what Matt Garman, the CEO of AWS said on TBPN yesterday, because I asked him, will you be buying TPUs?

Starting point is 00:08:10 And he said, hey, look, we're very excited about Traneum. And I think it has, and we think it has enormous potential. And we absolutely think there's a benefit to. optimizing every layer of that stack. And so he, you know, people were joking on the timeline, you know, oh, there's this new Tranium chip and somebody was like, all five people using Traynium are ecstatic, you know, that there's this new news. But probably ballistic here says, Amazon's so bad at hype. Traynium is used by 500 million people through bedrock, but their marketing team just can't. AWS is undervalue, blah, blah, blah, blah. And he's obviously a bull on the

Starting point is 00:08:48 stock. But what's interesting is that like, it is deployed. He says, I'm out some of their GTM staff today. Let's just say you'll have years to accumulate stock at cheap prices. Very funny. And so, and so like, yes, there obviously is value, even if Traneum winds up being for a particular niche. Like, maybe it's for real-time video. Like, maybe that's what it gets really good at. It can get really good at diffusion. It can get really good. It doesn't need to just be, like, your ASEC can be honed and honed. honed and honed to fit a particular work. The thing with real-time video that's interesting,

Starting point is 00:09:22 something that Descartes is focused on is working with live streamers, specifically on Twitch. Amazon owns Twitch. Oh, that'd be cool. That makes that kind of partnership more interesting. I like that. And so, but so obviously there is value to saying,

Starting point is 00:09:41 hey, if you go to AWS, you can get bedrock and some services that have been fine-tuned specifically for Traneum. You go all the way down. you're going to get very good performance because we have a stack from top to bottom that's very efficient. But at the same time, if you're trying to do something

Starting point is 00:09:55 that's sort of like not within the training ecosystem, you might have a rough go. You might wind up on a different chip. But he did say something. He said, we are going to support choice for our customers as well. And so we'll continue to offer GPUs from Nvidia as an example.

Starting point is 00:10:12 And we have a very tight partnership there. So this idea of customer choice I think is important. And if you go back to Jeff Bezos, he said, we're not competitor obsessed. This idea that Google is there arch rival, that's not in Amazon's DNA. Jeff Bezos said, we're not competitor obsessed.

Starting point is 00:10:30 We're customer obsessed. We're customer obsessed. And so if the customer says, look, it's great that you acquired Anna Perna Labs for $350 million. I'm really happy with what you've done with Trainium 3. It doesn't work for me.

Starting point is 00:10:43 I'm the customer, and I want you to give me an Nvidia GPU in your server or in your data center, or I want you to give me a TPU in your server. They might do that because that's actually in Amazon's DNA. Yeah, and then the follow-up question is, is there any world where Google sells TPU to Amazon? Maybe, I don't know. Already, they are partnering. Like, this was another partnership that came out that Ben Thompson actually wrote about in intrateree, which you should go subscribe to. So separately, there was an announcement of an AWS partnership with Google Cloud. Now, they aren't buying TPUs, but what they're doing is they're enabling customers to establish

Starting point is 00:11:23 private, high-speed links between the two companies computing platforms in minutes instead of weeks. And so the general idea here is that Google has some amazing AI capabilities that customers are just struggling to match on AWS at this point. And the same thing's happening on Microsoft as well, because on Azure. you have access to open AI models that you might not have access to on on a tobS. And so even though your whole infrastructure might be on AWS, you might be going back and forth to GCP constantly, or you might be going back and forth to AWS all the time being like, oh, I got to go over to a ABS, got to go back.

Starting point is 00:12:00 I got to go Azure, back to AWS, back to AWS. And so Amazon finally just said, like, hey, look, we have a partnership and we're just going to create a dedicated pipe that puts these two systems together. And so companies used to think about AI as a special piece of their application. So it would be fine to bounce around to another cloud to get the best possible results. But if the next generation of companies, I'm sure we'll talk to some of the AI-focused YC Demo Day companies today about this. I hope there's at least one. I hope there's at least one company that's doing something with AI.

Starting point is 00:12:33 That would be a real treat. And if you're just tuning in, YC Demo Day coverage starts in 30 minutes. Yes. But, so it used to be fine to bounce around. Now the next generation companies, they're maybe making their entire infrastructure decision based on who has the best AI products. What do you laughing at?

Starting point is 00:12:55 I'm laughing because I texted Simon. They have a turbopuffer has a booth at AWS. I said, how's it going at Reinvent? And he says, I'm not there. I just make it seem like I'm there as a joke because the VCs keep going to the booth and then our growth intern is like, oh, Simon, I don't know, I think I saw him over there. Just continuing to MOG while ARR SkyR rockets.

Starting point is 00:13:22 Shout out to Will the growth intern at TurboPuffer, holding it down at Reinvent. That's fantastic. I love it. But so let me go back to AWS. Amazon needs to fight back against this and allowing high-speed. interconnect between ABS and GCP. Solves a piece of that, but will they go further? Back on Tuesday, October 21st, 2025,

Starting point is 00:13:48 I wrote in the daily update in our newsletter at tbPN.com about increasing competition in the AI supply chain. Here's what I said. I said, not every link in the supply chain can be completely commoditized. This is about open AI trying to dual source from every part of the stack. And I said,

Starting point is 00:14:05 Nvidia has an insane amount of power right now. They've just ramped full year revenue from $27 billion in 2023 to $60 billion in 2024 to $130 billion in 2025. That's like one of the greatest revenue ramps at scale in history. And then also they grew their net profit margin from 16% to 56%. That's insane. Yes, goat. That's why Jensen Wong is on Joe Rogan. and I'm sure it's going to be a fantastic episode

Starting point is 00:14:38 because he's got a lot to talk about. All the hyperscalers and OpenAI, but that creates problems, right? Because all the hyperscalers and Open AI are now sort of incentivized to form a bit of an anti-NVIDIA alliance to commoditize the accelerator market and drive down those margins a bit.

Starting point is 00:14:55 So 56% net profit margins on 130 billion of revenue. People are just sitting there and they're like, there's $50 billion of profit over there, Like, that's a lot of acquisitions. And that's our- And that's our costs. Yeah, that's our costs.

Starting point is 00:15:10 Like, you're just eating a lot off of these plates. And so, um, CO2, I think has done a good job explaining the current state of the anti-Vidia, anti-NVIDIA alliance. They call it the Google complex, which is probably a little bit better. Uh, that consists of Google, broadcom, Celestica, Lumentum, and TTM technologies. This coalition stands in contrast to the open AI complex that consists of

Starting point is 00:15:33 Nvidia SoftBank, Oracle, AMD, Microsoft, and Corweave, but you know who they left off the chart entirely, Amazon. Amazon doesn't fit neatly into either of this. KOTU just loves, I think they just love leaving a major player off any sort of graph or chart that they make, right? They left Google off of their fantastic 40 AI companies. So I think that's just a little, that's just them messing around a little bit. But there's, yeah, I mean, I think it's accurate.

Starting point is 00:16:02 If you said, is Amazon more aligned with OpenAI or Google? You'd be like, what are you talking about? Neither. That's correct. They're not in one of the complexes. Maybe they need to be. Maybe they don't. Maybe they will form their own complex outside of it.

Starting point is 00:16:19 But I just think it's interesting that I agree with you that it's like it was ridiculous to consider the idea of them buying TPU. That feels so uncharacteristic. And yet they serve up plenty of competitive products. within AWS and they they they will you go back to the early days of Amazon you can get Amazon basics paper towels you can also get name brand paper towels and that's and that exists within the AWS stack from the databases that they have on offer there's a lot of products should rebrand training them to Amazon Basic GPU Amazon basics

Starting point is 00:16:57 Accelerated basic basic chips basic chips it was on basics chips It would be really, really hard. They're like, actually, it's like one of the greatest things ever. It's the most incredible thing that America or that humanity has ever created. It's extremely difficult to make. We taught sand a thing. Anyway, I just don't think Traneum 3 is the, you know, obviously everyone at ABA is like excited about it and it's a big deal.

Starting point is 00:17:25 But it's just not the backbone of their business. And in the long term, they might just retreat to supporting choice for their customers. And so, you know, I keep going back to that Jeff Bezos line. We're not competitor obsessed. We're customer obsessed. And so I wouldn't be as surprised. How much do you think it hurts Amazon that they don't have a dedicated podcast guy? Like they don't have a Sholto.

Starting point is 00:17:47 They don't have a Sam. They don't have a Satya. You know how much that hurts because they definitely have someone in that role. You just don't know them. That's what I'm saying. Yeah, they might have the title, but they're not really in the driver's seat, right? They don't have a run. They don't have a run, right?

Starting point is 00:18:00 They don't have a Shulte. Yeah, they should step it up. They should definitely get someone. I'd love to see it. Well, fortunately, I mean, the semi-analysis crew was over there, taking pictures, sharing photos in the timeline of the Traneum 3, Ultra-Server liquid cooled with a lot of hard eyes. That's some good news from, that's a glowing endorsement from the semi-analysis crew. And look at this, very purple. I wonder if that's like intentional. I wonder if they set up the purple, like, the purple There's a bunch of funny things going on over at Reinvent. It's also just like, it's a punishing time of the year. I guess it's like right before the holidays or something because we've just been completely torn. We obviously wanted to go to YC Demo Day. I also wanted to go to NERIPs, which is going on right now, the premier AI conference.

Starting point is 00:18:51 There's also Deal Book Summit. Andrew Sorkin's doing like all the greatest interviews at the same time. There's Reinvent. I wanted to go to that. Crazy interviews coming out of Deal Book. I just saw some clips this morning. You got Scott Besson just going hard. You got Alex Karp going hard.

Starting point is 00:19:07 No real surprises on either of those fronts, but excited to get the update there. Let me tell you about Cognition. The team behind the AI software engineer, Devin, crush your backlog with your personal AI engineering team. Let's close out the Traneum coverage with the Zephyr Post, who says Google is having this kind of success with TPUs. What about Amazon's Traneum?

Starting point is 00:19:29 Traneum is new and underpowered, just 667 T-flops BF-16. It has lots of HBM, but the bandwidth is lower than the H-100, TPUV-6E, is competitive with H-100, not on HBM or bandwidth. And Ironwood is competitive with Blackwell on Flops, bandwidth, and HBM capacity. I expect Ironwood to quickly gain market share as it ramps up, as you can see from throughput slash TCO, NVIDIA versus Trinum-Mogg's Trinium-3, harder than Blackwell versus Trinium-2. on TCO training flops and reduces the gap by 5% on TCO MEM bandwidth. So the gap between NVIDIA and Traneum is actually increasing rather than decreasing. By the way, this math was done before CPX was introduced.

Starting point is 00:20:12 I won't be surprised if CPX plus Rubin is cheaper than Tranium for inference. So I do think that there's a world where there's something specialized, like what's going on with Descartes, some sort of special model that's that that that thrives in what Traneum is good at, and they can further niche down. But we'll see. I mean, maybe they come from behind and they just destroy TPU, and we're all talking about training them next year.

Starting point is 00:20:40 Anyway, let me tell you about linear. Meet the system for modern software development. Linear streamlines work across entire development cycles from roadmap to release. We're going to say a little rest in peace. Rest in peace. To quad. San Francisco's beloved

Starting point is 00:20:58 albino alligator has passed away at age 30. That's a good age. I don't know how long alligators typically live, but I'm glad. Looking it up. It feels like 30 to 50 years for the American alligator. A little bit short, but Claude was of course, often, often reaching 70 years or more. Yes. Anyways, RIP, there was, you know, obviously people started speculating immediately, anthropic, of course, was the sponsor of Claude. And, you know, people were wondering, was there foul

Starting point is 00:21:34 play involved? Was it possible? This poor dinosaur, not dinosaur, alligator, passed the day that they, that it got announced that they've hired IPO lawyers. Some people were

Starting point is 00:21:50 speculating could, is it possible? Claude was sacrificed to the capital markets gods and some type of ritual. But anyways, he, look at this expression he has on his face. Can we zoom in a little bit? What a, what a cool guy. And he will be remembered. Yeah. Dan Primack here is talking about X-Light. I think we might have the CEO on the show soon. The Trump administration will invest $150 million into a lithography startup called X-Light. Its first Chips Act award, chat this morning with X-Light CEO.

Starting point is 00:22:26 There's a few lithography companies now. We've had some on the show. This feels like an entirely new. It's a very interesting tier of investment, like $150 million from the government that feels like a series B. They did raise a series B this past summer led by Playground Global with Playground Partner and former Intel CEO, Pat Gelsinger, becoming X-Lights executive chairman. Wow. And so makes sense that the government. investing in Intel. Pat Gelsinger, of course, former Intel CEO. Now he's getting involved in

Starting point is 00:23:02 X-Light, marshaled 40 million of capital, went and got 150 from the government. The story continues. There's also another AI startup that wants to remake the $800 billion chip industry. This one's in the Wall Street Journal, founded by ex-Google researchers recursive intelligence, raised 35 million with backing from Sequoia to automate chip design. Obviously, this is not lithography. This is the design process, but still, companies are... Dylan Patel was talking a little bit about this. And down the stack. Oh, he did.

Starting point is 00:23:32 I didn't hear about that. Very cool. This is AI for AI chip design. Oh, that's right. Yes, AI for AI chip design. Everything we need. On a quiet residential street, a few blocks from Stanford University. Two former Google researchers are launching a startup.

Starting point is 00:23:48 They hope will remake the $800 billion chip industry. Anna Goldie and Azalea Mirjouzni are trying to, to build software that can automate the design of cutting edge chips, a prospect that would allow every company to build their own chips from scratch. Working from the top floor of a suburban home, the duo recently raised 35 million to kickstart recursive intelligence with funding from Sequoia Capital and Strike. The recursive, we got to add that. We got to add that to the list of because there's standard capital, modern capital, standard intelligence, modern intelligence. Raw intelligence was the low-hanging free. applied was another one.

Starting point is 00:24:26 Cap intelligence. And then what was the other one? There's, what's Lockheed Groom's company? Physical intelligence. There's physical intelligence, physical capital. So it's the matrix of like capital, what was it? Capital intelligence and intuition or something like that. And you multiply them all out and you get the whole thing.

Starting point is 00:24:46 Eventually we're going to run out, right? There's somewhat finite. No. There will always be more names. Startup new words. So, wow. the company, 35 million for a valuation of 750 million, that's very low dilution. What, 5% or something like that? Pretty remarkable. Definitely. VCs were mocked. Yeah, I would have assumed this would be a very capital-intensive business, but I suppose if it's just a software that they're developing, maybe they have more control here. Companies such as Amazon and Google have developed custom chips for AI and data center use,

Starting point is 00:25:24 Apple save billions of dollars by insourcing chips for its devices, including the M-Series chips that have helped revitalize its MacBook laptops. Such silicon options can be cheaper. I had a funny moment yesterday. We got an Amazon package, and it was covered with like alienware. Like alienware branding. And I asked, I asked Sarah, I was like, did you get something from alienware? Like what is going on?

Starting point is 00:25:50 And it turned out to be an ad, but they were advertising that is powered by like Intel. Oh, interesting. Which didn't make me necessarily want to immediately buy an alienware device. If you do, you put the money straight back in your pocket because you're a taxpayer. You own Intel. That's true. That's true. You should support Intel.

Starting point is 00:26:09 No, Intel is undisputably great for gaming. There's no question there. The question is, are they going to be able to build a fab that competes at TSM? It's a completely different question. I might go build an alienware Intel PC Well we're going to for the office Sim racing rigs.

Starting point is 00:26:29 The Sim racing needs the Intel inside for sure, for sure. This is just going to turn into a sim racing show where we watch other podcasts while sim racing and reacting to it. Yeah, I like it. Vanta Automate Compliance and Security, AI that powers everything from evidence

Starting point is 00:26:45 collection and continuous monitoring to security reviews and vendor risk. Dwar Cash Patel has a massive essay shaking up the timeline. Thoughts on AI progress. He says he's moderately bearish in the short term, but explosively bullish in the long term. Very interesting. So he says he's confused why some people have short timelines. They say AGI is coming soon. But at the same time, they're bullish on RLVR, which is reinforcement learning with verifiable rewards. And so he says, If we're actually close to a human-like learner, this whole approach is doomed.

Starting point is 00:27:24 Currently, the labs are trying to bake in a bunch of skills into these models. Through mid-training, there's an entire supply chain of companies building RL environments, which teach the model how to use Excel to write financial models. For example, I think we're actually talking to an AI Excel analyst for Excel power users called Crunched at 1250 YC company. I think that these are good ideas. I'm actually very bullish on this model. But in the context of when does AGI arrive, when a superintelligence arrive,

Starting point is 00:27:58 I understand, to our case's point, he says either these models will soon learn on the job in a self-directed way, making all of this pre-baking pointless, or they won't, which means AGI is not imminent. Humans don't have to go through a special training phase where they need to rehearse every single piece of software we might ever use.

Starting point is 00:28:15 Barron 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 an 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

Starting point is 00:28:49 reasoning and process, formalized, and tracked, and then we distill them into models through behavioral cloning. This has updated me slightly towards longer AI timeline since we, 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 teleoperate 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

Starting point is 00:29:34 makes it necessary to go out into thousands of different homes and factories and learn how to pick up dishes or fold laundry. One counterargument I've heard, from the takeoff 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 Ilya 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?

Starting point is 00:30:16 That seems super implausible to me. Besides, even if you, 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 Ilya. So clearly the lab's actions hint at a world where, 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.

Starting point is 00:30:47 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, security spent up white label wallet, sign transactions, integrate on-chain infrastructure all through one simple API. So you've been asking about economic diffusion, what is the rate that we're diffusing? Let's see what Dwar Keshe has to say about economic diffusion. He says that economic diffusion lag is cope for missing capabilities. And so this also seems informed by the Tyler Cow intake that AGI is here.

Starting point is 00:31:22 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. It'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.

Starting point is 00:31:57 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 Dorcasian is very much. two, where he was trying to find the most interesting pieces of a full podcast with one big Gemini prompt.

Starting point is 00:32:42 And he was trying all the different models and couldn't get it to actually find the most salient and viral points. Yeah. So one of the, the other thing that stands out is like one of the seeming missing capabilities is like ability to like identify humor or even something like it's almost emotional. So Ilya and Dwar Keshe talked about this where I think Ilya was giving the example of of scientists studied people who had had various brain injuries that limited their ability to experience emotion.

Starting point is 00:33:12 And when they took out emotion, it took them, it can take somebody two hours to figure out which pair of socks to choose. And they were kind of stunned. Like it's just a pair of socks. 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

Starting point is 00:33:35 is like, okay, finding out, like, what's an interesting moment of a podcast in Varkesha's case, right? Is it something that makes the audience member feel something, right? Is it? I mean, there's just so much to pull through. Like, I remember during the Carpathie interview, I was watching it and Tyler was watching it, and there's this moment where Carpathie says,

Starting point is 00:33:56 like, the coding models are amazing and they're magical, but what they produce is slop. And 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 that rage bait beat out slop for the word of the year.

Starting point is 00:34:15 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, that word, Carpathie 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. identify that it was like that was the crazy moment that we should be like reacting to and taking in and it's crazy the other thing that's that's that's notable is like on wop one of the best

Starting point is 00:34:45 one of like the top jobs that people do on wop or way they make their first dollar online is just like clipping for various content creators and media companies and 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 people we're still paying humans to do that still i mean it just feels notable yeah well let's read dwar kesh's take on economic diffusion lab lag being cope from missing capabilities says sometimes copium would be a beautiful name for an ai chip by the way it would you got tranium maybe they need copium uh sometimes people will say that the reason that aIs aren't more widely deployed across firms

Starting point is 00:35:34 and already providing lots of value outside of coding, is that technology takes a long time to diffuse. Dorcash 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.

Starting point is 00:35:55 It says new technologies take a long time to integrate into the economy. Well, ask yourself, how do highly skilled, experienced, and entrepreneurial immigrant humans managed to integrate into the economy immediately. Once you've answered that question, note that AGI will be able to do those things too.

Starting point is 00:36:13 Dworkesh 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.

Starting point is 00:36:31 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. This 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.

Starting point is 00:37:05 We hire someone. Yeah. Like we hire an AI or we're leveraging an AI and they've listened to every single minute of TBPN ever. Yeah. And watched every clip. Yeah. 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.

Starting point is 00:37:22 Yeah. And I'm just saying like the, 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 a missing capability set

Starting point is 00:37:39 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. Yeah, I agree with that. The one thing that I don't necessarily agree with here, he says, well, ask your stuff. this quote from Stephen Burns, how do highly skilled experience and entrepreneurial immigrant humans manage to integrate into the economy immediately? I mean, they do sort of integrate

Starting point is 00:38:06 into the economy immediately, but like the immigration flow is like a slow process. Like it doesn't just happen immediately. It's not just like, you know, the amount of immigration went from like zero to like, I don't know, a million people or something. Like it's like people move around. There is like a, there is a bit of a drag. But I understand what he's saying here. It does make sense. Anyway, let me tell you about public.com investing for those who take it seriously. They got multi-asset invest in and are trusted by millions. The Verge is trying to get it on the action, trying to attack David Sacks with a headline. It's like so funny that the New York Times went after David Sacks and then the Verge was like,

Starting point is 00:38:48 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. You know, this article, that's a little bit too. Well, while I don't agree with this journalistic approach, it is a pretty funny headline. Yeah. Oh, yeah. It's hilarious. The headline is Silicon Valley is rallying behind a guy who sucks.

Starting point is 00:39:13 It's like, what does that mean? Just pure. It's pure, like, qualitative, like, just name calling. They're just like, we don't like this guy. Pure ad hominin. But, you know, go off if people, if people, 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.

Starting point is 00:39:35 On a linked article, the Verge is not putting up a thousand likes per link. So this is outperformance. And it's heavily paywall. You cannot learn how David Sacks sucks without subscribing to that thing. They did a good job. You got to pay. You want to know why he sucks. I didn't.

Starting point is 00:39:53 Did you pay? I don't know why he sucks, but... 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? Paul Graham, 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

Starting point is 00:40:14 and wanted them to sell the 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. A lot of people, a lot of people, like, say that's bad. Yeah. 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.

Starting point is 00:40:52 Yeah. It certainly, it certainly seems. at this point, startups tend to be smarter, less bureaucratic, more representative to future trends. Like, even if there's a, you know, 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. Yeah, and these are, these are every found, yeah, they're being rational. It's not like, it's not like, I'm sure there's been small instances where companies were actually, you know, had 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

Starting point is 00:41:30 good. Yeah. It has to work. Did you see, did you see Stewart 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. Where it is, there might be $1,500 payout per book, according to my agent Max Brockman. That's a good name. He said, I wrote them, 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 and 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. This is a, he's the co-founder of the Long Now Foundation, which takes no sides in this forum.

Starting point is 00:42:22 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.com. Code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster. 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 Anderals' growth, while, leasing 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 a soliciting investors via public Google Doc to invest in an

Starting point is 00:43:03 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 and oral employee. A few problems here. First off, so-called forward contracts are notoriously hard. to settle in private companies and counter-party risk is extremely real. What about the many complicated 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

Starting point is 00:43:41 gets, you know, again, married or divorce or passes away or bankruptcy is another situation where you might not be actually able to collect, even if the, even if your investment should have generated some return. Matt says, second, this deal memo includes basically no details about Anderil's performance, no revenue figures whatsoever, no product specifics. I guess that's good, right, like if they were, 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's stock plan and bylaws,

Starting point is 00:44:26 which means that Anderol will never consent to Team Ignites SPV, actually taking possession of these shares while we are privately held, zero 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. As 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.

Starting point is 00:45:20 And I believe 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... And then... There's like seven people that share a screenshot of, like, a direct email we got with this exact memo. Okay. And the other thing is, they say not soliciting investment for any Anderol-related vehicle. Matt says, really? The draft was written by your founder and managing partner.

Starting point is 00:45:51 I literally watched him edit the dock in real time. And he has a screenshot of, like, the founder's name in Google Docs, like, you know, basically... What a mess. Anyways. Well, don't do this. Don't do it. Instead, why don't you start a company and apply to Y Combinator? Build the 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.

Starting point is 00:46:23 We have Hars Tegar here in the Restream waiting room. Let's bring him into the TVP and Ultram. Harsh, thank you so much for taking the time on a busy Y Combinator demo day to come talk to us. How 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?

Starting point is 00:46:54 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, their background, the pretty quick fire presentations, one minute each. And then there's sort of like a break in between sort of blocks of presentations

Starting point is 00:47:24 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 a project. 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 Dior. So it's kind of like a fun vibe. It's like live. It's the best. Party rounds. We 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?

Starting point is 00:48:01 Yeah, I mean, we didn't go two 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. 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 and that's all like very directly from AI. Okay. 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 you see that even post Demo Day.

Starting point is 00:48:53 Like there's companies that keep growing. Like you're like in the SaaS world, you were used to sort of just a consistent month over month like 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 leaprogs again interesting uh yeah help me square sort of the shape of revenue with some of the yc batch that we might talk to today because uh paul graham was on the timeline sort of defending this idea of selling to startups we were in in complete agreement with that that uh selling to startups can be so much better in a bunch of different ways but it does feel like we're entering an air

Starting point is 00:49:28 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? Is 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 ball case for selling two 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

Starting point is 00:50:08 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 were just like keep growing because like the co-olds 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 could if they wanted I think if you have a product like that where you can grow with the startups and you can get in early and they were just like, those startups in the future will become your enterprise customers. That's like fantastic.

Starting point is 00:50:34 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've got like a thousand startups. And like in aggregate, we're processing like X or like we're reliable.

Starting point is 00:50:52 We're not going to shut down. I think now with 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

Starting point is 00:51:07 because they're the only ones that can actually deliver the product. And I think that's just new. So, like, we still give the advice as very dependent on the company and the product and, like, will you be able to scale with startups or not? But, like, in general,

Starting point is 00:51:18 there's just more options as a founder for how you do sales than there's ever been. Let'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, like, various, like, infrastructure. It was, like, infrastructure for building agents. Last batch really felt, like, much more applied.

Starting point is 00:51:41 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, 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. Then it's like vertical agents just take off, like customer support, logistics, like name any like healthcare, like all these

Starting point is 00:52:16 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 dispatch, you'll notice, is like the companies are going the next step and they're not actually selling the agents to the incumbent. They're going like AI native full stack. They're just actually doing the thing. So you have like Fernstone being like an AI native insurance brokerage. They're just they are insurance broker and they're just going to use AI to be the best one.

Starting point is 00:52:49 Sava is doing that with trust. It's like a company that sets up trust, but it's doing it with AI. it. So I think 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've talked to a couple 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, 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. Yeah, I think if you go bad, you remember it was, I mean, it was like a decade ago now, but it was Balagie that started this whole thing with like the full stack startup. He like, 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.

Starting point is 00:53:49 Right. So I think like back in that area 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. Ultimately, those companies didn't, it turned out that being a marketplace or selling software was just a better scalable business in that era. But now with AI, like, I think the promises were kind of going back to the full-stack

Starting point is 00:54:08 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 a thousand 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?

Starting point is 00:54:27 Yeah. Yeah, he's got, he's got picnic, and I think it's Otter, and then he has cloud kitchens. So he's like, I can do it. But maybe at his scale, maybe it's a scale thing, I don't know, but it is, it is more complicated financial. I think if you're, if you have traversed, it's like access to capital and his, like, background, like, operating, that you can, you can, you can do that. Yeah.

Starting point is 00:54:45 How are, how are companies or founders grappling with, uh, what's happening at the largest foundation model labs. I remember there was some Sam Altman interview where he said, you know, here's how not to get steamrolled. If the models, 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, open eye in particular, to go after probably like maybe more of like the sexy consumer

Starting point is 00:55:33 ideas that like capture the public's imagination. And it's going to be hard to compete with them on that. But there are like the startups in the batch in particular that 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 Open AI are, anthropic, I'm not going to be thrilled to build, like, auditing software or auditing agents, you know? Or actually sell the, 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, it training on it a thousand times to get that. Yeah, this is

Starting point is 00:56:11 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. We don't really want it that badly. That sounds actually sort of miserable. And it's just not me doing it. It's just not even if they don't want to do it, right? The best engineers at Google don't want to build a shopping product,

Starting point is 00:56:32 they are like back in the day, they wanted to work on search quality. Now they want to work on Gemini. Totally. Yeah. 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.

Starting point is 00:56:48 They're like, you can leave the company. actually. We don't like you at all. So yeah, you know, your margin is my opportunity, both directions sometimes. What are, what are some companies from previous batches that you really feel like are hitting their stride now? We had Calcian 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, so long ago, right? Yeah, that was 2019, I think. So yeah, I mean, obviously, Kauci is like the prime example of the 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, like, super sinacious went for it. I think, like,

Starting point is 00:57:31 more recently, it's a company that announced around doing customers for called Gigar, which I think is, like, really exciting one. Like, they're competing with Sierra and Decacorn, like, superstar founders of those companies, tons of capital raise, but they've been able to, like, beat them on head-to-heads with customers like DoorDash through, like, technology. really. So I think like gigos seems to be really growing. I mean another one like non-AI that's like post hoc is actually like 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 that they've done that from day one and it seems to actually

Starting point is 00:58:10 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 start up trying to build multiple products from day one and have like the compound startup effect. I 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 like 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. Wanted one. Yeah. And we got to do. We I'm going to do this more often.

Starting point is 00:58:51 Come back. Come back on. I would love to. Thanks for having me. Yeah. Let's talk soon. Have a good one. See you guys.

Starting point is 00:58:57 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. Join millions who use Julius to connect their data, ask questions, and get insights in seconds. We have clad labs. And have we been able to. If you're launching a startup and you want a pig theme's name, swine theme name, you could have Wilbur, Babe, Babe, Hamlet, Daisy, Peanut, and Cookie. Okay.

Starting point is 00:59:31 I like that. Ham Solo. I like Babe. I think Babe. Mud pie. Okay. So, we have the founder of Clad Labs in the Restream waiting room. Let's bring him into the TBPN Ultradome.

Starting point is 00:59:44 What's going on? Look at the shirts. It look fantastic. Incredible. You know, you're winning me over already. Ready, break 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 Plaid Labs. We're building Chad IDE, the world's first brainwry ID. Okay. Why? So great. So, so, so, we exchanged some comments

Starting point is 01:00:07 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. So why doesn't apply? What are you actually building? Like, why brain rot? Is it just for fun or is there something meaningful here?

Starting point is 01:00:32 Do 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-art models for much, much cheaper, mostly free actually to most developers. And so that's why you're putting, you're putting, so you're, so you're, you're acting as a funnel to, you know, any affiliate that.

Starting point is 01:00:54 So it could just be ads, but you picked specifically the most controversial ones, the gambling and the and the subway surfers, like the stuff that feels more brain-roddy because that would get into a reaction. Was that the plan? Yeah. Yeah. I mean, there's a, I mean, I think Jordan touched on this earlier. There is a difference between the marketing and the product.

Starting point is 01:01:16 Sure. We actually started out with affiliates on these very normal sites. And a lot of our users actually request is saying, hey, we actually like school on rainbed. 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, you know, the debate was, are you making something people want?

Starting point is 01:01:35 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. Like, like 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

Starting point is 01:02:17 I code website, code me a website. Right now, ClaudeCodeCode has a multi-stage planning, right? It 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, super base. That's a super base 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,

Starting point is 01:02:56 and then you just, and 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 like at the right time. I mean, yeah, it makes a ton of sense to me on that level, a little bit less on the steak gambling while you're waiting. That feels like that would actually reduce developer productivity. Do you have any plans to actually assess what? 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, you know, resource,

Starting point is 01:03:34 my most valuable human capital tuning out every other second while they're waiting for, you know, the generation to come back? Well, one of those engineers might say, well, I would, because I'm betting on rain bet with my personal dollars, you're paying less for the IDE. I'm saving the company money. Gone. But don't you think that it would be better to show educational videos than something like that? Oh, we have that as well.

Starting point is 01:04:01 Yeah. So we have educational videos, learn about the code that you're actually writing. But I think our thesis is basically that we followed the YIC advice, talk to your user, and the user wanted the gambling integration. So we made it for them. And at some point, the user doesn't want it anymore. We'll take it away, right? So it's all about, I think, for BUSC is being close to the user, iterating close to the user,

Starting point is 01:04:19 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 Gero board, the whole productivity workflow into the generation time. And we're like, we're serving consumer right now. But I mean, there's infinite possibilities here to scale at like various business levels.

Starting point is 01:04:44 How has the traction been to date? It's been great. Yeah, I think I would thank you guys for that as well, helping us go viral. So we have a great wait list of 11K. 11,000 people on the wait list. Successfully baited. Has anyone used it yet? Have you built it?

Starting point is 01:05:00 Is it in the wild? Is it a BS code for? What were the metrics that you shared at Demoday? Yeah, so the message 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.

Starting point is 01:05:21 Amazing. Find Tyler. I know he's probably in the same room. Let's get Tyler on Clad Labs or Chad IDE. We should hit the gong. Yeah, we should. And how's the round going? It's going great.

Starting point is 01:05:39 Yeah. We filled half the round. We have a lot of allocation to give out to people who are interested. Awesome. All right. 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.

Starting point is 01:05:52 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 ultradome. 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. seat, sit down. Jordy, you can take a view here. This is a live view into the very cool.

Starting point is 01:06:24 Into YC. Demona. So if we, if we jump ahead of the schedule, we can always check in there. But there we go. We have the founder of absurd in the Restream waiting room. Let's bring him into the TV here in Ultram. How are you doing?

Starting point is 01:06:37 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.

Starting point is 01:06:47 We appreciate you. Fantastic. Have you. Please introduce yourself. Tell us what you're building. Yeah. My name is Philip. I'm CEO of Obsurd.

Starting point is 01:06:55 Obsurd makes AI marketing videos. An ad that we've made, you've probably seen on your feed is a college cheese, Mamdani versus Cuomo 1V1 basketball match, which we did before the elections. We like to joke that we influence the New York City elections. Amazing. So what, walk me through the product, it sounds like you're more using the foundation models using SORA V-O-3, then training your own. But what are you building?

Starting point is 01:07:22 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? Where 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,

Starting point is 01:07:46 instead of like 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 like 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 say, I want one launch video please. And you say, sure, here's the Facebook. price and then you guys use your internal tooling and whatever models you have access to to

Starting point is 01:08:21 generate the best possible output and you deliver that end product. Exactly. And what are you, 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. Yeah. You're in like the proper video production realm, at least in terms of price.

Starting point is 01:08:52 What are the secrets to using the video models appropriately to actually go viral? What do you hire for? What are you focused on making sure that the video that you deliver is actually hitting, you know, 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. Second thing, in terms of what we're prioritizing, what we're really thinking about internally is just how many videos per person per week? Like, what's that throughput looking

Starting point is 01:09:36 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 week. 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 1,500 of our kalshi super bowl ads in a month and that's the type of quantity that we're talking about here wow like this is this 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

Starting point is 01:10:16 Like, we're actually, 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, you just said it's ramping. Because we still don't have capacity now. We are, we could literally like double-and-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 back startup launches, you know, a week. Yeah.

Starting point is 01:10:42 So the way, the way we were seeing things right now is, 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?

Starting point is 01:11:01 And eventually it's going to go to 50, then 100, and 200. A lot of this is going to be used in ads. Because the more you spend on ads, the more you have to switch out ad copy because of, 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. And then eventually we're going to get to a point

Starting point is 01:11:22 where 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. Because if you think about the ad, an AI ad, it's literally just like images

Starting point is 01:11:39 and you're animating them. And as long as you have an agent that edits to images and changes to 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, I, I, I, uh, you think maybe. That's a good answer.

Starting point is 01:12:03 That's a good answer. You should make it up. He can't, he can't, you know, people are going to look up his customers. Yeah. What do you think about, uh, the role of, of taste, of craft, a lot of what's, 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, you know,

Starting point is 01:12:37 existing ideas. Yeah, historically, the best creative agencies have been the agencies with the best ideas, right? It's like you pay, you pay to work with somebody that has a track record of generating great campaign concepts. And then they'll oftentimes just like 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 in terms of like creative production is like so much faster with AI. Yeah, I think, um, we think of like creativity, not as a modelist, but really in terms of two

Starting point is 01:13:23 parties, exactly how you put it. So there's a taste layer. There's next, then there's an execution layer. Our job here is we want to remove that bottleneck between an idea and a finished product. Um, so 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

Starting point is 01:13:54 tens and thousands of ads for. How much are you guys actually spending on the on the model, 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. We have an internal orchestration layer that picks the best models to use for all these specific use cases.

Starting point is 01:14:22 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. It's close to like 98%.

Starting point is 01:14:38 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? Or 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. Um, Seedream is good at specific use cases. Nano banana is good as specific use cases.

Starting point is 01:15:07 Kling, Juan, all have their own, um, unique use cases that we use we use. Um, something that's interesting beyond just the models is just like work, in terms of workflow orchestration. Um, before Nanobanana Pro came out. I'll give this 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. Um, and that wouldn't work.

Starting point is 01:15:30 So the way you do it is you'd actually tell you. 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 Nanobanana Pro. So there are all these like little workflow things that we've learned just by experimenting and playing around these models, which play a huge role in making all our ads like the creation of our ads really effective. Fascinating. Have we entered a post-slop era? Will we enter a post-slop era? What is your post-slop timeline?

Starting point is 01:16:02 I was speaking to Jess Lee actually about this She was talking about how photography used to be seen as slop And because they used to say that photography was this way that she Like artists were actually painting something But photography allowed people to realize that Allow 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.

Starting point is 01:16:38 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 cool 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. Incredible. John, hit that gong.

Starting point is 01:17:02 I will. For Philip in 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.

Starting point is 01:17:24 And by the way, before I go, I'd love to make a launch video for you guys. Let's talk. I would love that. I want to see what you can do. We have a benchmark here, Bezell Bench, 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. It's a particularly hard shot to get right.

Starting point is 01:17:46 But we can come up with a bunch of different ideas. Let's do it. That'd be fantastic. Let's do it. Perfect. Well, have a great rest of your demo day. He'll be in contact. Thank you guys for having it.

Starting point is 01:17:57 Talk to you soon. Cheers. Goodbye. 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 Aliatar. I like LightBerry.

Starting point is 01:18:13 Social brains for robots. Social brains for robots. Let's bring in. I like the sound of that. Lightberry. Yes. Very interesting to see what robots we're talking about, but we have him here in the studio. Welcome to the show.

Starting point is 01:18:29 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. I like it. Yellow, 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, hi 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.

Starting point is 01:19:10 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. Yeah. So we literally have a humanoid robot upstairs right now,

Starting point is 01:19:40 emceeing the entire event for Demo Day. And, you know, he's fully autonomous. He talks. We give him some instructions about, like, how he should be able for today. 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

Starting point is 01:19:54 from at least 50 different manufacturers. But if you do that... Who did you buy yours from? So ours is from Unitary. It's a Unitary robot. Did you buy it on Wall? Walmart.com? No, no, no. I know they sell. I know they sell Unitri.

Starting point is 01:20:06 No, no, no, no, not at all. No, no, we actually work directly with Unitary. And so, like, you know, if you buy a robot from them or any of the 50 others, like, it literally doesn't do anything. It can't talk. You can't teach it anything. You can't. 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. what uh yeah what does adoption kind of look like with this like how are you actually selling it is this something that you want unitri to uh kind of uh 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 uh happen to want to go through all the different hoops in order to actually get value out of a

Starting point is 01:20:52 out of a humanoid i mean that's exactly it you hit the nail on the head like we're working directly with the manufacturers. There's like over 50 of them. We actually just last week closed the deal with Unitry. They're like, they correspond to like 90% of market share in the world. I'm giving you the air horn, but I have encouraged various government officials to ban Unitri from the United States. Oh no. Well, look, you know, the truth is like they're the only one shipping. Like we want to work with the American companies too. We want to work with literally everyone. But Unitri is 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 U.S.

Starting point is 01:21:28 But we're also working with other companies, some European ones, some American ones. Yeah, what's happening? So I would imagine 1X has no interest in partnering with external providers. That 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?

Starting point is 01:21:54 optimists, 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 figures deal with Open AI just fell through. I don't know if that's true, but, like, that's the rumor.

Starting point is 01:22:12 We'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 the most dominant form factor for robotics in daily life

Starting point is 01:22:29 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 or you know a one robotic arm on a Roomba phase like how do you see because the self-driving cars

Starting point is 01:22:45 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? I mean, if you look at sci-fi as an indicator of what people want, we don't just want humanoid. There'll be different kinds of robots. You're going to have some 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

Starting point is 01:23:13 humanoids because like, why do you need locomotion in those cases? Human nodes 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 where we're building humanoid is because they look like people. And 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 like a fully functional autonomous humanoid at the 11 Lab Summit like three weeks ago.

Starting point is 01:23:42 And it was just working there for 10 and a half hours, like 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? So we run a hybrid pipeline. We rely heavily on the cloud because that's where the best models are.

Starting point is 01:24:05 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. We'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 like the it's not this, it's that. Like 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 they all kind of 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

Starting point is 01:24:52 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 like people love C3PO But C3PO is very obviously a robot

Starting point is 01:25:12 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

Starting point is 01:25:36 and the interactions. Are you, are you excited about robot pets as a category? I know dogs are they're cool. 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 like a little pet droid in our office. It's like a bipedal that kind of looks like R2D2. 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 human noise, just because the price point is so much higher

Starting point is 01:26:19 that we could just focus on quality rather than trying to optimize for cost. Obviously, 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, like, deliver

Starting point is 01:26:33 on, like, toys, pets in the near future. Yeah, the toy market seems really, really interesting. Yeah, our first customer was a toy company, actually. Yeah, it's very funny. What about security? I feel like there's a potential use case for humanoid's 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. And 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.

Starting point is 01:27:05 And he was like, you know what? I would love to deploy them for security. How much does it cost? And I told them, it's going to be like around 60 to 70K. It's like, I want four. I was like, okay, deal. So he already pre-ordered them. Like people want this for security,

Starting point is 01:27:18 not because they can fight, not because it can harm people. These things can't. It's about the best deterrence. Yeah, it's just the best deterrent. And like, you know, we can literally talk to weird people in the evening. It's like, who are you?

Starting point is 01:27:28 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? Robust to help people, not to replace them. Yeah, I do think it's interesting that a lot of these humanoid companies are focused on,

Starting point is 01:27:44 the hardest possible thing, which is replacing, like, a housekeeper, 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. And that's, like, the job. And they make, like, the same amount as a housekeeper. Yeah. So 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.

Starting point is 01:28:23 And that's just really soon. That's going to be fun. Very cool. Yeah, how big is a 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. Amazing.

Starting point is 01:28:40 And how's the round going? It's been very fun. I mean, we managed to close it like pretty. early. There's a lot of, there's some interest now because, you know, like, we're with the unitary deal, we're pretty close to a series A milestone, so we're trying to like discuss that. There we go. Series A time. Love it. Let's go. Really great to meet you. We'll talk to you, sir. Thank you for coming on and excited to fall on. 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-

Starting point is 01:29:14 Pick a favor. Take a favor. There is a lot of arbitrage to be done. On the topic of robots, I'm just, I'm super excited about the lamps that are happening. Have you seen that there's two robotic lamp companies now? They're like,

Starting point is 01:29:29 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, you know,

Starting point is 01:29:40 full humanoid tomorrow for this much money, like that feels like a taller order It's going to be a couple of years away. But the lamp, I feel like we can do today. The lamp can talk to you. It's going to be funny. It's going to be awesome. I'm excited.

Starting point is 01:29:50 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 TBPN Ultradome. You're in the Ultradome. I love it.

Starting point is 01:30:05 Please introduce yourself in your company. What do you do? Hi, my name is Kroosh. 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? Are you talking hedge funds or like the most advanced traders?

Starting point is 01:30:23 Yeah, honestly, it's all of the above. A lot of our current customers are our 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 parlay. So there's a lot of applications currently being built right now. It'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

Starting point is 01:30:58 question. Yeah, yeah. No, no. I mean, it's unfortunate, you know, 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. They want to be the exchange. But how does this, how does this evolve? Yeah, I mean, we're supporting currently polymarketing in Kalshi. They're both great. Obviously, we don't, we don't pick a winner in the fight. everyone to do well. And what we're currently seeing is there are a bunch of new platforms launching

Starting point is 01:31:44 different regions, different specific verticals. Some folks are just like only sports, some are doing crypto, mention 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. And so in addition, you have Cal Sheep Polymarket, you will have Robiton and a bunch of other big players that are probably launching soon. But you'll also have a lot of these like smaller players in different specific regions and verticals. And so we're excited to see like the whole world basically start adopting this. Do you have a reference point for how cross-market transactions,

Starting point is 01:32:18 like is there a public markets equivalent to you or some sort of like layer that's not necessarily a hedge fund, but they're like 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, it's a great question.

Starting point is 01:32:47 For what it's with Flash Boys is my co-founder's favorite book. I mean, 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. So if you actually look at just calcium polymarket themselves, about like 80% of their markets, their underlying contracts are the same event.

Starting point is 01:33:03 So you actually have a good amount of overlap there. But you also hit it on the nail as well. 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 or is some of your volume people just arbing markets on the different you know basically seeing like okay what are the odds on

Starting point is 01:33:33 kalshi what are the odds on polymarket and trying to find alpha through that Yeah, I mean, arbitrage is a very like common request from a lot of our customers, right? We actually had a customer that like 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 like 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 one-to-one market versus like a maybe one-to-one market because personally with the way we got started was we were trading ourselves and got burned as well when two months. markets look similar, but they're not perfectly similar, and you lose a lot of money.

Starting point is 01:34:11 And so that's something we're very... 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 is hosted on. A lot of people have been seeing the rounds coming together for the different prediction market platforms and having flashbacks to like OpenC 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?

Starting point is 01:34:46 Yeah, great question. Biggest answer is, like, we've kind of seen this exact playbook. But before, both 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, really, like, 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,

Starting point is 01:35:10 including OpenC and Polymarket. So we've seen this way. We've built a lot of the similar technology, the infrastructure layer at these previous companies. What you typically see is, like, there's a huge hype and boom cycle. Everyone's excited. And then, like, interest kind of fades away,

Starting point is 01:35:22 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.

Starting point is 01:35:33 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. Are you actually routing trades on behalf of clients

Starting point is 01:35:56 or just providing the data layer? Because I imagine it could get quite difficult when some exchanges are using digital assets. set, 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's the first version of product is just give them data, give them prices, APIs, tools, whatever they need to display on their applications so that they can build applications, right? The next part of our plan

Starting point is 01:36:29 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 outer 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. Do you think it's interesting that a lot of the sports books are funding lawsuits against the prediction markets while also starting prediction markets products themselves? I think it's super interesting. 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.

Starting point is 01:37:07 There's so many more advantages to having a pure prediction market, a P2B experience. It's a lot better for the end consumer as well. So 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 the building. I had a feeling. I had a feeling. I appreciate that. Yeah, I appreciate it. It's been an exciting journey so far. Well, thank you so much for coming on

Starting point is 01:37:41 the show. Yeah, great to meet you. Congratulations. Congratulations. Thank you for celebrating domes. Yes, we appreciate you. 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. Cerberalus Vector and Fult 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.

Starting point is 01:38:18 He made money for his investors. Well, yet this is 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 purpose. person making the four. There's always a steel man. But there's some good folks on the 30 under 30.

Starting point is 01:38:35 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.

Starting point is 01:38:52 Yeah, thanks for having me, guys. My name is David. I am one of the founders of Source. Sources 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?

Starting point is 01:39:07 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. So it just saves the filling out form time. How's the traction?

Starting point is 01:39:29 What is, what, yeah, so, so talk about, can you talk about the state of the hiring market? Oh, yeah. Because I feel like the, the number one complaint that, uh, candidates and people that are applying for jobs have is that, like, seemingly nobody reads, nobody actually looks at job applications. And a lot of roles don't actually end up getting hired, uh, based on traditional job boards. Um, but yeah, what, what, 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 company. the role in the sector, but in general, people definitely still get interviews from just inbound applications.

Starting point is 01:40:04 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 it. Like a lot of people email themselves into a job or a lot of people refer their way into a job, But the inbound is definitely still something that companies use because when you're hiring people at scale,

Starting point is 01:40:36 there's just no other way to do it. Like if you're a company that's hiring like 200, 300 people a month, it's impossible to do it through inbound. Yeah, so where 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 is the focus been? Yeah.

Starting point is 01:40:55 Yeah, I guess a misconception about sources 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. So 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? Does just scrape these? Because I know LinkedIn used to be amazing for scraping and then. I'm assuming yes, because they're like you're going to get you more jobs.

Starting point is 01:41:27 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, indeed 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.

Starting point is 01:41:44 Like we want to 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. react into it to answer someone's question. Like, we've helped to get over 25,000 interviews in the past year. And those range from, yeah, those range from, thank you.

Starting point is 01:42:11 That's fantastic. From, like, I guess there's a very wide range of companies. Like, we've helped somebody get a software engineer role at Enderil, like a couple months ago. But then very often, you'll see someone get like a line cook job. but it's really just the universal fact is that filling out the form is very, very pointless. How do you do top of funnel? Like, how do you get people to be aware of your app actually install it, download it? How are you driving attention on that side?

Starting point is 01:42:43 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.

Starting point is 01:43:05 That's very cool. How are you going to make money? Are you making money already? So we actually launched this while we were in school. Like I just graduated in May, but we launched this last, like at the beginning of the fall semester. And we used to make money from charging people for, for by charging people for more swipes. We recently have gone like very, very free.

Starting point is 01:43:25 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. But right now, we're very much just, like, product focused, and we're kind of willfully ignoring revenue. Yeah.

Starting point is 01:43:49 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 more money. Tell them to get back in the grind. You don't need to be talking to investors if you close around. Small recommend, small recommend, I don't like Tinder 4X.

Starting point is 01:44:13 Oh, sure. I'm sure that that actually resonates really well with consumers. But the product experience makes a ton of sense. People think swiping. they know swipe thing. Yeah, they know swipe thing. They know swipe thing. They're not getting away for that.

Starting point is 01:44:28 It makes sense. But anyways, very, very cool. Congrats on all the traction. And hopefully we find some people on source at the point. Yeah, that would be great. Yeah, absolutely. Thanks so much.

Starting point is 01:44:40 Great to see you, David. 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,

Starting point is 01:44:53 to the next guest. Drew Roe in the chat says, I don't know if anyone said it, but the Risen X3D is the only way to go for your racing sims set up. Oh, that's an AMD. That's an AMD. We might have to do AMD.

Starting point is 01:45:07 I had a redwra. Could you email us and give us some, we've been talking. I think we're dealing with an expert here. An expert. We've been talking to our friend Paul, who's a racing enthusiast, getting some recommendations there,

Starting point is 01:45:20 but putting together some rigs for the team. Yeah. Well, up next we have Materiel with Kareem, the integration layer for AI agents. Welcome to the show. How are you doing, Kareem? Thanks for doing. Finally, somebody that is integrating agents. Great time. Wow. Almost, almost correct. Okay. Thank you, 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 Freed. He was saying that Open AI just wound up building a base camp integration. Out of nowhere one day, they just kind of told him, hey, it's live now, if you didn't have to do anything.

Starting point is 01:46:02 Is that not happening fast enough? 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? They all want to do the integrations as fast as possible. How is this going to play out? I mean, actually, one of the Open AI member of Technicists that have 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, Open AI won't give you AI integrations for the other providers.

Starting point is 01:46:31 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? Because these Fortune 500s can't just unleash an LLM with access to whatever your CISO's ASAP 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.

Starting point is 01:47:02 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 O'Penai reached out. That's a development from yesterday, so not too much, not too many updates on that.

Starting point is 01:47:24 But 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 are also in final stage discussions with some Fortune 500s and unicorns who would deploy this across the organization. Good side 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, right? So LMs, 10 years from now, will still need access to apps and data sources with access control.

Starting point is 01:48:01 Right now, the standard for that is MCP. So we basically have this middleware layer translating between our platform and MCP. But 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,

Starting point is 01:48:20 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. 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,

Starting point is 01:48:41 maybe customer support agents. Okay. We are completely unopinionated about how you build your age. We just provide you with the integrations. Sure. Right? Because every agent will need to do read and write operations on these apps and data sources. And if you can take a tax on that, you figure out how big the market is.

Starting point is 01:48:59 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 three people go in there, use these LN capabilities

Starting point is 01:49:24 and these, for example, legal agents or healthcare agents to compete with unicorns or large established players. I think that's really exciting. You kind of got this Goliath 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,

Starting point is 01:49:41 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,

Starting point is 01:50:06 and then sold those extra things like enterprise Java, et cetera, on top, we want to be the substrate for the integration layer and the access control layer and then adds 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, like, what's breaking out in their supply chain?

Starting point is 01:50:28 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. And what I mean by that is we, my co-founder and I have been, have had formal computer science education for over 11 years. Sure.

Starting point is 01:50:55 So we met in an 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 the 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...

Starting point is 01:51:30 You need to get an organic certification on the website, you know? Like, this is organic code? You can get the Austrian Amaguta Ziegle. Yeah, I love it. Let me guess the round's already done. Yes. Very fast. Makes you wrapped up in around five days.

Starting point is 01:51:47 Five days. I knew it. I knew it. Oh. I knew it. Congratulations. Love. Thank you.

Starting point is 01:51:54 Yeah, loves hearing how you're, you know, thinking about the opportunity and how opinionated you are. So, congrats on all the progress. Excited to follow on. I'm, I'm sure, I'm sure you'll be back on the show soon. We'll talk to you soon. Thank you so much.

Starting point is 01:52:08 Have a good rest of your day. Before bringing our next guest, let me tell you about fin.a.i, the number one AI, AI agent for customer service automate the most complex customer service queries on every channel with fin.a.i. And we have Philip 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? You always had to have one hand on the mouse. You never just on the keyboards guy. Always had one hand. Very soft. Very soft. I can hear Andrew Reed losing respect from you all the way from here.

Starting point is 01:52:46 He's getting cooked. All the way from the valley. Indeed. Well, he is in the Restream waiting room. Let's bring in Philip from Crunch to the TBP and Ultram. Philip, welcome to the show. What's happening? Thanks for joining us.

Starting point is 01:53:00 Please introduce yourself in the company. Hey, guys. Pleasure to be on. Great to meet you. Michael, actually, from Crunch, who did the last minute switch here. Oh, okay. Good to see you, Michael. Co-founder as well, CEO of CROCed.

Starting point is 01:53:12 Fantastic. Maybe I give you a two-second description of Crunch then. Crunch 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. And 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.

Starting point is 01:53:37 But there is a company that's trying to build co-pilot. 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 from 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.

Starting point is 01:53:58 They're building a co-pilot for 2 billion Excel users, and they're in competition with Google Sheets, right? I 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, right? So this is more of the 5 million of the Excel users the top 1%.

Starting point is 01:54:21 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

Starting point is 01:54:43 and working super closely with these power users to make something that actually integrates into their everyday Excel life? Yeah, 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 me and my co-founder, Philip, in McKinsey and another finance

Starting point is 01:55:12 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 like some of the bit artificial benchmarks you see around. So, for example, crunch can detect mistakes and workbooks. Plenty of time is spent in like private equity firms. I'm actually reviewing Excel so making sure they are correct.

Starting point is 01:55:36 as 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 like basic analysis 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 Cursors' main advantages is that they have a really solid data flywheel

Starting point is 01:56:04 now from open source. developers and developers who are not in a 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. like it is probably a higher bar to not letting that leak into a training run. So how do you get a data flywheel going?

Starting point is 01:56:41 How do you improve the product iteratively? It's a good question, right? And as you say, security is top concern, I think, for all of our customers who live with a global consulting firms, but also... Let's give it up for global consulting firms. They don't get enough love. They don't get enough love. Except here. Except here, except here.

Starting point is 01:57:04 I will defend Accenture. Exactly, exactly. That's good. But they're obviously super 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,

Starting point is 01:57:31 We want to make sure that we tailor crunch to every single firm. That's great. And then when we tailor it, we have discussed with a few customers, like the opportunity to, like, for some of the large organizations, they do enough modeling work on a global base that is possible to like tailor, do some fine-tuning and tailor to their specific organization. But as well, we come in in a forward-deployed manner and do customization, whether that is formatting or solving for their specific workflows

Starting point is 01:58:00 and linking into their templates. How, like the Sims that they get, how can we 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.

Starting point is 01:58:18 I can tell you about the most impactful. 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. Crunch has this error detection system.

Starting point is 01:58:41 And on a live deal for an associate that one of our private equity clients in London used the sort of crunch mistake detection system to identify or like 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 from $5 million right now.

Starting point is 01:59:06 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, Michael. We'd love to talk to you more.

Starting point is 01:59:18 I live for Excel agents. I'm so excited about this category. It just feels like I would love to. Thank you. We'll have a great rest of your day. We will talk to you soon. Great hanging, Michael. All right. Thanks, guys.

Starting point is 01:59:33 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,

Starting point is 01:59:49 there's some folks put in Menlo Ventures in the Truth Zone. Enterprise Large Language Model API Market Share has been falling for OpenAI. It'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.

Starting point is 02:00:11 He says, people are quoting this Menlo Ventures chart and extrapolating from it like its 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, too. At the same time, is it possible that OpenAIs Enterprise Large Language Model API market share is falling? Sure, you know, they were the only game in town when they launched.

Starting point is 02:00:42 And so you would expect their market share to fall a little bit over time. We'll 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 that happens, we will return to our coverage of YC Demo Day 2025. We have Sava, the AI-powered trust company.

Starting point is 02:01:05 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.

Starting point is 02:01:14 Tell us what you're building. Great. Yeah, I'm Nimit Maru. We're building Sava. We'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, not, not, because people would say a trust company could be somebody that make sure your, your password doesn't get leaked or something, but this is specifically for

Starting point is 02:01:41 angi 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? What were you doing before this? Well, my, my previous company was actually in John's, um, oh, no way. batch, summer 12 batch. No way. No way. What company? Yeah.

Starting point is 02:01:57 And we, so at the time we were building Yelthy, which was a, 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 code education and like tech education company. And that's how we kind of built that. And then sold it in like 10 years later. If you hadn't pivoted, you could have been selling math at scale. some of the other telemedic companies, but I'm glad you did. I'm glad you went the code.

Starting point is 02:02:29 Very cool. Did you say selling meth? No, no, I'm just, I'm just joking because. I got sure. But there were some, there were some, there were some telemedicine companies that went a little bit too far. And one of the founders is in jail now. They're like, check if the patient's breathing.

Starting point is 02:02:44 If they are, give matter all. That's, that was going on. No, more seriously, talk about, uh, what's, are these Nevada trusts? like what's what's the what's happening at the actual like entity layer sure yeah so we so we're not drafting the trusts we we will basically like a an attorney or a like a fintech or legal tech that uses lLM to drafts 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,

Starting point is 02:03:27 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. So would you, do you have like no consumer-facing brand essentially? It's like 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 choose. Because, I mean, how would a family know even what a trust company is or so we think of them as the ICP? Sure, sure. Are trust underrated?

Starting point is 02:04:11 Yeah. I think they're underrated and they're underutilized. And also right now they're very annoying and expensive to create and manage. Sure. And 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 are being utilized. Yeah.

Starting point is 02:04:35 Do you have a ballpark cost figure for, you know, doing a trust? At what scale does it start to make sense for customers to even participate in the market to even consider a trust? 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 for, like when someone would own house. Just as soon as your own house. Makes sense.

Starting point is 02:05:05 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 and assets before they start utilizing that. I think that as as like tech makes it a like a lot easier and cheaper to create trust in a good way and also, you know, people like us can make it a lot more friendly and modern to administer trust. Like I think more people will be able to use them. It should just get way cheaper.

Starting point is 02:05:46 I mean, if you think about just the YC store. 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 like fees across everything. Now it's like Stripe Atlas, one click, they charge you, what, 200 bucks or something? 500 bucks. And then the safe is like one second and, you know, administered by a bunch of folks. And it's like really, really low cost, and that's obviously led to just more entrepreneurship. You would imagine that something similar happens.

Starting point is 02:06:26 When the infrastructure gets better, like usage goes up. And even the safe, like I was talking about a co-parano the other day. Like the safe is an incredible invention that makes this like early stage of fundraising, you know, so much smoother. Like back when we did it in the summer 12 badge, it was like all convertible notes. And, you know, even that a lot of investors wanted price rounds. At this stage, it's like a pretty difficult. thing. So yeah, I think when the infrastructure gets better, like, more people utilize it and, like, more people can take advantage. Well, congratulations in the progress. Thanks so much for coming

Starting point is 02:06:59 on the show. Yeah, excited. Just check the product out. And we'll talk to you soon. Have a good rest of your day. Thank you. Cheers. Goodbye. Thank you guys. Let me tell you about profound. Get your brand mentioned in chat, GBT. Reach millions of consumers who use AI to discover new products and brands. I want to pull up this chart of the day from CO2. They say, hey, look, look. there's no code red here. It's all Baja blast because chat chpity traffic historically dips this time of year.

Starting point is 02:07:27 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 triptophan is coursing through their blood. They're getting a little sleepy. They're getting a little sleepy.

Starting point is 02:07:42 They're having an extra bottle of wine. And they're taking time off from their chat app specifically from chat chbtee. This is bizarre that this chart tracks so much with when people do work. You can see that chat chagipt grows in the 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.

Starting point is 02:08:08 It's almost like it's a tool used by students and students and people with jobs. That's everyone. That's everyone. That's everyone. 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 were supposed to continue to use all the AI apps. Anyway, it's a fascinating, it's a fascinating chart. I'm sure we'll be digging into it

Starting point is 02:08:37 more reading the tea leaves. But up next, we have Ben from SF TensorFlow. It's Versal for GPUs. Welcome to the show. Thank you so much. Please introduce yourself in the company. Great to have you. Hi. Yeah, thanks. I'm Ben. We're building the infrastructure layer for AI researchers. So basically from, you know, training models from like small experiments all the way up to large-scale frontier training runs.

Starting point is 02:08:59 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 neoclux? Are you a neocloud? How are you positioning yourself? Yeah. So we work with all sorts of neoclods 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. And so we deal with, you know, finding GPU allocations, optimizing for different GPUs.

Starting point is 02:09:39 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, you know, from last batch, 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. What are your clients, like, what's the shape of them?

Starting point is 02:10:17 I guess there's a lot of focus when people think training, they think Open AI, Anthropic, Google, Deve Mind, 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, how they're, 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, you know, or

Starting point is 02:10:47 researchers at home who are training like small models. And 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 training their own models.

Starting point is 02:11:13 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. Things 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?

Starting point is 02:11:43 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-a-speech, for example,

Starting point is 02:12:00 is another type of model. 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.

Starting point is 02:12:28 And that felt like an interesting proposition when you think about if you do want a text-based model and you want it to be 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. That 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?

Starting point is 02:12:58 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 like post-training but sort of you know continuous pre-training almost, you know, continuing the pre-training. I think there's going to be a lot of use cases that come out of that And I think we can help there.

Starting point is 02:13:33 I mean, we don't really care what you're training on the hardware. You know, 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.

Starting point is 02:14:02 And how's the round going? We closed the first day of fundraising. First day of fundraising. There we go. I'm not going to docks, 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,

Starting point is 02:14:20 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. We'll talk to you soon.

Starting point is 02:14:33 Cheers. Have a good rest of you. Good to meet you. Let me tell you about getbezl.com. Shop over 26,500 luxury watches. Super intelligence for your wrist. Fully authenticated in-house by Bezel's team of experts. Brad Gersner on Trump accounts, POTUS was elected on a Main Street agenda to get the rest of America into the game.

Starting point is 02:14:54 And that's exactly what this does. Bill Gurley is 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 were some pushback. Some people are saying, well, if you compound at the S&P, even if you compound a 10% for 20 years,

Starting point is 02:15:23 like it's only a thousand bucks or a couple thousand bucks. It's not that much money. It's not life-changing. but, you know, it's like a piece of, it's one, that's just Dell's contribution. Like, there's going to be other people that are contributing corporations. There's $1,000 from America. And yeah, yeah, and there's a whole bunch of other ways to add money to the account over time, at birthdays and Christmas and stuff.

Starting point is 02:15:44 It's like targeted donations. And the most important thing is that's just a lockbox. So it's psychologically a lockbox. So I still stand with the, with the Gersner accounts. It's incredible. But we have our next guest in the Restream Waiting Room from, from Locus, payment infrastructure for agents. How are you doing?

Starting point is 02:16:01 Welcome to the tie-dye. Please introduce yourself and tell us what you're building. First tie-dye shirt after 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.

Starting point is 02:16:11 It's a first. Thank you. Yeah. And they, you know, thank you. And so they actually switched me up with the other guy. Oh, okay. I'm Henry. I'm, sorry.

Starting point is 02:16:18 Nickerous. Great. Yes, sir. Henry Tidei. Welcome to the show. Yes, sir. Henry from Icarus. Please introduce yourself and tell us what you're building.

Starting point is 02:16:26 Yeah, so I'm Henry, founder and CEO at Icarus, my background, airspace engineer, Georgia Tech, built 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. How, yeah, yeah. Not the closest, but not the closest. And in fact, if we flew any higher, we'd actually fall out at the sky. So we want to stay at 60,000 feet. You're like, but we're going to try flying a little higher.

Starting point is 02:16:54 Okay. How many hard tech companies were in this batch? I believe, like five or ten. Yeah, that seems about right. So you feel like it's been like steadily at five to ten for forever, basically. Take me through the bare case for stratosphere drones. What I've heard is, you know, people always refer to the SR 71. It's such an amazing plane.

Starting point is 02:17:23 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 the folks, we're like, yeah, it kind of sucks,

Starting point is 02:17:39 we can't build that because it was 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. So why not satellites for this use case? Yeah, from first principle. you're 20 times closer than Lower Earth Orbit,

Starting point is 02:17:56 and you can say 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, which has been too expensive. Sure. 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?

Starting point is 02:18:22 Are you using cheaper materials? Are you standing on the shoulders of giants? Like, what are you leveraging to actually make? Yeah, well, 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, very unique. It's icarus1.com. Or sorry, icarus.

Starting point is 02:18:42 That one. Icarus. That one. Correct. Yeah, the, to your point, John, it's about getting the right product specifications. Okay. For the first go-to-market. And so, yeah, our first product is.

Starting point is 02:18:54 It's a 20-foot solar-powered bird. Fly for weeks at a time. Yep. The bird. 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 has a battery, but it can generate solar power on the fly to increase the battery.

Starting point is 02:19:22 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 1 is 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,

Starting point is 02:19:58 you can't really carry very heavy payloads. You can't carry and deliver a lot of power. But the future looks like, and there's like no lots 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 up an area. So then that's like, that's the future. And what you can do from that, it's, I don't know, anyone's imagination near term there's a lot of clear directs line of sight towards defense and a market there again it's like really difficult it's not it's not like a category yet today there's no real markets but with defense there's there's a clear need uh very cool how do you actually get the drone up is this

Starting point is 02:20:43 something that you launch uh like a rocket and then it and then it sort of spreads its wings at some point like how do you actually get a 20-foot drone 60,000 feet in the air? You eat it? Yeah, so we use a balloon. Do you eat it? Oh, use a balloon, okay. Okay, that seems less violent than yeeding a 20-foot drone in the air. Some drones are yeated, I believe.

Starting point is 02:21:04 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. Like can you use Starlink effectively? is the backbone for communications. Yes.

Starting point is 02:21:21 That is our Beyond Linusite 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.

Starting point is 02:21:35 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.

Starting point is 02:21:51 There you go. There we go. Yeah, super impressive traction. I noticed, is it Ronik on your team? Was that Red Bull racing before this? Oh, no way. How cracked is Ron. That's awesome.

Starting point is 02:22:04 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 third of our team is SpaceX Tesla. Ronix worked at Tesla. before Red Bull Racing and also SpaceX as well,

Starting point is 02:22:21 but he's definitely a character. Yeah. Awesome. Well, great to meet you. I'm excited to follow along. The round already done. How's it going? Yes, raised a lot of money.

Starting point is 02:22:35 There you go. Hit the gong again, John. There we go. Yeah, buddy. Yeah, buddy. Yeah. Just coming on. Absolute legend.

Starting point is 02:22:47 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, so. Very cool. Well, have a good rest of demo day.

Starting point is 02:23:01 Congratulations for 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.

Starting point is 02:23:14 What a legend. I need to know from you if we have some. 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. I will also tell you about adquick.com, out-of-home advertising made easy and measurable, plan, buy, and measure out of home with precision.

Starting point is 02:23:36 Also, people are calling for Google to make glasses now because Google Glass. They did this 20 years ago, practically. Google Glass. But they're still working. Yes, yes, yes, yes, but through partners, through partners. So they've done the Google Pixel. They've done a variety of hardware devices, and they are working on some augmented reality

Starting point is 02:24:00 glasses again. But they're certainly not making as much of a big push, media push as they did with the original Google Glass, which was, like, it dominated the news. And 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.

Starting point is 02:24:23 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.

Starting point is 02:24:39 We build payment infrastructure for AI agents. Okay. MCP currently doesn't have payment infrastructure. That's why you exist. Is that what's going on? Yeah, basically. Plus trust. Trust is a huge part of it.

Starting point is 02:24:50 Okay, interesting. Are people actually like solving this manually right now? Are there payment, are they like agent to agent payments that are happening right now? Or is this something where we're thinking like 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,

Starting point is 02:25:22 payment automation has been deeply rooted in conditional automation, a series of ifs, ends, ors, et cetera. Now 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. I was, me and Jordy have been talking about this with the agentic commerce stuff.

Starting point is 02:25:52 We're using chat GPT. 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, you know, what's going on on that website. And I'm like, oh, you actually could if I gave you my credit card. I 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 is 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.

Starting point is 02:26:24 Right? In terms of like the more commerce side, I think that will be an industry that evolves over the next few years as trust is really developed because frankly on a on a wide scale consumer basis, that's really the biggest barrier right now is trust rather than tech. Yeah. 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.

Starting point is 02:26:48 locust so far. Amazing. What were you doing before this? John's got the gong for you. 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 Scale AI. Studied CS at Waterloo. Business at Wilford Laurier was the Finance Act's elite at Waterloo blockchain. Waterloo mentioned. Fantastic. Well, thank you so much for coming on the show. Congratulations. Yeah, great to me.

Starting point is 02:27:20 And I'm sure we'll be seeing you soon. Have a good rest of you day. Thank you. We'll talk to you soon. Let me tell you about wander.com. Book of Wonder with Inspiring Views, Hotel Great a Menis, Dreamy Beds, top tier cleaning, and 24-7 concierge service. It's a vacation home, but better.

Starting point is 02:27:35 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. Yes, that's right. And it's Jessica's second time on the show. We had a fantastic

Starting point is 02:27:53 conversation with her. The last time she was on the show, we talked about the get your bag culture and the carpet baggers and just all the cultural ebbs and flows of Silicon Valley and where we are culturally. So I'm very excited to bring in

Starting point is 02:28:08 Jessica and Paul, the founders of Y Combinator. They are being situated, living legend. We are closer. You are. They are. You're live now. 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. 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.

Starting point is 02:28:47 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. It's magical. I'm on a high. Incredible. There's a lot of stuff happening.

Starting point is 02:29:10 Yeah. How are you thinking about there was this moment. of 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, that open AI 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 build 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. Have you noticed anything in the founders that you talk to in an ebb and

Starting point is 02:29:44 flow of just the confidence with which they view the future right now? No. No, they weren't, founders weren't really worried that Open AI 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, Open AI, eating them in some theoretical future three years from now. Like, they're not thinking about anything three years from now. So I'm not thinking about that. We had another, we were talking to Hage about this, this idea that, potentially, I don't know, we're just in a new era where it is become easier for a small team of scrappy entrepreneurs to sell to Fortune 500 companies, to sell to the government

Starting point is 02:30:29 even. Do 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 AIify our organization, right? And he's thinking, damn, I have no idea what to do. And so some startup shows up and says, will AIify your organization? He's like, great, come in here. Very different from the way it used to be.

Starting point is 02:30:58 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. What 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.

Starting point is 02:31:28 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 special?

Starting point is 02:31:45 Well, you have to not suck because startups are discern. You can't 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've got to actually be good. I'd love to reflect on how marketing and launching startups, has changed over the last few decades.

Starting point is 02:32:14 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. They were offending people. Well, in their view is the right reasons. And their view is the right reasons. 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, like the concept of using rage bait,

Starting point is 02:32:38 both at the marketing level and the. product level, like, kind of exploded. I guess the question is, like, has intentionally pissing people off been something that YC founders have utilized across the eras to get, to get attention? Is it really new? You know, that's, that sort of technique sounds like the technique that would be popular with someone you describe as a bit of a scammer. And the thing about these scammers is they don't make the giant companies. They don't have a long-term. 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

Starting point is 02:33:20 random shit like that because, you know, they're never going to be that big. And of course, I haven't heard of the term rage-baiting either. Of course, in keeping with- Oxford-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. This is like talent, the media, investors, customers, etc.

Starting point is 02:33:58 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 in media 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 and tense fire, right?

Starting point is 02:34:20 Or when Apple was getting started and the users were like the people at the home brew computer club, right? The media didn't know about that. There was a no coalition. Hey, guys. You are an epiphenomenon. Zuck kind of did a little rage bait. 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 raided.

Starting point is 02:34:38 Yeah, but he didn't do it deliberately. No, exactly, exactly. And I was thinking about the Airbnb example, like the whole Obama O's 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.

Starting point is 02:34:57 That's all. And no, actually it was to make money. It was to make money. That was before YC. They didn't have any money, remember? They were dying. They needed to make money. They went and got these off-brand Cheerios, and they glued together the box of themselves just to make money.

Starting point is 02:35:10 I don't think they knew they were going to make money. We're going to have to consult Chesky. That was mainly to get money. What's it like being back in San Francisco? Sunny. It's fabulous. The energy is so great here. I'm so happy to be back and so happy to be around startups right now.

Starting point is 02:35:33 I'm having a great day if you can't tell. It 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.

Starting point is 02:35:49 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. Yeah, I have one more. I want to think through this concept that's been sort of, sort of lightly bandied about in the startup discussion, you know, ecosystem, this idea of the

Starting point is 02:36:11 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 what I remember about the Y Combinator promise, which was just the earnest hacker. The earnest hacker. And 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 capital and, you know, do something that's just been forgotten, not necessarily discover something new. And I was wondering if you have any reactions to this idea that increasingly there are

Starting point is 02:36:48 entrepreneurs that sort of get really big. Who knows if they win, but they seem to win on the back of just raw dealmaking talent, as opposed to raw engineering leadership? Maybe an enterprise more. You know, like, enterprise, you like sell crap to CTOs instead of selling good stuff to programmers. So salesmanship has always mattered more in enterprise. I have one observation from this morning session of Demo Day. Most everyone that presented this morning is an earnest hacker.

Starting point is 02:37:27 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. I think, you know, honestly, I would still bet on earnest hackers.

Starting point is 02:37:55 Yeah, I agree with you. Do you think that that's, that that is what the essential skill set of YC leadership needs to, 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, you know, the carpet bagger. And now it's, there's a whole industrial complex for how to fake your way and make it appear that you're in earnest hacker when in fact you're not.

Starting point is 02:38:26 If the YC partners are themselves hackers, you can sniff out a faker like that. It's not even a problem. Yeah, yeah, yeah. But that seems like the main way that YC creates value these days will just be continuing to hold that line, essentially. What do you think is your most? Yeah, I think, I think, you know, here's something that will reassure you. If you think, okay, is the earnest hacker thing, do that, did that just work for a while? And now maybe it's over?

Starting point is 02:38:52 Isaac Newton was an earnest hacker. It's way older than startups. Yes, yes, yes. This is what wins. 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.

Starting point is 02:39:14 So it's hard to say. How to Do Great Work is pretty good. But I think people like that one. Yeah. Right? I read Life is short at least once a year, but people like that one too. Yeah. I don't know.

Starting point is 02:39:29 I don't know. a weird question. You'd have to, you'd probably have to look at inverse page views, which gets the least page views historically. 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, that's very funny. Do you have anything else, what else? Paul, are we in a bubble? No. No, everybody is always saying we're in a bubble, you know. Like every year, people say we're in a bubble. Every year people say, like, the valuations at Demodai, they're too high now. They were saying this back in like 2010 when the valuations were like $4 million.

Starting point is 02:40:14 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.

Starting point is 02:40:45 Are foundation models good at writing LISP? You know, I've never, I 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, right? and there's a lot of LISP source code. So I think they'd be fine at writing this. How are you using AI in your life? I just use it like ordinary people do. I ask you questions.

Starting point is 02:41:10 Sure. Sure. Very boring answer. It's a good answer. It's not like, 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.

Starting point is 02:41:27 I really should write an LLL. Because you can't really understand this stuff unless you've written one. I should write an LLM, but I haven't done it. Yeah, didn't Carpathie publish a whole? Yeah, he did it. He did it. He did it. To teach himself.

Starting point is 02:41:41 You know that's why he did it. Well, he's 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, you know, to introduce founders to VCs or some crap like that. And I say, don't start a startup.

Starting point is 02:42:03 Get good at technology. Write an LLM. Yeah. 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, like, what the key insight was? I remember a lot of people saying, like,

Starting point is 02:42:22 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. And that was like a second wave of entrepreneurial energy that was unlocked by the YCE ecosystem.

Starting point is 02:42:49 We always had internet. We understand countries aren't all that. But do you think there are. other like underappreciated aspects of like the YC strategy or or is it really just as simple as you know 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 yes it's staggering how many are investors now actually yeah it's amazing

Starting point is 02:43:26 It's like taken 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 it sway into. the rest of the YC community, and it overall raises the level of founder-friendlyness.

Starting point is 02:44:00 Is that correct? You know what, though? It's not simply one-sided, because if founders screw over investors, if they, like, 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, like, 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, like,

Starting point is 02:44:25 thousand X returns, right? It's for the same reason, like, people in Silicon Valley don't focus a lot on tax evasion. Because what's tax evasion going to get you? Like 2x returns in a world where getting the right startups will get you a thousand X returns. Yeah. Do you think that the process of founding a company, raising money, is at its, the end of history in terms of efficiency. Like, the safe is the most efficient document we will ever have. Or do. 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.

Starting point is 02:45:07 So she has twice rewritten the rules. She has 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. We'll ask her. In fact, trilogy is very popular. Oh, yeah.

Starting point is 02:45:24 Okay. 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? Yeah. So probably not, because C. Levy's not slack.

Starting point is 02:45:39 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? I mean, think like housing affordability or any of these sort of major... You know, we don't have. have any grand strategic vision for what the startups do. Because the founders know that, not us, right? That would be like asking a publisher,

Starting point is 02:46:04 what novel do you think, would you have expected someone to write, right? Good publishers, they just let the novelists write the novels. So we would just, we just try and find good people. What do they do? Whatever these good people are interested in. Anything, 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?

Starting point is 02:46:29 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. If anything more common. 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 specialty 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,

Starting point is 02:47:03 hey, I have $200,000 raised and 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 $5 million and I got $20 million already or something like that. 20 employees. It's happening, right? You do see this, right? Well, no.

Starting point is 02:47:22 Usually they don't have 20 employees. Okay. Usually, usually, I mean, that would be, 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 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? Yeah, yeah, yeah.

Starting point is 02:47:43 Which really constrains your options. Yeah. So the problem with the 20 employees is not the cost. It's that they change what they limit what you can think of. You know, which is why you shouldn't hire. Just don't hire. What kind of guidance you give to founders around that are feeling a pressure to go from zero to 100 million in ARR in like three years or whatever, like 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.

Starting point is 02:48:18 If your growth rate is high enough, it doesn't matter what the absolute numbers are. You'll get there. You know, and so you just get a really good growth rate. And so the great thing about focusing on growth rate means you can like focus on startups. You can sell stuff to startups for cheap instead of having to go and do these big deals of big companies that take a long time and make your product stupider, right? You 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.

Starting point is 02:48:49 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 can 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. I 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.

Starting point is 02:49:34 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 like one 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.

Starting point is 02:49:48 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. And they're like, oh, isn't there some trick I could use to get virality? Couldn't I get virality instead? Just like 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.

Starting point is 02:50:12 It was in 2005 and it's just as much the recipe now. How many startups do you think, how many startups do you think YC will have per batch a decade from now? Because I think in a perfect world, we have a lot more earnest hackers. And they can apply to YC and if they meet them. I know you're not setting targets and there's not like a specific acceptance rate that you're trying to track. but we feel like YC is one of the most important institutions in the world, and ideally it can be bigger, but maybe there's some... No, no, no, they will be bigger.

Starting point is 02:50:56 They will inevitably 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 Seacorp in a few minutes, right? It's like there's all this sort of like 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.

Starting point is 02:51:23 And that maybe helps somebody that hasn't found the YC blog yet figure out how to get going. Where the training data, even if they don't know it. Yeah. 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.

Starting point is 02:51:51 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 people's wants that are limitless, not literally limitless because eventually you run out of Adams in the universe. but for all practical purposes in the near term, people's wants are infinite.

Starting point is 02:52:16 And 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,

Starting point is 02:52:34 and it's been great having you guys on. Yeah. Nice to meet. Thanks for having us. I love you guys. Yes, we love you too. Thank you so much. Have fun in SF.

Starting point is 02:52:43 Have a great rest of your trip. We'll talk to you soon. Thank you. Goodbye. We have to hop on a flight, but I hear it. Yes, 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.

Starting point is 02:53:00 If you know, you know. 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.

Starting point is 02:53:15 Deal Book Summit's 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 ProfG Markets podcast. I 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,

Starting point is 02:53:40 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, before we jump, can we, can we play this? Oh, Gary Tan's in the chat. Ali's in the chat. Gary, we hope you feel better. Canada's in the chat.

Starting point is 02:53:59 Gary feel better. 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. We talked to tons of YC. founders and the state of YC is healthier than ever, stronger than ever. Gary's got a elementary school or preschool. It's so rough. I've been there, man. I've been there. It's a care virus. Yeah. Well,

Starting point is 02:54:24 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 it was a world win. tour and I'm very excited about a lot of these companies. Yes, we will talk to you later. Cheers. Goodbye.

TBPN - 🟠 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

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