TBPN Live - 🟠 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 Ultrademps. 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 were 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 rage bait kings. Yeah, the company that sparked by their own definition. They call themselves the brain rot IDE.

Starting point is 00:00:45 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 businesses, what they're building, what they're seeing. It's always a fun time to check in with the good folks. over at YC. And of course, we will be telling you about ramp.com. Time is money. Save both.

Starting point is 00:01:04 Easy use corporate cards, bill pay, accounting and a whole lot more. Ayah, aye. And I will also be telling you about fall, the generative media platform for developers. Develop and fine-tuned models with serverless GPUs and on-demand clusters. So today I wrote about will AWS buy TPUs from Google

Starting point is 00:01:25 in the front page of the Wall Street? Journal's business and finance section, they're singing the Traneum chips praises. Amazon chips. Amazon's chips pose risk to NVIDIA. The whole week we've been talking to people

Starting point is 00:01:42 about... I don't know. What we're going to find out. We'll see. It certainly doesn't seem good to have more competition in the market. And take him, came on the show yesterday to talk about how NVIDIA was strong,

Starting point is 00:01:58 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 TPUV7 was pretty good and Anthropic was going to be buying some and they were also going to be leasing some and they maybe had some really...

Starting point is 00:02:18 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. 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.

Starting point is 00:02:43 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 To be clear, he didn't, 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

Starting point is 00:03:12 is the latest big tech company to muscle in on NVIDIA's turf. 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 Trainium 3 custom AI chip, which it says is four times as fast as its previous generation of artificial intelligence chips, 4X speed up. 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, or 350 million. 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.

Starting point is 00:04:00 But Anapurna Labs has been working on custom silicon for Amazon for a long time. 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 training 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 Leitersorf, the co-founder and chief executive officer of the

Starting point is 00:04:43 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. Yeah, he basically, yeah, it was real time. Yeah.

Starting point is 00:05:04 He looked like he was in a video game, but it was happening with little to no delay, a 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.com. So he said his company had a breakthrough enabled by Traneum 3-Each. by the Trainium 3 chip after trying out several other competitor chips, including

Starting point is 00:05:29 invidious 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. AWS gave Descartes early access to Training 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, 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

Starting point is 00:06:09 behind him. Wait. Well, that's like a reference. I think that's a reference to the actual call that I'm referring to. Weird. This is very weird reading the journal. 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. 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

Starting point is 00:07:07 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? I asked Matt Garman that question. You asked me that question. Yes.

Starting point is 00:07:34 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 funny to mock anyone for something like, you know, 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

Starting point is 00:08:00 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? 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,

Starting point is 00:08:26 you know, oh, there's this new Traynium 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 stock. but what's interesting is that like it is it is deployed i'm out some of their gtm staff today let's just say you'll have years to accumulate stock at cheap prices they're funny uh and so and so like yes there there obviously is value even if tranium winds up being for a particular niche like maybe it's for real-time video like maybe that's maybe that's what it gets really good at it could get

Starting point is 00:09:11 really good at diffusion it can get really good it doesn't need to just be like your your asa can be honed and honed and honed to fit a particular work. The thing with real-time video that's interesting, something that Descartes is focused on is working with live streamers, specifically on Twitch. Amazon owns Twitch. Oh, that'd be cool. That makes

Starting point is 00:09:31 that kind of partnership more interesting. I like that. And so, but so obviously there is value to saying hey, if you go to AWS, you can get bedrock and some services that have been fine-tuned specifically for Traneum. You go

Starting point is 00:09:47 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 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. And we'll have, 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,

Starting point is 00:10:28 we're not competitor obsessed. We're customer obsessed. We're customer obsessed. And so if the customer says, look, it's great that you acquired Annapurna Labs for $350 million. I'm really happy with what you've done with Traneum 3. It doesn't work for me. 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. This was another partnership that came out that Ben Thompson actually wrote about in intrateree, which you should go subscribe to.

Starting point is 00:11:13 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 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 AWS. And so even though your whole infrastructure might be on AWS, you might be going back and

Starting point is 00:11:52 forth to GCP constantly. Or you might be going back and forth to ATS all the time being like, oh, I got to go over to ABS, I got to go back. I got to go Azure, back to AWS, back to AAS, back to AAS. 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.

Starting point is 00:12:23 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. That would be a real treat. And if you're just tuning in, YC Demo Day coverage starts in 30 minutes. Yes. So it used to be fine to bounce around. Now the next generation companies,

Starting point is 00:12:47 they're maybe making their entire infrastructure decision based on who has the best AI products. What do you laughing at? 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

Starting point is 00:13:07 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 sky rockets. 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.

Starting point is 00:13:36 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, 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

Starting point is 00:13:59 can be completely commoditized. This is about open AI trying to dual source from every part of the stack. And I said, 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%.

Starting point is 00:14:30 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 because he's got a lot to talk about. All the hyperscalers and Open AI, but that creates problems, right? Because all the hyperscalers and Open AI

Starting point is 00:14:46 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. 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 perna labs yeah that's our cost yeah that's our

Starting point is 00:15:10 costs like you're just you're you're you're 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 video anti invidia alliance they call it the google complex which is probably a little bit better uh that consists of google broadcom celestica lumendum and ttm technologies this coalition stands in contrast to the open a i complex that consists of Nvidia SoftBank, Oracle, AMD, Microsoft, and CoreWeave, but you know who they left off the chart entirely, Amazon.

Starting point is 00:15:41 Amazon doesn't fit neatly into either of this. KOTU just loves, I think, 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.

Starting point is 00:16:00 But there's, yeah, I mean, I think it's accurate. I like, if you said, is, is Amazon more aligned with Open AI 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.

Starting point is 00:16:14 Maybe they will, you know, form their own complex outside of it. 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 competitor 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

Starting point is 00:16:51 they should rebrand training them to Amazon Basic GPU Amazon basics Accelerator basic 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 to think. Anyway, I just don't think Traneum 3 is the, you know, obviously everyone at AWS is like excited about it.

Starting point is 00:17:23 And it's a big deal. 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?

Starting point is 00:17:45 Like they don't have a Sholto. 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? Yeah, they don't have a run.

Starting point is 00:17:59 They don't have a run, right? 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 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.

Starting point is 00:18:46 I also wanted to go to NERIPS, which is going on right now, the premier AI conference. 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.

Starting point is 00:19:02 You got Scott Besson just going hard. You got Alex Karp going hard. No real surprises on either of those fronts. But I'm 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

Starting point is 00:19:26 this kind of success with TPUs. What about Amazon's Traneum? 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 Traneum 2. on TCO training flops and reduces the gap by 5% on TCO MEM bandwidth.

Starting point is 00:20:05 So the gap between NVIDIA and Traneum is actually increasing rather than decreasing. By the way, this math was done before CPX was introduced. I won't be surprised if CPX plus Rubin is cheaper than Traneum 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, that, that, that, uh, that thrives in what training is good at, and they can further niche down. But we'll see.

Starting point is 00:20:34 I mean, maybe they come from behind and they just destroy TPU, and we're all talking about training next year. 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.

Starting point is 00:20:54 Rest in peace to Claude. San Francisco's beloved albinan. alligator has passed away at age 30 that's a good age I don't know how long alligators typically live but I'm looking it up feels like 30 to 50 years for the American alligator a little bit short but Claude was of course often supportive often reaching 70 years or more yes anyways RIP there was you know obviously people started speculating immediately anthropic of course was the sponsor Claude and you know people were wondering was was there foul play involved

Starting point is 00:21:35 was it possible this it this poor dinosaur not dinosaur alligator passed the day that they that that it got announced that they've hired IPO lawyers some people were speculating could is it possible Claude was sacrificed to the capital markets gods and some type of ritual but But anyways, he, look at this expression he has on his face. Can we zoom in a little bit? What a cool guy. And he will be remembered. Yeah.

Starting point is 00:22:11 Dan Primak 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. 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,

Starting point is 00:22:35 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. And so makes sense that the government's investing in Intel, Pat Gelsinger, of course, former Intel CEO.

Starting point is 00:23:00 Now he's getting involved in 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,

Starting point is 00:23:19 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 attacking and down the stack. Oh, he did. I didn't hear about that. Very cool.

Starting point is 00:23:35 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. They hope will remake the $800 billion chip industry. Anna Goldie and Azalea Mirosni are trying to buy. build software that can automate the design of cutting edge chips, a prospect that would

Starting point is 00:24:00 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 cap intelligence and then what was the other one there's what what's locky grooms uh company physical intelligence there's physical intelligence physical capital so it's the matrix of like capital uh what was it capital intelligence and

Starting point is 00:24:41 intuition or something like that and you and you multiply them all out and you get the whole eventually we're going to run out right there's somewhat finite no there will always be more names start up new new words so Wow, the company, $35 million for a valuation of $750 million. That's a very low dilution. What, 5% or something like that? Pretty remarkable. Definitely.

Starting point is 00:25:07 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 use and 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.

Starting point is 00:25:33 I had a funny moment yesterday. We got an Amazon package, and it was covered with, like, alienware branding. And I asked, I asked Sarah, I was like, did you get something from alienware? Like, what is it going on? And it turned out to be an ad, but they were advertising that is powered by, like Intel. Oh, interesting. Which, which, uh, didn't make me necessarily want to immediately buy an alienware device. If you do, you, 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. No, Intel is

Starting point is 00:26:10 undisputably great for gaming. There's no question there. The question is, are they going to, you know, be able to build a fab that competes at TSM? It's a completely different question. Um, I might go build an alienware Intel PC. Well, we're going to for the office sim racing rigs. The sim racing needs to be Intel inside for sure, for sure. This is just going to turn into a sim racing show

Starting point is 00:26:35 where we watch other podcasts while sim racing and reacting to it. Yeah, I like that. Vanta, automate compliance and security, AI that powers everything from evidence collection and continuous monitoring to security reviews and vendor risk. Dwar Cash Patel

Starting point is 00:26:50 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. 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.

Starting point is 00:27:37 For example, I think we're actually talking to an AI Excel analyst for Excel power users called Crunch 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 is AGI arrive, when does superintelligence arrive, I understand, to our case's point, he says either these models will soon learn on the job in a self-directed way,

Starting point is 00:28:04 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. Barron made interesting points about this in a recent blog post. When we see frontier models improving at various benchmarks, we should not, we should think not just of increased scale and clever ML research ideas, but billions of dollars spent paying

Starting point is 00:28:29 PhDs, MDs, and other experts to write questions and provide example answers and reasoning targets. Let's give it up for the experts. These precise capabilities. In a way, this is like a large scale reprise of the expert systems era, where, instead, of paying experts to directly program their thinking as code. They provide numerous examples of their reasoning and process, formalized, and tracked, and then we distill them into models through behavioral cloning. This has updated me slightly towards longer AI timeline since we, since given

Starting point is 00:29:01 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 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 with

Starting point is 00:29:43 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, that seems super implausible to me.

Starting point is 00:30:19 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

Starting point is 00:30:47 beforehand. I want to go to the section on economic diffusion. But first, I'm going to tell you about Privy. Privy makes it easy to build on crypto rail, securely spend up light label wallet, sign transactions, and 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 Dorcas has to say about economic diffusion. He said, that economic diffusion lag is cope for missing capabilities. And so this is also seems informed by the Tyler Cow intake that AGI is here. The models are good, but it just takes time to adopt them.

Starting point is 00:31:26 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. There's just someone who runs that doctor's office is like, I like doing it the old way, right?

Starting point is 00:32:02 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 TVPN 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 Doric Cash is fair to that too, where he was trying to. trying to find the most interesting pieces of a full podcast with one big Gemini prompt. And he was trying all the different models and couldn't get it to actually find like the most salient and viral points.

Starting point is 00:32:48 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 scientists studied people who had had various brain injuries that limited their ability to experience emotion. Yep. And when they took out emotion, it took them, it would, it can take somebody two hours

Starting point is 00:33:19 to figure out which pair of socks to choose. Yes, true. And they were kind of like stunned, like, it's just a pair of socks. Like, you know, like, you know what's going on in your day. Yeah. Why do you need emotion in order to make that kind of decision? And so it seems like at least in, uh, AI, a missing capability is like, okay, finding out, like, what's an interesting moment of a podcast in Varkesh's case, right?

Starting point is 00:33:42 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, 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. the word of last year.

Starting point is 00:34:07 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. 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.

Starting point is 00:34:34 Like someone on the timeline had also identified. that it was like that was the crazy moment that we should be like reacting to and taking in and it's crazy the other thing that's that's notable is like on wop one of the best 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 we're still paying humans to do that still. I mean, it just feels notable. Yeah. Well, let's read Dwar Keshe's take on economic diffusion lab lag being

Starting point is 00:35:16 copium for missing capabilities. It says sometimes... Copium would be a beautiful name for an AI chip, by the way. It would. It would. You got tranium. Maybe they need... Got copium. Sometimes people will say that the reason that AIs aren't more widely deployed across firms and already providing lots of value outside of coding is that technology takes a long time to diffuse. Dworkash thinks this is cope. He says people are using this cope to gloss over the fact that these models just lack the capabilities necessary for broad economic value. Stephen Burns has an excellent post on this and many other points. It says new technologies take a long time to integrate into the economy. Well, ask yourself how long, how do highly skilled, experienced

Starting point is 00:36:02 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. 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

Starting point is 00:36:23 than a normal human employee. They could read your entire slack and drive in minutes and immediately distill all the skills that your other AI employees have. Plus, the hiring market is very much like a lemons market where it's hard to tell who the good people are beforehand and hiring someone bad is quite costly. 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.

Starting point is 00:36:48 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 to spend trillions of dollars a year buying tokens, knowledge workers. Yeah. Think about that. We hire someone,

Starting point is 00:37:06 like we hire an AI or we're leveraging an AI and they've listened to every single minute of TBPN ever 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. Yeah. And I'm just saying like the, we do end up hiring a lot of people that are like previously just listeners.

Starting point is 00:37:29 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 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 yourself, this quote from Stephen Burns, how do highly skilled experience and entrepreneurial immigrant humans

Starting point is 00:38:03 manage to integrate into the economy immediately? I mean, they do sort of integrate 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.

Starting point is 00:38:19 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 out on the action,

Starting point is 00:38:39 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, we want to go after him to do. We want to get some of the hate. Wait, wait, wait, let us cook. Let us cook. We heard everybody in tech hates this article.

Starting point is 00:38:57 I do think... Well, 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. 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.

Starting point is 00:39:24 Pure ad hominin. But, you know. know off if people if people if people if your fans like it if that's what your your audience wants uh it's it's it's rage bait it's gonna go hard it already got a thousand likes on a linked article the verge is not putting up a thousand likes per link so this is outperformance and uh it's heavily pay Walt you cannot learn how david sacks sucks without subscribing to that thing they did a good job you got to pay you got to you want to know why he sucks uh i didn't you pay i don't know why he sucks but uh that'd be really funny if behind the paywall is like we're just kidding he's actually awesome that we think

Starting point is 00:40:00 the new york times missed on this one who knows uh paul graham yeah on the timeline he says a startup told me that one of their investors didn't like that they were selling to newly founded startups and wanted them to sell 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, we'll 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.

Starting point is 00:40:52 Yeah. 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 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 somewhat bad behavior.

Starting point is 00:41:25 general, it's like if I'm going to pay for the SaaS tool or the beta that you're running, it has to be good. Yeah. It has to work. Did you see, 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.

Starting point is 00:41:49 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, he's the co-founder of the Long Now Foundation, which takes no sides. In this forum, as a private person, I do take sides occasionally. So I thought that was a funny thing.

Starting point is 00:42:27 There is secondary market fraud going on left and right. But first, let me tell you about graphite.dev. 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 Anderl's growth while fleecing retail investors through unreasonable or opaque fee structures. In this week's episode of Nonsense, Ignite VC, a fund we've never. taken a meeting with or had any contact with whatsoever, founded by Brian, who we've never

Starting point is 00:43:00 met a soliciting investors via public Google Doc to invest in an SPV that will in turn invest in another SPV that will in turn potentially enter into a forward contract with a supposedly though unnamed early and oral employee. A few problems here. First off, so-called forward contracts are notoriously hard to settle in private companies, and counterparty risk is extremely real. what about the many 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

Starting point is 00:43:40 and then somebody 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 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? If they were just floating around information that they had acquired.

Starting point is 00:44:10 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, 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 pass through, in addition to an 8% upfront fee, 3% and, annual fee for two years, 20% carried interest, and the craziest part, an implied price per share that is

Starting point is 00:44:51 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 um and i believe the founder the founder replied and said appreciate the heads up the document reference was an internal draft prepared for discussion with an existing LP and was not intended for public circulation it appears someone shared it without

Starting point is 00:45:33 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 so got with this exact memo okay and the other thing is they say not soliciting investment for any Anderil related vehicle. Matt says, really? The draft was written by your founder and managing partner. I literally watched him edit the dock in real time. And he has a screenshot

Starting point is 00:45:56 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.

Starting point is 00:46:18 But we are moving on to our Y Combinator coverage. We have Harsh Tagar here in the re-stream 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.

Starting point is 00:46:37 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 what's the run of the show today and where are we in the course of the process of you know yeah graduating these companies so we got we got started like a 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,

Starting point is 00:47:10 and then the founders start giving presentations talking about 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 where the investors can hang out and talk to some of the founders and get to meet them

Starting point is 00:47:28 and, you know, obviously hopefully invest in a bunch of them. So that's kind of, we're like, we're just about approaching lunch. So it's kind of like that part of the day where people have listened to a bunch of companies He's probably got 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.

Starting point is 00:47:44 It's like live. It's the palace of 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? Yeah, I mean, we didn't go to 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,

Starting point is 00:48:13 which is just like the companies during the batch are just getting faster revenue growth, assigning contracts with, like, big companies. In some cases, like even like government, defense tech, like the dollar value contracts that startups can close in like the first few months of their life are just bigger than anything we've ever seen. And that's all like very directly from AI. So it's like, it's just exciting. And it's a very interesting kind of approach.

Starting point is 00:48:38 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, 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,

Starting point is 00:49:07 leaprogs again. Interesting. Yeah, help me square sort of the shape of revenue with some of the YC batch that we might talk to today because Paul Graham was on the timeline, sort of defending this idea of selling to startups. We were in complete agreement with that that selling to startups can be so much better in a bunch of different ways.

Starting point is 00:49:27 But it does feel like we're entering an era where maybe it's AI, maybe it's just the maturity of the ecosystem. Like it's also been easier than ever. to sell to the government or to sell to Fortune 500. And so are both happening in, are there specific companies that are really great at one or the other? 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, the ball case for selling two startups as your customers is like the Stripe or the AWS case. And like it's like,

Starting point is 00:50:01 you get them all early. I mean, you could put gusto, rippling deal into that. bucket as well. It's like if you get the startups early and you can grow with them, that is one of the most powerful business models you can have, right? Like the Stripe team could go on vacation for like two years and they would just like keep growing because like the cohorts would just keep going up and to the right, right? So like I don't think they're going to do that any time 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 will just like those startups in the future will become your enterprise customers, that's like fantastic.

Starting point is 00:50:33 day. 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. 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 the startups in the batch are able to go to a big company and actually get them as a customer because they're the only ones that can actually deliver the product. I think that's just

Starting point is 00:51:10 new. We still give the advice. It's very dependent on the company and the product and like will you be able to scale with startups or not. But like in general, there's just more options as a founder for how you do sales than there's ever been. 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. 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.

Starting point is 00:51:55 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 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

Starting point is 00:52:28 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. Saver is doing that with trust. It's like a company that sets up trust, but it's doing it with AI. So I think that 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, yeah, we've talked to a couple like law firms that have done that and also like investment banks, just people who have

Starting point is 00:53:08 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 um yeah i think i think you'd go bad you remember it was i mean it's like a decade ago now but it was ballagy that started this whole thing with like the full stack startup um he like he had this blog post and like i don't know if you guys were in san mcisco at the time but like there was this moment where there was door dash 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

Starting point is 00:53:47 San Francisco cooking the food, right? So I think back in that era 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

Starting point is 00:54:01 or selling software was just a better scalable business in that era. But now with AI, I think the promises were kind of going back to the full-stack startup idea, but this time, like, you know, we're all hoping and kind of seems like these things will actually scale because you don't need to hire like a thousand people

Starting point is 00:54:16 to do the work. 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,

Starting point is 00:54:25 oh, what if I did the full stack thing? Yeah. He's got picnic and I think it's Otter and then he has cloud kitchens. So maybe he's like, I can do it. But maybe at his scale,

Starting point is 00:54:35 maybe it's a scale thing. I don't know, but it is more complicated financial. I think if you have Travis it's like access to capital and his like background like operating, that you can, you can do that.

Starting point is 00:54:45 Yeah. How are companies or, or founders grappling with what's happening at the largest foundation model labs. Like, 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.

Starting point is 00:55:15 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, like, opening eye in particular to go after probably like maybe more of like the sexy consumer 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

Starting point is 00:55:42 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 or Anthropic are not going to be thrilled to build, like, auditing software or auditing agents, you know? Or actually sell the end service, right? Yeah, exactly. Like, doing it, like, going, like, all the way and, like, learning what that customer wants and how to do it really well and, like, it training on it a thousand times to get that.

Starting point is 00:56:10 Yeah, this is the whole thing with Google versus Amazon. Like, Google did wind up building a company. shopping product, but they never really had that in them to be like, we're going and doing warehouses. And we're going to compete with Amazon, even though we want e-commerce. It's like, we don't really want it that badly. That sounds actually sort of miserable. And it's just not going to do it, right? The best engineers at Google don't want to build a shopping product, they are like, back in the day, they wanted to work on search quality. Now they probably want to work on Gemini. Totally. Yeah. And there's, and there's also just cultural. I feel like culturally, there are certain

Starting point is 00:56:41 companies where, like, if you're like, we do 80% gross margin work and you show up and you're like, I'm the guy who does 30% gross margin work. They're like, you can leave the company, actually. Like, we don't like you at all. So, yeah, you know, your margin is my opportunity, both directions sometimes. Yeah. 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 long ago, right? Yeah, that was 2019, I think. So, yeah, I mean, obviously, Cali is like the prime example of a company that just made a bet on

Starting point is 00:57:23 a space early and, like, had to just wait for the market to actually exist for it. And, like, those founders, like, super sinacious went for it. I think, like, more recently, he's a company that announced around doing customer support called Giga, which I think is, like, really exciting one. 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 what like post hoc is actually like a little bit more under the radar.

Starting point is 00:57:59 But they are sort of like taking the rippling approach of. Yeah, they're launching a new product like every week, it feels like. Yeah, it's like really interesting to see. They've done that from day one, and it seems to actually be compounding and working the way that it has for Rippling. So I'm curious to see if you start seeing more of that, just like startups trying to build multiple products from day one and have like the compound startup effect. I like animal-themed companies. I like post-hog. I like the hog-themed.

Starting point is 00:58:27 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. Yeah, yeah. And we've got 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 Plaid Labs, makers of the Chad IDE. First, let me tell you about Julius AI, the AI data analyst that works you join millions who use Julius to connect their data, ask questions, and get insights in seconds. We have clad labs. While we wait, I have some other names for, if you're launching a startup and you want a pig theme's name, swine theme name, you could have Wilbur, 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 re-stream waiting room.

Starting point is 00:59:42 Let's bring him into the TVPN Ultradelm. What's going on? Look at this shirt. It looks fantastic. Incredible. You know, you're winning me over already. Break it down first. Introduce yourself.

Starting point is 00:59:53 Tell us what you're building. Good to meet you. How's it going, guys? Yeah. I'm Richard, the CEO of Clad Labs. We're building Chad IDE, the world's first brain rot ID. Okay. Why?

Starting point is 01:00:03 So, why? So great. So, so, we exchanged some comments. and wanted you to come on the show. I think you get the TBPN award for the best rage bait at the product level of the year. And I thought your response

Starting point is 01:00:18 to the essay that I did was amazing. You were like, cool essay. Unfortunately, it doesn't apply to us. So why doesn't it apply? What are you actually building? Like, why brain rot? Is it just for fun or is there something meaningful here? Do you think this turns into a real business?

Starting point is 01:00:34 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, so you're acting as a funnel to, you know, any affiliate that, 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,

Starting point is 01:01:05 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. Sure. We actually started out with affiliates on these very normal sites. And a lot of our users actually requested saying, hey, we actually like score on rainbed.

Starting point is 01:01:24 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? want, is this in keeping with the Y Combinator thesis and the values of the organization? Yeah, I guess so break down what's actually happening, 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,

Starting point is 01:01:53 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, right? So we have these AI native ads that are in context, and it's really great for code generation. Here, let me give you an example. So I say I code website, code me a website. Right now, Claude code has this 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 super base, say, yes, super base, that's a super base conversion right there. So the ad is actually in the context, in the application layer.

Starting point is 01:02:34 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, 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.

Starting point is 01:03:06 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 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? source, my most valuable human capital, tuning out every other second while they're waiting

Starting point is 01:03:39 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, John. But don't you think that it would be better to show educational videos than something like that? Oh, we have that as well. Yeah.

Starting point is 01:04:01 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?

Starting point is 01:04:16 So it's all about, I think, for BUC is being close to the user, iterating close to the user, and serving what they want. Have you been banned at any companies yet? Actually, the opposite. We had quite a few companies reach out to us and say, hey, we actually really want you to integrate our notion, our GERA board.

Starting point is 01:04:33 the whole like product productivity workflow into the generation time and we're like we really we're serving consumer right now but i mean there's a there's infinite possibilities here to scale at like various business levels uh how has attraction been to date it's been great yeah i think i other thank you guys for that as well helping us go viral so we have a great wait list successfully bated 11000 people on the wait list successfully baited has anyone has anyone used it yet have you built it is it is it is it in the wild? Is it a BS code for? What were the metrics that you shared at Demo Day?

Starting point is 01:05:08 Yeah, so the metrics I shared at Demo Day were 11K on the wait list, 30K in revenue from ads. We have people using right now in beta, and we're going to give out codes today at Demo Day. So anybody who comes up to us in Demo Day, we're giving you a code. It's going really great. Amazing. Find Tyler. I know he's probably in the

Starting point is 01:05:23 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, yeah.

Starting point is 01:05:39 We filled half the round. We have a lot of allocation to give out to people who were 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.

Starting point is 01:05:50 Have a good one. Let me tell you about Figma. Think bigger, build faster. Figma helps design and development teams. Build great products together. You can get started for free. We have our next guest coming into the Ultradome. This next company is absurd.

Starting point is 01:06:09 Really? Oh, wait, it is absurd. That's the name of the company. They will be joining in just a minute here. We might need to pop back to the timeline while we wait for them to sit down. Jordy, you can take a view here. This is a live view into the YCDemite. So if we jump ahead of the schedule, we can always check in.

Starting point is 01:06:30 there. But there we have the founder of Absurd in the Restream waiting room. Let's bring him into the TVPN Ultram. How are you doing? What's happening? Thank you so much for taking the time to talk to us. Of course. I'm doing good. How are you guys doing? I know you guys are only taking on a couple companies today. So thanks for having me on. We appreciate you. Fantastic. How you have you? Please introduce yourself. Tell us what you're building. Yeah. My name is Philip. I'm CEO of Absurd. Absurd makes AI marketing videos. an ad that we've made you've probably seen on your feet

Starting point is 01:07:00 is a college cheese Mamdani versus Cuomo 1V1 basketball match which we did right before the elections we like to joke that we influence the New York City elections amazing so what walk me through the product

Starting point is 01:07:13 it sounds like you're more using the foundation models using SORA V-O-3 than training your own but what are you building how do you fit into the stack are you more of like a creative agency that I hire and pay a lot of money for an ad

Starting point is 01:07:29 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, right? Basically, instead of building like an AI-native accounting firm or an AI-native law firm,

Starting point is 01:08:06 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 fixed price, and then you guys use your internal tooling and whatever models you have access to to generate the best possible output, and you deliver that end product.

Starting point is 01:08:26 exactly and what are you what are you charging on on like a per video basis today uh so a lot of that's confidential but i can say we charge upwards of 30 grand per video oh so so in the same you're effectively charging the same somewhat similar to like what somebody would pay for like a full day shoot totally yeah yeah you're in like the proper video production realm uh at least in terms of price. 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

Starting point is 01:09:20 company we work with regardless of whether you have 200 followers on Twitter or you have like a million um second thing in terms of what we're prioritizing um what we're really thinking about internally is just how many videos per person per week like what's that throughput looking like and then how do you drastically increase that week over week so three weeks ago that was one video per person per week today it's 10 super bowl quality ads per person per week made in parallel next week it's going to be 50 following week it's going to be a thousand i mean there was a company that came to us i can't say their name but um they said they won 1 500 of our kalshi super bowl ads in a month and that's the type of quantity that we're talking about here like this is this this is a lot of

Starting point is 01:10:05 money that we turned down 200 000 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 like you turn that you turn that revenue down uh 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 it's rampant. We still don't have capacity now. We are, we could literally so how many $30,000 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, uh, you know, a week. Yeah. So the way we were seeing things right now,

Starting point is 01:10:44 sure, we start out with launch videos that we charge 30, 40 grand for, but now, but now, we're going towards more of like a retainer, right? So now we're striking deals with companies like Kalshi, Replit, WOP, and we're telling them, you know, we'll do a bundle deal, 10 videos a month for X price. Sure. Right. And eventually it's going to go to 50, then 100 and 200. A lot of this is going to be used in ads 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 getting at to a point where like we have this huge compounding

Starting point is 01:11:24 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 in an AI ad, it's literally just like images and you're animating them. And as long as you have an agent that edits to images and changes the prompt slightly, you can create a thousand different variations and then test multiple things at once. Will we see any absurd commercials during the Super Bowl this year? I can't say, I, I, I, uh, you think maybe. That's a good answer.

Starting point is 01:12:03 That's a good answer. He can't, he can't, you know, people are going to look up his customers. Yeah. What do you think about 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, existing ideas. Yeah. Historically, the best creative agencies have been the agencies with the best ideas,

Starting point is 01:12:44 right? It's like you pay, you pay to work with. somebody that has a track record of generating great pain 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 yeah in terms of like creative production is like so much faster uh with AI yeah I think we think of creativity not as a modelist

Starting point is 01:13:21 but really in terms of two parts exactly how you put it so there's a taste layer then there's an execution layer our job here is we want to remove that bottleneck between an idea and a finished product so internally what we're doing to solve that is like sure we're not going to replace

Starting point is 01:13:38 human creativity we're going to automate human labor we're going to make it so easy for like a comedian or a script writer or someone who just wants a part-time job and we're going to pay them like a really high salary, really easy for them to like create the seed of an idea that we can spin off tens and thousands of ads for.

Starting point is 01:13:57 What, how much are you guys actually spending 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. 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

Starting point is 01:14:28 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 like close to like 98%. But if you add in human labor, I think it's still like above 90. How many different models are you using on an average 30-second video? Do you feel like it's worthwhile to stick to one model because you get more of a consistent look, 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. Seedream is good at specific use cases. Nanobanana is good as specific use cases. Kling,

Starting point is 01:15:07 Juan, all have their own unique use cases that we use. Something that's interesting beyond just of models, it's just like work, in terms of workflow orchestration, 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. And that wouldn't work. So the way you do it is you'd actually tell Nanobanana 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'd swap faces before Nanobanana a pro. So there are all these 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

Starting point is 01:15:53 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 timelines? I was speaking to Jess Lee actually about this. She was talking about how photography used to be seen as slop and because you know it used they used to say that photography was this way that she like artists were actually painting something um but photography allowed people to realize that allowed people to capture like a smile really quickly through slow motion um and something will emerge from this AI era where you can do something with AI video to capture some essence of human that you wouldn't be able to do otherwise. And we don't know what that is, but I'm pretty sure we'll be the first to figure that out,

Starting point is 01:16:42 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. for Philip in the absurd team. Thanks for coming on, breaking it down.

Starting point is 01:17:08 I'm actually surprised there's not more companies trying to do this exact sort of playbook. But it's cool to hear how you're thinking about this and excited to see more of the work that you guys put out. Of course, yeah. And by the way, before I go, I'd love to make a launch video for you guys. Let's talk. I would love that.

Starting point is 01:17:31 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. But we can come up with a bunch of different ideas. Let's do it. That'd be fantastic. Let's do it.

Starting point is 01:17:51 Perfect. Well, have a great rest of your demo day. He'll be in contact. Thank you guys for having. Talk to you soon. Cheers. Goodbye. Before we bring in our next guest, let me tell you about Adio.

Starting point is 01:18:02 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. Social brains for robots. Social brains for robots. Let's bring in. I like the sound of that.

Starting point is 01:18:18 Lightberry. Yes. Very interesting to see what robots we're talking about, but we have him here in the studio. Welcome to the show. Hello, how are you? What's happening? Lightberry. owning yellow, verticalizing yellow. I love it. I love it. You know, we have to wear something different. Everyone's wearing like gray and blue and black and like we need to stand up. 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 Lightbury. 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.

Starting point is 01:19:02 Before this, I ran a browser company called Sigma OS. I was running product and design there, and I went through YC in Summer 21. Very cool. Yeah, so that's me. Very cool. Talk more about that. This feels like a very big opportunity, but I'm not using a lot of robots in my day-to-day life today. I assume that I will be much more in the future.

Starting point is 01:19:29 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, emceeing the entire event for Demo Day. And, you know, he's fully autonomous. He talks. We give him some instructions about, like,

Starting point is 01:19:46 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 from at least 50 different manufacturers. But if you do that... Who did you buy yours from? So ours is from Unitary.

Starting point is 01:20:00 It's a Unitary robot. Did you buy it on wall? Walmart.com? No, no, no. I know they sell. I know they sell Unitary robots. 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.

Starting point is 01:20:14 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? How are you actually selling it?

Starting point is 01:20:34 Is this something that you want Unitri to kind of encourage their customers to adopt? Because, again, I'm sure any manufacturer of robots doesn't want to just sell to developer, hacker types that happen to want to go through all the different hoops in order to actually get value out of a humanoid. I mean, that's exactly it. You hit the nail on the head. We're working directly with the manufacturers. There's like over 50 of them. We actually just last week closed the deal with Unitri.

Starting point is 01:21:02 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.

Starting point is 01:21:25 We're going to be selling Lightberry powered robots with them all over the U.S., 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, Optimus, et cetera?

Starting point is 01:21:56 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 that's the rumor we'd love to help

Starting point is 01:22:13 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 will be in just maybe like two or three years.

Starting point is 01:22:32 Do you think we're going to go through like a wheeled robot phase or, you know, a one robotic arm on a Roomba phase? Like, how do you see? Because the self-driving cars are sort of here. The Roombas are sort of here. The full humanoid robot, that feels a little bit farther out. But is there going to be more of a transitionary phase in your mind? I mean, if you look at sci-fi as an indicator of what.

Starting point is 01:22:59 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 humanoid because like, why do you need locomotion in those cases? Humanodes are going to be the first like general purpose form factor that's going to make it, in my opinion, just because you know, they look like us. And the reason why we're building humanoids is because they look like people. 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?

Starting point is 01:23:35 Like, we have done this before. We deployed like a fully functional autonomous humanoid at the 11 Lab Summit like three weeks ago. 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.

Starting point is 01:23:53 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. Sure. And people prioritize the quality of interaction more than, you know, like the reliability of it. Sure. Now, we also run it, as I said, hybrid.

Starting point is 01:24:13 So we have an offline version that's also running in the same time. So if, you know, connection drops or anything, the robot will still talk to you. They'll still understand. It will 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.

Starting point is 01:24:34 Like, 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 all the robots talk like robots. And I'm wondering if you have any thoughts about where that all goes. I think prompting is just, I mean, these models are getting more and more steerable and they're better at following instructions. So as long as you do a great job of spending time on designing those interactions, you'll be able to get these robots to behave less like robots.

Starting point is 01:25:05 Now, we're not trying to make robots that behave just like people. Like, people love C3PO, but C3PO is very obviously a robot. It has a robotic voice. It's a bit awkward in the way it speaks. And that's the inspiration. It should just be 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

Starting point is 01:25:25 that it's representing if it's at an event. And that's what we're here to do. Like, we're just here to make that easier for all of those manufacturers because they're racing on hardware. They don't have time to think about the software and the interactions. Are you excited about robot pets as a category?

Starting point is 01:25:40 I know dogs are substantially cheaper, and that feels like something that a robot pet doesn't need to necessarily add any value outside of companionship, and so it feels like potentially an area where we could see a lot of growth in the near term. So we actually have like a little pets droid in our office. It's like a bipedal that kind of looks like R2D2.

Starting point is 01:26:04 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 that we could just focus on quality rather than like trying to optimize for cost. Obviously, as these robots get smaller, the cost gets lower, and so, you know, for us, we just want to, we just care about quality.

Starting point is 01:26:30 The models are going to get cheaper, too, so we'll be able to, like, deliver 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 just so much lower stakes, my opinion. What about security? I feel like there's a potential use case for humanoids, just having a human-shaped thing, just moving around. Actually, 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.

Starting point is 01:27:04 It was like, yeah. And he was like, you know what? I would love to deploy them for security. How much does it cost? And I told them, it's going to be like around 60 to 70K. It's like, I want four. I was like, okay, deal. So like he already pre-ordered them.

Starting point is 01:27:16 Like, people want this for security, not because it can fight, not because it can harm people. These things can't. It's just about the best deterrent. It's the best deterrent. And, like, you know, we can literally talk to weird people in the evening. It's like, who are you? And, like, run facial recognition. It's like, are you meant to be here?

Starting point is 01:27:31 And then just alert, like, whoever's on guard at staff and just call them and ask for help. Like, that's how it should work, right? Robots to help people, not to replace them. Yeah, I do think it's interesting that a lot of these humanoid companies are focused on the hardest possible thing, which is replacing, like, a housekeeper. Sure. who is already not the highest comps person doing the most, like, intricate, specialized tasks where somebody that's a security guard, their primary job is to just stand there and look like they're paying attention, and that's, like, the job.

Starting point is 01:28:05 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. And that's just really soon.

Starting point is 01:28:26 It's going to be fun. Very cool. 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. And how's the round going?

Starting point is 01:28:42 It's been very fun. I mean, we managed to close it pretty early. There's a lot of, there's some interest now because, you know, 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.

Starting point is 01:28:56 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.

Starting point is 01:29:05 Up next, we have Dome, a unified API for prediction markets. This should be fun. It's trying to sit on top of Colchin. Pick a favor. Pick a favorite. Pick a favorite. Well, 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

Starting point is 01:29:26 that there's two robotic lamp companies now? They're like, 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, full humanoid tomorrow for this much money, like that feels like a taller order. It's going to be a couple years away. But the lamp, I feel like we can do today. The lamp can talk to you. It's going to be funny. It's going to be awesome.

Starting point is 01:29:50 I'm excited. I'm really bullish on the lamps. But I'm also bullish on a unified API for prediction markets. So we'll bring in the founder of Dome. Welcome to the show. What's going on? Welcome to the TPP and Ultradome. You're in the Ultradome.

Starting point is 01:30:05 I love it. Please introduce yourself in your company. What do you do? Hi. My name is Kroo. 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 in a

Starting point is 01:30:16 analyze across multiple platforms at once. Okay. Who's the customer? Are you talking hedge funds or like the most advanced traders? Yeah, honestly, it's all of the above. A lot of our current customers are folks building applications in prediction markets. So these are folks building like prediction market skins or markets themselves or copy trading and agentic trading is like really popular right now. We talk to a lot of sports books and hedge funds as well. They're getting interested in high frequency trading. And also like platforms like, you know, things, sweepstakes apps, folks who are trying to like price internal parlay so there's a lot of applications currently being built right now

Starting point is 01:30:49 it's crazy uh very cool uh who's your favorite polymarket or kalshi i'm just kidding i'm just kidding i won't make you i won't make you answer that i was about to say that's the million dollar question yeah yeah no no i mean it's uh it's unfortunate you know it's unfortunate that the timeline is just so incredibly uh 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 uh exchanges how do you think this market it 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 evolve? Yeah, I mean, we're supporting currently Polymarketing and

Starting point is 01:31:36 Kalshi. They're both great. Obviously, we don't pick a winner in the fight. We want everyone to do well. And what we're currently seeing is there are a bunch of new platforms launching different regions, different specific verticals. Some folks are just like only sports, some are doing crypto, 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,

Starting point is 01:31:55 find their little market, their community there. And so in addition, you have Kalshi Polymarket, you will have Robin 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 basis start adopting this.

Starting point is 01:32:11 Do you have a, do you have a reference point for how cross-market transactions, like, is there a public markets equivalent to you or some sort of, like, 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, 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, hit it on the nail. But yeah, absolutely. So one, as you get a lot more providers in right now, a lot of the liquidity is fragmented. So if you actually look at just calcium polymarket themselves, about like 80% of their markets, their underlying contracts are the same event. So you actually have a good amount of overlap there. But you also hit it on the nail as well.

Starting point is 01:33:07 Like there are other markets you can match against. Like sports books are obviously very, very clear. There's a lot of prediction market overlap there. Crypto prices, perps, and all of 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,

Starting point is 01:33:31 basically seeing like, okay, what are the odds on 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 a one-to-one market versus, like, a maybe one-to-one market. Because personally, the way we got started was we were trading ourselves and got burned as well when two markets look similar, but they're not perfectly similar, and you lose a lot of money.

Starting point is 01:34:11 And so that's something we think you're just squeezing 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. are kind of not the right comp for this industry. Yeah, great question. Biggest answer is, like, we've kind of seen this exact playbook before. Both my co-founder and I, we were founding engineers at a company called Alchemy.

Starting point is 01:34:54 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, including open sea and polymarket. So we've seen this way. We've built a lot of, like, 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.

Starting point is 01:35:20 And then, like, interest kind of fades away, but people keep building. And then the next hype cycle, you realize, wow, the floor is raised. And so with prediction markets, you saw this during the 2024 election. Everyone was super excited. They thought this was the future. The election ended. Everyone's like, oh, this is fine. We'll see you in 2028.

Starting point is 01:35:36 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 or just providing the data layer? Because I imagine it could get quite difficult when some exchanges are using digital asset, you know, stable coins, others are using traditional fiat rails.

Starting point is 01:36:09 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 was then, okay, let's actually start doing order routing and routing these requests to these different platforms. And we actually just recently launched our order router as of last week.

Starting point is 01:36:37 And so we will be doing, we first are starting off on the crypto angle, like process. 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. 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

Starting point is 01:37:17 the lawsuits are like the equivalent of like maybe the taxi industry suing Uber back in the day, I think eventually most of this industry will move towards prediction markets. How's the round going? Round's been good. We actually closed up yesterday and so super super excited. We're excited to get back to the building. I had a feeling. I appreciate that. Yeah, I appreciate the excitement. It's been exciting journey so far well thank you so much for coming on the show yeah great to meet you congratulations thank you for writing domes yes we appreciate you we'll talk to you soon cheers have a good one uh before bringing our next guest let me tell you about none other than

Starting point is 01:37:52 turbopuffer serverless vector in fault deck search built from first principles and object storage fast 10x cheaper extremely scalable um for the forbs 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. 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 person making the 4.5. There's always a steel man. But there's some good folks on the 30 under 30. We'll have to take you through them at some point.

Starting point is 01:38:38 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. 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? Because I'm 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

Starting point is 01:39:23 applications. So it just saves the filling out form time. How's the traction? What is, what, yeah, so talk about, can you talk about the state of the hiring market? Because I feel like the number one complaint that candidates and people that are applying for jobs have is that, like, seemingly nobody reads, nobody actually looks at job applications. And a lot of roles don't actually end up getting hired based on traditional job boards. But yeah, what can you say about kind of what you're seeing in the market? Yeah, I guess it very much depends on the company and the role in the sector. But in general, people definitely still get interviews from. just inbound applications.

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.

Starting point is 01:40:29 But the inbound is definitely still something. that companies use because when you're hiring people at scale, there's just no other way to do it. Like if you're a company that's hiring like 200, 300 people a month, it's impossible to do it through. Yeah. So where we're 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, maybe that's incorrect. But where is the focus been? Yeah. 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

Starting point is 01:41:08 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. I'm assuming yes, because they're like you're going to get you more candidates. Yeah. So the ATSs themselves aren't like advertising or marketing. Like they're just fast, 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. Like, we want to want to get scraped.

Starting point is 01:41:45 But the ATS themselves, obviously, they are just, like, sending out emails to candidates and managing that whole pipeline. So, yeah, that's completely fine. And as for how the companies are reacting to it to answer someone's question. And, like, we've helped to get over 25,000 interviews in the past year. And those range from, yeah, those range from, thank you, 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 universe. universal fact is that filling out the form is very, very pointless.

Starting point is 01:42:32 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? 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

Starting point is 01:43:02 the camera and telling people about what we're doing and people like it. So 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, or by charging people for more swipes. We recently have gone like very, very free. like you really don't need to pay to apply to a lot of jobs anymore, but yeah, we used to make money from that. Since we've taken that down, we don't really make money from that anymore. And in the future, obviously, we plan to take the traditional job board route and work directly

Starting point is 01:43:38 with employers, just faster matches, get more applicants, et cetera. But right now we're very much just like product focus and we're kind of willfully ignoring revenue. Yeah. How's the round going? round is basically done. I think my co-founder is talking to investors, but it's really just for fun. We're not planning on raising any more money. Tell me to get back in the grind.

Starting point is 01:44:04 You don't need to be talking to investors if you close around. Small recommend, small recommend date. I don't like Tinder 4X. Oh, sure. I'm sure that that actually resonates really well with consumers. But the product's experience makes it makes a ton of sense. People think swiping.

Starting point is 01:44:24 They know swiping. Yeah, they know swiping. They're not getting away for that. 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.

Starting point is 01:44:39 Yeah, absolutely. Thanks so much. We'll talk to you soon. Have a good rest of your day. Let me tell you about Gemini 3 Pro, Google's most intelligent model yet, state of the art reasoning, next level vibe coding,

Starting point is 01:44:49 and deep multimodal understanding. before we go to the next to the next guest Drewro 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 chip.

Starting point is 01:45:04 Thank you for, we might have to do AMD. I had a redwhip for years ago. 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.

Starting point is 01:45:37 Great to have you. 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, right?

Starting point is 01:45:53 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. You didn't have to do anything. Is that not happening fast enough? Like, in what scenario would I need your service if all of the, it feels like there's a massive war going on between the LLMs? They all want to do the integrations as fast as possible.

Starting point is 01:46:15 How is this going to play out? I mean, actually, one of the opening. member of technical staff reached out to us for our products. Okay, okay, this makes sense. There's that, but basically one way to think about this is, right? First of all, OpenEI won't give you AI integrations for the other providers. People still want to be using Gemini.

Starting point is 01:46:32 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. LLM with access to whatever your sales post 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 Op. I reached out.

Starting point is 01:47:20 That's a development from yesterday, so not too much, not too many updates on that. 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 sign effects against the organizations with 80,100,000, 100,000 members. Is MCP complementary, competitive, substitutive? Like, 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 agent. we just provide you with the integrations, right? Because every agent will need to do read and write operations on these apps and data sources. And if we can take a tax on that, you figure out how big the market is. Yeah. Is there, I mean, I guess to flip the question around, just what agentic capabilities?

Starting point is 01:49:07 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 LM capabilities and these, for example, legal agents or healthcare agents to compete with

Starting point is 01:49:28 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, I might buy some AI legal SaaS, but I also might need to integrate

Starting point is 01:49:47 with some more niche tools or some more legacy tools. Are you the firm that I would go to to do those integrations for me? Yeah, we basically want to become the substrate for your integrations. So really, long term, we want to have a sort of Oracle story here. Similar to how Oracle became the substrate for enterprise databases, and then sold those extra things like enterprise Java, et cetera, on top, we want to be the substrate for the integration layer and the access control layer and then adds these additional things,

Starting point is 01:50:16 like the workflow builders or also hosting your agents, right? Yeah. 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. What's a tool or company or service or technology that you are leveraging to build this company

Starting point is 01:50:36 that you're particularly thankful for? See, this might surprise you, but kind of compared to a lot of other people, We are very OG software engineers. What I mean by that is we, my co-founder and I have been, have had formal computer science education for over 11 years. Sure. 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.

Starting point is 01:51:04 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... You need to get an organic certification on the website, you know, like, this is organic code? We can get the Austrian Amaguta Ziegle.

Starting point is 01:51:38 Yeah, I love it. Let me guess the round's already done. Yes. Very fast. It makes you wrapped up in around five days. Five days. I knew it. I knew it.

Starting point is 01:51:50 Oh. I knew it. Congratulations. Love. Thank you. Yeah, loved hearing how you're, you know, thinking about the opportunity and how opinionated you are. So, congrats on all the progress.

Starting point is 01:52:01 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. 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.

Starting point is 01:52:31 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 I can hear Andrew Reed losing respect. from you all the way from here. He's getting cooked. All the way from the valley. Indeed. Well, he is in the stream waiting room. Let's bring in Philip from Crunch to the TVP and Ultram. Philip, welcome to the show. Thanks for joining us. Please introduce yourself in the company. Hey, guys. Pleasure to be on. Great to meet you. Michael actually from from Crunch who did the last minute, last minute switch here. Oh, okay. Good to see you. Michael. Co-founder as well, CEO of Cunched. Fantastic. Maybe I give you a two second description.

Starting point is 01:53:14 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 have to 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 copilot, but there is a company that's trying to build copilot and they happen to own Excel. How are you imagining this plays out? Are you going to live in plug-in world? Are you going to live at the OS level and be screen scraping? Are you worried about sharp elbows from Microsoft? How are you dealing with all that? Ah, that's a great question. I think Microsoft is for sure going to build a great

Starting point is 01:53:58 product. 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%. So that's

Starting point is 01:54:21 a bit of the 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 what do you think they're getting

Starting point is 01:54:37 wrong or like you know or is this just going to come down to actual product quality and working super closely with these power users to make something that actually integrates into their everyday Excel life? Yeah, absolutely. So I think we have plenty of startups going after this opportunity. We don't think about competition too much,

Starting point is 01:54:59 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, and me and my co-founder, Philip, in McKinsey and another finance gigs. And I think that really shines through in the product. I think also crunched is modeling more like a real-life analyst and performing more of the real tasks that you do on the analyst floor versus like some of the bit artificial benchmarks you see around.

Starting point is 01:55:28 So, for example, crunch scan, detect mistakes in workbooks, plenty of time is spent in like private equity firms. I'm actually reviewing Excel and making sure they are correct. 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

Starting point is 01:55:51 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 now from open source. developers and developers who are not in a, you know, enterprise level contract, I imagine that the top one percent 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

Starting point is 01:56:31 information. It is probably a higher bar to not letting that leak into a training run. So how do you get a data flywheel going? How do you improve the product iteratively? It's a good question, right? And as you say, security's top concern, I think, for all of our customers who rely 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, except here. I will defend Accenture. That's good.

Starting point is 01:57:12 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. We want to make sure that we tailor crunch to every single firm. 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

Starting point is 01:57:48 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, right, and do customization, whether that is formatting or solving for their specific workflows 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, the, you don't need to name the company. Yeah, you don't need to name the company. It was a $500 billion company. they were doing a $1.4 trillion deal. They were doing about $20 billion in revenue. I'm not going to say who it was. Exactly, exactly. No, but I can tell you a real story about the mistake we caught,

Starting point is 01:58:37 though. Crunch has this error detection system. 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

Starting point is 01:58:57 that overvalued the deal by 10 million pounds. Wow. Whoa. You saved his job. Send him an invoice from 5 million right now. You just saved him 10. Give me 50% of that. That's your seed round right there.

Starting point is 01:59:11 Exactly, exactly. Well, congratulations on a fantastic demo day. Thank you so much. Yeah, great to meet you, Michael. We'd love to talk to you more. I live for Excel agents. I'm so excited about this category. It just feels like there's not.

Starting point is 01:59:24 I would love to. Thank you. We'll have a great rest of your day. We will talk to you soon. Great hanging, Michael. Good bye. All right. Thanks, guys. Numeral.com. What 500 billion dollar company could that be? Numeral.com. Compliance handled. Numeral worries about sales tax and VAT compliance. So you can focus on growth. Speaking of growth, there's some folks putting Menlo Ventures in the Truth Zone, enterprise large language model API market share has been falling for open AI. 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 Anthropical. 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 OpenAI's enterprise, large language model API market share is falling? Sure, you know, they were the only game in town when they launched. And so you would expect their market share to fall a little bit over time.

Starting point is 02:00:46 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. But until that happens, we will return to our coverage of YC Demo Day, 2025. We have Sava, the AI-powered trust company. Welcome to the show. How are you doing?

Starting point is 02:01:08 What's going on? Hey, I'm doing great. How are you? We're fantastic. Please introduce yourself. Introduce the company. Tell us what you're building. Great.

Starting point is 02:01:16 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, because people would say a trust company could be somebody that make sure your password doesn't get leaked or something.

Starting point is 02:01:39 But this is specifically for. How old were you when you realized you wanted to use AI to spin up trust? I'm just kidding. What were you doing before this? Well, my previous company was actually in John's batch, summer 12 batch. No way. No way. What company?

Starting point is 02:01:57 Yeah. And 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 a 10 years. later. If you, if you hadn't pivoted, you could have been selling meth at scale like some of the other telemedic companies by now. I'm glad you did. I'm glad you went the code. Did you say selling,

Starting point is 02:02:30 did you say selling meth? No, no, I'm just, I'm just, I'm just joking because. I don't know. But 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. If they are, give matter all. That's, that was going. Yeah. Um, no, uh, more seriously, talk about what's at are these Nevada trusts like what's 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

Starting point is 02:03:14 need someone to administer the trust to be an independent trustee that's when we would take over. We're getting our charter in Nevada. So we're going to be chartered in Nevada. Maybe eventually we'll go to other states, but that's where we're going to be right now. And yeah, we work directly with attorneys, wealth managers, fintechs to serve as the trust administration there. 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

Starting point is 02:03:56 from the attorney or the wealth manager about which trust company choose because, I mean, you know, like 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? Yeah. I think they're underrated and they're underutilized. And also right now they're very annoying and expensive.

Starting point is 02:04:16 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're being utilized. Yeah. Do you have a ballpark cost figure for, you know, doing a trust?

Starting point is 02:04:41 Like, at what scale does it start to make sense for customers to even participate in the market to even consider a trust. So I think creating a revocable trust that, you know, owns your house or other assets, that's applicable at, you know, at like reasonably, you know, like almost any level for, like when someone would own house. Just as soon as you own house. Makes sense. Yeah.

Starting point is 02:05:06 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. some millions, like, you know, maybe like low single digits, but or maybe mid-single digits millions in assets before they start utilizing that. I think that as, 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.

Starting point is 02:05:44 It should just get way cheaper. I mean, if you think about just the YC story of how much it cost to set up a corporation and raise a seed round in 2005 or something, you were looking at like 20,000, maybe 50,000 in total 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, like, it's, like, really, really low, low cost.

Starting point is 02:06:21 And that's obviously led to just more entrepreneurship. You would imagine that something similar happens. When the infrastructure gets better, like, usage goes up. And even the safe, like, I was talking about my co-paroundary 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.

Starting point is 02:06:45 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 on the show. Yeah, excited to 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, GPT, 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, there's no

Starting point is 02:07:18 code red here. It's all Baja blast because Chachapit traffic historically dips this time of year. And it's a fascinating chart if you actually zoom in on this Gemini 3 launch day. It looks like people

Starting point is 02:07:34 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. They're having an extra bottle of wine. and they're taking time off from their chat app, specifically from chat GPT.

Starting point is 02:07:50 This is bizarre that this chart tracks so much with when people do work. You can see that chat GPT grows in the spring every year up until summer. Then it completely flatlines during summer. Then it peaks when school year starts again and work starts back up. Then it crashes on Black Friday.

Starting point is 02:08:08 It pops a little. Students and people with jobs. People with jobs. That's everyone. That's everyone. Come on. What about the unemployed? Oh, yes.

Starting point is 02:08:17 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're 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 more, reading the tea leaves.

Starting point is 02:08:38 But up next, we have Ben from SF TensorFlow for GPUs. Welcome to the show. Thank you so much. Please introduce yourself in the company. Great to have you. 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, we basically deal with the 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,

Starting point is 02:09:13 And then there's the neoclouds. Are you interfacing with multiple neoclouds? Are you a neocloud? How are you positioning yourself? Yeah. So we work with all sorts of neoclods and hypers 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,

Starting point is 02:09:30 our 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. 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 you're and less, uh, focus on, on like actually inferencing on the product side. Yeah. So we focus exclusively on the, 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. Uh, we focus just on training because we think

Starting point is 02:10:05 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? I guess there's a lot of focus when people think training, they think Open AI, Anthropic, Google, deep 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 home researchers at home who are training like

Starting point is 02:10:49 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 from YC as well who are training models for super niche use cases. And then there's also, you know, companies that have raised hundreds of millions or, you know, up to a billion dollars. There's a bunch of labs actually in that, like, area who are doing, who are training their own models. You don't just have anthropic. I mean, like, the text-based models, like LLMs, there's not an awful lot of competition going on there anymore. Things have sort of converged at the top there.

Starting point is 02:11:23 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, of, of, uh, smaller models for specific use cases or one day billions? I wouldn't say billions, but definitely a lot more than there is today, especially just in the modalities that haven't been explored today. I mean, we're all focusing on text, and text is great for a lot of things, but I can't really use a text-based model to do things like, you know, text-the-speech, for example, is another type of model,

Starting point is 02:12:01 or we have protein-folding models, or all of these things can't really be solved with text. We need models that are specialized in those. topics. What about, I mean, we were talking to the CEO of AWS yesterday, and he was saying that AWS launched a product that is actually a checkpoint, 80% of the way done on an actual foundation model, and then a company can come in and add their own data to the pre-train. And then they can do everything else with it. And that felt like an interesting proposition when you think about if you do want a text-based model and you want it to be, to really know your company's data at the core in the pre-trained, really know it, not just drop it in the prompt,

Starting point is 02:12:42 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? How do you think about that? So it's a very unexplored area so far, the idea of basically saying you have like, you know, 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,

Starting point is 02:13:25 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. I mean, we don't really care what you're training on the hardware. If it's an AI training, we can help with that. So, you know, that's definitely something we're looking into. Do you want to ask about progress? Yeah. What kind of metrics were you sharing today during Demo Day? Yeah. So the metric we're sharing is we launched like two weeks ago and we did $41,000 in usage-based revenue since then. There we go. Love it.

Starting point is 02:14:02 And how's the round going? We closed the first day of fundraising. I knew it. First day of fundraising. There we go. I'm not going to docks, but a friend of ours said... We got a text message about you. We got a text message about you.

Starting point is 02:14:18 A friend of ours just backed one company this batch, and he's known for backing great companies. And he just backed you. So I'm excited for you guys to announce the round soon. And come back on and do it on TBBBBB. on and do it on TBPN. Thank you so much. Awesome. We'll talk to you soon.

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

Starting point is 02:14:54 into the game, 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 compounded over 20 years. for a bunch of individuals. And there was some pushback. Some people were saying, well, if you compound at the S&P, even if you compound a 10% for 20 years, it's only a thousand bucks or a couple thousand bucks.

Starting point is 02:15:26 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,

Starting point is 02:15:42 at birthdays and Christmas and stuff. It's like targeted donations. And the most important thing is that it's just a lockbox. So it's psychologically a lockbox. So I still stand with the Gersner accounts. It's incredible. But we have our next guest in the Restream waiting room from Locus, payment infrastructure for agents.

Starting point is 02:16:00 How are you doing? Welcome to the tie-dye. Introduce yourself and tell us what you're building. I like it. I like it. On TBPN, we've done over a thousand interviews. I don't think we've ever seen one. This is unique.

Starting point is 02:16:10 I like it. It's a first. 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 Inchris. Sorry.

Starting point is 02:16:18 Okay. Great. Yes, sir. Henry Tidei, welcome to the show. Yes, sir. Henry from Icarus, please introduce yourself and tell us what you're building. Yeah, so I'm Henry, founder and CEO at Icarus. My background, airspace engineer, Georgia Tech, built drones for NASA and satellites at orbital.

Starting point is 02:16:35 Cool. Chris 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 sun. 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, but we're going to try flying a little higher. Okay. How many, how many hard tech companies were, we're in this batch?

Starting point is 02:17:00 I believe, like five or ten. Yeah. That seems about right. And so you feel like it's been, like, steadily at 5 to 10 for forever, basically. Take me through the bare case for stratospheric drones. What I've heard is, you know, people always refer to the SR 71. It's such an amazing plane. It flies, I think, around 60,000 feet. The SR 71 Blackbird, it's this amazing Lockheed Martin plane built at Skunk Works,

Starting point is 02:17:31 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 and 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 principles, you're 20 times closer than lower Earth orbit, and you can say fixed over an area. So just from an engineering perspective, it makes a lot of sense.

Starting point is 02:18:04 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? Are you using cheaper materials?

Starting point is 02:18:25 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. It's icarus1.com.

Starting point is 02:18:40 Or sorry, icris.orgas.org. That one. Correct. Yeah, the, to your point, John, it's about getting the right product specifications for the first go-to-market.

Starting point is 02:18:52 And so, yeah, our first product, 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,

Starting point is 02:19:09 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 life effectively. Like it's not sufficient to hold it in the air forever yet, but it can stay up over a specific area. So is this primarily like defense applications? Early on, who are you trying to sell this to? Yeah, act one, it's all defense.

Starting point is 02:19:40 I do think this is much bigger than a defense company. I do see the stratosphere as a category. And once you kind of are able to make the stratosphere affordable, then there's many things you can do. So one easy example, like, yeah, today you can't really carry very heavy payloads. You can't carry and deliver a lot of power. but what the future looks like and there's like no lots of physics that says you can't do this

Starting point is 02:20:06 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 in area so then that's like that's the future and what you can do from that it's I don't know it's anyone's imagination near term there's a lot of clear direct

Starting point is 02:20:26 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 the fence, there's a clear need. Very cool. How do you actually get the drone up? Is this something that you launch like a rocket and then it sort of spreads its wings at some point? Like, how do you actually get a 20-foot drone 60,000 beat in the air?

Starting point is 02:20:53 Into the air. Yeah, so we use a balloon. Do you eat it? Oh, use a balloon. Okay. Okay, that seems less violent than yeeding. Some drones are yeated, I believe. This is a real thing.

Starting point is 02:21:06 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 as like the backbone for communications? Yes. That is our Beyond Line of Site method. Sure.

Starting point is 02:21:24 So we have Starlink on it as an option. Yeah, that's very cool. Yeah, fascinating. How close are you to actually getting this up in the air? Have you flown? Yes. Just test at this point. Are you actually going to sell these things?

Starting point is 02:21:38 We are selling them today to the Army. And, yeah, we've done over 30 successful stratospheric flights, successful demos with Special Ops Command, Socom, and the Army as well. And we have, oh, there you go. There you go. There we go. Yeah, super impressive traction. I noticed, is it Ronick on your team?

Starting point is 02:21:58 Was that Red Bull Racing before this? Oh, no way. How cracked is, uh, that's awesome. He is, uh, he is very, very hardcore. Um, yeah, 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, uh, third of our team is SpaceX Tesla. Uh, Ronix worked at Tesla before Red Bull Racing and also SpaceX as well, but he's definitely character. Um, yeah. Awesome. Uh, well, great to meet you. I'm excited to, uh, to follow along. How the

Starting point is 02:22:29 round already done how's it going yes uh raised a lot of money um there you go hit the gong again john there we go yeah buddy yeah buddy yeah oh just coming on absolute legend you're a tbpn legend yeah thank you we might have to uh we might have to make a tbpn tie-dye shirt in your honor yeah let's do it i love it thank you sad very cool very cool well have a great great rest of demo day. Congratulations all the progress. We're very excited to see these up in the stratosphere. Just don't fly them too high.

Starting point is 02:23:08 Yep, exactly. Perfect. All right, Jordy, John, thanks so much. Have a good rest of your day. Goodbye. What a legend. I need to know from you if we have some breaking news

Starting point is 02:23:19 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. Also, people are calling for Google to make glasses now because Google Glass...

Starting point is 02:23:42 They did this 20 years ago, practically. Google Glass. But they're still working. Yes, yes, yes, yes, but through partners, through partners. Got it. So they've done the Google Pixel. They've done a variety of hardware devices, and they are working on some audience.

Starting point is 02:23:59 augmented reality glasses again, but they're certainly not making as much of a, you know, big push, media push as they did with the original Google Glass, which was like, it dominated the news 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. Okay. 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

Starting point is 02:25:19 to people. The way I like to explain it is historically, payment automation has been deeply rooted in conditional automation, a series of ifs, ends, ors, etc. 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. We're using chat GPT.

Starting point is 02:25:53 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?

Starting point is 02:26:13 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, right? in terms of like the more commerce side I think that'll be an industry that evolves over the next few years as trust is really developed because frankly on a wide scale consumer basis that's really the biggest barrier right now is trust rather than tech

Starting point is 02:26:37 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 Locus 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?

Starting point is 02:26:59 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-Loreen was the Finance Act's lead at Waterloo blockchain. Waterloo mentioned. Fantastic. Well, thank you so much for coming on the show.

Starting point is 02:27:18 Congratulations. And I'm sure we'll be seeing you soon. Have a good rest of your day. Thank you. We'll talk to you soon. Let me tell you about wander.com. Book of Wonder with inspiring views, hotel great amenities, dreamy beds, top tier cleaning, and 24-7 concierge service.

Starting point is 02:27:33 It's a vacation home, but better. And we have some surprise guests, I believe, joining in just a second. We will have them in. Jessica and Paul, you may know them. They started a small startup accelerator called Y Combinator. Yes, that's right. And it's Jessica's second time on the show. We had a fantastic conversation with her the last time she was on the show.

Starting point is 02:27:55 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 Jessica and Paul, the founders of Y Combinator. Living Legends. Living Legend. We get closer.

Starting point is 02:28:16 There they are. You're live now. Welcome to the show. Thank you so much for taking the time to talk to us. 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. 100 more years. We'll make it. Great to have you guys on. What's it been like today? It's been crowded. It's buzzing. And by the way, this is our first demo day that we've been to in a few. 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

Starting point is 02:29:03 are all excited to be here. It's magical. I'm on a high. Incredible. There's a lot of stuff happening. Yeah. How are you thinking about there was this moment a few years ago where I think in tech, maybe we were afraid to admit it, but it felt like a lot of founders and a lot of entrepreneurs were sort of grappling with this idea that 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 built companies,

Starting point is 02:29:33 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 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,

Starting point is 02:29:56 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, um, where it is become easier for a small team of scrappy entrepreneurs to sell to Fortune 500 companies, to sell to the government even. Do you feel like something has materially changed and go to market for YC companies?

Starting point is 02:30:36 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? It's like, great, come in here. Very different from the way it used to be. I mean, if you show up with other products for the big company, they'll still tell you to talk to the hand.

Starting point is 02:31:04 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, The circular economy, selling to other startups. There are a ton of benefits, obviously. Startups are very discerning. If you mess up and don't deliver the product that they're buying from you,

Starting point is 02:31:32 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 discerning. You can't like have some bullshit. product and sell it based on a bunch of hype. It's got to actually work because they don't have time to mess around with things that don't work. And they're very sharp observers of technology. They're run by the founders themselves, usually at that point. So you've got to actually be good. I'd love to reflect on how marketing and launching startups has changed over the last few decades. Jordy, we had clad labs on, which we had a really fun time talking to them. But they

Starting point is 02:32:19 they sort of went viral for the wrong reasons. They were offending people. And their view is the right reasons. Yeah, in 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, both at the marketing level and the product level, like, kind of exploded.

Starting point is 02:32:41 I guess the question is like, has intentionally pissing people off been something that YC founders have, have utilized across the eras to get to get attention? Is it really new? That sort of technique sounds like the technique that would be popular with someone you'd describe

Starting point is 02:33:01 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 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.

Starting point is 02:33:18 you can skip the companies that do random shit like that because you know they're never going to be that big and of course i haven't heard of the the term rage baiting um either of course in keeping with it's the oxford it's the oxford word of the year so you can go look at their uh definition it's it's so interesting it's getting attention by making people mad i know what it means but yeah and we and i had written an article and and gary and i had a nice back and forth uh where I basically said, like, in startups, 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 and media wanted it to take off. All that mattered was that Zuck had this thing

Starting point is 02:34:15 and everybody at Harvard wanted to use it. That's all that. matters, that small, intense fire, right? Were when Apple was getting started and the users were like the people at the Homebrew Computer Club, right? The media didn't know about that. There was a no coalition.

Starting point is 02:34:29 Wait, did Zuck do a little rage rating early on. Zuck kind of did a little rage bait with the hot or not app. That definitely enraged a lot of people who didn't want to be raided. 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

Starting point is 02:34:46 McCain's, uh, 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. And make, no, actually it was to make money. It was to make money. That was before YC.

Starting point is 02:35:01 They didn't have any money, remember? They were dying. They needed to make money. They went and got these, like, off-brand Cheerios, and they glued together the box of themselves just to make money. I don't think they knew they were going to make money. We're going to have to consult. I'm pretty sure.

Starting point is 02:35:15 That was mainly to do. Money. What's it like being back in San Francisco? Sunny. It's fabulous. The energy is so great here. I'm just so happy to be back and so happy to be around startups right now. I'm having a great day if you can't tell.

Starting point is 02:35:35 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. We're like, but we've turned the clock back to maybe two years into London Reed. Oh, that's good. Okay. Yeah, that's great. I have one, yeah, I have one more. I want to,

Starting point is 02:36:00 I want to think through this concept that's been sort of lightly banded about in the startup discussion, you know, ecosystem, this idea of the deals guy era that you can actually build a business now by being more of the business person, the more of the deals guy, and less of 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 This idea that increasingly there are entrepreneurs that sort of get really big.

Starting point is 02:36:51 Who knows if they win, but they seem to win on the back of just raw deal-making talent, as opposed to raw engineering leadership. Maybe an enterprise more. You know, like enterprise, you like sell crap to CTO 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%. And 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 are earnest hackers now. Yeah. You know, honestly, I would still bet on earnest hackers. Yeah, I agree with you.

Starting point is 02:37:57 Do you think that that is what the essential skill set of YC leadership needs to be? Because I don't want to discredit all the hard work you did in the early days, but you didn't have to fight the fact that there were people out there writing blog posts of how to reverse engineer and make it look like you're an earnest hacker when, in fact, you are the, you know, the carpetbagger. 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. 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, the main way that

Starting point is 02:38:36 YC creates value these days will just be continuing to, 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. Isaac Newton was an earnest hacker. It's way older than startups. This is, 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. So it's hard to say.

Starting point is 02:39:15 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. That's a weird question. You'd probably have to look at inverse page views, which gets the least page views historically over the past year, let's say. 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.

Starting point is 02:39:45 that's very funny. Do you have anything else, what else? Paul, are we in a bubble? No. No, everybody's always saying we're in a bubble, you know? Like every year people say we're in a bubble. Every year people say,

Starting point is 02:40:03 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. And now they're like, what 30 or something typically so um 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 is it as big a deal as prices seem to suggest it could be

Starting point is 02:40:39 maybe even bigger it's definitely real it's not hype the AI is real 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.

Starting point is 02:41:09 I ask you questions. Sure, sure. Very boring answer. that's a good answer it's not like i stringed i'm training my own model to do a better google search what uh no no no i haven't actually written anything using i yeah yeah you know i feel bad i really should write an llm 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 carpathy publish a whole uh yeah he did it yeah he did it chat gpcg from first principles type of thing you know to teach himself you know that's why he did it

Starting point is 02:41:42 Well, he is 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, get good at technology, write in an LLM. Then you can start a startup.

Starting point is 02:42:07 Do you think, reflecting on the history of YC, do you think it's, 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, 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

Starting point is 02:42:47 that was unlocked by the YC ecosystem. We always had international. We understand countries aren't all that. But do you think there are any other, like, underappreciated aspects of like the YC strategy? Or is it really just as simple as, you know, fun? Well, there were things we didn't appreciate in the beginning. Yes.

Starting point is 02:43:07 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.

Starting point is 02:43:25 Yeah. It's amazing. 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.

Starting point is 02:43:45 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 friendliness. 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 and then refuse to go through with it, we would tell them not to do that, too.

Starting point is 02:44:13 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, 1,000 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?

Starting point is 02:44:38 Yeah. You know? 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 we need to speed things up even further? Well, C. Levy, Carolyn Levy invented the safe. And she also invented the convertible note that everybody used before it. So she has twice rewritten the rules. She has twice recreated the chessboard that the game is played on.

Starting point is 02:45:14 If she thought there was a better thing than the safe, she probably would have created. Maybe she has a third one in her. We should ask. We'll ask her. In fact, trilogy is a very popular. Oh, yeah. Okay. Yeah.

Starting point is 02:45:25 And you could ask her that, John, when you come on our podcast. We'd love to. I'd love to. I can't work. Is there anything wrong with the safe? And if, like, if there is, why hasn't she fixed it already? Yeah. You know?

Starting point is 02:45:36 Yeah. So probably not, because C. Levy's not slack. If there was anything missing, she would have, she would have, like, made a new version. Yeah, I mean, from my perspective, it seems like it's worked for. 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 any grand strategic vision for what the startups do. Because the founders know that, not us, right?

Starting point is 02:46:02 That would be like asking a publisher, what novel do you think, you know, would you have expected someone to write, right? Good publishers, they just like, they 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 or 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 employees already or something like that. 20 employees. It's happening, right? You do see this, right?

Starting point is 02:47:21 Well, no. 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. There's 20 employees constrain the idea you're going to have. If you just have the founders, you could do anything.

Starting point is 02:47:38 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. 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,

Starting point is 02:47:54 you know, which is why you shouldn't hire. Just don't hire. Just don't hire. What kind of guidance do you give? to founders around that are feeling a pressure to go from zero to a hundred 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 with 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

Starting point is 02:48:48 huge. Are you still recommending to folks who ask for advice for kids that they should learn to code? Yeah. Oh, yeah, yeah, yeah. I still tell people that. Or at least learn technology. It doesn't have to be coding specifically. You 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.

Starting point is 02:49:29 do. That and save your money. Yeah. That's really good advice. And no one likes to hear that, by the way, but I tell them anyway. Yeah. No, no. We give a lot of advice. People come and they want advice. It's like if you went to the doctor and you said, doctor, what can I need to be healthier? And the doctor says, eat less and exercise more. And you're like, oh, I was hoping you'd say something else. Yes, yes, yes. Well, that's what it's like when they come to me. They come to me for advice. And I say the

Starting point is 02:49:54 startup equivalent of eat less, exercise more. And they're like, oh, isn't there some trick I could used to be get virality could not get virality instead just like do the startup equivalent and eat less and get more exercise which is build stuff and talk to users understand your users and be good at building that's the recipe it was in 2005 and it's just as much the recipe now yeah how many startups do you think 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.

Starting point is 02:50:45 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. They will inevitably bigger because there's this secular. trend of more people starting startups. Yeah, do you think we're early in this, in this trend? I mean, it feels like there's so much, it's now you can create a startup, you can create a C-Corp in a few minutes, right? It's like, there's all this sort of like underlying infrastructure that's been built that

Starting point is 02:51:17 is reducing friction to starting companies. You can ask Chatsypte, how do I start a business? And it'll give you a good playbook. And that maybe helps somebody that hasn't found the YC blog yet figure out how to get going 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 um and there's a lot of earnest

Starting point is 02:51:53 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 atoms in the universe, but for all practical purposes in the near term, people's wants are infinite. And so there's infinite demand for good stuff you could make. Well, that's a great place to end. 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

Starting point is 02:52:31 it's an honor to cover every batch and it's been great having you guys on. Nice to meet. Thanks for having us. I love you guys. Yes, we love you too. Thank you so much. Have fun in SF. Have a great rest of your trip. We'll talk to you soon. Goodbye. We have to hop on a flight, but

Starting point is 02:52:50 you hear that, 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 that just glow in the back. But if you know, you know, you know. And also, if you want exceptional sleep without exception, you go to 8Sleep.com, you fall asleep faster, you sleep deeper, you wake up energized, and we should close out. There's a lot of stuff going on, deal book summits going on. There are debates raging on the timeline, but we will have to cover them tomorrow. We will close out with a congratulations to Ed

Starting point is 02:53:24 Elson, the co-host of the ProfG Markets Podcast. I love his bio because he says he's not ProfG's son, even though they look somewhat similar. He had a viral post yesterday because he got into Forbes 30 under 30

Starting point is 02:53:40 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, can we jump? Can we play this? Oh, Gary Tans in the chat. Allie's in the chat.

Starting point is 02:53:56 Gary, we hope you feel better. Tana's in the chat. 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.

Starting point is 02:54:07 We talked to tons of YC founders. And the state of YC is healthier than ever, stronger than ever. Gary's got elementary school or preschool. It's so rough. I've been there, man. I've been there. it's a daycare virus yeah well uh we hope you get well soon uh team we need to definitely send some soup or some flowers to gary tan as soon as possible and uh and we will see you all tomorrow thank you for

Starting point is 02:54:34 tuning in thank you to y combinator for hosting us and all the founders there was a 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 Live - 🟠 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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