Speaker 1The quest for equivalent models at a cheaper price, it's just going to keep going up. Is the open-weight, low-cost LLM business a good business? I think it's a great time for OpenRouter to sell. All the good investments sure seem to be in the infrastructure.
Speaker 2At some point, the people spending a trillion dollars a year are going to want some apps to pay for all this. The only thing that matters is the open AI and anthropic growth rate in 26 and 27. If you're growing 10x year on year and you have any kind of positive and improving gross margin, it just covers all the nut. Growth for the last two or three years has been a very attractive place to make money.
Speaker 3This is 20VC with me, Harry Stebbings. It is my favorite show of the week. Rory O'Driscoll, the OG, Jason Lamkin, the total AI nerd, analyzing the biggest news in tech this week. So kicking us off, yep, we're heading to the model layer. China ships two near-frontier open models in a week. With Kimi absolutely crushing it. And yeah, Washington moves to wall off. You guessed it, Chinese models. Next, Databricks raising $3 billion, a Series M. I love this, a Series M at a $188 billion valuation. And then on top of that, we have Ramp releasing an OpenRouter competitor, just as OpenRouter are supposedly about to get bought. This and so much more in the conversation this week. But before we dive into the show today, you have the idea, but with most AI tools, you hit a wall. The setup, the config, the gap between what you pictured and what you actually ship. Well, Base44 is where that wall disappears. You describe it, yeah, Base44 builds it. Apps, websites, AI agents, real working products, built in minutes using nothing but plain language. And it's all batteries included. The backend, the database, the authentication, the hosting, the heavy lifting is handled. So you just really stay in the flow. This doesn't just take the busy work off your plate, but it gives you an advantage. And pushes you past what you thought you could build alone. So in this market, fast is the baseline. To win, you just have to be first. Base44 is that edge. The move that skips the troubleshooting and gets you straight to the breakthrough. Build your next thing at Base44.com. That's Base44.com. While Base44 turns ideas into apps, Plot turns conversations into insights. Founders and operators spend way too much time every week jumping between meetings, articles, brainstorms, customer conversations, and then trying to piece everything back together afterwards. And that's why I've been using Plot. Plot instantly captures conversations, voice notes, meetings, random ideas with one press, and then turns them into clean summaries, action items, mind maps and searchable notes that you can actually come back to later. Honestly, it feels less like a recorder and more like an AI powered like brain memory system. And the crazy part is the hardware itself. The Plot Note Pro is literally as small and thin as a credit card. So it's just. Always with you when something important comes up. There are already more than two million founders, operators, investors, consultants and professionals using Plot to stay organized. So think more clearly and stop losing great ideas and important details. Go to Plot.ai/20VC and use the code 20VC for 10% off. That's Plot.ai/20VC and use the code 20VC for 10% off. While Plot captures the conversation, Finn helps continue it. As AI agents become more common in customer experience, teams often end up juggling multiple siloed tools for every job. Well, Finn was built to change that. It's a single unified agent that works across your entire customer experience from service to sales to success and beyond. Finn is the agent making perfect customer experiences possible for thousands of customers. It's powered by custom models, trained on years of real customer interactions. So it understands the nuance and complexity of customer service better than any other agent. That means faster resolutions, more consistent support and just better experiences for every customer. It's also designed to be fully self-manageable so you can easily improve and adapt it as your business evolves. No third parties required. Leading companies like Gamma, Asana, DoorDash and Crypto.com already use and love Finn to deliver better customer experiences. So for a limited time, you can get $500 a month in Finn credits for your first three months. That's at Finn.ai/20VC. You have now arrived at your destination. Guys, I'm looking forward to this. There has been a lot, as always, going down. I remember when news cycles were so much shorter. I don't know if you remember this, but, you know, 100 million round and it would be like the thing for a week. And now days go by and you're like, wow, we're forgetting the Stripe and the PayPal, which we'll get to, which is mega. But I'm going to start on the two near frontier open weight models that we saw in the last seven days from China, one of them being Kimi, which has got a lot of attention, a lot of press. And then the other being Quan from Alibaba. How significant were the two model announcements that we saw today? And what should we be taking from there? Seemingly catching up or close to with the frontier models we have in the West?
Speaker 1Well, look, first of all, I mean, an eval is just an eval. So let's not take a bunch of folks on X who had someone in their in their engineering department, look at some evals and write a tweet for them, OK, saying something is similar in performance. Let's prove it in the field. Having said that, so let's not overreact. Having said that, I mean, we can't even sign up new as consumers for Kimi because it's blocked. They have so much demand since this happened, right? Demand is literally I don't know whether it's geometric or exponential, but it's so high we can't even we can come back to this next week when it opens up and I can use it on the consumer side even better. But there's a lot going on and there's a lot on politics and it's an aha moment and a wake up moment. On the other hand, it's not new. If you look at open router data, half the traffic's through China created models. Even China models is a confusing term, right? They may well be hosted on. Yeah, they may be hosted in the US, right? And when they have open weights, they may be for all intents and purposes, truly open source models hosted in the US, but it's not new. It's just going to accelerate this. And that's why you see the stress that 50% instead of being niche or for tech forward folks or venture backed folks, you know, in a year it could be everybody. And that that that's material just being known and even materially cheaper, it's just going to get more and more attention. I totally agree with that, actually, Jason.
Speaker 2I was curious to see what you'd say is that, Carrie, you kind of led with the one of these new models mean. I think Jason's cut's exactly right. It's exactly what you'd expect. It turns out the five Wiley and the five main Chinese LLM companies and a bunch of followers. It turns out that, you know, aggressively funded companies with smart engineers are just going to keep cranking through and building new models. They're not state of the art compared to the frontier models, but they're six, nine months behind, depending on how you measure it. So, yeah, actually no new news about that. But Jason's right. Quite a lot of fun news about how parts of the U.S. responded to that. We had the small p political response such one dimension, you know, the the policy adviser for OpenAI, formerly from the Trump administration, making some comments on Twitter leading to a wonderful firestorm that we'll absolutely talk about. That's one thread. And then another thread is just talking about what these models start to reveal about the economics of a model. So, you know, I mean, we've got some of these deep-seq models. We've got some of these small model companies. I mean, Jason hinted at it. We lump all these models in together. But some of the deep-seq models you can run on your PC. Conversely, Kimi K3 is like a two point eight trillion parameter model. It's a huge honking thing. And, you know, you need myriads of GPU just to run it. So they're not, quote unquote, the same thing. That's much more comparable in size and therefore in terms of compute capacity to some of the U.S. smart frontier models. But the inference implications and as that goes into the opportunity for fireworks. So lots of kind of downstream implications. But zooming out, nothing amazingly surprising in the news that after three years of competent execution along a pretty defined trend, we now have three years and three months of competent execution around a pretty defined trend.
Speaker 3If we dig into the small P in the political, how should we analyze that? We can talk about the tweet that you mentioned, which was as I can't remember his exact title. And then Emil Michael obviously latched on to it. I'm trying to remember. Is it Dean Ball?
Speaker 2It's Dean Ball and he is current. I think it's not a policy or communication director for OpenAI. He just started there two weeks ago. Before that, he's at the Trump part of the administration kind of an AI policy. And before that, a bunch of Hoover Institute type stuff. He set off a firestorm with the tweet and then he did a little bit. Oh, I can't really post because I'm now on OpenAI. Everyone was mean to me because I posted a bunch of stuff. And I think it was, frankly, a little naive comment. There are two comments about the tweet. One is you're in a senior role at OpenAI. One, there was a hysterical tone to it, right? He used the word AI communism and it was very over exaggerated. And then secondly, you know, when you start even hinting about, I mean, we saw this with Sarah Fryden, when you start hinting about significant regulatory, hinting at regulatory changes that will massively benefit you, you got to expect that everyone's going to say, dude, of course you're going to say that. You know, that's your side. And if you start, if you make the tweet, it's going to be an expensive, closed source product that sells for 10, 20 bucks and the Chinese are shipping something for two bucks. And you say, well, totally independently, just speaking as a common citizen, I think they should ban this shit. You got to expect that a whole bunch of people are going to say, dude, you're not talking as a common citizen, you're talking as the provider of the company who will jack up our rates the minute the stuff gets banned. It was a little naive not to expect that level of blowback.
Speaker 1First of all, I think that guy at OpenAI had been there like two weeks, right? Two weeks. Whether he used that as a reason to go on this. And as they say in the meme, Jason, two weeks so far. Yeah. so far. I'm not a total expert. It's difficult for me to imagine the federal government's ever going to use a China-built model at this point in the US, right? It's difficult. And anything adjacent to that, it's difficult to imagine. There's always, in our whole history of tech, the ability of Chinese technology to penetrate many US buyers has been limited. It has certainly been limited in telecom and other spaces. So I think, stepping back for a minute, the real question is, how limited is it going to be? How limited are we going to, because it's going to be limited. The availability of China-built models to penetrate the US is going to be limited. The question is just how much. You know, Jesse Zhang had a Twitter article today or yesterday, I think today. Yeah, that was good. And it was pretty good. I think people might have missed it because it's real data, which is what I like. But he said, here's one of our most regulated companies. We have highly regulated folks. Just our token use here has gone up what looks to be about 2.5x since January. Yeah. And the reasons are really interesting. I mean, I've lived this myself. The reasons are having supervisor models track the agents so the agents don't mistake running multiple agents in parallel so they don't make mistakes. The more regulated you are, the less forgiving you are of an error in an agent. And so it's like four times the agentic use just to have multiple agents regulating agents. If it's already grown that much in the first half of the year, the quest for equivalent models at a cheaper price, it's just going to keep going up. But we've always had cheaper, pretty good solutions. From other vendors, it's not new.
Speaker 3Do you think Washington should move to restrict access then to these Chinese models? Or is Bill Gurley right in suggesting that we should let free markets do what free markets do best, and we should not put it out?
Speaker 2I hadn't realized Bill had said that. There's something very pleasing about that, which I'll mention in just a second. Because one of the fun things about this policy dispute, it brings out the hater in everybody, right? And Dean Ball said what he said. And then two people who can be controversial came down strongly on the other side, and I support them, both. The first was David Sachs, the former AI czar, who basically said, this is rubbish, stop. And then the second one was Emil, whom you mentioned before, Emil Michael, I'm never sure the pronunciation of his last name, who was a guy at the Defense Department who got totally sideways with Entropic. I mean, what I like about that guy is that man knows how to hate. And one of his biggest hates for the last decade and a half has, of course, been Bill Gurley from his time at Uber. So I really find it... So if Bill and Emil are on the same side saying, don't ban these models... Then you've got to know that there's got to be some truth in that. You've got to make it think, because that's an interesting lineup. And I actually just saw, literally, as I came on, and look, this is the Trump administration, so things change every day. But a political league today basically saying some version of, we're not going to ban these things on any significant basis, which, as Jason points out, is very different than saying the White House decision support system will be run on Kimmy. Kimmy hosted in California. I think we can take it for granted. It won't be. Conversely, if you're a decagon and you're a startup doing inference on customer support queries for a very boring consumer product, there is no reason why you should pay marquee prices when something 10x cheaper is available. And it would be horribly bad policy to ban that.
Speaker 1Another rich, grouchy billionaire. Grouchy Bill Gurley's probably got 30 IQ points on me, OK? And he's seen it all, right? And even his grouchiest point, I learned something from, right? I always learn from it. So having said that, I don't think you're going to convince me there aren't some data export risks. I don't think you're going to convince me there aren't some data export risks. with China-based models. You're just not going to convince me based on what I've done with all our agents and building. And if you're not going to convince me, I don't think you're going to convince 99% of the world that there isn't some security leakage issue. It's already scary how much of our data we put into these closed source models in the US. It is scary. Here's Elon saying scam Altman every day to create distrust, right? We cannot understand what these models do. They are connected to the internet. Even if we have Fable read it and have it read it itself, I don't think you're going to convince most of us there isn't data export risk. So I think that's going to lead to tighter constriction than this leave everything open so we can compete in my portfolio company's benefit argument.
Speaker 3I think every CIO is being told right now, oh, don't worry, if you hosted on-prem, you remove any security risks and the backdoor then is removed that could potentially be there. Why would you not be alleviated by that reassurance of on-prem would solve that solution? And why would you not be reassured? We're always more of a historian here than me.
Speaker 1You can mock our regulatory bodies. But they're here to answer those questions for us. Is it safe to drink that cup of coffee? The American Heart Association, I think, just said six cups are safe now, right? This week. Now I know. Now I'm cool, right? I was a little worried about my caffeine consumption. No, seriously. I mean, I'm not sure they're right. Who has said my data is not being exported through the most complicated borderline self-aware software of our lifetimes? Who can say that, especially, and I admit this can be triggering, there is a history of data export risk with Chinese products. Our companies that are arguably run by the PLA. I'm just saying my lifetime of experience says I'm not confident there is. And just the internet telling the CIO I don't think is good enough. And if I were a CIO, it wouldn't be good enough to me unless, as long as if I thought my job was on the line, I don't want to take this risk, CIO of some Fortune 500, Global 2000 company, unless everyone to, I don't know, man.
Speaker 2I don't think it's triggering to say that there are IP risks at the risk of being kind of level headed here. The data is very clear. Technically important U.S. companies, Boeing, for example, suffer continual cyber attacks, many of which are attributable to sovereign state actors, including China. It's a thing. So we're not being sensationalist or alarmist. You know, it would be naive not to put it on the table. Second comment is, I'm thinking about, can you, I mean, the problem proving a negative is, can you know? If you have, and remember, these are open, I occasionally say open source incorrectly. They are open weight, which means you can see the weights, but, and you can run it yourself, but you don't have, technically the full definition of open weight is that you can run it yourself. The definition of open source in the context of an LLM means seeing the underlying training data, which you don't, but you have the open weight. The question is, if the model is being run in a trusted U.S. inference company, Base 10, Fireworks, some of those guys, right? You can get into a long technical question is, look, what can it really do? Could it initiate tool use on the customer side, whereby the model sends a command back to the customer to exfiltrate their data? You can imagine being able to use these models fairly comfortably and being fairly comfortable with the software, but you can't do it. You can't do it on your own. You can't do it on your own. You can't do it on your own. You can satisfy a technologist that the risk is not there. Whether you can satisfy a politician, whether you can satisfy someone who's just afraid of what they don't know is, Jason, to your point, another question, right? I mean, and I think you're right. You have seen things like Huawei has effectively been prevented from selling to U.S., to any cellular networks in Europe and the U.S. because of this unprovable fear. It's not crazy that there will be some level of, I think, on the government side, some restrictions. I think a blanket ban would be massive overkill, to be very clear. But I think the interesting question it raises is this. Two questions. First of all, it's also worth pointing out that while we're talking about banning Chinese open weight models, the Chinese administration are talking about preventing those companies from selling those models to the U.S., just like we don't let them buy NVIDIA. They're not going to let us buy their open source models, which is kind of totally zany. We think they're trying to sell it to us, and we don't want to buy it, and they think they shouldn't be selling it to us because it's so powerful. So we can, that's kind of just weird in and of itself. But I think the really interesting question here, and it gets to thinking machines, is, is the open weight, low cost LLM business a good business? And if it's a good business, why can't some red-blooded American company step up and give open AI and Entropic a run for their money? And Jason, it's the point you made. Where's Grok? Where's Gemini? Thinking machines had an announcement last week. They announced a model. They didn't position it as, you know, state-of-the-art for the frontier, but it kind of, I think they made a comment on something that you can build upon. Inkling, I think it was called. So at one point, Meta looked like they were going to go down this route. Is there a business, can you make money as a, maybe not completely open weight, but a low cost US provider of these models and be competitive with those guys? Because, you know, the open weight models in China are getting 50, $70 billion valuations. Like, it's not Entropic, but I wouldn't turn down a $50 billion outcome if someone could make a convincing case to me that a US company could do this. So I think that's one of the interesting questions here. Now, maybe it's because the dirty little secret is a lot of their advantage is distillation, which you can't legally do if you're US-based. So I do wonder, Jason, to your exact point, if there is a market for 80% cheaper intelligence, and that's roughly what we're looking at in terms of when you take into account the cost of inference, the difference between the bundled product that is a frontier model. I think that's a good question. If you're looking at an IP plus inference and an open source model where you dissociate the IP from the inference cost, if you're looking at an 80% cheaper opportunity and there's the mass demand for that, when is someone going to try and fill that demand
Speaker 3in the US? I've asked so many people on why we don't have leading open models in the US. No one's actually given me an answer. We're still waiting for models from Reflection, which I think is kind of one of the hopes that we have. I completely, I was, I was offered Kimmy today, by the way, Rory, at 20 billion. Fell into my inbox. I have an SPV for you. Do Kimmy at 20 billion. We're oversubscribed, but we'll make room for 5 million for Harry.
Speaker 2Yeah. That's because we say such nice things about them. Thank you for your check. We're going to gloss by it and I don't have an answer, but it's a huge fricking question. There's this new category called LLM intelligence, two companies in existence as premium products. The combined market cap is $2 trillion. Their combined revenue at this point is probably $100 billion plus or minus. There are four or five other companies in the US that are capable and have proven their ability. to build something roughly comparable. None of them are taking advantage of this. And there's five Chinese companies that have proven their ability to build something roughly comparable, and they're cranking night and day to take advantage of it. Where are you, Google? Where are, you know, where are you, reflection, as you say, where are you, thinking machines? Where are you, lab? I mean, the fact that there's four or five potential competitors, it's just fascinating. Rory, are you asking them to dance?
Speaker 3I'm asking them to ship, you know, a story, and I'm kind of throwing it in here as a wedge. But when we talk about all the different models that we have on offer, one of the big gossip stories or breakouts this week in terms of news stories was the information suggesting that OpenRouter is in talks to be bought, several different acquirers. And then on top of that, we have Ramp introducing their router, routing model provider product.
Speaker 1I think it's a great time for OpenRouter to sell. I think it's, I think, I think them leaking the story, it was very savvy. Why is it a great time for them to sell, Jason? Because the market's in flux. Everything. Everyone's figured out they need this. OpenRouter, like a lot of folks, was early and benefited from it and deserves it, right? This is a repeat founding team that saw that there would be value to having a fairly heterogeneous mix of models that when we started this pod probably made no sense at some level. It probably seemed too nerdy and too niche and too cool cat developer. Like, yeah, sure, there's a little, it's cool. But, you know, guys like Rory and me, we're going to stick to the big guns, right? Everything broke well for them, but it's still a niche product. And so, you know, we're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns.
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Speaker 1We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns.
Speaker 2We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns.
Speaker 1We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns.
Speaker 2We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns.
Speaker 1We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns.
Speaker 2We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns.
Speaker 3We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns.
Speaker 1We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. We're going to stick to the big guns. Yeah. It's just the way it goes. And the perfect outcome is to sell the moment it becomes commoditized, but before everyone fully realizes it. That's when they'll give you the money, but that's before the value decreets rather than it accretes. And my gut is it might be now, that crossover moment. I think Rory kind of made a version of that point. It might be now. If space is commodified, it doesn't kill everybody, but it might maim you. But it also makes it attractive. It also makes you attractive to acquirers for a window, and then that window closes. The commodification window closes, and probably why Cursor wasn't dumb to sell at $60 billion.
Speaker 2I think we can agree that's true. I don't love the commoditization description. I think it's an overloaded term.
Speaker 1Well, an included feature, and more and more folks will include some version of your functionality in their product. Agreed.
Speaker 2That's exactly it. Which segues to the next topic. Which is fireworks?
Speaker 3Yeah, an inference in general. Yeah, I mean, take it away, Rory. I'm going to butcher whatever context that you want to take it on. No, you do first, because I'm just... Are you sure? I'll lay the framework, and then you can just destroy it, steamroll away. I won't. Fireworks, a leading inference provider, announced their latest round, which was a $1.5 billion round, done by Index, Gavin Baker, Vidya, Lightspeed, 20VC, amazing firms. They're incredible. They're really fucking good. Lynn is amazing. Doing over a billion in ARR. Got there in 3.5. Yeah. In 3.5 years. And they announced around $40 trillion tokens a day, up from $15. First of all, I agree.
Speaker 2Yeah. Inferences are huge. It goes back, ironically, to the prior common open weight models. This kind of standalone inference is a big business. And, you know, obviously, you know, inference is both something that's done within the frontier model companies, where they do their own inference, and people like Microsoft and Google provide the CapEx, provide the compute for that. But people like Fireworks and Base10 and FAL, they all... They all make their money offering a variety of these open weight models to third party developers and enterprises that want to use open source models to do AI. As I said, the two trends go together. They're exploding because the open source trend is exploding. So if you're Base10, if you're FAL, more media, if you're Fireworks, if you're together, this is your market and your moment. Because this is how you access those. Because I can tell you one thing. Going back to the discussion about open weight models from China. And it's one thing to decide to use an open weight model on Fireworks in the U.S. What you're not going to do is be using the API back to China, even if they'd let you. Right? So this is a one-to-one linkage between the open source, the open weight trend. These are the companies that are benefiting massively from that trend. And it's not the only kind of route for inference. There are, you know, inference for U.S.-based models, et cetera, et cetera. But the vast bulk of it is, oh, my God, I'm hosting Quinn, Kimmy. I want to use it as cursor. I want to get someone to provide me some inference. These guys exist. And, you know, they have lots of customer skew at the high end. I believe, you know, companies like Cursor are probably big customers of all these guys. At least they were until they were acquired by SpaceX. And probably still are. Right? So, yeah, I mean, it's a great. Candidly, I think, again, it actually goes back to the point I made earlier. There's some businesses where, and I think you can look at it and say, oh, my gosh, you have margin compression in your future because you're buying your compute from the neoclouds and, you know, you're offering this product. And are you going to be scrunched? And margins. You know, we're probably slow for a while. But now the beauty of it is demand is massive. So whatever compute you have today, whatever compute you've already signed up for, and these guys sign up for compute from the neoclouds in general are starting to build their own. Whatever compute you own now, you can charge way more, which means what looked like a lowish gross margin business has now probably become a very attractive business. So not only are they probably growing 5x to a billion, but they're probably growing 5x to a billion with expanding gross margin.
Speaker 3And just to add some details there, Lynn said specifically that they were at mid-30s in margins, and that would move up as they eat more of the stack, and they do plan to move into the data center layer themselves. Yeah, and that's exactly where I thought they'd be, and good on them, right?
Speaker 230%. In other words, what they're saying, and this is going to be an interesting, and I agree with that sentence. It also means that the challenges I hinted at are there in the future, right? Because what they're saying is, if I'm buying data center compute and then effectively selling data center compute with hosted LLM, at some point, I'm going to want to own my own data center assets to have more control of my destiny, which means vertically integrating downwards, which also means a ton more CapEx. So these are going to become way more CapEx-intensive businesses. There is a risk of commodification here, even with massive complexity and massive CapEx.
Speaker 1There is one thread of the Twitterati who has said for a while, like, all this stuff's interesting, but ultimately, the application layer is going to be the most interesting. It's going to benefit from all this. Everything's commodified, right? All the good investments sure seem to be in the infrastructure. Absolutely. Even the ones that look good in software, the numbers pale in comparison anyway, right? The absolute numbers pale. So I'm waiting for the era of the application layer in AI and making bets and seeing some good stuff. But I don't believe it's here yet. I actually don't believe the application layer is here yet.
Speaker 3To put it again, Lynn said in the show, she expects to double by the end of the year.
Speaker 1Yeah, and that's just a slice of the market. Listen, people have gone all back. You know, when we started the show, it felt like vibe coding applications run amok. Everyone thought you'd replace your sales force. You even had a guest the other week who was, I forget his name, how great it was, he replaced sales force. Who cares, right? Didn't kill software. But where is the software renaissance? I mean, the revenue's there. We've talked about leaders, right? But it's so trivial compared to the infrastructure. It's so trivial. It's almost a rounding error, the application layer.
Speaker 2Just to mention that, because I agree, Jason. I mean, look, I'm an app. I'm an app investor. It hasn't. What's going on here? You've got companies like Fireworks doing a billion dollars. There's very few apps companies doing that. And, you know, zooming out a million miles, my mental model is I divide the AI world up into three buckets. It's the making AI, the infrastructure layer, right? And you're right. The spend there is $800, $900 billion a year. Then there's the two foundation model companies themselves, and they're doing plus or minus $100 billion a year. And then taking those guys out, rounding up every other apps company, you struggle to make full money. You know, you start with Cursor at four, because I think coding is an app. By the time you're chucking in Harvey, you're adding $200, $300 million, right? It's amazing. I mean, just the difference in spend. And, you know, at some point, the people spending a trillion dollars a year are going to want some apps to pay for all this. But right now, the volume, it's been front end loaded on the infrastructure side. And at some point, the revenue has to match it. But right now, infrastructure has been the place to be. There's probably more money being spent on training data for the. Foundation models, you know, the Merkur surges and that, than pretty much any app company outside of Cursor. In fact, probably the sum of all the apps companies outside of Cursor are probably less than the amount that Entropic and Opening Air are spending on training data.
Speaker 3That I can guarantee you, when you look at McCall hitting $2 billion in ARL.
Speaker 2Yeah, $2 billion for Merkur, a surge, another billion. You get to $4 or $5 billion, and, you know. Surges three. Yeah. Handshakes one. I mean. I mean, yeah. Maybe if you start throwing in on the other side, the consumer products like Higgsfield, you get to roughly the same. But it's astonishing. The scale of the investment versus the scale of the apps at this point means that all the actions on the info side for now.
Speaker 3If we bring this all together, you know, we mentioned fireworks at the start. Lynn said in the show, the future would be every company having specialized models with their own data. We mentioned Harvey there, who've been building their own models. Jason, I'm just intrigued. In the last week, you spent time labeling data, building your own model through that data. Any lessons, reflections from the last week? The last few days, labeling data and going through that process that you've been through?
Speaker 1I violently agree. I've been building this agentic recruiting app just to recruit from the Sastra community. It's been fun. I've learned a lot building it, right? Hopefully it can ship in the next week or two. But to really get it great, it needed a, it needed labeling to make it. Now I'm going to put model in quotes, right? It uses Sonnet and Opus, but so there's different definitions of model and it was good. And, but man, once I started labeling all of this, it, it. Got exponentially better, built our own little labeling tool. And so you need your own micro model, whether it is some sort of reasoning layer that you build on top of Claude or, or ChatGPT or Kimmy or Shmimmy, like it's still your own model, even if it's not technically a model, right? Because you, you have your own reasoning layer with your own rules, your own weights, your own, but you want more. You, if you have the resources, you want to go further than that, right? You want to, your big M model, as soon as you're at a certain amount of scale and it's not cheap all in, right? You are going to want to have your own model, right? Like a Harvier cursor. So some version of this, I think folks that are going to want to use at any application, a lot of folks that are going to want to use just the generic models is just going to decline to prototypes, prototypes and proofing.
Speaker 2Yeah. Or absolute state-of-the-art small parts of the overall task, but agreed. Parts. Yeah. Little parts, right? Like, I mean, again, you're going to want to use the expensive tool for the expensive parts, right? And you're going to want to use the cheap tool for most of the parts. It's on the customized tool to your usage.
Speaker 1But man, the outputs are just literally an order of magnitude better once you do it. So everyone wants your own model, whether that always benefits fireworks or not. It doesn't matter as long as they pick up some of the bigger end, right? That scales. It's a generic models are great, but it is amazing how much better you can do than them for any specific workflow. You can do epically better.
Speaker 3Would that change your confidence on the data labeling market? A lot of shade is thrown at it. As an investor in my core, I definitely see it. Does that change how you think about
Speaker 1it personally i'm totally i totally get it like having a subject matter go in and answer 20 questions about a disease about history i mean it's a lot of professors and teachers that they have there right that that model right the amount of power you can get in a domain by having a subject answer answer just 20 or 30 questions right five minutes 10 minutes the amount of power you can add versus the generic llms which are a sea of mediocrity combined into one giant llm okay every mediocre history professor every every mediocre doctor that doesn't even know what what caused your runny nose is in the llm but if you get the best people training it on the best answers it's a step function i'm less smart on the seeming low end of the model right this commodity thing that people made fun of macor but i ain't making fun of it anymore i tell you that much and these models are a sea of mediocre all combined in a giant soup that gets better these domain experts are so powerful in tuning your model to get the the better output so
Speaker 2powerful i think the answer though is really a derivative of the big question which is because your statement your company's going to want their own model is probably true right and the real question is not that the real question is will that be additive to the rough trajectory of the foundation models as it's established today in other words coming at or close to 100 billion combined revenue growing nicely or does it start to take away significantly if the foundation models continue to grow and we just saw the article information that you know for for all the training data companies the vast majority of their revenue comes from the foundation models to which your correct response is no shit of course it does right if that continues to grow and you have an additive market in enterprise of all these companies you know jp morgan building the jp morgan model on top then you know it's net expansive and net expansive is by definition good and it reduces customer concentration and i think that's what people like merco are forecasting if on the other hand you know which is hard to come by and i think that's what people like merco are contemplating today if these enterprise models if these open weight models really impacted the growth rate of anthropic and open ai then obviously when your 80 customer slows down it would have a significant impact on your growth rate but you know if it's any consolation harry if that happens worrying about your marker evaluation will be the least thing people are worried about because you'll see an implosion of much bigger market cap entities right and you know that's that frankly is the billion dollar question can these two foundation models maintain their growth trajectory which is starting to become profitable at least in the case of open of anthropic in the face of all this open weight competition in the face of this pushback on costs and basically kind of push for roi if they can maintain this trajectory for even another one or two years then everything's fine and everyone's fine and right now the data says they are if you start to see slow down on those two arr growth rates then you know all bets are off because the pressure because the amount of commitments they've made assuming that 10x growth rate continues will mean that even if it slips to a two or three x growth rate there's going to be a
Speaker 3mad scramble bets on yes or no answer will open impact that trajectory for anthropic and open ai
Speaker 2in the next one to two years yes harry it will impact it might impact at one percent or fifty percent what you really say what your question you're really trying to ask is does it reduce that growth rate to some 100 percent or is it going to reduce that growth rate to some 100 percent within one or two years and the answer that question is i genuinely don't know and if i did i'd be trading that stock if you know the answer to that question that one question you know the answer to the entire direction of the u.s stock market for the next two years all the hyperscaler rpo all of it is a function of the commitments they've gotten from the foundation model companies and yeah you can say if the open models open weight models explode there will be demand for inference and yeah you will have this kind of transition from oh i sold it to open ai but i should have sold it to cursor or base 10 or someone else and the capex will get repurposed but it will be a big ass dislocation and i just genuinely don't know it's the million dollar
Speaker 1question the really tough part i mean it's captain obvious right is can they afford for it not to and what i mean is look at what's happened with fable this week okay fable went from you can't use it it's not secure then the government lets you use it then hey we're going to turn it off except for variable usage on june july 15th now it can be 50 percent of your whole usage for the month why did they change when they don't even have enough capacity to serve it competition competition right so listen if they price fable at sonnet rates i think they'll own the market i'm oversimplifying because you don't need fable for anything but literally so the question is can they afford to compete and this is the stressor right of course they they could have 17 variants of the model at 17 price points like that's not the issue the issue is the because they have to pay to train these damn models and other reasons they have just this space and they're subsidizing it with venture capital right we whether we call this venture capital or not private private capital and so but listen you just cut the price of fable five by half tomorrow you don't need these kimmy shmimmies but can they afford to and over what schedule and the fact that you can use fable for half your credits is pretty telling right they're they're pushing it as far as they can but that's the limit today they can afford to compete 50 and we don't have time
Speaker 2for it because i do think we should spend at least half the show and stuff other than ai model companies and i think jason's insight is correct about price and if this was a software product with no gross cost of goods sold that's what they do i mean microsoft i've seen a bunch of articles on this it's again it's as you'd say jason captain obvious but it's worth emphasizing in the great software wars of the last couple of decades someone like microsoft was able to take it you know just use price ruthlessly because there was zero cost of goods sold and they just bundled the browser in with the operating system bundled all office in together didn't cost them anything and it just wiped everyone else out but as you're pointing out here there are real even at the margin even after you fully paid for your training costs there are real physical costs to serve these models and you got to cover your nut you got to cover the marginal cost of the model of the serve of the inference which gets you data two three bucks kind of blended average token then you got to recover the cost of the training and you got to recover pretty damn quick because it only lasts you know 12 24 months before it's obsolete and then on top of that you want to make extraordinary money out of it because you're being valued at 20 times revenues and if you're valued at 20 times revenues you better be like microsoft with 40 operating margins so when you look at all that you're right it's kind of back to the thing i said you can squint at that and say oh there's lots of things that could go wrong here when you look at that those fundamentals as yet the thing that's saving you right now if you're growing 10x year on year and you have any kind of positive and improving gross margin it just covers all the nut the minute that growth rate stops jason to you if you're growing your price per then your gross margins start to deteriorate instead of continuing to improve that in itself would be a different ballgame so you are right price could solve it but it would be a painful way to solve it yeah you have to start building your own chips and
Speaker 1building your own everything all the stuff you're trying to do to solve this problem but i think it's just a i think it's just a pricing problem right i mean there's a bunch of issues underneath and i would argue they've already bundled it like the consumer apps of claude especially but also chat gdb they bundled everything i can get ten thousand dollars worth of tokens for 200 bucks and i can just bundle it all together and i can just bundle it all together and i can just bundle it all together and i can just do just about anything in it right it's just outside of the consumer it's not it's not massively bundled and subsidized right you remember the old days in software jason when
Speaker 2you'd have to say i promise i'm only using this for personal use you remember that and licensing well if you're saying if you're telling those nice claude people that you're only using your personal subscription for personal use they're going to find you dude well yeah it's just it's just fable is very good that's why they're going to find a way to charge for it rory you were like
Speaker 3are we going to get away from this like ai stuff yeah yeah yeah i mean there's so much i mean
Speaker 1were you hoping to talk about like a vertical dentist company like ben affleck making 500 million for his oh that is an ai sorry sorry sorry that's an ai story oh it isn't it 587
Speaker 3million and fun fact his top three movies didn't add 60 million and so it's 10 times more than his three highest grossing movies combined wait say that it's higher than the batman for his pay like
Speaker 1how much he got he got like eight million dollars the amount he made from it you know context is so funny i don't want to distract we're like how much had been sold for 500 and some odd million to netflix right 87 our jaws drop and we're arguing whether we should sell a portfolio company for six billion well is it really worth our time gentlemen i it's really only a forex to the last round i you know and on the last fund it's not even a returner i don't even know if i may not even be retained as a gp at the firm if this is as good as i can do oh my god he sold sold the company for 500 million rory do you know what i find that triggering
Speaker 2get on him i mean you know no surprise it turns out that you can make more money with cap i mean it turns out that acting is you can make more money with capitalism techno capitalism than acting i mean you know it turns out bill gates is richer than you know the most famous actor in
Speaker 3the world right it's yeah no surprise all right rory i'm gonna listen to you then move away from this ai pure play discussion and we're gonna move to some irish twins the stripe and advent deal to take paypal private does that sound okay passes it sounds good i mean you gotta talk about it we've got to talk about it so this is a big deal um was it inevitable stripe would acquire paypal there were rumors of it a couple of months ago this is obviously taking those rumors one step further with with the offer rory how did you think about it i think that price clears all i mean i
Speaker 2think it's it's super interesting in a lot of different ways one is they both process kind of 1.9 1.8 trillion dollars a year right and as yet stripe and we'll talk about revenues and profits in a second stripe is valued at like 150 billion and it's not like it's not like it's not like it's not And I think, what was the offer for paying I looked at it this morning, but it's at $50-something billion, right? So, yeah, I mean, it's like Stripe taking advantage of PayPal trading at sub-10 times profits and deciding to go for it here. In one sense, it's a ballsy move because you're taking on a lot of operational complexity. On the other hand, it's a chance to really transform and double your footprint because I think the payment process is roughly the same. Revenue is tricky because Stripe supports revenue net, which is around $6 billion plus or minus. PayPal reports gross, and I think it was, and I checked it, but with my cold, I'm a bit feeble-minded today. It was about around $30 billion, so it was trading about 1.7 times revenues. So if you look at that 5 versus 30, I'm like, ooh, it's 5x. PayPal's 5x bigger, but it turns out on a like-width, like-basis, PayPal is still bigger, but it's about 1.5 times the size. It's still a company. Buying something 1.5 times its size for what looks like a third less because it's kind of, they're doing a joint deal with Advent, a PE provider, so for, you know, a lot less of its market cap. If they pull it off, they will look back and go, wow, that was an amazing deal. It also gives them, and, you know, and their economics will be amazing. It's a little like the Dell transaction. You know, obviously, the scary thing is it takes your perfectly wonderful company that's nice and running smoothly. And, you know, it's a desirable place to work. And all the positives that we all know about Stripe, you know, smartest guys ever, killing it, nice place to work, good reputation. And they're going to have to do a lot of hard-nosed stuff to turn PayPal around. And there'll be a lot more pushing and shoving in the future because, you know, you're probably going to be looking at that place and saying, we're going to get rid of a lot of people. We're going to rationalize a lot of stuff. So it's a different muscle, but I give them credit for it. It's a big, ballsy play to double your market cap.
Speaker 1Yeah, the part that I struggle with a little bit. Obviously, there's at least a decent synergy here, right? And in a PowerPoint slide, there's a ton of synergy. Plus, you get Venmo, you get a lot of stuff. Yes, you like consumer assets. The thing that is always a head-scratcher to me is blending something that's growing 7%. Because no matter what you say or do, unless you can radically shove those products through your channel, your blended growth rate goes down. What's Stripe growing today? I don't know, 30%, 40%? It's between 20% and 30%. So it's not that much bigger, Jason. But 7%? But 7%? So, okay, hold on. Rory, you're better at the math than me. But if I take... If I take 30 and 7, that's 37 and divide by 2, I'm only growing like 18% now. I've fallen below the Mendoza line of 20% growth at scale.
Speaker 2There's no such thing as a Mendoza line for growth at 5 billion and above because you can get out. I mean, I think the real point is...
Speaker 1But I found it stressful in M&A observation. Not quite at this scale, mind you. But it is stressful when it meaningfully decelerates you, right? It will meaningfully decelerate them in the short term, even if... I'm not sure how the accounting works, right? Maybe they only have to recognize half of it because of this advent thing. But they're going to have to recognize some of this. Right. Right. As a joint venture. So it's going to decelerate their growth. It's not stress-free. Plus, you have the operational need. Plus, I mean, even all the layoffs they're going to do, that alone may not re-accelerate growth. We've certainly seen this at a handful of portfolio companies, right? That's just the stressor for me. I've learned over the years when you have one messy code base and another code base, and you're like, how the hell are you going to combine these companies in different motions? You figure... As crazy as it sounds, you actually figure that part out. And the answer is, you don't fix it. You fix it over five years. Or you have an LLM lift. But the real answer is, you don't fix a lot of these things that seem like you can't rationalize in between the organizations. Everyone's got 11 products spaghetti-ed together. Even tech leaders have it, right? It's just the nature of M&A.
Speaker 2My guess is, this is one where you have, frankly, one well-won company for the last decade and a half in Stripe. And you have another company that, you know, ever since the PayPal mafia walked out, has been just a revolving door of executives. And it's a real mess. And they've dissipated their opportunity. So, yes. I mean, the interesting thing is, nobody has the kind of deal you do, after you go public. Because you have the market cap, and you just price the deal. And I was thinking, my first glance was, ooh, it's probably a lot harder to do this as a private company. Because you can't issue $50 billion of stock. So, you have to look at debt. You have to do advent. On the other hand, and again, I wanted to read the detail. I didn't get to it fully before this meeting. Maybe they're using advent to almost keep it slightly off balance sheet for a period of time while they rationalize it, right? So, I don't know. It would be easier to consummate this deal and just be done as a public company. But obviously, Stripe has chosen not to go public. So, at least yet. But it may well be that, even though that makes it less easy to do, it may also have pushed them to this kind of contained strategy with advent. Will this happen? I will still argue that it's actually getting done.
Speaker 1I think it happens. Let me just step back. Rory's got even more experience than the two of us. But it's just a dance. The board rejected it. And the fact that the board rejected it means to me that they're going to accept it. You reject it because no investment bank will tell you you're allowed to make your highest offer up front. It's like you probably breach your fiduciary duty if you make it. You have to offer whatever. You have to have another 5% or 10% to put into the deal. So, it's a dance. They're going to accept it. It's a bunch of mercenaries and a brand new CEO who's probably going to make nine figures for 10 or 12 months of work. By rejecting it, it means they're going to accept it.
Speaker 2I think Jason could well be right. I think I handed this over. When you're a private company, remember we talked about the sale king, Harry. When you're a private company. You can decide not to sell for any reason. When you're a public company, what the bankers are telling them right now is, first thing you do is instantly reject because you've got to look strong. And then you've just hired a banker and they're going to say to you, and the lawyers in particular are going to come in the room and they're going to say to you, Delaware law, you can only turn this down if you have a good business judgment belief that on a standalone basis you can do better than this offer in a reasonable period of time. So, even as we speak, the PayPal team are. They're building a three year model, a five year model, trying to prove that they're going to be amazing, therefore this bid is too low and they are comfortable in the risk of turning it down. But what's going to happen is this. They'll be able to make a model because they have smart people and the banks are smart people and the NPV will be wonderful because the banks will make it that way. But the pushback will be, well, guys, if you were so fucking smart, why didn't you fix it in the last five years? And then you're sitting there as a board member going, am I really sure this guy can take it? Can I turn it around? You know, do I believe if I got an extra 10 or 15 percent, would I say risk adjusted? I should take it. And as Jason pointed out, I don't know the CEO from Adam, but he's sitting there going bird in the hand versus slogging at PayPal being the third CEO in a row trying to turn this thing around. At some point, if Stripe wants to own this thing, you are kicking a little more in and you probably will own this thing. It's hard to have the stomach unless you could see evidence within the PayPal numbers that it is turning around. That's probably the only thing that could give the board the courage to say, I'm just not doing this. In other words, there's probably five key internal metrics that matter: take rate, new merchants per quarter, usage of wallets, whatever it is. If those numbers are already starting to turn because the new CEO is doing an amazing job, then maybe the board can say, I will extend that trend. I will say, hey, look, the last two quarters have been 10 percent better each quarter. If you extend that trend for five more quarters, it's an amazing company, we'll work twice as much. Let's turn it down. If those trends are still flat, and it's the new CEO's plan might start working next quarter, then it's really hard to say as an independent board member, you're getting 300 grand a year in RSUs, do you really want to be a hero here or do you want to, as Jason said, do you want to say no and negotiate for 15 percent, discharge your fiduciary obligation and take the money?
Speaker 1Yeah. I mean, certainly the argument would be the stock price is depressed, they're missing it, right? It's down from its lows, and that probably could tie into the business judgment rule, if you really believe it. But my guess is this is engineered. They made a 28 percent premium offer. The average take private like this is in the mid 30s. Now average does not control any deal. But that is the perfect amount of back and forth, 28 to 35. It's already pre-scripted. Yes.
Speaker 2It's already pre-scripted. And the bankers will charge you a couple hundred million bucks for it.
Speaker 1Yeah. How are we going to get from 28 to... Well, we could just... Let's just offer them 35. We'll never get there. We have to offer them a 28 percent premium to a public company stock so that we can land at 35. They have to go shop it. And if there are any other offers, they would have gotten them in the last year. There are no other offers. Sometimes it materializes. Rory has been through this. But usually if there are another offer, the offer already soft happened, like there've already been discussions at the whatever media summit or whatever. And so there probably ain't. So it's probably just a dance from 28 to 35. And then it gets parked with Advent while they figure out antitrust and capital issues. So Stripe finally, the powder one finally becomes the Jedi. Stripe takes over PayPal. It's just a matter of time. And it lands. That's where it should have been. And all the early PayPal guys that did the pre-seed along with Sam Altman's 2 percent, they're going to do pretty well in the end.
Speaker 2They're coming back through the back door.
Speaker 1Yeah. They're getting the old gang back together again.
Speaker 2For listeners who may not know it, one of the very early Stripe rounds, I know Peter Thiel was an investor, a number of the folks who were involved or connected with the PayPal mafia back in 2000, 2001, before they sold to eBay, subsequently went on to be great investors. Peter Thiel, most notably. He's stuck early money into Stripe and now, 15 years later, are having the joy of buying PayPal back. It's probably a sweet moment if you're one of those investors. You know, the first time you move into the headquarters, you'll probably say, can I come along? You probably ring the Collison's and say, hey, guys, if you're doing the victory lap on the PayPal headquarters, can you include me in on that trip?
Speaker 3Now, Rory, I want to hand the ball over to you because you said no more AI. So I gave you no AI. And then you were like, you missed topics. What did I miss that you wanted to cover, Rory?
Speaker 2I've been thinking about this a lot, actually. In one sense, I want to say there's more to life than talking about open AI and entropic because there are only two. of 2000 interesting companies. On the other hand, as you would be the first to point out, cap weighted, in other words, weighted by dollar, there are 2 trillion of 5 or 6 trillion of privately held market value. So on a cap weighted basis, we should be talking 30 to 40% of our time on OpenA and on Tropic, boring as it is, if you are kind of trying to be representative of private tech. So I hear you, Harry, it's hard not to, but I just don't want to be totally boring. I mean, the odd thing about, you had a list of other companies that to talk about, and in a weird kind of way, every single one of them is a company that's being pulled by this trend. I mean, you had Valor Atomics down there to talk about, you know, new technologies and nuclear. Then you had kind of TSMC and ASML. And the truth is all the dynamics for those two companies are about the insane demand for semiconductors, which is all about AI. So, you know, when you actually get to trying to talk about something that's not AI, I'm not going to talk about it. I'm going to talk about it. Data breaks, rockets to 188. Why? To buy GPUs, which gets back to my comment. The growth rate of those two foundation model companies, as Jason has pointed out many times, is a thing upon which
Speaker 3you're a 401k at an all time high dependent. One thing that I do find interesting is like another one, but it's like emergent AI coding startup, 120 million in ARR, raised 130 million in Series C at a 1.5 billion post money in July 15th. The thing that I find really interesting here is I'm seeing Series A is priced at 3 to 500 on 2 to 5 million in revenue. But I'm finding the B at 100 million in revenue priced at 1 to 1.5. It's a 3x price increase for a 50x revenue increase. It's just a very interesting market analysis today of where is a good insertion point for investors. It's true. And it's like risk adjusted always now. Like, we did factory at the one and a half round. And I think, yes, that was a worse deal than the 300 round. But the 300 round, they had next to no customers, very little product market fit. And well done to those investors. They saw what a lot of other people didn't. But risk adjusted, you're only paying 4x for incredible PMF and 70 to 100 times revenue scaling.
Speaker 2I think on those numbers, you're correct. The short answer is, is that, would you prefer to pay 300 for no revenues or 1.2 billion for a lot of revenues? Absolutely.
Speaker 1Well, look, I think for what it's worth, there obviously is, there is real multiple compression, even in the hottest Gentic folks at scale, right? There's real revenue, multiple compression. There's plenty of folks compressing to 10x revenues, right? Which is even far less than forward revenues, right? I mean, maybe unhelpful comment. I think the real pressure is, it means anything below that growth stage, you better be a damn good picker. Because it used to be, it used to be when Rory and I met, series B, even into series A, you actually didn't have to be a good picker. You just had to be good at math and good at assessing the team. The picking wasn't, wasn't so hard as it looked. It was all the rest. Now, a series, that gap, you better be like a, you have seed investor skills at the series B, or the math's going to be tough with that. It just, there's a lot of pressure on the picket. That's just what I think it is below the growth stage. So be it. That's the game. That's how I think about it. And it's harder. You don't really want to be a picker. You want to be a pricer.
Speaker 3Again, going back to my point, risk adjusted here. Would you rather be doing a series A, 2 million in revenue at 300 million price, which is the going rate for a hot AI company at series A, especially in the Valley? Or would you rather stick money into fireworks, which says they're going to hit 2 billion by the end of this year at 17 and a half billion? You're paying less than 10
Speaker 1X revenue. Well, if you want to, it depends. I mean, Rory's better at the math. It depends on fund size and other numbers, but you want to own the most you can of winners. You could argue at putting the absolute amount of money you can in the last entropic round. But for most of us without unlimited capital, you know, if you, if you can pick better earlier, you end up, you'll end up owning more. It does pay off that extra three to four X isn't terrible. That extra three to four X on the way to the, to the billion dollar round. It's not, it's not a terrible money people can pick. And I think we are here to make money. Pick is a more complicated than it sounds, right? Pick sounds like everyone's waiting outside your office for four hours in the lobby, like at a doctor's to pick like it's a 2006, right? But it is true. And the change that the biggest brands will pay the highest price in many cases, uh, makes that in between round tough, right? At least the growth round is sort of priced by the company one way or the other. And you either, you either in the
Speaker 3round or you're not right. And, and, and you know what, on top of that, I'm Rory, you can forgive me for going off on this ramp. You know, Brandon McCall has mouthed off, uh, and I say that nicely, but mouthed off on Twitter about Sequoia's trance rounds. I think it's brilliant marketing for Sequoia. Honestly, I would have retweeted it. I would have retweeted it. I would have retweeted it. But the amount of trance rounds I see, I saw a round the other day with four tranches.
Speaker 2Yes. But those two things go together. That trance comment goes together with your prior comment, right? Which is, I'm going to paraphrase it. It's like doing classic early stage seed AB investing is really hard because prices are high and you've got some really talented firms. So to win, you got to have differential access, differential picking, and you got to be competing every deal. Conversely, Harry is saying, I'd look at these companies at one and a half billion, they're doing a couple of hundred million in revenue. Yeah. That on an absolute basis, they're expensive, but on a relative multiple basis, they feel a little cheap. That's what you just said. Correct. And I think that's correct. And I think there's no, what you're basically saying is growth for the last two or three years has been a very attractive place to make money. Those kinds of deals at one, two, and 3 billion have been subsequently marked up a lot. And I think you're entirely correct. If you look at all the unicorns that were minted in Q1 or Q2 of 2025, by the end of Q2, 26, at least 40% of them will have had a subsequent markup. In other words, good things get more good things. We've been in the momentum side of the marketplace. So late stage, that kind of growth investing to your point now, and the reason you've been doing it, it's been a very good place to play. And I think you've found that that's what you've seen in your portfolio. You've put 10 million in, pick a hot company at a billion. And six months later, you're getting a markup to 3 billion. Like I'm a genius. I haven't lifted a finger and I just made it 3X. It's been a great place. So now what you're seeing with these tranche deals is nature abhors a vacuum and Sequoia abhors leaving a dollar on the table. So what's happening is people are realizing everyone wants these growth rounds. And this is how these trends end. They're going, oh, everyone wants these growth rounds. So now what we can do is do this tranche structure and effectively price the excess return away from Harry and back to us. So yes, because it's been such a good place to play that capital's rushing in. At some point, it won't be a good place to play. But you are correct. I mean, we talked about this last week. There's always the tension. And do you stick to what you're doing because you should do it? Or do you move around within the overall environment? And I know what you're going to say, you think you should move around. And I agree. If you can pull it off, from a pure, logically, over the long term, by long term, I mean longer than you've been alive, Harry, 30 years. The truth is, early should have a higher overall return multiple than mid, than late, because otherwise, national market theory isn't correct. And over the long term, it is, Harry. But where you're absolutely right is there are these disconnects in the short term, I mean, three or four years, where you kind of go, oh, wow, a combination of increasing equity valuations and a new trend means from 2022 on, late stage will be amazingly good. I completely agree. Obviously, if you are
Speaker 3in the best early stage firm, it will obviously have better numbers. I completely agree. But I'm also fully cognizant that venture is a crap asset class for the majority. And I think, essentially, Thrive and many other very large funds will have much better numbers than
Speaker 2the majority of early funds. I totally agree. And I don't think we're saying anything different, to be clear. Because I think that, look, the earlier you go, the more dispersion you're signing up for. When you get it right, you get it very right. When you get it wrong, you get it very wrong. The later you go, I mean, let's do this. The later you go, logically, the less dispersion you should have, the more bounded the thing. But on top of that, you have also this phenomenon, which is you go late. At certain periods in the marketplace, you get this kind of equity rising tide perspective. Which carries everything. And since the crash, not crash, small C, since 2022, you've just had tech lift and equity lift for three years. So yes, it's been a great place to play. You're
Speaker 1exactly right. I wonder if I was a founder, if I would really do contemporaneously tranched rounds. I don't know that I would. Is it not a good deal for them? I think I would feel like, I mean, I might do it in the moment. I think we're all caught up in the moment. I don't know that I'd be comfortable charging one investor $1 billion and another $5 billion within the span of the same week. I don't think I would feel good about it. I think that it's suboptimal for my 409A. If it's a tiny amount of capital, I don't know that it materially changes the dilution. If it's a massive amount of capital, I would do it, right? Don't get me wrong. If I'm raising $100 at $1 billion and $500 at $5 billion in the same 24 hours, I have to say yes to that as a founder, right? Because I can't raise $500 at $1 billion. But if it's all some sort of aesthetic, I don't know. Maybe I'm a fuddy-duddy. I just want my investors to make money. And I don't want them to rip me off, but 80% to 90% of a good deal, to me, always seemed to de-stress my life. Always just not taking that last nickel off the table. Always made me worry about one less thing. And I just don't know if I would do it. I don't know if I would do four different prices in one week. I just think the world's a lot more transactional, sadly. It is. It is. And I've rolled with it. I've rolled with it. But I don't know that I would do it.
Speaker 2I think you're right, Harry. The world is a lot more transactional. It leaves me with an icky feeling. And it is all aesthetics. you know every founder is wildly smart and they can calculate a blended pre-money if it's you know 100 million at 1 billion and 300 million at 5 billion they can calculate that the effect of pre-money is 2.something billion that these people are doing advanced ai they can do simple freaking that the interesting question is is there anything in those i mean i'll tell you what i think is there anything in those terms that subsequently bites you in the ass as a founder and this gets to your point jason which is yeah if you don't care about the one you know some you know you're effectively raising money in that example at 2.something billion two years later you decide to sell for 4 billion this is where you're right jason if you don't care that the 5 billion guys only get a 1x then whatever yeah i don't think anybody i don't think anybody cares and i think
Speaker 3it's liberating for founders but i don't think anybody cares you better make damn sure you have a drag along but on top of that it makes it more difficult for stock options but it does give you sorry this is important to say it does give you bragging rights and you're like oh who cares about bragging rights as markets get more and more competitive yeah i agree look it has if you're optimizing for bragging rights it optimizes bragging rights
Speaker 2it's generally the kind of thing that looks look it looks like a really good idea and a good market and then the real question is are the consequences horrific in a bad market and i will say they're silly but they're not horrific i mean if you look at that versus other alternatives like taking a high price but with a ton of structure real structure that's the worst mistake if you're looking at you know not raising money taking out a ton of debt that's a bigger mistake so in the in the litany of mistakes that you can make with your cap table doing a two tranche round that makes all your second tranche people feel like second class citizens it's not the worst thing in the world provided you don't give a damn that they're second class citizens and clearly you don't
Speaker 3is there anything else we should cover boys is there another story here that i've missed that
Speaker 2i should cover yeah it's kind of further afield but i mean i did spend a second on the valo atomic stuff it's just interesting is that you know you know we're all in this together we're all in this together we're all talking about but there is just continued progress on nuclear energy lots of risk you know lots of big step ups lots of private companies doing this some public companies doing it's not trading as well but progress on that dimension and valo atomics looking like they're about to raise at a 3x step up in you know four or five months so it's interesting they're still private but what's really funny i did realize one weird comment i had two weird one word comment on this was if you think about the kind of companies that should be private and the kind of companies trying to do next generation nuclear products should probably be private as yet there's three of them that are public they spacked and they're trading like crazy man up and down 50 in one day and then call me strange a company that's doing six billion in revenues and widely cash flow profit profitable like stripe or like databricks should probably be public as yet here we are with databricks and stripe private databricks doing a series m stripe doing some kind of acquisition that's kind of convoluted which are typically bought public company stages and then you got a whole bunch of these not valor but the other kind of wild frontier tech companies being public is this the weird world the spacks are taking stuff public that should probably be venture backed and the very best venture assets are staying private long after they're kicking off
Speaker 1cash and should be public it's weird i mean there's nothing to say except weird it's so minor but the c-square ipo is just mildly interesting as a footnote can you just give some context jason what is c-squared what's happening yeah so they're a c-tier data center leveraging ai they're doing a billion dollar run rate growing 16 and they ipo'd with a three billion dollar market cap so if you kind of reach this slow growth and you put a veneer and a wrap around it it's still growing at a billion revenue and you're trading at i need to know the enterprise value not the nominal probably lower right the enterprise value you got to figure out the debt it's higher because
Speaker 2they'll have probably debt too oh higher yeah you're right
Speaker 1i mean this is meh maybe rory's gonna say three billion is a great outcome but i i bet it's not when you trace back the history and all of this the lesson for me to see scores you gotta deliver like the market may be exuberant the market may go nuts but it's not stupid this this one wasn't doesn't have the the big ai boost and it didn't get the the the revenue boost it didn't get the
Speaker 2multiple boosts yeah no i agree it was like a yeah public but not i mean and the older assets
Speaker 1not as compelling agreed yeah you know the counter argument to so many things but yeah these other assets can ipo i'm not saying they're not compelling but i'm not saying they're not compelling but i'm not saying they're not compelling but i'm not saying they're not compelling i mean i guess you finally get to a billion in revenue with a bit of an ai veneer and you're worth three times that i mean i guess it's okay but that's not why i'd want to be a founder you got to go you got to make it you
Speaker 2have to deliver you guys done any deals in the last seven days not in the last seven days no sir no i do want to come back to the one other thing that really struck me is interesting you put them in there separately right but i've been thinking about this a lot that you had the tsmc's announcement asml announcement and i was thinking oddly enough about different kinds of trusted supply chains and i'm just going to contrast two because it's quite funny right you have the nvidia relationship with tsmc which famously they don't even have a written contract they've dealt with each other for 30 years nvidia is now tsmc's largest customer and you know it's you know there's there's tensions because they're pushing tsmc to invest more but you know they're managing that really and then the same kind of relation tsmc and asml asml makes the machine that enables tsmc and tsmc makes the wafers that makes nvidia and no one in that entire supply chain has ruthlessly gouged each other asml has raised prices gently tsmc has raised prices gently they're pushing people for forward commits and it's a real hey we know we're going to be dealing with each other for 10 20 more years trusted relationships how do we cooperate for the i'm just tensions but it's not all that crazy and then you just compare and contrast that to the adjacent market for d-ran there's three suppliers in there right you've obviously got the two of koreans and micron right and they're selling to the same customers they're selling to the nvidia's they're selling to all the other things they're selling to apple and there the dynamic is totally different it's like screw you we're raising prices 40 this quarter oh next quarter you still need our stuff raising another 40 right it's just hilarious to watch i mean you see these huge march i mean tsmc and asml kind of thinking long term how do we position ourselves so that we're great and cooperative for the next decade or two decades right all the memory guys are like this is a commodity business you all screwed us three years ago we're going to screw you now for every dime we can we're going to raise prices on you every quarter we're going to make 80 operating margins in what harry would call a commodity because we know that two years from now you're going to screw us and it's just super fun to watch because they're like literally adjacent supply chains benefiting from the same kind of broad trends on ai and one of them is just a super long-term oriented one with single player at every level and just once you get to three players it's just brutal fun to watch i mean there's no action from it it's like unless you're trading dram which is up on the day which is today's tuesday but who knows down on the month it's kind of crazy way to live but just an interesting dynamic the bigger half for me is when that pricing breaks it'll be brutal to the downside
Speaker 3but maybe that's a year two years from now core weavers in the just been depressed for a long ass
Speaker 2time huh well partly i mean one of the things no one ever says is the fact that memory prices the cost of building the product you're trying to build has gone up by 2x because the suppliers are charging you more right so it's getting more expensive to build stuff and then you know obviously they have the big open ai commitment and you know at some point people get worried about that and also i think there's an element of once you're public for a while things gravity takes over and you start thinking what is this company it's still you know i think attractively
Speaker 3valued on a sales multiple basis i don't understand why kimmy and why the open models don't make nvidia a little bit more elevated i mean jesus i'm like just looking at my nvidia position going how long are you going
Speaker 2to stay flat for i think that what's happened there it's interesting because again it boils back to the same big question i mean nvidia got this massive step up over the last you know three years yeah the chat gpt step up to plus or minus 200 bucks a share and if you look at their projections for the next two or three years they're basically saying yeah capex which exploded from you know 100 150 billion to 700 billion growing much more slowly over the next three to four years so it's basically uh we had a one-off step up and now it's going to continue but not amazing growth right and you know one or three things going to happen if it capex stays elevated but doesn't double and double again stock stays roughly where it is and it grows into that valuation if there's another uplift like the claude lift that happened at the start of this year you'll get your stuff you get your next acceleration harry and if there's any kind of slowdown then even this valuation look crazy and it's kind of in that middle until you get a signal either way i mean i think gavin baker had a very interesting term he said i think with some like cross-sectional comparisons i can't remember the exact phrase he was basically saying whatever assumptions you make to value nvidia about the future of to a rounding error you should make roughly the same assumptions in valuing the dram providers in valuing all the other beneficiaries of that what happened is nvidia got the step up first and then every all the bottleneck investors suddenly realized oh my god if nvidia is going to spend they're going to spend 400 million with nvidia or 300 million billion with nvidia they're going to spend 300 billion with memory and all the other bits and pieces and all those guys like sandisk kind of popped up in the last 12 months when nvidia as you say plus or minus has been in that kind of 180 to 210 range and now everyone's at the level that says okay let's see the next card going back to this first sentence the only thing that matters is the open ai and anthropic growth rate in 26 and
Speaker 327. i i love that as a way to finish you know we did miss jason from this episode we missed like a shakespeare quote from rory do you remember last week rory came out with a quote you don't have one for shakespeare i think it wasn't shakespeare no no it was it was another
Speaker 1intellect uh you got anything from the odyssey that would be great i'm actually just really
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