20VC: OpenAI and Anthropic Threatened by Kimi? | Should the US Ban Chinese Open-Source Models | Should Openrouter Sell & Value in the Routing Layer? | Stripe Buying Paypal: What You Need to Know

23 Jul 2026 · 1 h 23 min · 35 chapters

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In short

China’s near-frontier open-weight LLMs (Kimi, Alibaba’s Qwen) and the US policy debate over restricting Chinese models; whether open-weight “LLM intelligence” can be a profitable business; and the economics/opportunities in the routing and inference layers (OpenRouter acquisition chatter, Ramp’s routing product, Fireworks’ inference growth).

Guest backgrounds

Harry Stebbings hosts (20VC).

Guests

Rory O’Driscoll (“OG” tech/VC commentator); Jason Lamkin (“total AI nerd”); plus discussion references to policy and execs (Dean Ball, David Sachs, Emil Michael, Bill Gurley) and companies (OpenAI, Anthropic, OpenRouter, Databricks, Ramp, Fireworks, Base10, Fal, Cursor).

Key claims

China open-weight models are likely 6–9 months behind frontier but will accelerate adoption via much lower cost; a blanket US ban is seen as overkill, but data/IP/security export risks may drive tighter restrictions; open-weight inference providers benefit (Fireworks mid-30s margins rising).

Notable examples

Kimi demand outstrips consumer access; OpenRouter traffic is ~half China-models; Fireworks raised $1.5B, claims 40T tokens/day; OpenRouter in talks to be bought; Ramp launching a routing-layer competitor; labeling/custom “micro-models” and domain tuning can improve outputs by an order of magnitude.

Written by AI. May contain mistakes. Listen to the episode to check what was said.

Chapters

Tap a time to open that second in VO

Introduction to the Topic of Open-Weight Models

0:00 to 0:36

Explore the competitive landscape of low-cost LLMs and their implications.

“The quest for equivalent models at a cheaper price, it's just going to keep going up.”

Model Layer and Recent Announcements

0:48 to 1:23

Discussion on recent developments in the model layer including Chinese models.

“China ships two near-frontier open models in a week, with Kimi absolutely crushing it.”

Model Layer and Recent Announcements

2:14 to 3:07

Discussion on recent developments in the model layer including Chinese models.

“While Base44 turns ideas into apps, Plaud turns conversations into insights.”

Discussion on Chinese AI Models

4:28 to 6:11

Analyze the implications of China's AI models on the global market.

“There has been a lot, as always, going down.”

Political Responses and Regulations

6:11 to 9:48

Explore the political discourse surrounding the regulation of AI models.

“That 50%, instead of being niche or for tech forward folks or venture back folks, you know, in a year, it could be everybody.”

Data Security Concerns and Future Outlook

9:48 to 14:00

Discuss the potential data security risks associated with Chinese AI models.

“First of all, I think that guy at OpenAI had been there like two weeks, right?”

Concerns About On-Prem Security

14:00 to 15:20

Exploration of security reassurances regarding on-prem hosting and data export risks.

“I think every CIO is being told right now, oh, don't worry, if you hosted on-prem, you remove any security risks and the back door then is removed that could potentially be there.”

Data Export Risks with Chinese Products

15:20 to 17:10

Discussion on the risks associated with Chinese software and data export.

“Technically important US companies, Boeing, for example, suffer continual cyber attacks, many of which are attributable to sovereign state actors, including China.”

Open Weight vs. Open Source Models

17:10 to 19:20

Addressing the differences between open weight models and true open source in AI.

“companies from selling those models to the US.”

The Viability of US Open-Weight LLMs

19:20 to 22:50

Analyzing the market potential for US companies to compete in open-weight models.

“We're oversubscribed, but we'll make room for 5 million for Harry.”
Show all 35 chapters

The OpenRouter Acquisition Consideration

22:50 to 26:50

Examining the potential sale of OpenRouter and factors influencing the decision.

“you know, maybe this would be a great product to own if I was a cloud hyperscaler.”

Deciding to Sell: Founders' Perspective

26:50 to 28:00

Understanding the founder's mindset when considering an acquisition offer.

“but it's a terrible way for a founder to think about it because there's way too much risk for not enough money.”

Evaluating Company Sale Decisions

28:00 to 29:25

Discussing financial implications and personal motivations behind selling a company.

“If you have a chance to sell a company for$6 billion and make$600 million, you think you can run it another three years and get$1.2 billion.”

Commoditization and Market Timing

29:25 to 30:32

Analyzing the effects of commoditization on business value and acquisition timing.

“I mean, S to your job by this team, but sometimes if you're early, you can gain a lot of traction in something that becomes somewhat commoditized.”

Fireworks and Inference Market Insights

30:32 to 31:18

Exploring the recent funding and growth of Fireworks in the inference space.

“I don't love the commoditization description.”

Navigating AI Inference Business Models

31:18 to 34:08

Discussing the dynamics of AI inference providers and their market potential.

“Doing over a billion in ARR, got there in three and a half years, and they announced around 40 trillion tokens a day, up from 15.”

Investing in AI Applications vs. Infrastructure

34:08 to 36:54

Debating the current investment landscape between AI infrastructure and applications.

“and they do plan to move into the data center layer themselves.”

Building Custom AI Models for Business

36:54 to 39:48

Discussing the importance of data labeling and creating custom AI models for specific needs.

“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.”

Future of Foundation Models in AI

39:48 to 42:00

Evaluating the sustainability and growth of foundation models amidst rising competition.

“Would that change your confidence on the data labeling market?”

The Impact of Open-Weight Models on Growth Rates

42:00 to 45:30

Discussing how open-weight models might affect the growth of Anthropic and OpenAI.

“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.”

Pricing and Competition in AI Models

45:30 to 49:30

Examining the pricing strategies and competition pressures in the AI model market.

“And if this was a software product with no gross cost of goods sold, that's what they do.”

Stripe's Acquisition of PayPal

49:30 to 54:30

Analyzing Stripe's acquisition of PayPal and its implications for both companies.

“Was it inevitable Stripe would acquire PayPal?”

Challenges of M&A in Tech

54:30 to 56:00

Discussing the complexities and potential challenges faced during mergers and acquisitions in the tech industry.

“them to this kind of contained strategy with Advent.”

Evaluating Stripe's Potential Acquisition of PayPal

56:00 to 58:02

Insights on Stripe's interest in acquiring PayPal and the factors influencing this decision.

“And 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.”

The Historical Context of Stripe and PayPal's Relationship

58:02 to 1:00:09

Discussion about the early connections between Stripe and the founders of PayPal and the implications for their current dynamics.

“But that is the perfect amount of back and forth, 28 to 35.”

Market Dynamics and Investment Strategies in Tech

1:00:09 to 1:03:11

Analysis of current market trends in tech investing, focusing on valuation metrics and investment strategies.

“So on a cap-weighted basis, we should be talking 30 % to 40 % of our time on OpenAion and Tropic, boring as it is, if you are kind of trying to be representative of private tech.”

Challenges in Early-Stage Investing

1:03:11 to 1:06:34

Exploration of the complexities and risks associated with early-stage venture capital investments.

“or the math's going to be tough with that.”

The Impact of Tranche Rounds on Startups

1:06:34 to 1:10:00

Discussion on the implications of tranche financing rounds for startups and their investors.

“They're going, oh, everyone wants these growth rounds.”

Founders and Pre-Money Valuations

1:10:00 to 1:11:50

Explore the implications of pre-money valuations and their effects on founders.

“every founder is wildly smart and they can calculate a blended pre-money if it's 100 million at 1 billion and 300 million at 5 billion, they can calculate that the effect of pre-money is 2.something billion.”

Nuclear Energy and Private Companies

1:11:50 to 1:13:16

Discuss advancements in nuclear energy and the status of private companies in the sector.

“It's kind of further afield, but I mean, I did spend a second on the Valor atomic stuff.”

Public vs. Private Company Dynamics

1:13:16 to 1:14:20

Analyze the contrasting dynamics of public and private companies in tech markets.

“I mean, there's nothing to say except weird.”

NVIDIA, Pricing, and Supply Chain Relationships

1:14:20 to 1:17:37

Examine NVIDIA's stock performance and the implications of supply chain relationships in tech.

“You know, the counterargument to so many things, but yeah, these other assets can IPO.”

Future of OpenAI and Anthropic

1:17:37 to 1:19:46

Speculate on the growth rates of OpenAI and Anthropic and their impact on the market.

“once you're public for a while, things, gravity takes over and you start thinking, what is this company?”

Future of OpenAI and Anthropic

1:21:03 to 1:21:56

Speculate on the growth rates of OpenAI and Anthropic and their impact on the market.

“Founders and operators spend way too much time every week jumping between meetings, investor calls, brainstorms, customer conversations, and then trying to piece everything back together afterwards.”

Future of OpenAI and Anthropic

1:22:39 to 1:23:12

Speculate on the growth rates of OpenAI and Anthropic and their impact on the market.

“That means faster resolutions, more consistent support, and just better experiences for every customer.”
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Transcript

Automatic transcript. May contain errors.

0:00The 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. At 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 entropic 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.

0:36Harry Stebbings:This 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.

1:19Harry Stebbings: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.

1:57Harry Stebbings:So in this market, fast is the baseline. To win, you just have to be first. Base 44 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, Plaud turns conversations into insights. Founders and operators spend way too much time every week jumping between meetings, investor calls, brainstorms, customer conversations, and then trying to piece everything back together afterwards. And that's why I've been using Plaud. Plaud 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.

2:44Harry Stebbings: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 Plaud 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 2 million founders, operators, investors, consultants, and professionals using Plaud to stay organized. So think more clearly and stop losing great ideas and important details. Go to plaud.ai slash 20VC and use the code 20VC for 10 % off. That's P-L-A-U-D dot A-I slash 20VC and use the code 20VC for 10 % off.

3:22Harry Stebbings:While plaud captures the conversation, Finn helps continue it. As AI agents become more common in customer experience, teams often end up juggling multiple silo 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.

3:57Harry Stebbings: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 Fin to deliver better customer experiences. So for a limited time, you can get$500 a month in Fin credits. For your first three months, learn more at fin.ai forward slash 20VC. You have now arrived at your destination. Guys, I'm looking forward to this. There has been a lot, as always, going down.

4:34Harry Stebbings:I remember when like news cycles were so much shorter. I don't know if you remember this, but like, you know, 100 million round and it would be like the thing for a week. And now like 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 Kimmy, which has got a lot of attention, a lot of press. And then the other being Quen from Alibaba. Well, how significant were the two model announcements that we saw today?

5:07Harry Stebbings:And what should we be taking from their seemingly catching up or close to with the frontier models we have in the West? Well, 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 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 I mean, let's not overreact. Having said that, I mean, we can't even sign up new as consumers for Kimmy 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.

5:42We 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. You know, 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.

6:12And that's why you see the stress. That 50%, instead of being niche or for tech forward folks or venture back folks, you know, in a year, it could be everybody. And that's material. Just being in the zone and even materially cheaper, it's just going to get more and more attention. I totally agree with that, actually, Jason. I was curious to see what you'd say. He said, Carrie, you kind of led with the, what do 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 those five main Chinese LLM companies and a bunch of followers, it turns out that aggressively funded companies with smart engineers are just going to keep cranking true and building new models.

6:49They'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 US responded to that. We had the small p political response. So that's one dimension, the policy advisor 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 company.

7:24I mean, Jason hinted at it. We lump all these models in together. But some of the DeepSeek models, you can run on your PC. Conversely, Kimi K3 is, I think, a 2.8 trillion parameter model. It's a huge honking thing. And 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 US frontier models. So we can learn about, I think we'll kind of talk about the politics first, and then maybe oddly enough, talk about the inference implications and as that goes into the opportunity for fireworks.

7:57So 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.

8:13Harry Stebbings:If 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. Yeah. And then Emil Michael obviously latched onto it. I'm trying to remember, is it Dean Ball? It's Dean Ball. And he is current, I think it's at 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 open.

8:47Everyone was mean to me because I posted a bunch of stuff. And I think it was frankly a little naive comment because 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 when Sarah fired it, 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.

9:19You know, that's your side. And if you start, if you make the 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 jock up our rates the minute the stuff gets banned. It was a little naive not to expect that level of blowback. First of all, I think that guy at OpenAI had been there like two weeks, right?

9:51Yeah, 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 U.S., 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 U.S. 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?

10:28How limited are we going to? Because it's going to be limited. The availability of China built models to penetrate the oil 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.

11:00The 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 is just going to keep going up. But we've always had cheaper, pretty good solutions from other vendors. It's not new.

11:28Harry Stebbings:Do 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 cut it out? I 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 A.I.s are, who basically said, this is rubbish, stop.

12:01And then the second one was Emil, whom you mentioned before, Emil Michael. I'm never sure of the pronunciation of his last name, who was a guy at the Defense Department who got totally sideways with Antropic. 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. It's got to make you think, because that's an interesting lineup.

12:32And 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 Kimi. came to be 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.

13:08And it would be horribly bad policy to ban that. Another rich, grouchy billionaire. Grouchy Bill Gurley's probably got 30 IQ points on me, and he's seen it all. 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 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.

13:38It'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. And 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.

14:04Harry Stebbings:I think every CIO is being told right now, oh, don't worry, if you hosted on-prem, you remove any security risks and the back door then is removed that could potentially be there. Why would you not be alleviated by that reassurance if OnPram would solve that solution? Why would you not be reassured? We're always more of a historian here than me. You 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.

14:37No, 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. These are companies that are arguably run by the PLA. I'm just saying my lifetime of experiences, I'm not confident there isn't. 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, I don't know, man.

15:18I 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 US 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. It would be naive not to put it on the table. First comment. Second comment is, I'm thinking about, can you, I mean, the problem with proving a negative is, can you know? If you have, and remember, these are open, I occasionally say open source incorrectly.

15:50They 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 source in the context of an LLM means seeing the underlying training data, which you don't. But you have the open width. The question is, if the model is being run in a trusted US 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?

16:21You can imagine being able to use these models fairly comfortably and being fairly certain that you have blocked access and this can't happen. 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.

17:02But 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 US. 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.

17:29But 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 OpenAI and Entropic a run for their money? And Jason, that'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 state-of-the-art frontier, but 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.

18:04Is 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 the open-weight models in China are getting$50,$70 billion valuations. 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.

18:45And 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 IP plus inference and an open source model where you dissociate the IP from the inference cost. If you're looking at 80 % cheaper opportunity and there's the mass demand for that, when is someone going to try and fill that demand in the US?

19:08Harry Stebbings: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 Berlin fell into my inbox. I have an SPV for you. Do Kimmy at 20 Berlin. We're oversubscribed, but we'll make room for 5 million for Harry. Yeah. That's because we say such nice things about them. Thank you for your check. We're going to glass by it and I don't have an answer, but it's a huge fricking question.

19:37There's this new category called LLM intelligence, two companies in existence as premium products. Their 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, reflection?

20:11As you say, where are you, thinking machines? Where are you, lab? I mean, the fact that there's four or five potential companies, it's just fascinating. Rory, are you asking them to dance? I'm asking

20:19Harry Stebbings:them to ship 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 routing model provider product. I think it's a great time for OpenRouter to sell. 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. Everyone's figured out they need this.

20:55OpenRouter, 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 that more and more people are going to build variants of themselves.

21:26And is this the plumbing they will pick? Will, you know, if you're on adjacent platforms, if you're using Databricks gateway, they'll, they have their own harness. They'll figure this out for you. They will, I don't know whether ramps competitor even makes sense. Like my point is it's something that's going to become embedded in so many vendors that if I could sell for a lofty multiple of my last round, I might, I might check out a five or 6 billion. You've achieved a certain amount of victory in a market that's going through radical change and becoming part of everything, I might take the offer.

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21:57Jason is answering the question, why is it a good time to sell? And frankly, as you yourself, Jason, have said, and I say it too, the private market liquidity window opens so rarely that it's always a good idea to pay attention when it does. So I think it's easy to understand that side of it. I actually think the interesting side of the discussion is the other side. Why would someone want to buy? And I think when I saw that article, I was like, yeah, that makes sense. If you think about the last conversation we had, what's in the zeitgeist right now? It's this whole idea of can I get escape model dependency, manage my costs, have a whole load of alternatives easily available to me.

22:35If I'm someone like who makes my money as a hyperscaler hosting, especially someone that doesn't have their own, just one in-house model they're pushing like Gemini. If I'm maybe Amazon in particular, who's made a business of saying I'm going to support all the models, if you had maybe even Microsoft now that the divorce is coming true from OpenAI, you know, maybe this would be a great product to own if I was a cloud hyperscaler. So I will admit I had that moment of, because you often see, and it's step out, you often see this in this kind of market. You have these businesses where intellectually over a 10-year period, you can say, hey, margins are going to be tough in that business.

23:13It's going to be compressed and maybe it won't at scale in the end be an amazingly valuable business because it won't be able to extract margin. But on the other hand, when growth is so quick and people's urgency to adopt technology is so fast as it is right now, if you have a crucial piece of the plumbing at just the right time when two or three people need that piece of plumbing, you can find yourself in a very interesting position in terms of M &A. Because it may well be that, and this is where the finance guys miss it, it may well be that the NPV of the company on a standalone basis is, you know, couple of billion, not huge.

23:47But the value to it right now, to a hyperscaler, if they could shift 10 % market share in the enterprise to them over the next half a decade by saying, dude, we are the model agnostic people and we'll make it easy, could be interesting. So I remember thinking, shit, I wish I was in that. I mean, which is always how you know what a venture guy really thinks. It's like, damn, I bet you they could get a good offer right now. It's just interesting. An interesting time to sell, an interesting time to buy. I mean - Roy, if you're on that board, would you sell at five to$6 billion? You know, it's always hard to, I mean, my first comment is whenever you get an offer, I always do the same thing.

24:23Say to the founders, one, the window's open, it doesn't open often, we should take it seriously. Two, I'm going to support you in whatever you want to do. Three, if there's concerns that you have that you've been sitting on and not telling me, now would be a good time to share so we can make an informed decision, right? And then go away and think about it and have a whole process of how you talk to them about it. I don't think you should pressure people into selling. I think your job is to give them whatever experience you have to bring to bear, and then they'll make the decision. And it's so funny because founders agonize about this when they think about control and they think, oh, my God, these people are going to make a sale.

24:57Even if, as the VCs, we have board control, 70 % ownership, and a drag along for the founders. Jason knows this. If the founders who are core to the business don't want to sell, it's not going to happen. So the first thing I tell the founders is, it's your decision, which I think is very empowering, because it takes it away from people are going to make you. That's the beauty of being private, unlike being public, where you don't have that degree of freedom. So yeah, I would say to them, take this seriously. Do you think you can be worth 3x this in three, four years? Do you think that's worth it?

25:29But yeah, I would definitely say, take a day out of your life and think about this long and hard. The way Harry phrased his question is very VC-centric. Would you sell at six... I I can't do the accent. Would you sell at 6 billion? Okay. I hate the term triggering. That triggered me. That triggered me. Because this is a very VC-centric way to think of it. I've got an asset. What am I sitting at in my last round? 1.8 billion. Okay. There's going to be dilution. There's time value of money. There's IRR impact. The 6 billion worth, is it worth it for me? I think for a founder, when you start to get into nosebleed offers in absolute terms, it has to be 10X to go for it.

26:05It's not worth it for 3X. It is not, okay, let's say I own 15 % of open router, okay, for the money, okay? It's not, how much am I going to take home, okay? It's$4 billion. I'm going to take home$600 million, okay? I got, now one of the founders I think is super rich, right? But put that aside. I got$4 million in the bank,$400 ,000,$40 ,000. I'm going to walk away with$600 ,000,$700 million. 3x for you, maybe later in life, it's now 10x. and this is another trite VCism, building something truly generational, you kind of know as a founder when you're on that path, okay? And so the VC, should I do it for 2.8X on my last, you know, it's just, it's the right way as a financier to think about it, don't get me wrong, but it's a terrible way for a founder to think about it because there's way too much risk for not enough money.

26:55Like going from, again, going from 40 ,000 in the bank to 400 million versus 800 million, it's irrelevant if there's risk. then there is a handful of work there is a handful of work in those next three years it is a handful of sweat and a handful of market change and a handful of people that quit and move on and a handful of competitors that they're looking pretty good and they may pass you three three x not good enough man gotta be 10x i'm confused what are you saying are you saying to sell at six are you saying which is odd because i'm saying if it's financial sell at six 18 is not enough it's got to be 60 to be worth the risk for most founders it's not enough i understand down what he's saying.

27:33This isn't clearing the prep stack. This is clearing my life stack. It was weird. I didn't think you were going that direction. But as often happens with you, when I listen to the whole thing, I'm like, I get it. I think what he's saying is this, Harry, when you face that sell decision, you don't not sell because you think you can make twice as much in a year because you just never know. And in the end, even though I didn't think I'd agree with him, in the end, I did. It's like, what I think he's saying is, let's leave aside the what do you want you do with your life questions. From a return perspective, don't think incrementally.

28:02If you have a chance to sell a company for$6 billion and make$600 million, you think you can run it another three years and get$1.2 billion. Risk-adjusted, that mightn't be worth it if your current net worth is$40 ,000. And that's actually good financial advice. I mean, in other words, if you turn down a big-ass offer, you better be sure it can be way bigger. You better have high certainty and high bickerness. I think that's a fair comment. Yeah, if it's 10x, this is my net advice. If you know in your heart and soul you are building a company 10x bigger than this, right or wrong? I don't know.

28:32Then F and say no and go for it. Here's a few more shares, in fact, friends. Let me reload you. But they only vest at 10x, right? Go for it. It wasn't where I thought you were going, because I actually thought you were going to say, yeah, don't sell also just because financially you feel you should. I mean, because the other thing you're not taking into account is, it depends on the person. Some people just love running that company. And frankly, don't want to sell. It's their life's work. And I also think you have to respect, I mean, my point, you also have to respect that. I mean, again, this gets back to the, there's no one answer the founder decides.

29:04I've known people who are like, this is my first hit. I'm going to take it. Who ran exactly that logic. I am not, I'm going to make 60 million bucks. I don't have 1 million buck and maybe I could make one 20 in four years, but I'm taking the 60. And I've also known other people who to a rounding error have said, this is what I want to do for the rest of my life why would i take that money i've got three or four million in the

29:25Harry Stebbings:secondary i got my house i'm done can i ask more more more my thing here so we said it doesn't matter ramp but ramp doing their own database doing their own i just interviewed the founder of fireworks who announced their 17.5 billion dollar valuation is there any value in this layer if it's as commoditized as everyone well that's why i would sell with my limited knowledge but as a user right as a customer i would sell just because i think there's some commodification at a minimum, right? Sometimes you're lucky. I mean, S to your job by this team, but sometimes if you're early, you can gain a lot of traction in something that becomes somewhat commoditized.

30:00It's just, 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 decretes rather than it accretes. And it, my gut is it might be, it might be now that crossover moment. And 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.

30:31And it's probably why Cursor wasn't dumb to sell at$60 billion. I think we can agree that's true. I don't love the commoditization description. I think it's an overloaded term. Well, it included feature. And more and more folks will include some version of your functionality in their product. Agreed. That's exactly it. Which segues to the next topic.

30:51Harry Stebbings:Which is fireworks? Yeah, and 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, Media, Lightspeed, 20VC, amazing firms. They're incredible. They're really fucking good. Lynn is amazing. Doing over a billion in ARR, got there in three and a half years, and they announced around 40 trillion tokens a day, up from 15.

31:34First of all, I agree. Yeah, inferences are huge. It goes back, ironically, to the prior command on open-weight models. This kind of standalone inference is a big business. And obviously, 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 and provide the compute for that. But people like Fireworks and Base10 and File, 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.

32:11They're exploding because the open source trend is exploding. So if you're Base 10, 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, it's one thing to decide to use an open weight model on Fireworks in the US. 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 way trend. These are the companies that are benefiting massively from that trend.

32:45And it's not the only kind of route for inference. There are 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. And I believe 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, but candidly, I think, again, it actually goes back to the point I made earlier.

33:16There'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 near clouds and you're offering this product and are you going to be scrunched? And margins were 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.

33:52So not only are they probably growing 5x to a billion, but they're probably growing 5x to a billion with expanding gross margins.

33:59Harry Stebbings:And 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? 30%. 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.

34:31At 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. There is one thread of the Twitterati who has said for a while, like, all this stuff's interesting, but ultimately it's the, you know, the application layer is going to be the most interesting. It's going to benefit from all this. Everything's commodified, right?

35:01All 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.

35:24Harry Stebbings:But to put it again, Lynn said in the show, she expects to double by the end of the year. Yeah, yeah. 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 a vibe coding applications run amok. Everyone thought you'd replace your sales source. You even had a guest the other week who was, I forget to say how great it was to replace sales source. 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.

35:52It's so trivial. It's almost a rounding error, the application layer. And just to dimension that, because I agree, Jason. I mean, look, 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 eight, nine hundred billion dollars a year. Then there's the two foundation model companies themselves, and they're doing plus or minus a hundred billion dollars a year.

36:23and then taking those guys out, rounding up every other apps company, you struggle to make 40 or 50 bill. You struggle. You start with Cursor at four because I think coding is an app. By the time you're checking in Harvey, you're adding two, 300 million, right? It's amazing. I mean, just the difference in spend. And 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, Info has been the place to be.

36:55There'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 OpenAI are spending on training data.

37:12Harry Stebbings:That I can guarantee you when you look at McCall hitting$2 billion in ARL. Yeah,$2 billion for Merkur, Surge, another billion. You get to$4 or$5 billion and, you know. Surges, three. Yep. But handshakes one, I mean... I mean, yeah. Maybe if you start throwing in on the other side the consumer products like Higgs field, you get to roughly the same place, but it's astonishing. The scale of the investment versus the scale of the apps at this point means that all the action's on the info side for now. If we bring this all together, we mentioned fireworks at the start. Lynn said in the show, the future would be every company having specialized models with their own data.

37:46Harry Stebbings:We mentioned Harvey there, who've been building their own models. Jason, I'm just intrigued. and the last week you spent time labeling data, building your own model through that data. Any lessons, reflections from the last few days, labeling data and going through that process that you've been through? I 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 labeling to make it. Now I'm going to put model in quotes, right?

38:20It uses Sonnet and Opus. So there's different definitions of model. And it was good. But man, once I started labeling all of this, 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 ChatGPT or Kimmy or Shmimmy. It's still your own model, even if it's not technically a model, right? Because you have your own reasoning layer with your own rules, your own weights, your own. But you want more. If you have the resources, you want to go further than that. Right. You want your big M model.

38:56As 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 Harvey or Cursor. So some version of this, I think folks that are going to want to use at any application folks that are going to want to use just the generic models is just going to decline to prototypes, prototypes and proofing. Yeah. are absolute state of the art small parts of the overall task, but agreed. Parts. Yeah. Little parts. Right. Yeah. I mean, you're going to want to use the expensive tool for the expensive parts. And you're going to want to use the cheap tool for most of the parts on the customized tool to usage.

39:31But 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.

39:50Harry Stebbings:Would that change your confidence on the data labeling market? A lot of shade is thrown at it. As an investor in McCore, I definitely see it. Does that change how you think about it? 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 model, right? The amount of power you can get in a domain by having a subject manager 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?

40:30Every mediocre history professor, every mediocre doctor that doesn't even know 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 Mercure, 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 better output. So powerful. 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?

41:09And 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 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 reduces customer concentration.

41:54And I think that's what people like Merkur are forecasting. If, on the other hand, you know, which is hard to contemplate 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 if it's any consolation, Harry, if that happens, worrying about your marketer valuation will be the least thing people are worried about because you'll see an implosion of much bigger market cap entities, right? And that frankly is the billion dollar question.

42:26Can these two foundation models maintain their growth trajectory, which is starting to become profitable, at least in the case of Entropic, in the face of all this open weight competition, in the face of this pushback on costs, and basically it's 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 slowdown on those two ARR growth rates, then 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 2 or 3x growth rate, there's going to be a mad scramble.

43:10Harry Stebbings:Bets on yes or no answer will open impact that trajectory for Anthropic and OpenAI in the next one to two years. Yes, Harry, it will impact. It might impact at 1 % or 50%. What you're really saying, the question you're really trying to ask is, does it reduce that growth rate to some 100 % within one or two years? And the answer to 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 US 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.

43:48And yeah, you can say if the open models, open weight models explode, there will be a demand for inference. And yeah, you will have this kind of transition from, oh, I sold it to OpenAI, 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 question. 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.

44:20Then 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 % 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 could have 17 variants of the model at 17 price points. That's not the issue.

44:52The issue is because they have to pay to train these damn models and other reasons. They have just this high cost base and they're subsidizing it with venture capital, right? Whether we call this venture capital or not, private capital. And so, but listen, you just cut the price of Fable 5 by half tomorrow. You don't need these Kimmy Schmimmys, 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 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 for it because I do think we should spend at least half the show on stuff other than AI model companies.

45:27But 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 rootlessly 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.

45:59But as you're pointing out here, there are real, even at the margin, even after you've fully paid for your training costs, there are real physical costs to serve these models. And you've got to cover your nut. You've got to cover the marginal cost of the model of the inference, which gets you to, either, two, three bucks, kind of, blended average token. Then you've got to recover the cost of the training, and you've got to recover it 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 profits because you're being valued at 20 times revenues.

46:30And 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, ooh, there's lots of things that could go wrong here when you look at 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, if the only way you can keep that growth rate up is by lowering your price per, then your gross margins start to deteriorate instead of continuing to improve.

47:03That 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 building your own everything, all the stuff you're trying to do to solve this problem. But 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 ChetGD, they bundled everything. I can get$10 ,000 worth of tokens for 200 bucks and I can just do just about anything in it, right? It's just outside of the consumer, it's not massively bundled and subsidized, right?

47:34You remember the old days in software, Jason, when you'd have to say, I promise I'm only using this for personal use. You remember that? And licensing? Well, if you're telling those nice Claude people that you're only using your personal subscription for personal use, they're going to finds you dude well yeah it's just it's just fable is very good that's why they're going to find a

47:51Harry Stebbings:way to charge for it rory you were like are we gonna get away from this like ai stuff at some yeah yeah i mean so much were 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 is at 587 million 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 how much he got he got like eight million dollars the amount he made from it yeah yeah you know context is so funny i don't want to distract we're like how much had been 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.

48:40Well, is it really worth our time, gentlemen? It's really only a 4X to the last round. 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 the company for 500 million.

48:55Harry Stebbings:Rory, do you know what? I find that triggering. Get on him. I mean, no surprise. It turns out that you can make more money with 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 the world. Right. It's yeah. No surprise. All right, Roy, I'm going to listen to you, though. Move away from this A.I. pure play discussion. I'm going to move to some Irish twins. The Stripe and Advent deal to take PayPal private. Does that sound OK? It sounds good. I mean, you've got to talk about it.

49:28Harry Stebbings:We've got to talk about it. So this is a big deal. 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 the offer. Rory, how did you think about it? I think that price clears all. I mean, I think it's super interesting in a lot of different ways. One is they both process kind of$1.9,$1.8 trillion 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 I think, what was the offer for PayPal? I looked at it this morning, but it's at 50-something billion, right?

50:04So 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.

50:44So 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 one and a half times the size. It's still a company buying something one and a half times its size for what looks like a third less because they're doing a joint deal with Advent, a PE provider, so for 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 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, is a desirable place to work.

51:27And 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. Yeah, the part that I struggle with a little bit, obviously there's at least a decent synergy here, right?

51:56And in a PowerPoint slide, there's a ton of synergy. Plus you get Venmo, you get a lot of stuff. Yes, you get 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 percent? It's between 20 and 30. So it's not that much bigger, Jason. But seven. But seven. So, OK, hold on. Help me. Rory, you're better than math than me. But if I take 30 and seven, that's 37 and divide by two.

52:27I'm only growing like 18 percent now. I've fallen below the Mendoza line of 20 percent growth at scale. There's no such thing as a Mendoza line for growth at five billion and above because you can get out. I mean, I think the real point is. But I found it stressful in M &A observation, not quite at the 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 gonna have to recognize some of this revenue, right?

52:54As a joint venture. So it's gonna decelerate their growth. It's not stress-free. Plus you have the operational need. Plus, I mean, even all the layoffs they're gonna 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.

53:25But the real answer is you don't fix a lot of these things that seem like you can't rationalize them between the organizations. Everyone's got 11 products spaghettied together. Even tech leaders have it, right? It's just the nature of M &A. My 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 is a real mess. And they've dissipated their opportunities. So yes, I mean, the interesting thing is nobody's the kind of deal you do after you go public because you have the market cap and you just price the deal.

53:57And I was thinking, my first glance was, oh, 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.

54:36Will this happen? I don't know. It's actually getting done. I think it happens. Let me just step back. Rory's got even more experience, 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. They're just 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.

55:12By rejecting it, it means they're going to accept it. I think Jason could well be right. I think I hinted this earlier. 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, you know what the bankers are telling them right now is, you know, 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, you can only, 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.

55:51So even as we speak, the PayPal team are 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. And 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 with a board member going, am I really sure this guy can turn it around?

56:24You 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 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're 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 already. That's probably the only thing that could give the board the courage to say, I'm just not doing this.

56:58In other words, I have an internal. There's probably five key internal metrics that matter. You know, take rate, new merchants per quarter, you know, 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 % 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.

57:36Do 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 % to charge your fiduciary obligation and take the money? Yeah, 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 % 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.

58:06It's already prescripted. Yes. It's already prescripted. And the bankers will charge a couple hundred million bucks for the property. How are we going to get from 28 to 35? Well, we could just, let's just offer them 35. We'll never get there. We have to offer them a 28 % 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 they've already been discussions at, you know, at the whatever media summit or whatever.

58:37And so there probably ain't. So it's probably just a dance from 28 to 35. And then it gets parked with Advent to while they figure out antitrust in capital issues. So Stripe finally, the Padawan finally becomes the Jedi. Stripe takes over PayPal. It's just a matter of time. And it lands where it should have been. And all the early PayPal guys that did the pre-seed along with Sam Altman's 2%, they're going to do pretty well in the end. Totally. They're coming back through the back door. Yeah. They're getting the old gang back together again. For listeners who may not know it, one of the very early Stripe rounds, I know Peter Thiel was an investor.

59:09A number of the folks who are 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, and 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? They probably ring the Collison's and say, hey, guys, if you're doing the victory lap on the PayPal HQ headquarters, can you include me in on that trip?

59:42Harry Stebbings:Now, 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? I'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 2 ,000 interesting companies. On the other hand, as you would be the first to point out, cap-weighted. In other words, weighted by dollar, they're$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 OpenAion and Tropic, boring as it is, if you are kind of trying to be representative of private tech.

1:00:20So 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 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 ain't got shit.

1:00:56Data 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 you're a 401k at an all-time high dependent.

1:01:10Harry Stebbings: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 1.5 billion post money on 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.

1:01:57Harry Stebbings: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. I 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. Well, 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?

1:02:38There'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 so hard as it looked. It was all the rest. Now, that gap, you better have seed investor skills at the Series B, or the math's going to be tough with that.

1:03:14There's a lot of pressure on the picket. That's just what I think it is below the gross stage. And 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.

1:03:24Harry Stebbings:Again, 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 two billion by the end of this year at 17 and a half billion you're paying less than 10 well if you want 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 some point i guess it doesn't matter it's just putting the absolute amount of money you can in the elastanthropic round but for most of us without unlimited capital you know if you can pick better earlier you end up owning more.

1:04:05It does pay off. That extra three to four X isn't terrible. That extra three to four X on the way to the billion dollar round. It's not a terrible problem. I just don't think many

1:04:12Harry Stebbings:people can pick. And I think we are here to make money. They can't. It's hard. Pick is 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 office. And you get to pick like it's 2006, right? But it is true. And the change that the biggest brands will pay the highest price in many cases, 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're either in the round or you're not, right? And you know what? On top of that, I'm worried you can forgive me for going off on this ramp, but Brandon at McCaw has mouthed off, I may say that nicely, but mouthed off on Twitter about Sequoia's tranche rounds.

1:04:51Harry Stebbings:I think it's brilliant marketing for Sequoia. Honestly, I would have retweeted it. But the amount of tranche rounds I see, I saw a round the other day with four tranches. I thought it was a multi-story car park. Those two things go together. That tranche comment goes together with your prior comment, which is, I'm going to paraphrase it, it's like doing classic early stage A-B 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're going to be competing in every deal. Conversely, Harry's saying, I'd look at these companies at one and a half billion, they're doing a couple hundred million in revenue.

1:05:30Yeah, 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 three 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.

1:06:04We'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 fucking 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.

1:06:33So 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 a tension in, do you stick to what you're doing because you should do it? Or do you move around within the overall environment?

1:07:05And I know what you're going to say, you think you should move around. And I agree. From a pure, if you can pull it off, from a pure, logically, over the long term, over the long term, and by long term, I mean, you know, longer than you've been alive, Harry, 30 years. Like, the truth is early should have a higher overall return multiple than mid, than late, because otherwise, cap M, the rational 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.

1:07:35You know, a combination of increasing equity valuations and a new trend means from 2022 on, late stage being amazingly good.

1:07:42Harry Stebbings:I completely agree. Obviously, if you are in 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 actually, Thrive and many other very large funds will have much better numbers than the majority of early funds. 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, it's two things.

1:08:13The 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 exactly right. I wonder if I was a founder, if I would really do contemporaneously trunched rounds. I don't know that I would. Is it not a good deal for them?

1:08:44I 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?

1:09:15Because 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 want my investors to get not under – I don't want them to rip me off. But 80 % to 90 % of a good deal to me always seem to de-stress my life. always just not taking that last nickel off the table always made me worry about one less thing. And maybe, and I just don't know why 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.

1:09:50I've rolled with it, but I don't know that I would do it. I'm kind of with Jason for the record. I think you're right, Harry. The world is a lot more transactional. It leaves me with an icky feeling. And it is all aesthetics because, you know, every founder is wildly smart and they can calculate a blended pre-money if it's 100 million at 1 billion and 300 million at 5 billion, they can calculate that the effect of pre-money is 2.something billion. These people are doing advanced AI. They can do simple freaking math. The interesting question is, is there anything in those terms? I mean, I'll tell you what I think.

1:10:18Is there anything in those terms that subsequently bites you in the ass as a founder? And this gets to your point, Jason, which is if you don't care about the one, 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 cares. And I think it's liberating for founders, but I don't think anybody cares anymore.

1:10:43Harry Stebbings: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, if I can come out and say I've raised at$5 billion with Sequoia leading, it will create fear among other VCs to fund competitors. No, I agree. Look, if you're optimizing for bragging rights, it optimizes bragging rights. It's generally the kind of thing that looks, look, it looks like a really good idea in a good market.

1:11:14And 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 look at it, not raising money, taking out a ton of debt, that's a bigger mistake. In the litany of mistakes that you can make with your cap table, doing a two-tronche round that makes all your second-tronche 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.

1:11:45Harry Stebbings:And clearly you don't. Is there anything else we should cover, boys? Is there another story here that I've missed that I should cover? It's kind of further afield, but I mean, I did spend a second on the Valor atomic stuff. So it's just interesting is that, you know, we're all talking about the world, 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 this, not trading as well, but progress on that dimension. And Valor Atomics looking like they're about to raise at a 3x step up in four or five months.

1:12:17So it's interesting. They're still private. But what's really funny, I did realize one weird comment. I had two weird, one weird comment on this was, if you think about the kind of companies that should be private and the kind of companies that should be public. Companies trying to do next generation nuclear products should probably be private. As yet, there's three of them that are public. They SPAC'd and they're trading like crazy men, up and down 50 % in one day. And then call me strange, a company that's doing 6 billion in revenues and widely cash flow profitable like Stripe or like Databricks should probably be public.

1:12:47As 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. It's just a weird world. The SPACs 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 cash 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.

1:13:22Harry Stebbings: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$3 billion 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 they'll have probably debt too. Oh, higher. Yeah, you're right. I mean, this is meh.

1:13:55Maybe Rory's going to say 3 billion is a great outcome, but I bet it's not when you trace back the history and all of this. The lesson for me to see scores, you got to deliver. Like the market may be exuberant. The market may go nuts, but it's not stupid. This one doesn't have the big AI boost and it didn't get the revenue boost. It didn't get the multiple boost. Yeah, no, I agree. It was like a public, but not. I mean, older assets, not as compelling. Agreed. Yeah. You know, the counterargument to so many things, but yeah, these other assets can IPO. 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.

1:14:28I 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 have to deliver.

1:14:33Harry Stebbings: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 as interesting. You put them in there separately, right? But I've been thinking about this a lot. 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.

1:15:04NVIDIA is now TSMC's largest customer. And, you know, there's tensions because they're pushing TSMC to invest more. But, you know, they're managing that relationship. 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.

1:15:37How do we cooperate for the long time? There's tensions, but it's not all that crazy. And then you just compare and contrast that to the adjacent market for DRAM. There's three suppliers in there, right? You've obviously got the two, EPCoreans and Micron, right? And they're selling to the same customers. They're selling to the NVIDIAs. 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.

1:16:08I mean, you see these huge launch. 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.

1:16:44And 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 big aha for me is when that pricing breaks, it'll be brutal to the downside. But maybe that's a year, two years from now.

1:17:10Harry Stebbings:Core Weaver is in the, it's been depressed for a long ass time, 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 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, I think, attractively valued on a sales multiple basis.

1:17:46Harry Stebbings: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 to 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 three years, 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 CapEx, which exploded from 100, 150 billion to 700 billion, growing much more slowly over the next three to four years.

1:18:21So it's basically we had a one-off step up and now it's going to continue, but not amazing growth. And one of three things going to happen. And if 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 step. You get your next acceleration, Harry. And if there's any kind of slowdown, then even this valuation will 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.

1:18:52He said, I think it was something 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 two rounding errors, 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 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 with NVIDIA, they're going to spend$300 billion with memory and all the other bits and pieces.

1:19:22And 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, OK, let's see the next card. Going back to this first sentence, the only thing that matters is the open AI and Antropic growth rate in 26 and 27.

1:19:43Harry Stebbings:I love that as a way to finish. You know what we did miss, though, 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 us i think it wasn't shakespeare no no it was it was another intellect uh rory you got anything from the odyssey that would be great i'm actually just really looking forward to seeing it you know right but before we leave you 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, base 44 is where that wall disappears.

1:20:23Harry Stebbings:You describe it? Yeah, base 44 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.

1:20:57Harry Stebbings: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, investor calls, brainstorms, customer conversations, and then trying to piece everything back together afterwards. And that's why I've been using Plaud. Plaud 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 brain memory system.

1:21:37Harry Stebbings:And the crazy part is the hardware itself. The Plaud 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 2 million founders, operators, investors, consultants, and professionals using Plaud to stay organized. So think more clearly and stop losing great ideas and important details. Go to plaud.ai slash 20VC and use the code 20VC for 10 % off. That's P-L-A-U-D dot A and use the code 20VC for 10 % off. While Plaud captures the conversation, Finn helps continue it. As AI agents become more common in customer experience, teams often end up juggling multiple silo tools for every job.

1:22:20Harry Stebbings: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.

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From the publisher

AGENDA:

00:04 China's Kimi and Qwen Put Frontier AI on Notice
00:08 Washington Debates Whether Chinese AI Models Should Be Banned
00:17 Can America Build a Profitable Open-Weight AI Champion?
00:21 OpenRouter's Moment: Is This the Perfect Time to Sell?
00:31 Fireworks' $1.5B Raise Signals the Real AI Money Is in Infrastructure
00:39 Why Every Great AI App May Need to Build Its Own Model
00:50 Stripe's Bold Play to Buy PayPal
01:01 The AI Funding Frenzy: Why Late-Stage Venture Is Winning
01:12 Nuclear Startups Go Wild While Databricks and Stripe Stay Private
01:15 The AI Supply Chain War: TSMC, ASML, DRAM—and Nvidia's Next Move

 

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