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Frontier Labs Threatened by Kimi? Should the US Ban Chinese Open-Source Models & Stripe Buys PayPal

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Frontier Labs Threatened by Kimi? Should the US Ban Chinese Open-Source Models & Stripe Buys PayPal
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Jason Lemkin is one of the leading SaaS investors of the last decade with a portfolio including the likes of Algolia, Talkdesk, Owner, RevenueCat, Saleloft and more. Rory O’Driscoll is a General Partner @ Scale where he has led investments in category leaders such as Bill.com (BILL), Box (BOX), DocuSign (DOCU), and WalkMe (WKME), among others. ----------------------------------------------- Timestamps: 00:00 Intro 01:08 China's New Open Weight Models — Should the US Be Worried? 07:14 OpenAI's "AI Communism" Tweet Causes a Firestorm 13:45 Why Can't the US Build a Competitive Open Weight Model? 19:35 Open Router in Talks to Sell 31:27 Fireworks AI Raises at $17.5B 36:32 The Application Layer Still Hasn't Arrived 52:28 Stripe & Advent Bid to Take PayPal Private 1:04:18 Databricks at $188B: Private Companies Acting Public 1:18:34 Nuclear Energy: The Quiet Progress Nobody Talks About ---------------------------------------------------------------------------------------------- Try Plaud at https://plaud.ai/20VC and use code "20VC" for 10% off. ---------------------------------------------------------------------------------------------- Subscribe on Spotify: https://open.spotify.com/show/3j2KMcZ... Subscribe on Apple Podcasts: https://podcasts.apple.com/us/podcast... Follow Harry Stebbings on X: https://x.com/harrystebbings Follow Jason Lemkin on X: https://x.com/jasonlk Follow Rory O’Driscoll on X: https://x.com/rodriscoll Follow 20VC on Instagram: https://www.instagram.com/20vchq Follow 20VC on TikTok: https://www.tiktok.com/@20vc_tok Visit our Website: https://www.20vc.com Subscribe to our Newsletter: https://www.thetwentyminutevc.com/con... ----------------------------------------------- Legal Disclaimer: The content of this podcast is for informational and entertainment purposes only and does not constitute financial or investment advice. Any discussion of stocks, public markets, or investment strategies reflects the personal opinions of the s

Summary

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At-a-Glance

  • Verdict: Watch fully
  • Core thesis: Cheap, near-frontier Chinese open-weight models are accelerating model commoditization, making routing, trusted inference, domain-specific tuning, and AI infrastructure valuable now while placing long-term pressure on foundation-model pricing and growth.
  • Why it matters: For an operator building agent systems, the discussion connects model choice, security posture, routing, supervision, labeling, custom models, and inference economics into a practical view of where durable control points may sit.
  • Best use: Use it as a strategic market and architecture briefing: pressure-test whether to stay model-agnostic, adopt hosted open-weight models, build workflow-specific evaluation/labeling loops, and avoid overcommitting to a single foundation-model cost curve.

Executive Summary

The panel argues that China releasing Kimi and Qwen near the frontier is less a sudden technical breakthrough than an acceleration of an existing trend: capable models are becoming widely available at dramatically lower cost. They caution against treating social-media evals as proof of parity, but point to OpenRouter data showing roughly half of traffic already passing through Chinese-created models. The central consequence is an expanding demand for “good enough” intelligence at materially lower inference cost.

The practical constraint is trust. The speakers distinguish open-weight from fully open-source models and argue that U.S.-hosted, self-run deployment can technically reduce data-exfiltration risk, but may not satisfy CIOs, regulators, or government buyers. Their expected outcome is not a blanket U.S. ban, but segmented access: Chinese models may remain viable for lower-risk private workloads while being constrained in government and sensitive enterprise settings.

For AI builders, the most useful argument is that generic frontier models increasingly become components rather than complete products. Enterprises will combine expensive models for high-value reasoning, cheaper models for routine tasks, supervisor models for agent control, and proprietary labeled data or “micro-model” layers for workflow-specific quality. The panel’s anecdote is that labeling a recruiting workflow made outputs improve by an order of magnitude.

The investment layer of the discussion is that infrastructure—not applications—currently captures disproportionate revenue and valuation: inference providers such as Fireworks benefit directly from demand for hosted open-weight models, while frontier-model growth remains the macro variable underwriting hyperscaler CapEx. The panel sees model routers like OpenRouter as strategically valuable but vulnerable to being absorbed as a feature by clouds, data platforms, and application vendors.

Key Takeaways

  • Claim: Chinese open-weight models are likely to expand quickly in commercial use because being near-frontier at a much lower cost matters more than winning isolated eval comparisons. | Evidence: The speakers cite OpenRouter data indicating about half of traffic already runs through Chinese-created models; they characterize leading Chinese models as roughly six to nine months behind frontier systems depending on measurement, while estimating an approximately 80% lower-cost opportunity in some deployments. | Implication: Ken should architect agents for replaceable models and continuously evaluate price-performance on actual workflows rather than assume OpenAI or Anthropic is the permanent default. | Caveat: They explicitly reject treating online benchmark screenshots as proof of real-world equivalence, and Kimi's demand spike was so large that the speakers could not access it for direct consumer testing.
  • Claim: Open-weight availability does not eliminate security or policy risk, especially for sensitive enterprise and government workloads. | Evidence: The panel distinguishes open-weight models from full open source: weights may be inspectable and runnable locally, but underlying training data is not available. They cite persistent sovereign-linked cyberattack risk against U.S. technical companies such as Boeing and compare likely policy caution to restrictions placed on Huawei. | Implication: Treat model provenance, hosting jurisdiction, tool permissions, network egress, and auditability as separate controls; do not equate on-prem or U.S. hosting with automatically resolved governance risk. | Caveat: They believe a trusted U.S. inference provider running the model can potentially block tool access and data exfiltration paths sufficiently to satisfy technologists, but that may still not satisfy politicians or risk-averse CIOs.
  • Claim: Agentic deployments can multiply token consumption because regulated workflows require models to supervise other models. | Evidence: Jesse Zhang reportedly shared that token usage among a highly regulated customer segment grew about 2.5x since January; the explanation offered was supervisor models monitoring agents, including multiple agents running in parallel, to reduce costly errors. | Implication: For high-consequence workflows, budget for a layered agent architecture—execution, verification, policy checking, and escalation—rather than assuming one model call per task. | Caveat: This is an anecdotal operating datapoint rather than a general market-wide measurement.
  • Claim: Model routing is strategically important now, but standalone routers may be exposed to feature commoditization. | Evidence: OpenRouter is reportedly exploring a sale while Ramp launched a competing routing product. The panel expects clouds, data platforms, and adjacent vendors such as Databricks to embed model-choice and routing functions into their own stacks. | Implication: Build routing as a control-plane capability, but avoid making a third-party routing layer an irreplaceable dependency; retain portable provider abstractions, policy logic, observability, and fallback paths. | Caveat: A standalone router can still be highly valuable to an acquirer because model agnosticism may help a hyperscaler win enterprise share during the current transition.
  • Claim: Workflow-specific labeling and custom reasoning layers can outperform generic models by a step function, even without training a foundation model from scratch. | Evidence: One speaker described building an agentic recruiting application using Sonnet and Opus, then creating a labeling tool; after labeling examples, outputs became “literally an order of magnitude better.” The panel argues that expert answers to even 20–30 domain questions can materially improve a specialized system. | Implication: Ken should prioritize labeled workflow data, domain-expert feedback, task-specific evals, and a proprietary decision layer before considering expensive foundation-model training. | Caveat: They use “own model” broadly: this may mean a proprietary reasoning layer, rules, weights, retrieval, or fine-tuning built over a foundation model—not necessarily training a large model.
  • Claim: The near-term economic winners remain inference and infrastructure providers, but their margins and capital intensity will be tested as they vertically integrate. | Evidence: Fireworks was described as serving roughly 40 trillion tokens per day, up from 15 trillion, with mid-30% margins and an expectation of expansion as it owns more of the stack. The panel says providers such as Fireworks, Baseten, Fal, and Together benefit from enterprises using hosted open-weight models rather than calling overseas APIs. | Implication: For platform selection, distinguish temporary API economics from the provider's durable capacity, margin, and supply-chain position; lock in portability and benchmark providers before volume becomes material. | Caveat: Owning more of the data-center stack can improve control and margin but turns these firms into much more CapEx-intensive businesses; demand is strong now, but infrastructure can still face compression.
  • Claim: The critical macro risk is whether low-cost open-weight and custom models materially slow OpenAI and Anthropic growth during 2026–27. | Evidence: The panel frames the two foundation-model companies at roughly $100 billion combined revenue and notes that AI infrastructure spending has surged from roughly $150 billion to $700 billion in CapEx. They argue that hyperscaler commitments, NVIDIA expectations, training-data companies, and adjacent supply chains all depend heavily on sustained frontier-model demand growth. | Implication: Avoid strategic assumptions that depend on continuously falling frontier-model prices or unlimited vendor capacity; track foundation-model revenue growth, enterprise substitution behavior, and gross-margin trends as leading indicators. | Caveat: The panel does not claim to know whether open models will cause a meaningful slowdown; it presents this as the central unresolved market question.

Detailed Brief

Foundation-model economics and the missing U.S. low-cost challenger

  • Claims: The panel sees a conspicuous gap: several U.S. firms appear technically capable of making competitive models, yet few are aggressively positioning as low-cost, open-weight alternatives to OpenAI and Anthropic.; They suggest that Chinese providers may benefit from practices such as distillation that U.S. firms may not be able to pursue legally, but they do not establish this as the full explanation.; Frontier labs cannot use classic software-style price warfare freely because inference has real marginal cost, model training must be repaid quickly before obsolescence, and premium valuations presume improving margins.
  • Evidence: Kimi K3 was described as a roughly 2.8 trillion-parameter model requiring substantial GPU capacity, unlike smaller models that can run locally.; The panel contrasts frontier-model consumer subscriptions, which bundle large amounts of usage, with enterprise usage where prices remain less subsidized.; They argue that a frontier lab may be able to offer multiple price tiers, but cannot simply cut prices without confronting physical serving costs and training-cost recovery.
  • Caveats: Most claims about valuations, company revenues, and pricing dynamics are conversational estimates rather than independently validated analysis in the transcript.; A lower-cost open-weight market can expand total AI demand rather than only cannibalize frontier vendors; the net effect remains uncertain.
  • Implications: The durable opportunity may be in a mixed model portfolio rather than in betting exclusively on either frontier APIs or open-weight substitutes.; Price reductions by frontier labs should be treated as a signal of competitive pressure but not automatically as evidence that their economics have broken.

Market structure: M&A, funding, and supply-chain signals

  • Claims: The panel views an OpenRouter sale as plausible because a scarce control-plane asset can be worth more strategically to a hyperscaler than its standalone discounted-cash-flow value would suggest.; It argues that growth-stage AI deals have recently offered better risk-adjusted pricing than early rounds: companies with substantial revenue can trade at lower revenue multiples than fashionable Series A companies with only a few million dollars of ARR.; The panel considers contemporaneous multi-tranche financings at sharply different valuations economically understandable but potentially awkward for cap-table alignment, options, and later exits.; It contrasts the cooperative NVIDIA–TSMC–ASML supply chain with DRAM suppliers that are raising prices aggressively, suggesting that concentrated bottlenecks can create very different economics even within AI infrastructure.
  • Evidence: The reported Stripe/Advent proposal for PayPal is discussed as beginning at a 28% premium, with speakers expecting a negotiation toward the mid-30% range typical of take-private deals.; They cite examples of hot early-stage AI companies raising at $300–500 million valuations with $2–5 million in revenue, compared with later-stage companies around $1–1.5 billion with about $100 million-plus in revenue.; A cited example of a tranche structure is $100 million at a $1 billion valuation plus $300 million at a $5 billion valuation, which the speakers say produces a blended valuation but different investor outcomes.; DRAM suppliers were described as raising prices by roughly 40% per quarter in contrast to the slower, relationship-based price increases attributed to TSMC and ASML.
  • Caveats: The Stripe–PayPal transaction is discussed as a reported, unconfirmed deal process; its structure and outcome were not established in the transcript.; The funding-market observations are investor commentary and should not be generalized into a universal stage-allocation rule.
  • Implications: For acquisitions, value a control plane by the distribution, retention, and switching-cost advantage it gives a platform—not only its direct margin.; For investments or partnerships, separate genuine workflow lock-in from temporary AI-market momentum and be wary of financing structures that optimize headline valuation over long-term stakeholder alignment.

Notable Concepts & Terms

  • Open-weight vs. open-source: The speakers stress that open weights permit self-hosting and inspection of model parameters, but do not necessarily expose training data or provide the full transparency implied by open source.
  • Supervisor models: Additional models used to monitor agent actions, parallel execution, and errors; especially relevant where an agent mistake has regulatory or operational consequences.
  • Model routing: Selecting among models based on cost, quality, latency, policy, or task; presented as an essential but potentially commoditized AI control-plane function.
  • Standalone inference: Third-party serving of models, particularly open-weight systems, through providers such as Fireworks, Baseten, Fal, and Together rather than directly through a frontier lab.
  • Micro-model / proprietary reasoning layer: A workflow-specific layer built from labeling, rules, evaluations, retrieval, tuning, or specialized logic over a general model; the panel sees this as the practical meaning of many companies having their own model.
  • Distillation: A possible source of low-cost model advantage mentioned in the discussion; it is raised as a potentially constrained practice for U.S. companies, not established as the explanation for Chinese model performance.
  • Tranche round: A financing split into multiple investments at different valuations, which can improve headline signaling and capital availability but create uneven investor returns and cap-table complexity.
  • Cross-sectional comparison: The idea that assumptions used to value NVIDIA should also be applied to adjacent AI supply-chain beneficiaries such as memory vendors, because all ultimately depend on the same demand trajectory.

Operator Notes / Why Ken Should Care

  • Create a task-level model policy that routes by sensitivity, required reasoning quality, latency, and unit cost; include explicit fallbacks across at least two providers or hosting modes.
  • For any open-weight model pilot, run a security review covering hosting location, outbound network access, tool-call permissions, prompt/data retention, telemetry, and audit logs before connecting production data.
  • Instrument agent workflows with separate quality and spend metrics for executor, supervisor, and retry calls; token costs can rise nonlinearly once verification is required.
  • Stand up a compact labeling and evaluation loop for one high-value workflow before pursuing model fine-tuning or custom training; measure whether domain examples materially improve task success.
  • Avoid treating a router or inference vendor as the sole strategic moat: preserve a provider-neutral abstraction and retain ownership of routing policies, eval data, and observability.
  • Monitor OpenAI and Anthropic enterprise growth, pricing behavior, and margin signals as external indicators for future model-cost and infrastructure-capacity assumptions.

Source/Metadata

  • Title: Should the US Ban Chinese Open-Source Models | OpenRouter's Chance To Sell | Stripe Buying PayPal
  • Transcript words: 23259
  • Duration seconds: 5259
  • Timestamp note: No usable timestamps or chapter markers were present in the supplied transcript; the transcript also contains substantial repeated passages.

Transcript

16491 words en Processed in 693.6s

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 Atropic a run for the money? So, kicking us off, China ships two near-frontier open models in a week, with Kimi absolutely crushing it. Next, Databricks raising $3 billion, I love this, Series M, at a $188 billion valuation. And then on top of that, we have Ramp releasing an OpenRouter competitor, just as OpenRouter are supposedly about to get bought. This and so much more in the conversation this week. The quest for equivalent models at a cheaper price is just going to keep going up. At some point, the people spending a trillion dollars a year are going to want some apps to pay for all this. 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. Ready to go? Guys, I'm looking forward to this. There has been a lot, as always, going down. I remember when news cycles were so much shorter. I don't know if you remember this, but a 100 million round, and it would be the thing for a week. And now days go by, and you're like, wow, we're forgetting the Stripe and the PayPal, which we'll get to, which is mega. But I'm going to start on the two near-frontier open-weight models that we saw in the last seven days from China. One of them being Kimi, which has got a lot of attention and a lot of press, and then the other being Quen from Alibaba. How significant were the two model announcements that we saw today? And what should we be taking from their seemingly catching up, or close to, the frontier models we have in the West? 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, okay? We're not saying something is similar in performance, maybe. But let's prove it in the field. Having said that, we can't even sign up new consumers for Kimi because it's blocked. They have so much demand since this happened, right? Demand is literally, I don't know whether it's geometric or exponential, but it's so high we can't even, we can't even, we need, we can come back to this next week when it opens up and I can use it on the consumer side even better. But I think 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. It's not new, right? If you look at OpenRouter data, half the traffic's through China-created models. Even China models is a confusing term, right? They may well be hosted in the U.S., right? And when they have open weights, they may be, they may be, for all intents and purposes, truly open-source models hosted in the U.S. But it's not new. It's just going to accelerate this. And that's why you see the stress. It's just accelerating. And that 50%, instead of being niche or for tech-forward folks or venture-backed folks, 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. There wasn't, you kind of led with, what do these new models mean? I think Jason's cut is exactly right. It's exactly what you'd expect. It turns out the five wily and the 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 through and building new models. They're not state of the art compared to the frontier models, but they're six, nine months behind, depending on how you measure it. So, actually, no new news about that. But Jason's right, quite a lot of fun news about how parts of the U.S. responded to that. We had the small-p political response. 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. Jason hinted at it. We lump all these models in together, right? But let's take two. Some of the DeepSeek models you can run on your PC or your Mac or on a laptop, right? Conversely, Kimi K3 is, I think, a 2.8 trillion parameter model. It's a huge honking thing. And you need myriads of GPUs 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, than U.S. frontier models. So we can learn about it. I think we'll talk about the politics first and then maybe, oddly enough, talk about the inference implications, as that goes into the opportunity for fireworks. So, lots 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 along a pretty defined trend. 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. There you go. You keep going. No. No. And then Emil Michael obviously latched onto it. And I'm trying to remember, is it Dean Ball? It's Dean Ball. And he is current, I think, Head of Policy or Communication Director for OpenAI. He just started there two weeks ago. Before that, he was part of the Trump administration, kind of in AI policy. And before that, a bunch of Hoover Institute-type stuff. And 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. Everyone was mean to me because I posted a bunch of stuff. And I think it was, frankly, a little naive, the 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 exaggerated. And then secondly, when you start even hinting about significant regulatory, hinting at regulatory changes that will massively benefit you, you've got to expect that everyone's going to say, dude, of course you're going to say that. No, that's your side. If you make the expensive closed-source product that sells for $10, $20, and the Chinese are shipping something for $2, and you say, well, totally independently, just speaking as a common citizen, I think they should ban this shit, you've got to expect that a whole bunch of people are going to say, dude, you're not talking as a common citizen. You're talking as the provider of the company who will jack up our rates the minute the stuff gets banned. So, it was a little naive not to expect that level of blowback. We'll see. At some level, first of all, I think that guy at OpenAI had been there two weeks, right? Yeah, two weeks. Whether he used that as a reason to go on this or whether— As they say in the meme, Jason, two weeks so far. Yeah, so far. We'll see. Listen, 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. Simply, there's always, in our whole history of tech, the ability of Chinese technology to penetrate many U.S. buyers has been limited, right? It has certainly been limited in telecom and other spaces. So I think the quest— Stepping back for a minute, the real question is how limited is it going to be, right? How limited are we going to— Because it's going to be limited. The availability of China-built models to penetrate the U.S. is going to be limited. The question is just how much. Jesse Zhang had a Twitter article today or yesterday, I think today. Yeah, that was good. And it was pretty good. We'll see. Listen, I'm not a total expert. It's difficult for me to imagine the federal government is 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. Simply, there's always, in our whole history of tech, the ability of Chinese technology to penetrate many U.S. buyers has been limited, right? It has certainly been limited in telecom and other spaces. So I think the quest- Stepping back for a minute, the real question is how limited is it going to be, right? How limited are we going to- Because it's going to be limited. The availability of China-built models to penetrate the U.S. is going to be limited. The question is just how much. 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. Okay. And the reasons are really interesting. I've lived this myself. The reasons are having supervisor models track the agents so the agents don't mistake running multiple agents in parallel, so they don't make mistakes. The more regulated you are, the less forgiving you are of an error in an agent. And so it's 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. It's just going to keep going up. But we've always had cheaper, pretty good solutions from other vendors. It's not new. 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 didn't realize Bill had said that. There's something very pleasing about that, which I'll mention in just a second, right? Because one of the fun things about this policy dispute, it brings out the hater in everybody, right? And Dean Ball said what he said. And then two people who can be controversial came down strongly on the other side, and I support them both. The first was David Sachs, the former AI czar, who basically said, this is rubbish. Stop. Stop. And 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 the guy at the Defense Department who got totally sideways with Antropic. 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. But, yeah, I think there were- And I actually just saw, literally as I came on. And look, this is the Trump administration, so things change every day. But a political league today basically saying some version of, we're not going to ban these things on any significant basis, which, as Jason points out, is very different than saying the White House decision support system will be run on Kimi, right? Even if it's Kimi hosted in California, I think we can take it for granted. It won't be, right? But conversely, if you're a Decagon and you're a startup doing inference on customer support queries for a very boring consumer product, there is no reason why you should pay marquee prices when something 10x cheaper is available. And it would be horribly bad policy to ban that, right? Well, look, the one thing I will just add, and Bill Gurley, another rich, grouchy billionaire. Grouchy Bill Gurley has probably got 30 IQ points on me, okay? And he's seen it all, right? And even at his grouchiest point, I learn something from it, 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. It's already scary how much of our data we put into these closed source models in the U.S. 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 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. I think every CIO is being told right now, oh, don't worry. If you host it 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 on-prem would solve that solution? And 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. Nice, Jeff. No, seriously. 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, in my lifetime of experiences, I'm not confident there is. And just the internet telling the CIO, I don't think, is good enough. And if I were a CIO, it wouldn't be good enough to me as long as 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 took it. I don't know, man. I don't think it's triggering to say that there are IP risks in this. At the risk of being level-headed here, the data is very clear that technically important U.S. companies, Boeing, for example, suffer continual cyber attacks, many of which are attributable to sovereign state actors, including China. It's a thing. So we're not being sensationalist or alarmist. It would be naive not to put it on the table. First comment. Second comment is I do- I'm thinking about can you- The problem with proving a negative is can you know. If you have- And remember, these are open- I occasionally say open source incorrectly. They are open weight, which means you can see the weights 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 weight. The question is, if the model is being run in a trusted U.S. inference company, Base Tan, Fireworks, some of those guys, right? And you can get into a long technical question. Look, what can it really do? Could it initiate tool use on- It probably speaks- Could it initiate tool use on the customer side, whereby the model sends a command back to the customer to exfiltrate their data? You can imagine being able to use these models fairly comfortably and being fairly secure, fairly certain that you have blocked access and this can't happen. So I think you could satisfy a technologist, right, 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? And I think you're right. You have seen things like Huawei has effectively been prevented from selling to any cellular networks in Europe and the U.S. because of this as-yet unprovable fear. So 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, right? But I think the interesting question it raises is this. Well, two questions. You can imagine being able to use these models fairly comfortably and being fairly secure, fairly certain that you have blocked access and this can't happen. So, I think you could satisfy a technologist, right, 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? 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, as-yet unprovable fear. So, 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, right? But I think the interesting question it raises is this. Well, two questions. First of all, it's also worth pointing out that while we're talking about banning Chinese open-weight models, the Chinese administration are talking about preventing those companies from selling those models to the U.S. Just like we don't let them buy NVIDIA, they're not going to let us buy their open-source models, which is 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 that's just weird in and of itself. But I think the really interesting question here, and it gets to thinking machines, is: is the open-source, LLM, open-weight, let's call it 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. If this is, 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. At one point, Meta looked like they were going to go down this route, right? Is there a business, how can you make money, it's an interesting question, can you make money as maybe not completely open-weight, but a low-cost U.S. 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 U.S. 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 U.S.-based. So, I do wonder, Jason, to your exact point, if there is a market for 80% cheaper intelligence, and that's roughly what we're looking at in terms of when you take into account the cost of inference, the difference between the bundled product that is a frontier model, IP plus inference, and an open-source model where you dissociate the IP from the inference cost. If you're looking at an 80% cheaper opportunity and there's mass demand for that, when is someone going to try and fill that demand in the U.S.? I just don't know. I've asked so many people why we don't have leading open models in the U.S., and no one's actually given me an answer. We're still waiting for models from Reflection, which I think is one of the hopes that we have. I completely, I was offered Kimi today, by the way, Rory, at 20 Berlin. This fell into my inbox. I have an SPV for you. Do Kimi 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. But no, look, we're going to gloss by it, and I don't have an answer, but it's a huge freaking question, right? There'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 U.S. that are capable and have proven their ability to build something roughly comparable. None of them are taking advantage of this, and there are 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? As you say, where are you, Thinking Machines? Where are you, Lab? The fact that there are four or five potential companies, it's just fascinating. Rory, are you asking them to dance? I'm asking them to ship. A story, and I'm 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. How did we assess these? I think it's a great time for OpenRouter to sell. I think them leaking the story 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. OpenRouter, like a lot of folks, was early and benefited from it and deserves it, right? This is a repeat founding team that saw that there would be value to having a fairly heterogeneous mix of models that, when we started this pod, probably made no sense at some level. It probably seemed too nerdy and too niche and too cool-cat developer. Who's going to need, yeah, sure. There's a little, it's cool. But guys like Rory and me, we're going to stick to the big guns, right? And everything broke well for them, but it's still a niche product that more and more people are going to build variants of themselves. And is this the plumbing they will pick? If you're on a lot of platforms, if you're on adjacent platforms, if you're using Databricks Gateway, they have their own harness. They'll figure this out for you. They will. I don't know whether Ramp's competitor even makes sense. But 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 check out at five or six billion. It's just because 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. Jason 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? Right? 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? If I'm someone who makes my money as a hyperscaler hosting, especially someone that doesn't have their own 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, 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 it 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. It's going to be compressed. 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 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, 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 it 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. It's going to be compressed. 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. Right? Because it may well be that, and this is a, this is where the finance guys miss it. It may well be that the NPV of the company on a standalone basis is a couple of billion, not huge. But 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 cloud, we are the model agnostic people, we'll make it easy, could be interesting. So I remember thinking, shit, I wish I was in that. 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. So yeah, I'm with you. I think it's an interesting, an interesting time to sell, an interesting time to buy. Rory, if you're on that board, would you sell at $5 to $6 billion? It's always hard to, my first comment is whenever you get an offer, I always do the same thing. I say 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 are 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. And then go away and think about it and have the 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. Because, in the end, 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. Even 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 degrees of freedom. We could come back to that later. 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? But 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 was very VC-centric. Would you sell at six? I can't do the accent. Would you sell at six 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 six 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. It's not worth it for 3x. It is not. Okay. Let's say I own 15% of OpenRouter. 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. 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, 700 million. 3x for you. It doesn't, maybe later in life, it's now 10x and building something. 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, what should I do it for 2.8x on my last, 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. Like going from, again, going from 40,000 in the bank to 400 million versus 800 million. It's irrelevant if there's risk. This is, and sometimes 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. 3x not good enough, man. Got to be 10x. I'm confused. What are you saying? Are you saying to sell at six or are you saying not? Which is odd because- I'm saying if it's financial, sell at six. If the most, if the 18 is not enough, it's got to be 60 to be worth the risk for most founders. It's not enough gain. I understand what he's saying. I understand what he's saying. This isn't clearing the prep stack. This is clearing my life stack. No, no, no. It was weird. I didn't think you were going that direction, but as often happens with you and I listened to the whole thing, I'm like, I get it. I think what he's saying is this, Harry, right? When you face that sell decision, you don't not sell because you think you can make twice as much in a year, right? Because you just never know. 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 to do with your life questions. From a return perspective, don't think incrementally. If you have a chance to sell a company for $6 billion and make $600 million and 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. That's actually good financial advice. I mean, it doesn't, 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 biggerness. I think that's a fair comment. Yeah, if it's 10x, this is my net advice. If it's 10x, if you know in your heart and soul you are building a company 10x bigger than this, right or wrong? Like, I don't know. Then F and say no and go for it. Here's a few more shares, in fact, friends. Let me reload you. But they only invest 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, something that you also, 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. I'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. Go for it. It wasn't where I thought you were going, because I actually thought you were going to say, yeah, something that you also don't sell just because financially you feel you should. 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 my point. You also have to respect that. Again, this gets back to there's no one answer. The founder decides. I'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 bucks. And maybe I could make 120 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 made three or four million in a secondary. I got my house. I'm done. Can I ask more? More my thing here. This is, 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 million valuation. Is there any value in this layer, if it's as commoditized as everyone? 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, 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. 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 decrease rather than it creates. And my gut is, it might be now, that crossover moment. I think Rory kind of made a version of that point. It might be now. 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. 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, but yes. Well, it included feature, and more and more folks will include it. And then you include your function, some version of your functionality, in their product. Right. That's exactly it. Which segues to the next topic. Which is Fireworks. Yeah. And inference in general. Take it away, Rory. I'm going to butcher whatever context that you want to take it on. Oh 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. Fireworks, a leading inference provider, announced their latest round, which was a one-and-a-half-billion-dollar round done by Index, Gavin Baker, Nvidia, Lightspeed, 20VC. Amazing firms. They're incredible. Thank you very much. They're really fucking good. Lin 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. I think the story is inference. Yes, first of all, I agree. Inference is huge. It goes back, ironically, to the prior comment on open-weight models. This standalone inference is a big business, right? And inference is both something that's done within the frontier model companies, where they do their own inference, and people like Microsoft and Google provide the CapEx, provide the compute for that. But people like Fireworks and Base10 and Fal, they all 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. And as I said, the two trends go together. They're exploding because the open-source trend is exploding. So if you're Base10, if you're Fal, if you're Fireworks, if you're Together, this is your market and your moment. So yeah, this is 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. So this is a one-to-one linkage between the open-source, the open-weight trend. These are the companies that are benefiting massively from that trend. And it's not the only kind of route for inference. There are inference for US-based models, et cetera, et cetera. But the vast bulk of it is, oh my God, I'm sourcing Qwen. I'm sourcing Kimi. I'm hosting Qwen, Kimi. I want to use it as Cursor. I want to get someone to provide me some inference. These guys exist. And they have lots of customer SKU at the high end. I believe companies like Cursor are probably big customers of all these guys. At least they were until they were acquired by. Still are. Still are. Probably still are. So yeah, it's great. Candidly, I think it actually goes back to the point I made earlier. There's some businesses where, and I think you can look at it and say, oh my gosh, the cost, you have margin compression in your future because you're buying your compute from the near clouds, and you're offering this product, and now you're 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 near clouds in general, and are starting to build their own, whatever compute you own now, you can charge way more. Which means what looked like a lowish gross margin business has now probably become a very attractive business. So not only are they probably growing 5x to a billion, but they're probably growing 5x to a billion with expanding gross margins. And just to add some details there, Lin 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 just to be clear for people, 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 interesting, and I agree with that sentence. It also means that the challenges I hinted at are there in the future. Because what they're saying is, if I'm buying data center compute and then effectively selling data center compute with hosted LLM, at some point I'm going to want to own my own data center assets to have more control of my destiny, which means vertically integrating downwards, which also means a ton more CapEx. So these are going to become way more CapEx-intensive businesses. There is a risk of commodification here, even with massive complexity and massive CapEx. There is one thread of the Twitterati who has said for a while, all this stuff's interesting, but ultimately the application layer is going to be the most interesting. It's going to benefit from all this. Everything's commodified, right? All the good investments sure seem to be in the infrastructure. Absolutely. Even the ones that look good in software, the numbers pale in computing. And it's not a 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. To put it again, Lin said in the show she expects to double by the end of the year. Totally. Yeah. And that's just a slice of the market. Listen, people have gone all back. When we started the show, it felt like vibe coding applications run amok. Everyone thought you'd replace your sales source. It's going to benefit from all this. Everything's commodified, right? All the good investments sure seem to be in the infrastructure. Absolutely. Even the ones that look good in software, the numbers pale in computing. And it's not a 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. To put it again, Lynn said in the show she expects to double by the end of the year. Totally. Yeah. And that's just a slice of the market. Listen, people have gone all back. When we started the show, it felt like 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. He replaced 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. It'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. You look back and you, what's going on here? You've got companies like Fireworks doing a billion dollars. There are very few apps companies doing that. And, zooming out a million miles, my mental model is, I divide the AI world up into three buckets. It's the making AI, the infrastructure layer, right? And you're right, the spend there is $800, $900 billion a year. Then there's the two foundation model companies themselves, and they're doing plus or minus $100 billion a year, right? And then taking those guys out, rounding up every other apps company, right? 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 200, 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, right? But right now, the volume has 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. There's probably more money being spent on training data for the foundation models, the Merkur, Surge, and that, than pretty much any app company outside of Cursor. In fact, probably the sum of all the apps companies outside of Cursor, right, are probably less than the amount that Anthropic and OpenAI are spending on training data, which is just amazing. That I can guarantee you when you look at Merkur hitting two billion in ARR. Yeah, two billion for Merkur, or Surge, another billion. You get to four or five billion and, you know. Surge is three. Yeah. Handshake's one. I mean. I mean, yeah. Maybe if you start throwing in, on the other side, the consumer products like Higgsfield, you get to roughly the same 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. Lin said in the show the future would be every company having specialized models with their own data. We mentioned Harvey there, who've been building their own models. Jason, I'm just intrigued. In the last week, you spent time labeling data, building your own model through that data. Any lessons, reflections from the last few days labeling data and going through that process that you've been through? I've been building this agentic recruiting app just to recruit from the SaaStr community. It's been fun. I've learned a lot building it, right? Hopefully I can ship in the next week or two. But to really get it great, it needed labeling to make its... Now I'm going to put model in quotes, right? It uses Sonnet and Opus. So there are different definitions of model, and it was good. But man, once I started labeling all of this, it got exponentially better, right? 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. As soon as you're at a certain amount of scale, and it's not cheap all in, right, you are going to want to have your own model, right? Like a Harvey or Cursor. So some version of this, I think, folks that are going to want to use, at any application level, folks that are going to want to use just the generic models, is just going to decline to prototypes, right? Prototypes and proofing. Yeah. Or 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, right? And you're going to want to use the cheap tool for most of the parts, and the customized tool to usage. But man, the outputs are just... Literally an order of magnitude better once you do it. So everyone wants your own model. And so I do think 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 is. Yeah. The 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. Would that change your confidence on the data labeling market? A lot of shade is thrown at it. As an investor in my core, I definitely see it. Does that change how you think about it? Personally, I totally get it. 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? Every 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 Merkur for, 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? And the real question is not that. The real question is, will that be additive to the rough trajectory of the foundation models as it's established today? In other words, coming at or close to 100 billion combined revenue, growing nicely, or does it start to take away significantly? Because, to answer the specific question, if the foundation models continue to grow, and we just saw the article in The 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, JP Morgan building the JP Morgan model on top, then it's net expansive, and net expansive is by definition good, and it reduces customer concentration. And I think that's what people like Merkur are forecasting, right? If, on the other hand, which is hard to contemplate today, these enterprise models, if these open-weight models, really impacted the growth rate of Anthropic and OpenAI, then obviously, when your 80% customer slows down, it would have a significant impact on your growth rate, right? Of course it does, right? If that continues to grow, and you have an additive market in enterprise of all these companies, JP Morgan building the JP Morgan model on top, then it's net expansive, and net expansive is, by definition, good, and it reduces customer concentration. And I think that's what people like Merkur are forecasting, right? If, on the other hand, which is hard to contemplate today, these enterprise models, these open-weight models, really impacted the growth rate of Anthropic and OpenAI, then, obviously, when your 80% customer slows down, it would have a significant impact on your growth rate, right? But if it's any consolation, Harry, if that happens, worrying about your Merkur 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. Can these two foundation models maintain their growth trajectory, which is starting to become profitable, at least in the case of Anthropic, in the face of all this open-weight competition? In the face of this pushback on costs, and it's a 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 2x or 3x growth rate, there's going to be a mad scramble. Betts 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 produce a sustain, does it reduce that growth rate to some 100% within one or two years? Right? And the answer to that question is, I genuinely don't know, and if I did, I'd be trading that stock. Because let me be clear, 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. Because all the hyperscaler RPO, all of it, is a function of the commitments they've gotten from the foundation model companies. And, yes, you can say if the open-weight models explode, there will be a demand for inference. And, yes, you will have this transition from, oh, I sold it to OpenAI, but I should have sold it to, I don't know, 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. I think the tough, the really tough part, it's Captain Obvious, right, is can they afford for it not to? And what I mean is, look at what's happened with Fable this week, okay? Fable went from, you can't use it, it's not secure, then the government lets you use it, then, hey, we're going to turn it off except for variable usage on June, July 15th. Now, it can be 50% of your whole usage for the month. Why did they change when they don't even have enough capacity to serve it? Competition. Right? Competition, right? So, listen, if they price Fable at Sonnet rates, I think they'll own the market. Yes. 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. The 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. 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. But 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, and this is one of the big, and I've seen a bunch of articles on this. 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 use price ruthlessly because there was zero cost of goods sold. And they just bundled the browser in with the operating system, bundled all Office in together, didn't cost them anything, and it just wiped everyone else out. But as you're pointing out here, there are real, even at the margin, even after you'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 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. And if you're valued at 20 times revenues, you better be like Microsoft with 40% operating margins. So when you look at all that, you're right. It's back to the thing I said, you can squint at that and say, ooh, there are 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 other. But the minute that growth rate stops, Jason, to you, 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. That in itself would be a different ballgame. So you are right. Price could solve it, but it would be a painful way to solve it. Yeah. You have to start building your own chips and 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. 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 ChetGTV. 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 fine outside of the consumer. It's not massively bundled and subsidized. Right. That's because you're still. Yeah. You remember the old days in software, Jason, when you had to say, I promise I'm only using this for personal use. You remember that on licensing, right? Well, if you're telling those nice Claude people that you're only using your personal subscription for personal use, they're going to find you, dude. They're going to find you. Well, yeah, it's just Fable is very good. Yes, that's why they're going to find a way to charge for it. Very good. Rory. You were like, are we going to get away from this AI stuff? Yeah. What were you hoping to talk about? Like a vertical dentist company making 500 million for his. Sorry. Sorry. That's an AI story. Oh, isn't it? 587 million. And fun fact, his top three movies paid. Yeah. Didn't add 60 million. And so it's 10 times more than his three highest-grossing movies combined. What would say that inspired than the Batman? Yeah. What are you talking about? For his pay? Like how much he got? He got like $8 million. The amount he made from it, yeah. Context is so funny. I don't want to get distracted. We're like how much had been sold for 500 and some odd million to Netflix, right? That's a good one. Yeah. Very good. Rory. Were you, are we going to get away from this AI stuff? Yeah. What were you hoping to talk about? A vertical dentist company making 500 million for his. Sorry. Sorry. That's an AI story. Oh, isn't it? 587 million. And fun fact, his top three movies paid. Yeah. Didn't add 60 million. And so it's 10 times more than his three highest-grossing movies combined. What would say that inspired than the Batman? Yeah. What are you talking about? For his pay? How much he got? He got $8 million. The amount he made from it. Yeah. Context is so funny. I don't want to get distracted. How much had been sold for 500 and some odd million to Netflix. Right? That's a good one. Yeah. Our jaws drop, and we're arguing whether we should sell a portfolio company for 6 billion. Well, 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. 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. Rory, do you know what? I find that triggering. Oh, look, good on him. No surprise. It turns out you can make more money with capitalism, techno-capitalism, than acting. It turns out Bill Gates is richer than the most famous actor in the world. Right? Yeah. No surprise. All right, Rory. I'm going to listen to you, though. Move away from this AI pure-play discussion. And we're going to move to some big Irish twins. The Stripe and Advent deal to take PayPal private. Does that sound okay? Passes to Rory. I mean, you got to talk about it. We 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 clear as all. I mean, I think it's super interesting in a lot of different ways. One is just a diff. I mean, they both process kind of 1.9, 1.8 trillion dollars a year. Right? And 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 50 bill, 35, hang on. It's about. I thought it was 58 or 60. 50-something billion. Right? And so, yeah. I mean, it's like Stripe taking advantage of PayPal trading at sub-10 times profits and deciding to go for it here. Right? I mean, 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, as I say, the revenue, not the revenue, the payments processed, 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 20, around 30 billion. So it was trading about 1.7 times revenues. So if you look at that five versus 30, I'm like, ooh, it's 5X, PayPal's 5X bigger. But it turns out, on a like-with-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? It 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. Right? It also gives them, and their economics will be amazing. It's a little like the Dell transaction. Obviously, the scary thing is it takes your perfectly wonderful company that's nice and running smoothly and it's a desirable place to work, and all the positives that we all know about Stripe. 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. Then there'll be a lot more pushing and shoving in the future because 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, listen, obviously there's at least a decent synergy here, right? And in a PowerPoint slide, there's a ton of synergy. Plus, you get Venmo, you get a lot of stuff. Yes, you got consumer assets. The thing that is always a head-scratcher to me is blending something that's growing 7%. Because no matter what you say or do, unless you can radically shove those products through your channel, your blended growth rate goes down. What's Stripe growing today? I don't know, 30%, 40%? It's between 20 and 30. So it's not that much bigger, Jason. That's why... But seven... Okay, hold on. Rory, you're better at math than me. But if I take 30 and seven, that's 37, and divide by two, I'm only growing like 18% now. I've fallen below the Mendoza line of 20% growth at scale. There's no such thing as a Mendoza line for growth at $5 billion and above because you can get out, right? I mean, I think the real point is... But to take that point... 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 going to have to recognize some of this revenue, right? As a joint venture, right? So it's going to decelerate their growth. It's not stress-free. Plus, you have the operational need. Plus, even all the layoffs they're going to do, that alone may not reaccelerate 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 that 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? As crazy as it sounds, you actually figure that part out. And the answer is, you don't fix it. You fix it over five years, or you have an LLM lift. But the real answer is you don't fix a lot of these things that seem like you can't rationalize 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-run company for the last decade and a half in Stripe. And you have another company that 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 opportunity. So, yes. I mean, the interesting thing is normally this is kind of... To the public... Normally, this is the kind of deal you do after you go public because you have the market cap and you just price the deal. And I was thinking, my first glance was, oh, it's probably a lot harder to do this as a private company because you can't issue $50 billion of stock, right? 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. revolving door of executives and is a real mess. And they've dissipated their opportunity. So, yes. The interesting thing is normally this is... To the public... Normally, this is the kind of deal you do after you go public because you have the market cap, and you just price the deal. And I was thinking, my first glance was, oh, it's probably a lot harder to do this as a private company because you can't issue $50 billion of stock, right? 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, at least yet. And so 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, right? And so, yeah. Will this happen? I will still argue that it's actually getting done. I don't know. I think it happens. I think it does. I think it does too. No. 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, right? 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 probably not, it's like you probably breach your fiduciary duty if you make your... You have to offer whatever. You have to have another five or 10% to put into the deal. So it's a dance. They're going to accept it. It's a bunch of mercenaries and a brand new CEO who's probably going to make nine figures for 10 or 12 months of work. By rejecting it, it means they're going to accept it. I think Jason could well be right. I hinted this earlier. When you're a private company, remember we talked about the sale, Harry. When you're a private company, you can decide not to sell for any reason. When you're a public company, what the bankers are telling them right now is, you're right. First thing you do is instantly reject because you got to look strong. And then you've just hired bankers, and they're going to say to you, and the lawyers in particular are going to come in the room and they're going to say to you, Delaware law, you can only turn this down if you have good business judgment belief that on a standalone basis, you can do better than this offer in a reasonable period of time. So even as we speak, the PayPal team are building a three-year model, a five-year model, trying to prove that they're going to be amazing, and therefore this bid is too low and they are comfortable in the risk of turning it down. But what's going to happen is this. They'll be able to make a model because they have smart people, and the banks are smart people, and the NPV will be wonderful because the banks will make it that way. But the pushback will be, well, guys, if you were so fucking smart, why didn't you fix it in the last five years? And then you're sitting there as a board member going, am I really sure that this guy can turn it around? Do I believe if I got an extra 10% or 15%, would I say risk-adjusted I should take it? And as Jason pointed out, I don't know the CEO from Adam, but he's sitting there going, bird in the hand versus slogging at PayPal, being the third CEO in a row trying to turn this thing around. At some point, if Stripe wants to own this thing, you're kicking a little more in, and you probably will own this thing. I think it's hard to have the stomach unless you can see, maybe, 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. In other words, I have an internal, there's probably five key internal metrics that matter, take rate, new merchants per quarter, usage of wallets, whatever it is. If those numbers are already starting to turn because the new CEO is doing an amazing job, then maybe the board can say, I will extend that trend. I will say, hey, look, the last two quarters have been 10% better each quarter. If you extend that trend for five more quarters, it's an amazing company, worth twice as much, let's turn it down. If those trends are still flat, and it's the new CEO's plan might start working next quarter, then it's really hard to say as an independent board member, you're getting 300 grand a year in RSUs. Do you really want to be a hero here? Or do you want to, as Jason said, say no, negotiate for 15%, discharge or reduce your obligation, and take the money? Yeah, they can, for certainly the argument would be the stock price is depressed, they're missing it, right? It's down from its lows. And they 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-thirties. Now, average does not control any deal, but that is the perfect amount of back and forth, 28 to 35. It's already prescripted. Yes. It's already prescripted. And the bankers will charge a couple hundred million bucks for the... Yeah. How are we going to get from 28 to the... 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. And 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. Now, sometimes it materializes. Rory has been through this. But usually if there is another offer, the offer already soft happened. They've already had discussions at the whatever media summit or whatever. And so there probably ain't. So it's probably just a dance from 28 to 35. And then it gets parked with ADVENT while they figure out antitrust and capital issues. So Stripe finally, the 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. Yes. They're coming back through the back door. Yeah. They're getting the old gang back together. So for listeners who may not know it, one of the very early Stripe rounds, I know Peter Thiel was an investor. There were a 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. The first time you move into the headquarters, you'll probably say, can I come along? You probably bring the Collisons and say, hey guys, if you're doing the victory lap on the PayPal headquarters, can you include me on that trip? 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. So what did I miss that you wanted to cover, Rory? Maybe the better comment, I will say that maybe the better comment is not, there's more to life. I've been thinking about this a lot, actually. In one sense, I want to say there's more to life than talking about OpenAI and Entropic, because there are only two of 2000 interesting companies. On the other hand, as you would be the first to point out, cap-weighted, in other words, weighted by dollar, there are two trillion of five or six trillion of privately held market value. So on a cap-weighted basis, we should be talking 30 to 40% of our time on OpenAI and Entropic, boring as it is, if you are kind of So I gave you no AI. And then you were like, you missed topics. So what, what did I miss that you wanted to cover? Rory. Maybe the better comment, I will say that maybe the better comment is not, there's more to life. I've been thinking about this a lot, actually. In one sense, I want to say there's more to life than talking about OpenAI 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, there are two trillion of five or six trillion of privately held market value. So on a cap-weighted basis, we should be talking 30 to 40% of our time on OpenAI and Entropic, boring as it is, if you are trying to be representative of private tech. So I hear you, Harry. It's hard not to, but I just don't want to be totally boring. I thought that the other fun things, and the odd thing about, you had a list of other companies to talk about, and in a weird way, every single one of them is a company that's being pulled by this trend. You had Valor Atomics down there to talk about new technologies and nuclear. Then you had 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 when you actually get to trying to talk about something that's not AI, I ain't got shit. Exactly. And then data breaks rockets to 188. Why? To buy GPUs. Sully. No, 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 your 401k at an all-time high is dependent. Right? But I did think it was interesting. So one thing that I do find interesting is another one, but it's emergent AI coding startup, 120 million in ARR, raised 130 million in Series C at a 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. I think it's just a very interesting market analysis today of where is a good insertion point for investors. Oh, it's true. And it's risk-adjusted always now. We did factory at the one and a half round. And I think, yes, that was a worse deal than the 300 round. But the 300 round, they had next to no customers, very little product-market fit. And well done to those investors. They saw what a lot of other people didn't. But risk-adjusted, shit, 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, 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, we talked about the history show, there is real multiple compression, even in the hottest agentic folks at scale, right? There's real revenue multiple compression. There's plenty of folks compressing to 10x revenues, right? Which is even far less than forward revenues, right? Maybe an 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, at Series A, that gap, you better have seed investor skills at the Series B or the math's going to be tough with that, right? There's a lot of pressure on the picket. That's just what I think it is below the growth stage. And so be it, that's the game, right? But that's how I think about it. And it's harder, it's, it's, it's, you don't really want to be a picker. You want to be a pricer. 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 2 billion by the end of this year at 17 and a half billion? You're paying less than 10x revenue. It depends. We're always 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 elastinthropic round. But for most of us without unlimited capital, if you can pick better earlier, you'll end up owning more. It does pay off. That extra 3 to 4x isn't terrible. That extra 3 to 4x on the way to the billion-dollar round, it's not a terrible problem. I just don't think many 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 objective. In many cases, it's just priced by the company one way or the other. And you're either in the round or you're not, right? And on top of that, I'm worried, you can forgive me for going off on this ramp, but Brandon at McCaw has mouthed off, and I say that nicely, but mouthed off on Twitter about Sequoia's tranche rounds. 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. Yes, but, but, but, but those, it was a multi-story car park. Those two things go together, right? That tranche comment goes together with your prior comment, right? Which is, I'm going to paraphrase it. It's like doing classic early-stage seed AB investing is really hard because prices are high and you've got some really talented firms. So to win, you got to have differential access, differential picking, and you're going to be competing in every deal. Conversely, Harry is saying, I look at these companies at one and a half billion. They're doing a couple of hundred million in revenue. Yeah, 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? Yeah. 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, right? Because those kinds of deals at one, two, and three billion have been subsequently marked up a lot. And I think you're entirely correct, right? I mean, I shared the statistic before. We looked at every, I mean, if you look at all the unicorns that were minted in Q1 or Q2 of 2025, by the end of Q2, 26, at least 40% of them will have had a subsequent markup. In other words, good things get more good things. We've been in the momentum side of the marketplace. So late-stage, that kind of growth investing, to your point now, and the reason you've been doing it, it's been a very good place to play. And I think you 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 three 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 26, at least 40% of them will have had a subsequent markup. In other words, good things get more good things. We've been in the momentum side of the marketplace. So late stage, that kind of growth investing, to your point now, and the reason you've been doing it, it's been a very good place to play. And I think you 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 three billion. 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. So what's happening is people are realizing everyone wants these growth rounds, and this is how these trends end. They're going, oh, everyone wants these growth rounds, so now what we can do is do this tranche structure and effectively price the excess return away from Harry and back to us. So yes, because it's been such a good place to play, capital's rushing in. At some point, it won't be a good place to play. But you are correct. 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? And 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 longer than you've been alive, Harry, 30 years. The truth is early should have a higher overall return multiple than mid than late, because otherwise 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 go, oh, wow. A combination of increasing equity valuations and a new trend means from 2022 on, late stage was amazingly good. Absolutely. Yes, I completely agree. Obviously, if you are in the best early stage film, 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. I agree. Totally agree. And I don't think we're saying anything different, to be clear. I think that, yes, 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, it's two things. The later you go, logically, the less dispersion you should have, the more bounded the thing. But on top of that, you have also this phenomenon, which is you go late. At certain periods in the marketplace, you get this kind of equity rising tide perspective, which carries everything. Right. And look, 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. I wonder if I was a founder, if I would really do contemporaneously tranched rounds. I don't know that I would. Is it not a good deal for them? I think I would feel like, I 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 one billion and another five 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. Don't get me wrong. If I'm raising 100 at a billion and 500 at five billion in the same 24 hours, I have to say yes to that as a founder, right? Because I can't raise 500 at a 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 seemed to de-stress my life. Always just not taking that last nickel off the table always made me worry about one less thing. And maybe, 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 there was a lot more transactional, sadly. It is. It is. And I've rolled with it. I've rolled with it, but I don't know that I would do it. 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 every founder is wildly smart and they can calculate a blend, 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 point something billion. These people are doing advanced AI. They can do simple fricking math, right? The interesting question is, is there anything in those terms that subsequently bites you in the ass as a founder? And this gets to your point, Jason, which is you can, if you don't care about the one, you're effectively raising money in that example at 2 point something billion, right? 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. I don't think anybody cares. And I think it's liberating for founders, but I don't think anybody cares anymore. 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 of my other VCs to fund competitors. Agreed. No, I agree. Look, if you're optimizing for bragging rights, it optimizes bragging rights. It's generally the kind of thing that looks like a really good idea in a good market. And then the real question is, are the consequences horrific in a bad market? And I will say they're silly, but they're not horrific. If you look at that versus other alternatives, like taking a high price but with a ton of structure, real structure, that's a worse mistake. If you look at not raising money, taking out a ton of debt, that's a bigger mistake. So in the litany of mistakes that you can make with your cap table, doing a two-tranche round that makes all your second-tranche people feel like second-class citizens, it's not the worst thing in the world, provided you don't give a damn that they're second-class citizens. And clearly you don't. Is there anything else we should cover, boys? Is there another story here that I've missed that I should cover? Yeah, it's further afield, but I did spend a second on the... What's interesting is that there is just continued progress on nuclear energy, lots of risk, 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. So it's interesting, they're still private. But what's really funny, I did realize one weird comment. I had two weird... One word comment on this was, if you think about the kind of companies that should be private and the kind of companies 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, and they're trading like Yeah, it's further afield, but I did spend a second on the... what's interesting is that there is just continued progress on nuclear energy, lots of risk, 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. So it's interesting, they're still private. But what's really funny, I did realize one weird comment. I had two weird... One word comment on this was, if you think about the companies that should be private and the 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, 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 Databricks should probably be public. As yet, here we are with Databricks and Stripe private. Databricks doing a Series M, Stripe doing some kind of acquisition that's convoluted, which are typically both public company stages. And then you got a whole bunch of these, not Valor, but the other 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. There's nothing to say except weird. Series M. The one, one, this, it's minor. If I had to let the phone in, it's so minor, but the C-square IPO is just mildly interesting as a footnote. Can you just give some context, Jason? What is C-squared? What's happening? It's a data center. Yeah. So they're a C-tier data center, leveraging AI. They're doing a billion-dollar run rate, growing 16%, right? And they IPO'd with a $3 billion market cap. So if you reach this slow growth and you put a veneer and a wrap around it, it's still growing at a billion in revenue and you're trading at, I need to know the enterprise value, not the nominal. It's probably lower, right? The enterprise value. You got to figure out the debt. It's higher because they'll probably have debt too. Oh, higher. Yeah, you're right. But I mean, this is meh. Maybe 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. 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 public, but not, I mean, older assets, not as compelling. Agreed. The counterargument to so many things, but yeah, these other assets can IPO. I guess you finally get to a billion in revenue with a bit of an AI veneer and you're worth three times that. I guess it's okay, but it's not why I'd want to be a founder. You got to go, you got to make it, you have to deliver. You guys done any deals in the last seven days? Not in the last seven days. No, sir. No. I do want to come back to the one other thing that really struck me 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. NVIDIA is now TSMC's largest customer. And there's tensions because they're pushing TSMC to invest more. But they're managing that. And then the same kind of relation, TSMC and ASML. ASML makes the machine that enables TSMC. And TSMC makes the wafers that makes NVIDIA. And no one in that entire supply chain has ruthlessly gouged each other. ASML has raised prices gently. TSMC has raised prices gently. They're pushing people for forward commits. And it's a real, hey, we know we're going to be dealing with each other for 10, 20 more years, trusted relationships. How do we cooperate for the long term? 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, right? And there, the dynamic is totally different. It's like, screw you, we're raising prices 40% this quarter. Oh, next quarter, you still need our stuff, raising another 40%, right? It's just hilarious to watch. I mean, you see these huge large, 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 literally adjacent supply chains benefiting from the same kind of broad trends on AI. And one of them is just a super long-term-oriented one with single player at every level. And just once you get to three players, it's just brutal. So fun to watch. 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. And when that, 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. Paul Weaver is just depressed for a long-ass time, huh? Yeah. Well, partly, one of the things no one ever says is the fact that memory prices are 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, obviously, they have the big OpenAI 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, gravity takes over and you start thinking, what is this company? It's still, I think, attractively valued on a sales multiple basis. I don't understand why Kimmy and why the open models don't make NVIDIA a little bit more elevated. I mean, Jesus, I'm 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. NVIDIA got this massive step up over the last three years, the ChatGPT step-up to plus or minus 200 bucks a share, right? And if you look at their projections for the next two or three years, they're basically saying, CapEx, which exploded from $150 billion to $700 billion, growing much more slowly over the next three to four years. So it's basically, we had a one-off step up, and now it's going to continue, but not amazing growth, right? And one of three things is going to happen. If CapEx stays elevated but doesn't double and double again, the 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 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. He said, I think it was something, a cross-sectional comparison. I can't remember the exact phrase. He was basically saying, whatever assumptions you make to value Nvidia about the future of two rounding error, you should make much more slowly over the next three to four years. So it's, we had a one-off step up, and now it's going to continue, but not amazing growth, right? And one of three things is going to happen 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 next acceleration, Harry. And if there's any kind of slowdown, then even this valuation will look crazy. And it's in that middle until you get a signal either way. I think Gavin Baker had a very interesting term. He said, I think it was something, a cross-sectional comparison. I can't remember the exact phrase. He was saying, whatever assumptions you make to value Nvidia about the future to rounding error, you should make roughly the same assumptions in valuing the DRAM providers, in valuing all the other beneficiaries of that, right? And I think 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. And all those guys like SanDisk popped up in the last 12 months, when Nvidia, as you say, plus or minus has been in that 180 to 210 range. And now everyone's at the level that says, okay, let's see the next card. Going back to this first sentence, the only thing that matters is the OpenAI and Anthropic growth rate in 26 and 27. I love that as a way to finish. What we did miss, though, Jason, from this episode? We missed a Shakespeare quote from Rory. Do you remember last week Rory came out with a quote? No, no, we have to do it. You don't have one for us to make? It wasn't Shakespeare, I think. It wasn't Shakespeare. No, no, it was another intellect. Rory, you got anything from the Odyssey? That would be great. You got a good idea. I need a good one for the Odyssey. No, I'm actually just really looking forward to seeing it, you know? But my guess is this is engineered. They made a 28% premium offer. The average take private like this is in the mid thirties. Now average does not control any deal, but that is the perfect amount of back and forth 28 to 35. It's already prescripted. Yes. It's already prescripted. And the bankers will charge a couple hundred million bucks for the. Yeah. How are we going to get from 28 to the, 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. Um, and they'll, 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. Now some may, sometimes it materializes. Rory can, has been through this, but, but usually if there are another offered the offer already soft happened, like they've already been discussions at, uh, you know, at, um, at the whatever media summit or whatever. And so there probably ain't. So it's probably just a dance from 28 to 35. And then it gets parked with advent to, while they figure out antitrust in, uh, capital issues. So, so Stripe finally, the powder one finally becomes the Jedi. Stripe takes over PayPal. It's just a matter of time. And it lands where, where it should have been. And all the early PayPal guys that did the pre-seed along with, uh, Sam Altman's 2%, they're going to do pretty well in the end. Totally. Yes. They're coming back through the back door. Yeah. They're getting the old gang back together. So for, for, for, for, for, for listeners who may not know it, one of the, the very early Stripe rounds, I know Peter Thiel was an investor. Some, I was a 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, you're one of those investors, you know, the first time you move into the headquarters, you'll probably say, can I come along? You probably bring the Collison's and say, Hey guys, if you're doing the victory lap on the PayPal headquarters, can, can you include me in on that trip? Now, Rory, I want to hand the ball over to you because you, you, you said no more AI. So I gave you no AI. And then you were like, you missed topics. So what, what did I miss that you wanted to cover? Rory. Maybe the better comment, I will say that maybe the better comment is not, there's more to life. I mean, I've been thinking about this a lot, actually. In one sense, I want to say there's more to life than talking about OpenAI and Entropic, because there are only two of 2000 interesting companies. On the other hand, as you would be the first to point out, cap-weighted, in other words, weighted by dollar, there are two trillion of five or six trillion of privately held market value. So on a cap-weighted basis, we should be talking 30 to 40% of our time on OpenAI and Entropic, boring as it is, if you are kind of trying to be representative of private tech. So I hear you, Harry. It's hard not to, but I just don't want to be totally boring. I mean, I thought that the other fun things, and 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 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 when you actually get to trying to talk about something that's not AI, I ain't got shit. Exactly. And then data breaks rockets to 188. Why? To buy GPUs. Sully. No, 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. Right? But I did think it was interesting. So one thing that I do find interesting is like another one, but it's like emergent AI coding startup, 120 million in ARR, raised 130 million in series C at a 1.5 billion post money 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. I think it's just a very interesting market analysis today of where is a good insertion point for investors. Oh, it's true. And it's like risk adjusted always now. Like we did factory at the one and a half round. And I think, yes, that was a worse deal than the 300 round. But the 300 round, they had next to no customers, very little product market fit. And well done to those investors. They saw what a lot of other people didn't. But risk adjusted, shit, 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, we talked about the history show, there is real multiple compression, even in the hottest agentic folks at scale, right? There's real revenue, multiple compression. There's plenty of folks compressing to 10x revenues, right? Which is even far less than forward revenues, right? I mean, maybe unhelpful comment. I think the real pressure is it means anything below that growth stage, you better be a damn good picker. Because it used to be, it used to be when Rory and I met, Series B, even into Series A, you actually didn't have to be a good picker. You just had to be good at math and good at assessing the team. The picking wasn't so hard as it looked, it was all the rest. Now, a series, that gap, you better be like, you have seed investor skills at the Series B or the math's going to be tough with that, right? It just, there's a lot of pressure on the picket. That's just what I think it is below the growth stage. And so be it, that's the game, right? But you just, that's how I think about it. And it's harder, you know, it's, it's, it's, you don't really want to be a picker. You want to be a pricer. 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 2 billion by the end of this year at 17 and a half billion? You're paying less than 10x revenue. Want to, it depends, I mean, we're always 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 elastinthropic round. But for most of us without unlimited capital, you know, if you, if you can pick better earlier, you end up, you'll end up owning more. It does pay off. That extra three to 4x isn't terrible. That extra three to 4x on the way to the, to the, to the billion dollar round. It's not, it's not a terrible problem. I just don't think many 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, but it is true. And, and the, the change that the, that the biggest brands will pay the highest price in many cases is, is, is makes that in between round tough, right? At least the growth round is sort of object, like it is just, in many cases, just priced by the company one way or the other. And you either, you either in the round or you're not right. And, and, and you know what, on top of that, I'm worried you can forgive me for going off on this ramp, but you know, Brandon at McCaw has mouthed off, uh, and I say that nicely, uh, but mouthed off on Twitter about Sequoia's tranch rounds. I think it's brilliant marketing for Sequoia. Honestly, I would have retweeted it, but the amount of tranch rounds I see, I saw around the other day with four tranches. Yes. But, but, but, but those, it was a multi-story car park. Those two things go together, right? That, that tranche comment goes together with your prior comment, right? Which is, I'm going to paraphrase it. It's like doing classic early stage, see AB investing is really hard because prices are high and you've got some really talented firms. So to win, you got to have differential access, differential picking, and you got on this, you're going to be competing in every deal. Conversely, Harry is saying, I'd look at these companies at one and a half billion. They're doing a couple of hundred million in revenue. Yeah. That on an absolute basis, they're expensive, but on a relative multiple basis, they feel a little cheap. That's what you just said, correct? Yeah. 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, right? Because those kinds of deals at one, two, and three billion have been subsequently marked up a lot. And I think you're entirely correct, right? I mean, I shared the statistic before. We looked at every, I mean, if you look at all the unicorns that were minted in Q1 or Q2 of 2025, by the end of Q2, 26, at least 40% of them will have had a subsequent markup. In other words, good things get more good things. We've been in the momentum side of the marketplace. So late stage, that kind of growth investing to your point now, and the reason you've been doing it, it's been a very good place to play. And I think you 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 three 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. So what's happening is people are realizing everyone wants these growth rounds, and this is how these trends end. They're going, oh, everyone wants these growth rounds, so now what we can do is do this tranche structure and effectively price the excess return away from Harry and back to us. So yes, because it's been such a good place to play that capital's rushing in. At some point, it won't be a good place to play. But you are correct. 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? And 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, like logically, over the long term, over the long term, and by long term, I mean longer than you've been alive, Harry, 30 years. The truth is early should have a higher overall return multiple than mid than late, because otherwise 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. A combination of increasing equity valuations and a new trend means from 2022 on, late stage was amazingly good. Absolutely. Yes, I completely agree. Obviously, if you are in the best early stage film, 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. I agree. Totally agree. And I don't think we're saying anything different, to be clear. I think that, yes, 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. The later you go, logically, the less dispersion you should have, the more bounded the thing. But on top of that, you have also this phenomenon, which is you go late. At certain periods in the marketplace, you get this kind of equity rising tide perspective, which carries everything. Right. And look, 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. I wonder if I was a founder, if I would really do contemporaneously tranched rounds. I don't know that I would. Is it not a good deal for them? I think I would feel like, I mean, I might do it in the moment. I think we're all caught up in the moment. I don't know that I'd be comfortable charging one investor, one billion and another five 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. Don't get me wrong. If I'm raising 100 at a billion and 500 at five billion in the same 24 hours, I have to say yes to that as a founder, right? Because of, you know, I can't, I can't raise 500 at a billion, but if it's, if it's, if it's, if it's all some sort of aesthetic, I don't know. I, I, I, maybe, maybe I'm a fuddy duddy. I just want my investors to make money and I, and I want my investors to get, uh, not under, not, I don't want them to rip me off, but, uh, you know, 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, and maybe, and I just don't know why I would do it. I don't know if I would do four, four different prices in one week. I just think there was a lot more transactional, sadly. It is. It is. And I, and I've rolled with it. I I've rolled with it, but I don't know that I would do it. I, I, I'm kind of with Jason for the record. I think, I think you're right, Harry. The world is a lot more transactional. It, it leaves me with an icky feeling and the real, and it is all aesthetics because, you know, every founder is wildly smart and they can calculate a blend, a blended pre money. If it's, you know, a hundred million at 1 billion and 300 million at 5 billion, they can calculate that the effect of pre money is 2 point something billion. These people are doing advanced AI. They can do simple fricking that, right? The interesting question is, is there anything in those, I mean, I'll tell you what I think. Is there anything in those terms that subsequently bites you in the ass as a founder? And this gets to your point, Jason, which is you can, you know, if you don't care about the one, you know, some, you know, you're effectively raising money in that example, at 2 point something billion, right? 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, you know. I don't think anybody, I don't think anybody cares. And I think it's liberating for founders, but I don't think anybody cares anymore. You better make damn sure you have a drag along. And you know. 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 of my other VCs to fund competitors. Agreed. No, I agree. Look, it has, 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. And then the real question is, are the consequences horrific in a bad market? And I will say they're silly, but they're not horrific. I mean, if you look at that versus other alternatives, like taking a high price, but with a ton of structure, real structure, that's a worse mistake. If you look at it, not raising money, taking out a ton of debt, that's a bigger mistake. So 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. 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? Yeah, it's kind of further afield, but I mean, I did spend a second on the... I mean, what's interesting is that there is just continued progress on nuclear energy, lots of risk, 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. So it's interesting, they're still private. But what's really funny, I did realize one weird comment. I had two weird... One word comment on this was, if you think about the kind of companies that should be private and the kind of companies 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, 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. As yet, here we are with Databricks and Stripe private. Databricks doing a Series M, Stripe doing some kind of acquisition that's kind of convoluted, which are typically both 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. Series M. You know, the one, one, this, it's minor. If I had to let the phone in, just, it's so minor, but the C-square IPO is just mildly interesting as a footnote. Can you just give some context, Jason? What is C-squared? What's happening? It's a data center. Yeah. So they're a C-tier data center, leveraging AI. They're doing a billion dollar run rate growing 16%, right? And they IPO'd with a $3 billion market cap. So if you kind of reach this slow growth and a, and you put a veneer and a wrap around it, it's still growing at a billion in revenue and you're trading at, I mean, I need to know the enterprise value, not the nominal. It's 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. But I mean, this is meh. Maybe 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. You know, the counter argument to so many things, but yeah, these other assets can IPO. I mean, I guess, I guess you finally get to a billion in revenue with a bit of an AI veneer and you're worth three times that. I mean, I guess it's okay, but it's not why I'd want to be a founder. You got to go, you got to make it, you have to deliver. You guys done any deals in the last seven days? Not in the last seven days. No, sir. No. I do want to come back to the one other thing that really struck me 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. NVIDIA is now TSMC's largest customer. And you know, there's tensions because they're pushing TSMC to invest more. But they're managing that. And then the same kind of relation, TSMC and ASML. ASML makes the machine that enables TSMC. And TSMC makes the wafers that makes NVIDIA. And no one in that entire supply chain has ruthlessly gouged each other. ASML has raised prices gently. TSMC has raised prices gently. They're pushing people for forward commits. And it's a real, hey, we know we're going to be dealing with each other for 10, 20 more years, trusted relationships. How do we cooperate for the long-term? 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, right? And there, the dynamic is totally different. It's like, screw you, we're raising prices 40% this quarter. Oh, next quarter, you still need our stuff, raising another 40%, right? It's just hilarious to watch. I mean, you see these huge large, I mean, TSMC and ASML kind of thinking long-term, how do we position ourselves so that we're great and cooperative for the next decade or two decades, right? All the memory guys are like, this is a commodity business. You all screwed us three years ago. We're going to screw you now for every dime we can. We're going to raise prices on you every quarter. We're going to make 80% operating margins in what Harry would call a commodity because we know that two years from now, you're going to screw us. And it's just super fun to watch because they're like literally adjacent supply chains benefiting from the same kind of broad trends on AI. And one of them is just a super long-term oriented one with single player at every level. And just once you get to three players, it's just brutal. So 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. And when that, 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. Paul Weaver is just depressed for a long-ass time, huh? Yeah. I mean, well, partly, I mean, one of the things no one ever says is the fact that memory prices are 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, 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 kind of gravity takes over and you start thinking, what is this company? It's still, I think, attractively valued on a sales multiple basis. I don't understand why Kimmy and why the open models don't make NVIDIA a little bit more elevated. I mean, Jesus, I'm like just looking at my NVIDIA position going, how long are you going 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, right? And if you look at their projections for the next two or three years, they're basically saying, CapEx, which exploded from $150 billion to $700 billion, growing much more slowly over the next three to four years. So it's basically, we had a one-off step up, and now it's going to continue, but not amazing growth, right? And one of three things going to happen 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 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. He said, I think it was something a cross-sectional comparison. I can't remember the exact phrase. He was basically saying, whatever assumptions you make to value Nvidia about the future of two rounding error, you should make roughly the same assumptions in valuing the DRAM providers, in valuing all the other beneficiaries of that, right? And I think 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. And all those guys like SanDisk kind of popped up in the last 12 months, when Nvidia, as you say, plus or minus has been in that kind of 180 to 210 range. And now everyone's at the level that says, okay, let's see the next card. Going back to this first sentence, the only thing that matters is the open AI and anthropic growth rate in 26 and 27. 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? No, no, we have to do it. You don't have one for us to make? It wasn't Shakespeare, I think. It wasn't Shakespeare. No, no, it was another intellect. Rory, you got anything from the Odyssey? That would be great. You got a good idea. I need a good one for the Odyssey. No, I'm actually just really looking forward to seeing it, you know?