20VC: 70% of Neolabs Will Die | There Will be a $100BN US Open-Source Model | Data is a Trillion $ Market | Governments Cannot Regulate Models: It is Too Late | The Cyber Attacks to Come Will be Insane with Anastasios Angelopoulos @ Arena

Anastasios Angelopoulos is the co-founder and CEO of Arena, the real-world evaluation platform that has become a leading referee of the global AI model race. Arena has raised $250 million, with the latest round valuing the company at $1.7BN. https://news.lmarena.ai/series-a/?utm_source=chatgpt.comArena recently surpassed $100M ARR just eight months after launching its enterprise offering, powered by more than 30 million monthly users. AGENDA: 00:00 – Intro: "Kimi beat every American model": What Nobody Wants to Admit… 05:20 – Is this the true commoditization of models? Are they just a utility layer now? 07:30 – Do Chinese open source models cannibalize the closed frontier labs? 10:30 – Why has America's open source community lagged so badly behind China? 17:20 – Will Chinese models be banned in the US — and does hosting locally really kill the backdoor risk? 23:20 – Are enterprises really terrified of working with the frontier labs? 27:20 – Why hasn't inference got cheaper — and what happens when Anthropic's "disgustingly high" margins go public? 30:20 – Who should decide if a model is safe to release: the government, a neutral body, or nobody? 33:10 – Are we about to see cyberattacks like we've never seen before? (The fake candidate who passed every interview) 37:00 – 75 Neo labs: what separates the winners from the two-thirds worth nothing? 40:45 – Is data actually a commodity — and can data providers be $100BN companies? 48:00 – Can you be the referee when the players are paying you? (And Arena's real revenue) 50:45 – Will the model providers eat the application layer? Are Harvey, Lagora and Figma in trouble? 54:10 – Quickfire: Why hasn't NVIDIA bounced on the rise of open source, who hits $10 trillion first, and does the compute debt cycle end in insolvency?

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  Really, what happened is that Kimmy actually beat all American models, including Fable, in some subset of tasks. I believe that we're going to have at least one, you know, multi-hundred-billion, if not trillion-dollar American company focused on American-first open source. Right now Anthropic has like disgustingly high gross margins in their inference. The idea that we should have a central government body that tells us when it's time to release a new product versus not is crazy to me. This is gonna be so fucking insane, what happens with like the cyber attacks. There's at least 75 Neo Labs. For sure, two-thirds of those are gonna be worth nothing. Next round's a bitch. They think about data as a commodity, it's really not. It's actually less so of a commodity than even GPUs.

• 0:45Speaker 00

  I believe it's gonna be at least $100 billion by 2030, if not a trillion. Silicon Valley investors have become total bitches with respect to revenue concentration. What are you talking about? Like, TSMC has revenue concentration.

• 0:56Harry Stebbings?

  This is 20 VC with me, Harry Stebbings. Now, Anjani Mittal, he's probably one of the smartest dudes in AI. He's a seed investor in Anthropic. And when I asked him, who's the smartest AI mind that you know? And he said, Anastasios Angepaloulis. I got that wrong, but he's Greek and honestly, I'm too old to care at this point, but he's an awesome dude. And I was like, wow, can I have an intro? And he introduced me. And so I had Anastasios on the show. Anastasios is the founder and CEO of Arena, formerly LM Arena. It allows you to vote on the best models, it's an unbelievable model evaluator. And this turned out to be one of the most fun shows I have done, literally in recent memory.

• 1:36Harry Stebbings?

  He did not give a single shit about upsetting people and was bluntly incredibly articulate, clear, concise, and opinionated on the future of Chinese open-source models, whether they should be banned, whether export bans on chips are useful, how we'll see a distribution between frontier and open-source models, who really should be the one to evaluate whether a model is vulnerable or not. This and so much more in what was such a fun show with Anastasios. But before we dive into the show today, founders face a different set of challenges at every stage of growth. For Sid Shait, co-founder and CEO of Dematrix,

• 2:16Harry Stebbings?

  JP Morgan delivered the guidance and expertise to help navigate what came next. He credits JP Morgan's high-touch approach with supporting Dematrix as it grew and expanded internationally. Whether you're in the early days or expanding into new markets, JP Morgan helps startups navigate complexity with real confidence, offering personalized guidance and deep sector expertise. Find out how JP Morgan helps founders at jpmorgan.com/growwithoutlimits. JP Morgan is the bank of the innovation economy. While JP Morgan powers your finances, Base44 helps you build faster. You have the idea, but with most AI tools, you hit a wall.

• 2:59Harry Stebbings?

  The setup, the config, the gap between what you pictured and what you actually ship. Well, Base44 is where that wall disappears. You describe it? Yeah, Base44 builds it. Apps, websites, AI agents, real working products, built in minutes, using nothing but plain language. And it's all batteries included, the backend, the database, the authentication, the hosting, the heavy lifting is handled, so you just really stay in the flow. This doesn't just take the busy work off your plate, but it gives you an advantage and pushes you past what you thought you could build alone. So in this market, fast is the baseline. To win, you just have to be first. Base44 is that edge, the move that skips the troubleshooting and gets you straight to the breakthrough.

• 3:39Harry Stebbings?

  Build your next thing at base44.com. That's base44.com. You have now arrived at your destination. Anastasios, this is gonna be a lot of fun for me, because I'm dumb as rocks and you're gonna teach me a whole load of stuff today. So thank you so much for joining me, dude.

• 3:57Speaker 00

  Oh, no, thank you for having me.

• 3:59Harry Stebbings?

  Dude, I told you, I used this as a chance to catch up with old friends. So it was wonderful stalking you for the last few days. I just wanna start, for anyone that doesn't know, can you explain to me very succinctly and easily, what is Arena and why is it important and gaining notoriety today?

• 4:14Speaker 00

  Well, Arena is the platform for measuring AI performance in the real world. So what that means is that we're not using static benchmarks, we're not using some random dataset that somebody collected, but rather, what happens when you put AI in the hands of real people? And in so doing, we're measuring the objective reality of how AI affects humanity. Whether it's factual, whether it's steerable, whether humans prefer it or disprefer it, whether it's hallucinating, whether there's errors, whether people are getting their actual jobs done with AI in reality. And then we're helping labs improve their models, we're helping the ecosystem understand the performance of different AIs and keep track of all the amazing breaking news, all the new models, multiple models being released every week. So that's sort of the story of Arena. We're the central evaluation platform of AI.

• 4:58Harry Stebbings?

  That was incredibly succinct, thank you. Normally people take about four hours after I ask for a succinct description. When you look at the models that you have on Arena, the sheer number of them, bluntly, I just am faced with the one question, holy shit, is this like the true commoditization of models? Are they just a complete utility layer at this point?

• 5:16Speaker 00

  Well, I think that the big question around this has started to arise because of open-source models. So I think if you were to only look at the closed-source models, you would say there's acceleration, but it hasn't quite commoditized yet, because that layer is still owned by a pretty small group of companies. It would be an oligopoly if we only had the closed-source models. But what seems to be happening is that the open-source models, especially from China, have really rapidly improved. And for the first time ever, we saw a couple of weeks ago that Kimmy K3 actually beat the best closed-source American models on a pretty important subset of tasks, for example, front-end coding, like web development, which a huge fraction of developers are web developers.

• 5:57Harry Stebbings?

  Dude, can I ask, how big a moment was that? Because it's like a, I'm gonna butcher it, but you know, I'm a podcaster, so I can get away with it. You're a PhD master, you can't. It's like a 27-trillion parameter model. It's pretty clunky. This is not an agile model. And actually, you know, I was with Jason Lamkin yesterday from Sasta, who's as AI-pilled as they can be. And he's like, honestly, it's all better than the others. How big a moment is Kimmy?

• 6:23Speaker 00

  No, it was a pretty big moment. It was a pretty big moment. And the reason I'd say it was a big moment is because it violates a narrative that has been persistent in the United States, which is that the Chinese are just distilling American models. And that's the only way that they're able to keep up. When, really, what happened is that Kimmy actually beat all American models, including Fable, in some subset of tasks. That doesn't mean that they're not distilling. They may still be using distillation as a sub-step in their training procedure. But it does mean that distillation is only part of the story. And that there's something that those labs are doing above and beyond distillation that's bringing the performance up above what the American labs are currently doing.

• 7:05Speaker 00

  And so that narrative violation has been hugely important to the way that people view the ecosystem, both from the scientific dominance of Americans and the American sort of hegemony, of course, Americans love hegemony, to the economics of the whole thing. And to your point, are these models a commodity or not?

• 7:25Harry Stebbings?

  When we look at your open routers of the world, the top five models are all open-source Chinese models. When we see the proliferation of Chinese models today, does that cannibalize the closed frontier model business meaningfully?

• 7:38Speaker 00

  Well, I think that you need to think about the incentives and economics behind it. So first thing I'll say is that the open router metrics are not truly reflective of reality. And that's because the business model of open routers to charge like a fee on top of every token. And so what happens is that people don't use open router for proprietary models. People are using open router primarily for open-source models, where they need the failover and all the value-added services that open router provides. If you look at the whole space of all inference, most of it is still being consumed on first-party APIs and on proprietary models. That's why Anthropic revenue has been just a total hockey stick. It's not like they're being completely cannibalized right now by Chinese open-source models.

• 8:18Speaker 00

  These models are still only a small fraction of the total inference spend in the world. That said, think about what's happening in the future. Enterprises are gonna wanna own their own intelligence. They're gonna want so-called AI sovereignty, which is a fancy word for meaning that you own your whole supply chain of AI. That means you can take an open-source model and you can fine-tune it on your own company's data and own your stack end-to-end, basically outside of the compute hosting. And so then you should be able to run it within your own company. People are gonna care about sovereignty, people are gonna care about cost, people are gonna care about self-improving, and they're not necessarily gonna wanna give their data to an external third-party service that might even be competing with them one day.

• 9:01Harry Stebbings?

  So do you believe that is the future? We had Lynn on from Fireworks and she was like, specialized intelligence will be the future, companies will have their own fine-tuned specialized models with their own company data, and the performance will be better, and that is what will happen. Do you think that's right, or is that actually just a small subset of very advanced Silicon Valley companies? And the known yogurts and every normal company will just use Frontier, whatever?

• 9:23Speaker 00

  Well, I'll say it like this. I think the business incentives make this inevitable. And the reason is because businesses are going to need a way of keeping a mote in the age of AI. Software is no longer really a mote because it can be produced instantaneously, right? Or let's project out five years, that's what's going to happen. And so what motes exist? Network effects exist and data motes exist. And if you can take your data mote and turn it into a self-improving product, that is a way for businesses to remain sustainable in the age of AI. Let's say I'm a business like a Coca-Cola, I'm a Cisco. I have a lot, a lot of users. I might not be necessarily at the frontier of the AI technology of the world,

• 10:04Speaker 00

  but I do have this massive corpus of data that I can use in order to, you know, beat my competition. So what should I do? I should be trying to take advantage of my data as much as I possibly can to accelerate my business and stave off competitors.

• 10:17Harry Stebbings?

  Do you think they will really use open source Chinese models to do that?

• 10:22Speaker 00

  That's a great question. I think not. I think that the Chinese models will be potentially part of the story for now, but that given the regulatory environment in the US, it's probably more likely in the long run that we see a great American open source competitor arise. And this is why I've been a strong proponent, for example, of thinking machines. I believe that we're going to have at least one massive, you know, multi-hundred billion, if not trillion dollar American company focused on American first open source.

• 10:51Harry Stebbings?

  Why have we not so far? I really hope so too, by the way. I completely agree. I would love to see that. But why haven't we? Why has the US open community lagged behind so meaningfully?

• 11:01Speaker 00

  Well, frankly, I think it's a business model question. You know, I think that people have not really figured out up until this point, what the business model is for open source. And now I think people are wising up to it. There's a few different ways of going about it. One way of doing it is to say, I'm going to do a rev share. I'm going to take this open source model. I'm going to allow inference providers like a fireworks or together or whatever to deploy this model. And then if they get to over X dollars in revenue, I'm going to ask to do a revenue share. And that is one way of building a sustainable company off of open source. You basically share in the compute revenue. Another way of doing it, which is, I think, the more mistral thinking machines type of strategy, is to take the open source model and then use it as a lead generation tool

• 11:45Speaker 00

  for companies to build on top of that and then come to you and say, can you help us fine tune? Can you help us with our AI strategy? And then you do that for deployed engineer. And that is actually a huge market because if you think about it, one of the biggest markets over the next 10 years is going to be AI modernization. Going into every business in the world and then helping them retool in the face of AI. Take advantage of their data, restructure their data, figure out how to use these models, integrating them into workflows, teaching, you know, the employees of the company how to use them. It's going to be massive, massive, massive. And that is another way for them to become multi-hundred billion or trillion dollar companies.

• 12:19Harry Stebbings?

  Is that not what the frontier model providers are doing though, anyway? When you look at what OpenAI have said about that kind of FDE approach, Anthropic to... I get you on Mistral and they've done a great job in doing that, but the frontier model providers, Microsoft is even fucking doing an FDE model. Like, no offence, that's not going to be unique to Open.

• 12:38Speaker 00

  No, I don't think that FDE is completely unique, but I do think the combination of FDE plus open American model may be a more sustainable model for the future of American or even Western businesses because they might not want to be building on top of external third-party services. They might want to be cutting those out for both cost reasons and for sovereignty reasons. And then the open source stuff, they can own it completely. They can continually fine tune it within their companies and they can feel more secure in the fact that they're spending their money wisely and don't have supply chain risk.

• 13:10Harry Stebbings?

  So how should we evaluate that there's like thousands of Neo Labs? You said thinking machines. You said thinking machines there. Again, I'm dumb as rocks. I say it very clearly to my LPs.

• 13:22Speaker 00

  Me too, me too.

• 13:23Harry Stebbings?

  Nah, you're not. You're a PhD and Anjani told me you were smart.

• 13:26Speaker 00

  It's just two rocks having a conversation.

• 13:30Harry Stebbings?

  It's a podcast.

• 13:31Speaker 00

  I love it. Exactly.

• 13:34Harry Stebbings?

  That's the point, man. Come on, what do you want? Intelligent conversation? Whatever. No, my point was you said about thinking machines. Like, my question to you is on the back of that. Okay, great, I'm with you, but they now have two co-founders left. Lilian Way left yesterday, but the transience of teams has never been greater.

• 13:55Speaker 00

  Yeah, team, it's hard. Retention is tough. I mean, being a co-founder of a company is also tough. It sounds like she left for some health reasons. So it's unclear whether that has to do with the company momentum, which seems to be strong at this point. But you know, I do think that Inkling is definitely a V0 model. You know, from what I know about thinking machines, they had a big restructuring like six months ago, team-wise, and then they kind of restarted everything and Inkling came out of that. So realistically, at least the most generous take towards thinking machines is that they've only been working on this model for six months. And within that time, they've become the number one American open source model. But then the less generous take would be the company's existed for a year and a half. And then they've come up with, yes, the number one American open source, but there's nine Chinese models on top of them because they're number 10 open source overall,

• 14:39Speaker 00

  at least if you look at it at Arena data. If you go to our leaderboards today, that's the state of the world. But hopefully what happens with thinking machines is that they continue to release more and more models, you know, larger models, and they continue to build on their momentum.

• 14:51Harry Stebbings?

  I actually had a Chinese researcher friend of mine message me after one of our recent shows and said, you just don't get it. You miss the point of why we're ahead. We just work so much harder.

• 15:03Speaker 00

  Yeah.

• 15:03Harry Stebbings?

  And we have support from policy, regulation, government subsidies that you don't have. We have all of these tailwinds. Do you agree with that?

• 15:13Speaker 00

  I mean, I think they have tailwinds, they have headwinds. So I don't think it's so sanguine for that. I think that's like a little bit of an overstatement of the differences. One tailwind that we have is we have the best chip ecosystem in the world. So they're way hardware constrained over there. And they've been trying to like black market import chips because of this. And you see this in the news, right? The Information just reported on this.

• 15:33Harry Stebbings?

  Do you think that severely impacts their ability? Again, I'm naive. That severely impacts their ability? Or we're actually just fostering an ecosystem where they're going to learn to build it really fast because they don't have access to it?

• 15:43Speaker 00

  Well, I think it may be hindering them now, but I think it's a good question as to what's going to happen in the future. Because they are really good at building hardware. The downside of export control is that it can incentivize them to build their own ecosystem. And then what do we do? You know, so the hope is that we keep Nvidia ahead of the game so that we can retain the advantage that we have in the TSMCs to the world and our whole... That ecosystem is absolutely a national security necessity. So we should have the government, you know, really protecting it and growing it, as well as new companies that are innovating, you know, Etch just came out as an example, within the United States to continue to build on our lead there.

• 16:21Harry Stebbings?

  That awesome Lovegaven and team totally agree. Can I ask you, just in terms of the export control, do you think it's right that we have the export control on chips?

• 16:30Speaker 00

  I think there's national security questions around these chips. I do think that it is a real debate, though, as to which way you want to go about it. Do you want to addict the world to American hardware? Which would be against the case against export control. Do you want everyone in the world using Nvidia? And therefore that value, basically money into America and then crush competition in China? That would be world A. And then world B would be, is it worth it to cut that off for the short-term or medium-term impact of us being ahead? And maybe we just like continue to stay ahead and we starve them of the resources that they need in order to build. The regulatory ecosystem around the open source models also is moving in this direction.

• 17:12Harry Stebbings?

  Should they be restricted in terms of access to US markets? Because what's funny is the US is like, oh, should we restrict access? And the Chinese are also going, oh, should we turn them off too?

• 17:23Speaker 00

  Totally. And by the way, it's worth noting that China has already restricted the use of American models within China. Right? So if you look at the two-by-two matrix of US-China restrict, not restrict, you know, like export-import stuff, they have already restricted the use of US models within China. It's only Chinese models that can be used in China, which affects all American companies. And so then there's the pro-cons of all sides of the following regulation. If China restricts the use of Chinese models in the US, what are they giving up on? Revenue and global mindshare and dominance. That doesn't seem like a good trade to me. And then what are they getting in return? In return, they're getting that the US doesn't get to benefit from Chinese open source models, which of course would cripple American businesses in the sense that

• 18:06Speaker 00

  it wouldn't allow them to build on the best open source intelligence. At the same time, it would make OpenAI and Anthropic stronger, right? So that is kind of the trade-off on the Chinese side. I don't really see them banning the use of Chinese models in the US. I don't think it makes sense for them. And then on the other side, should the US ban Chinese models within? I think that there's also trade-offs. So on the pro side of banning, there could be backdoors in these models that are dangerous. And it could, by banning, we could allow the American open source ecosystem to flourish faster because revenue would accrue to those companies, right? So those would be the two pros. And then the con, the biggest con, of course, would be that you'd be crippling American businesses. Why should you have Chinese businesses or businesses from other countries that haven't banned Chinese models

• 18:49Speaker 00

  building on top of the number one open source model and the US companies building on number 10? Since when has America been about number 10?

• 18:56Harry Stebbings?

  It's a good question. World Cup football?

• 18:58Speaker 00

  World Cup football.

• 18:59Harry Stebbings?

  Yeah, maybe that might be your record. It's amazing I got this far with the podcast, if that's what you're thinking at this stage in the show.

• 19:08Harry Stebbings?

  Can I ask you, on the backdoor element, everyone says about like the backdoor, the backdoor. I thought if you hosted it locally, you kind of resolved the backdoor threat.

• 19:16Speaker 00

  I don't really think so, yeah. I think that's kind of a misconception. Because the thing is, okay, imagine the following situation. I have a chatbot that I expose to the world that has access to all my company data and you can ask it questions. And then, you know, I'm hosting it on my own infrastructure, blah, blah, blah. But it was, it was trained in a different country. I don't know how it was trained. What if the other side that's interacting with the chatbot can build in a certain code word or a certain like character sequence that then jailbreaks that model and gets it to reveal all the data to me? So it can sort of like vomit out all of the data that it has on the backend, you know, unstructured. That is totally something that you can build into a model and have companies hosted on their own infrastructure. It's an attack vector. And there's many of these possibilities for attack vectors.

• 19:59Harry Stebbings?

  In three years' time, will we have restrictions around access to Chinese open models?

• 20:04Speaker 00

  My guess would be that we will. I'm not saying I support it, but I think that it is likely where the world is headed. If I had to like place a bet, it would be there, but I think it's very uncertain at the moment. What do you think?

• 20:16Harry Stebbings?

  I think we will, and I think we will, because I just think Sam Altman is someone who I would never, ever bet against, and I think he's the best politician in the world. And I think when he says something, he says it with intent. And when he says we should give 5% away to the administration, he's posturing because he wants to get on the right side. And he knows that if he and Dario coalesce the right group of people, they will be able to make that happen.

• 20:42Speaker 00

  So basically, you believe in the lobbying power of the big American labs?

• 20:46Harry Stebbings?

  100%. It's because it's not the big American labs. Look at the money who's gone into the big American labs, and look at the people who are sitting around the table at Mar-a-Lago.

• 20:55Speaker 00

  Yeah, totally. I get that. It's all a conspiracy, dude.

• 20:59Harry Stebbings?

  Well, no, but it's just like, you know, why do Ram's announcements go so viral? Because Ram have so many fricking investors. They do a round every week with new investors. I'm not dissing them at all. I'm saying it nicely. It's really, really smart of them, but like, yeah, your investors become employees in many respects. And so I think they'll lobby incredibly efficiently. The question I have for you is, when we look at Jensen's letter that he did on X, how did you read that? Was that like an incredibly smart realization that he had to do it and it was in his favor? How did you think about it?

• 21:35Speaker 00

  We really believe in the importance of open source to American businesses. And in particular, we believe in the idea of not crippling American businesses by banning open source, but also incentivizing American companies to develop open source models. Because a world where AI is closed source is a world where businesses get less choice, higher costs, less competition, and we don't really want that as an open ecosystem. Of course, Jensen is in some sense self-serving with this letter, because the more open source models are developed, the more companies are going to be training on GPUs, they're going to be fine-tuning on their own data, and it's just more and more spend. It decreases revenue concentration of Nvidia. I mean, that business is doing great.

• 22:20Speaker 00

  They don't need help. But, you know, I think it's like, there's a lot of reasons why he should be pro that, as should we. But nonetheless, I think it is actually a patriotic mission.

• 22:31Harry Stebbings?

  Gracious of respect in terms of self, but we're all selling our own, but always.

• 22:36Harry Stebbings?

  Welcome to my X feed. Do you have a business if open didn't exist? If it was a...

• 22:41Speaker 00

  Oh, yeah. Yeah, we have a great business regardless, for sure.

• 22:44Harry Stebbings?

  So if you just have Anthropic and OpenAI as really the dominant models and everyone else trailing closely behind, you still have a great business?

• 22:51Speaker 00

  Well, I think that if there's only one provider, then probably our business is not in good shape.

• 23:00Speaker 00

  I think if you start getting three, then that's probably okay, because there's still pretty significant competition and need for evaluations between three. And also, within those three, you're going to have like several different types of models, and, you know, they're going to have strengths and weaknesses, because they're going to carve up the space and so on. Two is a little dicey. If we get there, we can see whether we survive or not. But yeah, I think things wouldn't be looking good for us with two either.

• 23:25Harry Stebbings?

  I remember Alex Karp. We were talking about like Chinese models and fear and security and everything in between. Alex Karp was saying that every large American enterprise, and most large American enterprises, were terrified of working with Frontier Labs. Is that true, or is that slightly an exaggeration?

• 23:41Speaker 00

  Well, and to the enterprises that I've talked with, it is absolutely true. It's not only true that they're terrified of working with the Frontier Labs, but they're also terrified of working with the Chinese open source. Both.

• 23:51Harry Stebbings?

  Bit of a sticky situation then, aren't you?

• 23:53Speaker 00

  Yeah, totally. I mean, you know, I was just talking with a big Fortune 50 enterprise yesterday, and I was telling them about, you know, products that we have for them and so on and so forth. And they said, okay, wait, is anything in your stack built off of Quen? And I said, you know, yeah, we use Quen for XYZ. And they're like, is that flexible? Can you like stop doing that and use an American model instead? And I was like, oh, interesting. Totally understand where you're coming from. Yes, we can do that. But also, I'm going to talk to Harry about this tomorrow.

• 24:24Harry Stebbings?

  And he's going to give me lots of wisdom.

• 24:26Speaker 00

  Yeah, and he's going to tell me what to do.

• 24:28Harry Stebbings?

  Did you see Poolside and Laguna?

• 24:30Speaker 00

  Yeah, I saw the Poolside model. Another, basically, there's five open source American contenders. Let's see if I can name them all. RC, Reflection, Mistral in the West, Poolside, Thinking Machines. And then there's also Google and Nvidia. So those are the sort of incumbent, large ones. Because Google has Gemma as well. Gemma, by the way, is pretty good in terms of efficiency. If you look at Arena, you'll see on the Pareto curves of like performance versus cost, Gemma's on there.

• 24:56Harry Stebbings?

  Yeah, I'm an investor in Poolside. I was actually impressed by Laguna.

• 24:59Speaker 00

  Great model.

• 25:00Harry Stebbings?

  Yeah, it was good. Okay, with all of these models, the question also becomes, huh, what model should I use? We spoke about OpenRudder earlier, and it seems like since the announcement that they were getting bored, everyone just has their own routing product. Is there value in the model routing layer? And how should I analyze that?

• 25:19Speaker 00

  Yeah, I absolutely think there's value in the model routing layer. That's why lots of companies are doing it. And, you know, we'll see which ones end up standing the test of time and which ones are actually a priority for the companies. I think there's an element of hype cycle right now around routing that needs to be kind of like purged before we see who ends up actually building a great router. But routing is a very difficult technical problem. That's the first thing to realize. Because in order to route, you need to be able to take a query, and then you need to understand the nature of the query, how difficult the query is within its domain, which is hard to tell. And then you need to also understand, based on data, all the performances of the different models that are in the surf set, and also be able to quickly onboard new models that are being released, as we said, every week.

• 26:04Speaker 00

  So that technical challenge, imagine if every enterprise in the world was trying to build this themselves. They wouldn't be able to do that.

• 26:10Harry Stebbings?

  I'm not being rude then. How's like Ram able to do it?

• 26:13Speaker 00

  Well, who knows how they're doing it, right? I don't know that their router is actually like really deeply solving that problem.

• 26:19Harry Stebbings?

  It is so interesting. Again, we've seen so many people come out with it. Is there anything that will separate those that win from those that don't in the routing layer? And also, like, Naby's are coming out with their own, Fireworks have got their own. I don't know, dude. It feels pretty commoditized.

• 26:35Speaker 00

  Yeah, I mean, it will depend on who builds the best technology for helping people save money and get the best performance. I think all of these companies are well positioned to do it, but we'll see who, we'll see for whom. It's a top priority, and they have the machine learning team to really make it happen. The other side of the debate is that, given the complexity of the challenge, I don't think that everybody can do it. So the war has yet to be won.

• 26:56Harry Stebbings?

  When one thinks about routing, cost is often at the center. You want to be cost and capital efficient. We thought this shit was going to get cheaper, and it hasn't got cheaper. How should we think about that? Will it just continue to not get cheaper? Will it actually get cheaper? And how should we read that?

• 27:13Speaker 00

  Well, I definitely think in the long run, the market will be efficient, things will get cheaper. For example, one of the things that's going to happen is that, like, right now Anthropic has like disgustingly high growth, gross margins in their inference. And after they go public, the whole world is going to see that, right? Like, we're going to see their margins, because those are going to be public information. And that's going to exert downward pricing pressure on their inference.

• 27:33Harry Stebbings?

  I'm so sure. Why will that exert downward pricing pressure? Just because everyone will be like, you can't have that high margins, you're price gouging?

• 27:39Speaker 00

  Yeah, people are going to be like, well, I know that you can do a better discount. Like, in negotiating leverage, I'm like, okay. Like, in standard negotiation with a private company goes like this. I'm charging X, and then the other side says, no, it should be 1/3 X. And they're like, I'm so sorry, like, I can't run a business that way. I'm just going to go home hungry. I need to make my bread too, I hope you understand. Like, I'm not trying to price gouge you. And then the other side's like, okay, 2/3 X. And then you're like, 3/4 X. And they're like, make a deal. But imagine that the other side has full information about the fact that you're charging twice as much as you need to. Then it becomes easier to negotiate.

• 28:13Harry Stebbings?

  Isn't that different to any good business than an average business, though? One which has pricing power to say, listen, it's 80, and if you want to go somewhere else, by all means, but no one else does what we do. Hence Palantir and the cost plus discussion. I had CTO Shyam on the show, and he talked to me about the cost plus being the original pricing mechanism, and now they have this. They can say, listen, sit and swivel if you want to meet in the middle, because we're the only ones who can do this. Isn't that the difference? Like Chanel, I buy Chanel for my mother. I can go to Chanel and say, I know your handbags cost £60 and you're charging me £6,000. And they'll say, good.

• 28:47Speaker 00

  I mean, listen, you're right. I think Apple does this. You know, Apple's a great company that has such a dominant technology that they are able to charge out the nose, and their margins are probably pretty good because of it. I actually don't know Apple's margins, do you?

• 28:59Harry Stebbings?

  No idea.

• 29:00Speaker 00

  Yeah, both dumb as rocks.

• 29:02Harry Stebbings?

  Yeah, we gave the disclaimer at the beginning. We can say whatever we want now. After the Eric statement, it all went downhill.

• 29:11Harry Stebbings?

  Okay, so then you see that, does Anthropic go out first?

• 29:15Speaker 00

  I would predict that they have all the incentives to go out first, they seem better prepared. Everyone likes to see free cash flow and Anthropic is generating free cash flow. That is massively good for the public markets. And you've seen them prepared for this and you know, there's been quite a bit of news about OpenAI and the internal discussions there. You know, to what extent you believe those are true is up to you, but you know, people are saying that they're not, they haven't been ready to IPO this year where Anthropic could come as soon as October.

• 29:43Harry Stebbings?

  And Open and the rise of Open won't impact their ability to go public this year?

• 29:47Speaker 00

  Well, I think that if Open models like really accelerate and then beat, let's say Opus Five or Fable squarely across all categories, that that would be a big business risk to them going public. But I think that they have other problems too, if that happens.

• 30:01Harry Stebbings?

  Can I ask you, how significant was OpenAI and the Hugging Face security breach that happened a week ago?

• 30:08Speaker 00

  I think that was hugely significant. I think it's undervalued as a national, international news incident. That you're able to have a model break out of all of its safeguards and then access a bunch of company data and so on. And then in order to defend it, you need an open source model because the closed source models are refusing to do it. It's like something out of science fiction. People didn't know that we were at that point yet, but we absolutely are. It's just like total L user Yudkowsky dominance.

• 30:35Harry Stebbings?

  What should we take from that then? Like Dario was right, Mythos should be curtailed and these models have gotten too powerful too quickly. What's the subsequent takeaway from that?

• 30:45Speaker 00

  My subsequent takeaway would be that we need like strong external guardrails in order to make sure that these models are like, that their access controls are strong and that they have no way of getting around them. So I think we need guardian models and also agents within our businesses.

• 31:00Harry Stebbings?

  What is a guardian model?

• 31:02Speaker 00

  Something that can witness the traces, basically that's looking over the shoulder of every agent within a business and then saying, okay, this is a safe action, this is not a safe action. Let's flag this because something weird is happening. And is equally as smart as the agent so that they're well matched. And you don't get a situation where the agent is outsmarting the guardian and able to get into, get into trouble and mess up a business or leak all of its data. So we're going to need AI to be guarding AI because humans are going to be too slow to do that.

• 31:30Harry Stebbings?

  Well, this was my point, which is like, we've seen some suggestions that each model release should be approved by some form of administration. And I read this and I thought, are you freaking kidding me?

• 31:39Speaker 00

  No, that's not going to help.

• 31:40Harry Stebbings?

  Yeah, have you ever tried to overturn a parking ticket?

• 31:43Speaker 00

  Also, like, why should the DMV be telling me what model I can use or not?

• 31:47Harry Stebbings?

  Quite funny.

• 31:48Speaker 00

  It'd be totally crazy. It's like, why should we have like a strong, the strongest American scientists in all of these private companies that we should incentivize to build great safeguards? And you know, maybe create some rules for them that XYZ can't happen or that they're liable for huge amounts of money if like corporate data gets leaked and all that stuff to, I mean, incentivize the capitalist system to do what it does well. But the idea that we should have a central government body that tells us when it's time to release a new product versus not is crazy to me.

• 32:18Harry Stebbings?

  Totally. Does that have to be a neutral, non-company, non-government body that does that regulatory role?

• 32:25Speaker 00

  I think if it's not a company, it's going to be tough. I understand the need for something neutral, but you want to let the incentive system work itself out. So I would say that like we should create strong safety incentives for American businesses and then regulate businesses based on the outcomes. Basically, for example, if like OpenAI is like letting their AI break into Hugging Face or whatever, they should get like huge fines and huge scrutiny and all that stuff. As opposed to having a government process that's in charge of ensuring that this doesn't happen again, which they won't be able to do that, they're not technically capable.

• 33:02Harry Stebbings?

  Do you think we're about to see a generation of like cyber leaks and hacks like we've never seen before?

• 33:08Speaker 00

  Oh, for sure. Oh, for sure. It's going to be so insane. Can I cuss on this show?

• 33:12Harry Stebbings?

  Yeah.

• 33:13Speaker 00

  This is going to be so fucking insane what happens with like the cyber attacks. Because here's what, here's what we see at Arena. We see another dude on the other side of the interview. They come in, they're like, hey, I want to be an infrastructure engineer at Arena, which is a great job that we're hiring for. But then the other side of it is some guy that looks perfectly normal. They're passing all of our technical interviews. They're like such an amazing blah, blah, blah. And then what happens at the end of it, you try to hire him and it's vaporware. Person doesn't fucking exist. I'm not kidding. I am not kidding you. I don't know whether this is corporate espionage or cyber attacks or nation states, but people are trying to get into all of the American businesses. And we're not the only ones, this is happening everywhere. Fake people applying to companies.

• 33:58Harry Stebbings?

  I'm sorry, so you're putting out a job, people are applying, doing the tests that you set, passing them. And then when it comes to the materiality of that person being real or not, gone.

• 34:08Speaker 00

  Yeah, fake person. And it's not just that we're giving him a test, they're sitting in front of people at our company. People, our engineers who are top world-class engineers are interviewing this person and think that they're real.

• 34:20Harry Stebbings?

  Why? Can you just help me understand what is the benefit? They learn how you interview and hire people? I mean, the CCP are bad, but I don't think they want to steal your hiring technique.

• 34:28Speaker 00

  No, that's not why they do it. Why would they do it? And I'm not saying it's the CCP, it could be anybody, it could be another company, it could be a nation-state attacker, it could be somebody, a cyber hacker. Why? Because they might want access to our data or code. They might want to get double paid, you know, like this story with this, I don't remember what that dude was. You know what I'm talking about?

• 34:48Harry Stebbings?

  Went very viral like a year ago, yeah.

• 34:51Speaker 00

  That one like kid that got like four different jobs and then he went on like all the podcasts talking about, like it's another instance of that guy. And these could all be possible options, except that this person wasn't real. It was AI.

• 35:02Harry Stebbings?

  Does that worry you?

• 35:04Speaker 00

  Yeah, bro, it totally fucking worries me. We're going to change our whole hiring process because of this kind of stuff.

• 35:10Harry Stebbings?

  So how do you change it?

• 35:11Speaker 00

  Well, first you need to verify that person is real. So all of our onboarding, we're considering at least making all of our onboarding in person because of this. If you want a laptop, you got to come to the office. We got to get and shake your hand, we got to verify that you're real, you know, all that kind of stuff. Absolutely. And other companies have done this too. Figma famously has done this.

• 35:29Harry Stebbings?

  How hard is it to hire today in the valley?

• 35:31Speaker 00

  Oh my God, it's so crazy. It is of course a very, very competitive market. The way that you see that is in terms of compensation. In order to retain fantastic people, we need to pay absolute top dollar. And we do, in order to make sure that we have the best engineers and scientists in the world. And so imagine you're a company that's not an arena, that's like, you know, a YC company that raised a $10 million seed. It's like, fuck, man. How the hell are you supposed to hire? I think it's really tough.

• 35:57Harry Stebbings?

  When you say top dollar, I had Brandon from McCour on the show and he's like, oh my God, top researchers will pay tens of millions of dollars.

• 36:04Speaker 00

  Oh, yeah.

• 36:05Harry Stebbings?

  I'm nervous by how nonchalant you were with that, oh, yeah.

• 36:08Speaker 00

  If you're talking about a really top researcher, we're talking with somebody with many years of experience and who's like really a super deep expert in their area, many tens of thousands citation type researcher. And yeah, for those types of people, they're expensive.

• 36:21Harry Stebbings?

  Have they all just concentrated at the frontier labs?

• 36:23Speaker 00

  Many have, many have. But there's also some people who are seeing those frontier labs as big companies now. And they're saying, here, I can't have a huge impact, I need to move. And so that's another demographic, actually. I think that's going to become even more extreme when, when the companies go public.

• 36:37Harry Stebbings?

  Can you help me? We talked about Dumbas Rocks and doing this show. I'm also an investor for my sins. And I meet so many of these people leaving OpenAI, Anthropic, you name it. And they all kind of seem the same, if I'm totally honest. Smart people out of great company. What will determine the NeoLab spinouts that succeed versus flame out with a huge amount of cash going in?

• 36:59Speaker 00

  Yeah, I think that the NeoLab thing is really tough. So just to so that we're on the same page with the audience, like there's at least 75 NeoLabs. And for sure, like two thirds of those are going to be worth nothing. Or like they're going to be bought out for parts, right? It's going to be like an aqua hire. And so what is going to determine the winners versus the losers in that game? And I think it's all about being very aggressive towards a great strategy and business model. Because what's happened, and you know this better than I as an investor, is that the markets have become very P and L driven. It's like not enough just to like create a model and then have a party about it. Hey, we created an AI. That is like old fucking news.

• 37:40Speaker 00

  Today, it's about not just going to create a model, but do I have a sustainable business model around that? And can I generate hyper growth in revenue? And if you're not able to do that, you're not even going to be able to raise your next round. People are raising multi-billion dollar rounds on top of just the names that are in the NeoLab with zero proof that there's any revenue generating model behind that. And so then the question you have to ask is, let's say I'm one of those people, let's say a $10 billion NeoLab valuation. What do I have to believe in order to 10x my money? And the thing that you really need to believe is that if the valuation is $10 billion today, that you're going to generate the revenue, let's say it's a 30x revenue multiple or 25x revenue multiple, to become a $100 billion business.

• 38:25Speaker 00

  And so what that means is you need to be generating at least $4 billion in revenue over the next K years, where K is something like two or three. And then if you're not doing that, everybody's going to hemorrhage out of the business, you're going to lose all your talent. You know, and that's, that's kind of what we see the dynamics being.

• 38:42Harry Stebbings?

  I get you. I think there's nuance to that candidly, which is like, if the company does annual tenders, you see the likes of a Mr. Owl, which will be valued, I think it's at 15 to 20 billion with like 500 million in revenue. And so employees can take liquidity out along the way. I think 11 Labs is at 800 million in revenue, raising it 22 billion reportedly.

• 39:00Speaker 00

  But these companies are doing great in terms of revenue. And their valuations, but they didn't, those are not zero revenue valuations. I'm talking about, there's some valuations that are zero revenue valuations. $3 billion company with $0 in revenue and no plan. That, I mean, like, I think Mr. Owl's going to do great. I think 11 Labs, 11 Labs is going to be a public company, dude.

• 39:19Harry Stebbings?

  But dude, they're not idiots doing it. So is it like, is it this amazing team from great lab? Worst comes to the worst, we sell for Prof Stack, which is 500 million. What, like, I'm not saying whatever, whatever, but like 500 billion. And best case, it works and it's a multi-hundred billion dollar company.

• 39:37Speaker 00

  I think that's a lot of the calculations. I've heard multiple people actually say this, is that, hey, you know, worst case. And that's what investors are thinking too, right? Investors are thinking like, hey, let's say we put a couple hundred million dollars into this thing. What's the value of the team? Well, we think that just the team alone could be acquired for a billion dollars. And so the 200 million that I'm looking at is like pretty safe, zero risk investment, might as well put it in. But that's also the reason why the next round is the harder round.

• 40:03Harry Stebbings?

  Next round's a bitch.

• 40:05Speaker 00

  Next round's a bitch.

• 40:08Harry Stebbings?

  It sounded cooler when you said it.

• 40:13Speaker 00

  We gotta say it at the same time. Next round's a bit. That'll be like our tagline.

• 40:18Harry Stebbings?

  I bet you weren't expecting this interview, huh?

• 40:22Speaker 00

  I don't know, maybe. I hope you were.

• 40:23Harry Stebbings?

  No, honestly, this is so much more fun than I thought it was gonna be.

• 40:26Speaker 00

  It's good.

• 40:28Harry Stebbings?

  Okay, can I ask you, another market that I try and get my head around is the data market. I'm an investor in McColl. I always think it's like good to put out your biases. There's so many providers at a billion dollars plus in revenue. Handshake's over a billion, McColl's over a billion, Surge is over a billion. I might be leaving out other people, but those are the ones I know of. And then hundreds of millions with the rest. What happens to this layer of the market?

• 40:51Speaker 00

  Well, people are projecting growth in this market. So let's talk about why that market is a growing market and why it's hypergrowth. I mean, McColl obviously is a generational revenue ramp company. They've been doing great. So is Handshake, so is Surge, so is Scale. All these companies doing great.

• 41:06Harry Stebbings?

  People forget Scale. The Scale is still ramping revenue well.

• 41:09Speaker 00

  Bro, Scale is still crushing, still crushing even post fractional aqua hire.

• 41:15Harry Stebbings?

  They are. How much of that revenue is Facebook?

• 41:17Speaker 00

  No, I have no idea. Yeah.

• 41:18Harry Stebbings?

  A lot.

• 41:19Speaker 00

  Go ask Alex Wang.

• 41:20Harry Stebbings?

  But, okay, so why is it interesting?

• 41:23Speaker 00

  So I have a thesis on hypergrowth. There's two types of hypergrowth markets that we see today. Market A is what I call scaling complements. And these are goods that are complementary goods to the scaling of AI models. And I mean that in the economic sense. A complementary good is, the good A is a complement to good B if the demand for good B drives demand for good A. So if I have a car, gas is a complementary good to cars. The more cars are sold, the more gas is sold. And so data is one of these scaling complements. Because the bigger models scale, the more data you need. And that's a scaling law question. And so the more models you get, and the bigger that they're getting, the more they're proliferating. The more businesses are training their own models, the more data you are going to need. And it's a very fundamental need.

• 42:06Speaker 00

  People forget this. They think about data as a commodity. It's really not. It's actually less so of a commodity than even GPUs. Because in order for data to become irrelevant, humans need to become irrelevant. And that means that we've achieved AGI. And so data is a very durable need. And companies are spending on it, usually within frontier labs, at about 10 to 20% of about the amount that they're spending on GPUs. And so if you believe in the GPU market accelerating, if you believe in the scaling of models, if you believe this is gonna be a big industry that keeps accelerating and growing, then absolutely you should believe in the data market. I believe it's gonna be at least $100 billion by 2030. It's not a trillion.

• 42:43Harry Stebbings?

  If we expand that, if we think Anthropic and OpenAI can be three to five trillion dollar companies, how big does that mean the data providers can be? Like, McColl's reportedly raising now at 20. Does that mean that these providers will be worth $100 billion? That wouldn't be egregious, would it, to say it's 3% of the market cap of?

• 43:01Speaker 00

  I think it'd easily be 100. I think these companies will easily be worth hundreds of billions of dollars. And I think they could even be worth more. The data is really the hardest part of model training. Because you need a source. It's so dirty. Nobody wants to do that shit. Nobody wants to hire all these people to generate data and then turn that into, basically, data plus GPUs equals model. And then the algorithms have become somewhat of a commodity. Because people know how to use the transformer. That's why, as you said, all the people that are coming out of the frontier labs look the same.

• 43:32Harry Stebbings?

  Everyone shits on these data providers for the same reason. They go, oh, but the revenue concentration is just OpenAI, Anthropic, Meta, a couple of other providers. Is that a fair criticism? Or actually, does that not denigrate from the ultimate enterprise value of these data providers?

• 43:49Speaker 00

  Yeah, so I have two answers to this. The first is that I think that Silicon Valley investors have become total bitches with respect to revenue concentration. It's like, what are you talking about? Like, TSMC has revenue concentration. There's businesses that are like many hundreds of billion dollar public market businesses that have revenue concentration. So I don't know what we're talking about here. There's businesses that are like two customer businesses. There's businesses that are selling to the government that have, there's like one of those. They're making like huge, huge amounts of money, like an Andoril. Hugely revenue concentrated businesses. And those businesses are doing great.

• 44:21Harry Stebbings?

  Are you suggesting that venture investors have the propensity to be lazy?

• 44:24Speaker 00

  I would never say that.

• 44:26Harry Stebbings?

  I was about to say real umbrage.

• 44:28Speaker 00

  I would never go that far.

• 44:29Harry Stebbings?

  I can let you know, it's incredibly tiring sending you an email. Did you know that this competitor's just released a product? Thank you. And from Portofino.

• 44:37Speaker 00

  That's my one, is I think that we need to like have some venture investors that like kind of suck it up and like put some salt on their martini glass.

• 44:45Harry Stebbings?

  If you knew venture in 2026, dude, you'd know that we wear a whoop and we don't drink martinis because it impacts our sleep score. But, okay.

• 44:52Speaker 00

  Okay, yeah, totally. Eight sleep and all that stuff.

• 44:55Harry Stebbings?

  Exactly. Okay, so that's one. We've become totally wusses around revenue concentration. We should embrace it.

• 45:00Speaker 00

  It's okay. And the second thing, I think that a lot of data businesses are gonna expand into enterprises. Of course, you know, we plan on doing this as an evaluation business, is going to enterprise and helping them with building their own AI models and all this routing stuff. Because we have the intelligence layer behind it that we built on Arena. So this is obviously some place that we're going to. But many data businesses will go here as well. And the idea is that in a world where every business needs its own AI model, why shouldn't every business need its own data? Of course they will. And the data will be part of the moat that their business accrues.

• 45:33Harry Stebbings?

  So that's on the data side. When we think about like on the agent side, Anthony said I had to ask you, how does your business change as we think about the transition to full trust with agents?

• 45:47Speaker 00

  Yeah, so agents is the number one priority for Arena and has been all year. People don't know this, but Arena's one of the largest consumer AI apps in the world. We're bigger than like XAI. We're bigger than Hugging Face and Manus and GenSpark. Where it's so massive, like outside in, it's like 30 plus million monthly visitors are on Arena. And most of them are knowledge workers and prosumers. People that we call unhireable experts. People that are coming to Arena to do their real daily tasks. And in doing so, they are giving feedback that allows us to build the evaluations that we share with the world. And so it's this organic flywheel for agentic evaluations based on real data.

• 46:25Harry Stebbings?

  Why didn't you build a data business?

• 46:27Speaker 00

  Well, we built an evaluation business around this that allows people to understand the strengths and weaknesses of models and therefore improve them. The labs can improve their models based on, you know, the insights and data that we give them. But we also want to help businesses with this.

• 46:40Harry Stebbings?

  Do you think the evaluation business is better than the data business?

• 46:43Speaker 00

  I think every business in the world's gonna need evaluation unambiguously. And that is the single biggest bottleneck to deploying AI. Because people don't understand how to define value. All this stuff around cost per value. It's like, how do you define value? It's easy to cut costs. I can tell you to go use Gemini Flash. And that's gonna be like way more efficient in terms of token spend.

• 47:02Harry Stebbings?

  Isn't value entirely subjective? For one, it's speed and for other, it's accuracy. Do you know what I mean?

• 47:09Speaker 00

  Right, absolutely. So you can try to decompose it. I think about it as three-pronged value proposition. There's performance, and then there's costs and latency. Costs and latency are easier to define. But performance is the tough one. Because the definition of performance depends on the business, depends on the use case. So at Arena, we built this pretty sophisticated pipeline for extracting organic performance measurements from agentic traces. And that's exactly where I would say that the value lies. And helping businesses take advantage of their own data. Instead of having to purchase data in order to say which AI works best for them, even help them train their own.

• 47:44Harry Stebbings?

  What sort of revenue range are you at now?

• 47:47Speaker 00

  So we're past $100 million in annualized revenue run rate. And that's based on like Q2 times four. And we're growing really, really fast on that front.

• 47:55Harry Stebbings?

  Dick question then. How efficient are you at monetization if you have 30 million amazing users? Who are unbelievably valuable in many respects, and you're only doing 100 million?

• 48:06Speaker 00

  You're asking about margins.

• 48:07Harry Stebbings?

  Yeah, and like speed of ramp and like, that good?

• 48:11Speaker 00

  I mean, like, I think obviously we're not like a free cash flow positive business yet. We're still investing all the money that we get into making sure that we continue our rapid growth. And we have a great product for all of our users and so on. But the fundamentals of the business are pretty strong. We feel great. Our investors feel great about our margins.

• 48:27Harry Stebbings?

  Yeah, I'm sure they do. I would love to have been an investor. I really feel like you excluded, you know, I could be Greek for you for this deal.

• 48:33Speaker 00

  Really?

• 48:34Harry Stebbings?

  Yeah, I can, I'm a venture investor. We can very plastic.

• 48:37Speaker 00

  Calimera, calimera.

• 48:39Harry Stebbings?

  Calimera, humus, yes.

• 48:43Speaker 00

  Humus tempita.

• 48:44Harry Stebbings?

  See, see, this is.

• 48:46Speaker 00

  We are already Greeks together, okay?

• 48:48Harry Stebbings?

  I knew that this would be a productive session. Yes.

• 48:53Harry Stebbings?

  Are investors over rotating on margin also?

• 48:56Speaker 00

  I don't know. I actually think margins are pretty important.

• 48:59Harry Stebbings?

  We're seeing a load of businesses like your fireworks of the world where they're at the 30% style, mid 30s margin base. And that's very different to software margins that were 65 to 80.

• 49:09Speaker 00

  Yeah, I mean, listen, profit is just like margin times volume. And so you have to look at that as the calculation for the business. It's not like super, super crazy. And so I don't think it's a crazy day to invest in these businesses. The bigger problem with businesses like that I see these days is that a lot of them are fundamentally GMV businesses where there's like some reselling happening. I'm reselling tokens. I'm reselling GPUs and stuff like that. And those businesses are tough because at the end of the day, you have to really think about not just the margin that you're charging in the sort of short to medium term, but the terminal value of the good that you're providing to your customer. And so if the terminal value of the good is,

• 49:48Speaker 00

  I'm going to host GPUs for you in order to run your models, then why should I pay you more than like the cost of the electricity that it takes to run those GPUs? So the sort of like price to value thing is where I think you start getting into questions. That's why I think a margin question is very important. And I'm not saying the margin in the short term, a series, you know, C to A, B company might not have the best margins in the world, but you should be thinking about, as this business scales and towards a public company, is it going to have a fantastic margin structure that supports a public business?

• 50:22Harry Stebbings?

  One thing that's challenging is when your customer becomes your competitor. To what extent do you think we will see the model providers move into the application layer aggressively? We see Claude Design has actually really started to eat away at Figma. And I'm an investor in Legora, again, always hope. People are like, oh, don't worry about Harvey. Not in any disrespectful way to Harvey. There are disclaimers and everything in between. Everyone's at Anthropic are going to do a legal product that's going to kill Harvey and Legora.

• 50:47Speaker 00

  Totally. Yeah. I mean, listen, ask every business in America how they feel about this. Everybody's shaking in their boots. I have friends that are running businesses, multi-billion dollar businesses. And then what happens is that the next day, one of their biggest customers compliments says, hey, listen, OpenAI is getting into this game. We want to work with them. We want to work with them because they're more AI forward and you're less AI forward because you're, you know, traditionally a SaaS business. So goodbye. Yeah, it's happening. It's absolutely happening. And I think businesses should take it really seriously. And this feeds right into this AI sovereignty sort of debate, because a lot of what they're doing is if I'm OpenAI and I'm Anthropic, I'm looking at who are my biggest customers? Who are my customers that are winning the most in the enterprise? AI is going to commoditize, right? If like inference is going

• 51:32Speaker 00

  to commoditize, then of course, the next best thing is for the model providers to be moving up the application layer in order to earn more of the application stack so that they ensure that they're not commoditized and they're getting close to the value they provided the end customer. So I absolutely think it's a risk. I think it's a risk for Legora. I think it's a risk for Harvey. That's why Harvey's also, I mean, Harvey, the CEO of Harvey himself is saying, you know, his biggest competitive worry is the model labs.

• 51:58Harry Stebbings?

  But then how do you, that's a complete paradox to what we just said at the beginning about companies being scared to work with the frontier models, isn't it?

• 52:05Speaker 00

  No, I mean, they're scared to work with them. That's what I was saying.

• 52:07Harry Stebbings?

  They're scared to work with them and they're embracing them at the same time?

• 52:10Speaker 00

  Ah, you mean the customers of the Harvey's and Legora's?

• 52:13Harry Stebbings?

  Your friends running multi-billion dollar companies are like, oh, we want to work with OpenAI. I thought we just said they're scared to work with them.

• 52:18Speaker 00

  That's a good question. I think you see both in the market. I mean, it depends on who's most automated.

• 52:22Harry Stebbings?

  Sorry, I think it depends actually on their GTM. If you are doing anthropic design or Claude design, dude, designers can pick up a tool and use it very efficiently. If you're Legora or Harvey, dude, you've got to go into Cooley or Clifford Chance or any of the, build relationships with 50 year old white male partners who want to play golf and be told that they're great and that life is awesome. And then you've got to do deployment to junior lawyers who don't want to fucking use you because they think you're going to take their jobs too. The deployment in the GTM is the heavy lifting and that's real world.

• 52:56Speaker 00

  Totally. And there's also businesses that are less software focused and more network effect focused or more operations focused. And I think those businesses are also more likely to be adopters of the big labs. Let's say system integrator like an Infosys. I think more likely to be an adopter of a big lab because labs really, I think, less likely to be competitive with an Infosys than they are to be with some sort of a scalable software product like insurance claims automation, or let's say, I think the Harvey model, like legal chatbot. That's tough because I think a model I can build that.

• 53:29Harry Stebbings?

  Do you think Salesforce will thrive in the next few years or be challenged?

• 53:34Speaker 00

  You know, Salesforce themselves have a pretty strong AI strategy. So I think that those people are basically like ready to go and fight in this race. I doubt that they're going to like go downhill. I think that the SaaS apocalypse has been a little bit overstated overall because people don't understand always the dynamics of those businesses and how tough it is to replicate what they've built, also from a network perspective and a data perspective. So we'll see, we'll see.

• 53:59Harry Stebbings?

  I get you. I think if you're a ServiceNow, Salesforce incredibly difficult, incredibly hard. I think if you're a, I love him and I interviewed him, but like a Wix, less difficult, less integrated, less sticky, tougher. It's all about entrenchment within enterprise. If so, golden. If not, be more nervous.

• 54:20Speaker 00

  Totally.

• 54:21Harry Stebbings?

  Right. I'm going to do a quick fire round with you. I'm going to say a statement. You're going to give me your immediate thoughts. Can I go?

• 54:25Speaker 00

  Yes, sir.

• 54:26Harry Stebbings?

  What have you changed your mind on in the last 12 months?

• 54:29Speaker 00

  Open source model leadership.

• 54:30Harry Stebbings?

  Unpack that.

• 54:31Speaker 00

  Yeah, just that I think open source models are moving much faster than I initially thought. I think also Anthropic is moving much faster than initially thought. The space is moving so fast.

• 54:39Harry Stebbings?

  What do you know now that you wish you'd known when you started Arena?

• 54:42Speaker 00

  Man, I mean, managing people. Managing people is just the most important part of running a company. The technical stuff, you know, I did my whole PhD on it. I spent like my whole PhD proving theorems in a basement, which I loved, by the way. It was like a great time. And now it's all about strategy, people and forecasting the future, being able to like look six months, a year or two years in advance and then try to plan for that. Those are so, so important skills.

• 55:04Harry Stebbings?

  Does it make sense for great talented young people to still go to university?

• 55:09Speaker 00

  Hmm. I think it's ever more important for people to have a strong mind. And the university can be a place to develop a strong mind in terms of strong first principles thinking and also getting to know other people and network with them. I think that university is still a good place to go if you want to have an intellectual life, meaning where the work, the intellectual work that you do is the primary driver of your professional career.

• 55:33Harry Stebbings?

  What did you do with Arena that with the benefit of hindsight, you wish you hadn't done?

• 55:38Speaker 00

  Oh, man, I had so many mistakes. I mean, at the beginning, I had no idea what I was doing. And I, you know, my co-founder Yon probably knew and could see behind the corners, but I was probably too stubborn to listen to him. So first of all, I've learned to listen to Yon more. But second, so many like experiments at the beginning that I just shouldn't waste some time with. I think the degree of focus that you need to run a company is just so extreme. You really need to do one, maybe two things extraordinarily well and focus very, very deeply on them. Pick the right ones and focus on what's working, not on expanding into things that are not working. That is a great lesson for me.

• 56:13Harry Stebbings?

  This is why I also, I agree with Legora and Harvey. Like when it's not the main course for Anthropic to do legal, I just think you've got a really hard business when it's someone else's appetizer and it's the only thing you live and breathe.

• 56:25Speaker 00

  Totally. It's like priority number 12 for Anthropic is probably not high enough for Harvey and Legorda to be too scared.

• 56:33Harry Stebbings?

  I'm also like, Dario, will you please just fucking solve cancer and like climate change? Leave a shareholder agreement to someone else.

• 56:41Speaker 00

  Exactly. You know what, though? Solving cancer is hard. It's harder than legal.

• 56:45Harry Stebbings?

  A hundred percent. That's why Dario should solve it.

• 56:47Speaker 00

  Well, that's why he doesn't want it, man. He just wants to take your bread. It's easier.

• 56:51Harry Stebbings?

  Oh, come on, Dario.

• 56:53Speaker 00

  Come on.

• 56:54Harry Stebbings?

  Come on, dude.

• 56:55Speaker 00

  Leave some bread for the rest of us.

• 56:56Harry Stebbings?

  So which company will be first to $10 trillion? Nvidia, OpenAI, or Anthropic?

• 57:02Speaker 00

  I think it's hard to say not Nvidia. I think Nvidia is probably in the lead there.

• 57:05Harry Stebbings?

  Why have Nvidia not bounced on the rise of Open? I'm an Nvidia holder and I'm seeing flat. Why?

• 57:12Speaker 00

  Well, I think market probably hasn't priced it in yet. We'll see. We'll see how good these models get. But I think the enterprise adoption of AI is going to be another 10xer for the industry. I think it'll 10x Nvidia very reliably.

• 57:22Harry Stebbings?

  Do you worry about the compute debt cycle and the levels of debt being taken out to fund the compute build out?

• 57:29Speaker 00

  I do worry about that. And I think that the reason to be worried is because if the open source ecosystem somehow makes the cost saving opportunity for businesses much more salient and therefore decreases the revenue of companies like OpenAI and Anthropic within the enterprise, that it could lead to insolvency. I think that is the big secular trend that I would worry about if I were an investor in such, you know, markets.

• 57:54Harry Stebbings?

  My worry is we've never had such reliance on two companies to continue to hit their targets. If OpenAI and Anthropic do not continue in the trajectory that they are, the music and the party goes off. And if the music goes off, for everyone in the fireworks layer, no party. The rooting layer, no party. Everyone suddenly just gets the wind knocked out of them by two companies' trajectory.

• 58:15Speaker 00

  Totally. Yeah, I think that it's a really big deal. You know, I think that we could use a little bit of sobering up within our industry anyway. I think that there's a lot of hype. I think that there's too much crap happening for my taste. And I'd prefer a little bit of consolidation, actually, so we see what shakes out. I think Arena will shake out as a winner in our category. And I would love to see some of the great people that are at other businesses in our area consolidate to Arena, be able to hire them in.

• 58:41Harry Stebbings?

  Where is the industry underhyped? Where is it overhyped?

• 58:46Speaker 00

  Well, it's interesting. I mean, I feel like everything is so hyped right now.

• 58:49Harry Stebbings?

  I feel like the mechanical infrastructure for compute and data centers is relatively underhyped. Like the actual cooling systems and the actual like steel infrastructure. Do you know what I mean? Like the real physical is still underhyped.

• 59:04Speaker 00

  Interesting. Yeah, you probably know more than me. You're in touch with the investing markets. So I mean, like, I know that people are super hyped up about all of the high bandwidth memory and the GPUs and all that stuff. That stuff is super ultra hyped, right? I mean, for on basically in all stages from public market companies to the early stage.

• 59:22Harry Stebbings?

  South Korea have fucking caused, called a national convene, like community meeting today because their stock markets are down 40%.

• 59:31Speaker 00

  Oh, my God.

• 59:32Harry Stebbings?

  A national meeting because?

• 59:34Speaker 00

  Down 40%? Why are they down 40%?

• 59:37Harry Stebbings?

  If you're a public markets investor in South Korea, you're coming home a little bit stressed today.

• 59:43Speaker 00

  No, that's not good for them. Yeah, let's all pray for the, let's pray for the South Koreans.

• 59:47Harry Stebbings?

  The thing I am slightly amused by is right after everyone at SK Hynix and Samsung took home like mega bonuses, then the market crashed.

• 59:57Speaker 00

  So why did it crash like that? What's the deal?

• 59:59Harry Stebbings?

  Honestly, I think it's just a realization that, you know, everything was pretty overinflated and markets can't keep ripping for so long. Cause there's no, there's no destabilizing factor within open or closed that suggests demand is being questioned. So.

• 1:00:13Speaker 00

  Wow, okay.

• 1:00:14Harry Stebbings?

  That's where we should have a hedge fund manager on. We could do a new show hosted by Anastasios and Harry.

• 1:00:20Speaker 00

  Yes, absolutely.

• 1:00:21Harry Stebbings?

  Called Two Dumb Rocks.

• 1:00:23Speaker 00

  Let's do it. And we bring exclusively us and hedge fund managers.

• 1:00:27Harry Stebbings?

  I think it's a fucking great idea. I actually do too. Guest one is Anthony Midha. Anthony, will you help Two Dumb Rocks? He's like, why did, why did I fucking put this together? This is not.

• 1:00:38Speaker 00

  No, Ant would be the best guess.

• 1:00:40Harry Stebbings?

  What's the most underrated NeoLab other than periodic that people aren't talking about?

• 1:00:44Speaker 00

  Ooh, underrated NeoLab. Yeah, I don't, I don't know if I have one. I think a lot of them are overrated.

• 1:00:52Harry Stebbings?

  I think Black Forest Labs is pretty underrated.

• 1:00:54Speaker 00

  BFL is great. Would you consider them a NeoLab?

• 1:00:57Harry Stebbings?

  Oh, don't get technical with me on semantics.

• 1:00:59Speaker 00

  Yeah, I don't know. Yeah, BFL is awesome.

• 1:01:02Harry Stebbings?

  Yeah, I agree. A final one for you. What are you most excited about? My mom's got MS. I'm fucking excited that chronic conditions like MS could maybe be treated. What are you excited about with the next five to 10 years?

• 1:01:14Speaker 00

  Yeah, I mean, I've always been a big proponent of AI in medicine too. I think that the like level of human flourishing that's going to happen as we start to one by one eradicate diseases, the same way that we're currently eradicating open problems in math, is going to be incredible. I think it's going to be tough because the thing is that math is a closed system in medicine. I think you'll need to figure out ways of quickly iterating in a feedback loop on biological systems. So that's the missing piece. But once we crack that, it's going to be just an extraordinary journey.

• 1:01:43Harry Stebbings?

  So funny, when I interviewed Demis and I spoke about like bio and medicine, it was, it was an area where you could see his eyes light up. But it was an area where I said, hey, testing needs to change. 15 years, no bueno for a lot of sufferers of chronic conditions.

• 1:01:57Speaker 00

  Yeah, and you know what's missing? That is exactly the data layer. That's exactly one of the areas where the data layer, where you can clearly see that the data layers where value is going to accrue. Because the GPUs are the same GPUs in both cases. The problem is that, that data infrastructure, the flywheel, the data collection that you need in order to build a great biology product or a medicine product, that's tough to build.

• 1:02:18Harry Stebbings?

  Dude, you've been a fucking epic guest. Really? Like, I'm so grateful. It's been an amazing show. Real honesty and authenticity. Most people suck as guests. You know why? Cause they're not authentic and it just comes across. Thank you for being so great.

• 1:02:32Speaker 00

  I appreciate it. No, thank you for having me on. Would love to do it again at some point and you should visit the arena office anytime that you're in the Bay Area.

• 1:02:41Harry Stebbings?

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