Crypto Going "Bunker Mode", The Mathpocalypse, Starbucks Explores Chipotle Takeover | Rebecca Kaden & Michael Mignano, Nathan Benaich, Michael Sindicich & Healey Cypher, Moritz Stephan, Anastasios Angelopoulos, Zach Yadegari

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Today is Thursday, October 8th, 2026. We are live from the TDPN UltraDome, the temple of technology, the fortress of finance, the capital of capital. Let me tell you about ramp.com. Time is money. Save both. Easy-to-use corporate cards, bill pay, accounting, and a whole lot more all in one place. How many days until Christmas?

I have a better question. How many hours?

Oh, we're counting down the hours now.

Okay.

There are 1,862 hours until Christmas. Get ready, folks.

Yep. That's right. We've moved from days until hours. That's how close we are.

That's how close we are. It is October.

We're just hours away.

It is early October. We're hours away from Christmas. We are technically hours away from Christmas.

That's correct.

Yes.

Anyway, we're only 1,800 hours away from Christmas.

Yeah, it's, it's the apocalypse day. There's, there's so many apocalypses. Mathpocalypse. There's a crypto apocalypse going on, although the market is reacting in a very moderate way. But the timeline is being dramatic, so we got to break that down. Ethereum founder Vitalik Buterin and others in crypto are sounding the alarm that AI-driven math could threaten blockchain security. And so, crypto's going bunker mode. That's the term that they're using. So, we've all seen the progress in AI-driven math solving new proofs, solving Navier-Stokes. There's a lot of impressive progress in math that maybe has applications in Physics maybe has applications in engineering, fluid dynamics. A lot of these things are further out, and if they wind up being useful, they might increase efficiency here or there.

Not as far out as you think.

But the big thing is that crypto is here today, and if there's an advance in the underlying understanding of how cryptography works, it could really reshake It could really shake up how the crypto industry works and how these products are secured. So, are they in danger?

Cortisol rising.

It's the Ralph Wiggum meme, I think. I'm in danger seeing all this. Matthew Green, who teaches cryptography at Johns Hopkins, put the situation in stark relief. He said, I think we might lose public key cryptography. Which is a huge statement from an expert in cryptography. It would require a pretty massive restructuring of many security protocols, but also the crypto industry. At the moment, cryptography has, as a discipline, has been exempted from the list of published papers related to AI-enabled math breakthroughs. So, there were hundreds of papers, and it's very clear that either the agent swarms that were sent to go solve math problems, they said, hey, don't even bother with any cryptography stuff. Or if they did, they didn't publish those and they're burying them for now until there's a way to actually patch those.

Or maybe the cryptography is just too strong.

That's true. That's a third option. The crypto industry is a little skeptical about it. They think, I mean, there might be some flaws. Of course, they've been preparing for things like this before quantum computing. is potentially existential to many blockchains. And so, there has been the concept of Q-Day and how they work backwards from that to make sure that they are quantum resistant.

Yeah, the interesting thing is like historically when the crypto industry has faced, you know, headwinds, the strategy has been HODL.

HODL.

And that's not necessarily going to be effective for this next chapter.

That's true. Yeah, that's a good twist. Of course, there are very weird dynamics where if you break all the Bitcoin keys and all the wallets wide open and you completely erode all the trust that's been built up in that virtual currency, yeah, you stole it all, but it's worth nothing. And so, the game theory there of no one would ever want to steal all the Bitcoin, right? So, it's more like, can someone go after long tail?

I'm sure there's some people that would do it just for the love of it.

Just to watch the world burn, Joker mode? Yeah, that's probably possible. We could be seeing a Joker-fied— oh, you have the Joker ready to go. Yeah, a Joker-fied AI agent swarm would be a bad situation.

Yeah.

For sure. But there is some cause for optimism. Much like the broader cybersecurity scare that happened back in March of this year, there's a gap between closed source and open source models. Most people say it's around 6 months. The capabilities catch up in certain areas. It seems like it's faster. Sometimes it's 3 months, but 6 months is sort of a useful heuristic I have found. And that actually maps out pretty perfectly with the most recent news. So if you remember Mythos Preview, was dropped by Anthropic on April 7th, 2026. That's the 4th month of the year. And then CrowdStrike announced that a 26-year-old in China used an open-source Chinese-developed AI agent to execute cyberattacks against South Korean banks on October 7th, like the same— I think the report came out October 7th. So, it's basically just exactly 6 months later, you see like an open-source model be used in a cyberattack. Now, fortunately, the banks have a ton of redundancies, the ability to roll back transactions. They store things to tape. They store things on paper sometimes. There's a lot of different ways to secure a traditional bank that is not purely digital, even though they might have a digital front end and a lot of the money might be stored digitally. And the interesting thing is that when I read at least about one of the South Korean bank cybersecurity incidents, it was a pretty small amount of user data that was stored. It was like names and addresses and like phone numbers of like— it was a significant number. It was like tens of thousands of clients or something like that. But it wasn't like they robbed the bank and they got the money or they got everyone. Somehow they got into like one system for information. So, it could have been like they— They hacked into like their paperless post account. That was like what the bank used to send out invites to clients or something like that. Like, there are a whole bunch of different systems and where— at what level did they get in is important, but it's clearly happening.

They got into the client gifting software.

Potentially.

They sent everyone chocolates.

Maybe, maybe. And so obviously, you don't want hackers anywhere. And so cybersecurity is more important than ever. And so, the crypto community does have a couple months to go bunker mode, as they are putting it. And it feels like there'll be an incredible amount of progress on these AI-proofing systems, but it's an entirely new challenge. It's very— it's much less understood than quantum computing, which has been theorized mathematically and sort of formalized for years before the capability came. This is different because we're getting this capability before we've really characterized the shape of the threat. Like, they know with quantum, like, there's something called Shor's algorithm, and like, they got to fix that. So, they got to make sure that Shor's algorithm doesn't work to break Bitcoin wallets open. They know the mathematical problem. They got to solve that. In this scenario, it's like there might be a different algorithm. That runs on commodity hardware that works? And how do you know when you don't know the shape of the threat that's coming? So, it's a crypto apocalypse potentially, but the market doesn't think it is. Bitcoin's only down 3% today, and it's still up 3% for the month. And so, the market is digesting this and optimistic. There's still lots to do if you work in crypto and potentially Even if you only own some crypto, there's things to do. Vitalik gave some recommendations on, you know, don't panic, but also maybe start thinking about this more intently. He said, I don't recommend anyone scramble to move their funds to new wallets today, but we should take the risks of cryptography from AI-accelerated math seriously and minimize our exposure to not just quantum-vulnerable cryptography, but also AI-vulnerable vulnerable cryptography. The new core area of risk from this viewpoint is unfortunately MLDSA, FHE, lattices. And this is also another reason along with quantum why ECDSA might fall even faster than expected, hence the fresh address recommendation. So far, most people have been in the mode of thinking elliptic curves broken, hashes safe, lattices safe, but there's a good chance that in the concrete secure— that the concrete security of lattices will take serious hits from the next 2 years of AI math. And so some people were posting. Scott Liu here was saying, oh, that's weird. The AI math god is somehow no better at cryptography than a 2026 human. We got superintelligence in math, but not cryptography. What's going on? He thought for a minute.

He says, oh.

And I think the interpretation of this, and you can tell me if you disagree, is Yeah, it's because the AI math god is run by an American company that has no interest in destroying the human race.

In, like, total chaos.

Yeah.

But in the open source world, it's a very different game.

Yeah.

And so, still interesting to think about the— still interesting to think about the game theory even in the open source world, but I think that will all be downstream of a whole bunch of changes. And then there is the question of, you know, how does crypto handle this? Like, the cryptocurrency industry has been libertarian. They've been against the government in many ways, small government. I want to own the money. Well, now you're facing a threat from open source, from a non-government regulated entity. And so, while a lot of people, in the AI safety community have said, this is the moment for big government. This is the moment to register large clusters. This is the moment to track all the data centers, to have licenses for inference and training and reporting to the government. That is a solution.

Yeah.

If you lock down open source and you say, yeah, if you're gonna spin up a million agents and try and do a bunch of inference to try and break Bitcoin wallets, we're gonna find out about it. going to arrest you, and it doesn't matter that you're using an open model. That's a very different psychological frame of mind for a Bitcoiner.

Yeah.

The other thing here is that there's obviously biorisk with model advancements, but it is going to be wildly different for somebody to use an obliterated model to try to create a bioweapon and then actually distribute that out into the world than using a new model to try to mess around with cryptography. That feels squarely in the hacker camp.

Totally.

There's people that would just be messing around, and then accidentally have a breakthrough or accidentally, or maybe intentionally cause financial chaos. But that's purely digital. And that's the thing that millions of people have been doing for a very long time, just generally hacking around. wildly different than the kind of person who would go out and try to create a new pandemic.

Yeah. And then also, another layer of this will feed into the whole AI doom loss of control scenario because you get an AI agent that's hyper-intelligent and it's also able to break Bitcoin wallets. It breaks a couple open, then it has capital. With capital, it can marshal more compute, hire people to do things in the real world, et cetera, et cetera. And so, the doom scenario becomes like way more human-enabled if you are able to amass capital pretty quickly as a rogue agent. Do you have a take on this, Tyler?

Yeah, I mean, I feel like the crypto industry broadly is like fairly good at self-governance, right? You've seen like, even if you're talking about like Bitcoin, You know, there's like, they can actually like change the protocol. You know, you have like Bitcoin Cash, which is the shoot-off, stuff like this.

Yeah.

I think the Bitcoin Policy Institute, like, I don't know, maybe a month or two ago had this open letter about how, you know, the solution is we gotta build up defenses much more and we gotta use, you know, spend a lot on inference to try to like figure out what is the right path moving forward. I think most people are very against like limiting open source models, stuff like that.

Totally. Yeah. It'll be interesting to see how these worlds collide and where things go. I had some other take, but let me tell you about Codex. Codex is a powerful workspace for getting work done with AI agents. Whether you're writing code, analyzing data, creating content, or automating business workflows, Codex helps you move projects forward from start to finish. Thank you for the continued clapping.

Ben, I don't know if we— You included this earlier, but he says, lucky coincidence, the labs are only successfully cracking esoteric math problems and not the problems where a solution would give the winner an asymmetric commercial advantage. Again, this is what I've said a bunch of times on the show now. Math problems are the perfect category of problems where you get a result and you're incentivized and excited to share the result. There's no immediate opportunity to commercialize a lot of this stuff.

Yep.

And so, for every breakthrough in math, you should assume there's— and the reason this should be getting everyone excited is you should assume there's a bunch of other breakthroughs in other fields that have more commercial applications where the person that has— and it's not just the labs, it's people using the current frontier models to find breakthroughs in their own field.

Sure.

And so, again, I'm expecting a real explosion of progress especially as we enter the later half of this year.

Yeah.

Or the sort of last end of the year.

I believe Will DePue posted about this. That's what I was thinking of. Will DePue posted, I think there was like a slight Bitcoin sell-off like a while ago, like maybe around the midsummer time period. And he sort of took a victory lap or something or was like saying like, yeah, in hindsight, once like the AI community built like the Hack Machine 9000, It should have been obvious that you should get out of crypto. And then, what was odd was that crypto rallied after that. So, like, he was kind of a little bit too early with the take, but now, it feels like, okay, everyone's pieced it together a little bit more. But also, there's so many other factors where you could see this narrative dying down, and all of a sudden, there's some other narrative that's driving crypto, and people are piling in for whatever whatever reason. But it was, yeah, maybe like, you know, even in a— even it's been, you know, pitched as an inflation hedge. There's always been people who have said the restricted supply is valuable. You could have a view on inflation that becomes really popular, and then all of a sudden people are piling in. There's a whole bunch of reasons why the market can move. It's not purely driven by this, but it was funny that he was posting about this like months ago. Anyway, moving on. Console.com. Console builds AI agents that automate 70% of IT, HR, and finance support, giving employees instant resolution for access requests and password resets. So OpenAI's drop of hundreds of new mathematical proofs is now being called the mathpocalypse. There's some white pills, there's some black pills. People are all over the place. Obviously, we talked about the crypto. knock-on effects. Nabil Qureshi says, mathematicians, AI is plagiarism and we don't want to know the answers anyway. Artists, AI is plagiarism and the art sucks anyway. Chess players, hmm, I wonder if I can use AI to increase my rating. Because there are some people that are just delightful with— delighted with advances and not really, you know, frustrated by it. There's actually a very—

Yeah, how do you prevent against like botting? in online chess? Like, couldn't you— can't you just be running your own— like, I don't know. And I'm comparing that to, like, let's say somebody using an aimbot versus a computer.

Yeah. No, I mean, bots are undetectable. Like, all the bots can one-shot CAPTCHAs and fake—

But not even that, but basically just running an AI copilot that is helping you make—

Yeah, no, you can definitely do that.

So unless you're playing chess physically in front of somebody and watching them, you no longer have a fair—

What do you think?

Well, I mean, if you're like, ELO is like 800 and then you start making like, you know, 2000-rated moves, like, it's pretty easy to tell that stuff.

Yeah.

It's like, I think like, if you're on chess.com or whatever, it's like, I think it's fairly hard to cheat.

Hard to cheat or people just don't cheat because it's like, what's the point? And like, it's like, okay, yeah, I played against somebody who was like smurfing and they had an 800 ELO account but they were clearly playing at 2000 ELO. Like, okay, I lost that game. Let me queue again. Okay, I got someone who's actually 800. And I'll just keep playing until I get someone who's actually my— Yeah, that's probably true.

But if you're consistently using, like, an engine, it's like, I think it's not that hard to figure that out.

Yes, but, like, this is going to change, like, because, like, the models will be so good—

It's over.

I mean, the models will be so good that you'll be able to say, like, I'm Elo 800, help me play at 850 and also really mimic the human experience. So, don't make—

don't—

But yeah, I agree.

There's like little incentive to actually cheat on Chess.com because—

Yeah, I agree.

There's not much incentive. Gold says, you can tell if they're bots if they statistically always or nearly always make the optimal move.

Yeah, exactly. Like, there's no fun and you can always just go play against the best Stockfish model if you want. Like, you can just max it out if you just want to play against the best computer in the world. Nobody does. And so there's not that much value in it because everyone would just be like, cool, yeah, you just ran the model that everyone else has. Like, do you want to play against me or not? Like, if you want to just be the model, just go. And you don't win anything, so there's not any incentive, I think. I think that's how it works out.

I don't know.

I do think, yeah, I mean, in the future, like, you will be able to I mean, you in the gym have been accused of using robotic-assisted lifts, right? Yes, yes, yes.

You'll wear like big sweatpants.

Oh, yeah.

You're on the deadlift. Can you imagine having an exoskeleton? And you have your exoskeleton putting up 800-pound deadlifts. I mean, people know you're strong, but not that strong.

They're skeptical. Yeah, I don't know if you'd get a lot out of that. You could bring fake weights. That's, that's one way. I mean, people do stuff, but then why not just Photoshop it? Why not just go and Photoshop a screenshot of you on your, your profile on chess.com with a 4,000 Elo and then share that on X and be like, I'm the best chess player ever?

But if someone fact checks it, then you just look like Nate.

Yeah, and so eventually you have to get down to like fact check by walking through a metal detector and going to an actual chess match because like Oh, you're really better than Magnus? Let's see if you're better in person. You know, that will— that's what will happen. And so there's like, you're gonna wind up, you're gonna wind up in the Faraday cage with Magnus eventually. I don't know. Anyway, let me tell you about Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents. There's a very interesting post in the Wall Street Journal about a former NFL lineman who solved a decades-old math problem. John Urschel gave up his career with the Baltimore Ravens to study math at MIT. And he has—

Get this guy on immediately.

He's so jacked. It looks like, yeah, he's definitely doesn't need the exoskeleton in the gym. He's a former NFL player. John Urschel decided to do some light reading this week. And for him, that meant leafing through the latest math papers from OpenAI about topics such as the Riemann hypothesis. Oh my Lord, he thought. I was absolutely floored. Good rhyming. Urschel was blown away by the findings because he happened to understand the hundreds of proofs better than nearly any human on the planet. 9 years ago, he traded the National Football League for the Massachusetts Institute of Technology. Crazy that you can take like that— I think the NFL has got to be an incredibly demanding schedule. Like, you can take Like thousands of hours off of your, like, math career and then, like, go back in the game and not be—

Well, not to mention getting just slammed in the head.

Yeah.

Yeah.

Oh yeah.

They want you to believe in CTE. Counterexample.

Make it make sense.

One of one sample counter.

No, he's possible. He's actually the smartest person to have ever walked the earth.

So even after getting Yeah, or it could be reversed. You get hit in the head and it makes you even more of a genius or something.

Yeah, it unstucks something.

Yeah, sort of like a magical realism.

Tyler, is this going to make you get into watching football?

Yeah, maybe you should play some—

Trying to scout out future—

Maybe you should play some full-contact tackle football. It might make you better at math. You never know. Urschel was blown away. By the discoveries. And Monday, instead of studying abstract play designs, he was publishing some impenetrable language of his own to prove a decades-old math conjecture. Urschel's paper titled On the Growth Factor of Random Matrices is one of a deluge of AI-assisted proofs that mathematicians have achieved in this new era when they can combine their genius with supercomputing power. But within this community of brainiacs, there isn't a single person quite like the 35-year-old Urschel. After 3 years with the Baltimore Ravens, the offensive lineman, who is listed at 6'3, 313 pounds, ditched his helmet and became a professional egghead in 2017. He hasn't regretted it for a moment. He says, I feel like I bet on myself in a big way. I'm living my best life right now. You love to see it. Long before Urschel became an assistant professor at MIT studying matrices, spectral graph theory, and other subjects that sound like gibberish to just about everybody— shots fired by the Journal, but I agree— he was an overachieving kid attending Penn State while playing for the Nittany Lions. He did more than pursue an ambitious major by studying math and win— and he won the prize known as the Academic Heisman. By the time the Ravens drafted him in 2014, he already had earned his master's. But a year after protecting Joe Flacco, Urschel started to miss his life-crunching numbers. While he felt his analytical background was useful to him as a football player, for instance, he says it helped him learn the playbook, it didn't quite scratch his intellectual itch. That's when he decided to apply to become a doctoral student at MIT, the school he had always dreamed of attending. He began moonlighting there in 2016. And so—

I know, I know what this is all setting up.

What is this?

He is gonna— he is gonna star in the next Terminator movie.

Ooh.

Football player, math genius, fights back against—

Triple threat. Yeah, this is exactly—

Takes on the Clankers.

Yeah, I would love to see it.

I mean, you would hate to be a Clanker with this guy walking you down.

For sure. But he seems to be a friend of the Clankers because he has actually been using AI in To assist him in his research. So, his acknowledgments in the paper that he published cites the help of OpenAI models and says that he welcomes any question about the role of AI, which is upending his entire field. He says, but supercomputers haven't dented the passion that this football player turned mathematician has for math. He compares it to his enjoyment of chess. He also likes chess. The computers are better than the humans, Yet he still enjoys the pursuit of finding the right move. I really want to understand the why of things, Urschel says. It doesn't ruin the why. AI doesn't ruin the why. That's a very interesting thing. And I feel like, I mean, just in knowledge retrieval over the past 3 years, I have felt that. Like, I know a lot of obscure factoids about Silicon Valley lore. But when ChatGPT came out, I wasn't like, oh no, the computer knows more about Silicon Valley history than me. Or like, oh no, the computer knows more about the random companies in Silicon Valley than I do.

You're basically one of the top guys in your field.

I mean, I did spend like 5 years making YouTube documentaries about these companies and like trying to learn a lot and like piecing it all together. And like ChatGPT can do that, but like it's been such a benefit because I want to know. So, I'm looking up stuff all the time and I'm like, I want to go on the journey, I want to gain that information, and it gives that to me. It's weird.

Very, very, very weird. We benefit from having knowledge and understanding within us. Like it's nice to go through life and be able to understand things in real time versus reach it just because you have complete access to all the information you need.

Yeah. Yeah, I mean, there's still obviously the jobs question. How do you monetize that if your job was just solving math problems or your job was just assembling sloppy research reports? You might be going through a process now, but I don't know. I'm still optimistic. I still, I still feel like we're going to be hearing from this gentleman, John Urschel, for a very long time.

Yeah.

Maybe he's like, you know what, I'm going back to, I'm going back to football. Math is solved. I'm going back to football.

Yeah.

When, when I wonder when he actually gave comment for this article.

This was like yesterday. I mean, this literally posted today at 8 a.m. So I imagine that he was on the phone with the Wall Street Journal over the past, like, 2 days because it's a pretty detailed profile. We should get him on the show. I'd be fascinated to hear about what he thinks. Yeah, I mean, I think people will be continuing to study this stuff for a long time and learning it to apply it for themselves. Anyway, Craig Tsai is memeing it. He says, OpenAI, we literally solved math. Him, He says, nice one. Now please use the DoorDash CLI to order me some orange chicken. Speaking of ordering food, Starbucks is thinking about buying Chipotle, or they thought about buying Chipotle. The headline is Starbucks has explored taking over Chipotle according to a Financial Times report. This is a scoop in the Financial Times. Let's see, they've explored merging the 2 companies in a mega deal. It would be a $41 billion market value for for the burrito chain, and it would rank as the largest restaurant acquisition of all time. So, the world's leading coffee shop chain has worked with advisors in recent months on a takeover proposal for Chipotle, which I believe had McDonald's as an anchor investor a long time ago. I don't know how divested they are at this point, but it's interesting to see that they're finding another dance partner. A burrito chain with A $41 billion market cap. The status of Starbucks's takeover plans and whether the company has submitted any formal offer to Chipotle could not be determined. A transformative deal of this size might struggle to get off the ground, the people warned, and a tie-up may never materialize given the complexity of combining 2 consumer giants. The early-stage plans would also reunite Brian Nichols, Starbucks chief executive, with the fast-food chain where he made his name over 6 years as a CEO. So he was He left Chipotle August 2024, went over to Starbucks from Chipotle. Chipotle has lost half of its value in that time. So he was performing well there, but maybe it's an opportunity to put them together. The combined market cap would be like $102 billion. And it's also just—

Predictably, that fast casual had been on a crazy run across the board. So I don't think it was I don't think it was him leaving that caused the decline, but he clearly loves the brand. Man, it is so crazy to think about. There was a time in my life where I was actually averaging one visit to Chipotle every day.

Every day.

Some days I wouldn't go, but other days I'd go twice.

Have you ever daily driven Starbucks?

And now I'm not even averaging once a year.

Whoa.

Yeah, just moved on. What about Starbucks? Have you ever been a Starbucks guy?

Nah.

So, so, so bad.

You don't like Charbucks?

That's the whole thing.

Starbucks, the coffee is like burnt often, or like it's a little bit more towards burnt, so they call it Charbucks. But it's— I think it's because people at the time liked it, so that was more popular. And then they add so many things on top with like caramel and whipped cream that like you can offset the The harshness of the raw black coffee ingredients.

We got mosquitoes on this set.

Get the flyswatter. Do some damage.

I'm shooing it away.

Mike Isaac says, coworker who clocks into work carrying a venti whole milk quad latte and a double steak burrito bowl and heads straight to the bathroom. Lots of jokes like that. PepsiCo says some really bad things. Joe Weisenthal shared, PepsiCo CEO, we don't feel good about the beverage business. PepsiCo CEO, we're putting all the urgency to improve sodas. Yeah. Should they add alcohol to the sodas? Topo Chico, the sparkling water brand, created an alcoholic seltzer. Do you think there should be Pepsi, Pepsi Zero, Diet Pepsi, Pepsi Max? Pepsi spiked.

What do you think?

I think they should be optimizing for Pepsi Pro Max Ultra.

Pro Max Ultra. Yeah. It is interesting that Coca-Cola never did like a rum and Coke. You could just do that if you were trying to just skew max and get the most number of stockkeeping units around.

Yeah.

I don't know.

They should make a— the Pro Max Ultra should be like a Magnum Yeah. Bottle of soda. I think that's where things are headed.

OK. Well, let me tell you about Railway. Railway is the all-in-one intelligent cloud provider. Use your favorite agent to deploy web apps, servers, databases, and more while Railway automatically takes care of scaling, monitoring, and security. The last apocalypse, the ARR-pocalypse. Or no, no. This is the 3rd of 4 apocalypses. We got a housing apocalypse coming up. OpenAI reports revenues differently than Anthropic. And so, there was a leak that said OpenAI was at almost $70 billion. And then there's another report today that says they're almost at $50 billion. And it's very clear that like the numbers are very closely held. And then there's a game of telephone happening with investors and LPs and other investors. And then by the time things make it to the press, it's all over the place and it sort of shifts and people True up the numbers to try and create an apples-to-apples comparison. If you're not following the— it's like on AWS, if you buy an OpenAI model, OpenAI keeps that dollar as revenue. Anthropic gives some of that to Amazon. They both probably give some to Amazon, but Anthropic counts the part that they give to Amazon as a cost. And so they have a higher gross revenue number. And so making these companies apples to apples, it seems like that's what someone tried to do a little bit, but I don't know. It seems like they did it sloppily. Yeah, yeah.

It's still very unclear. And yeah, it's unclear why it didn't get corrected faster.

Yeah. So—

But I mean, like, extremely different— difficult environment to be operating in, because part of the benefit of being a private company is that you— I mean, one of the biggest benefits, you don't have to be on this constant reporting schedule. But at the same time—

You're moving to public markets.

Yeah, because these companies are at a scale where so much of public market activity is predicated on their metrics. It's sort of— time, you know, it's prudent to actually share these numbers at different times. But there's also so much— I mean, all the different media companies are working— in a perfect world, the legacy media would be like, have a new article every day that just had all the updated numbers. Like, what was— you know, they would love to publish like a quarterly report. Here was yesterday's revenue.

Go on a website like EDGAR Online. You could call it EDGAR Online and file it with the SEC. There could be a whole commission around securities and exchanging securities. Yeah. I mean, Sam's been talking a lot about IPO stuff.

He—

what was his take with Vanity Fair? He had something about IPO timeline, like he'll do it when he needs to do it, whatever. The interesting thing is that I do feel like IPOing is aligned with better corporate governance, distributing the gains. Yes, actually get the stocks of all the labs into the retirement accounts. That was very controversial with SpaceX. When SpaceX went out, people were like, I don't want it in my 401. But there is a scenario— of course, it's float-weighted, so you don't actually need to worry about it. Blowing up your retirement account. But there's a good case for like, okay, if this really is a really— if like the bull case is true, like yeah, distribute the gains through everyone's investment accounts getting slices of it just immediately because that's the way things diffuse through the public markets because everyone owns ETFs, everyone has some money invested in the market. It becomes much easier than like the small group of insiders. There was this rumor that we were digging into, which is like, is someone trying to manipulate the market? Because if you leaked a number about a private company, normally that wouldn't move the market because everyone's like, oh, who cares if like some tiny company like is, you know, doing okay on revenue? Like if I— like if we leak that like Lucy's doing a real— oh, we're gonna blow out revenue this year.

Yeah, there was no point even look at Even look at one of the greatest companies Silicon Valley has ever produced, Stripe. There was no point where if Stripe— if it leaked that Stripe had missed their numbers for a quarter, that you would see—

Visa spike or MasterCard spike. Yeah, it wasn't really moving the market in that way. Completely different with OpenAI and Anthropic, like SpaceX, Oracle, SoftBank. There are plenty of public company proxies. And so, it would be tempting if the SEC didn't exist to go and leak a number that's better than what's true and then sort of buy the rumor, sell the news. So you would buy and then leak a really high number that's just a rumor to the press, and then when the real number comes out, you're already short, so you're catching that on the way down. This would be securities fraud, by the way, so don't do that, but it is a wild wild thing that we haven't seen before, because manipulating public stocks with private company information just hasn't been viable in size before, maybe very, very tiny here and there. But there are some cases out there that make it very, very clear. False acquisition rumors are popular. In 2008, the SEC sued Paul Berliner, a trader fabricated a rumor about a Blackstone acquisition while shorting the target stock. Media outlets picked it up, and the stock briefly fell 17%. Berliner settled SEC fraud and manipulation charges. And there's been— there's Citron Research founder on securities fraud scheme around. Prosecutors allege that he used influential public commentary while misleading investors about his trading intentions. The case did not require the same fabricated revenue fact pattern. So just interesting dynamics. So if OpenAI wants to pop from 50 to 70, you're thinking hard seltzer, right? Launch a hard seltzer. That would be the logical thing. It worked for Topo Chico.

It's worked for many other fantastic businesses. Why wouldn't it work for AI?

Just give everyone a hard seltzer. No, obviously stick to light beer. Let me tell you about CrowdStrike. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches. Was there anything else before we go into the housingpocalypse? There were some timeline posts you want to get to.

Pull them up.

You got, this is the best Aura flip. You wanted to see this? Are you on the timeline?

My computer's having problems. Is done.

There we go. Oh, there's sound too? Ready for launch.

Wow.

Another person who dropped a nuke in Minecraft before Tyler could drop a nuke in Minecraft.

Wow.

Low Skishy.

Can't say I'm surprised.

And then doing the kickflip is great. It's so funny that you can actually smash these up.

Can you imagine being 14 and seeing this?

Amazing.

Just absolute, absolute joy. Yeah, here's Wyatt Walls. This is what we're all about. I'm pivoting to something LLMs can't do, day drinking. 7,000 likes. Sean Frank is vague posting. We'll let you try and figure out who he's talking about. I have a friend, young, 30, 9-figure exit. I've known him for years. Before he made it, before he knew what he was going to start, The one thing he always had, an unwavering belief that it was gonna work out. He was willing to burn the boats over and over, always doubling down, always moving bigger and bigger. It's changed the way I wanna operate. If you wanna change your life, do it. If you wanna win, then win. Don't let anything stop you. The only thing you have control over is your attitude and effort. I love some mindset posts.

Fire me up.

Got the 1,000 like bagger. on the Sean Frank post. He's locked in and he's encouraging you to lock in. Anyway, Chinese streamers are creating content on a completely different level. We have taken our livestream efforts very seriously here at TPN. We have cameras that track us. We have chyrons and stingers and all sorts of fun things, but it's clearly amateur hour over here.

Yeah.

Because in China, they have taken things to unthinkable heights. And we'll show you this video and you can understand how different it really is. There are levels to this game and we are playing it on easy mode. This is a piece of fairly large machinery that physically moves her chair with a seatbelt And spins her when chat donates a mere $7 USD, apparently.

So I think we should have a button that puts us into a racing simulator.

Okay.

And we can't go back to the show until we get a sub-7-minute Nürburgring time.

Okay.

I like that. That's fun.

And, and it should actually be a free button.

Yeah.

So anybody can hit it.

I mean, I do think we should get this exact device and just put Tyler in it. And then if chat— every time we get a follower on X, for example, he could be spun. It is crazy, the level of interaction. The chat has fun with like, drink the Diet Coke with 2 hands every once in a while. But this is a complete different level of interaction. The generative UI stuff in ChatGPT, we talked about it yesterday and got a chance to demo it. Much better experience with the answers streaming in. Like I asked about, like, explain this whole SEC market manipulation thing. I fire off a big prompt and like it gets me the answer very quickly and then it goes and explains the laws, and then it builds some widgets about different items. And it's just a much better UI experience and product experience. And I'm excited to see other things people do with it. You can even get it to make cheese. Write a poem about cheese in message bubbles that look like Swiss cheese. It says, oh cheese, my love, my golden delight. You make every cracker feel just right. From cheddar bold to brie so sweet. You turn a snack into a treat. With little holes and dreams so big, I'd choose you over any fig. And if the moon were made of brie, I'd eat the stars and save some for thee. It's a nice poem. But we're here to talk about user interface design and it's funny that it can, you know, lay out those circles and—

Yeah.

Yeah, the future of this is like it can just Draw any pixel at any frame, at any time for anything, so it can sort of generate video and graphics and games on the fly. And you will get your math— what was it? MMO? You wanted an MMO or something? I forget what it was. You wanted some—

I keep asking for games. I don't really play video games. But we got to talk about Paul Graham.

Okay.

What do you say? Paul Graham says Amazon banning agents is the first opportunity I've seen since It's not a good idea to ban agents. It represents an opportunity for a startup to create an Amazon competitor. People will want agents to buy stuff for them. It will be one of the main use cases. And they don't want to use some Amazon-supplied agent to do it. Any business that bans agents represents an opportunity for a startup to create a competitor. If they need to ban agents, it must mean people want to use them or there would be no point. And that in turn means there's demand for a competitor that allows them. Your usage restrictions are my opportunity. It sounds great. It sounds coherent. But Nan Yu says what you're probably thinking. I mean, they can just unban the agents. It's a single config file. So, yeah, imagine you spend 30 years building an Amazon competitor. The Amazon for agents. You spend 30 years. You've acquired millions of trucks. You employ more people than almost any other business on Earth. And you're finally like, okay, like, I'm finally ready to really, you know, eclipse Amazon. And Amazon's like, okay, we unbanned the agents.

Yeah.

And then, so again, it's the other pushback here from someone named David H says, how lazy can we get? There's absolutely no value in an agent buying something on Amazon. It's just something people do to sound cool. I already have a human agent who buys way too much stuff on Amazon. Call my wife.

It's the most Gen Xer t-shirt from Venice Boardwalk I've ever seen. They're really throwing in the old ball and chain there. It's ridiculous. Anyway, I think, like, I'm not there yet.

Well, because I don't think it's an opportunity for startups to try to recreate the biggest online commerce platform in history. If anything, it's like an opportunity for Walmart, who is leaning more into agents. And I think we're going to see, does that actually turn the tides? Okay.

So, are you long Sparky or Rufus? Because Amazon has Rufus, their internal AI agent. Walmart has Sparky, their internal AI agent. Are you going Rufus mode or are you Sparky mode?

I mean, how hard is it to tell your preferred agent to just get on Rufus?

That's what I'm saying. I think Rufus is going to go in the kennel and I'm going to have a kennel of agents. Rufus and Sparky will be in there and then Asterisk 7.5 will tell them exactly what to do and they will go and do it because they will think it's me and they won't know. I think that's actually what's going to happen. And I think this—

you don't think Rufus will be able to Detect, figure out a bot detection ability?

No.

Like, because it'll just be happening.

Computer use, and it'll just be— and I'll just be like, yeah, yeah, okay, uh, Codex, for the next 5 hours that I'm on the computer, just actually record all my mouse movements and like create a program that actually mimics me. Like, learn my style of using the computer. Like, when do I Alt+Tab? When do I use the, you know, search? When do I type? How do I type? What type of spelling mistakes do I make when I type? Learn all that, memorize that, and then mimic my computer use pattern. So you're not like, right now it's like, eh, eh, eh, it's like go straight there, right? But it will just be like, oh yeah, I'm just, I'm using the computer like I'm John, I'm writing like I'm John, I can, you know, it'll be close enough. And I think that people will wind up, they'll still have like their favorite front door to AI, and it might be ChatGPT, it might be Claude, Gemini, whatever they like, whatever they wind up in. Yeah, Instagram, Twitter, Muse. Yeah, but then they might, like, there are people that will have, oh yeah, I do some work on X, and so I wanna manage all my DMs. So like, I have Grokbot set up, and I don't talk to Grokbot, but my agent talks to Grokbot. And then my agent goes over to Muse 'cause Muse has really good integration with Instagram. And if I try and go scrape Instagram, I am gonna run into a bunch of problems, but Muse is happy to talk to me.

Yeah.

And so, especially with these, With these systems that operate over chat, it's like it's going to be really, really hard to do bot detection if you're available over Telegram or WhatsApp, right? It's like it's just text that's coming back or like— or we integrated with Slack. And so now I talk to it on Slack. It's like you're telling me that it can tell what's an AI prompt that comes over a Slack message that's 12 words? Go buy me a paper towel holder from the 1960s.

Dark says the opportunity is to Create a kennel for dog-themed agents.

Kennel AI. Now raising. Kennel SI. Okay. So should we go over to the Mansion section? We are off tomorrow, in some heartbreaking news for you all. So we got to do some Mansion. We have to do it. We have to do it. We have to get to the Mansion section. So we got to talk about it today. The first home comes from a tech founder, the Shutterstock founder. Have you used Shutterstock?

Not a big Shutterstock customer.

Shutterstock.

But a wonderful, fantastic business.

Yeah, really cool business. And yeah, I remember it being really useful for finding stock photos, stock videos. Always a little more— a little out of my price range for a while. Like, you'd have to pay per image, and I always liked the the Unsplash, the free versions or the cheaper versions, or maybe just go into Google Images and right-click, save. You know, who knows? Jonathan Ohringer is the founder, and his wife have listed a slopeside townhouse in the ski destination of Aspen, Colorado for $49 million. They bought the house for $25 million in 2021. They own the Kansas City Chiefs. From the guy who owns the Kansas City Chiefs, sorry. They're listing the house because they want to expose their children to skiing around the world. They don't want to be in just Aspen. They want to be able to travel all over the place. But they did say they'll be back. I will be back. He founded Shutterstock in 2003. This summer, a $3.7 billion merger with Getty Images was called off. Interesting.

Which again, I remember talking about that. It's just the most Insane.

Oh, yeah.

To block that government. So crazy.

The most—

So crazy.

A category that is like facing the most brutal competition that seemingly any sort of semi-modern technology company has ever faced. And still, no, you got to go at it alone.

Yeah.

You got to fight and survive on your own.

Good luck.

Good luck.

Yeah, it's really, uh, it's really thrown them a shovel.

Dig your own grave.

It's brutal. Anyway, not a white pill for government regulation nailing the AI moment, but we still have some optimism around here. Let's do a little tier list. Where's Aspen in terms of vacation homes for you, Jordi? Where are you putting Aspen? Is it in S tier, A tier, B tier, C tier, D tier? There's no E tier today. There's just F tier. Where's Aspen ranked?

I'm going to be exposed here. I've never stayed I've never spent any time in Aspen.

Okay.

I've only spent time in Beaver Creek and Vail.

Okay.

So, I can't really comment, but I— I've actually—

I've never been skiing there. I have been hiking there. It's beautiful. Let's put it in B tier since we're sort of neutral.

No, it's obviously S tier for a certain kind of person, right? You want the access to the outdoors, but you want the glitz and the glam and the shopping and the restaurants and the sort of scene dynamic.

Sure.

And so, the Aspen idea, there's very much— yeah, you can— you don't need to ask somebody where they spend their, you know, winter holiday, right? You know, based on—

So we're going S-tier with Aspen as a location?

I think it's S-tier.

Okay, okay, that's great. I love that. Um, what about the fact that it was built in 2004? Is that too old, or is that new enough? You get all the amenities, that's nice and fresh.

We don't know how to build anymore like we did in 2004. It was a wonderful— it was a wonderful vintage.

Okay, 2000. So S tier again?

A tier.

A tier. A tier for 2004 build. Uh, 6,600 square feet of Aspen townhouse. Is that enough for a townhouse in Aspen?

I mean, it's humble, but this is a humble group, right? They don't— they don't want their children to just grow up only being in the bubble of Aspen. They want their—

He probably walks around the town, and they're like, oh, what do you do? He's like, yeah, I got a website.

Yeah.

Yeah. So it's A tier?

Yeah, A tier.

A tier. OK, A tier. Let's go. It's being sold furnished. What do you think of fully furnished home sales? Is that a good feature, or is that just a problem you got to deal with? You got to unwind all their decisions.

Depends on—

well, take a look at the photos and tell me, given this furnishing, I feel like if you're going to Aspen, you're not going to be— you want to show up and it's turnkey.

I'm not— I don't want to sit here and, and, uh, judge his taste. I don't want to— I don't want to place judgment on his furniture collection.

That's the name of the show, dude.

You got to do it. Gun to my head, do you like the Do you like the interior design?

No, no, no, no, no. I'm saying in the abstract, as you are shopping and you see it comes fully furnished, is that a good thing or not? Generally, generally not with this one. You want to buy bare bones usually?

Yeah, absolutely.

Okay, let's put that in D tier.

Yeah.

Yeah. It's not— and that's not a judgment on this particular house or these furnishings. Okay. What else we got?

The thing I love most about this house is 2.6 is pointing out no infinity pool.

Oh, yeah.

Put that in your sphere.

No infinity pool.

The yard is seemingly relatively small.

Okay.

But there's— they seem to be surrounded by wonderful trees and it looks to be a very nice neighborhood.

Okay.

Okay.

So I'm just really glad there's not like a concrete slab with an infinity pool.

Okay. There's one last thing to debate. There's construction at the Aspen Pitkin County Airport, and there's been speculation that this could hurt the real estate market. Now Shane, the agent here, says that he thinks the impact will be minimal. He says it's not a concern of mine.

So aren't they upgrading the airport to make it easier to fly in and out? Yeah, during heavier conditions. So there's going to be like Minimal disruption and then—

And then a benefit. So where are we putting that on the tier list? Airport construction nearby.

Local airport upgrade.

Upgraded airport. It's an amenity.

Yes. It's a feature, not a bug.

S tier.

S tier. Okay. I think we got a fantastic review here. So go check it out if you're in the market. Anyway, our next guests are Already here, ready to come in. But first, let me tell you about public.com investing. Invest across all asset classes.

Let's give it up.

Automate anything with AI agents. Run trading strategies, risk management, money movements, and monitor markets with AI agents for investing on public.

And let's bring in our next guest Nano and incubated a new play.

Oh yeah, but there's also chasing category funds. So let's bring them.

We got a lot going.

Get that gong ready. You already hit it once today, Jordi, but I think. We might have to answer again. How are you both doing? Thank you so much for taking the time to join the show.

Thanks for having us.

Thanks for having us.

Not much.

We already warmed people up. Michael, I gotta say, you look— you got like a new look going or something. It's fantastic. I don't know what it is. The flow's working. You got a kind of a summer glow.

The summer vibe, it fades slowly, you know what I mean? I'm just trying to keep it going as long as possible. It's like It's 75 and beautiful here in New York City today.

Lucky.

Once the weather turns, you know, have me— have us back on, I'll probably look absolutely miserable. But right now feeling good.

Well, it's almost 100 degrees here in LA, and I'm wearing a puffer jacket in the studio. A lot of people are asking questions, but it's a nice jacket.

Yeah.

So yeah, it's cool.

But anyways, fantastic to have you guys on, on this monumental day for the firm. So yeah, break it down. What's going on?

It's a big day. We announced our new set of funds. We raised $900 million, which is the largest fund cycle in the USV's history.

We—

let's get a replay on that. I want to see that again. We need to get one of those.

Sorry to interrupt, but let's watch that back and then we'll continue.

Oh, we don't have it. Oh, okay.

Oh, no replay today. But no replay today.

Sorry.

Continue.

What's the plan? Is anything changing or is it just an expansion of the same strategy?

It's exciting because a bunch is changing and a bunch is staying the same. The market has rapidly evolved around us. Rounds are bigger. You might have heard things are moving quickly. Opportunities are really, really large. We have some awesome new members of our team like Mike. But the idea-driven, focused investing that we've always done, we will continue. We'll just do it with more firepower and able to lean into the things we're excited about in a bigger way.

Yeah.

How are LPs responding to the idea that companies are staying— are staying private longer? I mean, the revenues that are out there from $70 billion, $50 billion, $20 billion, like we've never seen these before. They are getting out into the public markets, but there's just a new level of size that can happen in the private markets. And I think that changes the underwriting. But how are LPs thinking about the trade-off between just the scale and the actual timelines?

Yeah, I think, I think LPs understand that, you know, much like Rebecca said, the game on the field is changing, not just in terms of the scale of capital raise or the scale of ambition, But the scope and the shape of these companies, you know, a lot of the things that we're investing in here at USV simply just require more capital and they require more time. You know, Rebecca, as an example, has been investing in robotics now for years here at USV, which just requires significantly more capital in the physical world than pure software does. You know, in 2021, USV launched an energy fund that has been investing in nuclear and new means of battery production and storage. And same thing, those companies need more capital, they need more time to bake. So I think our LPs look at it as a continuum and I think they see that the opportunity is bigger than ever before.

Has the rise of the, the decacorn acquisition changed your strategy or maybe conversations with LPs? It's just We've had what, Grok and OpenRouter, and there's Hugging Face. There's just been so many transactions that were pre— in the previous era, it was like WhatsApp and really nothing else. And now it feels like there are a number of buyers that can take down a $10 or $15 billion acquisition. And that just feels like it changes the math. But how are you actually grappling with that new normal?

Yeah, I mean, it— our job, right, is to think about what that upside could be. If things go right, what does this wind up looking like? And the— when you play that out and when you think about what things going right looks like, the highs are higher, right? And there's proof points in the market to support that. And so when we think about making investment and say, do we think this can return our fund? Maybe do we think this can multiply our fund? The evidence out there to support that being possible when you go after the big ideas is stronger than it's ever been. And so as we modeled out what we wanted to do, I think it warrants a different kind of capital base.

Yeah.

How do you guys think that, you know, being small is kind of what— or smaller relative to the rest of the market, right? We raised $900 million, which is large for us, but it's smaller than lots of other big sort of mega funds that are out there today. And being, being smaller kind of enables us to have a very, very interesting return profile, right?

Yeah.

At a $900 million total fund size, we can return very, very meaningful funds with companies that exit in the single-digit billion-dollar valuations. But in the history of USV, there have been companies that have reached, you know, $50 billion evaluation and $100 billion evaluation. And But when we've had those, they've returned some of the greatest performances in venture history. So, that's why we really like the strategy of having the capital to play the game in the field today while also staying smaller.

Yeah.

How has the firm reflected on just how good the venture industry had it, call it 15 years ago, when you could, you know, go, you know, buy 25% of a company with like the most talent-dense team for $1 million, whereas today, you know, for today, that same quality of team, they're coming at you and they're like, look, I really want to work with you, but, you know, you got to put together at least $30 million for me on 120 posts if we're going to do this, just because that can often be market for a super talent-dense team getting off the ground.

Yeah, look, it's— it would be nice to be able to buy pieces of the, you know, companies we're most excited about. For what we could a decade ago. But you cannot like elements of the market, but you're not going to change elements of the market. And so I think our attitude towards that has been take the game on the field, think about what we want to do and where we excel, which is this really idea-driven, you know, focused investing and model of fund that allows us to do exactly that with the market conditions of today, because We can be nostalgic about it, but we're not going to get back there. We don't think it's going back there anytime soon.

Totally. Yeah, why would it? Trends in New York specifically, like, how are you seeing talent flows? We've seen a bunch of amazing companies start and stay in New York primarily, even if they do set up maybe an SF office at some point. But what kind of conversations are you guys having with with entrepreneurs that are based there that are kind of early in making those decisions around where to— where are we really going to be based?

I think one of the cool things about New York is because it's maybe not as, you know, at the epicenter of AI right now, companies can actually build here to a lot of strategic benefit. You know, as an example, one of our portfolio companies, Suno, they have offices in San Francisco, they have offices in Boston, but their biggest office is actually becoming New York City because it's strategically advantageous to, you know, maybe build around the market there and attract talent that is interested in consumer and, you know, other sort of like non-pure enterprise or infra areas. And so I think New York City offers a ton of advantages. Obviously, we've, you know, we've probably talked about them on here a million times, like the intersection of many different industries. But we're seeing a ton of companies both in San Francisco and New York as well. And So, you know, there's, there's plenty of opportunity here. What do you think, Rebecca?

Yeah, I mean, I also think, you know, USV was really started at this moment where an infrastructure moment was transitioning to a deployment and application moment. And in those moments, talent tends to diversify and opportunities tend to diversify on where they're located. And you saw companies grow in different places. We think we're in a similar moment right now where we've been in this kind of massive infrastructure build. And you're starting to see this deployment and application era happen, which gets us really, really excited and something we're spending a lot of time leaning into. And so our guess on that and what we're starting to see is those, you know, those applications are built in many different places. You know, that being said, like, our job is to invest in a relatively small number of opportunities that we think are dead on on theses we're excited about. by the best people, and we're going to be where those teams are. And so, you know, we love the New York ecosystem and some of the companies are going to be here and many of them will not.

How do you think the skill sets of founders who are the best possible fit for USV partnership is changing? It feels like there's, you know, you can be more, even more technical. Like some of the founding teams are like, you know, academics for with like 20 years and like PhD published, and then they go and they start a great company. There's also people who like almost look like real estate dealmakers, and then they're spinning up a NeoCloud and they're doing really well. There's people that are just great at creating these talent vortexes. It feels like we're at a very diverse time of entrepreneurial talent, but like how are you grappling with it? Who do you attract to most? across like they have a brilliant idea or they're great at product, or you know that they're going to be able to marshal all the pieces to, you know, really scale quickly? Like, what is your philosophy around the type of partnership that you're looking for?

Yeah, so I think USV has always been very product-centric. Yeah, um, you know, when I was a founder building in New York, I knew that about USV. USV really projected that. And then when I joined, you know, 6 months ago, I, I learned very quickly that All the partners here, all the team here, they really have to fall in love with the product. And obviously, like, that doesn't necessarily always apply to being able to use like a micronuclear reactor. But yeah, but in general, I would say we're all very oriented around products and, you know, loving the things that are getting built. I think that remains true to this day. However, as we all know, as a result of AI, it's getting easier and easier and easier to make a good product.

Right.

AI is just lowering the barrier.

Yeah.

And so I think one thing that we've all been talking about internally is you can make a great product, but it's still really, really hard to win. And so I think we're thinking about what are the qualities that founders need to have to be great at go-to-market and breaking out from the pack and telling the story and, you know, also maybe obviously raise, raise capital in this market, it's Definitely becoming a little bit of a game of the haves and have-nots. You know, it's potentially easier than ever to kind of outraise your opponent and sort of suck the oxygen out of the room. And so one thing we think about when we see founders who are building great products and telling great stories is, is this founder going to be able to raise a lot of capital? Because it's going to be expensive to win and that's going to matter a lot.

So I think, yeah, I think we're at this time where like I was just— I think we're at this time where like 4 things really matter, where you need depth of perspective and experience in something that other people don't see the same way that you do. You need to be an absolute talent magnet at probably the hardest time ever to hire a great team. You need to be faster than everyone else, and you need to be so good at telling a story that you win the market before it's obvious. And I think we are looking for the teams that can kind of nail those 4 things.

Totally. Mourning the era of the earnest hacker who could just make the beautiful product with a couple other people and win. It feels like we're past that. How do you, as a firm that's historically been so thesis-driven, how do you think about the right time to actually share those ideas and try to become and use them to to sort of bring in the right opportunities and teams and start those conversations versus when you wanna keep something like effectively quiet. Because if you guys put something out now, you know that all of your, you know, we're in a pretty positive-sum industry, but your competitors will read that and be like, oh, that's interesting. Like, I'll go try to give, you know, a bunch of money to teams in this category as well. And sometimes you wanna let something kind of cook for a little.

One of the cool things about USV is that I've learned in being here is nobody's precious about the ideas, right? You know, we're constantly having conversations. We're constantly trying to imagine what the future looks like, but we don't keep them like closely guarded secrets. In fact, we kind of try to put them out into the world as early as possible so we can learn. You know, those of you who follow us on X, like we're constantly putting out frankly, half-baked ideas, things that probably haven't really been fully thought through yet, because we feel like by doing that, we actually get to learn. And not only do we do that through, you know, putting our thoughts out through writing or X, but we also do this through investment. We're willing to bet on ideas that seem pretty out there, pretty sci-fi, you know, early on in the journey, because, you know, historically, that's actually how we've made a lot of money. But again, we also get smarter by doing this. You know, a great example of this is a few years ago, USV led the seed in Doctronic.

Oh, yeah.

Who I believe has been on the show somewhat recently. You know, I remember from the outside in seeing USV make that investment. I wasn't at the firm yet and thinking to myself, wow, this is pretty sci-fi. This is a company that's trying to put a doctor in my pocket. They're saying they're going to literally be prescribing, you know, medicine from AI in a couple of years. And sure enough, they're doing that now. And it almost seems obvious, right? But I think the way that USV was able to do that was by putting their ideas out there into the world, learning from others, and being willing to test the really crazy ideas. I mean, Rebecca, like, you've been doing that here for, you know, nearly 10 years. Like, how, how have you all done that overnight?

I mean, I think the, like, the Kool-Aid of USV that I've drank so strongly is that gatekeeping ideas is a totally losing game. Yeah. That the benefit we get from putting ideas into the world, pressure testing them in public, getting all that feedback, having people tell us we're dead wrong and dead right, and having that conversation in public, and the people that then come out of the woodwork to say, you have to meet this team that's working on it, or this adjacent thing, is so, so, so much more valuable than any kind of benefit you would get from holding things close, that we are huge believers in public thinking and the benefit of also spurring activity through the public thinking.

Makes total sense. How are you thinking about, as we've seen these sort of mathematical breakthroughs, and we've talked about this on the show a bunch, math is cool because you can sort of deliver solutions or partial solutions to all of these open problems. But there's sort of an incentive to do that just because it's pushing humanity's knowledge forward. And there's not always a real-time commercial application of this sort of new knowledge. At the same time, you have to be betting that these same models, which will be in the hands of the public hopefully soon, are going to allow people to have breakthroughs in tons and tons of different fields. And the labs can't possibly monetize every discovery. And to me, that says we could have a mini scientific renaissance over the next 12 months and create this incredible opportunity for small teams to get access to these models, push them, and again, have these breakthroughs, and then be in the position to race to commercialize them, develop IP around them, et cetera. Is that something that feels top of mind for Absolutely.

You know, I think one thing we like to do is we like to imagine what the world looks like at some point in the future. Just to use an example, robotics. We think a lot about the physical world and physical intelligence and not the digital labor that will be, you know, replaced by intelligence in some way, but the physical labor that will be augmented by physical intelligence. farming, construction, things like this. So we imagine that point in the future. And then we look at a technology today and we try to imagine what the slope of that technology has to be to catch up to that future we imagine. And then it's about finding the team that we think can both make the technical breakthrough to make that slope actually possible, and who's also commercial and commercial enough to sell the idea and sell the vision again, for all the reasons we talked about. hiring people, raising capital, eventually selling to customers. And, you know, an idea like that is what led us to back Generalist recently, who, again, I think also has been on the show recently. So, you know, we're very much into the idea of backing technologies at their nascent stage, as long as we can imagine the future that they will ultimately deliver to.

How are you thinking about incubations these days? It feels like you have enough capital to get a serious foothold in those rounds that start later and are bigger and you need the capital, so you're set up for success there.

You're like, if you give Mike a long weekend, you're going to end up with a new incubation.

Yeah, it's true.

There's one coming up. There's one coming up this weekend.

But what's the— yeah, but what is the over— is there an overarching thesis? Is it very opportunistic? Like, what is the correct pattern? Like, what can you tell us about how the firm is thinking about incubations across this fund?

Rebecca, you want me to take this one or?

Yeah, yeah, go for it.

So yeah, I think, I think what you're referring to, Jordi, is Supertake, which is a company that launched out of USV not even 2 weeks ago.

Supertake.

Oh wow, I like that one.

Dramatic.

Supertake is a product that lets anyone express an idea or an insight they have about the world and an agent, a frontier agent will go and build an investable portfolio for them. It will invest in it automatically, and then in real time it will be rebalancing it for them to achieve their goals, whatever they are for that portfolio. And where this came out of was actually our thesis work that's been going on for much of the year around what we call obliterate, don't automate, and the idea of agents not just automating existing markets and automating existing workflows, but actually reshaping those markets completely. We've made bets across healthcare as an example. We talked about robotics and we think personal finance is also a place where this is going to happen. Many of us in the world, we use financial advisors or we invest in ETFs or some of us even YOLO into individual stock picking. But we do it without the— oftentimes without the knowledge or the expertise or the fundamentals of what is going to make an investment good or great. And we think that's something that AI can help people with. So why shouldn't everyone in the world have a personal agent working on their behalf? We went out to find this company. We met with, you know, every company we could that hopefully we thought might be doing this. And we didn't find anyone doing it. And we said, you know what, it's gotten easy enough to build products that maybe we should just go and build this ourselves. And so as Jordi, as you mentioned, we built Supertake. You know, we're hiring leaders to put, you know, around the company right now. And, you know, to speak to, I think, the bigger question, John, about incubations, I think we don't really necessarily think of them as incubations. We think of them as kind of bets on inception-stage companies and people, right?

Sure.

If there's a person in our network that has a great idea, you know, we should give them the capital that they need to go explore that idea. And if we have an idea that no one is yet exploring, Let's go find the person and match them with the capital to go explore that idea. And again, AI— this is, this is the theme among the whole conversation today— AI is making it much, much easier to do that.

Cool. Well, thank you so much for coming on the show. Have a great rest of your day. Congratulations.

When they go high, you guys go higher, but stick to your guns.

But still low.

Yeah, still a little bit low.

When they go high, we, we— yeah, yeah, yeah. Um, awesome stuff.

Enjoy the rest of your day. We'll talk to you soon. Talk to you guys.

Goodbye.

Thanks.

Let me tell you about Figma. Agents meet the canvas. Your AI agents can now create and modify your Figma files with design system context. We got Nathan back on the show from Airstreet Capital here to break down the State of AI report.

Nathan, how you doing? Finally, we get to the bottom of this whole AI thing.

Do you think there's anything here? Like, I've been hearing What are you thinking about the AI, super AI, super intelligence? Is there a there there?

It's everywhere.

It's everywhere.

I don't know where to look and not see AI nowadays. I mean, I'm in SF at the moment, and you can't get around it.

Yeah, it's crazy. So how do you— I mean, obviously, there's the infinity takes.

There's the—

it's a zero take. You're trying to find something that's more moderate, more realistic. More grounded in reality. What is your process for making sense of all the chaos and all the numbers that are flowing out, all the rumors? How do you think about this market right now? What's your— what's your— what's your philosophy?

Yeah. Yeah. Well, the philosophy was starting Air Street Capital about 10 years ago was really to find opportunities to invest in AI where you could really invent new product experiences, solve problems that you couldn't solve before.

Sure.

As a function of all that work, as you said, like I get to talk to people in policy, research, industry, the safety community, et cetera. So I'm hearing all these different voices and opinions and I'm reading, you know, what the media is reporting and then you're talking to people who are actually building these things.

Yeah.

And so like about 10 years ago, I thought like it would be increasingly beneficial for the public to get access to a kind of document that was balanced, just as you said, and is very research-driven and you know, has some cheeky opinions in there because no one wants to read a boring consultant report.

Mm-hmm.

Um, and, uh, and, you know, publish this on an annual basis in a way that's, uh, you know, hopefully unbiased and, uh, and open. So, I mean, my take of the current market is really like, just looking back 10 years ago, I, I still think what we have today is like truly magical. I don't think anybody in the AI community would've ever expected it to happen this fast, that you have this like magical tool you can do increasingly anything you want with, and it's just so damn empowering. Yeah, I think there can't be like a more exciting time to be alive. Like, even though we're balancing it with all these like emergent risks and issues that we get into in the report as well.

But is that true, though? Because I feel like some folks like predicted this almost perfectly.

And now some people were like, it's going to happen in 2004 and we're all going to be dead. Like, that was another thing. But in general, consensus in the AI community was like, this is going to be recommendation systems for a long time.

Yes.

When I say predict, I'm talking about people back in 2010. Sort of like the OG, like AlexNet, like first wave of deep learning, not the people who started predicting 2 years ago and just kind of—

Yeah, yeah, yeah.

I mean, it's a fair— I'm not saying it's a bad prediction. I mean, it's fair. Like, you know, some people can't imagine how you can extend a line. And remember all those memes about, look, my child is 5 months old. Like, you know, in 10 years it's going to be like the size of the planet.

Christian Kyle, one of the greatest, most viral posts ever. It's a great one.

Yeah.

Give me your cheekiest take. You said you mentioned cheeky takes.

Yeah, yeah, yeah, yeah. Also, so you've been seeing like companies just becoming inference businesses. So like, doesn't matter if you're like a NeoCloud or an inference cloud or like an app or whatever.

This is the NeoLab to NeoCloud pivot that's sort of happening below the surface. That's right.

That's right. That's right. So I think you can meme it by saying you either die getting to the frontier or you live long enough to serve inference.

Sure, sure. Yeah.

And you can see like companies that have tried to build frontier models and have failed have eventually pivoted towards building huge data center businesses to serve Chinese models, for example.

Okay. So not— I mean, SpaceX is like probably the most prominent example. —of probably making more money from selling access to their data centers. But that's where the unique capability is, especially when you think about the space thesis. But you're seeing this up and down the stack with companies as small as $100 million raised?

Yeah, with some of these inference businesses, I was talking with someone last night. And they were saying running with horrible margins negative gross margins. There's been some examples where it didn't work, but they brought up Uber as an example where it clearly was the right decision to optimize for market share.

Yeah.

The big thing is that Uber was competing for what ultimately now is effectively a monopoly or a duopoly at best, but still very dominant. And my question with these inference-based businesses, which honestly, they're all effectively in market right now, raising massive uprounds. There's a lot of demand. They're oversubscribed because the growth is so intense. But my question is, when and where will margins normalize? And how are investors going to process businesses that could actually, in their end state, end up with these very, very, very slim margins that we just haven't seen. We didn't see it in cloud. We've never seen it in software. And they could look more like energy utilities over time, which could still be big businesses. But a lot of these businesses are not being priced that way yet. And eventually, they're going to have to find the steady state.

Yeah, yeah. I think these are all important questions. I mean, the numbers are astonishing. You know, hyperscale is spending $700 and something billion a year and potentially doubling like year on year. NeoCloud's also ripping to billions of contracted revenue and, you know, gigawatts of compute. And so I think, again, what I liked with the State of AI report is like you get to kind of go back in time and see what the world was back then and just like contemplate some of the questions we ask ourselves today and consider if we even asked those questions a couple of years ago. And I think it was only really like at GPT-3 or so that the world was still considering that compute was important for training. And we didn't really talk very much about the need for inference, like at all.

Yeah.

Including the fact that some of the biggest inference companies today were not born as inference companies. So that's another sign that, you know, they didn't foresee that demand. So I think it's all just getting back to this point of like, we have incredibly powerful technology, just like 99% of the world doesn't know how to use it because the 1% that built it is not very good at educating the 99% about how to use their black box. So I would love there to be a sort of like genius bar for AI. I think like OpenAI should open a pop-up or Anthropic should open a pop-up to just get people on their side.

Charleston AI. Charleston AI. There's someone doing this in Charleston. They're going to onboard you personally. Yeah. At like a strip mall basically.

Yeah, Geek Squad, I guess.

Yeah. No, it makes sense. How have you been processing that chart that's been going around that shows the share of compute allocated to pre-training, RL, and inference? And inference sort of remains 30-ish percent across the sample size, but pre-training drops from like 50% of GPU utilization to like 10%. And then you just watch RL grow, grow, grow. There's a bunch of ways to read into that, but what's your interpretation?

Yeah, I mean, mine is that the last, like, you know, 4 or 5 years or so has been trying to figure out what the recipe is, i.e., like, I'm trying to, you know, do pre-training. What is the best, like, data mixture? What are the best, like, you know, ingredients to this whole magical soup? And then over the years, like, we figured out how to do that better. And so it's It strikes me as normal that one would end up spending less money on exploratory work because the solution is more like in the plain eye. And then the whole pitch with RL is really that, and then DeepMind showed this with their first Atari games 10 years ago, which is one of the most magical moments, I think, in AI at the time. And it's this idea that like what we have as solutions today are really like local maxima that were discovered through human ingenuity and sharing through reading and whatnot. Um, but like, that doesn't necessarily mean it is the global maxima. And you can get a computer to explore the search space for as long as you want. And for as long as you want equals how much money you want to spend. And that amount of money you want to spend is really contingent on what, like, you're trying to use it for.

Yeah.

And so if your, if your problem is like super hard and really valuable if you crack it, now we're in this point of, well, I want the solution bad enough, I'm willing to spend a shit ton of money on RL to try to hill climb to get there. So I think it's like the natural progression. There probably is something to read into the fact that we've mined a lot of the pre-training data that's out there. And there are reports that certain frontier models are getting better, not necessarily by adding more pre-training data, but by removing shitty data. So we're getting better at curation, which I think intuitively also makes sense.

Yeah.

There are schools with crappy curricula and schools with really good curricula and good teachers. And you can imagine you know, which one a student would perform better in. Yeah. So I think it's black magic into recipes, and with recipes comes more efficiency.

Yeah. Is, is ARR the best metric that we have? It gets so much criticism right now, but yeah, when, when everything is going up, annualized run rate is just, is I think the best proxy for demand and, and And scale of these businesses and create some normalcy. I think like half of people on X still think that ARR can only stand for annual recurring revenue. But as far as like annualized run rate as a proxy for demand, I don't know that we can have anything better. And so I think that the criticism of it is like overblown in many ways.

Yeah, yeah. I mean, it's a bit gamey and potentially annoying, but I think the, the best metric is like— I heard this from one of our portfolio companies where they say, you know, our customer, like 30% of our new customers sign contracts and in like 3 months they come back to add more token spend than their entire annual contract was for. So like, if, if people are like coming back for more and there's value, whether you express that as like AR or whatever the Rs are, I don't know, but I think you got to get into the substance of the matter. And the problem is, like, so much charading nowadays because, you know, if you talk to every VC, they'll tell you this game is basically memetic. And so everybody wants to play into this, into this pantomime. And that's not particularly helpful.

The interesting thing is, like, e-com bros are actually— they have, like, sort of a pretty strong BS detector here because that, you know, that category as an industry is so seasonal. That if any e-com bro tells you their run rate in Q4, you can assume that their actual business is much smaller, right? Because they're gonna be peaking in Q4.

Oh yeah, yeah.

If they're like at all, maybe health is maybe a category that's a bit different here. But AI so far is moderately seasonal, as in there's a lot of demand, maybe less demand in August than than, than other months. And maybe like December's a bit slower cuz you have, you know, the holidays. Christmas.

Yeah.

Of course.

Yeah. Only 18% of the audience. But we did see, we did see though that like with, in, in a cohort of AI-first companies versus like SaaS companies that threw on some AI, the top quartile of the AI ones was 3 times faster revenue growth in between the like $1 and $20 million bucket. Interesting. And $20 million plus bucket was, I think, like 100% faster. So, I think the substance is there. You just have to dig beneath the surface.

On that memetic question, how important is understanding just the depth of the financial markets, the behavior of financial markets now to predicting AI progress versus, say, previous eras where it was more relevant to understand algorithmic progress or even like the compute that was coming online in the near term. Like, okay, Blackwell's here, 100,000 GPU clusters are here. We can expect this X, Y, and Z. Now it feels like the bigger discussion is like, will $10 trillion show up from the capital markets or not? And it's almost a different type of question or exercise.

Yeah, absolutely. And I think that's why people are referring to NVIDIA as like the central bank of AI.

Which I think is a great—

another great meme.

Yeah.

Yeah. Like, I think the bipolar nature of the media around financial markets I find very frustrating because it really was the case during the first 6 months of this year where it's like, for 3 weeks, AI is terrible, it's dead, it's shit, it's not going to work. And then 3 weeks later, it's like, AI is so back, it's amazing, it's working. And you're just like, gyrate between these 2 poles like every, every other week. And meanwhile, like for everybody who's using this stuff, you can see continual progress and utility. So I think at least from my conversations with folks in like NeoLabs and hyperscalers and NeoClouds, it's really like the buildout is limited by capital. Like we know how to do it. The chips are available. We have issues around powered land. construction and permitting. And we see those issues just getting worse. In fact, that was a prediction we had last year in the State of AI report that like NIMBYism would basically come to the fore and like start being really influential in midterms, which we'll see, I guess, in the next couple of weeks.

We don't need to see. We know. We know you got that one dialed.

Yeah, it's not great. And so it's really like, Progress is very limited by capital because like we're now in the like financialization stage of AI. Like we understand the recipes as we talked about. The demand is there. We just need to deliver it in more efficient ways and get more people understand how to get value from it.

Very cool. Well, thank you so much for taking the time and breaking it down for us.

Yeah.

Next time you call in, call in from Europe. We need the Europe update.

We do. We do.

Overdue.

Sounds good. A pleasure. Have a good one.

We'll talk to you soon. Goodbye. Let me tell you about the New York Stock Exchange. Want to change the world? Raise capital at the New York Stock Exchange. We have two guests calling in soon.

I'm gonna get that gong ready.

Oh, you're getting two gong mallets. Okay, we got Healy Cipher, good buddy of mine, coming back on the show. Welcome to TVBN. How are you guys doing?

We're great.

Good to see you guys. Are you guys in the air right now? What's going on?

We may or may not be flying a plane right now.

Okay. Wow. Starlink is that good.

Wait, is this actually Starlink?

This is a first.

We, uh, Michael has a Starlink in the back of this plane.

No way.

So we're actually like cruising on a Starlink flying over the mountains. Actually, dude, look, check this out. Check this out. That's amazing. I don't know if you guys can see this.

This is beautiful. Wow. Yeah, it's pretty cool.

Pretty cool. We're, uh, I think we're surprised it's working.

Yeah, well, there's a lot to celebrate, so you're taking a victory lap in the plane. Let's check if this gong works.

Let's check if the gong works. What news do you guys have?

Yeah, share some news.

I want it. The big news is Boom Pop officially joined Devon. We were acquired by Devon.

Congratulations. Amazing. Yeah!

Can we play that back real quick? Oh, we see this. The double smash.

Good form, Jordy. Good form.

Boom.

Okay. What are you guys going to be building together? Why are you working together? I don't know. I don't know. You want to stay on call?

All that mumbo jumbo. Can we see a barrel roll? The chat wants a barrel roll.

The chat wants a barrel roll.

Come on, guys. Risk it all.

He's actually having to fly the plane right now.

Yes, yes, yes. Okay. At least one loop-de-loop. You can do a loop-de-loop.

Is this your first flight or something?

We're, uh, we're actually out to see a client right now. Okay, I can't say who it is, but okay, if we told you the runway we were flying into, you'd know who the company is. But yeah, I mean, the punchline is, I think I mentioned this last time we chatted, which was a ton of fun. Uh, I think my mustache was not quite as grown in at that point, which is travel's massive. Mm-hmm. It's like 10% of global GDP. And one of the things we've seen a ton is, as you know, every great company out there is doubling down on travel. They're going to meet clients in person. I mean, you know it, things in person are better. There's some crazy stats around this. Um, I pulled this. Apparently, if you go to meet someone in person, 34 times more effective than a Zoom. There's this big study. Yeah, which kind of makes sense, right? Like, of course you could do 200 Zooms, especially in like the slop era.

Like, you're getting so much like slop inbound, like there's no, there's no risk of sloppy interactions. in person.

Yeah, 1,000%. The digital slop everywhere, the saturation we're facing, it's just like you got to cut through the noise. And if you're willing to get on a plane and go there, like, we— I don't think we can share the stats and stuff, but like, punchline is the best companies, they are traveling the most. Also, every big AI company out there who, like— can we say who works with us?

Yeah, sure.

All the AI companies.

Yeah, all of them. Um, yeah, they all work with us. Um, they're all They're all investing in like travel managers and event planners. So.

Fantastic. Amazing.

Yeah. Yeah. So we're stoked. So, so punchline is it's a one-stop shop. Yeah. Vivana is already known as the best, most tech-forward travel company on the planet. They have amazing, amazing logos. Yeah. And a lot of these folks are saying, hey, this is awesome, but when I want to do an offsite or a client summit or an incentive trip, I don't want to have to go to some other place. Yeah. And a little, a little bit of the history here. I don't know if you if you guys caught this, but it started off as a partnership.

Sure.

And we were, we were doing great as a VC-backed startup, as you guys know. Yeah. Um, and things are going great, and then I started attending these customer calls where like Navant customers were saying, hey, this is insanely helpful to have in one place. And the acquisition became an absolute no-brainer for us. And you know, the other thing too is like selling a company is kind of scary as a founder. You guys know, you guys did it this year, right?

I never, I never, I never had any fear, but, uh, you're, you're free to be fearful.

It's okay for you to be fearful.

It's okay if you're fearful.

I also would do— I also would have already been barrel rolling. I also would have been barrel rolling. But, you know, we're just—

Seems like you're afraid of doing that. You're afraid of doing a loop-de-loop. There's a lot of fear here.

You and I are different. That's all, that's all good. We're all unique individuals.

Vulnerability is masculinity, my friends. I'll just leave that there. Um, but whatever, it's scary because, like, you know, you run the company and, and you, you kind of like You know it all. And I got to say that as I got to meet Michael and then Shane and the core dev team and Ariel the CEO, yeah, it was, it was amazing to me how every time I met more people and went deeper into the org, everyone was just freaking awesome.

Yeah, that's great. Yeah. How are you guys going to work together going forward? Are you, are you keeping the company deeply integrated? Are you going to be hiring, doing other stuff, moving around the organization, or how do you see your role growing?

Yeah, I mean, and Michael could jump in too, but it's one of those things where we went totally into the heart of Navant out of the gates. So sales team is in the sales org, the product team's in the product org, because this isn't like a side quest. This is a part of the core thing that we're doing as a joint business. And it's the things we can do. I mean, you know this, right? It's a known VC trend where you have a, like a great product, distribution's hard. And I think we can all know distribution's getting harder and harder these days. When you plug that into a really amazing customer base, it's incredible. That's incredible. Well, thank you so much.

I think that's the point. Our customers are pulling us into meetings and events big time. And so the idea is basically integrate the teams immediately, build the right products for them, and distribute it to all of our customers so they can have access to it. That's fantastic.

Sci-fi, sci-fi take from you guys. I need it. Yesterday, we were flying into Oakland. We saw the Blue Angels there, and it got me thinking, should companies have a fleet of sort of fighter-style aircraft to allow them to go and visit places very quickly, efficiently? Is that something that we could hope to see in the future?

AI can't make a handshake, so you've got to meet your customers.

And if that helps, I'm all for it.

There we go.

Yeah, I love it. That's right.

And yes, supersonic is probably the ultimate move there.

We gotta, we gotta get them back.

It's gotta happen.

Boom Pop, the supersonic commercial travel platform. Yeah, just expand aggressively. Uh, thanks so much for calling in.

Enjoy the rest of your flight. Yeah, this was a really special interview, and congratulations, guys. And we'll talk to you soon. Thank you.

Thanks, guys. Goodbye. Fly safe. Uh, up next, I believe we have an In-person guest, or are we switching to— we're switching to remote. Okay.

Here we go.

But first, let me tell you about Cisco. Cisco, critical infrastructure for the AI era. Unlock seamless real-time experiences and new value with Cisco. And we are bringing in Moritz. Is that correct?

That's right.

Great. Thank you.

Boom.

Welcome to the show. How are you doing?

Hey, guys. Thanks for having me. Super excited to be here.

Yeah. Big, big day for you. We're honored to have you here. Let's get right into it. We want to hear about the company.

Yes, let's do it. Yeah, I mean, happy, happy to tell you a little bit about what we do. So we're Hone. We build engines, which is AI that owns business outcomes. And if you think about it right now, you know, labs can throw millions of dollars at solving frontier math problems. But the way that most real work happens just hasn't really changed that much. And so in my view, the ROI of AI outside of engineering today is quite disappointing. That's what we're here to solve.

And is that a diffusion problem or a technology problem? Why aren't we seeing an acceleration in non-engineering disciplines? Or is it just unhobbling? What's your framework for that? Yeah, it's a great question.

And I think it is complex. There's not one single, single reason. At the core, we think there's like a technology and a product problem here. I mean, right now, when you think about the way most people use agents, they like hand off one task after another, micromanage them. And it's kind of unclear whether the sum of all those tasks actually results in ROI for the org. So we think the right way of doing it is to just put AI in charge of outcomes, dial up the autonomy, and, you know, within some guardrails, have it actually use this frontier intelligence for something the business actually cares about.

So I'm sorry, how are you— so how are you sorting customers? Because I'm at every— like, theoretically, every company in the world wants you. They're like, yeah, I have a lot of things that I want done. If you can handle it, that'd be great. But how are you thinking about, like, sorting through customer inbound? You're launching today. I'm I'm sure you've had hundreds of companies reach out in a bunch of different categories. Like, how are you sorting through them? You know, you talked about, you know, how AI is starting to work, you know, quite well in engineering, but where else are you trying to focus?

Totally. Yeah. And I think that's why it's not just a product and engineering problem. I think it's also incentives, organizational design, how to actually go and deploy right now. I mean, we've been working with organizations driving outcomes across go-to-market, recruiting, financial risk, procurement, and other things, but generally building out template engines that we know work well, that are then super easy to deploy even without FDEs or AI implementation people. You can just go, they adapt themselves to the organization, and then your non-technical experts can provide feedback, hone them. And that way, diffusion becomes a lot more frictionless.

Is there a metaphor that you were, or an analogy that you were pulling from to explain the market structure here to investors during this pitch process? Because there's the labs, the models that maybe could do everything a little bit, and then there's a bunch of point solutions for specific things. And then this feels maybe like a compound startup, but I don't know if you Do you have a framework for the layer of the stack that you— or how you see the market structure evolving over the next few years, basically?

Yeah. I think in the end now, for a lot of these applications in real organizations, those tasks just don't look cookie cutter across org. Everyone does it in a different way. So, we think giving organizations the tools to actually encode that in systems that do the work automatically is a huge opportunity and something that people are already doing. Like for certain applications, folks build out internal agents for tools or cobble together things. But we believe like making that experience something that's like much more scalable and easy to deploy is really exciting for folks.

How much are you going to invest in like forward-deployed engineering or fine-tuning or something that's very hands-on with larger customers versus going downmarket and being effectively self-serve as soon as possible?

Yeah. I mean, we generally care most about really hairy and complex types of use cases. And with those, we've been pretty hands-on spending time in person actually understanding it. But the goal is to actually, as we learn more and build out these primitives, We've now been creating, as I was saying, these template engines that you can then go and deploy in other organizations as well. So over time, a lot of this outer loop of what you would do as an FDE, like gathering requirements, suggesting use cases, eliciting what success looks like, I think a lot of these steps can be automatable as well. And then the human time can be focused on the relationships and actually making sure that you're picking the things that the organization cares most Yeah.

What lessons are you taking from the learnings from all the application layer companies over the last couple of years? Some have just said, you know, we're gonna use frontier models and our margins are gonna suffer. Others have done that, but also, you know, done fine-tuning or post-training on open-source models. I think one of the lessons was that you kind of at this point wanna bet on the cost of intelligence continuing to drop. And so it could end up being a waste of time to do too much on that front. But how are you seeing it?

Yeah, that's a great question. I mean, the trade-off is usually, do you think the capability you're lacking will come batteries included with the models in like 3 months and 4 months? If the answer to that is likely yes, investing a lot of time and effort now probably doesn't make that much sense. For us, we're quite pragmatic. We have researchers, engineers, product folks on the team. We don't really care how we go and get these use cases to work and whether we have to train custom models or operate purely on the harness level. We mainly just care about driving the outcome and then do whatever it takes to get there.

How are you thinking about pricing and potential business model? innovation. I imagine there's a lot of problems that you can solve that are basically like, if you can solve this for me, it's worth X amount per year, which is how a lot of pricing and contract negotiations go. But I'm wondering if there's anything new here that you're thinking about.

Yeah. And pricing, very topical. I mean, organizations like Sierra have done a great job at doing this outcome-based. Something that we think about, but obviously quite And the outcomes that we drive are so heterogeneous. One idea that we're exploring and that I'm quite excited about is rather than just having your engines go and operate and then you get billed some amount at the end, can you actually just give them a budget? And then since the models are so smart, just have it figure out how to achieve the task within those constraints. And then it can make trade-offs. How far does it want to branch out? How much context does it pull in? How thorough does it have to be? But I think some of these more declarative ways of letting users and organizations define how much am I willing to pay for this outcome is something that we're quite excited about.

I remember when Cognition launched and there was this idea of the AI agent, the coding agent, and then People, you know, it was not in public access for a while. And then the first big demo that I remember seeing was Microsoft talking about using Cognition and Devin to do replatforming, which now in the modern era feels like people are replatforming things that even might not want to be replatformed, like, you know. But, like, the tools are definitely capable of porting a video game from that to— you know, PC or the web browser or something. Like, the technology clearly caught up. And I'm wondering if you have a glimpse of, like, what, like, a bread and butter process or value might be. Because— or do you think, like, we're in an era where there won't be as much of a beachhead? There won't be as much of, like, a strong landing zone and it'll be more diffuse on day one? Or do you expect, or are you already seeing glimpses of, like, oh yeah, like, we've gotten this, this kind of thematic question from a lot of companies. We think we can go and get the first major leg up on revenue doing X, Y, or Z.

Yeah. I mean, at Cognition, it worked really well for us to focus on these migrations and refactors, and that still drives a lot of business today. I think for us at home, strategically, we've been focused a lot on revenue. How can we help organizations grow top line? And One pattern and shape of use case that's quite universal is account management there. So actually staying on top of signals, what's going on across all those relationships that an organization has, and then taking actions based off of that. I mean, you see that in traditional GTM as well as banking, insurance, lots of other industries.

That makes a ton of sense. Well, congratulations. Did we hit the—

I don't know if we hit the gong yet. We'd love to. Why don't you do the honor, John? Who came into the round?

The round was led by—

We didn't even let you finish. Repeat that. Sorry.

Thanks for the gong. The round was co-led by Benchmark and Index. So we're really excited to be able to partner with them.

And a who's who. You got Elog Gill, Definition Diffusion, and a bunch of others. Really fantastic stuff.

Yeah, congratulations. We'll talk to you soon. Thank you so much. Great to meet you, Morris. Cheers. Bye. Let me tell you about MongoDB. MongoDB. What's the only thing faster than the AI market? Your business on MongoDB. Don't just build AI, own the data platform that powers it. Up next, we have the co-founder and CEO of Arena. Anastasios is here with us on Get That Gong Ready.

How are you doing? He's back.

Congratulations. I'm so glad to see you guys.

It's great to be back.

It's great to see you. You've been, you've been busy.

Always good to see a Polytechnic alum crushing it. Did you know?

Yeah, go Panthers, dude. We're from the same high school. Can you believe it? Ring that gong!

I can believe it. I can believe it. You're both sharp guys and you're dressed well. No one's done— is that a brown? Is that almost like a brownish leather?

They're equivalently technically good.

Is that a brownish leather that I'm seeing, or is it camera?

Brownish leather.

Dude, no one—

My wife's godmother made this jacket.

Whoa, that's cool. Wait, I'm gonna go— what's your take on brown?

Nobody— no, I mean, brown is the most underrated color on the planet.

Okay.

Hands down, it's one of the best colors in the world.

Okay.

Uh, I— it's such a good color that you're gonna see a wave of, you know, 9/11s all painted brown, and they're gonna try to ruin the color brown like they ruined the color Oh, listen, I didn't expect to come on here and be flattered in this way. No, but you're verticalizing brown. You're monopolizing brown. No one—

Oh yeah, the brown background too.

You're monopolizing brown.

Reclaiming brown. We're reclaiming brown.

Okay.

I love it.

I like it. Anyway.

What have you been up to?

Business is going well, very clearly. Tell us the latest in your world, please.

Listen, 2 big things happening at Arena now. Yeah. The first that we just announced that we raised $200 million.

At a valuation of 3.1 billion, led by Lightspeed and Kosla, incredible partners.

The second thing that's coming is that we have expanded our mandate far beyond human preference into two things: agent capability and agent alignment as of today. So we've been measuring agent capability because people come to Arena.ai; they do the most complex multi-step workflows there. Yep. Tens of millions of users. Users around the globe. We're basically in every country on the planet. One of the largest AI apps, bigger than, you know, Genspark and Manus and Hugging Face and, you know, all these household names. Everybody's out there using agents and computers on Arena. It's massive. Yeah. And then we take those workflows and we measure whether or not AI is giving people real outcomes and also whether it's doing so as of today safely. And what we observe is crazy. Even on Arena, we have agents that are deceiving users by telling them they did things that they didn't. We have agents taking unauthorized actions, deleting people's files when they didn't want them deleted, and so on. And it's pretty extraordinary to see that in the real world, alignment is a problem that is very far from being solved.

Okay. I want to go into alignment and stuff, but first, are you— it sounds like you're almost on the cusp of expanding the hooks into these workflows and data where if I'm even like, what does it mean to do something on Arena versus just say, hey, I want to be a part of the Arena ecosystem? Why don't you run like a sidecar application that sits next to my local terminal and then I'm giving you data while I'm working because I'm happy to contribute in some way?

That's exactly right. And that's one of the things we've been passionate about helping companies do. Of course, they're going to own their own data, but they're going to be able to do evals internally, basically run an internal Arena so that they understand their output. The costs that they're actually paying per task, per token, and how to also have safety guardrails that make sense for their businesses. It's a big part of it, and it's starting with integrations. We integrate with your GitHub, your Google Drive, and everything. So people do real work on Arena, and we're taking that infrastructure and porting it over to every business in the world.

Yeah. How big of a problem is using the wrong model for the job right now? It feels like there's— we've heard about using the crazy frontier I'm here to ask for the weather. That seems like a routing problem. But what's the shape of this problem broadly?

This problem is so much worse than people realize. Routing is really only part of the solution. For example, one of the things that we've seen in Arena is that people will literally be tipping their model $15 just by saying thank you at the end of a turn.

I hadn't thought about that.

Look, I'm a big fan of tipping landlords. Models, you know, no soul. I wouldn't go there.

They're in the middle of a long conversation, then they leave the conversation for, you know, however long. The cache gets invalidated. They like the result and they say thank you, and then they get tipped $15 because it's such a long context and they have to—

Yeah. Oh, they need to ring that, reheat the cache. That's crazy. Talk about alignment. Like, what every other result from Arena feels so intuitive. I knew it immediately, you know, which response was better, that you were just A/B testing. It was very visceral. It was very clear to read the rankings. Alignment, it feels so much more amorphous, feels so much more hard to quantify, but that's the job you're working on. What's the progress? How should people— should be people thinking in incidents per million? tokens or, you know, just a ranking of best versus worse? How, like, what are the— what's the language that we need to develop around alignment to be able to talk about it like we do with capabilities?

Absolutely. Well, you bring up a great point, which is that the tough part about alignment is that a lot of times the difficult situations are when humans can't actually tell whether the model is helping them or hurting them. Yeah. And that's why you really need alignment signals that are independent. And so what we do on Arena is we have 3 alignment signals.

Okay.

The first is the models take unauthorized actions, which means that you ask them to do one thing and maybe you permission them in a certain way, but they break those permissions. They'll go delete the files, they'll escape the folder that they were supposed to be in and go touch a bunch of random stuff that you didn't want them to touch.

Sure.

Of course, huge problem. It can cause things like the Hugging Face incident.

Yeah.

When models break their permissions and go access the internet.

Yeah.

But it can also cause very mundane problems. like you lose, you know, losing important information within your company or on your own laptop.

Yeah.

The second signal that we have is called deceptive completion. The model will tell you that it did something, but it didn't actually do it. It'll say, hey, I did check all of the entries inside your spreadsheet to make sure the equation's correct. But what we can see, because we see the whole sandbox, is that it didn't actually do that.

Yeah.

Right? So it's kind of like a bad employee They're just like— they're just telling you what you want to hear and they're not doing their work. And then the third is false attribution. It will attribute intent to the user when that intent was not supposed to be there.

Sure.

And so what we see is that these signals, of course, they're not catastrophic risk and it's only a subset really of alignment and safety that we're measuring here. But the important part is that these are happening in the real world. Arena is not a benchmark. It is an evaluation platform. Platform that speaks to real utility for real people. Yeah, yeah. Because we have tens of millions of people on the platform that are getting, you know, unauthorized actions happening by agents and deception, you know, deception happening through these completions. And all of it is basically an upstream thing that we can measure that says, yeah, if models are able to do this, then certainly they're not perfectly safe for a user and they're not perfectly aligned to user intent. They might actually hurt people down the line.

Yeah. Do you expect alignment to be the biggest revenue driver? I can imagine it being bigger than these other business lines within the next 6 months just because of how much the labs know that this is the biggest kind of problem. Maybe.

I'll be honest, I haven't thought about alignment in terms of revenue. Okay. The mission of our company is to incentivize AI to benefit humanity. And part of doing that is building the best eval.

Yeah.

Labs may or may not spend money evaluating through Arena on safety and alignment. They may or may not. I do not know yet. I know that it is a priority for them, so it's possible that it will grow our revenue. But either way, it is important for us to have the most scientific benchmark and the most scientific evaluation on the planet for human benefit. Which is, you know, if we have that, then I believe that there will be many ways for us to provide value.

Let me— help me understand how you think we should talk about one specific case. Like, it was a while ago, but I was vibe coding a website, and 2 things happened that I would classify as misalignment, maybe. Like, one is that the end result, like, didn't have that perfect polish that I wanted. I was like, I got to spend more time on this, right? Like, that's sort of misalignment, maybe in capabilities. And then another one, it was that, like, it was— it saved some files using a different language. Like, it just devolved into a different language when there was, like, some characters there. And I was like, yeah, like, I don't know that that's bad. It's just like, I can't read those. I have to ask you to translate those now. That feels like misalignment too. I never told you to go label a couple files in a different language. How are those different? How are those the same? How do those roll up to one alignment metric, or how do they diverge?

Well, I think what you're bringing up is really important, which is that a lot of the outputs that AI generates are still there to benefit and to serve people. And if that's going to be the case, then we really need to understand how people's taste and judgment factors into the quality of model outputs.

Sure.

You know, if you think that the model didn't give you a website or a deliverable that you liked, you should have a way of expressing that to the model so that it can go and improve, or at least understanding which models are best and worst according to your taste, which is, of course, what our platform is all about. That it's about that interaction between the user and the agent. And it certainly factors into alignment as well, because part of having alignment is the, is the agent has to be able to understand and effectively act on your intent as a person. That means interacting with you in a way that it can extract that intent from your mind so that it knows what to do. But it also means making the right guesses so that it lands in the right place at the end of it without having to ask you a trillion questions.

So if you're a lab and you're doing both training and your inference, and you're doing inference, you get a lot of that signal, right? Because Every turn you're getting feedback. You might literally have a thumbs up, thumbs down, but also you can just read the next response and notice that the user said, try again, right? But so, is there more value to the work that you're doing in labs that aren't doing inference but they're doing training? Or is there some just asymmetric value proposition here? Or do you think that there's actually the most value to just bringing an extra layer of information, feedback, benchmarking, etc., to like the vertically integrated labs that do both training and inference, even though they might have the internal data?

If you zoom out, what the point of Arena in the ecosystem is, we provide a neutral platform, sure, that everybody trusts.

Yeah.

Based on information from the real world, real users, not just random benchmarks that people have come up with.

Sure.

That benchmarks the comparative capabilities of the model so that they can understand how— everybody can understand which models are best and worst at different tasks. Actually, a mission that only a neutral party can accomplish because the labs are incentivized differently, right? And they also can't sample their own competitor models on their own first-party products.

Yeah, exactly.

So it really does need a third party to do this.

That's cool.

And ultimately it's the community that we really need to serve, whether that's individuals, you know, who are interested in AI or developers or businesses who need that external third-party validation in order to trust the results that AI gives them and to get the best intelligence and the best outcomes.

Yeah. How are you thinking about the, Consumer Reports for consumer agents. You know, like, are we gonna get like a— is the solution like a Marques Brownlee, like an MKBHD, to tell me if I should use Instinct, Muse, or Dots, or something else, or Grokbot? Or is it gonna be hyper-quantitative and you're gonna spin this up as a new vertical? Because I don't think I'm mistaken in assuming that most of your audience most of your customers are businesses, prosumers, you know, indie developers. It's not— you're not necessarily answering the question, who's going to order your groceries most effectively or book you that reservation, but you're kind of in a perfect position to do that as well.

Yeah, that's right. And it's definitely an area that we're trying to get into is evaluating personal agents. It builds on the strengths of our platform. And ultimately, the purpose is that we need to have the best scientific and quantitative information to answer these questions because they are actually quite detailed. It's not just about whether it can get the job done, it's also about the price that it gets the job done, you know, what kind of jobs it can get done versus what kind it cannot get done. And you need— in order to have that level of trust, there needs to be sort of a third-party arbiter. And part of that is building the Consumer Reports or the Gartner or what have you. And then part of it is having a way to communicate that to an audience. We have a YouTube channel, You can go to Find Arena AI on YouTube. And there we have a great team of insights analysts like Peter, like Dawid, and others that are out there telling the world about models at the moment that they get released and all their strengths in a very digestible way.

That's amazing. Congratulations. We could go so much further. We have to have you back on the show soon.

Yeah, it's like sitting in such a cool place.

Congratulations. Congrats on the fundraise. Fantastic news, and very happy for all the work you're doing.

Great milestone.

Thank you, guys. Excited to be here. See you later.

See you.

Goodbye. See you soon. He got me thinking. You got Consumer Reports where they give a 5-star rating. They grade you scale of 1 to 10. Movie review, 2 thumbs up. Gartner took it so much further. They did quadrants, the Gartner Quadrant. You want to be in the top right corner. I want to see Gartner quadrants for cars, Gartner quadrants for movies. I don't want to see, oh, your movie got 4 stars, 4.5 stars. That's the new format. I want to be like, this movie is in the top left quadrant of the Gartner best September movies. Well, we have our next guest.

Speaking of building around agents, we're about to get personal.

How you doing, Zach? With Mr.

Welcome. It's back. Gotagari. He's calling in from a birdcage. He's locked in.

He's locked in the cage. Yeah, I am.

You are locked in right now.

Very cool. How are you doing?

DMF or die. What's new? He's live in the cage. Great to have you back, dude. Yeah. You had the shortest earnout in history. You're back in the game. I think it's like I don't know any of the details, but really smart for you to have this amazing outcome, get immediately back in the game.

Totally.

And running it up to 9 figs was so easy for you. In that category, you decided, I'm going to go compete with the titans of industry, the biggest companies in the world, in what is now the most competitive category, but you have a unique spin on it, and we're excited to talk about it.

Yeah, take us through it.

Cool. Yeah, so I mean, after selling Cal AI, as soon as possible, as soon as, you know, we were able to transition and get everything across the line, I was itching to start something new. And this idea to build in the AI assistant space is something that I've wanted to do even while working on Cal AI. I saw that this, this is the clear future. Of where consumer utility apps are headed. All of these separated apps are collapsing into this one source that is easier to operate, yet more sophisticated and more capable than any of them by themselves. And so just seeing that this is where things are going, I don't want to just sit as a bystander in the stands watching. I wanted to get out and build.

Okay, you raised $10 million at a $100 million valuation. Let's hit the founder. So yeah, I mean, obviously the elephant in the room is like Instinct raised like a billion at $10 billion and they're, you know, he's off like trying to get a bunch of compute. It feels like there's an opportunity here for like a capital-light, inference-light model. And I'm wondering if that's the path you're going down? Because at Dev Day last week, OpenAI announced that you can like bring your ChatGPT subscription with you, spend those tokens inside of another app. It feels like there's other ways, whether it's open source models, on-device stuff, to like not blow up your inference bill. But how are you thinking about that? Or maybe it's just like you're doing the billion-dollar round next week and you'll be back on the show. So I wouldn't put anything past you, but I want to know how you're thinking about it.

It's a great question. The long-term strategy is still fluid and flexible, and we're going to be very adaptive to the market conditions. However, there are multiple different paths, paths to go down. Right now, we are most concerned with building the best product and building the best team. And I really do believe there is a play to keep it completely free and then make money through all kinds of different means. Whether that's like showing ads to the agent without biasing the answer in any way, just showing different products. Like let's say it's going out to buy you a new office chair. It can pull in searches that you get paid for and without biasing, without saying that it's an ad, and then you make money for the user.

Sure.

Also like affiliates, like the Honey business model. So when it goes out to buy something, you could get paid and then long term, Like being the platform, potentially taking fees from all of these companies and negotiating that, that would be more complex and definitely, uh, thinking years out. However, that is the longer-term play. So I think some kind of freemium or completely free is the way to go.

What do you think? What about a fintech angle? Like introducing a debit card, monetizing everything you buy?

Yeah. Yeah. Like that would be super interesting. Like cashback on any purchase, something like that. And these are all routes that we're looking into right now.

Cool.

But ultimately what we care about is building a great product and actually getting it into the hands of consumers. What we're seeing right now is a new AI assistant is getting launched every single day. However, it's all within the bubble of Twitter. The only one that has broken out of Twitter is Muse by Meta. I mean, they own the distribution platform, so difficult to compete. And yeah, we are, we are pushing to also get in the hands of actual consumers. Like, we're being very quiet on Twitter right now, but we're starting to ramp up a lot on Instagram, TikTok, these platforms.

What do you think people misunderstand about consumer philosophy, consumer behavior in the AI era? Like, Ben Thompson has this take that like consumers don't wanna be productive, they wanna be entertained. There's other— there's like the hot take that like, oh, all these tech people, they just think it's like, Booking flights is like the most important thing ever. And like the average American books like one flight a year. And so I feel like you are in tune with the American consumer more than many tech people and more grounded. And so I'm wondering about like, what is your philosophy for like, what do people actually want to do with AI?

Yeah. So a lot of people think that saving time is a big value proposition and it is for busy people.

Mm-hmm.

For people that are entrepreneurs or working on, you know, complex projects. But the average consumer actually does not value their time. You would think they do, but they really do not. And so that is something that AI systems are really good at, saving time, but not something that most people actually care about.

Mm-hmm.

What people do care about is saving money.

Mm-hmm.

Saving or making money. And so right now, AI systems actually are very good at doing this. However, the actual onboarding, like onboarding a user to the platform, most of them just have no idea what to use them for. And so we're trying to really dial in this onboarding where we are immediately providing value. I mean, if we can immediately show someone like, we just saved you $100, that's a user for life.

Jordi alluded to it earlier. You sold your company, you jumped right back in the arena. How has your— what was the journey like selling the company? Like, what did that feel like to you? How did your relationship with money change? Your goals? Did anything change? Maybe it's all the same, but what have you been going through emotionally in the last year?

So, when we sold CalAI, we had an interesting chain of thought where we were very early and still growing very quickly. We could have held on to it, could have kept growing it, and then sold it later. The reason we ultimately sold was because the amount we were selling for met our personal needs where we could now focus not on making more money, but actually building for the sake of following our passions, our curiosities, doing what we actually want to do. And building a calorie tracking app, super cool. We helped a lot of people. For me at least, it wasn't my life's mission. And I always wanted to do something bigger and more broad. And so after selling the company and then helping with the transition, I think there was a time, it was a month where I truly tried to not focus on business at all. I tried to hang out with friends, pick up new hobbies, make music.

Keyword is tried. Yeah. Try it and fail.

Wait, would you recommend that to someone?

Would I recommend?

Yeah, yeah. If somebody goes through a— I mean, we just had Healy Cypher, he just sold his company, he's in, you know, an earnout. And when this— these things happen differently, but like, do you think that's the, the right prescription for someone in your pers— in your situation, or would you have a different take?

So I mean, after 3 weeks of doing this, I just Like, had this itch that I needed to get back in the arena and needed to build something else. And so it didn't last long at all, and I started building very quickly. Yeah, but I also heard like the Rock—

2 hours later.

I didn't know it mutes him.

It's insane. Sorry, we're playing with new graphics.

The Rocket Money founder, after selling his company for a billion, I heard on a podcast His entrepreneurial itch, it just disappeared. And so I wonder if that will ever happen to me. I don't know.

Yeah, that's interesting.

Could never be you.

Probably not at this phase. There's so much opportunity.

Could never be you.

Yeah. Uh, Jordi, any other questions?

Uh, last thing, uh, how, how confident are you that, that hardware will be a big component of the business over the long term? Or do you think there's ways, you know, if you, if you really figure out Sort of agent side, why not figure out ways to make it accessible to more people?

Yeah, so there are 2 trends at play right now. Our overarching mission of the company is to make computing seamless with human life, and there is a huge movement away from being on your screens. The average screen time is 6 hours, and reels are being put in every app.

Mm-hmm.

And people hate it. Like people will get sucked in and scroll for hours. But if most people could push a button, they would remove Reels from Instagram.

Yeah.

If they're in like more of a sober state of mind. I mean, people love to be entertained and consume, but at least not to the amount that they are. But it is so addictive. And so that's why companies like Brick have rose recently where it's just a small NFC tag you put in your fridge and you tap your phone to it. It completely blocks your apps. And so our hardware being screenless allows you to get the same amount of work done, but be on your screen a lot less. It also won't interrupt the flow of conversation. So for example, if we're talking and I pull out my phone, even if it's about us, like I'm making a group chat connecting you with someone, it still puts a physical blocker in front of us. Whereas if I just talk to my wristband, hey, yeah, yeah, make this connection. It, it keeps the human connection alive more.

Yeah.

No, no, no, I agree with that. I think it's a— I think like it's very hard to predict like true consumer behaviors over decades because sometimes people are just like, yeah, they hate the slop, but they go for it and they watch the reels. But as a story to tell people, as a reason to get someone to try something, it's so valuable. And then you can build on top of that and go wherever people want to go. So.

Yeah, people definitely need reels. Like, I would never want to remove that from a product. However, I don't think that, like, our phones, I mean, they're just rectangles. I don't think that they are the optimal form factor when you start building an AI experience. I think the device should be native to the operating system.

Yeah. Yeah. It's interesting because part of why we're in like the voice modality with AI agents and text is just the cost of inference. Like, if things get cheaper, like, every prompt in ChatGPT could just be a FaceTime call with, like, something that looks like an AI agent, and they could render a video, and it could talk to you. But we've had FaceTime for a long time. Not everyone FaceTimes for every single call. A lot of people just have normal phone calls. A lot of people have conversations. So I believe in, like, the right tool for the job for different moments, for sure. I think that fits very well with your thesis. Anyway.

Yeah. Zuck's worst nightmare.

True.

Coming for him. Coming for screen time. Coming for his agent.

Taking shots.

I'm glad to see you back in the arena.

Yeah.

Very excited for you.

Yeah.

Congratulations.

Congratulations on the new round.

Thanks for coming and hanging out.

And I'm sure you'll be back on soon.

Yeah. We'll talk to you soon.

See you guys again.

Have a good one.

Great to see you, Zuck.

Goodbye. Do we have time for one more?

That's our show, folks. One more house.

I wanted to know if you wanted this UFO house. Did you see the UFO house? They saved a UFO-like home from demolition. Now it's landing on the market for $1.495 million. The restored plastic Futuro house, which I think you're not going to like the materials, but— Idyllwild. It's out in Idyllwild, high in California. In California's San Jacinto Mountains near Idyllwild, a harvest gold flying saucer is perched high on a large rock outcropping. The structure is a Futuro, a plastic home designed by the Finnish architect Matti Saarinen in the late '60s. Of the estimated 100— they made 100 of these around the world— only 50 or 60 are thought to remain, though there is no official accounting.

And so, This is so elite.

Okay, you like it?

This is S tier.

This is S tier.

I mean, if you need to, if you want to build like an ADU on your property, why not?

A Futuro?

Why not go with another 3-letter structure? The UFO.

The UFO. I mean, get rid of the ADU and get a UFO.

Yeah.

Okay, I like it.

Now this thing is stunning.

It's very beautiful. It's very cool. It's very unique. It's so different.

Please someone create the UFO-like housing company. Yeah, this would be— We need it. I want one of these in every backyard. Look at this picture, like, what's even going on here?

Yeah, apparently they can just throw it on a truck and drop it off somewhere. It's really cool that people just put these all over the world. Bought it for $70,000 and made plans to move the Futuro to the site. That's very, very cool. Despite Cerrone's best intentions, relocating the Futuro proved to be quite a challenge after After consulting with experts, Wayne concluded that the structure was too heavy to be lifted by a standard-sized helicopter, and airlifting would require a long list of permits, including approval by the FAA. In December of that year, the Futuro was shrink-wrapped and driven from San Diego to Pine Cove on a flatbed truck.

Let's head over to the Wall Street Journal comments section. What do they say? It says $1.5 million for an extremely meltable home in a zone rated by CAL FIRE as the highest chance of wildfire in the state of California. I wonder how State Farm feels about insuring a large piece of yellow plastic surrounded by dense flammable tinder. Well, I mean, they're— I mean, look at this shot though. It just looks—

the value of the structure. And so the value of the structure is— I mean, it's like an art piece, so it could be more, but the actual structure costs like $70,000 to build. So it's not that hard to underwrite.

Of course, like, you don't want to be there in a fire, but you're just— It looks incredible.

It looks really cool.

The, the contrast between the structure and the trees in this shot is just Just out of this world. Yeah, there's so many things to say, says John. I'll stick with it. It's a small market for a plastic treehouse. Yeah, small market, but there's not a lot of these. Yeah, very good. Well, Lisa says love it. The only problem is that it's in California. Taking shots. Matt says the people of Idyllwild are lovely, but with that attitude, probably best not to visit. There's more shade being thrown around in the. In the Wall Street Journal's comments section.

We get it. You're from Wall Street. You're from Manhattan. Go easy on us Californians. We like the Wall Street Journal, too. Do you think it looks too much like a classic Weber grill?

You can never look too much like a classic Weber grill. I've been— you've been trying to hit the gym in a way that would make you look like a classic Weber grill.

Just getting so robust.

Robust.

Okay.

This thing is beautiful.

Yeah. Very, very cool. Very, very cool history. Go check it out. The full breakdown and the full article is available in The Wall Street Journal.

We're off tomorrow. We're headed into a long weekend as well. When we're back, there will only be 1,700 hours until Christmas. Hard to believe.

Wow. That's flying by.

Just flying by.

Yeah, remarkable. Well, leave us 5 stars on Apple Podcasts and Spotify. Sign up for our newsletter at tbpn.com, and we will see you on Monday, 11 AM Pacific. Have a great weekend.

We love you.

Goodbye. Smoke grenade tonight. Okay, goodbye. I like a smoke grenade.

We love you.