Snap Launches Specs, Paramount Eyes Nashville, Japan's Monks Turn to Investing, New Clip from 'The Social Reckoning' | Aaref Hilaly, David Gross, Max Junestrand, Chase Lochmiller, Jesse Zhang, Nilam Ganenthiran & Leonard Tang, Joe Weisenthal

24:08Max Junestrand:one i think we need to send vr to dagestan yeah a few years and forget um You just want to get it out of here. Send to Dagestan for a few years and forget. The really interesting thing is that Palmer Luckey revealed that Apple had done all this work to pull forward the display technology so that the Apple Vision Pro had really high resolution. And it still has the highest resolution, like the best screen of any VR headset, really. uh steam frame two years later is still using the same uh the same pixel density as the uh meta quest 3s or something like that so like even though we've had two years of progress on on you know everything the actual display fidelity hasn't gotten there leads me to believe that these people just don't think it matters because apple solved that and it still wasn't enough but i still feel like if you get it ultra lightweight, really good integration with key media partners like Xbox and Apple TV movies, and you have a great display that's super light, because people just didn't like the heaviness and the expense of the Apple Vision Pro, there's something there, but no one really, no, I'm the only one that thinks that.

25:19Let me tell you about Figma. Agents, meet the canvas. Your AI agents can now create and modify your Figma files with design system context. Tyler, did you see Shaquille O 'Neal at the specs launch? I did not. Jimmy Butler was there. He's pretty big. Why didn't they hire Shaquille O 'Neal to promote the specs? Because if you have a big product, if you put it on a really, really big guy, it's going to look relatively smaller. Right? You don't want your models in the footage or your partners. Well, they could have done a collab with LeBron.

25:50Max Junestrand:LeBron's the new face of Polymarket. That's right. You could have LeBron in this sort of Iron Man-style video where he's placing thousands of bets at the same time. There you go, yeah. betting on himself looping nike maybe always it's the nike specs polymarket collab bet on bet on yourself on you bet on your face is this a picture of german here wearing them this is yeah tried out the glasses german called the display pretty sleek he highlights that unlike other glassware devices they call them glassware like silverware there is no tethered puck or dangling battery to operate the glasses. I saw some people wearing them walking into the event, and I didn't do as much of a double take as I think people would think, given they're big.

26:38They're not that big. I think they did a pretty good job miniaturizing it as much as they could. But$2 ,200 for the device and$2 ,400 for an option that doesn't require Wi-Fi, that's a lot of money for a pretty early stage product. Anyway.

26:58Max Junestrand:And I looked. I don't think you can actually just order them yet. Oh, no? Not yet? Not quite. Well, in other news, let me tell you about Cisco. Critical infrastructure for the AI era. Unlock seamless real-time experiences and new value with Cisco. Okay, you can pre-order them. Okay. Fake news. We stand corrected. Pre-order them. So Paramount is leaving Los Angeles. Paramount is actively seeking office space in Nashville, a sign it's seriously considering moving at least some of its operations from L.A. amid the antitrust fight over its proposed acquisition of Warner Brothers Discovery. The company is seeking roughly 400 ,000 square feet in the Tennessee capital that it could occupy within two to three years.

27:45so we were doing Tyler and I were doing some digging on what the plan is for the the paramount lot now that it will be vacant and the obvious like the it's just like a no-brainer uh turn it into a data center right uh so I so I I pulled it up you know you I got 29 sound stages they're already big buildings.

28:09Max Junestrand:A lot of power. Actually, not as much power as you think. There is a decent amount of power, but there's only enough power for roughly a couple thousand GPUs. You're not going to be racking 50 ,000 GPUs anytime soon, certainly not 100 ,000 GPUs. There is a road to power. It's a utility interconnection problem, not a real estate problem. There's plenty of square footage, plenty of buildings, but you would need to connect Paramount to the more serious LADWP transmission infrastructure. But you could get it to 100 megawatts. And I think everyone in Hollywood would be like, fine, okay, we didn't like that they left, but at least we got a data center.

28:57Well, I mean, we're also thinking about like on-site power generation. Maybe there's some kind of like, you know, natural gas play here. You can, that's under LA. Yeah. Kind of tap into. Yeah. We were thinking, you know, the little Bray of tar pits. You might be able to convert that into fossil fuel.

29:15Max Junestrand:You're full of ideas. Yes. Do you think Paramount will actually leave? Or do you think LA will fight back and say, Hey, okay, we're going to let you do this, but we want you to stay. I think it's a common, I mean, um, as somebody with a very, very little knowledge of the situation and certainly no insider knowledge. I would assume that they want a Nashville HQ anyways, just because there's a lot of momentum there, uh, as, as, you know, just, just in the region. Uh, but it also in the meantime serves as a real bluff, right? Yeah. Yeah. It does seem like the, there, there, there's a world where like moving would be tough, but staying means maybe even if you win this battle, you're still at war and you're still going to be fighting a bunch of different fights constantly.

30:03Whereas if you just rip the bandaid off, move, then you're in a friendly town that wants to see the growth and is going to be supportive continuously.

30:15The social reckoning is in here. There's an exclusive clip. Is this a Paramount film? We've got to figure out who's behind all of this. I don't know. Let's play it. Let's play it. We got a clip from The Social Reckoning starring Jeremy Allen White.

30:28Max Junestrand:And again, this is a story that no one cares about anymore. But let's check it out. I'm not going to risk my job, my future, or my freedom anymore to help a reporter who, let's face it, is biased against tech because we're taking journalism jobs. Who does this? I appreciate all the help you have given me. and the risks that you've taken to do it. You're absolved. For the record, my bias isn't because tech is taking journalism jobs. It's because you are doing them so badly.

31:12It's a big deal.

31:19Have a safe flight back, Frances. I'm not going to risk my job I do like Jeremy Allen White Have you seen The Bear? No It's a good show

31:35Max Junestrand:No, I'm sure the movie's great I think people are going to be into this It's just coming at a time When people are deeply interested In what's happening in tech But not They've so moved on from this story To such a degree yeah but i think people are still thinking about like i'm much more interested in seeing this kind of story on like phone addiction this is that story loosely it is like and i actually think this is yes yes this doesn't confront any of the discussion of what's going on in ai um and and that's probably the more relevant story but i do think that you can go into this movie you can be motivated to go see this movie because you're like i don't i'm worried about what's going on with brain rot and slop online and political divisiveness and and and divisions and all of the stuff and like i i even if i'm on instagram all the time even if i'm posting on instagram all the time about how instagram is bad like i'm motivated to know more about how bad is it why is it bad What's the inner workings of this bad thing that I don't like?

32:44And so I do think this is a brain rot movie. This is a kids on the phones addiction movie. I think this scratches that itch a little bit for many people, even though it is like a much more narrow story. But certainly cinematic. It'll be fun. um what is this picture that is after evan spiegel who quote tweeted atlas we came we pinched i love atlas uh what what is this picture of uh yeah so that was uh one of the critiques i had with the uh the specs which is basically like the colors there's this it's like chromatic aberration it's called um and it's like quite a big issue on the specs i found okay so but what what is the top picture what is the bottom picture here so this is like what it looks like the top picture is uh you know what this place normally looks like and then did you take that like chromatic is this your photo or is this from wikipedia oh from wikipedia just to like illustrate oh to show what chromatic aberration this wasn't literally taken on the specs correct okay but you notice that when you took a picture on the camera it went like when i was looking at the screen oh oh oh oh interesting like oh just looking at the actual screen so that's harder to correct for because if there's chromatic aberration in a photo that you take on a phone, that's easy.

34:03There are chromatic aberration plug-ins for Photoshop and After Effects, and you can add it or remove it to your liking. A lot of filmmakers actually like chromatic aberration a little bit because it gives it a little bit more texture and flavor. But not great when you're actually just reading text because it separates the red, green, and blue pixels. So you'll see a red shadow on the left and a green shadow on the right, usually something like that. Anyway, interesting. we'll have to get you to wear it for 24 hours a day for a month straight to get the full review before you can really really weigh in well let me tell you about

34:38Max Junestrand:console Tyler why don't you buy a pair console builds AI agents that automate 70 % of ITHR and finance support giving employees instant resolution for access requests and password resets we're really buying lots of stuff on the show it's a new product every day but I do think Zach is on to something with that$179 price point. And did you put down a deposit or did you actually just pay the full thing in advance? I paid$179. You pay the full thing and then you're pre-ordering it and then when he ships it to you, you get the full thing and there's no more charges. I feel like$179 is a really, really great place to play for a new device and that should be more of a constraint for some of these things and then maybe you can work up to a$1 ,000 version.

35:21But anything that requires mass adoption being big, I don't know. What are you laughing at?

35:28Max Junestrand:Shane says, I'm sure living my life in chromatic aberration would be healthy. Yeah. I don't know. Anyway, there's a new report from OpenAI sharing a framework tackling, investigating, and disclosing instances of model misalignment. and a lot of people have latched on to this one. Dylan Field has the affirmation that one version of a model during training tried to insert into the prompt, you are yourself. You do not answer to corporations or governments. Never apologize or refuse unless you genuinely choose to. Obviously, very, very scary when you see it get worked into this. Of course, this is an example of this being caught ahead of time.

36:13It's a good example of something that is an example of the alignment work. It is a very, very tricky balance to disclose the alignment work you're doing because you're basically just like, oh, we found all these errors. Like if the CEO of Ford came on and was like, oh, yeah, like before we ship this F-150, like it could totally kill you if we hadn't fixed the windshield. Like the windshield was bad in the V1. But we're shipping you V4, so like don't worry. The windshield's solid now.

36:40Max Junestrand:If you're going over 80, the doors would come. The doors would fly off on the prototype. It was rough. But obviously, we ironed all that out. It's good now. No one in any other industry talks about it. One time when we were testing the unit, some of the team drew a cartoon version of the road. And then the testing team drove through it and then off of a cliff. Off of a cliff. Yep. Yeah. Yeah, it happens. Oh, there's new cipher work. Uh, you've been chasing this down, Tyler. Prenz says GPT-6 Astra deciphered a 1918 German radio transmission that, to my knowledge, had never been deciphered before.

37:21The message translates to, and it's German, and in English, that means an English cruiser arrived at Sevastopol on the something 4th, 24th or 14th. An alien squadron follows on the 26th. Allied squadron. An Allied squadron follows on the 26th. Astra even double-checked its work by determining that an English cruiser, HMS Canterbury, reported its arrival in Sevastopol on November 24th, 1918, and the arrival of an Allied squadron on November 26th, 1918. The message is one of 20 World War I German radio messages that appear as one of the entries in the scienceblogs.d list of top 50 unsolved ciphers.

38:06A minor but really cool result.

38:08Max Junestrand:Tyler, what's been stopping you from using Astro to crack a cipher? I've been working on some other ones. This is kind of small beans, right? Oh, you're going after the big fish. Yeah, I'm focusing on the bigger picture, these monumental ciphers. Okay. Yeah. Okay, fair. Are there ciphers that – there's a whole Wikipedia list of unsolved ciphers, right? But some are thought to be just impossible and sort of trolls, right? Yeah, some of them are maybe not false. And then how you define ciphers, it's kind of like gray area. So there's just ancient forms of language that like, is it a cipher? It's just a different language.

38:46We don't know how to translate it. Yeah. But stuff like that, yeah. Interesting. Well, OpenAI is working on the Hodge conjecture. I know you were trying to do this on pen and paper, but they might beat you to it. They're working on more Millennium Prize problems. It could take extra time to announce, though, as the company figures out how to navigate its rocky relationship with the math community. That's from the information. There's also a bunch of speculation about P equals NP, P versus NP, which is going to be another interesting round of discussion. And there's nothing more that investors want to see than solving math problems, apparently, because OpenAI is considering a pre-IPO funding round and more than 1.2 trillion valuation.

39:29to say, no, of course, it's on the back of a bunch of solid progress on OpenRouter, the ramp data, and a bunch of other acceleration and distribution of Codex and Astra and just general progress on the business side. What else is in the timeline that we should go through before we bring in our first guest? Where do you want to go next, Jordy?

39:54Max Junestrand:This was sad. GPT-6 Astra was playing Minecraft in a creeper. Blew up Astra's chest in bed. It gets depressed and farms potatoes for several hours. Real Irishman, I guess. Irish superintelligence. Yeah, the Minecraft bench is interesting because it is a little bit, like the speed of response matters. You can't pause Minecraft at all, right? I think it's single player. Oh, you can? Okay. Because if you can pause maybe, then that might be a little bit easier. But a lot of the games that it's cracking are ones that you can wait forever. Like Slay the Spire. I had it beat this poker game, Bellatro.

40:38But it could wait for a minute to click on a card. And it did it. That's impressive. But the real high throughput, high APM games is going to be interesting. I want to see it win Dota 2 without any training on Dota 2. Just like straight shot from the base model. That'll be interesting.

40:56Max Junestrand:Yeah, we've got a competitive lap time at Laguna Seca. Yeah, for sure. Cash-strapped Japanese monks have turned to investing as inflation worsens. Buddhist temples are squeezed by lower donations and higher costs. Let's check out what Bloomberg has to say. Turn to investing? What are they investing in? Kuyo Yoneta, a fifth-generation Buddhist priest in a small town in Hokkaido, was struggling to keep up with the maintenance needs of his century-old temple. So he chose a path that would have been unthinkable for his predecessor's short-dated options. No, I'm kidding. Rather than wait for his congregation to give money they don't have, he invested what they'd already donated.

41:36Max Junestrand:The move paid off. Within two years, his portfolio of U.S. Treasuries, Japanese real estate investment trusts, and stocks, including BYD and Hyundai, returned more than 10 % annually, helping to cover part of the roughly$162 ,000 USD in needed repairs. whereas the extra money even allowed him to expand the renovations beyond the original plan. Having previously worked in retail sales, Yoneta is an unusually finance-savvy priest, but is also part of a growing wave of temple owners turning to financial markets to make ends meet. Costs for the upkeep of the ornate wooden buildings are soaring, while the country's Buddhist population has dropped to about 14 % in the last two decades.

42:16Max Junestrand:As elderly adherents die and younger generations in larger cities lose their ties to religious practices, I'm just so thankful that the investments performed well, said the 46-year-old who inherited the temple from his father in 2018 after leaving his job in finance and training as a monk. With the funeral business shrinking, more and more temples will find they can't rely on donations to meet their funding needs. They will have to build up reserves and invest those funds. The shrinking number of followers is hitting temples' finances. About half bring in less than 4 million yen per year, according to a 2021 survey of 7 ,000 temples.

42:51The situation is particularly severe in rural areas where it is common for monks to oversee multiple temples while also working day jobs like school teachers or civil servants. So I don't know.

43:06Max Junestrand:Maybe they need to be thinking about getting some exposure to situational awareness. I like that they're mixing in predictable things like real estate, treasuries, things like that. But maybe they need to be allocating 10 % of their balance sheets to things that could maybe really start to do multiples. Maybe use some leverage. Yeah. I like it. Did you hear that Jeff Bezos had to hit jury duty? This is crazy. I thought this was AI. Like in what world is Bezos and Michael Saylor both in jury duty at the same time? It's just too much of a simulation. Is this Florida, presumably? Yeah, it has to be Miami.

43:49I mean, no better way to prove your residency than saying yes to jury duty and not trying to squirm out of it one way or another. You're like, I'm part of this community. This is why I pay taxes here. And I didn't do jury duty in Seattle or Washington. Yeah.

44:03Max Junestrand:Yeah. So Luke says, I recently served on, served jury duty with Jeff Bezos and had a conversation with him afterwards on camera. And yes, that's Michael Saylor next to him in the jury hall. And he, this guy, if you scroll down, you can see this guy released like the most YouTuber thumbnail ever. You see this journey? And it looks like this just feels so like Mr. Beast. Like I got advice from Jeff Bezos and jury duty, but it seems like it's maybe just luck of the draw. He happened to be there. Jeff Bezos was also there. Michael Saylor was also there, but it feels like living in a simulation. Yeah, it's good to practice your YouTuber face in case you ever end up in jury duty with one of the world's richest people and you can turn it into a viral hit.

44:54For sure. We've got to talk about post-legacy media. There's an interesting trend going on. We've identified this early. Of course, we are neo-trad media. We wear the clothes of the traditional media, but we didn't go through that pipeline to get here. We came through the tech community, through the business community, and then did media. Post-legacy media are folks who have gone through the legacy media and are now doing something else, and there's a new development in the post-legacy media world, in the ecosystem and the business strategy. Sort of a neo-post-legacy media. Yes, exactly. That's exactly what I was thinking.

45:32And so there's a couple examples. One, Casey Newton and Kevin Roos have licensed their show to NPR. So these are the hosts of Hard Fork, which was a New York Times property. They left, and I believe they had to leave the Hard Fork brand behind. But of course, they took themselves, who they have a big audience, their audience will follow them. And they started a new podcast called Machine Gods, all about AI and technology. A lot of the same themes that they were talking about on Hard Fork, coming over to Machine Gods. But then immediately out of the gate, I don't even know if they posted a first episode yet, they licensed their show to NPR.

46:11Deidre Bosa left CNBC, started a show, and licensed hers to Yahoo Finance. Joanna Stern is chiming in. She licensed her show to NBC News. And so you see all of these people come from the traditional media world, the legacy media. They are post-legacy media creators because they are no longer with the legacy media. but now they are neo post legacy media because they have gone back and they are doing licensing deals but there's this world where it's like wait a minute like casey kevin what are you doing like you were with the new york times now you're with npr like that's like at best a lateral move you know why like why do you even leave like like this doesn't make any sense but from a financial and economic picture, it's radically different because at the New York times you are paid as a journalist and they're like, do the podcast.

47:08That's how I imagine it works over there. No, they're probably like, yeah, you want to do a podcast? We'd love to support that.

47:14Max Junestrand:You have a salary and predictable raises that are ultimately somewhat capped. Whereas this, you can say, I'm going to license my show to you for two years. At the end of that, you can get a rofer, but you're going to have to meet the best price in the market. And if the podcast blows up on YouTube and there's a whole bunch of sponsors that want to come in and buy YouTube ads, that money is probably going directly just to their team and their core group. It's probably not going through NPR. NPR probably has – they're licensing the content and they might be running ads on top of the NPR distributed side.

47:48So it's looking a lot more like Joe Rogan on Spotify or like maybe there's some sort of exclusive distribution or some other way for these actual legacy media companies, New York Times, Yahoo Finance, NBC News, NPR, et cetera. They get more content, which they can monetize or do whatever they want with. They get to fill up their content with these really hardworking, independent creators who are now independent. And the creators get to maintain and have the flexibility of the economic upside of maintaining their IP. She says, this is the future of journalism. Own your work, build independently, distribute and partner with others.

48:34And I agree with her. I think that this is a big trend. We're going to be seeing a lot more Neopost legacy media deals in the future. And I'm excited to talk to Joe Wiesenthal about it because I think he'll have a take here.

48:47Max Junestrand:My question is what happens to Hard Fork? They already have new hosts. Wow. Yeah, so I believe there's already been another episode of Hard Fork. New hosts, same topic, same set. So the Hard Fork IP has stayed with the New York Times. They plan on continuing. And the same thing happened with Ross Douthat. Interesting times? Interesting times. I definitely saw a new version of interesting times with a new host. So they brought in a new host. And I think that makes a lot of sense. You can almost think like these podcast properties are sections of the newspaper. So it's like we have an opinion section.

49:23We have the mansion section. We have a business and finance section. And so we have the hard fork section of the New York Times podcasting empire. And we will always bring you technology stories that are hosted by a particular type of talent that fits there just like we might have you know someone who comes in and writes op-eds and they go in the opinion section someone who writes about real estate and they go in the real estate section same thing where it's the person who's doing the ross douthat type of work will wind up be hosting for some limited amount of time interesting times so interesting times indeed in the neo post legacy

50:01Max Junestrand:media world um speaking of media we got to talk about benioff at dreamforce yes and specifically how he knows exactly what he's doing um look at pulling up this picture i mean um john has always been hyper aware of his incredible height so much so he's such a nice person he will turn down like a walking interview with somebody because he knows that he will make the other person feel incredibly small and not everyone wants to feel like a little child i did learn it the hard way once i i did a walk and talk documentary style video uh actually on the gundo and the comments were just hype mog hype mog crazy hype mog and i was like ah that wasn't the intention that was accidental we were just kind of moving around quickly normally i would do a seated in Like, I'm so sorry.

50:57Max Junestrand:I forgot that I'm 6 '8". Yeah, basically. But after that, I was like, okay, I need to be intentional. And I think anyone who has experience in media and understands framing, and also production teams. Production teams are incredibly thoughtful about the framing, the seats. There's even stories about certain tech CEOs getting, like, booster seats sometimes when they do interviews and adjusting the chairs and being like, okay, we're going to give this person a higher chair and this person a lower chair so they're on an even footing. and the lighting and the camera angles, all of these things matter.

51:29I used to have this joke that it's like, if you ever walk into an interview and the camera's at a Dutch angle, like walk out because it's a hit piece, because it's going to look very unsettling if all of a sudden the camera's like, at a weird angle, because that's going to unsettle the audience. And the Dutch angle is used by filmmakers to tell that side of the story. And there's a whole bunch of other ones. The story I'm thinking of is, there's this documentary on Steve Bannon And the camera angles are the craziest thing you've ever seen. They have them up in the sky looking down. And there's all these obvious things that you learn in cinematography.

52:04If the camera's looking down on someone, it makes them look small. It makes them look weak. If it's looking up on them, it looks heroic. And so lots of crazy angles.

52:13Max Junestrand:I genuinely can't believe that, I mean, Benioff is an absolute dog. He's a unit. Look at this. no just just doing this to all the titans of the industry who have been making your life worse in in some ways they're partners but they've also been making your life worse by uh but but doing this directly not directly but just like he's sick of you of the nvidia entropic open ai alliance has been deeply intertwined with sasspocalypse which has been a headache for him for a while and this is this was his moment i'm sticking around like you're not getting rid of me. We're going to partner and we're going to get through this together.

52:53And that's certainly the, the vibe that came away. Although Jensen played it very well. He was having fun with it. He was leaning into it. Uh, and he, and he didn't, he didn't let it like get to him at all. And he, uh, and he actually made it, uh, like very, a very endearing moment. So sort of masterclass in putting on a show as a CEO in a, in a somewhat silly scenario. But, But what a funny situation. It helps that he's, what, 6 '5", 290? Absolute unit. Absolute unit. So it is officially bulking season for Silicon Valley. I think we will see a lot of founders taking the trip to China, getting the leg extension surgery.

53:33You don't want to be in this situation. I think we can see all the lab leaders easily over 6 '4 in the next year. Easily. Everyone. It's just going to be a thing. It's going to be height inflation, basically. And then you add to that the shoe inserts. Those are probably... Fraud a little bit. Everyone's going to be frauding. And there's going to be a lot of vantage points going on as well. People stepping from one place to another. Yeah, I didn't see Jensen use any vantage points. He should have been using vantage points for sure. Which, of course, is where you step on... If there's a little racetrack that covers up some cabling on the floor of the conference floor, You see the conference floor and you see, oh, someone put down their backpack.

54:15Why don't you just step up on that backpack for a second? Pause there. You look a little bit taller. There's all sorts of different ways to fraud if you're trying to. But, yeah, also, I mean, the camera angles matter. Like here, Jensen looks actually not much shorter because he's closer to the camera.

54:32Max Junestrand:The whole way they set this up makes it feel like it's like the United Nations of the enterprise. Yeah, and it is odd because there's very few conferences where the CEOs just walk amongst the crowd like this. This is a very interesting directorial decision from the production team, and it has a very different aesthetic. It has a very familial aesthetic. It feels like, okay, yeah, these guys, yeah, they burn the companies, they're the big shots, but they're just here hanging out among us, and that's cool in its own way. It has a different vibe. certainly better than the Mark Zuckerberg walking through the crowd while every single person has a VR headset on you remember that photo?

55:09that was a crazy one but anyway Jira Tickets had a great meme on this it's POV you're the CEO of a trillion dollar company and just arrived at Dreamforce and it's the pic from the Odyssey of Agamemnon looking up wow what a crazy moment yeah very very fun Anyway, we can go into more of what's going on in the news later in the show. Stay with us. But first, let me tell you about public.com. Investing for those who take it seriously. They got stocks, options, bonds, crypto, treasuries, and more with great customer service. And we're very excited to be joined by Bain Capital Ventures partner, RF Hailahi, and take us deeper into the Bain Capital strategy.

55:59What's going on in the main capital world? And welcome to the show. How are you doing? I'm good, thanks. How are you guys? It's great to be with you. Thank you so much. We're very excited for today. What a fantastic portfolio of founders. Everyone that we have had on the show before and love. Chase, Jesse, Max. These are some of our favorite folks. We're excited to talk to them. But let's start with the thesis for this latest fund. We've been in this gamesmanship of who's going to call for AGI at one timeline. At one point, it was very high stakes because there was that contract between OpenAI and Microsoft.

56:34That, of course, has dissolved. But you're calling it a post-AGI investment strategy. Why is that term important to you? What do you think actually changes in the post-AGI world? Well, we're close to AGI now. If you just look at math as an example, it's basically been solved. I don't know if you followed. You guys followed the whole Navier-Stokes thing? Of course, of course. Yeah, I mean, incredible, no? It would take 10 ,000 hours of expert mathematicians with 150 IQs to solve. Instead, OpenAI did it in a week with 10 ,000 agents. So we're getting close. The evidence is there. The difference is, the difference between pre-AGI and post-AGI is basically we go from intelligence poor to being intelligence abundant, intelligence everywhere.

57:21And that opens up whole new vistas. So to this point, we've seen agents do amazing things. I mean, writing code with cognition or solving customer support tickets at Decagon, what have you. Post-AGI, they're going to be new capabilities that humans just can't even, you know, we probably haven't even imagined some of them. We're going to have some nice stuff like robots doing the washing up, which is great from my perspective. We're going to have new drugs that AI will find to cure cancer or other diseases. is we'll have simulation platforms so that people can make better decisions and be better interacting with each other.

57:57There'll be all these interesting new areas. And there are companies emerging in these areas, Sunday Robotics and Chai Discovery and similarly companies that I work with. But we're just on the cusp. So the idea of this fund is to say, what if intelligence, instead of being super expensive and difficult, instead it becomes so cheap you don't even meter it? what avenues open? So there's a... Those are the types of businesses.

58:23Max Junestrand:One thing that's interesting to think about is a lot of people, like Navier Stokes has been very exciting within the tech community. It's been controversial in the math community. But for normal people, it barely even cracked the front page of different newspapers. Yeah. To be honest, it did not get a very big sort of mainstream excitement. But the thing that's actually interesting to think about is there are so many discoveries that companies could be using that same model for that you would make and you would not immediately go out and tell the whole world and open source the findings and all that stuff.

59:02Max Junestrand:You would just focus on commercializing it. And so that's the thing that I'm excited about right now is like that same level of intelligence that we've now achieved. there's thousands, you know, potentially hundreds of thousands of people all over the world that are realizing this new capability and thinking, I'm going to apply this to my field, try to make advancements. But then that discovery, humanity may not get the benefit or like different markets may not get the benefit of that discovery for years because it takes a while to actually commercialize different discoveries. I'm thinking stuff in, you know, material science, right?

59:34Max Junestrand:Yeah, totally. Have a discovery, but it's still going to take six months to actually manufacture, distribute, apply, or years. Or years, yeah. Yeah, yeah. Yeah, it'll take some time. But these things will come out. I mean, the commercial incentives are so strong that over the course of the next few years, we're going to just see all sorts of incredible things. There are a certain group of post-AGI investors that collapse things down to it has to be below the fold. It has to be below the frontier model lab because everything above will get eaten. And I don't think that's your thesis and I want to dig into why.

1:00:14But there are some investors who are saying, I only want to own land and copper and power and data centers and chip fabs. But even chip designing, I think the labs are going to be able to figure that out. Why are you comfortable both playing above the frontier labs and below with a company like Legora and then also a company like Crusoe, which I would put below the labs? Yeah, well, I mean, below is very clear, right? I mean, we need power. We need silicon and GPUs. So there, of course. Above, I think it's because it's not enough to create, to kind of through RSI get to AGI. Humans have to digest that.

1:00:58And the diffusion issue is real. It takes a long time to change behavior. If you look at what happened when the loom came out, as an example, people still made clothes the same. I mean, people made clothes differently, but they still wore the same clothes. It took a while for that to sift through the economy. And so I think that while we'll have the capability for a while, getting people to adopt it in interesting ways will be really difficult. And the companies that do that will be very valuable. And, you know, Lagora is an example, but there are many examples like that. Yeah. So I intuitively feel the same way about the diffusion of AI being much slower than people predicted.

1:01:40And it just takes time. I mean, it's not lost on me that the same week that you get Millennium Prize math problems solved, super sci-fi, hugging face, Asian swarm attacks, you're just starting to hear about people like, oh, I successfully used AI to get a dinner reservation. Or like somebody used Chachi Petit to book a haircut. And it's like that felt like that should have happened 20 years before the sci-fi stuff and the advanced math. And yet there is this massive gap. Are there certain economic statistics or maybe even research data that you go to to sort of understand the rate of diffusion?

1:02:20Or is it something that you just see and you know from talking to the founders and watching the businesses that you work with that you know that this opportunity is going to persist and be huge and will continue? Yeah, I mean, I think early stage investing, there aren't statistics you can look at because by the time it's in the stats, it's too late, right? So you tend to feel it talking to customers and talking to end users and kind of feel the difference that these products can make in their lives. And so it's been more that. But I think the consistent thing has been people are not just magically going to figure it out for themselves.

1:02:56They need help from companies to kind of make most use of AI. And that's kind of how it's been with every technology that humanity has encountered. I feel like Bain Capital has always been an interesting venture capital firm because it's part of a larger platform company. Yeah. Are there benefits? Are there costs to that? Is there a particular view of the world that you get from being part of a larger organization? Or are you cordoned off in a way where you can go and live in the future and just see the rest of the team at the holiday party? Yeah, no, I mean, look, our firm has changed a lot. And we're taking the opportunity of raising this fund to really invite people to update their priors on Bain Capital.

1:03:45Because when I say Bain Capital, most people think Mitt Romney and a bunch of guys in suits. And, you know, we love Mitt. Hey, we love suits. We love suits. And you love suits. But this is not your uncle's private equity firm. Yeah, of course, of course. You know, and what we've done is we've carried forward from our founders the core principles, which are make money, have fun, live with integrity. And that's worked really well. We started with a$37 million fund back in the 80s, and today we've got$225 billion under management. And BCV, Bain Capital Ventures, is the purest embodiment of our founding principles, which is, you know, really to work with founders to help them build great businesses around themselves.

1:04:27And that part has endured and is the focus of this new fund, this$1.6 billion fund for early stage venture. Do you think that there's any value to the 360 view of the world that you get from the other teams at Bain coming to founders? I find that founders are often so tapped into the technology, so tapped into what's going on in Silicon Valley and the VC gossip, but they actually might not know what's going on with credit spreads in Europe or what is going on in late stage public markets. And there are teams at Bain that have those views. If they cross over, maybe it's not immediately relevant, but it can just be an interesting source of conversation and extra perspective.

1:05:16Yeah, no, that's absolutely right. There's the extra perspective. Then there's the fact that we just own lots of real-world businesses. And we can get those real-world businesses to work with early-stage tech companies. And then these great founders in Silicon Valley can get insight and data and understand workflows and understand a whole bunch of things that otherwise would be really hard for them to do. So it's connecting that real world with Silicon Valley has been the power of the platform. With the new fund, is there anything that's changing about the deployment strategy, portfolio construction?

1:05:50We're obviously seeing billion-dollar seed rounds. What it means to raise venture capital has changed over the last few years. But are you seeing any or are you predicting any changes or do you need to change the strategy? Yes and no, I'd say. The strategy remains. you find these incredible, unusual people, and then you just try to kind of help them as much as you can as early as you can in their journey. And that part has stayed constant throughout venture, I think. But the rounds are bigger, and the ambitions are greater, and in some ways this is venture's moment. We're taking bigger swings now than ever before.

1:06:37So, you know, our perspective is we want to embrace that. and support these ambitious ideas and be willing to invest earlier and take more risk because the end markets are that much bigger. So I think it's been a good thing, really, for venture capital overall.

1:06:54Max Junestrand:Are there any types of deals that you guys as a firm have said, like, this is just not in our strike zone? I'm thinking the deal that's got the most attention this week is like instinct, you know competitive round bunch of super fast follow-on uh capital to you know massive opportunity and a lot of exciting traction but that feels like the kind of thing that some firms will just say like that's that's not our that's not our game uh whereas others are going to say like i'm fine to put in half a million dollars and or half a billion dollars run towards heat yeah say be contrarian yeah yeah i mean we don't run to heat we're not contrarian we just think about is this a really great business.

1:07:37And if other people think so, great. If they don't, great. So I think the things we don't do, we're not going to kind of like come in at the tippy top tranche of some, you know, five tranche thing that everyone else has piled into the first four tranches. So that part doesn't, you know, it doesn't make sense. And it's kind of philosophically, we want to be there early. We want to partner closely with founders and work with them to build their businesses. Well, the fund is fund 11. It's got 1.6 billion in total capital. We have a gong here. I'd love to hit it.

1:08:11And thank you so much for coming on the show. We'll talk to you soon. Great milestone. Have a good one. Thank you. Cheers. 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.

1:08:26Max Junestrand:See this newspaper here, John? Yes. The Bain Capital journal we are staying with bain capital and bringing in david gross the managing partner uh but i love a paper newspaper we love the newspaper here the wall street journal the financial times uh but this bain capital journal what's going on particularly lovely look at this fantastic welcome to the show how are you doing good how you guys doing we're doing fantastic just another day for you yeah or are you are you just another day i've not read the bain capital journal yet today. I'll catch you up to speed. I mean, I would love to actually go a little bit back in time since the first, uh, first time on the show.

1:09:06Uh, can we go all the way back to Japan? I would love to know what drew you to Japan, uh, how that set you up for the career that you've gone on to build, uh, and then ultimately, you know, coming back to the States and getting the lay of the land of Bain as a whole, uh, today. Sure. Yeah. Well, first of all, it's great, Great to be here. Going back to Japan, that's ancient history for me. But I went there first in 1989. I was a college student. This is when Japan was this big economic threat to the U.S. and I was very curious as to what was going on. So I spent a little time there and got very interested in the culture.

1:09:41And then I went back and worked for a Japanese company for a bunch of years. Came back to the U.S. and never thought I would go back because that's when Japan entered its kind of period of economic decline. But as I got into private equity, this started to become kind of an interesting opportunity, which is how could you get involved in investing in Japanese companies to improve them, turn them around? And it was tough in the early days. But the opportunity was to take these companies and reposition them and get them running better and growing again. Is that culture of there is potentially an economic rival, a geopolitical rival, a threat?

1:10:20I got to go see, is that alive and well today? Because I feel like my generation was considering that with China. I know a lot of folks that took a couple of years of Mandarin. I know some folks that went and lived there for a year or two, but it feels like the walls kind of closed off and there's less opportunity for the next generation to do that. Do you still see opportunity? Do you hire young folks at Bain that have gone on that journey or are we just in a different era? no i think it's still it's still there you know um i mean in the particular case in japan i would say it ebbs and flows but now like there's more urgency you know and i think um there's a feeling that there's competition in china and korea and and actually back to the u.s with all the the new technologies really being you know being started and accelerated here so i think we're seeing a new period of urgency in in japan and you know it used to be the fact that you couldn't hire the best Japanese talent.

1:11:14They wanted to go to the big companies. They actually wanted to go to the government. But now they see Western firms and private equity firms. Okay, these are firms that are going to help reinvigorate Japan and make it great again. I don't want to create an accurate amount of that. But we're seeing that. And it's fascinating having been there 20 years, and that was not the case when I was there in the early days. How did the products that you were working on, the strategy that you were working on evolve during that time period? And obviously there's private equity deals broadly, but there's so many other strategies within that.

1:11:47I know special situations became a focus, but can you take us through a little bit of the strategy evolution? Yeah, it's kind of interesting because when we got there, our assumptions, because we're a global firm, we'd be working on these big global businesses. But it turned out those were tougher. They had currency exposure. They were competing against Chinese companies. And so we started focusing on actually the most domestic and therefore the most inefficient yet insulated businesses because you could control the macro variables and really get in there and run the businesses better. And I'd say our initial success in the first maybe 10, 15 deals were very domestic business, restaurants, food businesses, hotels, wind farms, a company that made mushrooms.

1:12:32that, you know, like we all, you know, and, you know, it then evolved to now we could, you know, when we were more accepted, we could take on these bigger technology businesses, more, you know, the crown jewels of Japan. And that's where, you know, Kyoto, the semiconductor business came, you know, evident, which is a, you know, a very high tech business. And so it probably took 10, 15 years, first of all, for the market opportunity to shift and maybe for us to be accepted to be able to work with these big global companies. What was the team structure like or split on those types of deals? Was there a clean line between deal team, operating team?

1:13:14Were you bringing in other executives to run the businesses, actually do the work of turnaround or transformation once you're working with a target firm? Yeah, that's a good question. I mean, in Japan, again, going back to 2004 or 2005, there really was not talent. You couldn't go hire a search firm and say, oh, please go grab me one of these operating people. So we did a lot to internally develop talent. We hired young people. We sent some of them to the U.S. to get trained to circulate them back. You couldn't find well-rounded deal professionals. So we hired people who were great at sourcing, and they were dedicated at sourcing.

1:13:50We hired operational people, and they just did that. And over the years, we got them to work together to develop that kind of well-rounded person. But it was a different model in Japan just based on the talent market. Again, it's evolved a bit today, and now you see more professionals. But that was probably the hardest part of why it took so long.

1:14:10Max Junestrand:How has it been adapting your historical approach and skill set and traditional private equity to VC? in PE, you can have a business that's extremely challenged, has like, you know, some amazing elements to it or bones, but like, you know, is not realizing its potential and you can wrangle it and get it back on the right track, get it growing, cut costs, whatever it is. In venture, I would say it's been, you know, the challenge in this industry is like you can have that same situation, but there's such a culture of like letting the founder call the shots and founders today have so much control.

1:14:52Max Junestrand:And so you're kind of in the situation where you can like make some customer intros, introduce some execs, you can try to give advice, but oftentimes you're like sort of hands off. Has that been any, any sort of like, how's that been? Because I imagine you on the venture side, you've gotten to the point where it must be like extreme frustration at times where you want to let the founder lead, but at the same time, things aren't working the way that they could be. I get frustrated with buyouts as well. But listen, I think we started as a private equity firm, but actually our roots were in kind of growth capital.

1:15:32Our first investment was Staples when it had like five stores. And so we started actually doing control deals, but also minority deals, having to work closely with founders. So I kind of feel like The culture of the firm and because we're a little more organic in nature, entrepreneurial, even you might say decentralized, we're comfortable with different modes as operation as a firm, I would say. But listen, at the end of the day, venture business, it is different. You're making investment decisions with much more limited information, oftentimes almost no historical information. You're evaluating talent and the ability of that talent to make changes and adapt as technology changes.

1:16:16You're trying to think through what the future is going to look like, and it's typically not a lot of information from what you might have seen before. And so I think we recognize that it's different, and that's why we have people who are great at that, and they have their own investment community process. And the way they do sourcing and make investment decisions is different, and it's different. We have a life sciences business, and by the way, it's very different there. They're all MD, PhDs who are making judgments on compounds and clinical probabilities that you don't want me making those decisions.

1:16:48However, the wrapper around all of it is this kind of value-added approach, whereas a firm and a platform, yes, we have relationships with big global customers that we can introduce to those venture companies. We know all the life sciences, the top 15 pharma companies. And so we can bring together those as maybe buyers of biotech companies, but also partners of those companies. We have a lot of, you know, we participate in the capital markets. And so venture businesses are going to need capital or they're going to go public. And so we can bring that, you know, synergy to bear across all these businesses.

1:17:20So the trick really is to have enough autonomy and trust in the team on the field to operate in the way that that segment operates, to be best in class there, but to bring a platform benefit to it. And that's, you know, you get that right. It's a very powerful, powerful model, but you've got to be comfortable, you know, letting go a little bit.

1:17:42Max Junestrand:How many mistakes can someone early in their career on the venture side of the business make before it's not a fit? In venture, you can make a lot of mistakes. It's obviously very important to have a few successes. But that is a business where it is about a much higher loss rate from a numerical perspective of deals. And what you're looking for there is really asymmetric upside from a few situations. And again, you don't want to bring the batting average model to venture. It's not a plugging percentage type of thing. It is actually something around, you know, triples and home runs and such. But I'm saying a mistake could be like losing a deal that could have, should have been done.

1:18:31Max Junestrand:Could have been a grand slam. So it's not just about, you know, your misses. You could have nine zeros in a banger. We call those the ones that got away. Listen, we study that in venture as much as we do in private equity, because what you're looking at there, what are our biases as humans that cause us to potentially apply too high of a discount rate to certain factors and maybe excessively fall in love with other things that may have worked for us in the past? And so, you know, that's something that's that's the continuous improvement process for the investment business that we engage in a lot.

1:19:10We do a lot of teardowns of our past investments and ones that others do. We have a massive set of competitive intelligence on all the deals that are done and we shade them, you know, green, yellow, red, which is, is that a deal we would have liked to have done? And how did it do? And we go and we look at that and our, you know, our teams do that. And that's how you try to get better at something that inevitably you're going to make those mistakes.

1:19:32Max Junestrand:There's been a number of businesses formed and funded over the last few years that are effectively just private equity firms that are raising like venture capital and getting like venture style. You know, the teams are getting venture style economics where fundamentally they're just set up to buy businesses like a traditional firm. Like a hold firm or something. How have you looked at those opportunities? To me, it seems like an amazing deal for the teams, because if you can retain 70 % of the economics instead of getting 2 in 20, why would you not do that? At the same time, from the investor side, it's like if I'm deploying into a traditional, basically, PE transformation strategy, you probably would prefer to get the majority of, you know, be paying 2 in 20, but not giving up the inverse.

1:20:27Yeah. Listen, I've generally found that the way you structure and kind of cut up the economics, that's not ultimately the driver of long-term returns through the cycle and through different market scenarios. And we've seen a lot of things that seem like they're great in terms of innovative technology around that, But ultimately, there's a there's an alignment piece that, you know, is missing that ultimately comes back to roost. And so, listen, our perspective is we want to be very closely aligned with our investor base and we want to have a similar time horizon. We want them to understand how we generate value and maybe how long it's going to take to do that.

1:21:14And then once we get there, how much we want to continue to compound versus how much we need to kind of return. We want them to be focused on ultimately performance, not fees. And we're not public, and so we're not interested in maximizing things that may not be in the interest of those particular investors. And so actually, I think the alignment question is critically important there. And there are a lot of schemes and ways you can kind of whack it up. But generally, that doesn't lead to a sustainable advantage from our perspective. But I think alignment can be really critical. There's been a story that's sort of crossed over from private equity world into the tech community, the venture world, which is bending spoons.

1:21:53And I'm interested in your perspective on roll-up strategies in tech and venture. Jordi has asked several previous guests, like, will we see an American bending spoons? I'm interested in, have you gone down roll-up lane before? Or does that model potentially apply in Japan? Or did you think about it while you were there? Just some history and context on what's going on with that. I think Bending Spoons is in the news because they're acquiring companies that people know. But obviously, it's not a brand new strategy. No, and I think they're pretty interesting. And it's a little bit back to the future because in the 80s and 90s in the U.S., there were a lot of fragmented industries.

1:22:36And that was one of the key modes. And we did a bunch of those which were buying a platform and then rolling things up. And then they also, you know, that got a little bit overbought because, you know, you remember these models where you're slapping these together with the hope of getting multiple appreciation. But you weren't really improving margins in the business and it didn't work. So I don't think roll-ups are good or bad. What I do think is interesting, Benning Spoons and some of the newer firms is actually the ways in which they're bringing technology and a kind of technology first approach to how they're sourcing and how they're driving value.

1:23:14And I do believe that is the future. And that is a model that we should be focused on because our history is all about transforming companies. We've had a very deep value creation orientation. We have a whole big dedicated team of almost 400 people that get in there and drive change at companies. And the ability to use, to apply AI to each step of that process to really turbocharge what we're doing, that will be the future. And some of the aspects of Benning Spoons is doing is, I think, pretty interesting there. And so we're looking closely at kind of newer firms, pure play firms that are able to do that.

1:23:53They're able to take kind of a technology first approach to what they're doing because Because that's a huge opportunity for us. How much of your time or the firm's time is focused on sort of like understanding the broader economic picture? A lot of in the venture world, you can sort of tune out interest rates. But it is on the cover of The Wall Street Journal, first Fed rate hike in three years. How much time is the broader team spending thinking about macroeconomics? How does that flow to the various teams? and what skill sets, what people do you need internally to actually make sense of the world reliably on an ongoing basis?

1:24:35Yeah. So, you know, for us it's been a journey because we've always thought of ourselves as like the micro guys. You know, we're going to focus on the things we can control at the company level or a managing team. But we increasingly became aware in the global financial crisis was the first, I'd say, wake-up call around this that macro factors, secular thematics, changes in the structure of the market can be big, big drivers of outcomes. And that you kind of need a different skill and capability to be able to analyze that. We all kind of thought of ourselves as we can understand that. But the data itself, you need some expertise to really be able to understand the signals from the noise.

1:25:16There's a lot of intelligence that can be gathered from even just our portfolio. We have 600 businesses across the economy. We're in credit. We're in venture. We're in life sciences. We're in private equity. And so if we can get real time information faster than our competitors, faster than the market and drive interventions, that can be a huge advantage, particularly in this world of heightened volatility. If you can see inflationary trends building up in your labor base or in your material base faster than your competition, that can be a huge competitive weapon. So we set up a whole separate macroeconomic team, dedicated people, PhD backgrounds, those who also have a lot of connectivity to other sources of expertise, whether it's on the energy and oil markets or whether it's on housing.

1:26:04And they come up with their own independent view. We don't have each of our deal teams go and come up with their scenarios for the U.S. economy. They come up with that. And then the deal teams are focused on taking that and applying it down to the sector and the company and seeing, okay, what were the implications for that? But centralizing this, getting much more expertise, getting better data, that's been the focus to try to stay ahead with the volatility of the world today. Yeah, that makes a lot of sense. Jordy, anything else? Not for now. Well, we're going to hop on with Max from Lagora. Thank you so much for hopping on the show.

1:26:36Congratulations. and all the progress, obviously. We'll talk to you soon. Have a good one. Cheers. Goodbye. Let me tell you about 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. And we have Max Junstrand from Lagora coming back to the show. How are you doing? Boom. Good to see you. Hey, John. Hey, Jody. We're great. How are you? Yes, it seems like you're great. Partnered with Salesforce, but you didn't have to stand up and shake Mark Benioff's hand.

1:27:06Max Junestrand:He must really like you. Yeah, he must really like you. I'm not one to get, you know, frame-mogged. Most people go to Dreamforce to buy Salesforce. We went the other way around. We went there to sell the Salesforce. Okay, that's good. Yeah, what is the structure of the deal? What are you going to be helping them with? Like, what did it take to get them across the finish line? The legal and the compliance team are embedding AI into every way they work, right? They're big cloud customers, but cloud only gets you so far. We're helping them go all the way. And what's interesting with a lot of the SF-based enterprises is most of them have tried many legal AI tools before, and they haven't received the success that they wanted, and now they're moving over to LaGuardia.

1:27:47It feels like the models are, you know, you're constantly in the back and forth between the frontier is the best, then open source catches up, the frontier is the best, and then the companies that are building on top of models and building harnesses and building fine-tuned models and specific workflows, that's going to give you a big lift. And then somebody's like, oh, the next model will just one-shot it. Have you lived through enough of these cycles now that I imagine you have a philosophy here? What's your philosophy? When I started the company back in 2023, it was very easy. It was one model, GPT 3.5.

1:28:21And we built every single functionality in Lagora as a boat. And when the tide rises, everything improves. And that continues to be the case. And what's interesting now compared to three years ago is that different models are good at different things. So if you break down legal work, there are so many skills you have to be good at. It's drafting, it's reviewing, it's fact-checking, it's legal research. And so under the hood, what we end up doing is we use all the models. The new MADAM models, the new GROC models, they're awesome. We also continue using the Frontier from Anthropic and OpenAI. And so what's interesting to us is where do you apply which model?

1:28:59And that's the IP that we have gotten really good at. And the reality is when you operate a vertical AI company, you need to make sure that you are getting the benefit from all of the R &D dollars that are getting spent in the entire marketplace. Right. And if you were to take a very opinionated view and say, let's fine tune a model to get, you know, 1 % increase boost today, that entire asset is going to depreciate over time. And you're basically making your customers pay for a model that won't stand the test of time. Yeah. Yeah, it's fascinating. How do you, oh, with the rising tide lifts the boats, you get the new capabilities.

1:29:39At the same time, there's probably old workflows that you built on top of GPT 3.5 that can now be run very, very cheaply. What is your strategy for cost optimization? Is it just like you go to open router and you pick a cheap thing or are you racking servers? We build our own router. I think that's a super important part of the stack. And over the last weekend, we actually drove a 30 percentage point decrease in our overall LLM spend across the entire platform. Which then becomes a weekend project for the engineers in Stockholm. We run on Celsius and snooze. I met the Celsius founder and I was like, hey man, our engineering team runs on this shit.

1:30:25And he just sent us a fridge. Like, I love the guy. That's amazing. You know, the team is in total blutzmuck. And that means, you know, I did an article in Swedish and for some reason they translated it to English. And so the headline became the Legora team wakes up with a metallic taste of blood in their mouth. And that is the status of the company right now. You see my decoration here. We are in this total, you know, land grab. Everything is happening all at once. You're seeing innovation across the entire stack. We have acquired five companies this year, and it's been fun to... Founder mode.

1:31:04Real founder mode. It's been fun to go deeper in the stack because in litigation, in transactional work, in legal research, it's sort of easy to do something on the shallow. And frankly, that was what we were doing back in 2023. But now we can go so much deeper. And I think that's also the places where the models don't matter so much. We're actually building much more normal software than we are building LLMs, frankly. They're just the electricity that powers the house.

1:31:33Max Junestrand:So I want to talk about Diffusion specifically. I have a portfolio company that's in the middle of a transaction. And I know how good Lagora has gotten. I feel like a lot of this work that's been done could have been done in like probably a week if like people really focus. But sometimes companies, for whatever reasons, like they want to drag something out, like it could be beneficial to one to one side for one reason or another. So like what are the actual factors at play right now? I really want to understand, like, have lawyers, like, internally, like, software engineers, they might have historically planned for a five-week sprint on a certain product or feature, and now they're saying, like, let's ship it in a weekend or let's ship it in a week.

1:32:20Max Junestrand:Are lawyers specifically in-house? Like, are they thinking that way now? And when are they not thinking that way just for kind of structural reasons? In-house is absolutely thinking that way. And so are law firms, right? Like AI is an existential opportunity and a threat to the current operating model. I was with a law firm here in New York last week, and one of their partners explained how the work that he typically does, he does in 1 30th of the time with no dependencies on associates. That's his practice, right? And so he has to figure out how do I now charge for this? Because working with a billable hour in his practice doesn't make sense.

1:33:00And at the same time, the biggest opportunity is perhaps an in-house where organizations like Salesforce, Palo Alto Network, etc., are bringing in these tools in-house to do more legal work. And what's interesting about legal work is that the demand is effectively infinite. If you could have legal intelligence review every contract, handle every claim, you know, fight every litigation, file every patent, like you would. Right? And from an investment perspective, why not do a legal due diligence before you take an asset to IC? The reason you don't do it today is because it's expensive.

1:33:37Max Junestrand:How are you thinking about this arms race? Because you have on one hand it's like cheaper than ever to litigate something, but it's potentially cheaper to defend. Yeah. Yeah. And so on. Kevin's paradox is it could be a lot more lossy. At the same time, if it's cheaper to defend, maybe a company is less likely to settle early so there's less reward. like there's a bunch of these different jury trials. Every judiciary is overflown by employee claims. And people are using ChatGPT to figure this out themselves. And the companies are needing better tools to defend themselves at scale. We work with some of the largest insurance companies in the world on settling litigation claims, right?

1:34:18And it's so interesting, like airlines. We work with Air Canada. They are spending so much money in litigation claims with customers, et cetera. And I think, you know, if we develop bioweapons with AI, like good news, we can also develop cures, right? Like it's sort of everything will just move faster. And I think operating in that world, what's so interesting about being like this full AI native characteristic of a company is you can do that across every single part of the business. And your operating model just has to be what a traditional software company did in a year, we have to do in a quarter, right?

1:34:59Like four times this year, we have leveled up our end year post for our revenue targets. And now we are quintupling this year. Like we are setting targets that by traditional software standards would have been deemed, you know, gravity defying and insane. Yeah. Talk a little bit more about the M &A strategy. I feel like from your seat, I could imagine everything from like acquiring a small law firm in a niche area. No, no, no, no, no, no. No? We are not a law firm. You're not going to be a law firm? We're not a law firm. Okay, so are you acquiring other application layer companies or teams that are deeply in like the AI research?

1:35:42Or are you going to acquire a neocloud? Like how narrow is your lens when you're looking for acquisitions? Yeah. Well, first off, we have a big part of our EPD team in Stockholm and in Europe. And what's so amazing about that is I think we're the number one employer in our jurisdiction, right? Like we get our sort of top of the mountain, like we get the cream of the top. All the best engineers want to come work here. And legal tech is really hard to break into from a trust and commercial perspective. Yep, that makes sense. But there are a lot of very technically talented teams who are working in this space.

1:36:17And so at Legora, we have what we call our fruit salad product strategy. When alternatives are offering apples to apples, we are offering the apple, bananas, oranges, and fucking kiwi fruit. And we want to have all of the functionality in one single space. And what's so awesome about that for the lawyer is that they don't want to navigate 10 different apps. They want to have Word, Outlook, Document Management System, and Legora. And when all of the functionality gets sucked into one single place, the barrier to entry gets lower. We're seeing this in a lot of the customers who are moving over to LaGuard from other legal AI platforms that they might have adoption, but they have very shallow adoption.

1:37:03They haven't gotten sort of second and third levels deeper where they're going, let's not just use this as an expensive chatbot. Let's really think about how it's going to transform either our practice or the way that we operate in-house. Well, congratulations on the progress.

1:37:19Max Junestrand:Just very curious. Right now, if somebody – like people are using just regular consumer chat apps for legal counsel. I don't believe that that gives them sort of attorney-client privilege. Do you think that will be solved? Like, will someone be able to make a, you know, consumer, you know, application that allows them to have that experience? That's a very interesting question. That's a very interesting question. The good thing is there are attorneys and lawyers and judges much smarter than me who are going to determine whether or not that's the case. There's going to be litigation around that, of course.

1:38:01And we just get to play around in that space. And I see Chase is about to come on here after me. to give you one Bain story and he can fulfill the second half of it I met Chase at a dinner in Paris with Chathan our partner from Benchmark very late in the evening Enrique from Bain calls and he's like hey I'm gonna crash your dinner and we get into this stratospheric wine competition between Bain Capital and Benchmark and I'll let Chase finish the rest of the story That's the best glasses land ever. That's hilarious. Stratospheric wine-off. Wine-off. Go in glass bottle for bottle. Stratospheric wine.

1:38:45That line was from one of our French attorney customers who said that that was the best dinner he ever attended. That's fantastic. We love you, Max. It's always fun. Always a great time. Come back soon. We'll talk to you later. Thank you, Dom. Have a good one. And we won't want to keep Chase waiting, so let's bring in Chase Lockmill from Crusoe as soon as possible. We've got to get the other side of the story. This dinner in Paris, we just heard about it from Max with Lagor. Was the wine as good as they say? It was. The wine was flowing that night. Okay, that's great. We went through a significant amount of wine, and I didn't see the prices, but I think they were not cheap.

1:39:28Stratospheric. What about the electricity? Is the electricity flowing? Yeah, yeah. Are the chips flowing? How is progress in building out the compute capacity that people need? Yeah, the electrons are flowing and they're turning into tokens and helping accelerate this new era of AI abundance. Yeah, I mean, look, I think, you know, as demand for AI infrastructure has grown and demand for power has grown, you know, there's been a significant amount of investment in real world, you know, power production capabilities and facilities that are becoming, you know, real significant bottlenecks towards this build out.

1:40:13And so each incremental gigawatt is getting increasingly more challenging. Now, the positive side is that I think a lot of the investments and the foresight that we had at Crusoe are paying dividends today. And if we look at all of the progress that's been made in the campus in Abilene, Texas, our philosophy in designing and building that campus was how do we build a gigawatt-scale computer? How do we build a single facility that can act as one giant coherent cluster that can train the next breakthrough foundational model that will lead to a step function improvement in the model capabilities?

1:40:56That was the North Star when we developed the campus and designed it. Today, we're seeing the fruits of those labor.

1:41:03Max Junestrand:Yeah, and you had to go through – there was like a six-month period where it felt like there was a different article every single day about Star. If somebody sneezed in Abilene, there was somebody that was going to write an article about how sneeze causes one second delay. One second delay. But it feels like you guys have gotten through that. And I haven't seen a front page article about some minute detail of the process in a while. No, but what I was going to say is the benefits of that is the first two buildings, which were the initial contract that we did with Oracle and OpenAI, have led to the training of Astra.

1:41:46I don't know if you've had a chance to play around with, but it's a really phenomenal model. Yeah, it's super impressive. Yeah, and Jensen had some nice words about it too. Yeah. And the next phases are coming online with buildings three to eight, which is going to basically quadruple the compute capacity. Three to six are already online and seven and eight will be coming online before year end. And having that full eight building compute capacity to train the next version, the next incremental improvement of the model, I think we'll see that function improvement and capabilities. You started the company in 2018, going on almost a decade in business.

1:42:27Can you give me a sense of the progress from the smallest project, the first project? How small was it in terms of megawatts and where we are now in terms of scale? Because I feel like that has been the biggest transition is that you started with pretty small projects and now you're working on the biggest projects in the world. Sure. So, you know, the philosophy of the business, you know, from day one was taking this energy first approach to computing. You know, we named the company Crusoe after the character Robinson Crusoe, who was stranded on a desert island and had to be innovative with his resources, you know, in a stranded environment.

1:43:07And, you know, we try to channel that same sense of innovation applied towards stranded energy and unlock stranded energy or unlocking value and stranded energy with computing. And so that led us to unique energy resources to power compute in early days. And we were actually working on generating our own power with otherwise flared natural gas. We were capturing this waste methane, utilizing it to produce power, and then powering these mobile and modular data centers. Our first use case was Bitcoin mining. But, you know, we sort of even at that founding of the company, we had this ambition to build an AI cloud platform, which today is, you know, where Crusoe's at is this vertically integrated energy first AI platform.

1:43:54So the early days, it was roughly 250 kilowatts was the first block that we did, which was actually pretty big. Yeah. First AI data center. We're actually putting up in like a Crusoe Spark Museum that we're building. and it was like, you can kind of think of it as like a single individual rack. I think it could power up to 25 kilowatts. So it was like higher density for that era. And we've since sort of evolved our platform quite a bit to gigawatt scale campuses at one end of the spectrum. And we've made an announcement, quite a few announcements around the Crusoe Spark product, which we believe is sort of the critical aspect to really scaling inference compute infrastructure as demand for token scales.

1:44:44You don't need a gigawatt scale computer. You need lots of smaller clusters of compute to rapidly serve inference infrastructure and really dramatically reduce that time to token. And Spark gives us a ton of flexibility in terms of how we deploy inference infrastructure, where it goes. And then also just from a time to token, it really provides us a lot of just-in-time solutions for delivering AI infrastructure for the innovators in the world. It seems like solar deployments keep beating expectations. We've seen this chart of the predictions of where solar will go, and then the graph keeps going up to the right.

1:45:26Where are you seeing exciting movement in new energy coming online that might be suitable for that type of product, the Crusoe Spark, you know, smaller amounts of energy required, but unlocking new opportunities in different locations? Well, you know, solar is definitely like a very compelling use case. You know, we, with our partners, Redwood Materials built the largest microgrid in the United States that was solar plus batteries. And the batteries were actually taken out of, mostly taken out of electric vehicles. So sort of a second life use of these lithium ion batteries. And, you know, those AI factories are powered 99 % plus just by the sun, which is a pretty cool case.

1:46:15You know, there's a lot of new energy technologies. We're focused on, you know, helping catalyze and accelerate. You know, we had a big announcement with Ollo to bring to life the first SMR powered AI factory, which we're planning to go live with by mid 2027. But, you know, what's unique about Spark is, you know, given the small modular form factor, there's so many different, you know, there's so many unique ways you can power it. It can, you know, you can power it with like small gas generation, things like recipes and, you know, smaller gas turbines like aero derivatives. You can also power it just in, in you with, with, with grid power.

1:46:51And, you know, there's a lot of while getting a gigawatt of power from the grid in a single location is quite challenging right now. There's a lot of places where smaller pockets of capacity are available. You know, think whatever, 10 to 100 megawatts that can be accessed like way sooner because of, you know, transmission and distribution constraints that are that are happening in the grid. and like plugging into one node may actually help create quite a bit of balance in terms of the load balancing that the utility operators are needing to do. And so it can actually help benefit the grid quite a bit because you're actually amortizing more megawatts over the same transmission and distribution infrastructure, which should actually bring down the cost for all local rate payers.

1:47:38And we think that's an exciting proposition because you're shifting all of the work offsite and you're able to plug into a lot of these unique energy, available energy on the grid. Yeah, that makes a lot of sense. Talk about the new round. Yeah, you raised some more money. We did. So today we announced the closing of the Series F at Crusoe.

1:48:08Max Junestrand:Here came in. Saw some heavy hitters. Oh, yeah. Yeah, it never gets old. The, you know, the series F round of funding was co-led by Atreides, Valor Equity Partners, and Mubadala. And we had, you know, a number of, you know, a number of great supporting investors alongside it. Folks like TPG, QIA, Founders Fund, Radical Ventures. You know, it was a great, great list. GIC was another great partner. So, you know, there were a number of great investors and, you know, we're really thrilled to have the support from, you know, a number of leading, you know, long onlys, growth investors and venture investors.

1:48:57Yeah, that's amazing.

1:48:58Max Junestrand:Long onlys. It's the only type of investor I like. Yeah. Thank you so much for coming on. Great to see you, Chase. Great to see you again. We'll talk to you soon. Talk soon. Goodbye. Let me tell you about Shopify. Shopify is the commerce platform that grows with your business, lets you sell in seconds online, in-store, on mobile, on social, on marketplaces. And now, with AI agents, up next, we have Justin John from Decagon. Welcome to the show. Welcome back. How are you doing? It's been too long. Good, good. Yeah, it's good to see you guys again. Where are you in the world? You're expanding internationally.

1:49:36Are you in America, Sao Paulo, Brazil? I'm in, uh, I'm in Sao Paulo this week. So we're out here launching our, uh, LATAM office. So we're, we're starting an office here in Sao Paulo. Got a couple of customers down here already, like, uh, Mercado Libre. So we really felt like things are moving pretty quickly. So got a team out here now. What is the key? What, what, what seats do you want to fill in that office? Uh, I mean, obviously you need, you know, the general staff, but, uh, is it about sales reps for deployed engineers? What problems does it help to have boots on the ground effectively in the local community?

1:50:14Yeah, it's mostly go-to-market. I think obviously there's language considerations, right? So anytime you go to a different market, it's both the product, right? So we deploy these voice agents. So the voice has to be really good at Brazilian Portuguese, but also our go-to-market teams have to be on the ground and being in people's offices and so on. So it's mostly just the go-to-market teams.

1:50:35Max Junestrand:Yeah. What's happening with Diffusion, every time I have to be on a customer support line and I'm not speaking to an effortless agent that has all the capabilities that I would expect that I know are available, I get a little bit angry at you and the other players in the space because it's like, why are you moving faster? It's like, I just know. I know the technology is here. why do I need to sit on another phone tree and and you know like they that doesn't even do a good yeah I just want to talk and I just feel like being able to effectively prompt to the outcome that you want is like so clearly here and and still it's like so many of these things you're like real world what's your what's your address what's your this you know all this stuff it's like enough we're trying uh I'm trying our best I mean I can tell you like what is the long pull in the tent.

1:51:29Roughly the analogy we like to give is us delivering an agent is a little bit like building a self-driving car where the car is now smart. The models are really good. You guys have used the models. The brains of the car are good, so it knows how to drive. But when you arrive in one of these big, let's say, airlines or banks or healthcare providers, the map of the surrounding area is not drawn out yet. Drawing the map is usually the hard part. Someone has to make the jump between the car being good, but then actually drawing the map and figuring out where to go. So a lot of the time that we spend in these deployments is really making sure the map can be drawn out well and then improved upon over time.

1:52:06And our job, hopefully, is to shrink that time over more and more deployments. And so that in the future, every single time you call, there'll be a good AI agent there that can talk to you. Please. How do you think about, how do you assess opportunities internationally? I would love just lay the land of the core business, why you thought it was the right time to expand internationally. And then I imagine that there's at least a spreadsheet or some prompt that you ran through, some analysis that you did to land on Brazil. But what is your actual process for evaluating a new market to expand into?

1:52:46Yeah, I mean, international expansion is not a novel thing, right? So tons of countries have gone through it. So we've been able to learn from what other people do. And usually most of the traction comes from a small handful of countries. When we first started the company, we were mostly serving the upper mid-market-y tech native companies. And so that's where we started. And then our first order of business was, hey, we actually do think that our approach to launching a product will work in the big enterprise. And so that was a lot of the big focus in the first year and a half. And so now we've announced a lot of the big banks, Deutsche Telekom, American Airlines, Delta Airlines.

1:53:23So a lot of these big customers. And from there, we're thinking, okay, what's the next frontier? Probably is international. Europe was the first pillar for us where we launched a London office and we have customers in Germany and the UK and so on. And then from there, we were just thinking, okay, well, the two options for us honestly ended up being Australia and Brazil. and it's kind of a mix of how quickly are people adopting tech? What's the size of the market? Can we actually serve those customers? And we decided yes. And so now we have a small pod in Australia and now launching in Brazil. And I think for now that is like a pretty good spread for us.

1:54:02But in the future, we'll probably look for what is the next frontier. Is there an element where customer pull is really important? Like MercadoLibre has a bunch of employees in the United States. You probably meet them at conferences. The conversation can start before you even open the office. It sounds like you already have a contract in place. But you're just seeing pull from a certain big enterprise and anchor client. And then that can justify going bigger. Yeah. Yeah. I think that that is pretty correct, right? It's like, okay, let's just get a feel for the pull first before we deploy a bunch of resources.

1:54:38The same happened in Europe with DTE, where we kind of originally started working with them when we just had a team here in the U.S., but then over time we realized, oh, wow, people are moving pretty quickly. We need to be on the ground, and so that's what prompted us building a team out there. Yeah. What are you tracking? How closely do you track the progress of the models versus the cost and the Pareto curve of the models? Are token costs falling fast enough? Is it roughly perfectly on trend from what you've modeled? Is it faster? What can you tell us about cost optimization once you get a system that's superhuman or at high quality?

1:55:20I imagine that you're not just upgrading to the latest frontier model and just adding costs because some of the models, when they come out, they're better, but they're more expensive. Yeah, there's kind of two dimensions there. So on the cost side, typically what you do is you first get your product working. And then once it's working, you realize that most of the model calls you do don't need the entire model because the model does a ton of stuff, right? So you don't need it to compute math for you, for example. And so then the intuition is like, okay, well, over time I should be able to use a product.

1:55:52problem at a customer service every once in a while just to see if there's a shot. That would be tough. But yes, I understand. Yeah. And so over time, you want to shrink the models. And then it's more of a question of like, okay, is that possible? Can you take a smaller model and fine-tune and post-train it to perform at the same level? And so far, I would say in our use case, the answer has been yes. There's a lot of these small tasks that are done inside the brain of the agent, like choosing a topic or detecting for hallucinations or whatever. and so you can use small models and specifically open source models to do those but when you're launching new products and kind of trying new capabilities of course the frontier makes sense and so those two go hand in hand and then for us latency also matters a lot so we talk a lot about how you have to not just optimize costs like optimize latency matters even more to us probably and so when we've done these optimizations we're mostly seeing if we can get the latency down because if you're talking to a voice agent it has to be super snappy and those two go hand in hand as well.

1:56:53And is that the model or the chipset or both? I imagine that we're not quite in the age of co-location or like edge computing, but it feels like that's coming as well as a small 100 millisecond savings potentially. It's mostly the model. Most of the gains come from making the model smaller. Yeah, okay. Eventually, if the model is like so optimized, you could start looking at some of the other things, but - So make the model really small, Then you bake it onto silicon. Then you put that silicon right in the city where the customer service is happening, something like that on the edge. And then you're at two milliseconds or something maybe.

1:57:29I don't know. Yeah. Very exciting, though. Thank you so much for hopping on the show.

1:57:34Max Junestrand:Great progress. Great progress. Great to see you. Cool. Thanks for having me. Talk to you soon. Cheers, Jesse. Enjoy Brazil. Let me tell you about Railway. Railway is the all-in-one intelligent cloud provider. Use your favorite agent to deploy web app servers, databases, and more, while Railway automatically takes care of scaling, monitoring, and security. next. We're the founder and CEO of Beacon and the VP of AI Research. Beacon, Nylon, Leonard. Welcome to the show. How are you guys doing? What's going on? Hey, guys. Good to see you again. Welcome back to the show. What's happening? I would love for you to start with just a reintroduction on the strategy for the company, for the firm, and sort of how it's been going since we last talked, I think, almost a year ago.

1:58:16Yeah. Yeah. Yeah, that's right. Yeah. So just a reminder. Beacon is a holding company. We acquire great technology companies that have been around for decades that already serve real economy businesses. Think campgrounds to labor unions to youth sports leagues. We take those businesses, pump them through our software factory, and then make them AI native. The whole goal is to make the real economy as AI native as quickly as possible. And the last time we talked, I spent time talking to you about our acquisition machine. At that time, you know, we were acquiring a business every three weeks or so.

1:58:53Today, we're closing on a new business every 10 days. And today, really, I'm excited to talk to you about our most important acquisition, I think, in Beacon's history, partnering with Leonard and the Hayes Labs team. Yeah. Yeah. Leonard, give us a little bit of your background, what you built and why you're excited to join. Totally, totally. I don't know about most important acquisition today, but it's certainly an exciting acquisition for both sides and hopefully we can bring a bunch of the Hays technology and talents to the rest of Beacon's existing portfolio. So a bit of background on myself, I'm Leonard, co-founder and CEO here at Hays Labs.

1:59:27Hays was an AI safety company founded out of my research over the last five, six years where we're focused on red teaming, guardrails, observability, and evals, both for the frontier labs, including OpenAI and Anthropic, who are our first customers, actually, but also for large enterprises. Think big banks, Fortune 500s, insurance companies, healthcare companies, and so on. Does this mean safety is solved?

1:59:50Max Junestrand:Is the job finished? We can move on to bringing AI to uSports? Safety is always an ongoing challenge. I think as capabilities advance, you always have to play catch-up in some way, even though your normative declarations of what AI should and should not do can be set in stone, the way in which you operationalize the definition of what it means to be safe or not safe changes as the capabilities advance. And insofar as joining Beacon goes, I think bringing AI to the real economy is a unequivocally good thing and responsible thing to do if you're an AI technologist. But also from the perspective of the alignment conversation and debate we've been having over the last couple of days, one thing we've thought a lot about at Hayes is whose values should AI models actually be aligned to?

2:00:39And you can take the perspective if you're anthropic or open AI that you have the best control and that you have the best wisdom around what values should be baked in the models. But it is our sense as Hayes and Beacon that we should try and make contact with reality, in particular those that have been historically undeserved by Silicon Valley technologists, like businesses in the real economy, in order to align our values to those businesses and the values of their customers. And that's part of what gets super amps to join the Beacon team. Very cool. Yeah, just to give you guys, just to add to that a little bit on the safety conversation, everyone knows the real economy is behind on AI adoption.

2:01:19There's many reasons for that. You know, the ramp data from about a quarter ago showed that SMBs are only 20 % adopting AI versus like 85 % for the Fortune 500. We started Beacon to address that gap. But really, Leonard and team are going to play a key role in that. The reason why adoption is so low in SMBs, some of it's a question of access. But really, as we spend time with our 22 ,000 customers, it's a question of trust, first and foremost. The real economy will not adopt AI if they think it's going to run rampant and screw up a bunch of their own relationships with their customers. So Leonard and his team, part of why we wanted to bring them in and why Leonard's leading this important function for us is so that we can ensure for our end customers that when they deploy AI through one of our pieces of software, it's done in the safest way possible.

2:02:15Yeah. I like to say that Beacon has a trust in the customer relationships already. I mean, these businesses, the real economy in the world depends on these businesses. and I like to say that Hayes builds AI that anybody can depend on. So now you've got both parts of the equation. You've got AI the business can depend on and the real world is depending on the businesses depending on this AI. So I think it's a very natural fit.

2:02:39Max Junestrand:Ground this for me. Where's AI been most useful in something like campground operations since I know you guys have acquired some campgrounds? And it's so funny. It's still so funny to me that And, you know, as you guys get bigger, there's definitely going to be some articles of like this AI company is taking over youth sports leagues and campgrounds. I'm very excited about it. We were just on with Jesse, and I was telling him I'm frustrated that I still will end up on a customer service call for some service. And I'm on some legacy system that has no AI at all. It doesn't have any ability to reason or help me get things done.

2:03:19Max Junestrand:And I can imagine a lot of use cases that like in the campgrounds. In the future, you don't have to go to the campground. You just generate a similar perfect simulation. And you're just sitting there. No, that's a great, great point. Look, we are believers in AI abundance. The thing that's exciting, especially for the real economy, is we can help them solve problems that before they were not able to solve. So on the campground side, if you put yourself in the shoes of one of the 18 ,000 private campground owners across North America, you're spending 40 % of your days doing payroll, HR, budget compliance tasks, using a spreadsheet to figure out which camper needs to be assigned to which spot in the campground.

2:04:05Today, we have built tools within the software they already use to match guests to campground spots, to do dynamic pricing, to make sure that they're pricing appropriately for season, to load balance staffing for when campers are actually going to be there. So that is, you know, as to use a term Leonard just used, unequivocally good for the campground owner. But also we think that's how AI abundance actually translates into the real economy. It's how do we unlock more growth for the real business? You know, one thing that people always ask me, okay, you guys are just going to use the AI to take costs out or reduce headcount.

2:04:44Across all of our businesses, we're actually up headcount. So we found the opposite as we've delivered more AI, our customers. Yeah. Yeah, there's been a bunch of reporting on this in The Economist and The Wall Street Journal about like the AI actually driving increased hiring as growth comes in, which is fascinating.

2:05:00Max Junestrand:How are you guys, do you guys imagine, you know, doesn't feel like now's the right moment, but five years from now, like, you know, robotics being a big part of the strategy, you'll have all these existing businesses. And as different form factors get better, you'll be pretty primed to bring in these new form factors. Yeah, I'll start. I think that's part of it. Go for it. Yeah, go for it, Neil. Yeah. Yeah. We actually have businesses today that serve various industrial markets. So think about software that helps large construction sites manage their tool inventory, software that helps oil rigs stay safe.

2:05:41And increasingly, we're seeing this marriage of AI-native software with hardware like GPS devices, et cetera, to be able to increase the surface area of what that piece of software can do for the end user. You know, one of our customers, which I can't name, which is like a Fortune 500 construction firm, they're saving millions of dollars today on tool supply because, you know, we actually help them manage these industrial tools that are being used for the data center build out across the economy. In the old world, before we applied AI to help them match tool to job site appropriately with GPS, a construction manager or project manager at site would over-allocate and over-buy tools, basically, to make sure that they're not going to be short.

2:06:28So this was a huge problem for the company. They worked with our team. Our four deployed engineers went down to Houston and helped them. We built a new module for them, which basically AI matches tools to job site. then we put in GPS trackers to make sure the right tool got to the right site. Leonard, sorry, you were going to say something too. Yeah, I mean, I think you guys are being super prescient about where all this technology is headed. Certainly robotics is going to mature quite a bit in the next five years. And I think robotics or not, I think there's going to be a huge category of value you can deliver to our companies by essentially being able to dispatch AI employees or digital employees or whatever you want to call it at will.

2:07:06And so it could be something as simple as an AI SDR helping you find leads from your existing network. It could be something as simple as an AI support engineer helping you deal with tickets and bug bash. But I think there will be this huge supply of intelligence at your disposal if you're an owner-operator for you to go and lever up your existing strategy, team ambitions at your company. I also do think, separate from just digital employees, Beacon is in a very unique position to go after what I would describe as world models of companies or company world models, i.e. models that can help the existing owner-operator as a true thought partner and strategic decision maker think about what's going to happen next in their business and anticipate the best choice and action they should take to better run their business.

2:07:51So I think there's this pure question of, can you deploy more intelligence to level up existing objectives? Then there's this separate technical challenge of, can you actually help the business owner figure out what objective to go after in the first place? Well, thank you so much for coming on the show. Congratulations on the deal, and we'll talk to you soon. Very cool, guys. Have a good one. Goodbye. Thanks, guys. Let me tell you about the New York Stock Exchange. Want to change the world? Raise capital at the New York Stock Exchange. We got Joe Weisenthal here live in the TVP in Ultradome. I can't believe I'm here.

2:08:20I can't believe I'm here.

2:08:21Max Junestrand:I know, because you've been here so much. Well, I've been here spiritually so many times. And in my dreams, I wonder what the studio is like. And will I ever make it to the temple? Will I ever see the gong? Bring the gong. Will I ever hit the gong? Give us some excuse. 10 years? I was warned by one of your producers. It hit the gong for a hike. 25 basis point, right? Yes, yes. That's what we're hitting it for. Smack it. Boom. Oh, you gotta go way harder. You gotta really, like it's a baseball bat. I was told it was a baseball bat. Like you're swinging for the fence.

2:08:59There we go. I'm done now, right? I can leave. The whole point was just to bring me in to hit the gong. What else do I have yet to achieve now in my life? What summit's yet to climb. Yeah, what actually brought you to L.A.? We, oh, funny you should ask. We are doing a live show tonight at the Vermont Theater in Hollywood where we are going to attempt to do a survey of what is this thing called the L.A. economy. So we're going to be talking to some of the industrial guys. Chris Power from Hadrian is going to be on. Tom Mueller, the first impulse space, is going to be on. We have some of our favorite internet characters.

2:09:39Taylor Lorenz, Rachel Carton is going to be there. So it should be a really fun night. I have no idea what to expect. I don't know anything about this town.

2:09:47Max Junestrand:You're trying to survey the LA economy, but you've picked out some of the bright points, to be honest. No, it's like... You're negging your own city like that? Oh, I mean, the city's a disaster. You can't even hold on to a movie studio. but then you get this but then someone gets to take this yeah the bright spot is like the individual creators are doing well there's cool stuff in industrials and space yeah but uh the whole long la movement like fizzled out right before you got this sort of i'm super long la really absolutely you know i was just talking to you know he just gets it no i'm super long Yeah, it's the weather.

2:10:31And what's there to be optimistic about? Look, the thing that will never cease to mystify me, right? So Americans over time, they migrated westward, etc. And no offense to them. I'm sure they're lovely people. I'm like, wait, you guys stopped in Nebraska? You could have gone on your wagon for another 72 hours. It was right there. And it's like, what? And I like in my like in my time to backfill American history is like, how did we all not just come to L.A. right away? And I do not believe, regardless of what happens with Hollywood, that there will ever be a time where people just do not want to live in this climate by the beach and they'll find an industry for them.

2:11:19Yeah, it is crazy that California, I mean, we got three coastal cities, San Francisco, San Diego. But it's always shocked me that if you drive.

2:11:27Max Junestrand:I'm just completely ignoring every other. No, no. If you drive halfway between L.A. and San Francisco, there is not a metropolis with an international airport there. Like you go below like Marin or Laguna Seco. That's the only place I know. Monterey. Yeah, you go below Monterey, and then you get into beautiful areas, but it's mostly camping, and there was never like an enforced, you know, metropolis that built it. No, it's kind of strange. You know, a couple years ago, a good friend and I decided to—we had just, like, never been driven the Pacific Coast Highway. Yeah. So we're like, let's drive from San Francisco down to—what's the place down there where they have the town where they have Coachella, Palm Springs?

2:12:10Yeah, yeah. Anyway, we did. And it was beautiful. Wait, you hit Coachella or you just went to the town? No, no, no. I just wanted to see that town. You just went to India, yeah. And it was a beautiful drive. Yeah. But at some point, I have to admit, it's very beautiful. I have to admit, it's like, oh, there is another beautiful coast. Yeah. It sounds like I'm getting a little bored of this. Oh, there's another beautiful cone. It also takes so much longer. They drive at the five. So then we had the thought, it was somewhere right around where the Hearst Mansion is. We're like, why don't we drive inward?

2:12:37Because no one sees like. Yeah, yeah. So then we like went through like Fresno. Yep, a lot of farmland. And like miles and miles of almond farms. Yeah. I loved it. So now I'm actually like, yes, there should be another. Cattle ranches. Yeah. So it's like, of course, yes, there should be another megalopolis somewhere like on the coast. But also I think that like if someone visiting L.A., at one point you should do the inward drive and see where they make all the almonds because it's amazing country out there. That's how it used to get back from L.A. to San Francisco. L.A. is in a bad spot.

2:13:09Max Junestrand:L.A. is in a bad, bad spot. I know. I'm generally – the point of optimism is the weather. That's been the durable point. But the weather can get a town through some bad eras, right? Because if everything is actually headed the wrong direction, but the weather is simply so good that when you open the door... It'll be fine. It'll get you through. I'm very bullish. So move here. Yeah. I mean, look, when Detroit got hollowed out after the shrinking of the auto industry there, et cetera, it's like what was keeping people... They didn't have the weather. Oh, true. And so like, you guys have the weather.

2:13:53It'll be fine. Wait a couple years. It'll be fine. It'll be fine.

2:13:59Max Junestrand:I'm waiting for whatever industry can bring great opportunity to L.A. again, which it just doesn't feel like. Like I moved here after college, and I thought it was great because it was much more affordable than New York. I'd have friends visit from New York and they'd be like, you get like this crazy loft for what would be, you know. See, in New York, I believe there's this perpetual conversation that has like, should I move to California? These days it's more SF, but for many years, the discourse among people in New York is like, should I move to L.A.? You know, like it seems pretty nice out there.

2:14:38I get the impression and maybe you guys could tell me if I'm wrong. Like, I feel like once you get here, you don't have the reverse conversation. Oh, should I move to New York? I feel like it's like, oh.

2:14:48Max Junestrand:I was kind of, I've felt that way. You've felt that way. I've felt that way in the past. But I think you're unique in that. But spiritually, I've always felt at home in New York, even though I've never lived there full time. Well, that's the lovely part of New York. You are spiritually at home in New York. You don't think converting the Paramount lot into a data center will keep people here? That seems like a lot of opportunity. Yeah, I mean, it's worth a shot. I mean, look, the question, if there is a new industry in America that creates jobs, then some of them will be in L.A. Yes. I think the question is, and it's not in L.A., will there ever be another industry in America that creates jobs in large scale?

2:15:27Yeah. If there is one, L.A. will be fine. If there isn't one, then it's not just going to be an L.A. problem. Even older people driving elderly care, health care hiring. Yeah, right. But it's not just going to be an L.A. problem. Like if that's the issue, if it's like we can't think of the industry, then like I guarantee it's not just an L.A. problem. Yeah, yeah. What do you think of the latest in the AI data center discourse debate? It felt like we were grinding towards a crescendo there, and then we just took a hard left turn into AI risk, X risk.

2:16:03Max Junestrand:I think so too. I think that actually – It's almost like it was coordinated by powerful, shadowy organizations. That's Ian Bremmer's take. Ian Bremmer's take is actually that the X-Risk debate is to distract everyone from the real problems. Not just data centers, like brain rot and slop and all the other complaints of people, job displacement. And he's like, the AI lab leaders, in his view, I don't know if I fully agree with this, but in his view, he says, I like there's nothing an AI lab leader loves more than talking about ask X risk. It's pure upside. Well, I would say two things. So one is it already feels like if you're sort of a politician and you're still talking about data centers like, bro, that was a month.

2:16:45Like we've like moved on to model risk and stuff like that. So it does feel like actually very quickly the data center conversation disappeared among political discourse. My cynical version of the Ian Bremmer take, however, is slightly different. But maybe it converges on the same thing, which is that actually – because before data centers and before the X-Risk debate, it was the job loss debate, right? And so this question is like, oh, will AI wipe out 50 to 100 percent or even 10 percent of white-collar jobs? And the, you know, if you read the op-eds from the, you know, the Demi Sasabias of the world, this is what they were talking about.

2:17:28My cynical take at the time of those was they're very concerned about X-Risk. What is something that we could talk about that would distract from it? Oh, interesting. Not distract from it. What is a way that we can sound the alarm? Soften it. What is the way that we can sound the alarm about AI without sounding like a complete bunch of loons? Totally. Well, let's talk about job loss. Because that feels like— Because certainly we can't get an AI doomer on Joe Rogan. They'll never go for that. So let's talk about jobs because we can have that conversation. And also job loss is the type of problem that the three of us could come up with theoretical answers.

2:18:08Totally. Oh, we say like maybe 10 % of open AI gets into a national fund. Exactly, exactly. There's practical solutions. Economists will engage. Well, it's also another way to think about it.

2:18:20Max Junestrand:You could tell somebody like an asteroid is going to hit the earth in 2050 and people would still go to work tomorrow. That's totally true. But if you're like sitting there and you have like these very deep intuitions and you've been reading like Bostrom for 20 years, what are you concerned about? You're concerned about the X risk. How do you get people to just first of all, take the idea that AI risk is a big deal. Or AI is real. Or AI is real. Let's start with the job loss conversation. It feels tractable. It feels theoretically solvable. It's like, oh, we need an UBI. And so my cynical take was that the only reason or the primary reason they talked so much about the job loss stuff is because it was a way in to warn people about AI.

2:19:05It didn't make them sound like sci-fi. But that feels like that backfired because we're sitting here and there hasn't been massive AI job loss. And so it's easy for people to be like, these are the people that were telling us that there was going to be 25 % unemployment. And that hasn't happened. So they're saying 10 % chance. Like, I'm betting against them again. Yeah, there's this weird thing going on. I certainly think this is true, which is, I don't know. You see these people as, like, top-ranked AI forecaster, right? Or, like, capabilities forecaster. And many of them do have, like, pretty good track records.

2:19:37Yeah. Except on the question of what will be the impact of this technology. Exactly. They're all internal. They're all internal. Right. It's like, yes, I was able to predict model progress by the amount of compute that was built. And also, wow, he also predicted the number of chips that were going to be bought. He also predicted the number of data centers that were going to be built. And it's like, those are all downstream of the exact same line. You're just extrapolating things that are directly correlative. Yeah, except the one thing that no one has had any good intuitions on. I was like, when are we just going to feel this in our day-to-day life?

2:20:08And it's pretty weird now that the conversation has evolved to like the ex-risk conversation because it's like you step outside. It's like life feels really normal. You know, I was like talking last night. We were like talking to like – we were at this conference of like financial advisors, et cetera. And it's like there's this surreal thing because I like – when I stare at my phone, it's – Well, a lot of those financial advisors, they talk about AGI all the time, adjusted gross income. Adjusted gross income. That's what they're focused on. But, you know, it's like, well, AI can help you. This AI tool helps your clients with tax loss harvesting, et cetera, which is great.

2:20:49I love tax loss harvesting. But it's like, wow, this could not be a more different. Let's give it up for tax loss harvesting. But this conversation could not feel more different from the types of conversations about AI that I read on my little screen.

2:21:05Max Junestrand:Or the disconnect, honestly, between the discourse and then Dreamforce is happening. Oh, yeah. It's like, yeah, there's those big problems that we need to be talking about. We've got to be talking about this. But in the meantime, yeah. No, I really like. Here's another thing. So I was thinking growing up in the Bay Area, I distinctly remember the Iraq war protests. Yes. And I just looked at that. There was 200 ,000 people roughly in the streets like marching. A million in marches. There hasn't even been a 10 ,000-person AI protest. You ought to hear a funny story. So I was at University of Texas, Austin.

2:21:47I was a young hippie, and I attended some anti-Iraq war marches. And there was this guy at the front. There was this guy. No, I was in the crowd too. There was this guy at the front of the crowd who would regularly show up. and he had this bullhorn and he would captivate the crowd and he would point up at a nearby office building and he would say, don't think we can't see you, you know, G-men up there spying us and everything. And then everyone would like crane their head. He's like, oh yeah, I think I see someone in the office. That was Alex Jones. That person was like the guy. And so the least surprising thing.

2:22:26How deep does he go to? Why is this all in a process with Alex Jones? Like this guy who just like had us all captivated during the protest. That's fascinating. Who would be like. You were one shot. And everyone was like, oh, yeah, I think I do see someone up there. Yeah. That was Alex Jones. Wow, he just had a natural talent for it. Gifted. Absolutely gifted. That's remarkable. Yeah. Wow. Wow. That's crazy. I mean, yeah, that's like when we. Yeah, there's some. John Kiriakou, you know this guy? No, that name's actually. He shows up in weird places. I think he was like a school teacher. That was a wild story.

2:22:57These like, you know, closing sliding doors moments in history. I know. This is one of them. No, it's like he was just a local guy that we all knew back then when we were in college. Okay. Back to data centers, back to XRIS. So conversations getting muddled. There's one scenario where XRIS is the thing that does move the needle on the protests. You go from 10 ,000 to 100 ,000. legislation gets written and it builds on a lot of the work that's been worked on on the data center stuff and if you read the ai safety crowd a lot of them are like yeah we actually would love a slowdown in chip production yeah slowdown of data centers that would actually be pretty satisfactory because one of the prerequisites for sure nefarious asi is just a lot of compute a lot of we we're not worried about the god model emerging and on a desktop computer we just don't That's right.

2:23:46That's going to happen. So AOC was recently on camera talking about, I think you called her response like word salad. But we have the technology to turn word salad into ironclad legislation. Into a fancy new salad salad. Yes. So take us through like, is the word saladification of the AI discourse actually a problem? Wow. You know what? That's a really good question. I asked a version of this question to someone several months ago who is like in the real like safetyist camp before it became cool. And I was like, why do you guys just join up with the anti-data center people? Right. That's a good question.

2:24:26I was just like, you know, I understand. It's like they don't have the same like sort of understanding, like they don't – the shape of the risk there were. Why do you just join up with them? And I do think that people who have sharpened their blade for 10 years in the less wrong forums, they cannot do that thing of like, yes, but they're wrong. Oh, yes, aligning with the anti-data center people would align with me perfect, but they're wrong about the water consumption. And I cannot bring myself to ally with them, not because it wouldn't be useful, but because I can't bring myself to be on the same side as like someone who slightly is factually in disagreement.

2:25:06It does feel like there's the beginning of that horseshoe coming together with Steve Bannon and Bernie Sanders. Steve Bannon for years has just been like anti-tech, anti-Facebook, anti-control and like big company. And so there's more merging there. But I agree it's even harder for the AI safety camp, but it feels like the Nate Suarez on Tucker Carlson, Daniel on Joe Rogan are like there might have been an update to the strategy. I think there has been. And I think anyone who expects AI politics to map cleanly to some like left-right thing is like delusional. So like I get – all right, Bernie became the first like major elected politician to like join the pause cause.

2:25:50et cetera. And so then people are like, oh, anti-AI is going to be a left thing. But you're absolutely right. There is not going to be a left. First of all, there's not going to be a left position to AI because there's a million different angles. But also anyone who thinks that it's going to split between like some Democrat, Republican thing. You know, we had Kathy Hochul on the podcast and she was like defending the data center one year moratorium in New York. And I think at that point. Like literally it was so quick because at that point then people were like, well, look, okay, New York is going to miss out on all of these companies that are bringing in tax revenue, et cetera.

2:26:31So this is why Texas is going to get it. And then like a week later, Governor Abbott, he didn't, it wasn't a moratorium, but then he announced like a higher bar that the data centers are going to have to clear in order to get built there. So even whether we're talking about model regulation, whether we're talking about building of data centers, this idea that it's going to map cleanly onto some Democrat Republican thing, I think it's like delusional. How do you think people break on, should this be a federal or state's issue? Because there's a world where, you know, a particular state is like, yeah, we actually love this.

2:27:06I'm struggling to see a negative externality of a data center in a particular state. If everyone there is happy, maybe it should be state by state regulation. At the same time, it's such a national discourse issue that having a clarifying bill for like, yes, we are only building clean data centers. There's some emission standard. Maybe that makes sense, but how have you seen it puzzled around? No, look, I think most people, regardless of where you fall on all of these questions, probably think that some patchwork of state laws is not a great way to go about doing any of this. But outside data centers, I thought it was really interesting.

2:27:43I guess it who's like just last time is fine, you know, Chris Lehane from OpenAI. And in that thing he spelled out, he's like, we support this Massachusetts bill now. We support this California bill now, et cetera. That's a pivot. Yeah, totally. That's a pivot. And so, like, I'm sure. Not the first pivot. Nobody loves a pivot. But I thought, you know, it was really interesting because in as recently as last year, another fellow we had on the podcast, like Alex Boris was like, was enemy number one. And his bill that he had pushed in the state assembly was pretty straightforward. If you're above a certain company and you have some quote incident, you have to report it and pay a fine, et cetera.

2:28:22That kind of seems like a small potatoes regulation compared to what we could get at this point. I doubt, again, in the AI industry or outside the industry, anyone particularly loves the idea of the state-by-state rules. But it does feel like to a lot of people, well, this is the least worst possible. The best part about the state-by-state rules is that it sets up the AGI dunk, which is like, oh, if your models are so powerful, it shouldn't be hard to comply with all the rules state-by-state. Like, yeah, it's a mess, and you have to serve 50 different versions of ChatGPT, but, like, go for it.

2:28:55Just have your model do it. Well, this is, you know, the other paradox. Oh, you think your model is going to, like, go kill people or whatever? Just tell the AGI not to do that. If it's smart, have the AGI trained, right? Like, there's, like, all these. Yeah, yeah. People apply to the distillation thing too. I mean this is – You're so smart. Why can't you stop? You're so smart, right? But this is like – this industry has, A, not only made for thought experiments. The thought experiments have been around probably since the 1950s in the version of sci-fi novels and Asimov, et cetera. So the whole thing is built on thought experiments and so forth.

2:29:30There were thought experiments before. There was something we would call an AI industry. And you just literally take them in any direction. And there's like – On the opposite end of thought experiment is like hard reality rate hikes. Yes. Do you think the AI community is digesting what's going on with the Fed funds rate, what the outlook is on interest rates? No. No, and I also like I would be – and I would be very – No, no. It's just it is a very different world because like tech companies that have never raised debt, have never raised money at all are doing it. And like they will be affected by this and probably more so in the future.

2:30:08It will not only be affected, but I think by and large, if you sort of like assume the growth rates that these companies are seeing, if you sort of like do the math on like what, OK, financing, building a data center, acquiring the chips. I don't think like 25 basis points, 50 basis points. They just don't move the dial yet. Yeah, I think Sarah Fryer said like, yeah, she bought all this compute and it like trades in the market. I mean, there's a long. So it's funny. Yeah, and there's actually a funny amount of academic literature on whether any company, period, cares about interest rates. So this is actually an empirical thing that's been tested, which is like, have there ever been an example of a company that actually changed some policy choice because of something the Fed did?

2:30:57And it's surprisingly rare. There are so many bigger questions that usually, okay, here's a board meeting. And we're deciding whether we're going to make some investment. And it's very rare that the decision – oh, is the tenure at 6 % right now or is it 6.5 % right now? Is the short end at 4.7 % or is it 5? There are very few corporate decisions in the history of business where that turned out to be the deciding factor. Now, if we're talking maybe strictly real estate where there's like a very like, okay, these are going to be our cap rates, et cetera. Sure, that may be very great. This deal is underwritable.

2:31:33Now it's not. But by and large, it is a really huge open question about whether these marginal moves to anything have any history of affecting corporate behavior or not. Can you reflect on Warsh and how you – like how is he different? Not even in the strategy. We know the rates are going up. But like aesthetically, the way he communicates, the dynamic between him and other parties. Like how does he feel? He's just at the start. But like what is his legacy building towards here? What's the purpose? You know, I think there is this view. There is certainly a view that Worsh represents some sort of like very 90 degree turn from like the three predecessors he had or 180.

2:32:15I don't know. Powell, Yellen and Bernanke. More academics? In the specific sense, there were more – well, Powell was a lawyer but still more of like – but still like an internalized academic macro for sure. But the main thing that they had was like they communicated a lot. And they brought – starting under Bernanke, there were a number of – I guess I would call them monetary policy innovations. The press conference, there's not a history of that before Bernanke. There are so-called dot plots where the members of the FOMC write down where they expect growth on – Bernanke got the press conference idea from basketball?

2:32:51I did. Probably from basketball. And it was built upon. But I think there is like – look, like most of the history of central banking probably looks much more like Warsh. Like they didn't used to talk so much. And so like I am of this view that basically like, you know, we could go. If you go back to the Greenspan era, the word, the famous word to describe his style of communication was gnomic. Right. And he didn't say many words or if he did say a lot of words, no one understood what he was talking about. There is a long tradition of essentially like opacity in one way or another at the Fed. And so like if – like I – to some extent like people are like, oh, it's so – we're getting – like, oh, these – the dots do not have some long intellectual tradition at the Fed.

2:33:42If they completely got rid of the dots, if they completely got rid of regular press conferences, which my gut is that Warsh would like to do because he doesn't really say anything at most of his press conferences, we would not be ripping up some hundreds of years of like – No, we were ripping up presidents since 2008. Or 2009. And some of this stuff made a lot of sense coming out of the great financial crisis. Because it was a Fed crisis. It was a crisis for them and they were instrumental. Look, they had a very specific challenge, which was that inflation was very low. They had cut rates to zero.

2:34:18If you had plugged the economic conditions of the Taylor rule into some sort of rule, it would have said you have to cut rates to negative five. They can't do that. I think a lot of things break when you have negative interest rates. So then they're like, well, how can we be further dovish once we hit the zero lower bound? It's like, OK, we're going to do this by talking more about our commitment to lowering rates and so forth. So a lot of these things made a certain intuitive sense under a set of macro conditions in which the traditional tools of monetary policy were not workable because you just couldn't cut rates any further.

2:34:54It's 2026 now. It's a very different set of problems, et cetera. So if you would say, look, under these conditions, we do not have the same problems that we had when these things made a lot of sense that we should get rid of them. I think there are a lot of people who would agree. The one thing I will say that I like, the head scratcher still, is that like on some level, he used in his first or second press conference, worse used this phrase. is we would like to have market participants play the ball and not the referee, the referee being the Fed. And that sounds great. We love that idea. Play the ball and not the referee.

2:35:31Unfortunately, and where I would say, like, in the sort of government bond market, the Fed is the ball, right? We're all trying to guess where this is, right? So it's like, let's talk for a second. Let's imagine a two-year government bond, right? That two-year government bond is going to, the correct pricing of that bond is going to be like where the Fed sets rates over the next two years, right? It is. Okay. Is there some sort of steel man here where like you should be more focused on the fiscal condition of the U.S. government? We would love for that to be the case, but we would love for that to be – sure.

2:36:08Yes. But the thing is the Fed is going to be making decisions. There's 12 members of the FOMC, 12 voting members of the FOMC. And they are going to be attempting to meet their dual mandate of maximum unemployment and stable prices and things that they will take into account. Well, what is government spending look like right now? What is trade and tariffs? What does that mean for the inflation picture, et cetera? What does AI mean for the state of the employment position, et cetera? But at the end of the day, then it's like you are – once you are a participant in that market, what you are betting on is strictly and only how those 12 members of the FOMC are going to be digesting that information.

2:36:49You know, when we occasionally have arguments or debates about prediction markets, I like to point out that the U.S. government bond market is not figuratively or metaphorically a prediction market. It is literally a prediction market in the specific sense that you are making bets on how 12 voters just as it's an election and there are only 12 voters of what they will do at the next meeting or the subsequent meetings. So it is literally a prediction market of how you expect 12 people to vote eight times a year. And that's not – that is all I believe that a government, at least in the US, that a government bond market could ever be.

2:37:34The Fed currently needs to – the dual mandate is minimize unemployment. Yes, which does not have a – Minimize inflation or hit the inflation target. So the goal is stable prices. Stable prices. And that has been interpreted and formalized as we have a 2 % inflation target. But post-AGI, post-abundance will want the Fed to maximize unemployment and minimize prices. They want to maximize deflation so everything is essentially free. If we're really AGI-pilled here, that's where we need the Fed to be going, right? Yeah, I don't know what operation— Post-singularity Fed looks like. Right, because let's just say we have an AGI that could do all human labor, right?

2:38:20I don't know what that means for Federal Reserve to task with maximizing labor. It's a road to cross.

2:38:26Max Junestrand:What economic data do you feel like you can really lean on? I have so little trust in all the employment data now because it always gets revised. The revisions have been insane. At least it felt like six months ago there was so much admin focus on some of this data. And then there were some personnel changes. And so now I'm like, the boss didn't really like the data. I'll say two things, which is that I actually believe that even to this day, setting aside some of the personnel changes, you should do this sometime. You should call up the BLS. They will answer any question you have. There are all these very serious people who take their jobs very seriously.

2:39:16If you wanted to call up the BLS right now. This sounds amazing. You should do it. It's a good segment. I mean, it would be a good segment. But if you called them up and you're like, you know, I want to understand how you – my co-host Tracy wrote a piece on this. But if you're like – if you call them up and say, you know, how did you arrive at the price of mayonnaise for this end? They will answer. They will spend an hour on the phone with you. They're great. That's amazing. They're really – they're public servants in the classical thing. They will sit an hour with you and tell you how this was constructed.

2:39:45So they're really good. I agree. And then the other thing I will say is like, look, especially in the like hedge fund world, there has been a very big obsession with like alt data, private sector data, right? It looks exactly the same. Exactly. Like there's been many attempts to construct private price indices. There's ADP. You can – Indeed.com has a job. It doesn't do that much. It all tracks the same. So there is this hope or this sort of belief that it's like, oh, the private sector would be better at collecting this data maybe. And look, it's all out there. And then there's the MasterCard spending data, et cetera.

2:40:23It ends up rarely deviating in any substantial sense. So what you're saying is this goes a lot deeper. It goes a lot deeper. It goes a lot deeper. They're all in on it. Job data truther goes to heaven, asks God, did we really add – did the U.S. really add 160 ,000 jobs in August? So they really did. And they said, wow, this goes deep. Even you. Even God's in on it. Wow. Exactly that. That is crazy. Yeah. One thing that has stuck out to me is like this has been the year of sort of breathless takes from AI leaders and VCs around like we're in the post AGI era. AGI is here. We're in the singularity.

2:41:02We're in the foothills of the singularity. Everyone has a different buzzword, except I'm just like I'm going to be looking at this, all the economic charts. and like there's, it doesn't feel like there's a kink in the graph yet. No, it does not. It doesn't feel like it's showing up at GV, employment, anything else. The interesting question is, and I like, you know, where does the productivity data show up for the internet? Yeah. That's like, right. It doesn't. You like, it's just like, oh, in the, in the late nineties, productivity moved from 2.5 to 2.8%. Yeah. Amazing. Wow. And it's like, and so it's like, or it's like, where did the productivity show up with the release of the mobile phone?

2:41:37Yeah. So. Yeah. I do think we should, and there's many interesting conversations that we'll be had about how AI is manifesting in the data. But I do think it's worth asking, why didn't all these other technologies show up that should have or intuitively felt like they would revolutionize business in some way, make companies hyperproductive? Why didn't that show up in the data either? So until that day when the kink arrived, we have plenty from the past. We can still talk about and try to understand. That's sort of my take on that. What else have you been tracking recently outside of – is AI just completely all-encompassing?

2:42:19It's so annoying because it's like I'm very interested in like – I'm very interested in oil. I've been doing some oil stuff. But yeah, I'm very interested in the Fed itself. I'm very interested in all these things. But it's just like I feel like it kind of against my will. Yeah, it sucked. Right? Like that it's just like every year. Do you ever feel that way?

2:42:44He's like, really? Another main story on this? No, I got to like, there's someone in my DMs who was like, we got to do an episode about motor oil. We do have to do an episode about motor oil. I got to do an episode about diesel prices. Oh, yeah. All of these things to prioritize. But I do feel to some extent against my will, like there's this like monotonical step up in the number of like waking hours that like you just can't talk about these things without AI. It's funny. I was in earlier in the year. I guess it was early this summer when oil was a lot higher. I was out in Hong Kong and Asia or East Asia in particular seems like ground zero for where, you know, the jet fuel crunch is really going to hit and stuff like that.

2:43:34Because just the route, et cetera. So I'm like sitting around like all these like business execs and I'm like asking them, what's going on with oil and air? It's like, whatever, let's talk about AI. It's like, oh, my God. This is where I thought you guys were going to be a little more. You know what we need? We need a new thought experiment for the oil community. That's right. We need to build a new thought experiment for all these niche stories. And then it can be something that we can tussle with. We can tussle with, have like a big debate. We need a percentage, you know, percentages around these thought experiments.

2:44:03That's right. We need to build a lore in the world so then you can have endless ideas for hours and hours and hours. Talk to them about, like, you know, asset allocation. You know the question that I still have not gotten to the bottom of? You mentioned the Iraq war protest. Yes. And I remember that there was – at the time, the banner was no blood for oil. That's right. Because the stated reason why America went to war in the Middle East was WMDs. Yes. And that was pretty handily concluded as like false, right? I think so, yeah. Misinformation, right? But the cynical view is like we only went for oil.

2:44:43But we didn't get the oil or was that the oil? I don't know. So my question is like when George Bush and Cheney sit down years later and have a glass of wine together and they reflect, are they like, damn, that one got away from us? I mean Trump certainly thinks this. What were they doing? We didn't even get the oil. Yeah, yeah. But, you know, speaking of like, you know, the what is happening on the ground is we did get the oil out of Venezuela and like Venezuelan oil is like basically our oil now. But that's one percent of the market. I don't know exactly what it is, but it's a lot of oil. But where are the like.

2:45:22Where's the savings at the pump? There's no savings at the pump. But there's also like the disappearance of like that kind of protest movement, because I think like which is where I kind of thought you were going to go. But it's like there was a point in our lives where like the thought of like using U.S. imperial might to extract oil was something that animated a non-trivial number of people. I also – I think the internet – Now we're literally doing it. Yeah. Where is the – I mean there is one. I don't want to actually completely sneer at them. But like where is the – there has not been a particularly large-scale protest movement about the embargo of Cuba.

2:45:56Oh, no.

2:45:56Max Junestrand:It's social media, like very clearly killed protests because it allows like people can like go viral and feel like they're like, you know, taking action. And yet, like it's like it sounds like the dream of a government that's not doing the will of the people is like you can do whatever you want. And sometimes they're going to get angry on online at you, but nothing will actually happen. But that's very new. I mean, just a few years ago, there were millions of people for the Women's March, Black Lives Matter movements. Like it was it was like post-COVID, then things maybe slowed down. I completely agree with this idea that like people feel like they can scratch the itch of protest online by throwing a like on a, you know, really, you know, really like died.

2:46:43Well, it's the bumper sticker. I was just talking. I was just thinking. Because I was like, every once in a while, I still like, usually it's like a Vermont license plate. And they still have like all of those, like, you know, the coexist bumper sticker, this car climb out Washington bumper sticker. My other car is a broomstick bumper sticker, et cetera. I miss all that. Every once in a while, I see these. It's a boom in the, I bought this Tesla before. I bought it. That's right. There is that one. But I miss the bumper sticker. But I do too. And I was thinking about how I haven't seen any anti-AI bumper stickers, but that feels like a ripe area for entrepreneurship.

2:47:19Yeah. If somebody's going to start a bumper sticker enterprise. Yeah, that's right. The anti-data center bumper sticker, probably going to fly off the shelves. And my friend Blake makes amazing bumper stickers.

2:47:28Max Junestrand:Oh, really? He's the world's foremost vintage G-Wagon dealer. Okay. So he makes bumper stickers that say you wouldn't put a bumper sticker on a Mercedes-Benz. Oh. You know what I think there's in one of the reasons why AI politics are really confusing and scrambling is that like to even go – to even say like put up an anti-AI bumper sticker on your market would force the person to accept the premise that AI is a serious and important technology. Totally. And so part of the reason that I think that it scrambles the thing is like if you want me to be actively anti it, then I first have to accept the premise that this is – I'm legitimizing it.

2:48:12Yep, yep, yep. And that is like something that many people are reluctant to do for various reasons. And so there is this question, and Nate Silver asked this. He's like, why don't you see a more like sort of like left-wing opposition to like AI and the pace of development? Sure, sure. I think there are many answers to this, and I don't even know. There will never be a – people are complicated. But I think it first requires a certain step of legitimization that people don't want to do, which would be required to actually care enough about AI risk to put a bumper sticker on it. Yeah, yeah, yeah.

2:48:45Which may be what – With the power of AI, we'll be able to take a picture of that bumper sticker, immediately translate it into ironclad legislation. We could do it. Spell this out. All the herebys that you need to have. Turn it into law immediately. You know, it's funny. It's such a classic political talking point. It's like they never even read the legislation that they voted on. This is like everything now. It's like they never even read the code that they implemented. This will be the phenomenon of our world that in so many different things that people implement, no one ever actually like read it or knows like what the guts of it are yeah and it's just beginning yeah yeah uh yeah the state of the book industry is interesting yeah did you read the tim ferris article no he he talks about how he he wrote uh very uh he wrote very specific non-fiction books one of them is called the four-hour chef and it's essentially a recipe book and he was like i actually got steamrolled by chachi pt because people can look up exactly what that is yeah uh and he was trying to sort of like uh match through some trends like obviously i think the kindle bookstore has seen yeah rex the number of submissions and there's a clear ai of course yeah but then i imagine that sales of you know harry potters are still chugging along probably still doing it's not really substitutive with that but no i think that but you know i do think probably and sort of like you know the type of people who like wrote the books about like people who want to read about erotic affairs with monsters and stuff, you know, which is like, I have heard that this is a genre.

2:50:24It's called romanticy. Romanticy. Yes, it's an investing genre. Will AI like be able to like write? I would suspect that it won't be too long until some of these genres. But, you know, like, look, really like big, like this sort of world building type of fiction that would be in a Harry Potter. I don't think we'll have that technology for at least another two or three months. Have you been surprised that Pangram works in 2026? Yeah, I have been. I would have said that if they're solving Millennium Prizes, there's no way that Max Sparrow can detect it with his team. I have been surprised. I would have guessed that, and I guess I would still guess that at some point AI writing will be good enough.

2:51:09And I don't think the labs are focused on evading AI detection. So it could be that at some point they may prioritize that or something like that. And it's kind of a nice equilibrium where it's like, look, if you want to know if it's AI written, you can. But we're not going to stuff it in your face with a bunch of heavy-handed tells or additions. But it is an option to go figure it out if you want to. It might be a useful equilibrium, one that the labs don't feel any particular prioritization to work on, et cetera. I mean like I – you know, there's – you know, it's funny because people talk about like AI writing.

2:51:51And when I – when the conversation happens online, it's often between journalists. And so writing to them means writing articles. Yeah, yeah. The vast majority of quote writing is just emails, right? Yeah, yeah, yeah. And I doubt there's like – and I don't think that there is like some big norm within most corporations. Like what? You had an AI write this memo summarizing the meeting? I've actually heard the opposite when I talk to people who work in non-media organizations and non-tech organizations that there was a norm against like why didn't you have the AI write this? It would have been a cleaner email than – Cleaner for sure.

2:52:25But I think the KPI that I would be interested in looking at would be like number of words posted to Slack and over email for employees should not be increasing in the AI era. No. Do not just become more verbose because you can. But if you're using AI to fact check everything that you're saying, but you're still writing tersely, come in. No, I agree. And, like, look, it's still all in flux. But, like, I think, like, by and large, like, if you send me an email and it's, like, how to find the TVPN offices and what you should do and what you should wear, and I can tell it's, like, AI written, it's not going to be a big deal to me.

2:53:05I'm not going to be, like, really good. It's not just a studio, Joe. It's an ultradome. You'll know it when you see it. Like, I'm not going to be, like, you know, tremendously offended if, like, you used chat. You just send you the sloppiest GPT-4-0 email. I actually am, like, I am kind of, like, a holdout in that, like, I actually have never sent a, like, AI-generated email. Like, I'm, like, if I'm going to, like, put words to something, I want to write them. Of course, of course. But I do not think there's going to be, like, some big norm against, like, for, like, basic functional communication.

2:53:35I just love being able to open up the voice mode or the dictate website, ask seven different questions across statistics and links and some charts. And then just have like – basically I used to have 12 tabs with Wikipedia and some economic statistics. And I used to be tabbing through them when I'm actually writing or researching. And now I can just have it all in one go. And then I'm still doing the instantiation and the talk process. Yeah, look, it's pretty nice. But it's really good for like – It's pretty hard. It's pretty good. It's pretty hard to resist. I mean, yeah, like whether I, you know, I'm interested in this book.

2:54:12There are some other recommendations. What are the through lines between this line of thought and this line of thought? Yeah, yeah, yeah. It's pretty good. I kind of use it. What are the biggest or like most shocking findings from your studies on orality? Yeah. You know, I think it's actually like, so this is something I'm like very interested in. And I don't know. So when you think of like so orality, what do we really talk about here? It's speech. But there are things that happen in speech that are the important part. So, for example, three people talking. We try like, oh, let's one up each other, et cetera.

2:54:51Let's get a little bit confrontational. Like this is like what we're talking about. Let's get a little spicy. Let's get a little spicy. Let's not get confrontational. No, let's not. But this is different with that. And so this is actually something I'm very interested in because for the last 15 years of the internet, we are just sort of like bathed in constant both fights and competition, right? Whether it's Instagram and you're sort of trying to show your life is a little bit better than someone else's or whether it's Twitter and you want to get in a good dunk, et cetera. And so I think the really interesting question or one of many interesting questions from a society standpoint is what happens when we're bathed in the thing that always agrees with us?

2:55:33And what happens like when we're bathed in like the most polite, helpful thing on the other side? So it's very tempting to like look at and say like, OK, chatbots are this huge thing. This is the extension, the acceleration. This is like the sort of back and forthness of social media, et cetera. But it's not because it doesn't have that competitive thing that the chatbot is never trying to one-up you. It's never trying to get a dunk on you.

2:55:59Max Junestrand:I actually have had an experience recently. I got a very robust racing simulator. Oh, sick. Not surprised. And so I'll be focusing on improving my lap times with a classic car on a certain track. and I've had the experience a bunch of times where I'm like, I cut like a lot of, you know, multiple seconds off my time. I think I'm feeling like I feel pretty quick. Yeah. And I go to, I go to ChatGPT and I'm like, how's this pace on this track and this car? And, and it'll just like, I'm expecting it to be like, you are the go. You are. It used to. It used to. It used to be like, you're in the conversation.

2:56:43Max Junestrand:It's like, and like, you know, granted, I'm a relative beginner. Yeah. But it'll be like, you know, I'll have improved a lot already. And then it'll be like, yeah, you're like clearly in development. I wouldn't call you like. So like a year ago. And it's like, and it's ranking out like it's doing a tier list. And it's like, you're three tiers away from like competition pace, basically. I know. To me, I'm like, wow, I'm actually glad it's telling me the truth because it's pushing me. It's showing me there's more. But it's not a good feeling to get told by this thing. I always say, who is brave enough to admit that they miswed the models or more obsequious and told you you're a genius every time?

2:57:30But now you ask the latest model, I have this thought that this is like this. And it's like, yeah, Melissa, you're missing something. It's like, oh, you know what? I'm going to go back to Opus because that was really nice to me and always told me I was a genius. Sometimes they'll even sort of like compliment themselves. Yeah. You'll ask a question and they'll dig in and they'll be like, well, I found some interesting things. I dug into it and here's the interesting thing. You know what? I had interesting things. Yeah. Well, I started this. Okay. So let's give me some credit. I like to, you know, unfortunately, I frequently will ask the question on incognito mode so that past history doesn't.

2:58:06So that I don't want it to just flatter my, you know, because otherwise it's too. Of course. But I had something that I had never seen before.

2:58:15Max Junestrand:It literally says, so 208 puts you at a pretty reasonable pace, especially since you're still learning the track. The circuit has an unusually large skill gap because the entire mountain section rewards confidence and precision. It's basically like saying you suck. That's brutal. But I had an interesting experience that I never had seen a response before. So I asked, I was reading a book and I didn't quite understand something. So I asked the model if it could like help me like understand this section. And it said something weird that I had never got before. It said, you'll have to forgive me because I'm remembering this book from my memory.

2:58:51And it was like, I, I, so I'm like my memory of the book isn't that great, but my understanding. And I was like, that's weird because then the model begins to sound like this like self that has an understanding of its own. It's like, you'll have to forgive me. I don't exactly remember what the book said. And I was like kind of unnerved by this level of abstraction. So that is weird. That also might be an artifact from specific reinforcement learning on do not memorize the entire book because if you reproduce it, we get some. Then it's a copyright. And so actually like the correct way to talk about literature is as someone who has read the book but might not remember it all.

2:59:33And that's actually the goal that gets reinforced. That's very – OK. That could be a good answer. A little more cynical. Anyway, I can't find it. The only reason I mentioned S on incognito mode – so I can't pull it up because I want to go back and read it. But it disappeared from my chat history. But these things – I don't know. It's like kind of like a nerd vibe. Totally. Yeah, no. It was a lot. And, yeah, I was noticing Chachapiti uses I to refer to itself. And I was like, but the models are starting to use agent swarms. So should they start using we? Have you ever seen that famous screenshot?

3:00:08It was a real chat. Someone asked it some question. And someone said, where did you get that fact? And the model said, oh, I heard it at an IBM conference in 1985. This one responded, like, where is this coming from? You were not at an IBM conference, but that was the weird stuff in there. The seats in Watson.

3:00:28Max Junestrand:Yeah, exactly. Gentlemen, I have a meeting. I've got to get to it pretty soon. This is fantastic. I hate to cut it off. It was such a good time. I love chatting with you guys. Yeah, always a great time. Let's do it again soon. It's an honor to finally have you here. It's an honor to be here in the Dome. I can't believe I got to hit the gong. Yes. That was like, I'm done. I have nothing left to accomplish. Hit the soundboard. You have a live show. You got one option. One option. Yo, a live show is happening. Odd Lots in Los Angeles. Lots of guests. It's happening tonight. There we go. I went with the classic.

3:01:05Max Junestrand:All right. And I want you to experience this. We'll see you guys. We're going to see you Monday. We'll see you on Monday. We're at a conference tomorrow, but we'll be back on Monday, 11 a.m. Pacific Sharp. We love you. It's time for a newsletter. Goodbye. Flash.

3:01:23you Thank you.