TBPN - Benchmark's Future, SpaceX IPO, RIP Sora | Mike Knoop, Nathan Benaich, Rohin Dhar, Eric Jorgenson, Jenny Just, and Matt Hulsizer

Episode Date: March 25, 2026

Sign up for TBPN’s daily newsletter at TBPN.com(00:53) - The Benchmark Ship of Theseus (14:16) - OpenAI to Kill Sora (23:56) - 𝕏 Timeline Reactions (43:07) - SpaceX Could File for an ...IPO This Week (51:57) - Manus Founder Stuck in China (59:34) - Mike Knoop is the co-founder of Zapier, the automation platform that connects apps and workflows without code. He is also a co-founder of the ARC Prize, an initiative advancing progress toward artificial general intelligence through benchmark-driven research, and now focuses on early-stage investing and technical projects across AI and software infrastructure. (01:22:33) - Nathan Benaich is the founder and general partner of Air Street Capital, a venture firm focused on AI-first companies. He is also the creator of the State of AI Report, one of the most widely read annual analyses of the AI industry, and co-founded the AI research hub RAAIS (Research and Applied AI Summit). (01:35:26) - Rohin Dhar is a San Francisco–based real estate agent specializing in residential properties. He works with buyers and sellers across the Bay Area, focusing on navigating competitive markets and helping clients make informed investment and housing decisions. (01:46:42) - Eric Jorgenson is an author and investor best known for The Almanack of Naval Ravikant and The Book of Elon, where he distills the ideas, strategies, and operating principles behind Elon Musk’s approach to building companies. He writes about leverage, decision-making, and product-building while working with early-stage startups. (02:00:28) - Jenny Just & Matt Hulsizer are the co-founders and managing partners of PEAK6, a financial services and technology firm spanning trading, investing, and venture. They focuses on building and backing companies across fintech, consumer, and education, and is known for their emphasis on performance culture and long-term value creation. TBPN.com is made possible by:Ramp - https://Ramp.comAppLovin - https://axon.aiCisco - https://www.cisco.comCognition - https://cognition.aiConsole - https://console.comCrowdStrike - https://crowdstrike.comElevenLabs - https://elevenlabs.ioFigma - https://figma.comFin - https://fin.aiGemini - https://gemini.google.comGraphite - https://graphite.comGusto - https://gusto.com/tbpnKalshi - https://kalshi.comLabelbox - https://labelbox.comLambda - https://lambda.aiLinear - https://linear.appMongoDB - https://mongodb.comNYSE - https://nyse.comOkta - https://www.okta.comPhantom - https://phantom.com/cashPlaid - https://plaid.comPublic - https://public.comRailway - https://railway.comRestream - https://restream.ioSentry - https://sentry.ioShopify - https://shopify.com/tbpnTurbopuffer - https://turbopuffer.comVanta - https://vanta.comVibe - https://vibe.coFollow TBPN: https://TBPN.comhttps://x.com/tbpnhttps://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231https://podcasts.apple.com/us/podcast/technology-brothers/id1772360235https://www.youtube.com/@TBPNLive

Transcript
Discussion (0)
Starting point is 00:00:00 You're watching TVPN. Today is Wednesday, March 25th, 2026. We are live from the TBPN Ultrigal. The Temple of Technology, the Fortress of Finance. The Capital of Capital. Ramp.com. Time is money. Save both.
Starting point is 00:00:15 Easy use. Corporate cards, bill pay accounting, and a whole lot more all in one place. We have a great show for you today, folks. We got Mike from Ark Prize coming on. The Noopanator. He did it. He did it. We'll talk about this later.
Starting point is 00:00:28 We have Nathan, my buddy from Air Street, Capital, Rohan Dar, giving us an update on what's happening in San Francisco in the housing market. Eric Jorgensen, the author of the book of Elon's coming on. And then Jenny Just from Peak Six investments coming on later. Thank you so much for tuning in today. Linear, of course, is the system for modern software development. 70% of enterprise works based on linear are using agents.
Starting point is 00:00:52 So there's been a debate. Truth bomb dropped by Emil Michael. He says, For giving business. benchmark and others would be like letting the Wuhan Institute of Virology slide back into a good reputation because the new senior manager of pandemic causation has made more friends than his predecessor. And so this got me thinking, and I'm probably going to have to put on the steel helmet for this one, because this is waiting into dangerous territory, defending benchmark. But my question is, how close are we to actually being able to to forgive benchmark?
Starting point is 00:01:31 When is the right time? It's been a decade. Obviously, the drama between benchmark and Travis Kalanick was awful. I think everyone's against what happened. But the question is like, is like, what is a venture firm? It is its partnership. If the partnership turns over at some point, like, is it a new team? Do you get a second shot?
Starting point is 00:01:54 you can you actually change the reputation? And so, believe me, like, I get the benchmark criticism. Like, Travis is truly a generational entrepreneur and was on such an amazing run, right? So he was attacked. Jason from Saster was reacting to our interview to Travis. And his take, which I totally agree with, is it's hard to, if Travis had stayed in the role, it's hard to imagine Uber being worth less than something like a trillion dollars today. Yes.
Starting point is 00:02:26 So our friend of the show, own McCabe, over at bin.a.i and intercom, said, Waymo is superior to Uber in literally every way. This was a year ago in March 25th. Actually, to the day, a year ago, he said this. Waymo is superior to Uber in literally every way that matters to consumers. Smoother, safer, more reliable. No chatty, weird, rude drivers, private, quiet, self-driving car services are going to dominate their human driver incumbents.
Starting point is 00:02:52 And own says, TBT, when, I think that's throwback two, right? Throwback two when benchmark pushed Travis out of Uber and can the self-driving division that he started literally 10 years ago. And so this is what's so tricky about this is that, you know, Uber survived. It's 150 billion market cap. It's bigger than when Travis was ousted. But getting a 2X over a decade is not what I think people were expecting. from Uber under Travis's leadership.
Starting point is 00:03:23 And Lyft has fallen to just $5 billion. Like, he won the capital war, and Dar has done a great job managing the business. But I feel like a lot of the success of Uber has been built on the foundation that Travis set up. It wasn't a complete reinvention. If anything, they just honed down the core business. Yeah, and the thing that is holding the business back right now,
Starting point is 00:03:44 at least from a valuation standpoint, is this big question, right? Around self-driving. how, you know, and Dara has answered this question, you know, thousands of times right now. The strategy is to invest in self-driving companies, partner with self-driving companies, but not the same as like having, you know, having developed their own internal IP and product starting a decade ago and seeing where that would have been by now is just hard to think about. Yeah. And so Uber is valued at 150 today.
Starting point is 00:04:20 something like that. Waymo was valued in February of this year at $126 billion. And so, yes, Waymo's been working on self-driving longer, but you have to imagine that there's another 50 billion of market capital. You have a serious play. What would Waymo be valued if Travis was the CEO? Yeah. You would get some type of Travis premium on it. Just the market would be, would say, totally, totally, totally. You have this sort of one-of-one entrepreneur in the seat. 100%. And just to sort of recap where things stand, I mean, Shervin Pischvar, been on the show as well. We've had like everyone from this saga in the TBPN orbit, both Travis and Bill Gurley have been on the show. Shervin's been on the show. Amel Michael's been on the show. We've talked to a number of people that have been around this story. And it's a fascinating one. It's one of the most interesting. It was certainly formative in my career because I got to Silicon Valley. And this was the first big story that,
Starting point is 00:05:20 played out, really. So Shervin said, in my opinion, Gurley single-handedly destroyed hundreds of billions in value. Travis and Emile staying in charge of Uber would have led to a Tesla-sized win, 500 billion plus. For everyone, including benchmarks, LPs, he nuked decades of benchmarks' reputation with founders. The market has spoken in no future Travis quality founder would ever touch him or his former firm again, especially since three of the partners that approved of the ousting of Travis are still at the firm. And so my question is, like, how many partners, need to be at the firm until we can call this a ship of Theseus. So for those who are not up to speed on their Greek mythology, in Greek mythology, Thesias is the mythical king of the city of
Starting point is 00:06:02 Athens. He rescues the children of Athens from King Minos after slaying the Minotar, which is his mythical beast. And then he escapes onto a ship going to Delos. Each year, the Athenians would commemorate this success by taking the ship on a pilgrimage to Delos. to honor Apollo. Over time, because they're sailing the ship every year, various of its timbers rotted and were replaced. A question was raised by ancient philosophers. If no pieces of the original ship remained in the current ship,
Starting point is 00:06:36 is it still the ship of Theseus? If it was no longer the same, when had it ceased existing as the original ship? So some people might say 50-50, some people might say, yes, it is the same ship, because replacing one board at a time, the ship is the concept, and you can swap everything out 25 times. It's still the same ship.
Starting point is 00:06:58 It's a paradox. There is no right answer. It's a philosophical question. But it applies, I think, to benchmark. Because back when Kalanick resigned as Uber CEO on June 20th of 2017, after investor in pressure, after investor pressure that included benchmark. On that exact date, Benchmarks' equal GP roster was Bill Gurley, Eric Vistria, Matt Kohler, Mitch Lasky, Peter Fenton, Sarah Tavill.
Starting point is 00:07:27 Today, the partnership has changed dramatically. The only two that remain are Peter and Eric. And you have Chetton, Ev Randall, and Jack Altman, who are new to the partnership post the Uber scandal. And so it's not a full ship of Theseus, but only one third of the original 2017 partnership remains. And my question for those who remain reluctant to forgive benchmark is, like, what happens if Peter and Eric retire or leave at some point? And the full ship of Theseus is complete. Like, maybe you'll ship... Yeah, right now, right now 40% of the partnership was there.
Starting point is 00:08:02 33%. Oh, I mean, I guess two out of the five. Yeah. Two out of the five. Because they've added three, but only one third of the original partnership remains. The question is, did Chaton, Everett, and Jack come. in and as part of the interview process, say, like, you're absolutely right. I mean, to defend Ebb, he's going to show a good friend. Having two out of the three, I, Ev had just graduated from
Starting point is 00:08:26 college. Like, he was truly, like, not involved in the Uber scandal. And yet, you know, people will visit it upon him. Knowing Everett and Jack, I'm sure, I'm sure during the interview process, they were like, I, I, you know, the storied firm. Yeah. I'm excited to join, but we can never You can never do anything like that again. And so one question that's worth asking is like, is the firm that did this and ultimately, you know, stained this storied brand and has certainly suffered the consequences, right? They've put up incredible returns since then. But I'm sure they've missed a lot of deals that would have made their returns even better because of that kind of narrative around the firm. And so they have, I would say,
Starting point is 00:09:15 you know, Emil, Michael, and others are upset that they're doing great deals at all. Yeah. But I think it is that a question I have is like, are they, if they're in a situation again, right, in the same situation, kind of situation, are they more, what decision are they more or less likely to make, right? I would argue like they are probably less likely to go against the founder, given how this entire situation is played out. Yeah, yeah.
Starting point is 00:09:45 The only steel man, and this is, this needs the full steel helmet because it's so hard to steal man, the benchmark thing. But the full steel man of the benchmark thing is really bad. It's really bad to bench. I'm sorry for everyone. I'm sorry. But it's basically that every partner at benchmark, it's an equal partnership. So every partner was going to make a clean $1 billion. They were all going to be billionaires from this one deal.
Starting point is 00:10:11 And it was such a power law that, that like there was no path to becoming a billionaire for you know from the other from the other investments most likely and so you see the endless 24-7 hit piece pile stack up and you got mike isaic you know blood hounded on at the new york times writing books they're turning into movies like it's getting rough it's getting rough mike iacac's at your door yeah my guy's at the door the barbarians are at the gate And you're like, I'm either a billionaire or I'm going back to your paltry 10 million. And I can't, I can't do that. I can't do that.
Starting point is 00:10:50 And so they freak out. And they're like, we got to salvage this thing. We got to just push it out in the public markets. We got to get out of this name. And so they basically just, it's just too nerve-wracking. And yeah, it's not a strong steel, man. But I think, I think that's a little bit more of what happened than, like, taking a stand on like, oh, like, this particular thing that happened was so egregious. It was more just like, okay, like, wow, all my money, like, 99% of my net worth is in this asset.
Starting point is 00:11:19 And it's looking like it could be a zero because Lyft is coming from behind. There's a whole bunch of VCs. They're piling into that. The narrative is totally flipping. There's a boycott Uber campaign. And everyone's like, ah, like, what's going on? I got to get out of this. I got to salvage this.
Starting point is 00:11:35 And I think that was maybe more of the underpinning than, like, like, I'm taking some sort of, like, moral stand on. a particular hit piece or something like that. Anyway, it's rough. But fortunately, you know, ship the easiest process. Maybe it happens. I don't know. Would Delian accept that argument? Probably not.
Starting point is 00:11:53 Would Emil? Probably not. But they're not making any easier with the Manus investment either because there was a world where it was like, okay, yeah, the Uber thing happened a decade ago. The partnership is basically entirely new. And they're focused on. But it's not there yet. Yes.
Starting point is 00:12:10 It's just not there yet. It's not there yet. The mask is still there. I think you can rewrite this in five years. Yeah. You made this point that it's too early to call this. But I think it's interesting. Correctionally, given that the firm is still putting up great returns,
Starting point is 00:12:28 they've gotten to a bunch of great companies over the last five years. I think we are on a path to the benchmark. Well, yeah, Ventureliz. being the ventureship of Theseus. And VC Bragg said, Airbnb has no homes, Uber has no cars, and benchmark has no partners. Of course, that was an exaggeration. But they did get down to just three partners, which is very, very small for a venture capital firm. Some have dozens of partners.
Starting point is 00:12:56 But different strategy, and we will see where it goes. Anyway, let me tell you about app-loven. Profitable advertising, easy with axon.a. Get access to over one billion daily active users and grow your business today. And let me also tell you about Lambda. Lambda is the superintelligence cloud building AI supercompetters for training in the drinks that scale from one GPU to hundreds of thousands. So, Sora, rest in peace, Sora. The app is leaving.
Starting point is 00:13:21 Ev is in the chat. There he is. Class of 17 represent. Yes, yes. Ev was chugging beers while Uber is getting oustead. Do not visit the sins of the father on the son. That's what I would say. Ev not guilty.
Starting point is 00:13:35 Ev was a boulder. Yeah, he was hanging out. What happened? Senior year? What happened? I think, I think, I think, I think, I think Ev deserves a fair shake and should not, and should not have to bear the, bear the cross from. The question, the real question, do, do Ev and Jack pull a benchmark and force out the original partners? They don't have the legal control to do so, but neither did they during the Kalinick stock.
Starting point is 00:14:04 At this point, Ev is probably already getting, getting calls from Sequoia to come be the senior steward, you know? He's on a meteoric rise. We're really all over the place today. Anyway, Sora is now, is it still in the app store? I think it's like the announcement was that it will be leaving the app store. Millions of people have made content on the app. You have to leave it running for some amount of times.
Starting point is 00:14:30 There's a phase out. But the announcement happened. And now it is going out. And I have a bunch of takes on this. Obviously, this is not the end of video creation for OpenAI. This will be rolled into ChatGBT, BT, I imagine. Tyler, Hodge put it well, bullish. Killing products quickly is hard.
Starting point is 00:14:51 Almost no one can do it. It's a good sign for Open AI. They're consolidating. In many ways, it's like last week you heard about, like, the Code Red was like a month or two ago, and then it was like, we're refocusing. And then it's like, here's step one of refocusing. like a single app that we're going to push everything together. And also, I just, I've enjoyed making some videos in SORA.
Starting point is 00:15:15 I've never enjoyed having to go to a separate app. I want all of that to live in one place. So that makes a lot of sense. Let's see what Dax said. It's lame to see all the people saying, ha, I called it. I knew Sora wouldn't work, yeah, duh, because everyone thought that,
Starting point is 00:15:28 including me who were working on it. They probably learned a lot trying to make it work anyway for every successful thing that exists. a hundred efforts like this had to fail, and those learnings are fed into making something that ultimately does work and provides you with a steady paycheck. Yes, it's interesting because this quote of like people saying, ha, I called it, I knew SORA would work. That is not how I interpreted the vibes around the SORA launch. Like, I went back and revisited the essay that I wrote on October 1st. We had the slop versus farming debate. I was really on a tear back then.
Starting point is 00:16:03 So, slop is bad. We, the timeline, don't want to be pigs at the trough. We don't like it when tech leaders treat us like farm animals, but we love farming. Farming is Lindy. We, the timeline, want to return to a world where we are filling up troughs with slop on a daily basis, I guess. So between Google DeepMind, meta-superintelligence and Open AI, we now have three different variations on AI video products, each met with slightly different responses. So the interesting thing here is that, like, Google has been like charging ahead, launching it. It's in real, it's in shorts.
Starting point is 00:16:34 And that's just been like not a story at all. What was interesting was that the vibes around both meta vibes and SORA were like, this is going to one shot humanity. They're like, this is going to be too successful. Yeah. That was, it was like infinite jets. It was like an entertainment doom loop. Exactly.
Starting point is 00:16:52 You could imagine it just getting so good at generating the next thing that you would want to see better than even a billion humans on. Instagram could do. And that's not what we've seen so far. And so like my big question was was like, will this actually be sticky? Will people like this? And at what rate? I mean, I read I read LLM generated text daily, but I also read a ton of not LLM generated text. And my my ratio has grown exponentially, but it hasn't gone to 100 percent nowhere near it. Like probably five percent of 5% of the text that I read is LLM generally. I mean, we should actually revisit how we were processing it during launch when it was,
Starting point is 00:17:38 you know, rocketing. We should just throw on that three-hour stream and just watch that and react to how our art from that day. But even at the time, I remember saying very obvious that they built like a very cool creative tool. Yeah. And they have the potential to see a network with this. There's all this, you know, novel content.
Starting point is 00:17:58 They had allowing creators. and, you know, people like Sam to allow people to use their IP. It was very, very well-executed launch, but even from the beginning it was like, okay, obviously cool creative tool. It's a totally different ball. You know, this like come for the tool, stay for the network, has been like an enduring strategy. Chris Dexon probably wrote that in like 2014 maybe or like a long time ago, over 10 years ago. Yeah.
Starting point is 00:18:28 But just because you build it. a tool that is attached to a network, like that jump is just really, really, really, really tough. Especially when there are three or four or five serious networks that are at scale that can on day one support the format of the file that is produced from the model. So in a world where generative AI video came out not in a MP4 file or an MOV file, it came out in some sort of format, that could never be uploaded to Instagram Reels, then you have a chance to build a network and run away with it. And this was the story of Instagram. Like, Instagram just had better support for images than Facebook did.
Starting point is 00:19:13 And then Vine had support for video literally before Instagram. So Instagram, it was like, I have a video on my phone. It's cool. I want to share it. Sharing it to Instagram was not possible. Now on day one, you generate an AI video. You want to share it. You can share it on TikTok.
Starting point is 00:19:29 Yeah, it's just the incentive. If you create, if you created an amazing video on SORA, what is the most logical thing to do? If you're a creator and you want reach, post it to Instagram. There's just naturally, there's billions of people there. There were millions of people on SORA and a lot of energy momentum. Yeah. And it's not lost on me that the same day that Sora was killed, you have a viral breakout reality TV style series putting up incredible numbers on TikTok for fruit, Love Island, I believe it's called.
Starting point is 00:20:03 It's an AI-generated twist on Love Island. There's romantic intrigue and plot lines and stories and consistent characters, and a lot of things that have come from a variety of AI models. And we should talk to the person that's the entrepreneur behind that project, because I would be interested to know what the stack is, because I imagine it's not just going to a single Gen AI app. I imagine that they have a whole pipeline of a workflow in place to actually generate that. And so we're at this weird moment where, you know, SORA, the app is going away,
Starting point is 00:20:38 but we're also seeing more and more AI-generated content slowly see success, whether that's the podcast that's at the top of the charts that's fully AI-generated. There's this Love Island show. There's a number of niches where they've found the right product market fit. for AI generated content, but it's not overnight. We're living in infinite jest and we just can't look away. It's like for specific things, it makes a lot of sense. And so it's working there.
Starting point is 00:21:07 Yeah, it's interesting to think about Google's strategy with video. Even Google was like, we cannot operate this for free at scale. John, you were, you were, you were, no, that was the, that was the discounted rate. Oh, I think I had 500 a month. Yeah, it was like an entry to start. It was like $250 a month. month. And it was rudely weight limited. Like, yeah, even with, we were, we were laughing at this because, I'll get three a day. I remember we'd be like at the gym in the morning, you would fire
Starting point is 00:21:37 off a couple prompts. Yeah. And, and then you were like, rate limit. I hope I got it right. Yeah, it wouldn't get it right. Then you were rate limited. And you're like, wait, I'm rate limited on a, on a $250 plan that's going to jump to $500. You're probably paying, got to check the ramp. Yeah, I got to check our ramp. It's probably paying $500 a month still. No, seriously. And And that rate limit. And that's Google with all this cash flow, all this scale. It's insane data advantage with YouTube. And that, let me tell you, rate limits kill retention.
Starting point is 00:22:09 Like nothing, nothing is worse. If you're in Instagram, the endless scroll exists. TikTok, you can scroll endlessly. You can use the, imagine if TikTok was like, after five minutes, you have to close the app and come back in 20 minutes. Like, how successful do we think that would be? It would be a disaster. And that was the experience for both SORA and V-O-3, where you would fire off a prompt, and it would be like, okay, come back in a couple minutes, it's going to take me a wild cook.
Starting point is 00:22:33 And then you fire off five, and it's like, okay, no more for today. And then the next day happens and you forget about it, and you go on something else. So clearly the compute constraints are immense. And there's just so much more value that can come from enterprise and can come from deep research and so many of the other models that are immediately economically value. like code gen, like enterprise workflows. And it's maybe more boring and less viral and less controversial, but it's where the compute needs to go. And so I think you're going to see the chips be moved around inside of all the labs to,
Starting point is 00:23:11 like compute will find the most optimal output. Like the tokens of the most value will always be the ones that the compute flows to. And as a lot of people predicted, like just endless random generations, that aren't quite dialed yet, even the best video models, like they're just not there. They require a lot of work is not the same as where we are in terms of knowledge retrieval, where we are in terms of code gen. It's just way more valuable.
Starting point is 00:23:39 So anyway, let me tell you about ACTA. Octa helps you assign every AI agent a trusted identity, so you get the power of AI without the risk. Secure every agent, secure any agent. Thank you guys. And let me also tell you about Cisco. Critical infrastructure for the AI era, unlock seamless real-time experience is a new value.
Starting point is 00:23:56 with Cisco. Market clearing order inbound. You said, what do I say? September, people overestimate how much brain route happens in a year and underestimate how much brain rot happens in a decade. So yes. So I mean, I'm using brain rot pejoratively there, but, uh, but I do think that like this, this move does not really bend the curve of, of just AI generated content, but I still think it's like a slow rollout. Like it's, it's fast in the sense that like, we went from no slop on the timeline to lots and we went from like actually zero it was like one one cool AI video Harry Potter Balenciaga was like entertaining to general people and now we get like five and then we get like next year we'll get like 20 and then eventually it'll be like hundreds and it'll be like
Starting point is 00:24:44 oh yeah I'm actually into that like people are into cartoons and people are into CGI movies and superhero movies some people will be into it some people will never like it some people will always say I want a black and white film from the 40s that's what I want to to watch. And and and and and these rollouts, the diffusion of this stuff will happen. Should we revisit, uh, one of the tweet Davidson says what do what is this? Y'all are worried about the wrong open claw. This is a good post. This is the open claw that, uh, that F. Randall was worried about in 2017. He was not he was not thinking about was. Was, was white claw invented in 2017? When did white claw get founded? That's a great. That's a great. It's a great. I, it's a great. I, I, I, I
Starting point is 00:25:26 I feel like it really took off. It had a fast takeoff. Yeah, 2016. 2016, okay. Open claw. He was an early adopter. He might have been an early adopter of OpenClaught. It truly was, I'm calling it OpenClaugh now.
Starting point is 00:25:40 White Claw did have a fast takeoff for sure. It went from zero to 60 and it was just everywhere all of a sudden. Anyway, let me tell you about Century. Century shows developers what's broken helps them fix it fast. That's why 150,000 organizations use it to keep their apps working. I got a story for you, Jordy. Today, as I was driving into Hollywood from my hometown of Pasadena, I was driving through Hollywood and I look over and there is a new Hollywood sign.
Starting point is 00:26:07 I'm not kidding about this. I actually saw this. I took a picture. I can maybe send it into the chat, but I can just show you because I'm driving and I just see this. Billy Bowman. Billy Bowman. I don't know.
Starting point is 00:26:21 I'll send it into the chat so they can pull it up. Let me see, production. Here we go. But anyway, it is a remarkable story because Fiverr is running one of the coolest out-of-home campaigns. Like, just from an out-of-home inventory, I didn't know you could do this. Let's pull up either my picture or we can pull up this. Let's pull up this video from KTLA-5. KTLA-5 had a video breaking down what's going on.
Starting point is 00:26:47 Let's watch this and then we'll react to this. And while the team pulls that up, I'm going to tell everyone about label box, RL Enviour. voice, robotics, evals, and expert human data. Label boxes, the data factory behind the world's leading AI teams. So let's pull up the KTLA 5 report about AI coming for Hollywood, the mysterious sign along the 101. Underneath a logo for Fiver and a search box says, find the best AI directors.
Starting point is 00:27:17 It's a brash, bold statement. A. Brash, bold statement. Coming for Hollywood. Fiver has made a name for its self-connecting projects with freelancers. Now they're launching an AI video hub, which they say can make content at a fraction compared to traditional production. This Billy Bowman guy is one of the directors that you can hire. He's based in Sweden. He's made AI videos for Google, Universal Music Group, and others.
Starting point is 00:27:39 As you know, AI really hasn't taken over Hollywood yet, but it has certainly crept into commercials, brands like Google and Jeep rolling out AI on national campaigns. many are slowing rather to see the 30 foot sign which went up over the weekend. I first noticed it stuck in traffic yesterday morning after someone was so entranced they rear-ended somebody else. It's causing accidents. So interesting. AI director. So it's basically someone who puts the prompt into the machine and chooses is fiber going to pay the $500 in the box buddy.
Starting point is 00:28:14 That's a great question, yeah. Yeah, can they be held liable for such a distracting sign. I didn't get a crash for you time. These air companies are flush with money. Whether or not it is a bubble like you can debate. That's interesting because Fiverr is not one of those companies. KTLA 5 is not prepared for it not to be a bubble. So Fiverr's market cap now is $560 million and that's down about 95% over the last five years.
Starting point is 00:28:45 Where are you seeing that? I'm seeing 350. Sorry, yeah, 359. What did I say? 500. Oh, sorry. So it's a 360 million dollar company today, down 95% from five years ago. It started selling off in 2021, sort of pre-chat GPT.
Starting point is 00:29:05 So I think the AI narrative might be a little bit overblown there. It did IPO around this price. It was of $700 million IPO, I think, maybe a billion dollars. went through a massive boom during COVID and then sold off. But of course, the AI wave has not been kind to Fiverr because a lot of the tasks like, you know, generating an image for- Very, very, very good at $5 creative work. Exactly.
Starting point is 00:29:32 $25. Obviously, the prices go well beyond $5 since the early days. But in terms of the kind of projects that I always use Fiver for AI, just one-shots, all of that. And the nature of Fiverr is like, you have to. define your task in a prompt. It's not, it's not, oh, have like a long conversation, get drinks with somebody. Yeah, that was often, that was often the bottle. That was the bottle. Yeah, totally. It was like, okay, I need to do this task. Yeah. I need like 10 minutes to like properly define all these things. It's honestly way more time than you spend prompting normally. Because with prompting,
Starting point is 00:30:08 you're just like, I'll just try it a few times. A bunch times. Kind of iterate. Hit my rate limits and fire back up. Yeah, I mean, it was always a bottle like, I remember as an entrepreneur, I found out about Fiverr and I was like, this is amazing. I can get random stuff done for five bucks. But the time commitment, actually finding the right person, making sure the reviews are good, it wound up being like hours of work. And if you have a consistent flow, you're better off just hiring a person. So the, so they got kind of squeezed in the middle. Yeah, the market is is not excited about Fiverr right now. They're being valued basically at four times. Evita. Okay. Yeah. And so yeah. But this is an interesting pivot for them. They're basically saying that,
Starting point is 00:30:47 you can come to us to hire someone who has all the tooling set up to actually sit there and sort of nanny all the AI models because it is a hassle. As you described, with me and V-O-3, I was sitting there like, okay, I fire off four prompts, then I go back. Like, it's way better if you're on the API and you have Higgsfield wired up and you have, you know, runway, ML and you have access to the Chinese model C-dance. It's like, you know, the right tool for the job and then you do fine tune on someone's face. There's a whole bunch of things that you can do to get better results.
Starting point is 00:31:21 But it takes time and it's a hassle and it's more of a professional job. It's not actually out of one. Here's the main problem with the campaign. Yes. Is that Billy Bowman is a real person with his own website, with his own Instagram. You can just go and reach out to him. Which is interesting because like the primary issue with these labor marketplaces, like Fiverr, disintermediation.
Starting point is 00:31:47 If a business hires somebody on Fiverr and has an amazing experience, eventually they're just going to go direct because they build up a lot of trust. And it's very different than a platform like Uber where you don't necessarily want the same driver every time because they're not around you and all these things. And so the reason that the Fivers and the upworks of the world and there's been a bunch of other like engineering focused marketplaces just have never reached like insane scale like Uber is because of the disintermediation. And this campaign is effectively an ad for Billy Bowman who you could just go hire today.
Starting point is 00:32:28 Yeah. Dissingermidation has always been a problem on these platforms. Anyway, let's move on. But first let me tell you about fin. com. The number one AI agent for customer service. If you want AI to handle your customer support, go to fin. com.
Starting point is 00:32:39 And let me also tell you about the New York Stock Exchange. Want to change the world? Raise capital. at the New York Stock Exchange. Speaking of stocks, did you see that Bombardier, the manufacturer of private business jets, is down 10% over the past month?
Starting point is 00:32:56 A lot of people were wondering why this was happening. I think we now know why, and it's probably because the shot across the bow from United Airlines. So what competes with a private jet? Potentially, United Airlines' new product, which is an entire row of,
Starting point is 00:33:13 of economy seats. We got to pull this up. United Airlines says the entire row is all yours. Welcome to the United Relax Row. Three adjacent United Economy seats with adjustable legrests that can be raised or lowered to create a cozy, lie flat space for stretching out. You'll also get a mattress pad, blanket, and two pillows.
Starting point is 00:33:35 If you're traveling with kids, a plushy too. United Relax Row will be available starting next year on more than 200 of the 787s and 777. each with up to 12 of these brand new rows. So what do you think, Jordy? Is this the way? I was telling Tyler Cosgrove, who is out of the studio today, he's in Washington, D.C. He's got to demo this.
Starting point is 00:33:55 He's got to get on one of these. I don't know. Every time the airline announces something, it's always like five years until it actually is available. I've been waiting for Starlink for a long time. Took a long time for that to get rolled out from the PR release. I think United has pretty good pace. Haven't they been quick to Starlink? So you think Tyler could get on this tomorrow?
Starting point is 00:34:09 Or today? He's going to the airport today. I think if Tyler's resourceful enough, he could just, if he ended up in a row, two empty seats next to him, he could just figure out a way to detach the armrest, blocking this and just kind of build your own. Yeah. He might, they might have to land the plane and arrest him. Yeah. But potentially worth the risk. He could also, he could also potentially negotiate with whoever sitting next to him, say, hey, you go and spend the entire flight in the lavatory.
Starting point is 00:34:39 and in exchange, I will vibe code you a sloppy app of which I don't understand what programming languages is used. I'll trade you an app for your seat. I'll trade you an app for your seat. And somebody might be like, that's amazing. I don't have anyone that can vibe code for me. This is too good.
Starting point is 00:34:53 Now I'm sorry. Ryan Peterson says, now we just need to put stairs on the food drink cards so you can climb over the top of them to get to the bathroom instead of holding it. Yeah, this just feels like, this just feels very, very chaotic. But this is wild.
Starting point is 00:35:12 I don't know. Starlink, a relaxed row, a dream. I think that this could be a good option. United built the product that everyone who has been, who has ever been on a plane wanted, says John Collison. John, you need to work on fixing Bombardier's stock price. I don't think it's related. Oh, apparently Air New Zealand launched this in 2010.
Starting point is 00:35:33 No, it is related because he should help them build out their pipeline. Well, he's just pumping his bags because he owns a property in Ireland. How do you get there? You got to fly on United. So, you know, one hand washes the other on this. He's talking his own book. No, just kidding. Let me tell you about console.com.
Starting point is 00:35:53 Console builds AI agents that automate 70% of IT, HR, and finance support, giving employees instant resolution for access requests and password resets. And let me also 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. Carter says if you say no to pretzels, the flight attendant should give you something called a coin of restraint.
Starting point is 00:36:18 While worth nothing now, these coins will play a major role in the afterlife. The coin of restraint is very, very good. I like that. Well, Elon Musk is teasing something cooler than a minivan that might come because Elon said, the cyber truck rear bench has three seats of isofix, and is wide enough to fit three child seats or three adults.
Starting point is 00:36:42 So there's been a big debate on the ISO fix attachments. These are the little metal hooks that are installed in every car in the back seat for for child seats. And so child seat requirements mean that you have to have a car that has these. And it's been it's been called like the death of the five kid family or something like that or like the death of the big family. Because at a certain point in order to have another. kid you have to upgrade your car and that has an expense associated with it you need a three-row
Starting point is 00:37:13 SUV or you need a minivan or you need something bigger that's not as that's not as affordable as you know just a normal sedan they used to be able to just throw four kids across and maybe that was less safe regulation killed the birth rate people people actually say this people say that uh the child seats have saved like like a million lives but then they've stopped 10 million from being born they they they talk about the relative exchange ratios I haven't really dug in to it too much, but there's clearly demand for more spacious vehicles with more seating. The Model S used to come with a third row, which I still don't understand how that was possible. The Model X came with a third row, and in China they actually sell a Model Y, L, which is a long
Starting point is 00:37:55 wheelbase version of the Model Y. I hope they bring that to the States. People are saying, make a minivan, Elon says something way cooler than a minivan is coming. What do you think it is? And people are speculating. Garcia here. I think it might be a data center. uh, test. I think you might be like there's another data center coming. Chip fab. Yeah, chip fab.
Starting point is 00:38:13 He's like you, you're going to be able, I'm going to end and you're not going to Texas is going to change the child labor law. Yeah. Instead of worrying about bringing your kids around yeah, they'll just go working. No, they're in the fat. They're in the fat. They're in the clean room. They're fully suited up. They're making chips. But yeah, no, people are speculating. This is very cool. I love Tesla. I has been amazing for a car enthusiast to create basically their own concept cars. these look very, very cool. We were talking about a point of Bezell about this. Make a Tesla that looks, make a Tesla version of the Rivian.
Starting point is 00:38:45 Yeah. Because it looks exactly like it. But let's get into some of the speculation. Okay, what are people saying? Cyan Bannister says an RV. That could be fun. Arthur McWater says, I can't wait for the next roadster unveil. Elon was teasing.
Starting point is 00:39:02 It was on Joe Rogan, right, this concept of maybe it'll fly. And I think what Elon could be, could be getting at is a picture a roadster, not a great family car, hard to put kids in a sports car. Some of them you technically can, but it's so uncomfortable and kind of chaotic. Very few people would. And I think what we could see is the roadster comes with five kind of like, you know, that fury collaborative combat aircraft from Anderle. What if it comes with like up to five little mini roadsters, roadsters?
Starting point is 00:39:36 that are just trained to autopilot behind the primary roadster. So you can be in your sports car. And then however many kids you have are in the mini drones following. That'd be fun. What about a Chinook heavy lift helicopter with two massive rotors that can lift your roadster off the ground? Technically, a flying car then. Yes. Anyway, let me tell you about Phantom Cash.
Starting point is 00:40:03 Fund your wallet without exchanges or middleman and spend with a Phantom card. I have a question for you, Jordie. Are you running the new AI model? It's on co-work. It's literally on co-pilot. You can probably find it on Codex. Dude, it's on co-author. It's a cosine exclusive.
Starting point is 00:40:20 It's on cocaine. You can run it on cocaine. You can literally go to cocaine and run it. What a great poppy pasta. This is one of the funniest formats. But yes, the war for co-pilot and co-work is heating up. We've got to find a new term. think. People have been really, really fighting neck with this.
Starting point is 00:40:40 Well, I was telling Microsoft, they should nature's name a Coco. Coco. Microsoft copilot co-work. It's just Coco. Coco would be good. There's a few different options. I do, I think I prefer the non-anthropomorphized AI names, although they are a little bit colliding in the namespace. I have been a fan of, of, you know, the codexes and co-works and co-pilots. Those feel more collaborative to me and they feel more like tools than the bards and the series and the Alexis and the Rufus and the sparkies like that.
Starting point is 00:41:17 That's just a different vibe. And I think that if we're living in a world where people are going to form, you know, strong relationships with these tools, introducing them truly as tools is probably. Let's see what's going on with QVC. Let's pull up this video. And we also have one of our guests joining early at 11. No, he's going to be joining. He'll be ready to join in an hour.
Starting point is 00:41:44 Are you sure? Yeah. Okay. Let's check with the production team. I've already texted. Okay, cool. We'll continue for the next 15 minutes. Fantastic.
Starting point is 00:41:52 We'll take us through the next story. What do you want? River says QVC basically reinvented live streaming decades. Invented live streaming decades ago. They invented live TV. goes 24-7. A good 80% of the show is just the host going on long personal digressions. People watch it as background, heavy parisocial element. Hosts know the callers. 95% of repeat buyers. It's 100% Twitch for grandmas. Let's pull up QVC. And with the severance story. I wanted to tell you that I got that peasant blouse with the tassels. Yes. And I used to wear the tassels on my pasties. Do you know what pasties?
Starting point is 00:42:32 are? Okay. Ridiculous. What pasties are? Yes. Let me, I'm going to do. Crazy. We need to move on.
Starting point is 00:42:41 We're moving on. Let me tell you about 11 labs. Build intelligent, real-time conversational agents, reimagined human technology interaction with 11 labs. And let me also tell you about Gemini 3.1 Pro. We are going to deep dive RKGI today, and Gemini 3.1 Pro has done very, very well. With a more capable baseline, it's great for super complex. tasks like visualizing difficult concepts, synthesizing data into a single view or bringing creative
Starting point is 00:43:07 projects to life. SpaceX aims to file IPO as soon as this week. Yes, this is a good idea. Everyone is excited for the S-1, particularly, I think people will be focused on XAI, what they have going on. I think that I... Are they going to have to break it out in the S-1? I would assume so.
Starting point is 00:43:30 This might be the first time we actually see. the economics of inference, the economics of foundation lab, even though, yes, they are at a smaller scale. It's hard to read too much into it because they've been investing so far ahead of the land. Yeah. Yeah. I just think that like there is a world where we get broken out financials that you can dig through and you can understand based on groc pricing, which we see and top line revenue
Starting point is 00:43:57 and cost, we can actually see are they serving that model profitably? And there will be, you know, a lot to dig into there. Obviously, the other labs have different strategies, different vertical integration points, different economic, different pricing regimes. I mean, the true frontier, the models that are dominating Arc AGI, which we will talk about in 15 minutes, those command a premium, a price premium. And there's a wild difference between charging $15 per million tokens versus $2 per million tokens. So it will be. Yeah. And if you remember, it was, I think it was in Q4 of last year.
Starting point is 00:44:36 If you looked on open router, GROC was what had, I think it was like GROC fast. Yeah. Had a ton of usage. People are like, okay, why is this happening? And part of it, at least, I believe, was because they were subsidizing it. Well, space stocks are moving. Here's what I think. So people were posting this as though it was fact.
Starting point is 00:44:58 But I think, I think it's, very real possibility. So I think Elon will try to aim for the company to actually go out on April 20th, 420. Really? And I think it is possible if he goes, the ticker, we'll see what the ticker ends up being, but I think some people would like knowing Elon's very millennial sense of humor. I think the ticker S-E-X is plus. the April 20th IPO. I would assume that... You think there's a real prediction.
Starting point is 00:45:37 You're not trolling? I'm not saying I'm not saying I would bet on it. But I think there's like a... I think there's... I would put the April 20th at maybe like, you know, 30%. And then the ticker maybe down at 15%. Colchie has when will SpaceX officially announce an IPO before June 1st, which April 20th would be before June 1st.
Starting point is 00:46:01 Yeah, I'm not talking about, I'm talking about, like, list actual, like, listing day, like the day of the IPO. Yeah, this is just announcing the IPO, which I don't even know if they haven't even confirmed this. This is now, this is currently in the scoop, uh, in the scoop thing. So they haven't even Scoop, you said. They, so the, wait, John, did you say scoop? Yes, this is a scoop from, from, what is this thing over here? Can we go, can we go to the wide angle? We got Katie Roof scoop master. We have a new, we have to award her the first. TBPN Golden Scoop. Do you want to show her the
Starting point is 00:46:34 I don't want to pick it up yet. Why not? Okay, we can't. We need to give the Golden Scoop Award for the best scoop of the day to Katie Roof, who moved markets with her scoop. She, of course, is the Deputy Bureau Chief
Starting point is 00:46:48 of Venture Capital at the Information, and she's an absolute scoop athlete. She's Scoop Doggy Dog. And she moved markets. So, Sats is up 7.8%. B-K-S-Y is up 4.8% LUNR is up 4.1% every stock in the space.
Starting point is 00:47:08 And we're working on a new award show. The Scoopies. The CPPN Scoopies. I think Katie Roof is a lock for the Scoopies. She's a frontrunner for sure. She's been putting on a generational run. Frontrunner for sure. Yeah, it's so funny.
Starting point is 00:47:23 I mean, an incredible moment for the retail space investor community. Because they're just, for some reason, people, people, anytime you get SpaceX repricing, they're like, well, this other random company that happens to be technically on the same market map definitely deserves to be worth 7% more. Yeah. I don't know. I was as skeptical about the rest of the lunar economy for a long time. It felt like winner take all.
Starting point is 00:47:54 It felt like SpaceX was running away with it. But there have been interesting dynamics. where companies that are buyers of SpaceX capacity, whether on the satellite internet side or on the launch capacity side, they don't want a monopoly to exist. And so they're willing to throw money at competitors. And Jeff Bezos has stuck around with Blue Origin.
Starting point is 00:48:16 Rocket Lab's done very well. There's been a bunch. People are saying we need to redesign the scoop. I don't know what you're talking about. I don't even know what you could be talking about. It's an ice cream scoop. It's an ice cream scoop. people get your mind out of the gutter.
Starting point is 00:48:31 Out of the gutter, please. And head over to Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces. And now with AI agents. Okay, Casey Hammer is worried. What is he saying? He's worried.
Starting point is 00:48:45 He's stressed. Why is he stressed? What I worry about is a generation of talented, experienced engineers being too rich to work. So if you're worried about being demotivated by your incredible SpaceX liquidity, you have to do what I recommend, which is the Brewster's Millions approach, where you have to spend all the money in 30 days without telling anyone why you're doing it. This is from the 1980s, 1990s comedy called Brewster's Millions, which I highly recommend you watch.
Starting point is 00:49:12 In it, a man is gifted an inheritance from a wealthy uncle or father figure or grandfather, and it is conditioned on the fact that he needs to spend something like $30 million in 30 days without telling anyone why and he can't accrue assets so he can't go and just buy cars he needs to throw parties and give money away and and spend money wildly and it's uh it's to teach him that money does not bring happiness of course and i think that's the solution to this uh anyway let me tell you about mongo db what's the only thing faster than the a i market your business on mongo db don't just build a i own the data platform that powers it okay here's why i'm not worried Why are you not worried?
Starting point is 00:49:53 Because I think that these ultra-talented hardworking engineers, having some liquidity, let's say someone's been there for some number of years. They have five million liquid. They buy a nice house somewhere and then realize, hey, I've got a nice nest egg. I can keep working on crazy moonshot. I don't have to go join, you know, the historical example. would be like work on the hard thing or work on enterprise SaaS. And I think this just will give people more confidence to work on the hard thing,
Starting point is 00:50:31 the thing that might have a 5% chance of success. But if it's successful, you know, has a tremendous impact on our country and things like that. So it might happen for some people. But in general, I do think that there is this liquidity wave coming. Delian talked about on the show yesterday. at the same time, like, SpaceX has been doing tenders for over a decade. And it's not like the early employees have never had a crumb of liquidity or secondary throughout their journey. A lot of them have had opportunities to sell at least a portion of their stake and had been able to buy houses.
Starting point is 00:51:08 And there's always been a way to access some of that capital, either through a loan from a bank. And you're obviously more credit worthy if you own a bunch of SpaceX stock and it's going up. up. Yeah, a bigger issue for the kind of space economy overall is just the blue origin people who like, didn't they have like way more? Like they didn't, they didn't really know what their equity was worth. They didn't, it's not like there was regular tenders. And so why work at the number two, at least by many definitions space company?
Starting point is 00:51:41 And then that's potentially ultimately bad for competition. And that's bad for launch pricing for all these other. companies that are reliant on the SpaceX's and ultimately the Blue Origin. So anyways, crazy news out of China. Apparently, the co-founders of Manus are still in China and were called up to talk with the government and are now blocked. Have you seen the dark night? Yes.
Starting point is 00:52:15 Has everyone seen the dark night? You're thinking what I'm thinking? you think of what I'm thinking we go there wrap our arms around him the plane comes grabs the balloon sucks them out of the back of the of the skyscraper it's one of the greatest scenes and I think that's what we got to do because we need personal super intelligence okay so this was surprising to me because I feel like we've been messaged to for a long time that they were in Singapore yes that's true it was that definitely like it's not a Chinese company they're in Singapore yeah the whole team's in Singapore. And you would, it takes some audacity to sell your leading Chinese, one of the
Starting point is 00:52:56 leading Chinese AI companies during an AI, a global AI race, this battle between great powers and to sell to a big American hyperscalor. Maybe get out of the country before you do that, because it's not at all, I mean, this doesn't, when the Manus Acquisition happened, seemed very clear that you would be, if you were China, and you were competing in the AI race, even though Manus is not like a lab, you're still like, okay, they're building a powerful harness. Yeah.
Starting point is 00:53:27 We probably don't want them going to serve. And the harnesses are incredibly, probably under- More important. Yeah, it's super important right now. Everyone, everyone, you know, obsesses over the models, and the models are important, but the harnesses have shown incredible promise for actual diffusion and making these models.
Starting point is 00:53:44 So Josh Wolf says, I thought this wasn't a Chinese company. And Delian goes for the jugular and says so much for all the arguments about Manus not being influenced by the CZP. Yeah. I'm mostly shocked just about how this is playing out. You would think that if you're the CEO of Manus and you get a call from Mark Zuckerberg and it even smells like a potential acquisition, you're like, yeah, I'd love to come see the headquarters. Why don't I come and with my team? we'll just come and hang out in Menlo Park or Miami for a couple months while we hash out the deal. And if the deal doesn't go through, we'll head back.
Starting point is 00:54:22 But if it does, we'll just stay. And we won't go back because if it goes through, then there's going to be pressure and we're going to wind up in this situation. This feels almost predictable. I don't know. It feels like there's something else going on here. I'm excited for this story to develop. So the authorities are reviewing the sale and they're being asked not to leave. seems hard to reverse at this point.
Starting point is 00:54:46 But again, not sure why. I mean, when you look back at acquisitions that were blocked historically, who knows how feasible it is to fully block the acquisition, but they can certainly block these individuals from materially benefiting from it in some way or contributing to Mehta's efforts.
Starting point is 00:55:08 Well, here's some advice for the CEO of Manus. When you get here to America, when you get that liquidity, that payday for Mark Zuckerberg, open an account on public.com, investing for those that take it seriously, stocks, options, bonds, crypto, treasuries, and more with great customer service. Just do it.
Starting point is 00:55:24 And then, you know, tell your story. Start restreaming. One live stream, 30 plus destinations. You should be multi-streaming. So go to restream.com. Tell your story live on the internet. Gabriel says meekmill has been going off about AI.
Starting point is 00:55:41 AI is helping him organize his whole music career and other businesses and days and it's moving his business forward at a high rate some tech Young Bull I met on LinkedIn gave me an incredible template was probably G-Stack Who else can help me with Claude Gabe says Drake
Starting point is 00:56:01 I don't do K2 Kimmy Deepseek That's more for your kind My gal more like Demis theme park Ting London Deep Mine Meek Mill I clod-coded perks out of 18th and burks. I got 500 agent lawyers trying to free little dirk. That's a good line.
Starting point is 00:56:19 Bars. Drake, sing it. You got me loco. Trying to be your shultz. You didn't sing it. Sophie chimes in. You didn't actually sing it. Two chains.
Starting point is 00:56:32 Open claw on my laptop. Trapping off these Mac minis. Shout out to YC. Real Gs want to stack with me. Oh, that's good. that is good I mean yeah it's not a it's not a bubble
Starting point is 00:56:45 until until G-stack makes it into a actual hit the funny thing here is that there's some debate and there's this general vibe like some people were latching out of this trunk fan post about like you know are people making fun of meek Mill do are people like undercounting
Starting point is 00:57:02 his ability to actually build something for real and the interesting thing is that I would definitely bet on meek Mill to build a real valuable piece of software for his audience or his life or his business over any of these tech people writing rap lyrics, even with all the powerful LLMs. Like, the tools to actually build software are way better than the tools to write rap lyrics. And it's interesting because you are seeing this dynamic where the, like, I think a lot of
Starting point is 00:57:34 people are latching on to the older paradigm of like, oh, like, you know, Jeremy Renner built an Instagram clone at one point. and it was just the Jeremy Renner app, and it was just his feed of his photos. And people were like, why does this exist? You can just follow Jeremy Renner on Instagram. It doesn't make sense that he would have like his own private Instagram.
Starting point is 00:57:52 And he probably spent a lot of money developing that piece of software. And I don't think it wound up working and it didn't scale and he wound up winding that project down. But if you think about like, well, what if this cost of doing that is 100 bucks or 200 bucks or a thousand bucks? Like all of a sudden, the,
Starting point is 00:58:10 hurdle rate to clear something like that actually does open up the creative aspects where I wouldn't be surprised if there's a like maybe not like a breakout hyper scale incredible like generational company but just like in terms of like you like you can be a great musical artist and also produce great clothing like you will now be able to produce software at the equivalent level like it is available and so if you are constrained by your ideas and if you're creative artist, and you have a great idea, you're no longer going to be in this world where you're like, well, I need to put a couple million bucks down for a software engineering team, and they're going to not really take me seriously. And all of a sudden, you get into this
Starting point is 00:58:53 weird thing where, like, the app that they launch is like sort of iffy and not that good. So I don't know. I'm actually, I'm actually coming away bullish on what Meek Mill winds up producing over the next few years. And we're working on getting Meek on the show. I really hope we can talk to him. I'll cover you're good, you're good. I'll cover meta. Okay. Do you want to jump for a second? First, let me tell you about CrowdStrike. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches.
Starting point is 00:59:22 And I'm also going to tell you about Vanta, automate compliance and security. Vanta is the leading AI trust management platform. And I'm totally good, so I can take the next intro. I have a personal thing I'm going to run too, but I will see you guys tomorrow. Yes. I love you. Cheers. Thanks, Jordi. Up next, we have Mike from Ark Prize in the Restream waiting room. Let's bring him into the TBP and Ultradome. I'm very excited to talk to Mike.
Starting point is 00:59:45 How are you doing? Here we go. Hey, Gay, good to see again. Good to see you. I'm so excited. This is always the highlight of the show. I love talking to you about everything. But what are we talking about today?
Starting point is 00:59:58 Reintroduce Arc as an organization and then take us through the actual. Do you even call them benchmarks challenges? What's the right term? I think Benchbronks is a fair word. Okay. Yeah. A couple, almost three years ago now,
Starting point is 01:00:13 we co-founded of the Ark Prize Foundation, me and Francois Chalet. Yeah. The Ark Prize Foundation has a mission to be the North Star to AGI. So sort of our sort of job, we have two of them. One is to help be a useful public sense-finding tool for the public to understand
Starting point is 01:00:28 how close, how far are we towards AGI or not. And the second is to inspire progress towards AGI. Arc is a series of benchmarks that help highlight, what are some of the large remaining gaps between what frontier AI is capable of and what humans are capable of. And we sort of target that gap. That is sort of our definition of ultimately AGI is, you know, we produce an ongoing series of benchmarks, continually studying frontier progress. And, you know, at some point, we are not going to be able to do that job anymore.
Starting point is 01:00:58 We will run out of ideas. You know, we'll test frontier eye and say we can't find anything else, any more gaps. And I think that'll sort of be the moment when I think it becomes commonly accepted to say, okay, yeah, we've got AGI now. And today, we are announcing and launching the newest best version of Arc AGII. It's the latest in the series. This is a really large format change from the first two. Arc 3 is designed to test agentic intelligence. And it is, as far as I am aware, and I've been sort of interviewing folks all over the AIC in the last few weeks,
Starting point is 01:01:28 the only unsaturated general AI agent benchmark in the world. The headline score is human score 100%, and AI less than 1%. Okay. Unpack that, like, launch, because I, my conception of Arc AGI V3 is it's almost like a 2D game. It's no longer the puzzles where I'm picking colors to match a pattern. It's actual moving arrows on the keyboard. I'm stepping on triggers. I'm opening doors, switches, that type of thing.
Starting point is 01:02:01 And I played it with you on the stream a month ago. helped us launch our preview several months back. Okay, so that was the preview. Today, we got the full data set launching today. Okay, so, so does that mean more, I'm going to call them games, more, more actual levels launching, or is this that what you're launching is like you did the actual benchmark and got the four leading labs to devote the compute and actually open up their models to be able to interface with the system to get the scores?
Starting point is 01:02:32 Both things. Okay. actually. So today, on the benchmark side, the public version of the benchmark is, I guess, the overall benchmark, so over 100 games, nearly a thousand different levels across these game-like environments. I think it's fair to call them games. We've designed them to be fun, and games are fun. I think you could look at them, you know, from a research standpoint, more is environments, though. These environments are intended to test whether AI can effectively explore, discover its own goals, acquire strategy, develop plans, its plans, one of the really unique things about Arc 3 compared to the one and two format is that it is interactive now, whereas you mentioned, you know, one and two look like these kind of static IQ puzzles that were on a page. Three challenges both humans and AI to essentially figure out the goals of themselves. When you're dropped into one of these environments, your only goal explicitly is to win. And so in order to figure out how to do that, you have to actually
Starting point is 01:03:28 dedicate some extra regulation to figure out the rules, the mechanics, the strategy. And one important thing is you're sort of playing these environments, the strategy and mechanic, they grow and they evolve and they change over time. And this is one of the reasons I think ARC3 will be a really useful tool for understanding of agentic intelligence this year. I think it'll be our first real test, seeing early progress on these AI systems that are able to do on the fly world modeling, some degree of on the fly, continual learning. These are both like critical capabilities that we view is missing today that ARC3 tests for. Okay. Take me a little bit deeper on, you said there's a thousand games or a thousand levels. A few over 100 games.
Starting point is 01:04:11 Okay. Across those 100 environments, nearly 1,000 levels across all of them. Yeah, it's a much larger version of the benchmark than we've ever had previously. And then like I said, the venture before, the other major thing we're announcing today is Frontier scores. Okay. So the benchmark is launching. We're also publishing as of today the latest four models. across all the four major labs.
Starting point is 01:04:33 And yeah, I think soda is currently sitting at like 0.3%, 0.4. Yeah, I think I saw Gemini 3.1 Pro. Maybe there's an extra hyphenate on there, but basically the Gemini, Anthropic and Open AI were all in the 0.2.3 something. And then Grock was, I think it's 0%. Walk me through the actual buildout of the hundred games. Is this entirely human done? Is there some sort of computer-aided tooling to insert variation programmatically? Or is it important that they're all created by hand? How do you think about the creation? I wish we could use AI to help design games. We'd be able to make the
Starting point is 01:05:19 benchmark even better. The reality is like humans are still the bottleneck on creativity. And so every game has still been handcrafted and hand designed by humans. You could sort of imagine if you were embedding all these different levels on like a big manifold, you know, in an embedding, you want them all as far apart as possible in that sort of space. And today, still humans are kind of the limiting factor in terms of ensuring that, you know, every game is different and is novel from each other as possible. Yeah. There's a one of, there's a few interesting design changes, actually, from a benchmark standpoint compared to one and two. Maybe the largest is, you know, Arc studies the frontier progress. We have to design our future versions of benchmark to, to, to,
Starting point is 01:05:59 adapt to changing frontier progress. One of the design goals with one and two was we have what's called a private and a public test split where we have a public version of the benchmark and a private holdout version, which is what we actually used to verify the performance of frontier models. So the frontier models get no freebies. They don't get anything from the public set. But they can train on. You can memorize the public set, right?
Starting point is 01:06:21 Or they can experiment on the public set from like a prompting perspective maybe? Yeah. The idea is the public set is intended to demonstrate the format. Okay. And this was similar with Arc 1 and 2. However, we held the design goal that the public sets and the private sets were what's called IDD with each other. Basically, that they are supposed to be as close as possible to each other. And it's just split along visibility.
Starting point is 01:06:45 Some are private and some are public. Sure. With one of the big advancements with AI reasoning is this actually, like, not a very useful way to run benchmarks. AI reasoning systems are so powerful now that they can actually generalize across IDD, test splits. And this is what we saw with RQ 1 and 2. So with 3, one of the big design decisions is we're actually releasing fewer games into the public demonstration set. So there's only, I think, about 25 games that are in the public set. We're actually explicitly not even calling it a training set anymore. We're calling it a demonstration set just to show the format to humans,
Starting point is 01:07:15 you know, be able to test your systems to make sure you can sort of create them, get a few for them. There's obviously fun marketing value of being able to play the games as humans, too, which we really love. And on the private set, this is the set that's over 100, 100 games. They're specifically different, they're different, we design them with different characteristics, different goals, different intelligence capabilities are required to beat them, the difficulty. The acceptance criteria is more extreme between human and AI performance, all to hopefully produce the most useful, like, a high signal benchmark towards whether we actually are getting real progress towards the AI with the foundation models. So let me pitch you a strategy. If I have access and I'm at Google or Open AI or Anthropic and I want to do well here, can I take the public set and create a log of all the steps and all the reasoning chains and all the key strokes that are required to pass those levels and then sort of like dump that into the context window before I go off into the unknown. And train your model that way, basically.
Starting point is 01:08:23 Maybe train my model, but also I'm just wondering if that's helpful for setting up the context or like doing some sort of like pre-compaction of the strategies that are learned. I see. Maybe not even training a custom model because I feel like that would maybe be like bench hacking. I'm more thinking about just like, okay, we went and we played all the public games to completion and we monitored them, screen recorded them, tried to extract as many learnings as possible. into, you know, an MD file, basically. And then we include that in the prompt that kicks us off, that to sort of bootstrap the learning once we get into the unknown environment. If we've done a good job on the benchmark,
Starting point is 01:09:07 you should not be able to train a system on the public set and perform on the private set. If we've done a good job. Obviously, every benchmark really is, it's an experiment. Yeah. Right? We make contact with reality. We ship these systems, benchmark publicly.
Starting point is 01:09:18 We try to analyze the performance, understand what they're good at and bad at and evolve, you know, future versions of the benchmark. benchmark, but intentionally, you know, and this actually is a very closely related to another design decision that we're making with our scoring function going forward this year. And this is, again, in response to like AI progress that we've seen. You know, our scoring methodology is basically AGI-piled at this point. We are going forward with V3 are using as, I kind of have this idea of like, basically a philosophy of having essentially don't, no harness.
Starting point is 01:09:52 we want to create a testing experience that's as similar as possible between the human and the AI test takers. And when we have our human baseline, when we have rented literally a testing center in San Francisco and had hundreds of humans play these games, all they're given is you have sort of
Starting point is 01:10:08 sensory input through your eyes and action motor output through your hands back into our testing interface. And all of the intelligence happens between those two steps. And so we try to emulate that as close as possible for our verification function where we have this sort of philosophy
Starting point is 01:10:22 of having a very stateless client so that our scoring function basically tries not to introduce any kind of bias, any kind of help, any kind of maybe potential cheating strategy. If you go read our prompt, it's extremely simple. It's like, you know, you're playing a game, here's your actions, your conversation will be carried forward to the next turn
Starting point is 01:10:38 and that's it. In order again to produce this really clear signal towards when the real progress towards AGI and the base intelligence layer, we're able to detect that. Okay, so take me back through history a little bit because I'm surprised by why AI is struggling with this in particular, because I remember it feels like almost a decade ago that Open AI had a product,
Starting point is 01:11:02 I think it was called Jim, where they were able to beat Mario, and then they beat the Dota team, Dota 5, and they were able to do things that I can't do. I certainly can't beat Lisa Dahl and Go. I certainly can't, you know, win Jeopardy or any of these things. And yet, AI systems were able to dominate those games. You've created new games. What's different about the games or the strategies by the AI labs
Starting point is 01:11:31 where we're not matching up like we did in the past? I think the biggest thing is the expectation of what constitutes real progress for its H.I. Right? When labs were using games and maybe the 2016 to 2018, 2018, 2019 era, when they're very popular, you know, human beings. researchers are studying the games, trying to understand the failure modes of machine learning, deep learning, trying to build custom search like harnesses and sort of feedback mechanisms from the environments. It's very, very handcrafted.
Starting point is 01:11:59 It's loaded with what I'll call like human G, right, in the research process. We're now at a point where we want to control for that, actually. We want to understand, like, we want to control for as little human G in these like systems as possible, right? We want to understand is can basically AI do what the human, researchers were doing back in that era in order to beat those games that they had never been trained on or exposed to before. Oh, interesting. So I do think it's kind of elegant that, you know, we are coming to find a full circle
Starting point is 01:12:26 where games are these very minimal representations of, like, actually important capabilities that humans possess around exploring and developing strategy and world modeling and being able to learn on the fly. They're really elegant as far as an environment goes. But I think what's changed is our expectation of how much human crafting is needed in order to learn the games when they haven't been specifically trained on them is the big difference today, especially with Arc 3. Okay. Remind me of some more history, but more related to Arc. I remember with one of the Arc AGI
Starting point is 01:12:58 benchmark tests, there was a version of a model from OpenAI that was running on some sort of like extra high mode. And I seem to remember like $2,000 per task being cited. Yeah, 03. Is that what it was? A very big launch. Yeah, that was like a preview of 03 in December of 2024. So really the first, you know, there's a great chart on the Ark Prize homepage now where you can actually see this data points so clearly. I think one of the really, like I mentioned before, one of our missions of the foundation is to try and be useful public-sensefinding tool. And I think, you know, when we first launched Arc 1 and 2, it was a very common critique. It's understandable. You know, hey, these things look like toys.
Starting point is 01:13:37 Are they really economically useful? Are they going to lead to any, you know, real progress? And now in hindsight, I actually think that's a pretty outdated view because we've pretty strong evidence that Arc held quite strong predictive power of noticing really important any moments. We only started seeing saturation on the V1 benchmark. And remember, V1 was like five years old. We only started seeing any amount of progress from LMs on V1 once we got ARIZing, which was a really critical innovation I'd argue as important as the original transformer innovation. And then a year later, this was four months ago now with the November, December 2025-2, and Opus 4.5, we again,
Starting point is 01:14:14 started to see saturation on ARCV2, and it precisely correlated with this, like, agenic coding capability that emerged. Yeah. And so I'm optimistic that ARC3 will again be a very useful, sort of predictive tool to understand when, you know, basically AI agents are capable of operating more open-ended environments. Right now, you know, you need a lot of human handcrafting
Starting point is 01:14:35 to get these intelligence systems to work in domains, such as coding, right, with Cloud Code, or Codex and Cloud Code. Yeah. And that's, I basically expect that, like, when you are doing very good on V3, which will mean, by the way, 100% score on V3 means, like, AI can sort of beat all the games as efficiently as humans can on an action basis, that will lead to economically useful systems where agents are able to operate in more open-ended environments that they have been specifically trained on.
Starting point is 01:15:01 I still remember from RKGI 1. You know, you see these, like, three-by-three grids, and the first time I ever tried it, I tried on my phone, and I think my phone was in some way. weird like landscape mode or something. So it wasn't rendering correctly. And I was like, you didn't even get all the data points. Yeah. No, it's so normally it's like you see the blocks and then you see the blocks to the left
Starting point is 01:15:20 and the right. And I was like, wow, I'm like, I'm cooked. Like the fact that other people can do this. But of course, once you load it on desktop, it's very usable. I want to continue down that path of the, the, the, the, the, the, the, oh, three, extra high. Like, what are you seeing from the labs that put forth models that did test, on Arc AGIV3 in terms of just steering the models.
Starting point is 01:15:48 Because we talk about GPT 5.4, but that means a lot of different things these days. Was this in the max reasoning? Should I compare this to what I'm seeing in ChatGBT? I'm getting more and more drop downs where I can go, oh, I can go pro and then I can go extended thinking mode. Is it an off-the-shelf model, or are they able to sort of come to you and say,
Starting point is 01:16:10 hey, we want to actually marshal 10 times the amount of compute for this particular challenge. On our verification leader board, we have a new testing policy. It's actually something we did have with one and two introduced after O3, where we limit to $10,000 per verification run. Okay. This is somewhat of a practical, like, consideration. If we actually used, like, the most expensive, highest, you know, a million context window of the most expensive model, I think testing of the full V3 private data set would be like $100,000,
Starting point is 01:16:39 Which is just kind of like silly, right? Yeah. So we set a reasonable limit like humans nowhere near as much as sort of like dollars to sort of produce this. Yeah. I like that too because like that is the that is like getting AGI and it's like yes, it can do anything, but it costs a 50 million dollars per prom to do one hour of human labor. Like that's not really economically valuable. And so bounding it makes sense. I think you want to know progress, right?
Starting point is 01:17:05 And I think $10,000 is a reasonable amount of money where you actually see some degree of progress. and that would be a useful signal to start paying attention to it more. Yeah. And it's like just, you know, for practical reasons, we just can't. We're a strapped nonprofit.
Starting point is 01:17:16 So, you know, we have to be sort of thoughtful on our sort of money on how we deploy things. Well, good lie. That's, that's sort of, so I think of the high reasoning mode is the most we used on,
Starting point is 01:17:24 for the official verification stuff that we've used today. So, I mean, do you spend a lot of time thinking about your own AGI timelines? Has your work at ARC shifted your timelines at all? Or do you feel like,
Starting point is 01:17:36 oh, I've always been 20, 35, guy? I'm still a 2035 guy, something like that. Like, do you have an internal model of this? Or is that even useful these days? I, instead of listening to my predictions, you should probably follow our actions as our, like, best sign of a sort of review of progress.
Starting point is 01:17:57 I think the reality is we have made tremendous progress with their reasoning over the last 12 months. Arc is operating to bring the next version of the benchmark. We've already started work on Vee's, We actually have plans written down already for V5 as well. Our intention is to bring these to market annually over the next two years. And so that's sort of our expectation of having the next version ready right now. Now, like, will we actually launch them?
Starting point is 01:18:23 I think we'll have to see where Frontier Progress says. We want the future benchmarks to be as useful as possible. And so if there's like still a lot of utility and scientific value in the current version of the benchmarks, you know, we want to keep focus on those. But to the extent that like the scientific value is starting to wane, we want to have the next version. ready that has sort of like identified, hey, are there other interesting remaining large gaps between what humans can do and AI can do in order to drive that gap to zero. Again, we're very, we're very AGI-pilled organization. We want to see progress.
Starting point is 01:18:49 We actually love seeing progress. Yeah, of course. And part of our goal is to inspire as much progress as quickly as we can to get to these AGI systems. Yeah. So I'd say like, yeah, that's sort of the operating view. We'll, you know, a common question would be like, well, is V3 AGI, is V4 AGI, is V4 AGI, is V5 AGI. They were their honest answer, and this is something I've actually learned.
Starting point is 01:19:08 I had a different view of this maybe three years ago. The honest answer is no single version of any benchmark is ever going to be a GI. I think the frontier progress is a moving target. And our job is to like understand that the gap, the remaining gap. And the definition of that gap is going to change as time goes forward in order to keep chunking up. What are the largest pieces of that gap that we can find that are interesting, you know, that identify some missing important capability that humans are able to do and produce benchmarks that showcase that gap. Last question, I'll let you go.
Starting point is 01:19:38 what's going on with a Pokemon bench? That feels somewhat related, similar tasks. What are you learning from that? How are models becoming so good at that? It feels like they aren't specifically RLed on Pokemon, and yet they're learning, but also there's a massive amount of written text about what to do at every level in Pokemon.
Starting point is 01:20:01 Are they just learning that from the pre-training corpus? What's your thesis on Pokemon? It certainly seems helpful. If I use our experiencing developing ARC as a tool to true a sense finder on this, we have seen more understanding from the latest generation of AI reasoning systems over the last three months than we saw in the first six months when we were developing ARC V3. I think you can kind of fork, you can almost split the research problem of agents into two things. You can split it into a problem that says, can an AI agent effectively perceive some kind of environment state, apply a strategy that's written down to produce actions and successfully execute a plan?
Starting point is 01:20:48 That's half the equation. The other half of the equation is can you have agents that are effectively able to develop what that plan is? And to do that, you need to be able to on the fly, build like a world model of your task, acquire goals, create your strategy, create your plan. We've seen a lot more progress on the perception. through strategy to action problem than we've seen on the exploitation problem, the strategy generation problem. I actually think this is one of the areas
Starting point is 01:21:13 that I would point interested ARC3 researchers at because I think it's a lot more greenfield and will unlock a lot more progress even on things like Pokemon Bench where it's kind of coming down to like, okay, we know they can sort of, I should say,
Starting point is 01:21:29 execution. The exploration and planning step is still where there's a large degree of bottlenecking still happening. day. Well, congratulations on the progress. Where can people find it? How can people participate? How can people help out? Yeah, go to arcprice.org. You can play the games as humans. Like I said, we've got almost 25 of them, I think, on the site that they're all designed to be very fun. We're closely controlled for this, actually, when we were doing human baseline testing. So that actually be fun and can have fun. And you can also get details there to enter arc prize 2026,
Starting point is 01:21:59 our new $2, uh, prize pool this year that's on arc two and arc three. That's amazing. Yeah, our teammate Tyler Cosgrove was climbing the human leaderboard for a while. I imagine he's been knocked off, but we'll have to get him back on top. Thank you so much for taking the time to come chat with me. This was fantastic. We'll talk to you soon. Have a good one. Let me tell you about Gusto, the unified platform for payroll benefits and HR built to evolve
Starting point is 01:22:23 with modern small and medium-sized businesses. And let me also tell you about turbopuffer, serverless vector and full-text search built from first principles and object storage, fast, 10x cheaper and extremely scalable. And without further ado, we have our next scale. Nathan from Air Street Capital coming in to the TVV& Ultram. Nathan, how you doing? Great. How are you doing, John?
Starting point is 01:22:41 Thank you so much for staying up late. What time is it there? 725. Okay, not too bad, but past the workday. Reintroduce yourself. It is your second time on the show, but reintroduce yourself and give us the news. Yeah, I'm Nathan. I started a venture capital firm called Air Street Capital in 2019 to invest in AI for his companies.
Starting point is 01:23:03 Wait, what year were you investing in AI? Well, so I started the firm in 2019, but started investing in AI in 2013, which was probably around the time that deep learning was still definitely cooking only in the lab. And most people didn't really care too much outside of it. Yeah. What were the median deal like, what was the median deal like in 2013? Was that like recommender systems? Like, we're going to bring Netflix recommendations to everyone, like that type of thing? Yeah.
Starting point is 01:23:32 Well, it was e-commerce recommendation systems, ad tech. Yeah. Big data was the buzzword back then. Sure. A little bit in finance. Like insurance underwriting, like loan prediction, credit. Yeah, yeah, your risk. Yeah. Fraud detection. Just like a big, I guess it was like a, were they doing deep learning yet? Or was it mostly just like?
Starting point is 01:23:55 Yeah, they were. Yeah. I mean, it was 2013 was the year that computer started to be able to recognize images better than humans. Oh, yeah. That was, I remember like Andre Carpathie was. the infamous human benchmark on ImageNet in 2013, PhD. That's right. So that was the year when basically like Alex at University of Toronto, like built AlexNet, which was the first deep learning system running on an video card.
Starting point is 01:24:21 Yeah, yeah. What a remarkable time. So what has it, has it been easy? I mean, you just raised a new fund. Has it been easier to pitch this to LPs? What have been the challenges and opportunities over the last few years? Yeah, I mean, it's been a sea change. Like in 2018, you know, when I started for Arestredo, it was like, you know, by myself,
Starting point is 01:24:44 the solo GP super contrarian, starting in Europe where risk aversion is extremely high, trying to focus on AI, which most people didn't really care too much about, and then first time fun. Those are sort of like all the worst, like, buying selection criteria. No flash. One would have. Yeah. And then, yeah, like, I think, you know, this is very much like a long-term journey.
Starting point is 01:25:05 Like, you know, I set out with, I'm going to do these early stage investments, be high conviction, invest in biotech, defense, vertical software, dev infra. You know, I stuck with what I said. So, you know, investing in like Sintesia, 11, Black Forest and others. I'd like six exits to like recursion and, you know, a company that went public and Amazon, etc. Yeah. And then, and then, yeah, like first fund was like $27 million. Fund two was $121.
Starting point is 01:25:32 About three years later, again, pre-chat GPT. and then and then this one's 232 million, which at this point makes us the largest solo GP in Europe. That's amazing. So us, you said solo GP, but you said us, who else is on the team? You know what? Like I'm kind of guilty with the Royal We thing. But I have two colleagues who run talent and operations and then a pretty sizable back office for like admin. Sure.
Starting point is 01:26:00 But everything that comes along with like building brand, finding founders, investing, fundraising, I think that's all me. And the decisions are at the head just me. And then also the, is it an annual report state of AI? I mean, it's sort of a huge project. Do you bring in collaborators on that? Yeah, I started in 2018 to basically create like a kind of canonical open access document covering research industry, politics, and talent.
Starting point is 01:26:27 There are a number of contributors every year who are sort of like at the call phase during their PhD or like transitioning between roles in AI labs who help this kind of state. smart on things and also folks who've been working on policy because it's become increasingly important as we've seen the news almost every day. And then the cool thing is like I get contributions from companies and labs and researchers every year. And like I think this last year when we last talked, there was like 50 people in the Google Doc kind of like leaving comments being like, hey, I tried this implementation, this paper, like I had this problem and then some other person's like, that was my paper. This is what I tried. And it's like cool like community document basically
Starting point is 01:27:04 where we can kind of get to the center of truth. Not to call you like lucky on timing. It's very fortunate that you have the size of fun that you do for where we are in the market cycle. But how hard would it be to do what you're doing today with a $27 million fund? Because it feels like a $27 million is like a seed round for like a startup with just an idea.
Starting point is 01:27:29 Sometimes that's like 1% of the seed round. but like is it can you even make plays with that size fund if that's what you were constrained to today? I think you have to decide like what I did, which is either you want to be like a main player and lead rounds and express your conviction and be early, etc. Or you play the like large portfolio model and then you have checks and a lot of opportunities. And for me that job is like much more like a network SDR style job and less of like I can make my own opinions like do the research, be there early. then when I like something, like really make the bet. I don't think you can do the former. They'll be a lead investor in $27 million, no chance.
Starting point is 01:28:10 I think you can do the larger portfolio, you know, chipping into a variety of rounds and still have like good performance. But it's just a different job that I don't particularly enjoy and doesn't maximize like my strengths and my interests as much. Yeah. You know, so I think at the end of the day, like you got to pick what flavor is good for you and then try as best as you can to bring the best product to the best product to the market given your circumstances. And I was fortunate with Fund 3 to be able to really come
Starting point is 01:28:37 with like a blank slate with, you know, long-term partners and say, like, this is what I think is going to be the most convincing model, you know, right up to $15 million in first checks and do a couple of gross stage rounds up to $25 million. But still, you know, high conviction, 20 companies. And of course, like I'm, you know, mostly based in Europe, but still invest in the U.S. and spend decent time there as well. Yeah. I mean, I know you're in Europe, but you're not, you know, an exclusive European investor by any means, but I am interested in the thought exercise of like, where is the AI opportunity internationally? If I were to just back of the envelope, I'm, you know, I've seen some of the sovereign AI efforts. It sort of makes sense that
Starting point is 01:29:21 like a certain government might want to buy from a particular local lab. But at the same time, like, you know, Google has been very successful internationally. And, you know, China, got the Google of China, but many other European countries didn't get the local Google competitor or the local Amazon competitor or the local Microsoft or Apple competitor just because like they were consumer products and consumers kind of flow wherever they want. But at the same time, I can imagine if Google or Open AI or Anthropics going to build a data center, they might want to go to a local neocloud or there might be opportunities for, you know, the Harvey of some other country that has different laws and different rules.
Starting point is 01:30:00 And so how are you seeing the shape of like opportunity outside of America in AI? I think you covered it really well. And I would generally agree with you on this. You know, Europe doesn't need its own Google per se. And in fact, historically, like the government has tried. There was Quero and one or two other initiatives that, you know, had hundreds and millions of dollars. It was pumped into them so that they could, like, capture European culture better than Google could.
Starting point is 01:30:25 And I think that's a bit bizarre when you're talking about a learning machine. Yeah. But so there's certainly some sector. where I think the sovereignty really matters, and it's not just marketing speed. So, you know, defense and security is clearly one, where, you know, Europe woke up to this like two years ago and now even more so with the Middle Eastern war that's ongoing.
Starting point is 01:30:45 You know, as an example, like I got invested in a business called Delhi and Alliance Industries doing defense, autonomous defense systems, right, in Greece. And one of the number one things we got from people outside of Greece, particularly in the US, is like, why are you investing or building a company in a vacation resort that I go sailing in, you know?
Starting point is 01:31:01 Yeah. And then that narrative changes significantly. Once you start seeing Shaheed, like, drones hit, you know, UK bases in Cyprus, and you realize, like, okay, the border to southern Europe actually comes over the Mediterranean degrees. I think the other part, which is interesting, is like, ambitions change. And I think in Europe where traditionally there's been fewer role models that one can look to and say, I'm going to be like that person and I know the path.
Starting point is 01:31:28 some companies grow. And, you know, for example, I think Ligora originally started as Leah, like started in Sweden, right? And it was the idea of, hey, we should do this locally in Sweden. And now, like, clearly that company's ambitions are like, no, we can go head to head with Harvey. Yeah, yeah, it does feel like in Europe, like the entrepreneurs that break out, they're not saying I'm building X for Europe. It's like, I'm building 11 labs. I'm going to go everywhere. I'm building Spotify and I'm going to go everywhere.
Starting point is 01:31:57 And yes, I happen to be from some other country and I'm going to have a headquarters there, but get ready in New York because we're going to have an engineering hub and SF. And we're just going to be an international company and have our roots there. And that's the right path. Yeah. So this is why I think if you're going to invest in Europe, it's really important to have this foothold in knowledge of the U.S. market so that you can apply the same quality distribution that you see in the U.S. over in Europe. And either there are people who start from day one being that ambitious or there's others that grow and, and, and, kind of, yeah, just like fuel their batteries with ambition as they see and experience it, you know, like when you get success, you want more of it. And so that's like the kind of recursive
Starting point is 01:32:36 cycle of the continent is going through. Yeah, I mean, with all the progress from the big labs and they're at such incredible scale now, like, how are you processing the SaaSpocalypse and just advice for founders of like what gets steamrolled versus what doesn't? I mean, there were some there was some founder. We've had a couple founders on the show that have been like, we're doing AI generated video social network. And then it was like, you're getting steamrolled. And then it was like, actually, like, you know, SORA's not going to be in the app store anymore.
Starting point is 01:33:02 So like maybe that was a good bet. I don't know. I'm not on that particular app, but it feels harder and harder. It used to be just like, don't do an app that's just a prompt around the foundation model. Like that's done. But now we're talking about, oh, is there pressure on CRMs? Is there pressure on databases?
Starting point is 01:33:20 What will the labs do? It's unpredictable. But how are you working through it? I think, you know, one thing you could say is, like, what are the problem sets and areas that, like, the smartest AI people want to work on? And, like, don't do that. Okay. So, like, that's a good way. Like, don't do coding.
Starting point is 01:33:37 Yeah. Like, after, I think it seems like AI researchers really like AI for science. So, like, don't do that easier. Totally, totally. Yeah, yeah, yeah. We have a friend from the show that does, like, yeah, it's an AI company, but it's for, like, small businesses, like HVAC owners and helping them. It's like, yeah, I don't think that. on the roadmap.
Starting point is 01:33:58 That's really good. The jokes aside, I think it comes down to like this tacit knowledge and like where you can capture how people do a task and taste. Like I see this a bit with our job. Like, you know, I'm using like, I'm Claude Maxing as well and like codex maxing. It's amazing how it can, you can imbue it with your taste and you're like at some point you realize, we built like a learning machine that basically is like a sieve you can pour as much as you want into it.
Starting point is 01:34:25 still learn stuff, but before it was only one task at a time and, like, forget accumulating multiple tasks. So at this point, if you're really AGI-I-pilled, like, you have a call, you pipe the feedback in, you ask, like, hey, how did I do? And you get suggestions, you do that on the next one. You pipe it back in, and then you're, like, make a skill file. And then next time, like, here's the new opportunity. I'm like, dude, if you're not doing that, it's, like, game over.
Starting point is 01:34:47 Yeah. And so I really do think, especially for our job, like, there was a point at which you're, like, solo GP with, like, $200 or $300 million with a bunch of AI. Yeah. So I'll call you in 10 euros and see if it works. I'm excited. I'm excited. Well, I want to hit the gong for the new fundraise.
Starting point is 01:35:03 Congratulations. Thank you for coming on the show. Have a fantastic rest of your day and I will talk to you soon. Have a good one. Goodbye. Let me tell you about vibe.com. Where DDC brands, B2B startups and AI companies advertise on streaming TV, pick channels, target audiences, and measure sales just like on meta.
Starting point is 01:35:23 And let me also tell you about Plaid. Plaid powers the apps you use to spend, save, borrow, and invest. securely connecting bank accounts to move money, fight fraud, and improve lending now with AI. And without further ado, our next guest is in the Restream Waiting Room. We have Rohan Dar. He is a real estate expert. Thank you so much for joining the show. How are you doing, Rohan? Good to meet you. Good. Happy to be here. Since this is your first time on the show, would you mind kicking it off with an introduction on yourself? And I'd love to know some of your background, how you got to where you are today.
Starting point is 01:35:51 Yeah, I am a San Francisco real estate agent, and I'm among the highest producer. by volume in the city. And I came from a little bit of a traditional background. I did a YC startup. I went Stanford Business School. I did a bunch of startups. And then got into real estate when kind of learning about Airbnb early on and built a small portfolio of that.
Starting point is 01:36:13 And then learned the real estate craft from that. Did you have to get a license at some point? Did you join a big firm? Or did you just strike that on your own? My Twitter account started growing because I was like posting interesting houses. that I was like just kind of curious about. And then people were messaging me like, oh, I actually like bought that house you
Starting point is 01:36:33 posted about and says like, dang, like someone's making a lot of money off of this and it's not me. So then I like decided to get licensed. And originally I was going to focus on like Airbnb markets and short-term rentals and vacation areas. But I live in San Francisco and I could see the prices were like after the pandemic just like crashing here while they were shooting up everywhere else. in the country and I was like, oh, they're converging. And that's like odd to me. And so I was like, okay, well, Y-C moved here. Open AI is just sort of like getting traction.
Starting point is 01:37:06 And the city's getting better. I think everyone was sort of agreeing to that. And then I was like, well, this is the opportunity and I'm getting a license and like, this is what I'm going to focus on. And then I had a lot of traction with it. So I just sort of got sucked in to be sort of a full service, like, you know, Rohan in your corner, real estate agent when you're trying to buy or sell place.
Starting point is 01:37:26 I love it. When did the actual rebound start? Where was the trough after COVID? So the interesting thing about like COVID was 2020, 2021. Everyone was leaving San Francisco, but the prices kept going up because interest rates were like practically zero and there were always liquidity events. So prices were rising even though things were looking like a little bit desperate in the city. And then when interest rates rose, that sort of like tampered the liquidity in the market.
Starting point is 01:37:57 And then sort of at very end of 2022, things like abruptly dropped. So, end of 2022, 2022, 2023, 24, prices were way down. And then 2024, by the end of it, there was like a little trickle. And 2025, you sort of had come out of the bottom, but it was like a slow, you know, like pretty stable market, but on the upper trajectory. And then end of 2025, then it just sort of started booming like crazy in terms of pricing. And then even from like, you know, March 2026 is like way up compared to like two months ago. So yeah, what does it actually take to raise a family if you're working at a tech company in San Francisco? Because I think a lot of people will move to suburbs.
Starting point is 01:38:45 But walk me through, you know, if you're coaching someone that has a couple kids, they want schools, they want access to their employer. Like, how should they be thinking about what it takes to find a great place in San Francisco these days? I don't even know if people think of it that way. I think it's like, San Francisco is just, like, such a scarce place in all ways. It's like there's not enough housing. There's not enough, like, restaurants. There's not enough this or that. And it's sort of like, if you want a place, like, in San Francisco, you're, like, so convicted on the idea of it, of the city, of, like,
Starting point is 01:39:23 the tech industry. You're like, you know what? I'm just going to do this and then I'll figure the rest of it out. And so, like, I don't think people are like, oh, now I have to figure out like what school my kids are going to go to or like what my commute will be or this or that. It's like, if you're sort of like dilly dally around the edges, you sort of end up never really sort of being so committed and that kind of ends up being like what makes it hard to buy a place. But like the people that like actually win
Starting point is 01:39:49 these homes, whether they're like, you know, any price point, it's like there's something mentally inside them that's like this is the place for me and what does the the like the down the fairway place in san francisco look like these days is everything over two million three million like where are we in terms of like single family if you're kind of trying to find a place that is uh that would fit four people and might have parking and a second bathroom and two or three bedrooms um say like a year ago it was like around two million and And if you were slightly above that price, there'd be like a big drop-off in competition. And now it's like that level has sort of definitely moved up to like three-ish million.
Starting point is 01:40:32 Wow. But the bigger change, too, is that like there's like huge level of competitions at any price point now. Okay. If it's like one that sort of checks the box for buyers. So give me some advice if I'm trying to win one of those competitions. What do I have to do? I have to show up with all cash, just put the cash in the bag. What do I do?
Starting point is 01:40:50 I mean, all cash, I mean, in any given offer process, like there'll be a decent number of all cash buyers. So it's not like it's gonna, you can walk in and be like, oh, I'm gonna win this because I'm all cash. Like assume like a third or, you know, half might be over a certain price point. And like, I think what you're sure to have to realize is there's going to be a range of competition on any given house. So like some houses, you know, this could be like a five or six million dollar house,
Starting point is 01:41:18 so pretty expensive house and there might be like 15 offers. Whoa. And like the seller's not like going to be like, just sell it to you because you're a cool guy. Like, the market will sort of dictate the price. And unfortunately, for buyers, you just have to say, you know, the highest price and the best terms to win. Okay.
Starting point is 01:41:35 And so, like, what you're sort of trying to navigate is the level of competition any one house is going to have. So, like, say it doesn't have as many bathrooms as you want, but you could figure out how to add one. Or say, it's, like, off market and only a few people know about it, so there's less competition. So, like, your lever of getting a good deal on a house isn't, like, just, like, just, like, like participating in a massive auction. It's like trying to participate in an auction only you know
Starting point is 01:41:58 about or a smaller sort of, you know, a different kind of property. And you're probably expecting it to go a lot higher, I imagine, with IPOs, the labs are getting bigger, there's more liquidity, there's new investment rounds happening. What's your forecast? Well, obviously it's like, you know, hard to challenge, you know, predict the future. But I wasn't. like, oh, I'm a San Francisco real estate agent, you know, like, I'm going to say like, you know, whatever. Like, I decided to get into the market
Starting point is 01:42:30 because I thought like this was going to happen. I was like, oh, like, these scarce homes are going to become more valuable and people wish they bought them and, like, I should focus on this. And so, like, personally, I'm convicted, like, the city is on the right trajectory now. So it's not, like, contrarian to buy a place
Starting point is 01:42:47 here at the moment. And then there are, like, liquidity rounds and like that has made a big impact on the market. And if the liquidity rounds get bigger, like there's, it's a fixed number of homes that the, you know, that money goes into.
Starting point is 01:43:02 What do you think expansion looks like over the next few years? Are we going to, I know Mill Valley is booming. There's other suburbs. Is Oakland going to happen? There's this California forever development that's happening.
Starting point is 01:43:13 That's further out. Like, are you starting to broaden your horizons? Or do you want to stay focused? And what do you think the real estate buyer will want to do? in the near future. So I solely focus on San Francisco like buyers and sellers. Because like I found that like in order to like every time, especially on the buyer's side to win, it's sort of like pulling off this like mission impossible like heist where it's so elaborate. And you have to know
Starting point is 01:43:39 like every detail about the market. And so for me personally like I feel very strongly that I can really help people in San Francisco. That makes sense. And then if you put me in Mill Valley, it's like, oh, I mean, I don't, I mean, maybe it's good for me to help serve Mill Valley customers, but it's not good for them. So I think, like, you know, if you're going to use a real estate agent, you should use one that, like, really knows a particular market really well. So for me, I want that to be San Francisco. Yeah. How much of the San Francisco boom is attributable to the labs being based in San Francisco, like, specifically, as opposed to the previous generation of tech boom times happening in Lopar, Cupertino, sort of on the peninsula.
Starting point is 01:44:22 Yeah, I'd say it's about like 50-50, like explaining what's going on. Like, on one hand, like, what's really driving it is like the perception that the city is on the right track with like the mayor and like walking around and it just feels better and it feels fun and people are moving there and sort of like it's sort of regained the zeitgeist of like a place you move to invent the future. So I mean that's like half of it. And then the other half of it is like, yeah, like we've had very successful companies in San Francisco tech companies, but we never had the big one, like meta or Google or Apple.
Starting point is 01:44:53 And now, like, we have two, you know, that, like, just started that are within that range. And, like, it's somewhat unprecedented, I think, even though we've had, like, $100 billion companies before and, like, possibly successful ones. They never had this magnitude. But this is at a different level, an order of magnitude. And so that's just going to drive up attention and excitement and all sorts of things. what are the most underrated neighborhoods what's on the come up right now um you know everyone sort of really wants like noe valley pack heights like i think if like if you're sort of like
Starting point is 01:45:28 looking in the noy area like burnall like the the kind of the hills right next to it glen park like you know sunny side is like dramatically less expensive um like pack heights is now like getting to be like back to its sort of premier level pricing, but Russian Hill is like right next to it and like a little bit less like walkable and in this, you know, but like, you know, just as great. But now the prices are up there. And then like knob hills next to that and the prices are still a little bit down there. So maybe I'd say knob hill and, you know, Bernal Heights. Well, where can people get in touch with you? How do people reach out if they're looking to buy places in Zisco? You know, Google me, Rohen-Dar.
Starting point is 01:46:14 and then find my email or just reached out to me on Twitter and I'm pretty active there. And generally, I just share what's going on in the market over there. Fantastic. Well, we appreciate you taking the time to come chat. Thanks so much. Awesome, yeah. Happy to be here. We'll talk to you seeing.
Starting point is 01:46:27 Thank you. You too. Goodbye. Let me tell you about cognition. They're the makers of Devon, the AI software engineer. Crush your backlog with your personal AI engineering team. And let me also tell you about graphite. Code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster.
Starting point is 01:46:44 And without further ado, we have Eric Jorgensen, good friend of mine. He is the author, the publisher of the book of Elon. Thank you so much for sending these. It looks fantastic. And I was particularly, I want to get into the book, but I think partnering up with Jack Butcher on this, deeply underrated. He is an incredibly special illustrator, designer. I don't even know what you call Jack Butcher, but obviously he was helpful in this. But thank you so much for taking the time to join the show.
Starting point is 01:47:13 How are you doing? Thank you for having me. I'm honored to be here and extremely excited to put this thing out into the world. Yeah, listen to that voice. You got a voice for live stream it. Let's go. The microphone's helping. You got a good setup. It's good job. My wants to get discovered right now? I think so. No, of course, you've been online a million times. We know everyone knows you. But maybe take me back to a little bit of like how you got into publishing your business overall. The, the Naval book, and then we can go into the Elon book. Yeah, that's an amazing setup, because then I get to shout out Jack Butcher again. Basically, like, I was tweeting and blogging happily in, like, 2017, and I had been following Naval. I learned so much from him over the years, and I felt like he was putting out this timeless wisdom that was just dissolving into the stream every day, and it just broke my heart that it was going to get lost, get buried so quickly.
Starting point is 01:48:13 This is the thing with Twitter. It's ephemeral, which is amazing, but there's no rediscoverability. We actually put out this account once, Bangor Archive, or we would just share screenshots of old tweets, and they would go viral again. But Twitter doesn't, it acts isn't set up to resurface stuff like that, like YouTube is, like Netflix is. And so the back catalog really goes stale, but you were able to obviously repurpose it. Yeah.
Starting point is 01:48:37 I think so many of the great books have this, like, long, fat tale of timeless wisdom that we keep needing to revisit. And Naval was, you know, obviously has done an incredible job distilling that wisdom and articulating it for sort of our era. And I wanted to preserve that in a permanent format. And that side project that I did in nights and weekends and published, you know, hoping to sell a few thousand copies has gone on to sell. I think we're coming up on two million. I've given away five million more digital versions and 40 languages. It's crazy. That's It's such a huge number. I feel like it's hard to sell a thousand books and you've sold two million.
Starting point is 01:49:16 That is an unbelievable number for those that don't have like inside context in the book industry. Like I think the median outcome is like a few hundred and like 10,000 is top fraction of a percent. Yeah, absolutely incredible. What was the strategy? I mean, Naval has a big audience, but I don't see him pumping this book constantly on his Twitter feed or his X-Feed. Like how did this book actually get in the hands of? customers. Is it like top of Amazon? Is it on the New York Times bestseller list? Like, how do you even sell that many books? I cannot explain it other than to say it has become like
Starting point is 01:49:50 a word of mouth phenomenon. I think it is just so many people tell me they buy it as gifts or they recommend it or they give it to, you know, I know teachers they give it to every class that comes through. And it's just sort of, it's, who doesn't, the subtitle of the book is a guide to wealth and happiness. Like big tam, right? Like universal human desires. And new people graduate into trying to figure that out for themselves every day. And I think it is this really rich, dense collection of Naval, who's a really, really gifted sort of distiller and articulator of some of the most important principles that make life, make lives successful. What principles from that book either stick out to you are timeless or maybe even underrated that you keep coming back to you? I think
Starting point is 01:50:39 I mean the on the wealth side leverage is still an underrated one I mean you guys are living examples of this authenticity is another one that like that word is thrown around so much that it becomes
Starting point is 01:50:52 sort of a cliche but the people that we tend to admire the most or that are doing the best are a really interesting combination of like excellent authentic and leveraged right like Jack Butcher is an incredible example you don't even really know how to describe him He's like, he's an artist, but he's a contemporary artist in the digital era, and he's a really gifted designer.
Starting point is 01:51:14 He's kind of like inventing this category of networked art. But whatever he is, is him, and it's awesome, and it's massively leveraged. And, you know, he's doing things that nobody else is doing in the art game. Do you think that being controversial is correlated with authenticity? Because if you're not authentic, you can be this very polly, one side, you know, many-faced thing. You interact with one person in a certain way, another person in another way.
Starting point is 01:51:44 You make everyone happy. You're less controversial. As soon as you start wearing your heart on your sleeve being authentic, you're going to attract some people that don't like what you're showing them because you're showing them the true self. Is there anything there? It's a great question.
Starting point is 01:51:59 I bet there's two opposing archetypes. I bet there is a type of person that is extremely inauthentic in how they court, controversy for the benefit of, you know, the algorithm or just being elevated by being attacked. And I bet there's another set of people that are authentic despite any headwinds or controversy that might come up. And I think the only way to probably tell the difference is just zoom out and see who's been doing what for how long and in under what contexts.
Starting point is 01:52:29 So how obvious was it that Elon was going to be the next subject? I imagine that. I imagine that, that the playbook that you ran, the process that you ran with the Naval book could apply to a lot of entrepreneurs. It's a very interesting style where it's high leverage. I can only think, I can only describe it as high leverage because you're, you're standing on the shoulders of giants, which is like all of the work that they've produced, all of the podcasts that they've done, everything that they have written. There's a lot of primary research there that doesn't necessarily require the same, you know, access and permission. And you can do a lot of pre-work independent before you actually go in. Whereas some other books, it's like, okay, this author
Starting point is 01:53:20 didn't even get the interview with the person that they're writing about. Like, you know, no one wanted this book to happen. And that's a lot harder, right? So, so I imagine that the list was pretty long. How did you narrow it down? How did you land on Elon? Why this person? Why this time. Yeah. This is an interesting, it's an interesting type of book because as you point out, like, I'm not writing about someone. I'm trying to get out of the way. It's not about my opinion of them. Yeah. My North Star with these books is to just be as, for the book to be as useful as possible to the reader. I want the reader on every single page to be like, oh my God, this is a great use of time. I got a highlight on every page. I'm getting so much out of this. I feel like I'm getting personally
Starting point is 01:54:00 mentored by Elon Musk through a few hours of reading about his most valuable and timeless ideas. Right. And I think for those of us in tech, Elon's been interesting for a very long time. And over the last, you know, five, six years, he's become more controversial. But inside tech, he was, before he was a household name, he was the most ambitious person in tech. And nobody knew how that story was going to end, right? He was running on a very thin, tightrope for a really long time with both Tesla and SpaceX. And more recently, people have started, I mean, Mark, Indreason and Brian Armstrong maybe most famously have started asking the question like how does Elon do it?
Starting point is 01:54:40 What is this? Why is he an outlier among outliers? And I wanted to answer that question. And I think this book does that in more ways than I anticipated at the outset, right? Like there was some interesting stuff that everybody kind of knew would come in. There's like the greatest hits. And then there's the back catalog. And then how it all comes together is actually like what's really interesting. Yeah. I remember in. college, someone called me and was like, oh, I heard about this, this entrepreneur named Elon Musk, and he runs two companies, SpaceX and Tesla. And I was like, of course I know about that. I'd learned about it like three months earlier. But it really was a very, a very controversial thing to do.
Starting point is 01:55:24 The timeless wisdom is like, focus, focus, focus. How have you perceived Elon's ability to be like the exception that proves the rule versus a pattern that might actually be more replicable than people think if they just adopt a particular stance in how they leverage what they're capable of to build multiple companies simultaneously. Yeah, there's a couple, there was a period where Jack Dorsey was running two companies. Yeah. A period where Steve Jobs was running two companies. And there's plenty of companies that are collections of meaningfully different companies kind of in one under one name. I think it's kind of hard to extricate, like,
Starting point is 01:56:07 what does run the company mean, really, on a day-to-day basis? And who is around and who's running different functions? Like, Elon running a company probably looks a lot different than Steve Jobs running a company or then Bill Gates running a company or Mark Benioff, right? The motions that he dives deeply into are very different kind of on a per-leader basis. and there's an element of this that like,
Starting point is 01:56:34 Naval points this out, I think it's super interesting. He's like, you are probably working harder on your company than Naval is, or then Elon is working on any one of his companies just because he has this divided attention. So let's just say he's working 80 hours a week, but he's only working 30 hours a week on SpaceX. Like, how is he able to have orders of magnitude more impact in those 30 hours than you're having with your 70?
Starting point is 01:56:58 Well, it is sort of interesting, like maybe, ironic that his main competitor over the last two decades has been Jeff Bezos at Blue Origin, who's also running two companies. And so like, yeah, and retired. Yeah, I mean, now maybe more focused, you know, he's retired. But there was a long time, like a full decade where Jeff Bezos was running Amazon full-time and then, you know, Blue Origin was the half-time or side project. And Elon sort of didn't have a direct like full-time, you know, by the book entrepreneur,
Starting point is 01:57:29 just building a direct competitor in that one space fully focused. So I don't know, maybe that's luck. Maybe things play out differently if there was someone in that space. But it's clearly, it's clearly worked out. We kind of end up conflating like Elon the person. Yeah. Like Elon the core team around him and Elon the symbol, frankly. And especially at this point in his career, he's one of the most leveraged people alive, right?
Starting point is 01:57:55 So we are ascribing to like quote unquote Elon. on what is actually the effort of tens of thousands of engineers and plenty of other employees and fans and supporters. And there's beauty to that, right? Like we are humans, we rally around people kind of better than we do with symbols. But that becomes this rallying, this rallying point for people to organize around the values
Starting point is 01:58:24 exemplified by this person. And I think that's beautiful. and magical and part of the formula. But it does tend to like, if you conflate the conversation about the guy with the conversation about the symbol, you end up in this really weird kind of arguments with people.
Starting point is 01:58:40 You're not even really talking about the same thing. How do you think about the thinking in decades concept? You know, it's something that everyone's Silicon Valley says, oh, you've got to think in decades. And then Elon comes out with something that's like 20, 30, 40 years away. And everyone's like, no, we didn't actually want thinking of decades. I want to know something that's going to happen for sure.
Starting point is 01:58:59 in like five years tops. I'm thinking about this mass driver question. And I'm wondering, like, now that you've, you've written this book, you've studied Elon, like, is this a departure? Is he thinking even farther in the future? Or has he always been thinking around this time horizon? Like, how similar is this crazy mass driver on the moon pitch
Starting point is 01:59:22 compared to previous eras? I think it's difficult to, to predict, as are many things, but if his theory and his acting principle is that the future is arriving ever faster, right? And so things that at our previous growth rate or technology trajectory seemed like they were 30 years away are actually now maybe 10. It is really difficult to adjust for that like recursion factor. Yeah. Yeah, that makes sense. Yeah. Well, where can people find the book? Uh, anywhere you buy books. Amazon, Barnes & Noble.com, Target.
Starting point is 02:00:00 It just came out like yesterday. Are you going to do an audiobook? Yeah, the audiobook's out. I didn't read it. Oh, you got to read it. I'm sorry. You got this. We'll be up with pipes. Put them to work.
Starting point is 02:00:12 Well, Eric Jorgensen, thank you for joining. The book is the book of Elon. You can go find it everywhere books are sold. And we will talk to you soon, Eric. Thank you so much. Appreciate you. To join the show. Let me tell you about Figma.
Starting point is 02:00:25 Agents, meet the canvas. Your AI agents can now create and modify your Figma files with design system context in beta starting today. And our next guests are live here with us in the TBPN Ultrodrome. Thank you so much for taking the time to join us. How are you doing? Please, since this is your first time in the show, introduce yourself for everyone. I am Jenny Jess, co-founder of Peak 6.
Starting point is 02:00:46 Yes. And I'm Matt Holciser. I'm Jenny's husband and also co-founder. Fantastic. Take us back in time. I want to hear the founding story. Founding story. Yeah.
Starting point is 02:00:57 start. We both grew up on the option trading floor of Chicago and New York. And we were at an sort of an infamous options trading firm called O'Connor and Associates. You were both at the same firm. We were both at the same firm, different cities. So super lucky to be trained there when they did their merger acquisition, UBS. Who was in Chicago? I was. Did you ever go to series? Oh, of course. Still go to series. Series is amazing. Yeah. Anyway, it's a bar. It's even kind of modern these days. Oh, yeah. I worked at Citadel in college, and that was the place where we'd go and hang out, and they'd give you, you'd order like a, like a rum and Coke, and it would just be a full glass of rum. It was crazy. That's right. Yeah, it's a really good, greasyy sandwich to go with it. Yeah, yeah, yeah. Really good, good fries. Okay, so you're in Chicago. Yeah, so we're in Chicago. We decided, we started working together. Yeah. What were you trading at the time? Equity options, both of us were. Equity options. Yeah. And then when they did the original Swiss Bank, joined venture, we were part of the team that we were part of the team that. We were. We were part of the team that. We were. We were. We were. We were. We were. We were. We were. We were. We were. We were. We were. Equity. Equity. Equity. We were went to start the OTC derivative desk. So there was just three of us.
Starting point is 02:02:01 There's a gentleman from Goldman who came in. And so we're like, oh, this is cool. We're in our mid-20s starting a business, you know, an entrepreneur. And when things started going really well, and then UBS came in and they were moving to the East Coast, we're like, well, we're not moving. He had actually just come from New York. And my family's in the Midwest. So we're like, we're just, we'll just do that thing again.
Starting point is 02:02:23 So that thing was to partner with a bank. that was our plan A, and do over-the-counter derivatives. It's 28 and a half years later, we've still never done it, but we did invest really early in tech and education. And so we created proprietary options trading firm, which is 28 and a half years old that has never had a losing year. Wow. And it allowed us to self-fund all the things we've done since then.
Starting point is 02:02:51 And what's the secret to such an incredible run with no losing years? Is that risk management? Is that the particular strategy? Like, how does that come together? Because I can't think of another investor who's ever done that. It's unusual, for sure. Go ahead. It's a secret.
Starting point is 02:03:09 I think it tends to be about, like, our approach. Our approach was not to be smarter with our algorithms. It was smarter with our business model. So there are plenty of businesses that haven't had losing years in the last 29 years. They tend to be technology firms that are basically providing a service into the market, which is the approach that we, I mean, we, we talked about ourselves as, uh, Wendy's or Walmart, Walgreens, right? We're merchandisers. Yeah.
Starting point is 02:03:37 Carry inventory and then deliver it to customers. We're not trying to take the, the, we're not disagreeing with customers. We're providing a service. And then on the investment side, what is out further on the risk curve for you? Oof. I mean, I think we've lost money in more ways than anyone you've ever had on this show. Well, collectively. What is the nature of an investment that doesn't pan out?
Starting point is 02:04:03 Is it just, it's high risk and you know that going in? Or, yeah, what's the way? Well, there's a wide range. Obviously, in our trading business, it's really systematic. We have an amazing team. We educate kids right out of school into our model. It's really rare that they would leave and be able to do the same thing because it is about the collective.
Starting point is 02:04:22 But we started a whole bunch of other businesses. of course. So peak sticks today, based on what Eric was saying in your previous interview, it's a company of companies. Okay. So we have started or bought and turned around 15-ish companies at this point. And primarily in the back-end technology space in FinTech, definitely in InsureTech, which is relatively new to us, and edutech.
Starting point is 02:04:48 So those are the biggest risks we're taking. And then fast forward, as we built those businesses over the years, we started an investing side of the business, which is quite large because it's all AI stuff now. And we started early enough, so it grew really fast. We have some doozies. I mean, I don't want to dwell on it. I don't know. We'll refer.
Starting point is 02:05:07 This is a callback to your previous person. In 2008, we had, it was a good year for us, not because we were smart and short the market. Jenny was like, she's like, things are confusing. We should be in cash, and we were. So it's lucky. Well, she was right. The market goes crazy. And then we have a lot of cash.
Starting point is 02:05:27 Everybody starts knocking on your door in the fall. And she's like, well, why don't we do something good for humanity? We'll do electric vehicles. Sure. So we are early. Yeah. So we interview two different people. And we're not investors at this point.
Starting point is 02:05:39 We are traders. Yeah. So it's two different things. We're operators. You don't know for investors. Investors. Yeah. We get two people.
Starting point is 02:05:48 We're going to interview the two companies at the time. Yeah. One is this PayPal guy who's trying to do it. And the other is the guy. who was the chief architect at BMW. The PayPal guy gets on a call with us. With you? With me?
Starting point is 02:06:04 Just to be clear. He was going. Yes, I see what he was going. I mean, if he's listening to this, I don't know if he'll remember, because I think he was stoned out of his mind. It was the worst presentation I've ever heard. Like, this guy's never going to build a car.
Starting point is 02:06:20 It wasn't about cars. It was about the train. It was talking about trains. Trains between now and time from like electro-magnetic trains. Yeah, yeah, yeah. Also be useful. I was like, what the hell are we talking about here? It's supposed to be a business investment.
Starting point is 02:06:33 Yes. I want to hear the business pitch. And the other person comes in buttoned up, right? German engineer. Yep. Amazing. I built these my entire career. 100%.
Starting point is 02:06:44 So we go with that person. Okay. Wow. Nine months later, we find out that the one we invested in when it rains, the cars catch on fire and explode. That's the crazy outside. Yeah, that's not a good business. That's a bad dumb side, yeah.
Starting point is 02:06:59 Yeah, that makes a lot of sense. I think a lot of investors have had to really come around to the other pattern of thinking. I know some investors that, I mean, even on the other side, I know an investor that passed on Tesla, but not because Elon was thinking too futuristic. He was thinking, well, all the cars are going to be self-driving and no one's going to need a car anymore. So if this guy's just building cars, why should I invest in this? at all. And of course, Tesla was going to be the one to do that, but that was too hard to predict. And it just gets very, very hard when you think that far out. So walk me through a deal that is in the wheelhouse. What's the structure? Are you looking for a particular vintage and age, a size of, like,
Starting point is 02:07:43 you know, meat on the bones of the company? And then what are you looking to do? Because there's, when you come into a new company, you can be transforming the business with AI. You can be, you can be, focused on cost reduction, back office rationalization. There's so many different techniques that you can use to drive value. Yeah, I'll start, maybe. I'll start with Peak Six trials. So at its core, we're entrepreneurs, right?
Starting point is 02:08:05 That's what we do. So we're comfortable with that risk. Ironically, it doesn't make us super comfortable doing venture because we're not doing it. So we have to find really special people. We've been lucky in the universe of Peak Six to have some of those special people along the way. We just started something called Peak Six trials,
Starting point is 02:08:21 which is an... Think about entrepreneurs. membership and residence. We have, it's, you know, like previous accelerators, except for that, we have the capital, it's already there. We have the resources, the tech resources, for example, legal compliance, whatever it is, already there. And then we also have the customers. Yeah. Because of Apex FinTech solutions. So that's our back-end tech powers 40 million customers today, so end consumers were B2B. Yeah. So there's a unique opportunity for FinTech and SureTech type of young entrepreneurs who want to do something, that's how we want to make those bets.
Starting point is 02:08:58 That will go into our operating company scenario. And then, I don't know, you want to talk about the investment side where we take, what kind of, what kind of investments are looking for? Yeah, sure. Or even just the story of Apex. I'd love to know, like, how that came into the portfolio, what the process was like, that's, I can tell it's already going to be a good story. Yeah.
Starting point is 02:09:20 So there was a public company called Penson. We owned and operated a brokerage called Options House at the time. This predates wealth from betterment and Robin Hood, etc. And that business custody kept the assets, right, at Penson, along with a million other customers, retail customers. So we're in 2012 at this point. And we get a call from the CEO of the bank. This is the bank that holds our money, calls on a Friday. like, hey, you guys have some money, and could you lend us some money for a little bit?
Starting point is 02:09:58 It would help us a lot. Sure. And I'm like, let me think about, I've got to talk to Jenny. Yeah. She's like, we got to, that's not a good sign. For your listeners or your viewers, if your bank calls you and asks to borrow more money, like that's trouble. So Monday morning, we get a call from the SEC.
Starting point is 02:10:18 see there's fraud, announced fraud at the clearing firm. Wow. And we want you to put $70 million into the business by Friday. Wow. Or we're going to liquidate everybody. And that's everybody in the market. So think pre-generation Robin Hood for context, all those names out there, those middle tier names besides the big names, option south, our firm was one of them.
Starting point is 02:10:42 Sure. They're all going to go. Yeah. So 13 days later, we bought it. Amazing. Yeah. Announce fraud and all. That's wild.
Starting point is 02:10:50 Yeah, yeah, I've heard a number of these stories of like turning around a company when there is, I mean, Strauss-Zellnick sort of did this with Take 2. It's a fantastic turnaround of that business. It feels like an incredible cultural challenge to actually not just clean up the legal documents and make this SEC happy with whatever happened. It's actually a cultural problem sometimes that led the company down that path. That's right. How are you thinking about cultural development generally?
Starting point is 02:11:16 I feel like when I dig into different funds, there's fascinatingly different approaches. You know, the Ray Dalio's recording everything. There's like so many different. But you mentioned that like when you train a new grad, they come out with skills that are uniquely just synergistic with the rest of the firm. And so how do you think about the cultural values that you want to instill in the next generation? They are critical, really difficult in times of COVID and changing work from home and all those things. And as we continue to build new companies, right? So, you know, at our firm that's over 28 years old, they are ingrained.
Starting point is 02:12:03 It is a sense of urgency. It's a work ethic. Like, it's just high. And even when the market is telling you, you know, we ought to be different or nicer or something, like, people are so engaged. it's really fun to be in the markets, so it makes that easy. It's fun to be part of an entrepreneurial culture, so that makes that easy. So how do I, and if you don't fit, it actually, they weed out pretty quickly. We've had that benefit over the years.
Starting point is 02:12:31 But every time we take on a new company, it is a challenge for us to try and integrate or have them stand in their own culture, which is also fine with us. So if we sit at the top and we have CEOs of each of these businesses, they are dependent quite a bit on the peak six core because it's facilitating the financial stuff. It's facilitating the HR stuff. And if they want to sort of ignore that and not join the club, it's a hard road because we've figured out such a rhythm.
Starting point is 02:13:07 When you get in the rhythm, it makes the acceleration go so much faster, the leverage we get with our people with the culture is just really exponential. Yeah, some people refer to it as like you stress, the good type of stress. It's a stressful scenario, but it gives you energy. It doesn't actually drain you. Yeah. And I feel like if people get, you know, the runners high. So running is very stressful for some people, but for some people, it's invigorating.
Starting point is 02:13:33 And I feel like if, you know, being in the market at a tumultuous time gives you more energy during that day, that's something where you'll probably thrive. Yeah, I was going to say taking risk, starting as traders and becoming operators and then investors, like at its core, that trading, that heart and soul of trading and taking risk every day, all day, getting used to it. That isn't in everybody's DNA. It is part of the reason why we like poker so much. We're trying to teach a million girls and women to play poker solely to get these male dominant areas for the women to feel more welcome. But you have to be able to take that risk every day. and the organization thrives on it. Right?
Starting point is 02:14:14 It's a little scary. I know like 10 amazing female venture investors and they're all incredible poker players. They never sit down with them. They would absolutely smoke me. Well, the funny thing is I didn't play all these years. When I started playing in 2019, it was a conversation we had.
Starting point is 02:14:30 It was about our daughter, et cetera. But I realized I was like, wait, I've been playing poker my whole career. Sure. I just didn't know it. It's the closest thing I'd ever seen to options trading. Yeah. So I was like, wait, is this,
Starting point is 02:14:40 what's missing. Because if we get, who cares how people come into the puzzle, the more differentiated their backgrounds are for us, right? If you look at 1997 and he and I were partners, that's why, by the way, we weren't married at the time. We were together 10 years before we did. So making that decision, that was a highly unusual decision to be made. She chased me. I love it. I love it. What are you looking for in a CEO if I want to come work for you and and work for one of your portfolio companies? What does it take to make it as a CEO? I don't think there's any,
Starting point is 02:15:17 like there's no one thing, there's no prescriptive formula. Number one thing we've learned because we've, look, we've dealt with thousands of employees, CEOs, et cetera, invested, I don't, hundreds, not thousands of businesses.
Starting point is 02:15:32 Self-awareness is probably the most important thing because it can get you in trouble. If you think you're really smart, like you, You better be really smart. Poker teaches you a lot of that. That's a good call back there for you. The self-awareness.
Starting point is 02:15:49 Like you control effort. You control attitude. Those two things you really do control. Like it's a hard work, great. You're going to be positive, optimist. But awareness, like, hey, we're the best. Yeah. You know, by the way, these other people aren't that good.
Starting point is 02:16:04 Like, you should think about it. Like, constantly questioning where you're at and being humble. Yeah. Is self-awareness around intelligence the main flaw for CEOs? Or are there CEOs that are overconfident in their deal-making ability, and their emotional intelligence, and their managerial ability, and their ability to public speak and do, there's so many different things.
Starting point is 02:16:28 The CEO is a bundle of traits. I feel like intelligence is obviously super important in making good strategic decisions executing, but there's so much else that goes into actually running a company. I wouldn't say, I would not say lack of confidence is not necessarily an issue. Yeah. Overconfidence is disastrous. Interesting.
Starting point is 02:16:48 Interesting. You get yourself in a lot of trouble because you know for sure that this is going to happen. And when it doesn't, you're in a world of hurt. Yeah. That happens. So what are the signs that you're looking for to suss out if someone is self-actualized in that way, aware of their flaws, aware of their strengths, their weaknesses. How are you interrogating that in an interview?
Starting point is 02:17:15 We hate interviews. Okay. How do you recruit that? It's hard. It's hard. We've actually tried to build tech over the years. We've done all different things to try and figure it out. We try and have, without being inefficient, as long of a process as we can, to see somebody.
Starting point is 02:17:30 So if we can get a student in December for two, two, weeks during their break and see them or we have a women's trading experience that's eight weeks in the summer. Anytime we get an extension of time, if we can, I mean, the CEOs is the hardest. They often come from within for us. Now, some of our CEOs did not. But it is, our hit ratio, I think, on just cold interview making it right, I think is really hard. So then, of course, it's connections and recommendations and all those things. Because you don't know all of the different pieces of the puzzle. I think people get snowed all the time.
Starting point is 02:18:12 Yeah. Do you have a bright line between deal team operating team? Like those who evaluate a great company to join the portfolio versus those who will be going and operating the businesses? We have a very, very small evaluating team. Okay. Like, this is the team. Okay. No, we have some really smart.
Starting point is 02:18:31 There's some lawyers and some analysts in there. Yeah. But at the end of the day, so we don't have outside money. Sure. So it's ours and then our employees who have become partners over the years. So that's who we're investing on behalf. And so, but we are looking for any guidance. We are just, we know we're not the smartest, right?
Starting point is 02:18:51 That's what trading does for you. It humbles you really quickly. So how do we connect? How do we partner with great people on the outside? and then with the best people internally to make a decision. But we're also willing to take probably more risk on average, I would say, with some of these investments. I mean, we're not, you know, on the energy side or on the power side or on that infrastructure side for us is new. But we started early and we try and get smart and try and be surrounded by some smart people.
Starting point is 02:19:16 I want to get to energy that sounds fascinating. I want to first ask about sourcing. Are you close to a lot of investment banks or are you cold calling people saying, I want to buy the company? Like, if you're into the deal team, where are the ideas coming from? Yeah, I'd say, the good ones come from interpersonal relations. Sure. Which is why, like, in the age of AI, and everything's going to be automated, everything. Like, this really matters.
Starting point is 02:19:41 So showing up in a studio where you'll hopefully send us, you know, you'll say, hey, I have an idea for you guys. That's what happens. And vice first, huh? Yeah, of course, of course. I would say that's 99% of it. But it's worked pretty well. That's so interesting. I mean, yeah, we talk to investors across the category. There's some that are doing tons of outbound. They have a price for every company in their CRM. They have an army of deal associates that are getting out there pound on the pavement. There's other folks who, yeah, just wildly different strategies. It's fascinating. Well, for being a very quiet firm for a very long time, it didn't allow us to have what we now realize we probably should have been doing for a while. It's building those relationships.
Starting point is 02:20:24 But it's been quick coming out, like coming out, and building those relationships and figuring out how to make it work. We're more mature doing it. We know what we're looking for. We made a shit ton of mistakes. So, like, you know, it's easy to start, you know, they're not perfect, but they rhyme with the past, right? So we're good at, we're good at saying no, I would say. Yeah. Let's talk about the energy side.
Starting point is 02:20:53 What's interesting there? It's a very broad category. We talked to a founder yesterday who's refining uranium to go into nuclear power plants that won't come online for five years on the good side. Then at the same time, we talked to Chase Lockmiller from Crusoe. He's building data center putting up power plants today. There's so many other pieces of infrastructure. So many, the supply chain is so complicated. Where is the opportunity?
Starting point is 02:21:20 Go ahead. We like Crusoe or investors in Cruz. Oh, really? No way. Oh, yeah. That's amazing. We've got a lot of investments. Okay.
Starting point is 02:21:29 And what is interesting in energy is it tends to be this. There's some individuals or individual companies that are doing some stuff that we see as transformational. Yeah. So everybody's very worried about energy. Yeah. Whatever happens with the war, we don't have any thoughts on that. Yeah, yeah. But assuming that things are peaceful, like, hey, is it going to be nuclear?
Starting point is 02:21:50 Is it going to be solar? Solar, et cetera. Geothermal is really interesting. So we're big investors in a company called Fervo, based in Utah. Yeah. It's your viewers should look it up. Yeah.
Starting point is 02:22:02 It's transformational. And it's today. Today. So it's built. They're going to deliver, I don't know, 500 megs in- Wow. That's serious energy.
Starting point is 02:22:13 That's a 2027. Wow. Okay, yeah, that's enough. That's the average Metacampus right now. Okay. And remember, it's fracking. It's traditional drilling, but not in traditional areas. Okay. So I think more remote areas. Sure. Are there side effects? It's unclear.
Starting point is 02:22:28 I don't think there are necessarily, but maybe there could be some seismic. Yeah, sure. But like, that's super interesting. And the people who are doing that, like, by the way, there's plenty of heat down there. Yeah. It doesn't heat the planet. There's a bunch of physics around that. Sure, sure. But it won't make the planet hotter. Yeah, because it's net zero. So that's a good one. I think there's another company in Utah that we like a lot. We were talking to them earlier. It's a Taurus energy. And that is effectively what you saw in cloud, compute is cloud energy. And so Taurus is a, it's basically a flywheel business, like actually a flywheel. Okay.
Starting point is 02:23:02 Like a physical flywheel. Like a literal flywheel. Except it weighs about 3,500 pounds. Power. Okay. But it spins. Remember, the issue with power is that it's everybody draws at the same time. If you're Snow Basin in Utah and you draw on power to run your tram at the same time
Starting point is 02:23:20 that everybody's, hey, by the way, Open AI is going to run one of their loops. Then you're going to end up drawing tons of power, and that's expensive for the grid. So what Nate has done and his team at Taurus is solve. They're a balancer. The load balance. It's the load balance. And you realize there's actually quite a bit of power. How you actually balance the power is the hard part, and he's solved it.
Starting point is 02:23:46 So they are operating today. We talked to him earlier. He's in a bunch of different states, and he's coming to a state near you. Yeah, I love it. Well, tell me more about Peak Six Trials. Where can people get started? How do people apply or join?
Starting point is 02:24:04 Yeah, so Peak6Trials.com. Okay. And we're looking for entrepreneurs who have ideas. Cool. And everything else is sort of there. You don't have to go and raise money. You have to spend time doing that. Think about the things that where your specialty is is your idea.
Starting point is 02:24:19 Yeah. Right? This is a place with AI. Like, we can do a bunch of stuff around you. Yeah. And interestingly, like with Apex, right, we have these 40 million customers. Yeah. They might want your product.
Starting point is 02:24:29 Yeah. And if they don't want your product, that's also really good news. So we short circuit all these things that take to say, like, is this a good idea or not? You don't have to worry about the capital. You don't have to worry about paying your rent. We actually pay your salary. No way. Yeah.
Starting point is 02:24:42 Yeah. So it's really nicely packaged for someone. I wish we had it at the time. it would have made me feel better. Maybe we were better off because we took so much risk, you never know. But the balance here is we want the people who bring the ideas, and we help support and build it, ultimately to own the majority of the thing, not for us to own the majority of things.
Starting point is 02:25:03 So the way we've structured the deals are really creative, I think, and different than the marketplace is seen so far. So finding those people, right, those young entrepreneurs, or they may not be so young entrepreneurs. They can be anywhere. But it's really, I mean, I think it's super broad. Yeah. What the fintech sort of space is.
Starting point is 02:25:24 Like, everything's money. Every large CPG company who has a bunch of customers, there's some money product that exists or could exist in that ecosystem. Yeah. So there's a lot of ideas, I think, that are out there. We're going to pick 12 to 15 for the first year. And we're going to see what we can do and see what we can pump through. That's great.
Starting point is 02:25:44 Last question. What's the best way? I'm terrible at poker. what's the best way for me to learn and get better? Well, we have amazing teachers around the country, which is kind of crazy. We're like at 28 teachers. We have taught it like 360 companies.
Starting point is 02:25:58 So you can actually bring us to your company. Oh, really? The banks, the technology firms, the law firms, yes. I think they might like it. It's been wild how people have picked it up, right? Because first of all, we're not playing for money. We're actually teaching because these are people who know nothing. But, you know, 94% of poker players,
Starting point is 02:26:17 on the planet are men. So, yeah, it's really extreme. So, I mean, after a couple hundred years of this game coming around, it's probably time for women to be doing this. Yeah. We're in 70 countries. We're in rural villages in Kenya, for example. So we are super quick, turnkey events, best events that are on the-Pokerpower.com. Yeah, it's pokerpower.com. I love it. Yeah. Well, thank you both for taking the time to come chat with us. Yeah, of course. We will close the show here on This camera, leave us five stars on Apple Podcasts and Spotify. We'll be live tomorrow at 11 a.m. Pacific Sharp. Sign up for our newsletter at TBPN.com and we'll see you tomorrow. Goodbye.
Starting point is 02:27:00 Thank you.

There aren't comments yet for this episode. Click on any sentence in the transcript to leave a comment.