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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
You're watching TBPN. Today is Wednesday, 03/25/2026. We are live from the TBPN Ultra. The temple of technology, the fortress of finance, the
Speaker 2:capital Finance.
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Speaker 1:We have a great show for you today, folks. We got Mike from Ark Prize coming on. The noopinator. He did it. He did it.
Speaker 1:We'll talk about this later. We have Nathan, my buddy from Air Street Capital, Rohin Jorgenson, giving us an update on what's happening in San Francisco in the housing market. Eric Jorgenson, the 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 to tuning in for tuning in today. Linear, of course, is the system for modern software development.
Speaker 1:70% of enterprise works based on Linear are using agents. So there's been a debate. Truth bomb dropped by Emil Michael. He says, forgiving 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 gonna have to put on the steel helmet for this one because this is wading into dangerous territory defending benchmark.
Speaker 1:But my question is, how close are we to actually being able to to forgive Benchmark? When is the right time? It's been a decade. Obviously, the the drama between Benchmark and Travis Kalanick was was awful. I think everyone's against what happened.
Speaker 1:But the question is like is like what is a what is a venture firm? It is its partnership. If the partnership turns over, at some point, like, is it a new is it a new team? Is it do do you get a second shot? Can you can you actually change change the reputation?
Speaker 1:And so believe me, like I I get the benchmark criticism. Like Travis is truly a generational entrepreneur and was on such an amazing run. Right? So he was attacked.
Speaker 2:Yeah. Jason Jason from Saster was reacting to our interview Yeah. With 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.
Speaker 1:Yes. So our friend of the show, Owen McCabe over at in.aiandintercom, said, Waymo is superior to Uber in literally every way. This was a year ago in March 25. Actually, to the day, a year ago, he said this. In Waymo is superior to Uber in literally every way that matters to consumers, smoother, safer, more reliable, no chatty, weird, rude drivers, private, quiet.
Speaker 1:Self driving car services are going to dominate their human driver incumbents. And OWN says TBT when I think that's throwback two. Right? Throwback two when Benchmark pushed Travis out of Uber and canned the self driving division that he started literally ten years ago. And so this is this is what's so so tricky about this is that, you know, Uber survived.
Speaker 1:It's a 150,000,000,000 market cap. It's bigger than when Travis was ousted. But getting a two x over a decade is not what I think people were expecting from Uber under Travis's leadership. It's and Lyft has fallen to just 5,000,000,000. Like, he won the capital war and Dara's done a great job managing the business.
Speaker 1: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.
Speaker 2:Yeah. And the that is the business back right now, at least from a valuation standpoint, is this big question. Yeah. Right? Around self driving.
Speaker 2:Yeah. How you know, and and Dara has 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 So not
Speaker 1:the same as like having, you know, having
Speaker 3:Yeah.
Speaker 2:Developed their own internal Totally. IP and product starting a decade ago Yeah. And seeing where that would have been Yeah. By now is is just It's rough. Hard to think about.
Speaker 1:Yeah. And so Uber is valued at $1.50 today, something like that. Waymo was valued in February at $126,000,000,000. And so, yes, Waymo has been working on self driving longer but you have to imagine that there's another 50,000,000,000 of market cap
Speaker 2:if you have a serious play. What would Waymo be valued if Travis was the CEO? Yeah. That you would get some type of Travis premium on it? Oh.
Speaker 2:Just Yeah. Just the market would be would would
Speaker 1:say Totally. Totally. Totally. Totally.
Speaker 2:You have this sort of Yeah. One of one entrepreneur Yeah. In the seat.
Speaker 1:A 100%. And and just to sort of recap where things stand, I mean, Shervin Peshawar been 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. Chervin's been on the show.
Speaker 1:Emil Michael's been on the show. We've we've we've talked to a number of people that have been around this 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 played out, really. So Sherman said, in my opinion, Gurley single handedly destroyed hundreds of billions in value.
Speaker 1:Travis and Emile staying in charge of Uber would have led to a Tesla sized win, 500,000,000,000 plus, for everyone including Benchmark's LPs. He nuked decades of Benchmark's reputation with founders. The market has spoken and 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, Theseus is the mythical king of the city of Athens.
Speaker 1:He rescues the children of Athens from King Minos after slaying the Minotaur, 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, is it still the ship of Theseus?
Speaker 1:If it was no longer the same, when had it ceased existing as the original ship? So some people might say fiftyfifty. Some people might say, yes, it is. 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. There isn't like a it's a paradox.
Speaker 1:There is no right answer. It's a philosophical question. But it applies, I think, to Benchmark because back when Kalanick resigned as Uber's CEO on 06/20/2017, after investor pressure that included Benchmark, On that exact date, Benchmark's equal GP roster was Bill Gurley, Eric Vistra, Matt Koehler, Mitch Lasky, Peter Fenton, Sarah Tavill. Today, the partnership has changed dramatically. The only two that remain are Peter and Eric.
Speaker 1:And you have Chetan, Ev Randall, and Jack Altman who are new to the partnership post the Uber scandal. And so it's not a bullshit 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
Speaker 3:Yeah.
Speaker 2:Right now right now, 40% of the 40% of the partnership was there.
Speaker 1:33%. Oh, I mean, I guess two out of the five. Yeah.
Speaker 2:Two out
Speaker 1:the Two out five. Because they've added three, but only one third of the original partnership remains. The
Speaker 2:question is did Chetan, Everett, and Jack come in and as part of the interview process say like, you're absolutely
Speaker 4:absolutely right.
Speaker 1:Right. I mean, to to defend Evan,
Speaker 2:he's gonna show good two two out of the three.
Speaker 1:I I Evan had just graduated from college. Like, he he was truly, like, not involved in the Uber scandal and yet, you know, people will visit it upon him.
Speaker 2:Knowing Everett and Yeah. Jack I'm sure I'm sure during the interview process, they were like, I've I've you know, the storied firm
Speaker 5:Yeah.
Speaker 2:I'm excited to join, but we can never do
Speaker 1:Yeah.
Speaker 3:We can never
Speaker 2:do anything like that again. And so and so one one question that's worth asking is like is like is the firm that did this Yeah. And ultimately, you know, stained this this storied Yeah. Brand and has certainly suffered the consequences. Right?
Speaker 2:They've put up an, you know, incredible returns Yeah. 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. Yeah. And so, they have they I would say, you know, Emil, Michael and others are upset that they're doing great deals Yeah.
Speaker 2:At all. Yeah. But I think it is The 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 what decision are they more or less likely to make? Right? I would I would argue like, they are probably less likely to
Speaker 1:I would think so.
Speaker 2:Go against the founder given given how this entire situation has played out.
Speaker 1:Yeah. Yeah. The only the only steel man and this is this needs the full steel helmet because it's so hard to steel 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.
Speaker 1: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 $1,000,000,000. They were all going to be billionaires from this one deal, 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 $24.07 hit piece pile stack up and you got Mike Isaac, you know bloodhounded on at the New York Times writing books that turn into movies like it's getting rough.
Speaker 1:It's getting rough.
Speaker 2:Mike Isaac's at your door.
Speaker 1:Yeah. Mike Isaac'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 10,000,000, and I can't I can't do that. I can't do that. And so they freak out, and they're like, we gotta salvage this thing.
Speaker 1:We gotta just push it out in the public markets. We gotta get out of this name. And so they basically just it's just too nerve racking. And yeah, it's not a strong steel man. But I think I think that's a little bit more of what happened than than like taking a stand on like, oh, like this particular thing that happened was so egregious.
Speaker 1:It was more just like, okay. Like, wow. All my money, like 99% of my net worth is in this asset, 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.
Speaker 1:The narrative is totally flipping. There's a boycott Uber campaign, like Yeah. And everyone's like, oh, like, what's going on? I got to get out of this. I I I I got to salvage this.
Speaker 1:And I think that was maybe more of the underpinning than, 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, know, ship to DC is processed. Maybe it happens. I don't know.
Speaker 1:Would Deli and accept that argument? Probably not. Would Emil? Probably not. But they're not making it any easier with the Manus investment either because the like like there was a world where it was like, okay, yeah, the Uber thing happened a decade ago.
Speaker 1:The partnership is basically entirely new and they're focused on
Speaker 2:But it's some But it's not there yet. Yes. It's just not there yet.
Speaker 1:It's not there yet. But I think you
Speaker 2:can rewrite this in five years.
Speaker 1:Yeah. You yeah. You made this point that this is it's too early to call this, but But that's directional.
Speaker 2:Given that the firm is still is still putting up great returns. Yeah. They've gotten to a bunch of great companies Yeah. Over the last five years.
Speaker 3:Yeah.
Speaker 2:I think we are on on a path to the Yeah. To the to the Benchmark. Well, yeah, Benchmark's are the venture ship of Theseus.
Speaker 1: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 for a venture capital firm. Some some have dozens of partners. But different strategy, and we will see where it goes.
Speaker 1:Anyway, let me tell you about AppLovin'. Profitable advertising is easy with axon.ai. Get access to over 1,000,000,000 daily active users and grow your business today. And let me also tell you about Lambda. Lambda is the superintelligence cloud building AI supercomputers for training and inference that scale from one GPU to hundreds of thousands.
Speaker 1:So Sora, rest in peace Sora. The app is leaving.
Speaker 2:Ev is in the chest.
Speaker 1:There he
Speaker 2:is. Class of 17 represent.
Speaker 1:Yes. Yes. Ev was Ev was chugging beers while Uber is getting ousted. Do not visit the the sins of the father on the son. That's what I would say.
Speaker 1:Ev not guilty.
Speaker 2:Ev was Ev was a boulder.
Speaker 1:Yeah. He was hanging out. Was What happened?
Speaker 2:See senior year? What happened? I I
Speaker 1:I think I think I think deserves a fair shake and should not and should not have to bear the bear the cross from
Speaker 2:The question, the real question Yeah. Do do Ev and Jack pull a benchmark and force out Oh. The original partners?
Speaker 1:They don't have
Speaker 2:the legal control to do so, but neither did they during the Callanx.
Speaker 1:At this point, Ev is probably already getting getting calls from Sequoia to come be the senior steward, you know. He's he's he's 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
Speaker 2:App Millions of people have made content on the app. Yes. Perhaps they'll leave it running Yes. Some amount of time to be
Speaker 1:There's a phase out Excellent and now it is is going out. And there's a I have a bunch of takes on this. Obviously, is not the end of video creation for OpenAI. This will be rolled into ChatGPT, I imagine. Tyler, Hodge put it well, bullish.
Speaker 1:Killing products quickly is hard. Almost no one can do it. It's a good sign for OpenAI. They're consolidating. In in many ways, it's like last week you heard about like the red the 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.
Speaker 1:Like a single app that we're we're gonna push everything together. And also I just I've I've enjoyed making some videos in Sora. 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.
Speaker 1:Let's see what Dax said. It's lame to see all the people saying, I called it. I knew Sora wouldn't work. Yeah. Duh.
Speaker 1:Because everyone thought thought that 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 100 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 this quote of like people saying, I called it.
Speaker 1: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 1. We had the slop versus farming debate. I was really on a tear back then.
Speaker 1: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.
Speaker 1:So between Google DeepMind, Meta Superintelligence, OpenAI, now have three different variations on AI video products, each met with slightly different responses. So the, yeah, the the interesting thing here is that, like, Google has been, like, charging ahead, launching it. It's in it's in real it's in Shorts, and that's just been, like, not a story at all. What was interesting was that the 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.
Speaker 2:Yeah.
Speaker 1:That was it was like
Speaker 2:was it was like a entertainment doom loop. Exactly. You you could imagine Exactly. It just getting so good at generating the next thing that you would wanna see better than even a billion humans on Instagram Yes. Could do.
Speaker 2:And that's not what we've seen
Speaker 3:Yes.
Speaker 2:So far.
Speaker 1: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 a 100%.
Speaker 1:Nowhere near it. Like probably 5% of the text that I read is LLM
Speaker 2:I mean, we should actually revisit how we were processing it during launch when it was, you know, rocketing.
Speaker 1:We should just throw on that three hour stream and just watch them react to how how our
Speaker 2:teams
Speaker 1:were that day.
Speaker 2: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 seed a network Yeah. With this. There's all this, you know, novel Yeah.
Speaker 2:Content. They had they had allowing creators and Yeah. You know, people like Sam to allow people to use their their IP. Yeah. It was very very well executed launch.
Speaker 2:But even from the beginning, it was like, okay. Obviously, cool creative tool. Yep. It's a totally different ball. You know, this like come for the tool, stay for the network has been like an enduring It's
Speaker 1:Chris Dixon.
Speaker 2:Strategy. Right? Chris Dixon probably wrote that in like 2014 Yeah. Maybe or like a long time ago. Over 10 over ten years ago.
Speaker 2:Yeah. But just because you build a tool that is attached to a network, like that jump is just really, really, really, really tough.
Speaker 1:Especially when there are three or four, 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 like Instagram just had better support for images than Facebook did. And then Vine had support for video literally before Instagram.
Speaker 1:So Instagram, it was like, I have a video on my phone. It's cool. I want to share it.
Speaker 3:Yeah.
Speaker 1:Sharing it to Instagram was not possible. Yeah. Now on day one, you generate an AI video. You want to share it, you can share it on TikTok.
Speaker 2:Yeah. It's just being sent in. If you create if you created an amazing video on Yeah. On Sora what is the most logical thing to do if you're a creator and you want reach? Post it to Instagram.
Speaker 1:Yep. There's just Exactly.
Speaker 2:Naturally, there's billions of people there. Yeah. There there were millions of people on Sora Yeah. And a lot of energy and momentum.
Speaker 1: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, show putting up incredible numbers on TikTok for, Fruit Love Island, I believe it's called. 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 we we should talk to the person that's 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, you know, going to a single Gen AI app.
Speaker 1:I imagine that they have a whole pipeline of of, like, 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, 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 found the right product market fit for AI generated content. But it's not overnight.
Speaker 1: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.
Speaker 2:Yeah. It's interesting to think about Google's strategy with with video. Even even Google was like, we cannot operate this for free at scale. $150
Speaker 1:a month. I No.
Speaker 2:That was the that was the discounted rate.
Speaker 1:Oh, I think I meant 500 a month.
Speaker 2:Yeah. Was it was like an entry to start, it was like $250 a month. And it was And then it
Speaker 1:brutally weight limited. Like Yeah. Even even with
Speaker 2:we were we were laughing at this because I
Speaker 1:think three a day.
Speaker 2:I remember we'd be like at the gym in the morning, you would fire off a couple prompts
Speaker 1:Yeah.
Speaker 2:And and then you were like, rate limit.
Speaker 1:Hope I got it right.
Speaker 2:Yeah. I hope I wouldn't get it right. Then you're rate limited and you're like, wait, I'm rate limited on a on a
Speaker 1:Two fifty.
Speaker 2:$250 plan that's gonna jump to 500. You're probably paying gotta check the rate.
Speaker 3:Yeah. I Check check our rate.
Speaker 1:I saw it.
Speaker 2:It's probably paying 500 a month still.
Speaker 1:No. Seriously. And and that and that And that's Google with all this data flow. Literally, I understand.
Speaker 2:Insane data advantage with YouTube.
Speaker 1:And and that let me tell you. Rate limits kill retention. Like, nothing nothing is worse. If you're in Instagram, the endless scroll exists. TikTok, you can you can scroll endlessly.
Speaker 1:You can use the imagine if TikTok was, like, after five minutes, you have to close the app and come back in twenty 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 three where you'd fire off a prompt and it would be like, okay, come back in a couple minutes. Gonna take me a while to cook.
Speaker 1:And then and then you fire off five and it's like, okay, no more for today. Like Yeah. And then and then you the next day happens and you forget about it and you and you go on something else. So clearly, the compute constraints are are immense and there's just so much more value value that can come from enterprise and can come from deep research and so many of the other models that are immediately economically valued like cogen, like enterprise workflows. And it's maybe more boring and less viral and less controversial, but it's it's where the compute needs to go.
Speaker 1:And so I think you're gonna see the chips be moved around inside of all the labs to like, compute will find the most optimal output. Like, the tokens Yeah. Of the most value will always be the ones that it flow 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 as where we are in terms of knowledge retrieval, where we are in terms of cogen.
Speaker 1:It's just way more valuable. Anyway, let me tell you about Okta. Okta 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.
Speaker 1: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 with Cisco. Market clearing order inbound.
Speaker 2:You said What did I say? September, people overestimate how much brain rot happens in a year and underestimate how much brain rot happens in a decade. Yes. Yes. We're still
Speaker 1:I mean I'm using brain rot pejoratively there but 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, a like, zero it was 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, oh yeah, I'm actually into that. Like people are into cartoons and people are into CGI movies and superhero movies.
Speaker 1:Some people will be into it. Some people will never like it. Some people will always say, want a black and white film from the forties. That's what I wanna watch. And and and these rollouts, the diffusion of this stuff will happen.
Speaker 1:Should we revisit one of the Davidson says What what is this?
Speaker 2:Y'all are worried about the wrong Open Claw.
Speaker 5:This is a good post.
Speaker 2:This is the Open Claw that that Ev Randall was worried about in 2017. He was not he was not thinking about
Speaker 1:Was was White Claw invented in 2017? When did White Claw get founded? That's a great that's a great I I feel like it it really took off. It had a fast take off.
Speaker 2:Yeah. 2016.
Speaker 1:2016? Okay.
Speaker 2:Chance he was an early adopter.
Speaker 5:He might
Speaker 1:have been an open of Open Claw. It truly was open I'm calling it Open Claw now. 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 Sentry.
Speaker 1:Sentry shows developers what's broken, helps them fix it fast. That's why a 150,000 organizations use it to keep their apps working. I got a story for you, Jorgenson. 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. I'm kidding about this.
Speaker 1:The the I 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. Like
Speaker 2:Billy Bowman.
Speaker 1:Billy Bowman. I don't know. I I I'll I'll send it into the to the chat so they can pull it up. Let me see. Production.
Speaker 1:Here we go. But anyway, it is a it is a remarkable story because Fiverr is running a 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 we can pull up either my picture or we can pull up
Speaker 2:I'll just pull up this video from KTLA five.
Speaker 1:KTLA five had a video breaking down what's going on. 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 Labelbox, RL environments, voice robotics, evals, and expert human data. Labelbox is the data factory behind the world's leading AI teams. So, let's pull up the KTLA five report about AI coming for Hollywood, the mysterious sign
Speaker 6:along Underneath the 100 a logo for Fiverr and a search box that says, find the best AI directors. It's a brash, bold statement AI.
Speaker 1:Brash, bold statement.
Speaker 6:Coming for
Speaker 3:for
Speaker 6:Fiverr 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.
Speaker 6: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 slowly or 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.
Speaker 2:I
Speaker 1:was wondering. It's causing accidents. Yeah.
Speaker 6:Interesting. AI director. Yeah.
Speaker 1:So it's
Speaker 6:basically someone who puts the prompt into the machine and
Speaker 1:chooses This is elite.
Speaker 6:Is Fiverr gonna page
Speaker 2:We just put the $100 in box, buddy.
Speaker 6:Fender bender That's a great question. Yeah.
Speaker 1:Yeah. Can they be held liable for such a distracting sign? I didn't
Speaker 6:You know, the air companies are flush with money. Whether or not it is a bubble like you can debate
Speaker 1:about because Fiverr is not one of those companies.
Speaker 6:More of
Speaker 1:a state
Speaker 2:KTLA KTLA five is not prepared for it not to be a bubble.
Speaker 1:So Fiverr's market cap now is $560,000,000, and that's down about 95 percent over the last five years.
Speaker 2:Where are you seeing that? I'm seeing 350.
Speaker 1:Sorry. I yeah. 359. What did I say?
Speaker 2:500.
Speaker 1:Oh, sorry. So it's a $360,000,000 company today, down 95% from from five years ago. It started selling off in 2021 sort of pre chat GPT. So I think the AI narrative might be a little bit overblown there. It did IPO around this price.
Speaker 1:It was a $700,000,000 IPO, I think, maybe a billion dollars. It went through a massive boom during COVID and then 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
Speaker 2:AI is very very good at $5 creative work. Exactly. $25. Obviously, the prices go well beyond Yeah. $5 since since since the early days.
Speaker 2:But in terms of the kind of projects that I always use Fiverr for AI, just one shots,
Speaker 1:all And of the nature of Fiverr is like you have to define your task in a prompt. Yeah. It's not it's not, oh, have like a long conversation, get drinks with somebody.
Speaker 2:Yeah. Was often the bottle. Yeah. Totally. It was like, okay.
Speaker 2:I need to do this task. Yeah. Because I I need like Yeah. Ten minutes to like properly Totally. Totally.
Speaker 2:All these things. Yeah. It's honestly way more time than you spend prompting normally because with prompting, you're just like, I'll just try it
Speaker 1:a few times.
Speaker 7:Bunch of times.
Speaker 2:Kind of iterate.
Speaker 1:Hit my rate limits and then fire back up. Yeah. I mean, it was always a bottleneck. I remember as an entrepreneur, found out about Fiverr and I was like, this is amazing. Can get random stuff done for $5.
Speaker 1:But the time commitment, actually finding the right person, making sure the reviews are good, it it wound up being like hours of work. And if you have a consistent flow, you're better off just hiring a person. So Yeah. The the so they got kind of squeezed in the
Speaker 2:middle Yeah. The market is is not excited about Fiverr right now. Yeah. They're being valued basically at four times EBITDA.
Speaker 1:Okay.
Speaker 2:Yeah. And so, yeah.
Speaker 1:But this is an interesting pivot for them. They're basically saying that you can come to us to hire someone who has all the tooling set up to actually sit there and and sort of, you know, nanny all the AI models because it is a hassle. Like you as you described with me and vo3, I was sitting there like, okay, fire off four prompts then I go back. Like, it's way better if you're on the API and you have Higgs field wired up and you have, you know, RunwayML and you have access to the Chinese model Cdance 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, but it takes time and it's a hassle and it's more of a professional job.
Speaker 1:It's not actually at a
Speaker 2:warm Here's comp the main problem with the campaign
Speaker 1:Yes.
Speaker 2:Is that Billy Bowman Yeah. Is a real person Okay. With his own website Okay. With his own Instagram.
Speaker 5:Oh, so
Speaker 1:You can
Speaker 2:just go and reach out to him. He's Which is interesting because like the primary issue with with these labor marketplaces like Fiverr Yeah. Is disintermediation. Mhmm. If you if if a business hires somebody on Fiverr and has an amazing experience, eventually, they're just gonna go direct because they build up a lot of trust
Speaker 1:Mhmm.
Speaker 2:And it's very different than 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 that that that the Fiverrs and the Upworks of the world and and there's been a bunch of other, like, engineering focused marketplaces just have never reached, insane scale Yeah. Like Uber is because of the disintermediation. Yeah. And this campaign is effectively an ad for Billy Bowman Mhmm.
Speaker 2:Where you could just go higher today.
Speaker 1:Yeah. Disengagement has always been a problem on these platforms. Anyway, let's move on. Let me but first, let me tell you about fin.ai, the number one AI agent for customer service. If you want AI to handle your customer support, go to fin.ai.
Speaker 1:And let me also tell you about the New York Stock Exchange. Wanna 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? A lot of people were wondering why this was happening.
Speaker 1: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 economy seats. We gotta pull this up. United Airlines says the entire row is all yours.
Speaker 1:Welcome to the United Relax Row. Three adjacent United Economy seats with adjustable leg rests 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. If you're traveling with kids, a plushie too. United Relax Row will be available starting next year on more than 200 of the seven eighty sevens and seven seventy sevens, each with up to 12 of these brand new rows.
Speaker 1:So what do you think, Jorgenson? Is this the way? I was telling Tyler Cosgrove who is out of the studio today. He's in Washington DC. He's got a demo this.
Speaker 1: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.
Speaker 2:United has pretty good pace. Okay. But they've been quick to
Speaker 1:So you think Tyler could get on this tomorrow or today? He's going to the airport today.
Speaker 2:I think I think if Tyler's resourceful enough, could just if he ended up in a row Yeah. Two empty seats next to him, he could just figure out a way to detach the armrest Okay. Blocking this. Yeah. And just kinda kinda build your own.
Speaker 2:Yeah. He might They might have to land the plane and arrest him. Yeah. But potentially worth the risk.
Speaker 1:He could also he could also potentially negotiate with whoever's sitting next to him. Say, hey, you go and spend the entire flight in the lavatory. And in exchange, I will vibe code you a sloppy app of which I don't understand what programming language is used.
Speaker 2:I'll trade you an app for your seat.
Speaker 1: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 this is too good. No.
Speaker 1:I'm sorry.
Speaker 2:Brian Peterson says now we just need to put stairs on the food drink carts so you can climb over the top of them to get to the bathroom instead of holding. Yeah. This just this just feels like this just feels very, very chaotic. But is wild. It's good.
Speaker 1:I don't know. Starlink, a relaxed row, a dream. I I think that this could be a good option. United built a product that everyone who has been who has ever been on a plane wanted says John Collison.
Speaker 2:John, you need to work on fixing Bombardier's stock price.
Speaker 1:I don't think it's related. Oh, apparently Air New Zealand launched this in 2010.
Speaker 2:I wouldn't No. Is related because he he should he should help them build out their pipeline.
Speaker 1:Well, he's he's just pumping his bags because he owns a property in Ireland. How do you get there? You gotta fly on United. So, know, one hand washes the other on this. He's he's he's talking his own book.
Speaker 1:No. Just kidding. Let me tell you about console.com. Console builds AI agents that automate 70% of IT, HR, and finance support, giving employees instant resolution for access requests and password resets. And let me also tell you about Railway.
Speaker 1: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.
Speaker 2:And Carter says if you say no to pretzels, the flight attendant should give you something called a coin of restraint. While worth nothing now, these coins will play a major role
Speaker 1: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 Cybertruck rear bench has three seats of ISOFIX attachments and is wide enough to fit three child seats or three adults. So there's been a big debate on the ISOFIX attachments.
Speaker 1: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
Speaker 7:that you have to have a
Speaker 1: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 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 Regulation
Speaker 2:killed the birth rate.
Speaker 1:People people actually say this. People say that that child seats have saved like like a million lives but then they've stopped ten million from being born. They they they they talk about the relative exchange ratios. I haven't really dug into 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.
Speaker 1:The Model x came with a third row and there was and in China, they actually sell a Model y l, which is a long wheel based version of the Model y. I hope they bring that
Speaker 2:People to the are saying make a minivan, Elon. Elon says something way cooler than a minivan is coming.
Speaker 1:What do you think it is?
Speaker 2:And people are speculating. Garcia here.
Speaker 1:I think it might be a data center. Test. Think you might be like there's another data center coming.
Speaker 2:Chip
Speaker 1:Yeah. Chip fab. It's like you You're
Speaker 2:gonna be able I'm gonna end and Texas is gonna change the child labor law
Speaker 1:Yeah.
Speaker 2:So that instead of worrying about bringing your kids around
Speaker 1:complain Yeah. Just go work in
Speaker 2:the No. They're in the fab.
Speaker 1:They're in the fab.
Speaker 2:Clean room.
Speaker 1:They're in the clean room.
Speaker 2:They're fully suited up.
Speaker 1:Suited up. Yeah.
Speaker 2:They're making chips. But People are speculating. This is very cool. Love this. Has been amazing for car enthusiasts to create basically their own concept cars.
Speaker 2:These look very, very cool.
Speaker 1:We were talking about
Speaker 2:I mean, it's funny because
Speaker 1:it's like
Speaker 2:make a Tesla that look make a Tesla version of the Rivian. Yeah. Okay. Because it looks exactly like it. But let's let's get into some of the speculations.
Speaker 2:So
Speaker 1:Okay. What what do people think?
Speaker 2:Our Cyan Bannister says an RV. That could be fun. Arthur McWatter says, I can't wait for the next Roadster unveil. Elon was teasing. It was on Joe Rogan, right?
Speaker 2:Yeah. This concept of maybe it'll fly. Yeah. And I think what Elon could be could be getting at is picture picture a Roadster.
Speaker 4:Mhmm.
Speaker 2:Not a great family car. Mhmm. Hard to put kids in a in a sports car. Yeah. Some of them you technically can, but it's so uncomfortable and kind of chaotic, very few people would.
Speaker 2:Yeah. And I think what we could see is the Roadster comes with five kind of like, you know, that theory collaborative combat aircraft from Yes. What if it comes with like up to five little mini Roadsters Okay. Roadsters
Speaker 1:Okay.
Speaker 2:That can that are just trained to autopilot behind the primary Roadster. So you can be in your sports car Yeah. And then however many kids you have are in the mini drones
Speaker 1:Oh, I like
Speaker 2:that. Following. That'd fun.
Speaker 1:And a Chinook heavy lift helicopter with two massive rotors that can lift your Roadster off the off the ground? Yes. Technically a flying car then.
Speaker 2:Yes. Anyway,
Speaker 1:let me tell you about Phantom Cash. Fund your wallet without exchanges or middleman and spend with the Phantom card. I have a question for you, Jorgenson. Are you are you running the new AI model? It's on co work.
Speaker 1:It's literally on Copilot. You can probably find it on Codex. Dude, it's on co author. It's a cosign exclusive. It's on cocaine.
Speaker 7:You can run it on cocaine.
Speaker 1:You can literally go to cocaine and run it. A great Powerful. Copy pasta. This is one of the funniest funniest formats. But yes, the war for copilot and co work is heating up.
Speaker 1:We gotta find a new term, think. People have
Speaker 2:been really really fighting Yeah. Microsoft, they should just name it Coco.
Speaker 1:Coco.
Speaker 2:Microsoft Copilot Cowork. Yeah. It's just Coco.
Speaker 1:Coco would be good. There's a few different 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 name space. I have been a fan of of, you know, the the the the codexes and co works and copilots. Those feel more collaborative to me and they feel more like tools than the bards and the and the Siris and the Alexas and the Rufus and the Sparkys.
Speaker 1:Like, that that's just a different vibe. I think that if we're living in a world where people are gonna form, you know, strong relationships with these tools, Introducing them truly as tools Yeah. Is probably
Speaker 2:Let's see what's going on with QVC. Okay. Let's pull up this video.
Speaker 1:And we also have one of our guests joining early at eleven
Speaker 2:No. He's he's he's gonna be joining he'll be ready to join in an in an hour.
Speaker 1:Are you sure?
Speaker 7:Yeah. Okay.
Speaker 3:Let's chat with some production
Speaker 2:because I've already texted. Okay. Cool. We'll continue for the next Okay. Fifteen minutes.
Speaker 1:Fantastic. Well, take us through the next story. What do you want?
Speaker 2:Q River says QVC basically reinvented live streaming decades. Invented live streaming decades ago. Ghost twenty four seven they invented live TV. Ghost twenty four seven, a good eighty percent of the show is just the host going on long personal digressions. People watch it as background, heavy parasocial element.
Speaker 2:Hosts know the callers. 95% are repeat buyers. It's a 100% Twitch for grandmas. Let's pull up QVC.
Speaker 8:And with the sub rings
Speaker 4:I wanted to tell you that I got that peasant blouse with the tassels.
Speaker 7:Yes.
Speaker 4:And I used to wear the tassels on my pasties. Do you know what pasties are?
Speaker 8:This is Okay.
Speaker 4:Ridiculous. What what pasties are?
Speaker 8:Yes. Let me I'm gonna do Okay.
Speaker 4:Well, I
Speaker 2:have to
Speaker 1:go and write this. Move on.
Speaker 2:We're moving on.
Speaker 1:Let me tell you about 11 labs. Build intelligent real time conversational agents. Reimagine human technology interaction with 11 labs. And let me also tell you about Gemini 3.1 pro. We are gonna deep dive Arc AGI today and Gemini 3.1 Pro has done very, very well.
Speaker 1: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 projects to life.
Speaker 2:SpaceX aims to file IPO as soon as this week.
Speaker 1:Yes. This is
Speaker 2:a big Everyone is excited for the s one. Particularly, I think people will be focused on x AI Yeah. What they have going on. I think that
Speaker 1:think they gonna have to break it out in the in the s one?
Speaker 2:I would
Speaker 1:assume This might be first time we actually see the economics of inference, the economics of Foundation Lab even though, yes, they are at a smaller scale.
Speaker 2:Hard to read too much in into it because they've been investing so far ahead Yeah. Demand.
Speaker 1:Yeah. I 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 Grok pricing, which we see, and top line revenue 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 the the true frontier, the the models that are are are dominating Arc AGI, which we will talk about in fifteen minutes, those command a premium, a price premium.
Speaker 1:And and and there's a wild difference between charging $15 per million tokens versus $2 per million tokens. So it will be Yeah.
Speaker 2:If you and if remember, I think it was in q four of last year, if you looked on OpenRouter Yeah. Grok was what had I think it was like Grok fast Yeah. Had a lot a ton of usage. Yeah. People are like, okay.
Speaker 2:Yeah. Why is this happening? And part of it, at least I believe, was because they were subsidizing it. Here Well here's what I think. Yeah.
Speaker 2:So so people were posting this as though it was fact. But I think I think it's a very real possibility. So I think Elon will will will try to aim for the company to actually go out on on 04/24/2020.
Speaker 7:Really?
Speaker 2:And I think it is possible if he
Speaker 7:goes fast.
Speaker 2:The the ticker we'll see what the ticker ends up being. But Yeah. I think some people would like knowing Elon's very millennial sense of humor Mhmm. I think the ticker s e x is
Speaker 1:Oh, you think so?
Speaker 2:Plus the
Speaker 1:Yeah.
Speaker 2:April 20 IPO. I I would assume that You
Speaker 1:think it's a real prediction. You're not trolling.
Speaker 2:I'm not saying I'm not saying I would bet on it. There's like a I think there's I think there's I I would put the the April 20 at at maybe like, you know, 30% and then the ticker maybe down at at
Speaker 1:Okay. Well
Speaker 2:15%.
Speaker 1:But Call Call G has when will SpaceX officially announce an IPO? Before June 1, which April 20 would be before June 1. Yeah.
Speaker 2:I'm not saying about a 30 I'm talking about, like, list actual, like, listing day. Like, the day of the
Speaker 1:Yeah. This is just announcing the IPO.
Speaker 2:Which I don't even know if they
Speaker 1:This is now this is currently in in the scoop in the scoop thing. So they haven't even
Speaker 2:Scoop, you said? They so the Wait, John. Did you say scoop?
Speaker 1:Yes. This is a scoop from from
Speaker 2:What is this from here? We go can we go to the wide angle? We got
Speaker 1:Katie Roof, scoop master.
Speaker 2:We have a new we have a
Speaker 1:new award her the first TBPN golden scoop. The golden scoop Do you wanna show her the the scoop?
Speaker 2:I don't wanna I don't wanna pick it up yet. Why not? Okay. We can read it.
Speaker 1:We 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 of venture capital at the information and she's an absolute scoop athlete. She's scoop doggy dog. And and she moved markets. So Sats is up 7.8%.
Speaker 1:B b b k s y is up 4.8%. L U N R is up 4.1%. Every stock in the space.
Speaker 2:And we're working on a new award show, the Scoopies. The Scoopies. The TBPN Scoopies.
Speaker 1:I think Katie Roof is a lock.
Speaker 2:I mean, she's in she's she's a front runner for sure.
Speaker 1:Putting on a generational run. Front
Speaker 2:runner for sure. Yeah. It's so it's so funny the the I mean, incredible moment for the retail space investor community. Yeah. Because they're just for some reason, people people anytime you get SpaceX repricing, they're like, well, this this other random company that happens to be technically on the same market map definitely deserves to be worth 7% more.
Speaker 1:Yeah. I don't know. I I I I was as skeptical about the the rest of the lunar economy for a long time. It felt like winner take all. It felt like SpaceX was running away with it.
Speaker 1:But there have been interesting dynamics where 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. Rocket Lab's done very well. There's been a bunch. People are saying we need to redesign the scoop.
Speaker 1:I don't know what you're
Speaker 2:what you what you could be talking about.
Speaker 1:It's an ice cream scoop. It's an ice cream scoop. Right? People get your mind out of the gutter.
Speaker 2:Out of the
Speaker 1:to Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, mobile, on social, on marketplaces, and now with
Speaker 2:AI agents. Okay. Casey Hammer is worried.
Speaker 1:What is he saying?
Speaker 2:He's worried. Why is he worried? He's stressed.
Speaker 1:Why is he stressed?
Speaker 2:What I worry about is a generation of talented experienced engineers being too rich
Speaker 1:to 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 thirty days without telling anyone why you're doing it. This is from the nineteen eighties, nineteen nineties comedy called Brewster's Millions, which I highly recommend you watch. In it, a man is is gifted an inheritance from a wealthy uncle or father figure or grandfather And and it is conditioned on the on the fact that he needs to spend something like $30,000,000 in thirty 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 and spend money wildly, and it's it's to teach him that money does not bring happiness, of course, and I think that's the solution to this.
Speaker 1:Anyway, let me tell you about MongoDB. What's the only thing faster than the AI market? Your business on MongoDB. Don't just build AI. Own the data platform that powers it.
Speaker 2:Here's why I'm not worried.
Speaker 1:Why are you not worried?
Speaker 2:Because I think that these ultra talented, hardworking engineers
Speaker 1:Yep.
Speaker 2:Having some liquidity. Let's say someone's been there for some number of years. Yep. They have 5,000,000 liquid. They buy a nice house somewhere Yep.
Speaker 2:And then realize, hey, I've got a nice nest egg. Yep. I can keep working on crazy moonshot. I I don't have to go join, you know, the the the historical Totally. Example would be like, work on the hard thing or work on enterprise SaaS.
Speaker 2:And I think this just will give people more confidence to work on the hard thing, the thing that might have a five percent chance of But if it's successful, you know, it has a tremendous impact on
Speaker 5:Yeah.
Speaker 2:On our country and things like that.
Speaker 1:So It might happen for some people, but in general, I I I do think that there is this liquidity wave coming. Deleon talked about it 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.
Speaker 1:And there's always been a way to access some of that capital
Speaker 3:Yeah.
Speaker 1:Whether 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. And
Speaker 2:Yeah. A bigger a bigger issue for the kind of space economy overall is just the Blue Origin people who, like, wasn't didn't they have, like, way more? They, like, they didn't they they didn't really know what their equity was worth. They didn't it's like there was Yeah. Regular tenders.
Speaker 1:Yeah. Yeah.
Speaker 2:And so why work at the number two Yeah. At least by many definitions space company? And then that's potentially ultimately bad for competition. And it's bad for you know, launch pricing for all these other companies that are reliant on the SpaceXs and ultimately the Blue Origins. So Yeah.
Speaker 2:Anyways, crazy news out of China. Mhmm. Apparently, the co founders of Manus are still in China and were called up to talk with the government and are now blocked
Speaker 1:the Dark Knight?
Speaker 2:Yes.
Speaker 1:Has everyone seen The Dark Knight? You you thinking what I'm thinking? You thinking what I'm thinking? We go there, wrap our arms around him, the plane comes, grabs the balloon, sucks him out of the back of the of the skyscraper. It's one of the greatest scenes.
Speaker 1:And I think that's what we gotta do because we need personal super This
Speaker 2:was surprising to me because I feel like we've been messaged to you for a long time that they were in Singapore.
Speaker 1:Yes. That's true. Was definitely
Speaker 2:Chinese company. They're in Singapore. Yeah. The whole team's in Singapore. Wow.
Speaker 2:And and you would it it takes some audacity to sell your leading Chinese one of the leading Chinese AI companies during an AI, a global AI race Yep. This battle Yep. Between great powers and to sell to a big American hyperscaler. Yep. Maybe get out of the country before you do that because it's not at all I mean, this doesn't when when the Manus acquisition happened Yeah.
Speaker 2:Seemed very clear that you would be if you were China Yeah. And you were competing in the AI AI race Yeah. Even though Manus is not like a lab Yeah. You're still like, okay, they're building a powerful harness. Yeah.
Speaker 2:We probably don't want them going to serve
Speaker 1:And the harnesses are incredibly they're probably under
Speaker 2:More important now. Everyone
Speaker 1:yeah. It is 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.
Speaker 2:So Josh Wolfe says, I thought this wasn't a Chinese And Dalian goes for the jugular and says so much for all the arguments about not being influenced by the CCP. Bill.
Speaker 1:I'm I'm mostly shocked just about how this is playing out. You 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.
Speaker 1:But if it does, we'll just stay. And we won't go back because if it goes through, then there's gonna be pressure and we're gonna wind up in this situation. This feels almost predictable. I don't I don't know. It feels like there's something else going on here.
Speaker 1:I'm excited for this this story to develop.
Speaker 2:So the authorities are reviewing Okay. The sale. Yeah. And they're being asked not to leave. Seems hard to reverse at this point.
Speaker 2:But again, not sure why. I mean, when you look back at acquisitions that were blocked historically, who knows? Yeah. Who knows how feasible it is to fully block the acquisition, but they can certainly block these individuals from, you know, materially benefiting from it in some way or contributing to Meta's efforts.
Speaker 1:Well, here's some advice for the CEO of Manus. When you get here to America, when you get that liquidity, that payday from Mark Zuckerberg, open an account on public.com, investing for those who take it seriously. Stocks, options, bonds, crypto, treasuries, and more with great customer service. Just do it. And then, you know, tell your story.
Speaker 1:Start restreaming. One livestream, 30 plus destinations. You should be you should be multi streaming. So go to restream.com. Tell your story live on the Internet.
Speaker 2:Gabriel says Meek Mill has been going off Yes. About AI. AI is helping him organize his whole music career and other businesses in 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. It's probably G Stack.
Speaker 1:Yeah.
Speaker 2:Who else can help me with Claude? Gabe says, Drake, I don't do k two, Kimmy, deep seek. That's more for your kind. My Yeah. More like Demis theme park, Ting London deep mine.
Speaker 2:Meek Mill. I quad coded perks out of 18th And Berks. I got 500 agent lawyers trying to free Lil Durk.
Speaker 1:That's a good line. Bars.
Speaker 2:Drake, sing it. You got me loco trying to be your shulter.
Speaker 1:You didn't sing it.
Speaker 2:Sophie chimed in.
Speaker 1:Actually sing it.
Speaker 2:Two chains. Open call on my laptop. Trapping off these Mac minis. Shout out to YC. Real g's wanna stack with me.
Speaker 2:Oh. Oh, that's good. That is good. I mean, yeah. It's not a it's not a bubble until until g stack makes it into makes it into a Yeah.
Speaker 2:Actual hit.
Speaker 1:The funny thing here is
Speaker 2:You might see
Speaker 1:There's some debate and and there's this general vibe like some people were latching on to this trunk fan post about like, know, are people making fun of Meek Mill? Do are people like under counting 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 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 it I think a lot of 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.
Speaker 1: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. And he probably spent a lot of money developing that piece of software. But and and I don't think it wound up working and it didn't scale and he wound up winding that project down.
Speaker 1:But if you think about like, well, what if this what if this cost of doing that is a $100 or $200 or a thousand bucks? Like, all of a sudden the the hurdle rate to clear something like that actually does open up the creative aspects where I 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 a creative artist, you 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.
Speaker 1:And all of a sudden, you get into this weird thing where like the 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.
Speaker 2:And we are working on getting Meek on
Speaker 1:the show. I really hope we can talk to him.
Speaker 2:I'll cover
Speaker 1:You're good. You're
Speaker 2:good. I'll cover Meta. Okay. Do you want to jump for a second?
Speaker 1:First, let me tell you CrowdStrike. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches. And I'm also gonna tell you about Vanta, automate compliance and security.
Speaker 1:Vanta is the leading AI trust management platform. And I'm totally good, so I can take I the next
Speaker 2:have a personal thing I'm gonna run to, but I will see you guys tomorrow. Yes. Love you. Cheers.
Speaker 1:Thanks, Jordy. Up next, we have Mike from Ark Prize in the restream waiting room. Let's bring him into the TBPN UltraDome. I'm very excited to talk Mike. How are you doing?
Speaker 3:Here we go.
Speaker 2:Hey. Hey. Good to see you again.
Speaker 1:Good to see you.
Speaker 3:It's been
Speaker 1:a This day this is always the highlight of the show. I love talking to you about everything. But what are we talking about today? Reintroduce ARC as an organization and then take us through the actual do you even call them benchmarks challenges? What's the right term?
Speaker 3:Yeah. Think benchmarks is a fair word.
Speaker 7:Okay.
Speaker 1:Yeah. Tell me just
Speaker 3:a couple almost three years ago now, we cofounded the ARC Prize Foundation, me and Francois Chelet. Yeah. The ArcPrize 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 sense public sense finding tool
Speaker 1:Mhmm.
Speaker 3:For the public to understand how close, how far are we towards AGI or not. Yeah. 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's Frontier AI is capable of and what humans are capable of. And we sort of target that gap.
Speaker 3:That is sort of our definition of ultimately AGI is, you know, we we produce an ongoing series of benchmarks continually studying Frontier progress. And, you know, at some point, we are not gonna be able to do that job anymore. We will run out of ideas. You know, we'll test Frontiare 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 we've got AGI now.
Speaker 3:And today, we are announcing and launching the the newest best version of Arc Arc AGI three. It's the latest in the series. This is a really large format change from the first two. ARC three is designed to test agentic intelligence. And it is, as I as far as I am aware, and I've been sort of interviewing folks all over the AI scene in the last few weeks, the only unsaturated general AI agent benchmark in the world.
Speaker 3:The headline score is human score, 100% and AI, less than 1%.
Speaker 1:Okay. Unpack that launch because I my conception of Arc AGI v three is it's almost like a two d game. It's no longer the puzzles where I'm picking colors to match a pattern. Actual It's moving arrows on the keyboard. I'm stepping on triggers.
Speaker 1:I'm opening doors, switches, that type of thing. And I played it with you on the stream a month ago.
Speaker 3:Yeah. You helped us launch our preview Yes. Several months back.
Speaker 1:So that was the preview.
Speaker 3:We got the full dataset launching today.
Speaker 1:Okay. So does that mean more I'm going to call them games, 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?
Speaker 3:Both things. Okay. Actually. So today, on the benchmark side Mhmm. The public version of the Benchmark is or I guess the the overall Benchmark's over a 100 games, nearly a thousand different levels across these game like environments.
Speaker 3:I think it's fair to call them games. Yeah. 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 more as environments though. These environments are intended to test whether AI can effectively explore, discover its own goals, acquire strategy, develop plans, execute its plans.
Speaker 3:One of the really unique things about Arc three 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. Yeah. Three challenges both humans and AI to essentially figure out the figure out the goals themselves. Mhmm.
Speaker 3: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, you know, dedicate some 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 the strategy mechanic, they grow and they evolve and they change over time. And this is one of the reasons I think Arc three will be a really useful tool for understanding agent agentic intelligence this year.
Speaker 3:I think it'll be our first real test where we're, you know, seeing early progress on these AI systems that are able to do on the fly world modeling, some degree of on the, like, on the fly continual learning. These are both, like, critical capabilities that we view as missing today that ARC three tests for.
Speaker 1:Okay. Take me a little bit deeper on you you said there's a thousand games or a thousand levels?
Speaker 3:Few a few 100 games. Few over a 100 games Okay. Across those a 100 environments Yeah. Nearly a thousand levels across all of them. Yeah.
Speaker 3:It's a much larger version of of the of the Benchmark than than we've ever had previously. And then, like I said, mentioned before, the other major thing we're announcing today is Frontier Scores.
Speaker 7:Okay.
Speaker 3:So the Benchmark is is launching. We're also publishing as of today The the latest four models across all the four major labs. And, yeah, I think SOTA is currently sitting at like point 3%, point 4% something
Speaker 1:3.1 Pro. Maybe there's an extra hyphenate on there. But basically, the Gemini, Anthropic, and OpenAI were all in the point 2.3 something, and then Grok was, I think, at 0%. Walk me through the actual build out of these 100 games. Is this Yeah.
Speaker 1: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?
Speaker 3:I I wish we could use AI to help design games. We'd be able to make the benchmark even bigger like better. Yeah. The reality is, like, humans are still the bottleneck on creativity, and so every game has still been handcrafted and hand designed by humans. Okay.
Speaker 3: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 as as far apart as possible in that sort
Speaker 2:of space.
Speaker 3:And today, still humans are kind of the limiting factor in terms of ensuring that, you know, every game is is different and as novel from from 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 to one and two. Maybe the the largest is, you know, ARC study is the frontier progress. We have to design our future versions of benchmark to to adapt to to changing frontier progress.
Speaker 3:One of the design goals with one and two was we have what's called a private and a and a public test split. Yep. Where we have a public version of the Benchmark and a private holdout version, which is what we actually use to verify the performance of Frontier models.
Speaker 1:Wait. So so the the frontier models get no freebies. They don't get anything from the But public they can train They can't memorize the public set. Right? Or or or they can they can experiment on the front on the public set from like a prompting perspective maybe?
Speaker 3:Yep. The idea is the public set is intended to demonstrate the format. Okay. And this is similar with Arc one and two. However, we held the design goal that the public sets and the private sets were were what's called IDD with each other.
Speaker 3:Basically, they are are supposed to be as close as possible to each other Mhmm. And it's just split along visibility. Some are private Sure. Some are public. Sure.
Speaker 3:With one of the the big advancements with AI reasoning is this is actually, like, not a very useful way to run benchmarks. Mhmm. AI reasoning systems are so powerful now that they can actually generalize across IDD test splits. And this is what we saw with Arc one and two. So with three, one of the big design decisions is we're actually releasing fewer games into the public demonstration sets.
Speaker 3: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, you know, be able to test your systems to make sure you can sort of create them, get a feel for them. Yeah. There's obviously fun marketing value in being able to play the games as humans too, which we really love.
Speaker 3:And on the private side, it's this is the set that's over a 100 a 100 games. They're specifically different they're they're different we designed them with different characteristics, different goals, different intelligence capabilities required to beat them, the difficulty. The acceptance criteria is more extreme between human AI performance, all to hopefully produce the most useful, like, high signal benchmark towards whether we actually are getting real progress towards AGI with the foundation models.
Speaker 1:So let me pitch you a strategy. If I have access and I I would you know, I'm at I'm at Google or OpenAI or Anthropic and I I want to do well here, can I take the a public set and create a log of all the steps and all the reasoning chains and all the keystrokes 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?
Speaker 3:And train your model that way basically?
Speaker 1:Maybe train my model but also I'm I'm just wondering if if that's helpful for for setting up the context or or or like doing some sort of like pre compaction of the strategies that are learned
Speaker 3:I see.
Speaker 1:Maybe not even training a custom model because I feel like that would maybe be like bench hacking. More thinking about just like, okay, we we went and we played all the public games to completion and we 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 Yeah. Yeah. And then we include that in the prompt that that that kicks us off, just sort of bootstrap the learning
Speaker 2:Right.
Speaker 1:Once we get into the unknown environment.
Speaker 3:If we've done a good job on the benchmark, you should not be able to train a system on the public set and perform on the
Speaker 2:private set
Speaker 3:if we've done a good job. Obviously, every benchmark release, it's an it's an experiment. Yeah. Right? We make contact with reality, we ship these systems, put benchmarks publicly, we we under we try to analyze the performance, understand what they're good at and bad at and evolve, you know, future versions of benchmark.
Speaker 3:But intentionally, you know and it's actually it is a very closely related to another design decision that we're making with our scoring function going forward this year. This is again in response to, like, AI progress that we've seen. Mhmm. You know, our our scoring methodology is basically AGI peeled at this point. We, going forward with v three, are using as I I kind of have the this idea of, like, basically, a a a philosophy of having essentially don't no harness.
Speaker 3:Mhmm. 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 our we have rented literally a testing center in San Francisco have, you know, hundreds of humans play these games.
Speaker 1:Yeah.
Speaker 3:All they're given is you you have sort of, you know, 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 of having a very stateless client Mhmm. 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.
Speaker 3:It's like, you know, you're playing a game. Here's your actions.
Speaker 5:Yeah.
Speaker 3:Your conversation will be carried forward to the next turn and that's it. In order to, again, kind of produce this really clear signal towards when the the real progress towards AGI and the base intelligence layer were able to detect that.
Speaker 1: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 OpenAI had a product, I think it was called Jim, where they were able to beat Mario and then they beat the DOTA team, DOTA five. And they were able to do things that I can't do. I I certainly can't beat Lee Sedol in Go. I certainly can't, you know, win Jeopardy or any of these things.
Speaker 1:And yet Mhmm. 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 where we're not matching up like we did in the past?
Speaker 3:I think the biggest thing is the expectation of what constitutes real progress towards HCI. Right? When labs were using games in maybe the 2016 to 2018, 2019 era when they're very popular, human researchers are studying the games, trying to understand the failure modes of machine learning, deep learning, trying to build custom search like harnesses to and sort of feedback mechanisms from the environments. It's very, very handcrafted. It's loaded with what I'll call like human g, right, in the research process.
Speaker 3:We are now at a point where we want to control for that, actually. We want to understand, like, we we want to control for as little human g in these, like, systems Yeah. As possible. Right? Yeah.
Speaker 3:We want to understand is can basically AI do what the human researchers were doing back in the era in order to beat those games that they had never been trained on or exposed to before.
Speaker 1:Oh, interesting.
Speaker 3:So I do think it's kind of elegant that, you know, we are coming full circle 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 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 is is the big difference today, especially with Arc three.
Speaker 1:Okay. Remind me of some more history, but more related to Arc. I remember with one of the Arc AGI benchmark tests, there was a version from 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 something.
Speaker 3:O three.
Speaker 1:Is that what it was?
Speaker 3:Very big launch.
Speaker 5:Okay.
Speaker 3:Yeah. That was like a preview of o three in December 2024. So really the first, you know, there's a great chart on the Archprize homepage now where you can actually see those data points so clearly. I think one of the really you know, what like I mentioned before, one of our missions of the foundation is to try and be useful public sense finding tool.
Speaker 1:Sure.
Speaker 3:And I think, you know, when we first launched Arc one and two, you know, was a very common critique. It's understandable. Know, hey, these things look like toys. Are they really economically useful? Are they gonna lead to any, you know, real progress?
Speaker 3:And now in hindsight, actually think that's a pretty outdated view because we have pretty strong evidence that Arc held quite strong predictive power of noticing really important moments. Okay. We only started seeing saturation on the v one benchmark. And remember, v v well, v one was like five years old.
Speaker 4:Yeah.
Speaker 3:We only started seeing any amount of progress from LMs on v one once we got AI reasoning, was a really critical innovation, I'd argue is is is important as the original transformer innovation. And then a year later, this was, you know, four months ago now, with the November 2025 class of models with GPT five two and OPUS 4.5, we again started to see saturation on ARC v two and it precisely correlated with this like agentic coding capability that that emerged. Yeah. And so I'm hope I'm optimistic that ARC three will again be a very useful sort of predictive tool to understand when, you know, basically, AI agents are capable of operating in more open ended environments. Yeah.
Speaker 3:Right now, you know, you need a lot of human handcrafting to get these intelligence systems to work in domains, such as coding, right, with Cloud Codex and code or sorry, Codex and Cloud Code. Yeah. And that's we I I basically expect that, like, when you are doing very good on v three, which will mean, by the way, a 100% scoring v three 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 end environments that they haven't been specifically trained on.
Speaker 7:Mhmm.
Speaker 1:I I I still remember from Arc AGI one, you know, you see these like three by three grids and the first time I ever tried it, I tried it on my phone and I think my phone was in some weird like landscape mode or something. So it wasn't rendering correctly. And I was like
Speaker 3:You didn't need to get all the data points.
Speaker 1:Yeah. No. So normally it's like you see the blocks and then you see the blocks to the left and the right. And then I was like, wow. I'm like I'm cooked.
Speaker 1: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 o three extra high. Like, what are you seeing from the labs that put forth models that did test on Arc AGI V3 in terms of just steering the models? Because we talk about GPT 5.4, but that means a lot of different things these days.
Speaker 1:This in the max reasoning? Should I compare this to what I'm seeing in ChatGPT? I'm getting more and more dropdowns where I can go, oh, I can go pro and then I can go extended thinking mode. Yep. Is it is it an off the shelf model or are they able to sort of come to you and say, hey, we want to we want to actually marshal 10 times the amount of compute for this particular challenge?
Speaker 3:On our verification leaderboard, we have a new testing policy. It's actually something we did have with one and two Mhmm. Introduced after o three where we limit to $10,000 per verification run. Okay. This is somewhat of a practical like consideration.
Speaker 3:Yeah. If we actually used like the most expensive, highest, you know, million context window of the most expensive model, I think testing in the full v three private data set would be like a $100. Woah. Which is just kind of like silly. Right?
Speaker 3:Yeah. So we we set a we set a reasonable limit like humans near nowhere near as much as sort of like dollars to sort of produce this Yeah. Same performance.
Speaker 1:I like that too because like that is limit. That is the like like getting AGI and it's like yes, it can do anything but it costs $50,000,000 per prompt to do one hour of human labor like that's not really economically valuable and so bounding think you want
Speaker 3:to know progress, Right? And I think $10,000 is a reasonable amount of money where you will actually see some degree of progress and that will be a useful signal to start paying attention to it more. Yep. It's and it's like just, know, for practical reasons, we just can't because we're we're we're a strapped nonprofit.
Speaker 1:So Yeah. Yeah. You know,
Speaker 3:we have to be sort of thoughtful on our on our sort of money on how we deploy things. Well, good luck. Yeah. That's sort of so I think the high reasoning mode is the most we used on for the official verification stuff that we used today. Stay I down to that
Speaker 1: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, oh, I've always been a twenty thirty five guy. I'm still a twenty thirty five guy. Something like that.
Speaker 1:Like, do you do you have an internal model of this? Or is that even useful these days?
Speaker 3:I instead of listening to my predictions Mhmm. You should probably follow our actions as our, like, best sign of a sort of review of progress. I think the reality is we have made tremendous progress with their reasoning over the last twelve months. Yeah. Arc is operating to bring the next version of the benchmark.
Speaker 3:We're already we've already started work on v four. We actually have plans written down already for v five as well. Our intention is to bring these to market annually over the next two years. And so that that's sort of our expectation of having the next version ready right now. Yeah.
Speaker 3:Now, like, will we actually launch them? I think we'll have to just see what Frontier progress does. We want 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 focused 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, there other interesting remaining large gaps between what humans can do and AI can do in order to drive that gap to zero?
Speaker 3:You know? Yeah. Again, we're very we're very AGI filled organization. We want to see progress. We actually love seeing progress.
Speaker 2:Yeah.
Speaker 4:Of course.
Speaker 3:And part of our goal is to inspire as as much progress as quickly as we can to to get to these AGI systems. Yeah. So I I'd say like, yeah, that that's sort of the the operating view. Well, you know, a common question would be like, what is v five, you know, is v three AGI, is v four AGI, v five AGI? No.
Speaker 3:The honest answer, and this is something I've actually learned. I had a different view of this maybe three years ago. Honest answer is no single version of any benchmark is ever going to be a GI. I think it is a the frontier of progress is a moving target. Mhmm.
Speaker 3:And our job is to like understand 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 Yeah. You know, that identify some missing important capability that humans are able to do and produce benchmarks that that showcase that gap.
Speaker 1:Last question, I'll let you go. What's going on with the Pokemon bench? That feels somewhat related. Yes. Similar tasks.
Speaker 1:What are you learning from that? How are models becoming so good at that? It feels like they aren't specifically RL'd on Pokemon and they're learning. But also, there's a massive amount of, you know, written text about what to do at every level in Pokemon. Are they just learning that from the pre training corpus?
Speaker 1:What what's your thesis on Pokemon?
Speaker 3:It certainly seems helpful. If I use our experience in developing Arc as a tool to throw a sense finder on this, we have seen more understanding from the latest generation of AI reasoning systems over the last three months
Speaker 1:Mhmm.
Speaker 3:Than we saw in the first six months when we were developing Arc v three. Mhmm. I think you can kind of fork you you can almost split the research problem of agents into two things. Mhmm. 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, you know, successfully execute a plan.
Speaker 3:That's half the question. The other half of the question 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 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 the exploration problem, the strategy generation problem. I actually think this is one of the areas that that I would point interested Arc three researchers at because I think it's a lot more greenfield and will unlock a lot more progress even on, you know, things like Pokemon Bench where where it's kind of coming down to, like, okay, we know they can sort of or I should say, execution.
Speaker 3:Mhmm. The exploration and planning step is still where there's a a large degree of bottlenecking still still happening today.
Speaker 1:Well, congratulations on the progress. Where can people find it? How can people participate? How can people help out?
Speaker 3: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. They're all they're all designed to be very fun.
Speaker 3:We got mostly controlled for this actually when we were doing human baseline testing, so that should be fun. We can have fun. And you can also get details there. Enter our prize 2026, our new $2,000,000 prize pool this year that's on ARC two and ARC three.
Speaker 1:That's amazing. Yeah. Our 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.
Speaker 1:Was fantastic.
Speaker 3:Likewise, man.
Speaker 1:We'll talk to you soon. Have a good day. Me tell you about Gusto, the unified platform for payroll benefits and HR built to evolve with modern small and medium sized businesses. Let me also tell you about Turbo Puffer, serverless vector and full text search built from first principles in object storage, fast 10x cheaper and extremely scalable. And without further ado, we have our next guest Nathan from Air Street Capital coming in to the TBPN Ultram.
Speaker 1:Nathan, how are you doing?
Speaker 5:Great. How are you doing, John?
Speaker 1:Thank you so much for staying up late. What time is it there?
Speaker 5:07:25.
Speaker 1: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.
Speaker 5:Yeah. I'm Nathan. I started a venture capital firm called Air Street Capital in 2019 to invest in AI first companies.
Speaker 1:Wait. What year were you investing in AI?
Speaker 5:Well, so I started the firm in 2019, but started investing in AI in 2013, which was around the time that, like, deep learning was still definitely cooking only in the lab and Yeah. Most people didn't really care too much outside of it.
Speaker 1:Yeah. What were the median deal like what was the median deal like
Speaker 5:in Oh, yeah.
Speaker 1:2013? Was that like recommender systems? Like, we're gonna bring Netflix recommendations to everyone, like that type of thing?
Speaker 5:Yeah. Well, it was ecommerce recommendation systems Sure. Ad tech. Yeah. Big data was the buzzword back then.
Speaker 1:Sure.
Speaker 5:Sure. A little bit in finance Yeah. Like insurance underwriting, like loan prediction Sure. Credit
Speaker 1:Yeah. Yeah. Fraud detection.
Speaker 5:That stuff.
Speaker 1:Yeah. Fraud detection. Just like a big I guess it was like were they doing deep learning yet? Or was it mostly just like Yeah.
Speaker 5:They were. Yeah. I mean, it was 2013 was the year that computers started to be able to recognize images better than than humans.
Speaker 1:Oh, yeah.
Speaker 5:So that was remember, like, Andre Carpathi infamous human benchmark on ImageNet in Yeah. 2013, PhD?
Speaker 1:That's right.
Speaker 5:So that was the year when when basically, like, Alex at University of Toronto, like, built AlexNet, which
Speaker 1:Yeah.
Speaker 5:Was the first deep learning system running on NVIDIA card.
Speaker 1:Yeah. Yeah. What what a remarkable time. So what has it has it been easy? I mean, you just raised a new fund.
Speaker 1:Has it been easier to pitch this to LPs? What have been the challenges and and opportunities over the last few years?
Speaker 5:Yeah. I mean, it's been a it's been a sea change. Like, in 2018, you know, when I started for Air Street, it was like, I'm, you know, by myself, a 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 fund. Those are sort of like all the worst, like, buying selection criteria
Speaker 1:that one would Yeah.
Speaker 5:And then, yeah, like, I think, you know, this this is very much like a long term journey. Like, you know, I set out with Amadou's 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, Synthesia, Eleven, Black Forest, and and others. Yeah. I'd like six exits to, like, Recursion and, you know, a company that went public and Amazon, etcetera.
Speaker 5:Yeah. And then and then, yeah, like, first fund was, like, $27,000,000. Fund two was $1.21. About three years later, again, pre chat GPT. And then and then this one's 232,000,000, which at this point makes us the largest solar GP in Europe.
Speaker 1:That's amazing. So us Yeah. You said solo GP, but you said us. Who else is on the team?
Speaker 5:I'm you know what? Like, I'm kinda guilty with the royal we thing. Okay. But but I I have two colleagues who Okay. Run talent and operations, and then a pretty sizable back office for, like, admin.
Speaker 1:Sure.
Speaker 5:But everything that comes along with, like Yeah. You know, building brand, finding founders, investing, fundraising, that's all mean. The decisions are at the pages. Yeah.
Speaker 1:And then also the the is it annual reports, State of AI? I mean, it's Yeah. It's a sort of a huge project. Do you bring in collaborators on that?
Speaker 5:Yeah. That started in 2018 to Yeah. Basically create, like, a kind of canonical open access document covering research industry politics and talent. Yeah. There are a number of contributors every year who are sort of, like, at the coalface during their PhD or, like, transitioning between roles in AI labs who help us kinda stay smart on things and and also folks who've been working on policy because it's becoming increasingly important as we see in the news almost every day.
Speaker 5:Yeah. 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 kinda, like, leaving comments being like, hey. I 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.
Speaker 1:Mhmm.
Speaker 5:And it's like, cool like community document basically where we can kind of get to the the center of the truth.
Speaker 1:Not to call you like lucky on timing. It's very fortunate that you have the size of fund 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 $27,000,000 fund? Because it feels like a $2,027,000,000 dollars like a seed round for like a you know start up with just an idea. Sometimes that's like 111% of the of the seed round.
Speaker 1:Like is it can you even make plays with that size fund if that's what you are constrained to today?
Speaker 5:I I think you have to decide like what I did, is either you wanna be like a main player and lead rounds Mhmm. And express conviction and be early, etcetera. 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 of, a network SDR style job and less of a, like, I can make my own opinions, like do the research, be there early, and then when I like something, like really make the bet. Yeah.
Speaker 5:I don't think you can do the former. They'll like be a lead investor in 27,000,000, no chance. I think you can do the larger portfolio, you know, chipping into a variety of rounds and still have like good performance. Mhmm. 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.
Speaker 3:Yeah.
Speaker 5:You know? So I I think at the end of day, like, you gotta pick what what flavor is good for you and then try as best as you can to bring the best product to the market given your circumstances. And I was fortunate with Fund three to be able to really come with like a blank slate with, you know, long term partners and say, like, this is what I think is gonna be the most convincing model, you know, write up to $15,000,000 in first checks and do a couple of gross stage rounds up to 25,000,000.
Speaker 1:Wow.
Speaker 5:But still, you know, high conviction, 20 companies. And and of course, like I'm, you know, mostly based in Europe but still invest in The US and spend decent time there as well.
Speaker 1:Yeah. I mean, I know you're you're you're in Europe but you're not, you know, exclusive European investor But by any I am interested in the thought exercise of, like, where is the AI opportunity internationally? If I were to just back of the envelope it, I'm I'm, you know, I've seen some of the sovereign AI efforts. It sort of makes sense that like a certain government might want to buy from a particular local lab. But at the same time like Google has been very successful internationally.
Speaker 1:And 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 OpenAI or Anthropix going to build a data center, they might want to go to a local neo cloud or there might be opportunities for the Harvey of some other country that has different laws and different rules. And so how are you seeing the shape of, like, opportunity outside of America in AI?
Speaker 5:I 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 Yeah. One or two other initiatives that, you know, had hundreds of millions of dollars pumped into them so that they could, like, capture European culture better than Google could.
Speaker 5:And I think that's a bit bizarre when you're talking about a learning machine. Yeah. But but so there's certainly some sectors where I think, like, the sovereignty, like, really matters, and it's not just marketing speak. So, you know, defense and security is clearly one where, you know, Europe woke up to this like two years ago and and and now even more so with the Middle Eastern war that's ongoing. Yeah.
Speaker 5:You know, as an example, like, I invested in a business called Delia and Alliance Industries doing defense, autonomous defense systems, right, in Greece. Yeah. 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? Yeah. And then narrative changes significantly once you start seeing Shahid, like drones hit, you know, UK bases in Cyprus, and you realize, like, okay, the border to Southern Europe actually comes over the Mediterranean in Greece.
Speaker 5:I think the the other part, which is which is interesting, is like ambitions change. And and I think in Europe, where traditionally there's been fewer role models than one can look to and say, I'm gonna be like that person, and I know the path. Yeah. Some companies grow and, you know, for example, I think Ligura originally started as Leia, like, started in Sweden. Right?
Speaker 5:And it was the idea of, hey, we should do this locally in Sweden. And and now, like, clearly that company's ambitions are like, now we can go head to head with Harvey.
Speaker 1:Yeah. Yeah. It does feel like in Europe, like the 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 gonna go everywhere.
Speaker 1:I'm building Spotify and I'm gonna go everywhere. And yes, I happen to be from some other country and I'm gonna have a headquarters there, but get ready in New York because we're gonna have a headquarters there and we're gonna have an engineering hub in SF and like we're just gonna be an international company and have our roots there and that's a great Yeah.
Speaker 5:So this is why I think if you're gonna invest in Europe, it's really important to have this foothold and knowledge of The US market so that you can apply the same quality distribution
Speaker 1:Mhmm.
Speaker 5:That you see in The US over in Europe. And Yeah. Either there are people who start from day one being that ambitious or there's others that are that grow and and kind of, yeah, just, like, fuel their batteries with ambition as they see and, like, experience it. You know, like, when you get success, you want more of it. So that's, like, the kind of recursive cycle of the continent's going through.
Speaker 1:Yeah. We I mean, with all the progress from the big labs, and they're at such incredible scale now, like, how are you processing the SaaS pocalypse and just advice for founders of like what gets steamrolled versus what doesn't? I mean, were some there was some founder. We've had a couple founders on the show that have been like, we're doing an AI generated video social network. And then it was like, you're getting steamrolled.
Speaker 1:And then it was like, actually, like, you know, Sora's not going be in the App Store anymore. So like, maybe that was a good bet. I don't know. I'm 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.
Speaker 1:Like, that's done. But now we're talking about, oh, is there pressure on CRMs? Is there pressure on databases? Is there pressure like, what will the labs do? It's it's unpredictable.
Speaker 1:But how are you working through it?
Speaker 5: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 point. Like, don't do coding.
Speaker 5:Yeah. But like after coding, it seems like AI researchers really like AI for science. So like Yeah. Don't do that either.
Speaker 1:Totally. Totally. Yeah. Yeah. Yeah.
Speaker 1:Yeah. I remember 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's on the road map.
Speaker 5:That's actually that's really good. Amazing. Jokes aside, I think I think it it comes down to like this tacit knowledge and, like, where you can capture how people do a task and taste. Mhmm. Like, I see this a bit with our job.
Speaker 5:Like, you know, I'm using, like, I'm Claude Maxing as well and, like, Codex Maxing. It's amazing how it can how you can imbue it with your taste, and you're like, at some point, realize, okay. We built, like, a learning machine that basically is like a sieve. You can pour as much as you want into it, and it'll still, like, learn stuff. Mhmm.
Speaker 5: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 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 Yeah. Like, here's a new opportunity.
Speaker 5:I'm like, dude, if you're not doing that, it's, like, game over. Yeah. And so I really do think, for our job, like, was a point at which you're like, you know, solo GP with like 200 or $300,000,000 with a bunch of AIs. Yeah. So Yeah.
Speaker 5:I'll call you in ten years and see if it works.
Speaker 1:I'm excited. I'm excited. Well, I wanna hit the gong for the new fundraise. Congratulations. Thank you for coming on the show.
Speaker 1:Have a fantastic rest of your day, and I will talk to you soon. Have a good one. Thanks. Goodbye. Let me tell you about vibe.co, where d to c brands, b to b startups, and AI companies advertise on streaming TV, pick channels, target audiences, measure sales just like on Meta.
Speaker 1: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 Rohin Jorg. He is a real estate expert.
Speaker 1:Thank you so much for joining the show. How are you doing, Rohin? Good to meet you.
Speaker 8:Good. Happy to be here.
Speaker 1: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?
Speaker 8:Yeah. I'm a San Francisco real estate agent and I'm among the top highest producers by volume in the city. And I came from a little bit of a traditional background. I did a YC startup. I went to Stanford Business School.
Speaker 8: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 and and then learned the real estate craft from that.
Speaker 1:Did you have to get a license at some point? Did you join a big firm or did you just sort of Yeah.
Speaker 2:Strike out a row?
Speaker 8:I was my Twitter account started growing because I was like posting interesting houses Yeah. That I was like just kind of curious about. Then people were messaging me like, oh, I actually like bought that house you
Speaker 1:No way.
Speaker 8:Posted about. And so I was 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 gonna 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.
Speaker 8:And that's that's like odd to me. And so I was like, okay, well YC moved here. OpenAI is just sort of like getting traction. And the city's getting better. I think everyone was sort of agreeing to that.
Speaker 8:And then I was like, well, is the opportunity, and I'm getting a license, and like this is what I'm gonna focus on. And then and then I had a lot of traction with it, so I just sort of got sucked in to be sort of a, you know, full service, like, you know, Rohin in your corner real estate agent when you're trying to buy or sell a place.
Speaker 1:I love it. When did the actual rebound start? Where where was the trough after COVID?
Speaker 8: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. And then sort of at very 2022, things, like, abruptly dropped. So 2022, 2022, 2023, 2024, prices were way down.
Speaker 8:And then 2024, by the end of it, there was, like, a little trickle. And 2025, you sorta hit hit had come out of the bottom, but it was, like, a slow Mhmm. You know, like, you know, pretty stable market, but on the upward trajectory. And then 2025, then it just sorta started booming, crazy in terms of pricing. And then even from March 2026 is way up compared to two months ago.
Speaker 1: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, 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?
Speaker 8:You know, 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 Mhmm. In in all ways. It's like there's not enough housing, there's not enough restaurants, there's not enough this or that. It's sort of like, if you want a place in San Francisco, you're so convicted on the idea of it, of the city, of the tech industry, you're like, you know what, I'm just gonna do this, and then I'll figure the rest of it Mhmm.
Speaker 8:And so, I don't think people are like, oh, now I have to figure out what school my kids are gonna go to, or what my commute will be, or this or that. It's like, if you're sort of 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 these homes, whether they're at like, you know, any price point, it's it's like there's something mentally inside them that's like, this is the place for me.
Speaker 1:Mhmm. And what does the the the like, the Down The Fairway place in San Francisco look like these days? Is everything over 2,000,000, 3,000,000? Like, where are we in
Speaker 8:terms of like single family? Trying How does to find a place that is that would fit four people and might have parking and a second bathroom and two or three bedrooms. Say like a year ago, it was like around 2,000,000, and then if you were slightly above that price, there'd be like a big drop off in competition.
Speaker 1:Mhmm.
Speaker 8:And now it's like that level has sort of definitely moved up to like 3 ish million. But there are the bigger change too is that like there's like huge level of competitions at any price point now.
Speaker 1:Okay.
Speaker 8:Yep. It's like one that sort of checks the box for buyers.
Speaker 1: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 have to do?
Speaker 8: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 Yeah. 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 sort of have to realize is there's gonna be a range of competition on any given house.
Speaker 8:So like, some houses, this could be like a 5 or $6,000,000 house, so pretty expensive house, and there might be like 15 offers.
Speaker 1:Woah.
Speaker 8:And like the seller's not like gonna just sell it to you because you're a cool guy. Like they're 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. And so, like, what you're sort of trying to navigate is the level of competition any one house is gonna have. So, like, say, if it doesn't have as many bathrooms as you want, but you could figure out how to add one.
Speaker 8: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 participating in a massive auction. It's like trying to participate in an auction only you know about or a smaller sort of you know, a different kind of property.
Speaker 1:Mhmm. 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.
Speaker 1:What's your forecast?
Speaker 8:Well, obviously, it's like, you know, hard to predict the future. But I wasn't like, oh, I want I'm a San Francisco real estate agent. You know? Like, I'm gonna say, like, you know, whatever. Like, I decided to get into the market because I thought this was gonna happen.
Speaker 8:I was like, oh, these scarce homes are gonna become more valuable and people will wish they bought them and I should focus on this. And so personally, I'm convicted. City is on the right trajectory now. So it's not, like, contrarian to buy a place here at Yeah. The And then there are, liquidity rounds, and, like, that has made a big impact on the market.
Speaker 8: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. So
Speaker 1:What do you think expansion looks like over the next few years? Are we gonna I I know Mill Valley is booming. There's other suburbs. Is Oakland gonna happen? There's this California Forever development that's happening that's further out.
Speaker 1: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?
Speaker 8:So I I solely focus on San Francisco, like buyers and sellers. Because I found that in order to every time, especially on the buyer side to win, it's sort of pulling off this Mission Impossible heist where it's so elaborate. You have to know every detail about the market. And so for me personally, like I feel very strongly that I can really help people in San Francisco.
Speaker 1:That makes sense. And then if
Speaker 2:you put
Speaker 8: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 gonna 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.
Speaker 1: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 of tech boom times happening in Menlo Park, Cupertino, sort of on the Peninsula?
Speaker 8:Yeah. I'd say it's about, like, fifty fifty, 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 sort of regained the zeitgeist of like a place you move to invent the future. Mhmm. So I think that's like half of it.
Speaker 8:And then the other half of it is that 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. And now, like, we have two
Speaker 1:Yep.
Speaker 8: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, $100,000,000,000 companies before and, like, past weeks of this one, we never
Speaker 2:had this magnitude.
Speaker 1:But this is at a different level, an order of magnitude, and so that's just gonna drive up Yeah. Attention and excitement and all sorts of things. What are the most underrated neighborhoods? What's on the come up right now?
Speaker 8:You know, everyone sort of really wants, like, Noe Valley Mhmm. Pack Heights. Mhmm. Like, I think if, like, if you're sort of, like, looking in the Noe area, like, Bernal, like the the mat kind of the hills right next to it, Glen Park, like, you know, Sunnyside is, like, dramatically less expensive. Mhmm.
Speaker 8: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 Hill is 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.
Speaker 1:Mhmm. Well, where can people get in touch with you? How do people reach out if they're looking to Yeah.
Speaker 8:Talk mean, can Google me, Rohin Jorg and then find my email or just reach out to me on Twitter and I'm pretty active there. And, you know, generally I just share what's going on in the market over there.
Speaker 1:Fantastic. Well, we appreciate you taking the time to come chat. Thanks so much.
Speaker 8:Awesome. Yeah.
Speaker 1:Have a great rest of your day. We'll talk to you soon.
Speaker 4:Thank you.
Speaker 1: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.
Speaker 1: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. And without further ado, we have Eric Jorgenson, good friend of mine. He is the author, the publisher of the book of Elon.
Speaker 1:You so much for It sending looks fantastic. And I was particularly I want to get into the the book, but I I 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.
Speaker 1:How are you doing?
Speaker 9:Thank you for having me. I'm I'm honored to be here and extremely excited to put this thing out into the world.
Speaker 1:Yeah. Listen to that voice. You got a voice for livestreaming. Let's go. The microphone's helping.
Speaker 1:You got a good setup. It's good to you.
Speaker 9:Am about to get discovered right now?
Speaker 1:I think so. No. Of course, you've been online a million times. We everyone knows you. But maybe 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.
Speaker 9: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 the stream every day, and it just broke my heart that it was gonna get lost, get buried so
Speaker 1:this is the thing with Twitter. It's it's it's ephemeral, which is amazing, but there's no rediscoverability. We actually put out this account once, banger archive, where we just share screenshots of old tweets and they would go viral again. But Twitter doesn't 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.
Speaker 9:Yeah. I I 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 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 2,000,000. I've given away 5,000,000 more digital versions That's
Speaker 1:and so
Speaker 9:40 languages. Crazy.
Speaker 1:That's such a huge number. I feel like it's hard to sell a thousand books and you sold 2,000,000.
Speaker 9:That is a that is an unbelievable number for those that don't have like inside context in the book industry like Yeah. The I think the median outcome is like a few 100 and like 10,000 is top fraction of a percent.
Speaker 1:Yeah. Absolutely incredible. What was the strategy? I mean, Nival 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?
Speaker 1:Is it, like, top of Amazon? Is it on the New York Times bestseller list? Like, how do you even sell that many books?
Speaker 9:I cannot explain it other than to say it it has become like a word-of-mouth phenomenon. Wow. 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. Yeah. And it it's just sort of it's who doesn't the subtitle of the book is a guide to wealth and happiness.
Speaker 9:Yeah. Like, big TAM. Right? Yeah. Universal desires.
Speaker 9:Yeah. And new people graduate into like trying to figure that out for themselves every day. And I I I think it is, you know, this really rich dense collection of Naval who's a really really gifted sort of a distiller and articulator of some of the most important principles that make life Yeah. Make lives successful.
Speaker 1:What what principles from that book either stick out to you, are timeless, or maybe even underrated that you keep coming back to?
Speaker 9:I think I mean, the on the wealth side, like leverage Mhmm. Is is still an underrated one. I mean, you guys are living examples of this. Yeah. Authenticity is another one that, like, that word is thrown around so much that it becomes sort of a cliche.
Speaker 9: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. Yeah.
Speaker 9:He's like he's an artist, but he's a contemporary artist in the digital era. He's a really gifted designer. 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, he's doing things that nobody else is is doing in the art game.
Speaker 1:Do you think that being controversial is correlated with authenticity? Because if you're not authentic, you can be this very polished, one side, you know, many faced thing. You interact with one person in a certain way, another person in another way, 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?
Speaker 9:It's a great question. I bet there's two opposing archetypes. I bet there is a type of person that is extremely inauthentic in how they court controversy
Speaker 3:Mhmm.
Speaker 9:For the benefit of, you know, the algorithm or
Speaker 1:Yeah.
Speaker 9:Just being elevated by being attacked. Yeah. And I bet there's another p set of people that are authentic despite Yeah. Any headwinds or controversy that might come up. And I think the only way to probably tell the difference is to just zoom out and see who's been doing what for how long and in under what context.
Speaker 5:Mhmm.
Speaker 1:So how obvious was it that Elon was going to be the next subject? I imagine that the playbook that you ran, the process that you ran with the Naval book could apply to a lot of entrepreneurs. It's very it's a very interesting style where it's Yeah. It it it's it's high leverage. I I can only think I can only describe it as high leverage because you're you're standing on the shoulders of giants, 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.
Speaker 1:And you can do a lot of prework independent before you actually go in. Whereas some other books it's like, okay, this author didn't even get the interview with the person that they're writing about. Like they could sort of, you know, no one wanted this book to happen. And that's a lot harder. Right?
Speaker 1:So 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?
Speaker 9: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.
Speaker 9:My north star with these books is to just be as for the book to be as useful as possible to the reader. Mhmm. 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.
Speaker 9:I'm getting so much out of this. I feel like I'm getting personally mentored by Elon Musk through a few hours of reading about his most valuable and timeless ideas. Right? Yeah. And I think for those of us in tech, Elon's been interesting for a very long time.
Speaker 9:Yeah. 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 gonna end. Right? He was running on a very thin tightrope for a really long time with both Tesla and SpaceX.
Speaker 9:Yeah. And more recently, people have started I mean, Mark Andreessen and and Brian Armstrong maybe most famously have started asking the question, like, how does Elon do it? Mhmm. What is this? Why is he an outlier among outliers?
Speaker 9: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's 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.
Speaker 1: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've I'd learned about it, like, three months earlier. But but it really was a very a very controversial thing to do.
Speaker 1:The the you know the the 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.
Speaker 9:Yeah. There's just a couple there was a period where Jack Dorsey was running two companies. Yeah. There's period where Steve Jobs was running two companies. Yeah.
Speaker 9:And there's plenty of companies that are collections of meaningfully different companies kind of in one under one name. I I think it's kind of hard to extricate, like, what does run the company mean Yeah. 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 than, you know, Bill Gates running a company or Mark Benioff. Right?
Speaker 9:Like, the the motions that he dives deeply into are very different kind of on a per leader basis.
Speaker 1:Yeah.
Speaker 9:And there's an element of this that like and Naval points this out. I think it's super interesting. He's like, you are probably working harder on your company than Nival is or than Elon is working on any one of his companies just because he has this divided attention. Mhmm. So let's just say he's working eighty hours a week, but he's only working thirty hours a week on SpaceX.
Speaker 7:Yeah.
Speaker 9:Like, how is he able to have orders of magnitude more impact in those thirty hours than you're having with your seventy?
Speaker 1:Well, is sort of 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.
Speaker 2:Retired and Yeah.
Speaker 1:I mean now now maybe more focused, 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 and Elon sort of didn't have a direct, like, full time, you know, by the book entrepreneur just building a direct competitor in that one space fully focused. So I don't know. Maybe maybe that's luck. Maybe maybe things play out differently if if there was someone in that space, but it's clearly it's clearly worked out.
Speaker 1:Kinda end
Speaker 9:up conflating like Elon the person Yeah. Like Elon the core team around him and Elon the the symbol, frankly. And and especially at this point in his career, he's one of the most leveraged people alive. Right? So we are ascribing to like quote unquote Elon, what is actually the effort of tens of thousands of engineers and Yeah.
Speaker 9:You know, on the plenty of other employees and fans and supporters. And there's 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 like this rallying point for people to like organize around the values exemplified by this person.
Speaker 9:And I think that's 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 Yeah. Kind of arguments with people. You're not even really talking about the same thing.
Speaker 1:How how do you think about the the thinking in decades concept? You know, it's something that everyone in Silicon Valley says, oh, you gotta think in decades. And then Elon comes out with something that's like twenty, thirty, forty years away and everyone's like, no. We didn't actually want thinking in decades. I wanna know something that's gonna happen for sure in like five years tops.
Speaker 1:I'm thinking about this mass driver question, and I'm wondering, like, now that you've you've written this book, you've 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
Speaker 9:the moon pitch compared to previous eras? I think it's difficult to predict as are many things, but if his theory and his acting principle is that the future is arriving ever faster. Mhmm. Right? And so things that at our previous growth rate or technology trajectory seemed like they were thirty years away are actually now maybe ten.
Speaker 9:And it's really difficult to adjust for that like recursion factor.
Speaker 1:Yeah. Yeah. That makes sense. Yeah. Well, where can people find the book?
Speaker 9:Anywhere you buy books. Amazon, barnesandnoble.com Yeah. Target. It just came out like yesterday.
Speaker 1:Are you gonna do an audiobook?
Speaker 9:Yeah. The audiobook's out. I didn't read it. You got it. I'm sorry.
Speaker 1:You got this movie for pipes. Put them to work. Well Eric Jorgenson, thank you for joining. The the book is the book of Elon. You can go find it everywhere books are sold.
Speaker 1:We will talk to you soon Eric. Thank you so much.
Speaker 9:Appreciate you.
Speaker 1:To join the show. Let me tell you about Figma. Agents, meet the canvas. Your AI agents can now create and modify your Figma files with design system context in beta starting today. And our next guests are live here with us in the TBPN Ultradome.
Speaker 1:Thank you so much for taking the time to How join are you doing? Please, since this is your first time on the show, introduce yourself for everyone.
Speaker 4:I am Jenny Just, cofounder of Peak six.
Speaker 7:Yes. And I'm Matt Hulsizer. I'm Jenny's husband and also cofounder. Fantastic.
Speaker 1:Take us back in time. I wanna hear the founding story.
Speaker 4:Founding story.
Speaker 7:Yeah.
Speaker 4:Start. We both grew up on the option trading floors, Chicago and New York. Yeah. And we were at an sort of an infamous options trading firm called O'Connor and Associates.
Speaker 1:You were both at the same firm?
Speaker 4:We were both at same But in different different cities.
Speaker 8:Okay.
Speaker 4:Yeah. So super lucky to be trained there
Speaker 1:Yeah.
Speaker 4:When they did their merger acquisition, UBS.
Speaker 1:Who was in Chicago?
Speaker 4:I was.
Speaker 1:Did you ever go to Seres?
Speaker 4:Oh, of course. Still good. Seres is amazing. Yeah. Anyway, it's a bar.
Speaker 4:It's kind of modern these days.
Speaker 1:Oh, yeah? I worked at Citadel in in college and that was the place where we'd and hang out and they'd give you you'd order like a like a a rum and coke and it would just be a full glass
Speaker 4:of That's a rum.
Speaker 1:It was crazy.
Speaker 4:That's right. Yeah. Lot of sandwich to go with it. Yeah. Yeah.
Speaker 4:Yeah. Really good. Good fries.
Speaker 1:Okay. So you're in Chicago?
Speaker 4:Yes. So we're in Chicago. Yeah. We decide we started working together.
Speaker 3:Yeah.
Speaker 1:Were you trading
Speaker 4:at time? Equity options, both of us were.
Speaker 1:Equity options. Yeah.
Speaker 4:And then when they did the original Swiss bank Yeah. Joint venture, we were part of the team that went to start the OTC Okay. Derivative desk. Cool. There was just three of us.
Speaker 4:Yeah. There's a gentleman from Goldman who came in and so we're like, this is cool. We're in our mid twenties Yeah. Starting a business Yeah. You know, an entrepreneur.
Speaker 4:Yeah. And when things started going really well Yeah. And then UBS came in and they were moving to the East Coast Mhmm. We're like, well, we're not moving. He had actually just come from New York.
Speaker 4:Yeah. And my family's in the Midwest, so we're like, we're just we'll just do that thing again.
Speaker 1:Yeah.
Speaker 4:So that thing was to partner with a bank, that was our plan a
Speaker 1:Yeah.
Speaker 4:And do over the over the counter derivatives.
Speaker 1:Okay.
Speaker 4:Weeds twenty eight and a half years later, we've still never done it, we did invest really early in tech and education. Okay. And so we create we create a proprietary options trading firm
Speaker 5:Okay.
Speaker 4:Which is twenty eight and a half years old that has never had a losing year.
Speaker 1:Wow.
Speaker 4:And it allowed us to self fund Yeah. All the things we've done since then.
Speaker 1: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 how does that come together? Because I can't think of another who's ever done that.
Speaker 4:It's unusual for sure. Yeah.
Speaker 1:But It's a secret. Well, I
Speaker 7:think it tends to be about like our approach. Our approach was not to be smarter with our our algorithms. Okay. It was smarter with our business model. So there are plenty of businesses that haven't had losing years in the last twenty nine years.
Speaker 1:Yeah.
Speaker 7:They tend to be technology firms Sure. That are basically providing a service into the market, which is the approach that we I mean, we we we talked about ourselves as Wendy's or Walmart, Walgreens. Like, we're merchandisers. Yeah. Carry inventory and then deliver it to customers.
Speaker 7:We're not trying to take the the we're not disagreeing with customers.
Speaker 1:Mhmm.
Speaker 7:We're we're providing a service.
Speaker 1:Mhmm. And then on the investment side, what is out further on the risk curve for you? I mean,
Speaker 7:I think we've lost money in more ways than anyone you've ever had on this
Speaker 4:ship. Well Collectively.
Speaker 1:What is the nature of a of a of an investment that doesn't pan out? Is it just Oh. It's high risk and you know that going in or yeah.
Speaker 4:Well, there's a wide range. Obviously in our trading business, it's really systematic. Sure. We have an amazing team. Yeah.
Speaker 4:We educate kids right out of school into our model. Yeah. It's really rare that they would leave and be able to do the same thing because it is about the collective. Mhmm. That's interesting.
Speaker 4:But we started Yeah. A whole bunch of other businesses, of So Peak six today, based on what Eric was saying in your previous interview, it's a company of companies.
Speaker 1:Okay.
Speaker 4:So we have started or bought and turned around 15 ish companies at this point, and primarily in the back end technology space Yeah. In fintech Yeah. Definitely in Insurtech, which is relatively new to us Yeah. And EduTech. So those are the biggest risks we're taking.
Speaker 4: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. Yeah. And we started early enough, so it grew really fast.
Speaker 7:We have some doozies. I mean, I'll
Speaker 1:I don't want to dwell on it.
Speaker 7:Yeah. No. We'll refer. This callback is to your previous person. In 2008, we had it was a good year for us not because we were smart and short the market.
Speaker 7:Yeah. Jenny was like she's like, things are confusing. We should be in cash. And we were. So I was lucky.
Speaker 7:Well, she was right. The market goes crazy. And then we have a lot of cash. 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.
Speaker 2:Sure.
Speaker 7:So we are early.
Speaker 1:Yeah.
Speaker 7:So we interviewed two different people at
Speaker 4:the time And we're not investors at this point. We are traders. Yeah. So it's two different things. We are operators.
Speaker 7:Don't know
Speaker 4:for traders.
Speaker 7:We still don't know for
Speaker 4:knuckleheads. Yeah. Yeah. Okay.
Speaker 7:We get two people. We're gonna interview the two companies at a time.
Speaker 1:Yeah.
Speaker 7:One is this PayPal guy who's trying to do it and the other is the guy who was the chief architect at BMW. Yeah. The PayPal guy gets on a call on a call with us.
Speaker 4:With you.
Speaker 7:With
Speaker 4:me. Just to be clear.
Speaker 1:Okay. She You had a distance yourself from this.
Speaker 4:Yes. You know where it's going.
Speaker 7:I mean, if he's list if he listens to this, don't know if he'll remember because I think he was stoned out of his mind. Okay. It was the worst presentation I've ever
Speaker 4:heard. Like,
Speaker 7:this guy's never gonna
Speaker 4:build It wasn't about cars. It was about it was about the the train.
Speaker 7:He was talking about trains. Trains. Between trains. Electromagnetic trains. Yeah.
Speaker 7:Yeah. Yeah. Also be useful. Was like, what the hell are we talking This about
Speaker 1:supposed to be a business investment. Yes. I wanna hear the business pitch.
Speaker 7:And the other person comes in buttoned up. Right? German engineer.
Speaker 1:Yep. Amazing. Built these my entire career.
Speaker 7:A 100%. So we go with that person. Okay. Yeah. Nine months later, we find out that the one we invested in Yeah.
Speaker 7:When it rains, the cars catch on fire and explode.
Speaker 1:What? Yeah. That's a crazy
Speaker 7:not a good one. Yeah. That's not a good that's
Speaker 4:not That's a big bad downside.
Speaker 1:Yeah. Yeah. That makes a lot of sense. I think a lot of investors have had to really come around to the the the other pattern of thinking. I
Speaker 4:know That's right.
Speaker 1:Some investors that I mean, even on the other side, know I know an investor that passed on Tesla, but not but not because Elon was thinking too futuristic. He was thinking, well, all the cars are gonna be self driving and no one's gonna need a car anymore. So if this guy's just building cars, why should And I invest in and of course, the it was 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.
Speaker 1:What's the structure? Are you looking for a particular vintage, an age, a size of like meat on the bones of the company? And then what are you looking to do? Because there's when when you come into a new company, you can be transforming the business with AI. You can be focused on cost reduction, back office rationalization.
Speaker 1:Like, there's so many different techniques that you can use to drive value.
Speaker 4:Yeah. I'll I'll start. Maybe I'll start with Peak six Trials. Please. So at its core, we're entrepreneurs.
Speaker 4:Right? That's what we do. Yeah. So we're comfortable with that risk. Ironically, it doesn't make us super comfortable doing venture because
Speaker 7:Yeah.
Speaker 4:We're not doing it.
Speaker 7:Yeah.
Speaker 4: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. Yeah. We just started something called Peak Six Trials, which is an think about entrepreneurship and residents.
Speaker 7:Mhmm.
Speaker 4:We have it's, you know, like previous accelerators Yeah. Except for that we have the capital, it's already there. Yep. We have the resources, the tech resources, for example, legal compliance, whatever it is already there.
Speaker 1:Mhmm.
Speaker 4:And then we also have the customers Yeah. Because of APEC's fintech solution. That's our back end tech, powers
Speaker 7:Got it.
Speaker 4:40,000,000 customers today. So end consumers were b to
Speaker 1:b. Yeah.
Speaker 4:So there's a unique opportunity for fintech and sure tech type of young entrepreneurs who want to do something. That's how we want to make those bets. Mhmm. That will go into our operating company Sure. Scenario.
Speaker 4:And then, I don't know, you want to talk about the investment side where we take what kind of what kind of investments we're looking for?
Speaker 1:Yeah. Sure. Or even just the story of Apex.
Speaker 2:I'd love to
Speaker 1:know like Oh, great. How that came into the portfolio, what the process was like. That's I can tell it's already gonna be a good story. Yeah.
Speaker 7:Yeah. So there was a public company called Penson. Yeah. So we owned and operated a brokerage called Options House at the time. Yeah.
Speaker 7:This predates Wealthfront Betterment
Speaker 1:and Yeah.
Speaker 7:Robinhood, etcetera. And that business custody kept the assets, right, at at Penson along with a million other customers
Speaker 5:Mhmm.
Speaker 7:Retail customers.
Speaker 4:So we're in 2012 at this point. Sure. Yes.
Speaker 7:Yep. And we get a call from the CEO of the bank. This is the bank that holds our money, calls on a Friday. He's like, hey, you guys have some money and could you lend us some money for a little bit? Mhmm.
Speaker 7:It would help us a lot. Sure. I'm like, let me think about it. I gotta talk to Jenny. Yeah.
Speaker 7:She's like, we gotta that's not a good sign. For your for your listeners or watch your viewers Yeah. If your bank calls you and ask borrow more money Yeah.
Speaker 1:Like that's trouble.
Speaker 2:Yeah.
Speaker 7:Monday morning, we get a call from the SEC. There's fraud, announced fraud at the at the clearing firm. Wow. And we want you to put $70,000,000 into the business k. By Friday.
Speaker 7:Wow. Or we're gonna liquidate everybody. And
Speaker 4:that's everybody in the market. So think pre generation Robinhood for context. Sure. All those names out there. Yeah.
Speaker 4:Those middle tier names besides the big names.
Speaker 1:Yeah.
Speaker 4:Option South, our firm was one of them.
Speaker 3:Sure.
Speaker 4:They're all gonna go. Yeah. So thirteen days later
Speaker 5:Wow.
Speaker 4:We bought it.
Speaker 7:Amazing. Yeah. Announced fraud and all.
Speaker 1:That's wild. Yeah. Yeah. I've heard a number of these stories of, like, turning around a company when there is fraud. Mean, Strauss Zelnick sort of did this with Take Two.
Speaker 1:He'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.
Speaker 4:That's right.
Speaker 1:How are you thinking about cultural development generally? I feel like when I when I dig into different funds, there's fascinatingly different approaches. You know, the the 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?
Speaker 4:They are they are critical. Mhmm. Really difficult in times of COVID and changing work from home and all those things. Yeah. And as we continue to build new companies.
Speaker 4:Right? So, you know, at our firm that's over 28 years old
Speaker 7:Yeah.
Speaker 4:They are ingrained. Mhmm. It is a sense of urgency. It's a work ethic, like, it's 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.
Speaker 4:It's it's really fun to be in the markets Yeah. So it makes that easy. It's fun to be part of an entrepreneurial culture
Speaker 7:Yeah.
Speaker 4: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. But every time we take on a new company, it is it is a challenge for to try and integrate or have them stand in their own culture, which is also fine with us.
Speaker 4:Right? So if we we sit at the top and we have CEOs of each of these businesses, they are dependent quite a bit on the the peak six core, because it's 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 Mhmm. It's it's it's a hard road, because we've figured out such a rhythm.
Speaker 4:When you get in the rhythm, it makes each the acceleration go so much faster. The leverage we get with our people, with the culture is just really exponential. Yeah.
Speaker 1:Some people refer to it as like eustress, the good type of stress. Yes. Like it's a stressful scenario, but it gives you energy. It doesn't actually drain you. Yeah.
Speaker 1:And I feel like if you people get, you know, the runner's high. So running is very stressful for some people, but for some people it's it's invigorating. And I feel like if if, you know, being in the market at a tumultuous time
Speaker 4:Mhmm.
Speaker 1:Gives you more energy Yeah. During that day, that's something where you'll probably thrive.
Speaker 4:Yeah. Was going to say taking risk. Yeah. Right? Starting as traders and becoming operators Yeah.
Speaker 4:And then investors, like at its core, that that that trading, that heart and soul of trading and taking risk every day, all day
Speaker 1:Mhmm.
Speaker 4:Getting used to it, that isn't in everybody's DNA. Yeah. It is part of the reason why we like poker so much. We're try trying to teach a million girls and women to play poker.
Speaker 1:That's
Speaker 4:Solely to get these male dominated areas
Speaker 1:Sure.
Speaker 4:For the women to feel more welcome. But you have to be able to take that risk every day.
Speaker 1:Yeah.
Speaker 4:And the and the organization thrives on it. Yeah. Right? It's a little scary
Speaker 1:10 amazing female venture investors and they're all incredible poker players.
Speaker 4:Are they really?
Speaker 1:I would never sit down with They would absolutely smoke me.
Speaker 4:Well, the funny thing is I didn't play all these years. Yeah. When I started playing in 2019, it was a conversation we had. It was about our daughter, etcetera. But I realized I was like, wait, I've been playing poker my whole career.
Speaker 2:Sure.
Speaker 4:I just didn't know it. Yeah. It's the closest thing I'd ever seen to options trading. Yeah. So I was like, wait, is this what's missing?
Speaker 4:Because if we get who cares how people come into the puzzle? What the more differentiated their backgrounds are for us. Right? If you look at 1997, and he and I were partners. That's by the way, we weren't married at the time.
Speaker 4:Okay. We were together ten years before we did. Wow. So making that decision, that was a highly unusual decision to be
Speaker 7:chased me. I
Speaker 5:love it. I love it.
Speaker 4:Yeah. You wish.
Speaker 1:What are you looking for in a CEO? If I wanna come work for you and and work for one of your portfolio companies, what does it take to make it as a CEO?
Speaker 7:I don't think there's any like there's no one thing. There's no prescriptive formula. The number one thing we've learned because we've look, we've dealt with thousands of employees, CEOs, etcetera, invested, I don't know, hundreds, not thousands of businesses. Yeah. Self awareness is probably the most important thing because what's gonna it can get you in trouble.
Speaker 7:If you think you're really smart, like you better be really smart. Poker teaches you a lot of that. Sure.
Speaker 1:That's a
Speaker 7:good callback there. Mhmm. You have the Yeah. Self awareness. Like you control effort Yeah.
Speaker 7:You control attitude. Those two things you really do control. Mhmm. Like so hard work, right? You're going to be positive optimist.
Speaker 7:But awareness like like, hey, we are the best. Yeah. You know, by the way, these other people aren't that good, like you should think about it. Like Yeah. Constantly questioning where you're at and being humble.
Speaker 1:Yeah. Is is is self awareness around intelligence, the main, flaw for CEOs? Or 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. The CEO is a bundle of traits. I I 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.
Speaker 7:I wouldn't say I would not say lack of confidence is not necessarily an an issue. Yeah. Overconfidence is disaster.
Speaker 1:Interesting. Interesting.
Speaker 7:You get yourself in a lot of trouble because you know for sure Mhmm. That this is gonna happen. Yeah. When it doesn't, you you're in a you're in
Speaker 1:a world of hurt. Yeah. That happens. So so what are the signs that you're looking for to suss out if someone is self actualized in that way, aware of their their flaws, aware of their strengths, their weaknesses. How are you interrogating that in an interview?
Speaker 4:We hate interviews.
Speaker 1:Okay. How do you recruit that?
Speaker 4:It's hard. It's hard. We've 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
Speaker 1:As a
Speaker 4:student, probably. To see somebody. So if we can
Speaker 7:Okay.
Speaker 4:Get a student in December
Speaker 1:Mhmm.
Speaker 4:For two two weeks during their break
Speaker 5:Yeah.
Speaker 4:And see them, or we have a women's trading experience that's Sure. Eight weeks in the summer, anytime we get an extension of time, if we can I mean, the CEO's is is the hardest? Yeah. We they often come from within for us.
Speaker 7:Sure.
Speaker 4:Now, some of our CEO's did not. Yeah. But it is what our hit ratio, I think, on just cold interview, making it right, I think is really hard. So then, of course, it's connections Yeah. And recommendations and all those things.
Speaker 4:Because you don't know all of the different pieces of the puzzle. I think people get snowed all the time.
Speaker 1:Yeah. Do you have a a bright line between deal team, operating team? Like, who evaluate a great company to join the portfolio versus those who will be going and operating the businesses?
Speaker 7:We have a very very small evaluating team.
Speaker 1:Okay.
Speaker 7:Like this is the team. Okay.
Speaker 4:No. We have some really smart there's some lawyers and some analysts in there. Yeah. But at the end of the day so we don't have outside money.
Speaker 1:Sure.
Speaker 4:So it's it's ours and then our part our employees who have become partners Sure. Over the years. Sure. So that's who we're investing And on so but we are looking for any guidance. We are just we know we're not the smartest.
Speaker 4:Right? 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?
Speaker 4:But we're also willing we're 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 the that infrastructure side for us is new. And but we started early and we try and get smart and try and be surrounded by
Speaker 1:I wanna get to energy. That sounds fascinating. I wanna ask about sourcing. Are are you close with 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?
Speaker 1:Mhmm.
Speaker 7:Yeah. I'd say the good ones come from interpersonal relations. Sure. Which is why, like, in the age of AI, everything's gonna be automated, everything like, this really matters. Yep.
Speaker 7:Showing up in a studio Yep. Where you'll hopefully send us, you know, you'll say, hey, I an idea for you guys.
Speaker 1:That's why
Speaker 4:And vice versa.
Speaker 1:Yeah. Of course. Right. Of course.
Speaker 7:That I would say that's 99% of That's 99% of it. It wow. But it's worked pretty well.
Speaker 1:That's so interesting. I mean, yeah, we we 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. Have They an army of deal associates that are getting out there pounding the pavement.
Speaker 1:There's other folks who yeah. Just wildly different strategies. It's fascinating.
Speaker 4:Well, for being a very quiet firm Yeah. For a very long time Yeah. It didn't allow us to have what we now realize we probably should have been doing Sure. For a while, it's building those relationships. Sure.
Speaker 4:But it's been quick coming out, like coming out Yeah. 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.
Speaker 4:So like Absolutely. You know, it's it's easy to start, you know, they're not they're not perfect, but they rhyme Yeah. With the past. Right? So we're we're good at we're good at saying no Yeah.
Speaker 4:I would say.
Speaker 1:Yeah. Let's talk about the energy side. 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.
Speaker 1:Then at the same time we talked to, you know, Chase Lochmeller from Crusoe. He's building data center, putting up power plants today. Mhmm. There's so many other pieces of infrastructure, so many the supply chain is so complicated. Where is the opportunity?
Speaker 4:You want me go ahead?
Speaker 7:We like Crusoe. We're investors in Crusoe.
Speaker 1:Oh, really?
Speaker 7:Oh, yeah. No way.
Speaker 1:Oh, yeah. That's amazing.
Speaker 7:We've got
Speaker 1:a lot
Speaker 9:of investments.
Speaker 7:Okay. And I what is interesting in energy is it tends to be this. There's some individuals or individual companies that are doing some stuff that's that we see as transformational.
Speaker 1:Yeah.
Speaker 7:So I was very worried about energy.
Speaker 1:Yeah.
Speaker 7:Whatever happens with the war, we don't have any thoughts on that. Yeah.
Speaker 1:Yeah.
Speaker 7:But assuming that things are peaceful, like, hey, is it gonna be nuclear? Is it going to be Solar. Solar, etcetera. Geothermal is really interesting. So we're big investors in a company called Furvo Okay.
Speaker 7:Houston, Utah. Yeah. It's your your viewers should look it up. Yeah. It's it's transformational and it's it's today.
Speaker 7:Today. So it's built. They're going to deliver, I don't know, 500 megs in Wow. That's serious. 2027.
Speaker 7:Wow. Delivery.
Speaker 1:Enough for that that's the average meta campus right now.
Speaker 7:Okay. And remember, it's fracking. It's traditional
Speaker 1:Yeah. Yeah.
Speaker 7:Drilling, but not in traditional areas.
Speaker 5:Okay.
Speaker 7:Okay. So, like, more remote areas.
Speaker 1:Sure.
Speaker 7:Are there side effects? It's unclear. I don't think there are necessarily, but maybe there could be some seismic.
Speaker 1:Yeah.
Speaker 7:Sure. But, like, that's super interesting. And the people who are doing that, like
Speaker 1:Mhmm.
Speaker 7: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.
Speaker 7:Sure. Physicists, but it won't make the planet hotter.
Speaker 1:Yeah. Because net zero.
Speaker 7:So that's a good one. I think there's another company in Utah that we like a lot. We were talking to him earlier. It's Taurus Energy. Mhmm.
Speaker 7:And that is what effectively what you saw in cloud Mhmm. Compute is cloud energy. Okay. And so Taurus is a it's basically a it's a flywheel business.
Speaker 5:Okay.
Speaker 7:Like actually a flywheel. Okay. Like literal flywheel. Okay. Except it weighs about 3,500 pounds power.
Speaker 7: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
Speaker 3:Yeah.
Speaker 7:At the same time that everybody's, hey, by the way, OpenAI is gonna run one of their Sure.
Speaker 1:Sure. Sure.
Speaker 7:You know, one of their loops, then Yep. You're gonna end up drawing tons of power, and that's expensive for the grid. So what Nate has done and his team at Taurus Yeah. Is solve they're a balancer.
Speaker 1:The load balancer. It's the load balancer.
Speaker 7:Yep. And you realize there's actually quite a bit of power. Mhmm. How you actually balance the power is is the hard part, and he solved it.
Speaker 1:Mhmm.
Speaker 7:So they are operate operating today. Mhmm. We talked to him earlier. He's he's in a bunch of different states, and he's he's coming to a state near you.
Speaker 1:Yeah. I love it. Well, tell me more about Peak six Trials. Where can people get started? How do people apply or or join?
Speaker 1:Yeah.
Speaker 4:How does this work? Peak6trials.com. Okay. And we're looking for entrepreneurs who have ideas. Cool.
Speaker 4:And everything else is sort of there. You don't have to go and raise money. Don't have to spend time doing that. Think about the things that where your specialty is
Speaker 9:Mhmm.
Speaker 4:Is your idea.
Speaker 1:Yeah.
Speaker 4:Right? This is this is a place with AI. Like, we can do a bunch of stuff around you.
Speaker 1:Yeah.
Speaker 4:And interestingly, like with Apex, right, we have these 40,000,000 customers. They might want your product. Yeah. And if they don't want your product, that's also really good news. Yeah.
Speaker 4:So we short circuit all these things that take to say like, is this a good idea
Speaker 5:Yeah.
Speaker 4:Or not? You don't have to worry about the capital. You don't have to worry about paying your rent. We actually pay you a salary.
Speaker 1:No way.
Speaker 4:Yeah. So No. It's really nicely packaged Yeah. For someone. I wish we had it at the time, it would have made me feel better.
Speaker 4:Yeah. 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 this thing, not for us to own the majority of things. So the the way we've structured the deals are really creative, I think, and different than the marketplace has seen so far. So finding those people, right, those young entrepreneurs, or they may not be so young entrepreneurs.
Speaker 4:Yeah. They can be anywhere. But it's really I mean, I think it's super broad Yeah. With the fintech sort of space is. Like, everything's money.
Speaker 4:Yeah. 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 we're gonna pick Mhmm.
Speaker 4:12 to 15 for the first year and we're gonna see what we can do and see what we can pump through.
Speaker 1:That's great. Last question. What's the best way? I'm terrible at poker. What's the best way for me to learn and get better?
Speaker 4:Well, we have amazing teachers around the country Mhmm. Which is kind of crazy. We're like at 28 teachers. We have taught at like 360 companies. So you can actually bring us to your company.
Speaker 1:Oh, really?
Speaker 4:The banks, the technology firms, the law firms. Yes.
Speaker 1:Think they might like It's
Speaker 4:been wild Yeah. How people have picked it up. Right? Because it Yeah. First of all, we're not playing for money.
Speaker 4:We're actually teaching because these are people Yeah. Who know nothing.
Speaker 7:Yeah.
Speaker 4:But, you know, 94% of poker players 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
Speaker 5:I like that.
Speaker 4:To be doing this. Yeah. We're in 70 countries. Mhmm. We're in rural rural villages in Kenya, for So we are super quick, turnkey events, best events that are
Speaker 1:It's amazing.
Speaker 4:On on the
Speaker 7:pokerpower.com.
Speaker 4:Yes. Pokerpower.com.
Speaker 7:I love it.
Speaker 1:Yeah. Well, thank you both for taking the time to come chat with us.
Speaker 4:Yeah. Of course.
Speaker 1:We will close the show here on this camera. Leave us five stars in Apple Podcasts and Spotify. We'll be live tomorrow at 11AM Pacific sharp. Sign up for our newsletter at tbpn.com, and we'll see you tomorrow. Goodbye.
Speaker 1:Thank you.