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

You're watching TVPN. Today is Wednesday, March 25, 2026. We are live from the TVP Ultra Realm, the temple of technology, the fortress of finance, the Capital, Finance Capital. Sorry ramp.com Time is money save both easy use, corporate cards, bill pay, accounting and a whole lot more all in one place. We have a great show for you today, folks. We got Mike from arkprize coming on the newpinator. He did it. He did it. We'll talk about this later. We have Nathan, my buddy from Air Street Capital, Rohan Dhar giving us an update on what's happening in San Francisco in the housing market. Eric Jorgensen, the author of the book of Elon's Coming on. And then Jenny just from Peak 6 Investments coming on later. Thank you so much for tuning in today. Linear, of course, is the system for modern software development. 70% of enterprise workspace on Linear are using agents. So there's been a debate. Truth bomb dropped by Emile 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 going to have to put on the steel helmet for this one because this is wading into dangerous territory defending Benchmark. But my question is, how close are we to actually being able to forgive Benchmark? When is the right time? It's been a decade. Obviously the drama between Benchmark and Travis Kalanick was awful. I think everyone's against what happened. But the question is, what is a venture firm? It is its partnership. If the partnership turns over at some point, is it a new team? Do you get a second shot? Can you actually change the reputation? And so believe me, I get the Benchmark criticism. Travis is truly a generational entrepreneur and was on such an amazing run. Right. So he was attacking Jason.

0:00

Jason from Saster was reacting to our interview 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.

2:09

Yes. So our friend of the show, Owen McCabe over at FIN, AI and Intercom, 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, superior to Uber in literally every way that matters to consumers. Smoother, safer, more reliable, no chatty, weird, rude, rude drivers, private Quiet self driving car services are going to dominate their human driver, incumbents and own says tbt. When I think that's throwback to. Right, Throwback to when Benchmark pushed Travis out of Uber and can the self driving division that he started literally 10 years ago. And so this is what's so, so tricky about this, is that, you know, uber survived. It's 150 billion market cap. It's bigger than when Travis was ousted. But getting a 2x over a decade is not what I think people were expecting from Uber under Travis's leadership. And Lyft has fallen to just 5 billion. Like he won the capital war. And Dar has done a great job managing the business. But I feel like a lot of the success of Uber has been built on the foundation that Travis set up. It wasn't a complete reinvention. If anything, they just honed down the core business.

2:25

Yeah, just the thing that is holding the business back right now, at least from a valuation standpoint, is this big question right around self driving. How, you know, and Dara has answered this question, you know, thousands of times right now the strategy is to invest in self driving companies, partner with self driving companies, but not the same as like having, you know, having developed their own internal IP and product starting a decade ago and seeing where that would have been by now is, is just, it's rough, hard to think about.

3:40

Yeah. And so Uber is valued at 150 today. Something like that. Waymo was valued in February of this year at 126 billion. And so yes, Waymo's been working on self driving longer, but you have to imagine that there's another 50 billion of market cap if you have a series.

4:16

What would Waymo be valued if Travis was the CEO? Yeah, you would get some type of Travis Premium on it. Oh just. Yeah, just the market would be, would, would.

4:34

Totally, totally, totally, totally.

4:44

You have this sort of one of one entrepreneur.

4:45

Yeah, 100%. And just to sort of recap where things stand, I mean, Shervin Peshav been on the show as well. We've had like everyone from this saga in the TVP in orbit. Both Travis and Bill Gurley have been on the show. Shervin's been on the show. Emil Michael's been on the show. We've talked to a number of people that have been around this story and it's a fascinating one. It's one of the most interesting. It was certainly formative in my career because I got to Silicon Valley and this was the first big story that played out really so Shervin said, in my opinion, Gurley single handedly destroyed hundreds of billions in value. Travis and Emil staying in charge of Uber would have led to a Tesla sized win 500 billion 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. 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? If it was no longer the same, when had it ceased existing as the original ship? So some people might say 50, 50. Some people might say yes, it is the same ship because replacing one board at a time, the ship is the comm concept and you can swap everything out 25 times, it's still the same ship. It there isn't like, it's a paradox. There is no like right answer. It's a philosophical question, but it applies, I think to Benchmark because back when Kalanick resigned as Uber CEO on June 20th of 2017 after investor in pressure, after investor pressure that included Benchmark on that exact date. Benchmarks GP roster was bill Gurley, Eric Vistra, Matt Kohler, Mitch Lasky, Peter Fenton, Sarah Tavel. Today the partnership has changed dramatically. The only two that remain are Peter and Eric. And you have Chetten, Ev Randall and Jack Altman, who are new to the partnership post the Uber scandal. And so it's not a full ship of Theseus, but only one third of the original 2017 partnership remains. And my question for those who remain reluctant to forgive Benchmark is like what happens if Peter and Eric retire or leave at some point and the full ship of Theseus is complete? Like maybe yield ship right now, right

4:49

now, 40% of the 40% of the partnership, was there 33%?

7:59

Oh, I mean, I guess two out of the five.

8:04

Yeah.

8:05

So two out of the five, because they've added three. But only one third of the original partnership remains.

8:06

The question is, did Chitan, Everett and Jack come in and as part of the interview process, say, like, you're absolutely right.

8:11

I mean, to defend

8:19

two out of

8:23

the three, Ev had just graduated from college. Like, he was truly, like, not involved in the Uber scandal. And yet, you know, people will visit

8:24

upon him knowing Everett and Zach. Yeah, I'm sure. I'm sure during the interview process, they were like, I, you know, the storied firm. Yeah, I'm excited to join, but we can never do.

8:32

Yeah.

8:45

Never do anything like that again. And so, and so one, one question that's worth asking is. It's like, is the firm that did this and ultimately, you know, stained this, this storied brand and has certainly suffered the consequences. Right. They've put up, you know, incredible returns since then, but I'm sure they've missed a lot of deals that would have made their returns even better because of that kind of narrative around the firm. And so they have. They. I would say, you know, Emil, Michael and others are upset that they're doing great deals at all.

8:46

Yeah.

9:21

But I think it. Is that a question I have is like, are they. If they're in a situation again, Right. In the same situation kind of situation, are they more. What decision are they more or less likely to make? Right. I would argue, like, they are probably less likely to. I would think so go against the founder, given. Given how this entire situation has played out.

9:21

Yeah. Yeah.

9:44

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. I'm sorry. But it's basically that every partner at Benchmark, it's an equal partnership, so every partner was going to make a clean $1 billion. They were all going to be billionaires from this one deal. And it was such a power law that there was no path to becoming a billionaire. From the other investments, most likely, you see the endless 24.7hit piece pile stack up, and you got Mike Isaac bloodhounded at the New York Times writing books they're turning into movies. It's getting rough. It's getting rough.

9:45

Mike Isaac's at your door.

10:38

Yeah, Mike Isaac is at the door. The barbarians are at the gate and you're like, I'm either a billionaire or I'm going back to a paltry 10 million. And I can't do that. I can't do that. And so they freak out and they're like, we got to salvage this thing. We got to just push it out in the public markets. We got to get out of this name. And so they basically just. It's just too nerve wracking. And yeah, it's not a strong steel, man. But I think, I think that's a little bit more of what happened than like taking a stand on, like, oh, like this particular thing that happened was so egregious. It was more just like, okay, like, wow, all my money, like 99% of my net worth is in this asset. And it's looking like it could be a zero because Lyft is coming from behind. There's a whole bunch of VCs that are piling into that. The narrative is totally flipping. There's a boycott Uber, like, and everyone's like, ah, what's going on? I got to get out of this. I got to salvage this. 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, you know, ship Theseus process, maybe it happens. I don't know. Would Delian accept that argument? Probably not. Would Emile? Probably not. But they're not making it any easier with the Manus investment either because there was a world where it was like, okay, yeah, the Uber thing happened a decade ago. The partnership is basically entirely new and they're focused on.

10:39

But it's. But it's not there yet. Yes, it's just not there yet.

12:07

It's not there yet, but still there.

12:11

I think you can rewrite this in five years.

12:13

Yeah. You made this point that it's too early to call this, but.

12:17

But that I think it's directionally. Given that the firm is still putting up great returns. They've gotten to a bunch of great companies over the last five years. I think we are on a path to the benchmark. Well, yeah, Venture Lazard, the venture ship

12:22

of Theseus and vc. Bragg said Airbnb has no homes, Uber has no cars, and Benchmark has no partners. Of course, that was an exaggeration, but they did get down to just three partners, which is very, very small for a venture capital firm. Some have dozens of partners, but different strategy and we will see where it goes. Anyway, let Me tell you about Applovin. Profitable advert Easy with Axon AI. Get access to over 1 billion 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 drinks that scale from one GPU to hundreds of thousands. So Sora, rest in peace. Sora, the app is leaving.

12:40

Ev is in the chat.

13:21

There he is.

13:22

Class of 17 represent.

13:23

Yes, yes. Ev was chugging beers while Uber is getting ousted. Do not visit the sins of the father on the son. That's what I would say. Ev not guilty.

13:25

Ev was a Boulder.

13:35

Yeah, he was hanging out.

13:37

What happened senior year? What happened?

13:38

I think EV deserves a fair shake and should not have to bear the

13:45

cross from the question. The real question, do EV and Jack pull a benchmark and force out the original partners? They don't have the legal control to do so, but neither did they during the Callan expire.

13:50

At this point, Ev is probably already getting calls from Sequoia to come be the senior steward. You know, he's on a meteoric rise. We're really all over the place today. Anyway, Sora is now. Is it still in the App Store? I think it's like the announcement was that it will be leaving the App Store.

14:05

Millions of people have made content on the app. You have to leave it running for some amount of times.

14:25

There's a phase out, but the announcement. And now it is. It is going out. And there's a. I have a bunch of takes on this. Obviously this is not the end of video creation for OpenAI. This will be rolled into ChatGPT. I imagine Tyler Hodge put it well, bullish. Killing products quickly is hard. Almost no one can do it. It's a good sign for OpenAI. They're consolidating in many ways. It's like last week you heard about like the code red was like a month or two ago. And then it was like, we're refocusing. And then it's like, here's step one of refocusing, like a single app that we're gonna push everything together. And also I just, 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. Let's see what Dax said. It's lame to see all the people saying, ha. I called it. I need knew Sora wouldn't work. Yeah, duh. Because everyone 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, 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 quote of like people saying, ha, I called it. I knew SORA would work. That is not how I interpreted the vibes around the Sora launch. Like, I went back and revisited the essay that I wrote. On October 1st, we had the slop versus farming debate. I was really on a tear back then. Slop is bad. We, the timeline, don't want to be pigs at the trough. We don't like it when tech leaders treat us like farm animals. But we love farming. Farming is lindy. We, the timeline, want to return to a world where we are filling up troughs with slop on a daily basis. I guess. So between Google, DeepMind, Meta Superintelligence and OpenAI, we now have three different variations on AI video products, each met with slightly different responses. So the, yeah, the interesting thing here is that like Google has been like charging ahead, launching it. 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 vibes around both Meta Vibes and Sora were like, this is going to one shot humanity. They're like, this is going to be too successful. Yeah, that was, it was like, it

14:30

was, it was like a entertainment doom loop.

16:49

Exactly.

16:52

You could imagine.

16:52

Exactly it.

16:54

Just getting so good at generating the next thing that you would want to see better than even a billion humans on Instagram.

16:54

Yes.

17:02

Could do. And that's not what we've seen.

17:02

Yes.

17:06

So far.

17:07

And so like my big question was, was like, will this actually be sticky? Will people like this? And at what rate? I mean, I read, I read LLM generated text daily, but I also read a ton of not LLM generated text. And my, my ratio has grown exponentially, but it hasn't gone to 100%, nowhere near it. Like probably 5% of the text that I read is LLM.

17:07

I mean, we should actually revisit how we were processing it during launch when it was, you know, rocketing.

17:32

We should just throw on that three hour stream and just watch them react to how our text from that day.

17:38

But even at the time I remember saying very obvious that they built like a very cool creative tool.

17:43

Yeah.

17:49

And they have the potential to see a network with this. There's all this, you know, novel content. They had they had allowing creators and, you know, people like Sam to allow people to use their, their ip. Yeah, it was very, very well executed launch. But even from the beginning it was like, okay, obviously cool, creative tool. It's a totally different ball. You know, this like come for the tool, stay for the network has been like an enduring. It's Chris Dixon strategy. Right. Chris Dixon probably wrote that in like 2014 maybe, or. Yeah, like a long time ago. Over, over 10 years ago.

17:50

Yeah.

18:28

But just because you build a tool that is attached to a network like that jump is just really, really, really, really tough.

18:28

Especially when there are are three or four or five serious networks that are at scale that can on day one, support the format of the file that is produced from the model. So in a world where generative AI video came out not in a MP4 file or an MOV file, it came out in some sort of format that could never be uploaded to Instagram reels. Then you have a chance to build a network and run away with it. And this was the story of Instagram. Like Instagram just had better support for images than Facebook did. And then vine had support for video literally before Instagram. So Instagram, it was like, I have a video on my phone. It's cool, I want to share it. Sharing it to Instagram was not possible. Now on day one, you generate an AI video, you want to share it, you can share it on TikTok.

18:36

Yeah. It's just the incentive. If you created an amazing video on Sora.

19:30

Yeah.

19:34

What is the most logical thing to do if you're a creator and you want reach post it to Instagram? There's just naturally, there's billions of people there. There were millions of people on Sora and a lot of energy, momentum.

19:35

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 should talk to the person that's the entrepreneur behind that project because I would be interested to know what the stack is, because I imagine it's not just going to a single gen AI app. I imagine that they have a whole pipeline of workflow in place to actually generate that. And so we're at this weird moment where 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. 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. Yeah.

19:46

It's interesting to think about Google's strategy with video. Even Google was like, we cannot operate this for free at scale 250. John, you were. No, that was the discounted rate.

21:07

Oh, I think I'm at 500amonth or something.

21:21

It was like an entry to start. It was like $250 a month.

21:23

And it was.

21:26

And then it brutally.

21:27

Weight limited. Like.

21:28

Yeah, even with.

21:29

We were.

21:30

We were laughing at this because three a day. I remember we'd be like at the gym in the morning, you would fire off a couple prompts.

21:31

Yeah.

21:38

And. And then you were like, rate.

21:38

I hope I got it right.

21:40

Yeah, I hope. Wouldn't get it right. Then you were rate limited. And you're like, wait, I'm rate limited on a. On a $250 plan that's going to jump to 500. You're probably paying. Got to check the ramp. Check our ramp. It's probably paying 500amonth still.

21:41

No, seriously.

21:55

And that's Google with all this cash.

21:56

Literally.

22:00

I mean, it's an insane data advantage

22:01

with YouTube and that. Let me tell you. Rate limits kill retention. Like, nothing is worse if you're in Instagram. The endless scroll exists. TikTok, you can scroll endlessly. You can use the. Imagine if TikTok was like, after five minutes, you have to close the app and come back in 20 minutes. Like, how successful do we think that would be? It would be a disaster. And that was the experience for Both Sora and VO3, where you would fire off a prompt and it would be like, okay, come back in a couple minutes. Take me a while to cook. And then. And then you fire off five and it's like, okay, we're doing no more for today. Like, and then. And then the next day happens and you forget about it and you. And you go on something else. So clearly the compute constraints 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 code gen, like enterprise workflows. And it's maybe more boring and less viral and less controversial, but it's where the compute needs to go. And so I think you're going to see the chips be moved around inside of all the labs to like compute will find the most optimal output. Like the tokens of the most value will always be the ones that the compute flows to. And as a lot of people predicted, like just endless random generations that aren't quite dialed yet. Even the best video models, like they're just not there. They require a lot of work. Is not the same as where we are in terms of knowledge retrieval, where we are in terms of code gen. It's just way more valuable. So 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. Thank you guys. And let me also tell you about Cisco. Critical infrastructure for the AI era. Unlock seamless real time experiences and new value with Cisco market clearing order inbound. You said what did I say?

22:03

September. People overestimate how much brain rot happens in a year and underestimate how much brain rot happens in a decade. So yes, yes, we're still so.

24:00

I mean, I'm using brain route pejoratively there, but I do think that like this move does not really bend the curve of just AI generated content. But I still think it's like a slow rollout. Like it's fast in the sense that we went from no slop on the timeline to lots and we went from actually zero. It was like one. One cool AI video. Harry Potter, Balenciaga was like entertaining to general people. And now we get like five and then we get like next year we'll get like 20 and then eventually it'll be like hundreds and it'll be like, oh yeah, I'm actually into that. Like people are into cartoons and people are into CGI movies and superhero movies. Some people will be into it, some people will never like it. Some people will always say, I want a black and white film from the 40s. That's what I want to watch. And these roles. So the diffusion of this stuff will happen. Should we revisit we?

24:10

Davidson says, what is this? Y' all are worried about the wrong open claw.

25:03

This is a good post.

25:08

This is the open claw that Ev Randall was worried about in 2017. He was not thinking about, was White

25:10

claw invented in 2017? When did white Claw get founded That's a great. I feel like it really took off. It had a fast takeoff.

25:20

Yeah. 2016.

25:28

2016. Okay.

25:29

There's a very good chance he was an early adopter.

25:30

He might have been an early adopter of openclaw. It truly was. I'm calling it openclaw 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. Sentry shows developers what's broken, helps them fix it fast. That's why 150,000 organizations use it to keep their apps working. I got a story for you, Jordyn. 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 not kidding about this. I actually saw this. I took a picture. I can maybe send it into the chat, but I can just show you because I'm driving and I just see this.

25:32

Like Billy Bowman.

26:17

Billy Bowman. I don't know. I'll send it into the. To the chat so they can pull it up. Let me see. Production. Here we go. But anyway, it is a remarkable story because Fiverr is running one of the coolest out of home campaigns, like just from an out of home inventory. I didn't know you could do this. We can pull up either my picture or we can pull up.

26:19

Let's pull up this video from KTLA 5.

26:41

KTLA 5 had a video breaking down. What's going on? Let's watch this and then we'll react to. To this. And while the team pulls that up, I'm going to tell everyone about Label Box, RL environments, Voice robotics, evals and expert human data. Label Box is the data factory behind the world's leading AI teams. So let's pull up the KTLA 5 report about AI coming for Hollywood. The mysterious sign along the 101 underneath, a logo for Fiverr and a search box, it says, find the best AI directors. It's a brash, bold statement. Brash, bold.

26:44

Coming for Hollywood.

27:20

Coming for Fiverr has made a name

27:21

for itself 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.

27:22

This Billy Bowman guy is one of

27:30

the directors that you can hire. He's based in Sweden. He's made AI videos for Google, Universal

27:32

Music Group and others.

27:37

As you know, AI really hasn't taken

27:39

over Hollywood yet, but it certainly crept

27:41

into commercials brands like Google and Jeep. Rolling out AI on national campaigns.

27:44

Many are slowly are slowing rather to

27:49

see the 30 foot sign which went up over the weekend. I first noticed it in traffic yesterday

27:51

morning after someone was so entranced they rear ended somebody.

27:56

It's causing accidents.

27:59

Yeah.

28:01

So interesting.

28:01

AI director. Yeah.

28:02

So it's basically someone who puts the prompt into the machine and chooses, is Fiverr gonna pay?

28:04

Just put the prompt in the box, buddy.

28:11

Fender bender. That's a great question.

28:13

Yeah, yeah.

28:15

Can they be held liable for such a distracting sign?

28:15

I didn't, you know, blush with money. Whether or not it is a bubble, like you can debate.

28:21

That's interesting because Fiverr is not one of those companies.

28:27

KTLA 5 is not prepared for it not to be a bubble.

28:32

So Fiverr's market cap now is $560 million. And that's down about 95% over the last five years.

28:36

Where are you seeing that? I'm seeing 350.

28:45

Sorry. Yeah, 359. What did I say?

28:47

500.

28:51

Oh, sorry. So it's a $360 million company today, down 95% from five years ago. It started selling off in 2021. Sort of pre chatbots. So I think the AI narrative might be a little bit overblown there. It did IPO around this price. It was a $700 million IPO, I think maybe $1 billion 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,

28:51

generate AI is very, very, very good at $5. Creative work. Exactly $25. Obviously the prices go well beyond $5 since. Since, since the early days. But in terms of the kind of projects that I always use Fiverr for AI, just one shots, all of that.

29:27

And the nature of Fiverr is like, you have to define your task in a prompt. It's not, it's not, oh, have like a long conversation, get drinks with somebody.

29:45

Yeah, that was often. And the better bottleneck. That was the bottleneck.

29:53

Yeah, totally.

29:57

It was like, okay, I need to do this task. I need like 10 minutes to like, properly 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 a few times, kind of iterate, hit my

29:57

rate limits and then fire back up. Yeah, I mean, it was always a bottleneck. I remember as an entrepreneur, I found out about Fiverr and I was like, this is amazing. I can get random stuff done for five Bucks. But the time commitment, actually finding the right person, making sure the reviews are good, it wound up being hours of work. And if you have a consistent flow, you're better off just hiring a person. So they got kind of squeezed in the middle.

30:12

The market is not excited about Fiverr right now. They're being valued basically at four times ebitda.

30:34

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 nanny all the AI models because it is a hassle. As you described with me and VO3. I was sitting there like, okay, I fire off four prompts, then I go back. It's way better if you're on the API and you have Higgs Field wired up and you have Runway ML and you have access to the Chinese model Cdance, 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. It's not actually at a word prompt.

30:43

Here's, here's the main problem with the campaign.

31:28

Yes.

31:30

Is that Billy Bowman is a real person with his own website, with his own Instagram. You can just go and reach out to him. Which is interesting because like the primary issue with, with these labor marketplaces like Fiverr disintermediation, if you, 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. And it's very different than a platform like Uber where you don't necessarily want the same driver every time because they're not around you and all these things. And so the reason that, that that the Fiverrs and the upworks of the world and there's been a bunch of other like engineering focused marketplaces just have never reached like insane scale. Like Uber is because of the disintermediation. And this campaign is effectively an ad for Billy Bowman, who you could just go hire today.

31:31

Yeah, disintermediation 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. 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. 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. 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 787s and 777s each with up to 12 of these brand new rows. So what do you think, Jordy? Is this the way I was telling Tyler Cosgrove, who is out of the studio today? He's in Washington, D.C. he's got to demo this. 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.

32:28

United has pretty good pace. They've been quick to.

34:05

Do you think Tyler could get on this tomorrow or today? He's going to the airport today.

34:08

I think if Tyler's resourceful enough, he could just. If he ended up in a row, two empty seats next to him, he could just figure out a way to detach the armrest. Locking this.

34:12

Yeah.

34:22

And just kind of. Kind of build your own.

34:23

Yeah.

34:24

They might have to land the plane and arrest him.

34:25

Yeah.

34:27

But potentially worth the risk.

34:28

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 languages we use.

34:31

I'll trade you an app for your seat.

34:45

I'll trade you an app for your seat. And somebody might be like, that's amazing. I don't have anyone that can vibe code for me. This is too good now. I'm sorry.

34:46

Brian Peterson says now we just need to put stairs on the food drink carts. 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.

34:54

But this is wild.

35:10

Good.

35:12

I don't know. Starlink, a relaxed row, a dream. 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.

35:13

John, you need to work on fixing Bombardier's stock price.

35:25

I don't think it's related. Oh, apparently Air New Zealand launched this in 2010.

35:29

No, it is related because he should help them build out their pipeline.

35:33

Well, he's just pumping his bags because he owns a property in Ireland. How do you get there? You got to fly on United. So, you know, one hand washes the other. On this. He's, he's talking his own book. 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. Railway is the all in one intelligent cloud provider. Use your favorite agent to deploy web apps, servers, databases, and more, while Railway automatically takes care of scaling, monitoring and security.

35:38

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 in the afterlife.

36:11

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. These are the little metal hooks that are installed in every car in the backseat for child seats. And so child seat requirements mean that you have to have a car that has these. And 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 affordable as, you know, just a normal sedan. They used to be able to just throw four kids across and maybe that was less safe.

36:23

Regulation killed the birth rate.

37:23

People actually say this. People say that child seats have saved like a million lives, but then they've stopped 10 million from being born. 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. 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 wheelbase version of the Model Y. I hope they bring that to the space.

37:26

People are saying, make a minivan. Elon Musk. Elon says something way cooler than a minivan is coming.

37:58

What do you think it is?

38:03

And people are speculating. Garcia here.

38:04

I think it might be a data center.

38:06

Tesla.

38:09

I think you might be like, there's another data center coming.

38:09

Chip Fab.

38:11

Yeah, Chip Fab. He's like, you're going to be able.

38:12

I'm going to end.

38:14

You're not going to Texas is going

38:15

to change the child labor law so that instead of worrying about bringing your kids around, they'll just go work in the news. No, they're in the fab.

38:17

They're in the fab Clean room. They're in the clean room.

38:24

They're fully stuck.

38:26

Suited up. Suited up.

38:26

They're making chips. But no, people are speculating. This is very cool. Gen AI has been amazing for car enthusiasts to create basically their own concept cars. These look very, very cool.

38:28

We were talking about.

38:39

I mean, it's funny. Make a Tesla that look. Make a Tesla version of the Rivian.

38:40

Yeah.

38:45

Because it looks exactly like it. But let's. Let's get into some of the speculation. So, okay, what are people saying? Cyan Banister says an RV. That could be fun. Arthur McWhotter says, I can't wait for the next roadster unveil. Elon was teasing. It was on Joe Rogan. Right. This concept of maybe it'll fly. And I think what Elon could be. Could be getting at is picture, picture a roadster. Not a great family car. Hard to put kids in a sports car. Some of them, you technically can, but it's so uncomfortable and kind of chaotic. Very few people would.

38:46

Yeah.

39:21

And I think what we could see is the roadster comes with five kind of like, you know that Fury collaborative combat aircraft from Mandurah.

39:22

Yes.

39:32

What if it comes with, like, up to five little mini roadsters?

39:32

Okay.

39:35

Roadsters.

39:36

Okay.

39:37

That can. That are just trained to autopilot behind the primary roadster. So you can be in your sports car.

39:37

Yeah.

39:43

And then however many kids you have are in the mini drones following.

39:43

That'd be fun. What about a Chinook heavy lift helicopter with two massive rotors that can lift your roadster. Off the ground.

39:47

Yes.

39:58

Technically a flying car, then yes. Anyway, let me tell you about phantom cash. Fund your wallet without exchanges or middleman and spend with a phantom card. I have a question for you, Jordyn. Are you running the new AI model? It's on Cowork. 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. You can run it on cocaine. You can literally go to cocaine and run it. What a great copypasta. This is one of the funniest formats. But yes, the war for copilot and cowork is heating up. We gotta find a new term. I think people have been really, really fighting.

39:58

Well, I was telling Microsoft they should just name it Coco.

40:39

Coco.

40:43

Microsoft Copilot, Cowork. It's just Coco.

40:44

Cocoa would be good. There's a few different options. I think I prefer the non anthropomorphized AI names, although they are a little bit colliding in the namespace. I have been a fan of. Of the Codexes and Coworks and Copilots. Those feel more collaborative to me and they feel more like tools than the Bards and the Ceres and the Alexas and the Rufus and the Sparkys like that. That's just a different vibe. And I think that if we're living in a world where people are going to form strong relationships with these tools, introducing them truly as tools is probably.

40:46

Let's see what's going on with qvc. Let's pull up this video.

41:30

And we also have one of our guests joining early at 11:50.

41:35

No, he's going to be joining. He'll be ready to join in an hour.

41:38

Are you sure?

41:43

Yeah. Okay, let's check the production team because I've already texted.

41:44

Okay, cool.

41:49

We'll continue for the next 15 minutes.

41:49

Fantastic. Well, take us through the next story. What do you want?

41:51

Q River says qvc basically reinvented live streaming decades. Invented live streaming decades ago. Goes 24. 7. They invented live TV. Goes 24. 7. A good 80% of the show is just the host going on long personal digressions. People watch it as background heavy parasocial element host know the callers. 95% of repeat buyers. It's 100% twitch for grandma's. Let's pull up QVC.

41:54

And with the submarine, I wanted to tell you that I got that peasant blouse with the tassels. Yes. And I used to wear the tassels on my pasties do you know what pasties are?

42:20

This is. Okay, ridiculous.

42:33

Do you know what.

42:35

What pasties are?

42:36

Yes.

42:37

Okay, well I have to move on.

42:38

We're moving on.

42:41

Let me tell you about 11 laughs Bill 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 going to deep dive ARC AGI today and Gemini 3.1 Pro has done very, very well with a more capable baseline. It's great for super complex tasks like visualizing difficult concepts, synthesizing data into a single view or bringing creative projects to life.

42:42

SpaceX aims to file IPO as soon as this week. Yes, I know everyone is excited for the S1 particularly. I think people will be focused on Xi.

43:10

Yeah.

43:23

What they have going on, I think that.

43:23

Are they going to have to break it out in the. In the S1?

43:26

I would assume so.

43:29

This is the first time we actually see the economics of inference, the economics of foundation lab. Even though yes, they are at a

43:30

smaller scale to read too much into into it because they've been investing so far ahead. Yeah.

43:37

And yeah, I just think that like there is a world where we get broken out financials that you can dig through and you can understand based on 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 economics, different pricing regimes. I mean the true frontier, the models that are dominating Arc AGI which we will talk about in 15 minutes, those command a premium, a price premium and there's a wild difference between charging 15 bucks per million tokens versus $2 per million tokens.

43:44

So it will be remember I think it was in Q4 of last year if you looked on open router, GROK was what had. I think it was like Grok fast, had a ton of usage. People are like okay, why is this happening? And part of it at least I believe was because they were subsidizing it. Well okay, so here's what I think. 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 try to aim for the company to actually go out on April 20th for 20.

44:31

Really.

45:12

And I think it is possible if he so fast the ticker, we'll see what the ticker ends up being. But I think some people would like knowing Elon's very millennial sense of humor. I think the ticker S X is.

45:13

You think so?

45:30

Plus the April 20th IPO. I would assume that is a real prediction.

45:30

You're not trolling.

45:37

I'm not saying. I'm not saying I would bet on it, but I think there's like a. I think there's. I think there's. I would put the April 20th at maybe like, you know, 30% and then the ticker may be down at. Okay, well, 10% call.

45:38

She has. When will SpaceX officially announce an IPO? Before June 1st. Which April 20th would be before June 1st.

45:54

Yeah, I'm not talking about. I'm talking about like list. Actual like listing day. Like the day of the ipo.

46:01

Yeah, this is just announcing the ipo,

46:06

which I don't even know if they haven't even confirmed.

46:08

This is now. This is currently in. In the scoop in the scoop thing. So they haven't even.

46:10

Scoop.

46:15

You said they. So the.

46:16

Wait, John, did you say scoop?

46:18

Yes, this is a scoop from.

46:19

What is this?

46:22

Doggy Dog.

46:23

Can we go to the wide angle?

46:24

We got Katie Roof, Scoop Master.

46:25

We have a new I award her

46:28

the first TVPN Golden Scoop.

46:30

The Golden Scoop award.

46:32

Do you want to show her the scoop?

46:33

I don't want to pick it up yet.

46:35

Why not?

46:36

Okay, we can.

46:37

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 D. 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%. B B B K S. Why is up 4.8%? Lunr is up 4.1%. Every stock in the space we're working

46:39

on is award show. The Scoopies, the scoop, the TPP and Scoop.

47:08

I think Katie Roof is a lock.

47:13

I mean she's in. She's a front runner for sure.

47:15

Putting on a generation generational run.

47:17

Front runner for sure. Yeah. It's so funny. Incredible moment for the retail space investor community because they're just for some reason people, anytime you get SpaceX repricing, they're like, well, this other random company that happens to be technically on the same market map definitely deserves to be worth 7% more. More.

47:20

Yeah. I don't know. I was as skeptical about the rest of the lunar economy for a long time. It felt like winner take all. It felt like SpaceX was running away with it. 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, to throw money at competitors. 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. I don't know what you're talking about.

47:45

I don't even know what you could be talking about.

48:23

It's an ice cream scoop. It's an ice cream scoop, people. Get your mind out of the gutter,

48:25

out of the gutter.

48:31

Head over to Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents.

48:31

Okay, Casey Hammer is worried.

48:42

What is he saying?

48:44

He's worried.

48:45

Why is he worried?

48:45

He's stressed.

48:46

Why is he stressed?

48:47

What I worry about is a generation of talented experienced engineers being too rich to work.

48:48

So if you're worried about being demotivated by your incredible SpaceX liquidity, you have to do what I recommend, which is the Brewster's Millions approach where you have to spend all the money in 30 days without telling anyone why you're doing it. This is from the 1980s 1990s comedy called Brewster's Millions, which I highly recommend you watch. In it, a man is gifted an inheritance from a wealthy uncle or father figure grandfather and it is conditioned on the fact that he needs to spend something like $30 million in 30 days without telling anyone why. And he can't accrue assets, so he can't go and just buy car to throw parties and give money away and spend money wildly. And it's to teach him that money does not bring happiness. Of course. And I think that's the solution to this. 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.

48:53

Here's why I'm not worried.

49:51

Why are you not worried?

49:52

Because I think that these ultra talented, hard working engineers having some liquidity, let's say someone's been there for some number of years, they have 5 million liquid, they buy a nice house somewhere and then realize, hey, I've got a nice nest egg, I can keep working on crazy moonshot, I don't have to go join, you know, the, the, the, you know, historical example would be like work on the hard thing or work on enterprise SaaS and I think this just will give people more confidence to work on the hard thing, the thing that might have a 5% chance of success, but if it's successful, has a tremendous impact on our country and things like that.

49:53

It might happen for some people, but in general I do think that there is this liquidity wave coming. Dalian talked about on the show yesterday. At the same time, 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. And there's always been a way to access some of that capital either through a loan from a bank. And you're obviously more credit worthy if you own a bunch of SpaceX stock and going up.

50:42

And yeah, a bigger issue for the kind of space economy overall is just the blue origin. People who like didn't they have like way more like they didn't. They didn't really know what their equity was worth. It's not like there was regular tenders. And so why work at the number two, at least by many definitions, space company. And then that's potentially ultimately bad for competition and it's bad for launch pricing for all these other companies that are reliant on the SpaceXs and ultimately the blue origin. So anyways, crazy news out of China. Apparently the co founders of Manus are still in China and were called up to talk with the government and are now blocked.

51:20

Have you seen the Dark Knight?

52:12

Yes.

52:14

Has everyone seen the Dark Knight? 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 skyscraper. It's one of the greatest scenes and I think that's what we gotta do because we need personal super intelligence.

52:15

This was surprising to me because I feel like we've been messaged to for a long time. Time that they were in Singapore.

52:33

Yes, that's true. It was that.

52:39

We shouldn't have seen this. It's not a Chinese company. They're in Singapore. Yeah, the whole team's in Singapore. And you would. It takes some audacity to sell your leading Chinese. One of the leading Chinese AI companies during an AI, a global AI race, this battle between great powers and to sell to a big American hyperscaler, maybe get out of the country before you do that. Because it's not at all I mean, this doesn't. When the Manus acquisition happened, seemed very clear that you would be if you were China and you were competing in the AI race. Even though Manus is not like a lab, you're still like, okay, they're building a powerful harness. We probably don't want them going to serve.

52:41

And the harnesses are incredibly, they're probably

53:30

under more important now.

53:32

Yeah, 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.

53:34

So Josh Wolf says, I thought this wasn't a Chinese company. And Delian goes for the jugular, says, so much for all the arguments about Manus not being influenced by the CCP bill.

53:44

Yeah, I'm mostly shocked just about how this is playing out. You would think that if you're the CEO of Manus and you get a call from Mark Zuckerberg and it even smells like a potential acquisition, you're like, yeah, I'd love to come see the headquarters. Why don't I come and with my team, we'll just come and hang out in Menlo park or Miami for a couple months while we hash out the deal. And if the deal doesn't go through, we'll head back, but if it does, we'll just stay and we won't go back because if it goes through, then there's going to be pressure and we're going to wind up in this situation. This feels almost predictable. I don't know, it feels like there's something else going on here. I'm excited for this story to develop.

53:57

So the authorities are reviewing the sale and they're being asked not to leave. Seems hard to reverse at this point, but again, not sure why. I mean, when you look back at acquisitions that were blocked historically, who knows how feasible it is to fully block the acquisition. But they can certainly block these individuals from materially benefiting from it in some way or contributing to Meta's efforts.

54:37

Well, here's some advice for the CEO of Manus. When you get here to America, when you get that liquidity, that payday from, from Mark Zuckerberg, open an account on public.com, investing for those that take it seriously. Stocks, options, bonds, crypto, treasuries and more with great customer service. Just do it. And then, you know, tell your story. Start restreaming one livestream, 30 plus destinations. You should be multi streaming. So go to restream.com, tell your story live on the Internet.

55:08

Gabriel says Meek Mill has been going off 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. Was probably Gstack.

55:35

Yeah, yeah.

55:55

Who else can help me with Claude? Gabe says Drake I don't do K2. Kimmy Deepseek that's more for your kind. My gal more like Demos Theme Park Ting London DeepMind, Meek Mill I quad coded perks out of 18th and berks I got 500 agent lawyers trying to free Lil Durk that's a good line Bars Drake singing you got me loco trying to be your Schultz.

55:56

You didn't sing it.

56:28

Sophie chimes in two chains Open call on my laptop trapping off these Mac minis shout out to YC Real GS want to stack with me. That's good. That is good. I mean, yeah, it's not a, it's not a bubble until, until Gstack makes it into. Makes it into a. Yeah, actual hit.

56:28

The funny thing here is there's some debate and, and there's this general vibe, like some people were latching on this trunk fan post about like, you know, are people making fun of Meek Mill? Are people 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 any of these tech people writing rap lyrics. Even with all the powerful LLMs, the tools to actually build software are way better than the tools to write rapid lyrics. And it's interesting because you are seeing this dynamic where I think a lot of people are latching onto the older paradigm of, oh, Jeremy Renner built an Instagram clone at one point, and it was just the Jeremy Renner app and it was just his feed of his photos and people were like, why does this exist? You can just follow Jeremy Renner on Instagram. It doesn't make sense that he would have his own private Instagram. And he probably spent a lot of money developing that piece of software. And I don't think it wound up working and it didn't scale and he wound up winding that project down. But if you think about like, well, what if this, what if this cost of doing that is 100 bucks or 200 bucks or 1,000 bucks, like all of a sudden the hurdle rate to clear something like that actually does open up the creative aspects where I wouldn't be surprised if there's A like, maybe not like a breakout, hyperscale, 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 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 not going to really take me seriously. And all of a sudden you get into this weird thing where the app that they launch is sort of iffy and not that good. So I don't know, I'm actually coming away bullish on what Meek Mill winds up producing over the next few years.

56:52

And we are working on getting Meek on the show.

59:05

I really hope we can talk to him.

59:08

I'll cover.

59:09

You're good.

59:12

You're good.

59:12

I'll cover. Meta if you want to jump for a second.

59:12

First, let me tell you about CrowdStrike. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches. And I'm also going to tell you about Vanta Automate compliance and Security. Vanta is the leading AI trust management platform. And I'm totally good so I can take the next intro.

59:15

I have a personal thing I'm going to run to, but I will see you guys tomorrow.

59:31

Yes.

59:35

Love you. Cheers.

59:35

Thanks, Jordy. Up next, we have Mike from arkprize in the Restream waiting room. Let's bring him into the TVP and ultradome. I'm very excited to talk to Mike. How are you doing?

59:36

Here we go. Hey, good to see you again.

59:46

Good to see you. I'm so excited. This is always the highlight of the show. I love talking to you about everything, but what are we talking about today? Reintroduce ARK as an organization and then take us through the actual. Do you even call them benchmarks? Challenges? What's the right term?

59:48

Benchmarks is a fair word.

1:00:08

Okay. Yeah.

1:00:09

Almost three years ago now we co founded the ArcPrize Foundation. Me and Francois Chalet.

1:00:12

Yeah.

1:00:16

The ARC Prize foundation has a mission to be the North Star to AGI. So sort of our sort of job. We have two of them. One is to help be a useful public sense finding tool for the public to understand how close, how far are we towards AGI or not?

1:00:17

Yeah.

1:00:31

And the second is to inspire progress towards AGI. ARC is A series of benchmarks that help highlight what are some of the large remaining gaps between what Frontier AI is capable of and what humans are capable of. And we sort of target that gap. That is sort of our definition of ultimately AGI is, you know, we produce an ongoing series of benchmarks continually studying Frontier progress. And you know, at some point we are not going to be able to do that job anymore. We will run out of ideas. You know, we'll test Frontier and say we can't find anything else, any more gaps. And I think that'll sort of be the moment when I think it becomes commonly accepted to say, okay, yeah, we've got AGI now. And today we are announcing and launching the newest, best version of Arc AGI 3. It's the latest in the series. This is a really large format change from the first two. Ark 3 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 the last few weeks, the only unsaturated general agent benchmark in the world. The headline score is human score 100% and AI less than, less than 1%.

1:00:32

Okay, unpack that like launch. Because I. My conception of Arc AGI v3 is it's almost like a 2D game. It's no longer the puzzles where I'm picking colors to match a pattern. It's actual moving arrows on the keyboard, I'm stepping on triggers, I'm opening doors, switches, that type of thing. And I played it with you on the stream months ago.

1:01:37

Yeah, you helped us launch our preview several months back.

1:02:06

Okay, so that was the preview.

1:02:09

We got the full data set launching today.

1:02:10

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.

1:02:13

Both things actually. So today on the benchmark side, the public version of the benchmark is I guess the overall benchmark. So over 100 games, nearly 1,000 different levels across these game like environments. I think it's fair to call them games. We've designed them to be fun and games are fun. I think you could look at them, you know, from a research standpoint. More. More is environments though. These environments are intended to test whether AI can effectively explore, discover its own goals, acquire strategy, develop plans, execute its plans. One of the really unique things about Ark 3 compared to the 1 and 2 format is that it is interactive now. Whereas you mentioned, you know, 1 and 2 look like these kind of static IQ puzzles that were on a page. Three challenges, both humans and AI, to essentially figure out the goals themselves. When you're dropped into one of these environments, your only goal explicitly is to win. And so in order to figure out how to do that, you have to actually dedicate some explanation to figuring out the rules, the mechanics, the strategy. And one important thing is you're sort of playing these environments. The strategy mechanic, the grow and they evolve and they change over time. And this is one of the reasons I think arc 3 will be a really useful tool for understanding agentic intelligence this year. I think it'll be our first real test or seeing early progress on these AI systems that are able to do on the fly world modeling, some degree of on the fly continual learning. These are both critical capabilities that we view as missing today that ARC 3 tests for.

1:02:32

Okay, take me a little bit deeper on. You said there's a thousand games or 1000 levels?

1:04:00

I think a few. Over 100 games across those 100 environments. Nearly 1000 levels across all of them. Yeah, it's a much larger version of the benchmark than we've ever had previously. And then like I mentioned before, the other major thing we're announcing today is Frontier Scores. So the benchmark is launching. We're also publishing as of today, the latest four models across all the four major labs. And yeah, I think Soda is currently sitting at like 0.3%, 0.4%.

1:04:09

Yeah, I think I saw Gemini 3.1 Pro. Maybe there's an extra hyphenate on there. But basically the gemini anthropic and OpenAI were all in the 0.2, 0.3 something. And then Grok was, I think it's 0%. Walk me through the actual build out of these hundred games. Is this entirely human done? Is there some sort of computer aided tooling to insert variation programmatically? Or is it important that they're all created by hand? How do you think about the creation of it?

1:04:38

I wish we could use AI to help design games. We'd be able to make the benchmark even better. The reality is humans are still the bottleneck on creativity. And so every game has still been handcrafted and hand designed by humans. You could sort of imagine if you were embedding all these different levels on like a big manifold in an embedding. You want them all as far apart as possible in that sort of Space and today still, humans are kind of the limiting factor in terms of ensuring that every game is different and is novel from each other as possible. Yeah, there's a few interesting design changes actually from a benchmark standpoint compared to 1 and 2. Maybe the largest is ARC studies the frontier progress. We have to design our future versions of the benchmark to adapt to changing frontier progress. One of the design goals with 1 and 2 was we have what's called a private and a public test split, where we have a public version of the benchmark and a private holdout version, which is what we actually use to verify the performance of frontier models.

1:05:16

So the frontier models get no freebies, they don't get anything from the public set, but they can change JB's.

1:06:15

You can't memorize the public set.

1:06:20

Right?

1:06:21

Or. Or they can experiment on the public set from a prompting perspective, maybe.

1:06:21

Yeah. The idea is the public set is intended to demonstrate the format and this was similar with ARC 1 and 2. However, we held a design goal that the public sets and the private sets were what's called ID'd with each other, basically that they are supposed to be as close as possible to each other. And it's just split along visibility. Some are private and some are public.

1:06:28

Sure.

1:06:46

With one of the, the big advancements with AI reasoning, is this actually like not a very useful way to run benchmarks? AI reasoning systems are so powerful now that they can actually generalize across IDD test splits. And this is what we saw with arc 1 and 2. So with 3, one of the big design decisions is we're actually releasing fewer games into the public demonstration set. So there's only, I think about 25 games that are in the public set. We're actually explicitly not even calling it a training set anymore. We're calling it a demonstration set just to show the format to humans, be able to test your systems to make sure you can sort of create them, get a feel for them. There's obviously fun marketing value in being able to play the games as humans too, which we really love. And on the private set, this is the set that's over 100 games. They're specifically different. We design them with different characteristics, different goals, different intelligence capabilities required to beat them. The difficulty, the acceptance criteria is more extreme between human and AI port performance, all to hopefully produce the most useful high signal benchmark towards whether we actually are getting real progress towards AGI with the foundation models.

1:06:46

So

1:07:50

let me pitch you a strategy. If I have access and I'm at Google or OpenAI or Anthropic. And I want to do well here. Can I take the public set and create a log of all the steps and all the reasoning chains and all the 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 and

1:07:52

train your model that way?

1:08:22

Basically maybe train my model, but also I'm just wondering if that's helpful for setting up the context or, or doing some sort of pre compaction of the strategies that are learned. Maybe not even training a custom model, because I feel like that would maybe be like bench hacking. I'm more thinking about just like, okay, we went and we played all the public games to completion and we monitored them, screen recorded them, tried to extract as many learnings as possible into an MD file, basically, and then. And we include that in the prompt. That kicks us off that just sort of bootstrap the learning. Once we get into the unknown environment,

1:08:23

if we've done a good job on the benchmark, you should not be able to train a system on the public side and perform well on the private set. If we've done a good job, Obviously every benchmark release, it's an experiment. We make contact with reality. We ship these systems benchmarks publicly. We try to analyze the performance, understand what they're good at and bad at, and of course involve future versions of the benchmark. But intentionally, this actually is very closely related to another design decision that we're making with our scoring function going forward this year. And this is again in response to AI progress that we've seen. Our scoring methodology is basically AGI peeled at this point. We going forward with V3 are using, as I have this idea of basically a philosophy of having essentially no harness. We want to create a testing experience that's as similar as possible between the human and the AI test takers. When we have our human baseline, when we have rented literally a testing center in San Francisco and had hundreds of humans play these games, all they're given is you have sensory input through your eyes and action motor output through your hands back into our testing interface. All of the intelligence happens between those two steps. We try to emulate those as close as possible for our verification function, where we have this philosophy of having a very stateless client, so that our scoring function basically tries not to introduce any kind of bias, any kind of help, any kind of maybe potential cheating strategy. If you go read our prompt, it's extremely simple. It's like you're playing a game. Here's Your actions, 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 there's real progress towards AGI and the, the base intelligence layer, we're able to detect that.

1:09:06

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 Gym, where they were able to beat Mario and then they beat the Dota team, Dota 5 and they were able to do things that I can't do. I certainly can't beat Lisa Doll in Go. I certainly can't win Jeopardy or any of these things. And yet AI systems were able to dominate those games. You've created new games. What's different about the games or the strategies by the AI labs where we're not matching up like we did in the past?

1:10:46

I think the biggest thing is the expectation of what constitutes real progress towards AGI. When labs were using games in maybe the 2016-2018, 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 and feedback mechanisms from the environments. It's very, very handcrafted. It's loaded with what I'll call human G. In the research process, we are now at a point where we want to control for that actually we want to understand like we want to control for as little human G in these like systems as possible. Right. We want to understand is can basically AI do what the human researchers were doing back in that era in order to beat those games that they'd never been trained on or exposed to before.

1:11:36

Oh, interesting.

1:12:22

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 elegant as far as an environment goes. But I think what's changed is our expectation of how much human crafting is needed in order to learn the games when they haven't been specifically trained on them is the big difference today, especially with Ark 3.

1:12:23

Okay, remind me of some more history, but more related to Arkansas. I remember with one of the ARC AGI benchmark tests, there was a version of a model from OpenAI that was running on some sort of like extra high mode. And I Seem to remember like $2,000 per task being cited.

1:12:51

3.

1:13:10

Is that what it was?

1:13:11

Very big launch. Okay, yeah, that was like a preview of oh3 in December of 2024. So really the first, you know, there's a great chart on the Arkprise homepage now where you can actually see those data points, points so clearly. I think one of the really like I mentioned before, one of our missions of the foundation is to try and be useful public sense finding tool. And I think, you know, when we first launched Ark 1 and 2 it was a very common critique. It's understandable. You know, hey, these things look like toys. Are they really economically useful? Are they going to lead to any real progress? And now in hindsight I actually think that's a pretty outdated view because we have pretty strong evidence that ARK held quite strong predictive power of noticing really important AI moments. We only started seeing saturation on the V1 benchmark and remember V1 was like 5 years old. We only started seeing any amount of progress from LMS on V1 once we got AI, which was a really critical innovation I'd argue is as important as the original transformer innovation. And then a year later, this was 4 months ago now with the November December 2025 class of models with GPT 5.2 and Opus 4.5, we again started to see saturation on ARCV2 and it precisely correlated with this agentic coding capability that emerged. And so I'm optimistic that arc3 will again be a very useful sort of predictive tool to understand when basically AI agents are capable of operating in more open ended environments. Right now you need a lot of human handcrafting to get these intelligence systems to work in domains such as coding with cloud code in code codecs and Claude code. I basically expect that when you are doing very good on V3, which will mean by the way, 100% scoring V3 means 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 specifically trained on.

1:13:12

I still remember from ARC AGI1, you know, you see these like three by three grids and the first time I ever tried it, I tried on my phone and I think my phone was in some weird like landscape mode or something, so it wasn't rendering correctly and I was like, you didn't even get

1:15:01

all the data points?

1:15:15

Yeah, no.

1:15:16

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. Like the fact that other people can do this. But of course, once you load it on desktop, it's very. I want to continue down that path of the O3 extra high. 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. Was 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. Is it an off the shelf model or are they able to sort of come to you and say, hey, we want to actually marshal 10 times the amount of compute for this particular challenge

1:15:17

on our verification leaderboard. We have a new testing policy. It's actually something we did have with 1 and 2 introduced after O3 where we limit to $10,000 per verification run.

1:16:16

Okay.

1:16:26

This is somewhat of a practical like consideration. If we actually used like the most expensive, highest million context window of the most expensive model, I think testing of the full V3 private data set would be like $100,000, which is just kind of like silly, right?

1:16:26

Yeah.

1:16:42

So we set a reasonable limit, like humans, near, nowhere near as much as sort of like dollar to sort of produce this performance.

1:16:42

I like that too. Because like that, that, that is like getting AGI and it's like, yes, it can do anything, but it costs $50 million per prompt to do one hour of human labor. Like that's not really economically valuable and so bounding.

1:16:48

I think you want 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.

1:17:03

Yeah.

1:17:10

And it's like just, you know, for practical reasons, we just can't. We're a strapped nonprofit, so yeah, you know, we have to be sort of thoughtful on our, on our sort of money on how we deploy things.

1:17:11

Well, good luck.

1:17:19

So I think the high reasoning mode is the most we used on for the official verification stuff that we've used today.

1:17:21

So stayed under that. I mean, do you spend a lot of time thinking about your own AGI timelines? Has your work at ARK shifted your timelines at all? Or do you feel like I've always been 2035 guy I'm still a 2035 guy, something like that. Do you have an internal model of this or is that even useful these days?

1:17:26

Instead of listening to my predictions, you should probably follow our actions as our best sign of a sort of review of progress.

1:17:46

Sure.

1:17:57

I think the reality is we have made tremendous progress with Aries and over the last 12 months, Ark is operating to bring the next version of the benchmark. We've already started work on V4. We actually have plans written down already for V5 as well. Our intention is to bring these to market annually over the next two years. And so that's sort of our expectation of having the next version ready. Right now. Yeah. Now will we actually launch them? I think we'll have to just see where frontier progress is. We want the future benchmarks to be as useful as possible. And so if there's still a lot of use, utility and scientific value in the current version of the benchmarks, you know, we want to keep focus on those. But to the extent that like the scientific value is starting to wane, we want to have the next version ready that has sort of like identified, hey, are there other interesting remaining large gaps between what humans can do and I can do in order to drive that gap to zero? You know, again, we're very, we're very AGI pilled organization. We want to see progress. We actually love seeing progress. And part of our goal is to inspire as much progress as quickly as we can to get to these AGI systems.

1:17:58

Yeah.

1:18:56

So I'd say like, yeah, that's sort of the operating view. Well, you know, a common question be like, was V5? You know, is V3 AGI? Is V4 AGI5AGI? The honest answer, and this is something I've actually learned, I had a different view of this maybe three years ago. The honest answer is no single version of any benchmark is ever going to be AGI. I think it is a. The frontier progress is a moving target and our job is to like, understand that the gap, the remaining gap, and the definition of that gap is going to change as time goes forward in order to keep chunking up. What are the largest pieces of that gap that we can find that are interesting, you know, that identify some missing important capability that humans are able to do and produce benchmarks that showcase that gap.

1:18:56

Last question. I'll let you go. What's going on with the Pokemon bench? That feels somewhat related. Similar tasks. What are you learning from that? How are models becoming so good at that? It feels like they aren't specifically RL'd on Pokemon. And yet they're learning. But also there's a massive amount of written text about what to do at every level in Pokemon. Are they just learning that from the pre training corpus? What's your thesis on Pokemon?

1:19:36

It certainly seems helpful if I use our experiencing developing ARK as a tool to sort of sense find around this. We have seen more understanding from the latest generation of AI reasoning systems over the last three months than we saw in the first six months when we were developing Arcv3. I think you can kind of fork. You can almost split the research problem of agents into two things. You can split it into a problem that says can an AI agent effectively perceive some kind of environment state? Apply a strategy that's written down to produce actions and successfully execute a plan. That's half the question. The other half the question is can you have agents that are effectively able to develop what that plan is? To do that, you need to be able to on the fly, build a world model of your task, acquire goals, create your strategy, create your plan. We've seen a lot more progress on the perception through strategy to action problem than we've seen on the exploration problem, the strategy generation problem. I actually think this is one of the areas that I would point interested ARC 3 researchers at because I think it's a lot more greenfield and will unlock a lot more progress even on things like Pokemon Bench, where it's kind of coming down to like, okay, we know they can sort of, I should say execution. The exploration and planning step is still where there's a large great bottlenecking still happening today.

1:20:06

Well, congratulations on the progress. Where can people find it? How can people participate? How can people help out?

1:21:36

Yeah. Go to arkprize.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 designed to be very fun. We explicitly controlled for this actually when we were doing human baseline testing. So that should be fun. You can have fun and you can also get details there. Enter ARC Prize 2026, our new $2 million prize pool this year. That's on Ark 2 and ARC 3.

1:21:42

That's amazing. Yeah. Our teammate Tyler Cosgrove was climbing the human leaderboard for a while. I imagine he's been knocked off, but we'll have to get him back on top. Thank you so much for taking the time to come chat with me. This was fantastic. We'll talk to you soon. Have a good one. Let me tell you about Gusto, the Unified platform for payroll, benefits and hr. Built to evolve with modern small and medium, medium sized businesses. And let me also tell you about TurboPuffer, serverless vector and full text search. Built from first principles and object storage. Fast 10x cheaper and extremely scalable. And without further ado, we have our next guest, Nathan from airstreet Capital coming in to the TPP and Ultradome. Nathan, how are you doing?

1:22:04

Great. How are you doing?

1:22:40

John, thank you so much for staying up late. What time is it there?

1:22:41

7:25.

1:22:45

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.

1:22:46

Yeah, I'm Nathan. I started a venture capital firm called Air street Capital in 2019 to invest in AI first companies.

1:22:54

And what year were you investing in AI?

1:23:02

Well, so I started the firm in 2019, but started investing in AI in 2013, which is probably around the time that like deep learning was still definitely cooking, only in the lab and most people didn't really care too much outside of.

1:23:06

Yeah, what were the median deal like, what was the median deal like in 2013? Was that like recommender systems, like we're going to bring Netflix recommendations to everyone, like that type of thing?

1:23:18

Yeah, well, it was E commerce recommendation systems, Ad tech. Yeah, Big data was the buzzword back then.

1:23:32

Sure, sure.

1:23:38

A little bit in finance, like insurance underwriting, like loan prediction, credit.

1:23:40

Yeah, yeah. Fraud detection. Just like a big. I guess it was like, were they doing deep learning yet or was it mostly just.

1:23:45

Yeah, they were. Yeah. I mean it was 2013 was the year that computers started to be able to recognize images better than humans. Oh, yeah, that was. Remember like Andrej Karpathy was the infamous human benchmark on ImageNet in 2013. PhD, that's right. So that was the year when, when basically like Alex at University of Toronto like built alexnet, which was the first deep learning system running on Nvidia card.

1:23:55

Yeah, yeah. What a remarkable time. So what has it, has it been easy? I mean, you just raised a new fund. Has it been easier to pitch this to LPs? What have been the challenges and opportunities over the last few years?

1:24:21

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, so 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 that one would have. Yeah, yeah. 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, I'm going to do these early stage investments, be high conviction, invest in biotech, defense, vertical software, dev infra. You know, I stuck with what I said. So you know, investing in like Synthesia 11, Black Forest and others. I had like six exits to like recursion and you know a company went public and Amazon, etc. Yeah, and then, and then, yeah, like first One was like 27 million fund. Two is 121 about three years later, again pre chat GPT and then this one's 232 million which at this point makes us the largest solar GP in Europe.

1:24:35

That's amazing. So us, you said solo gp, but you said us. Who else is on the team?

1:25:42

You know what, like I'm kind of guilty with the royal we thing, but I have two colleagues who run talent and operations and then a pretty sizable back office for like admin.

1:25:48

Sure.

1:25:59

But everything that comes along with like building, brand finding, founders, investing, fundraising, that's all me. And the decisions are just me.

1:26:00

And then also the is it annual reports state of AI. I mean it's, it's sort of a huge project. Do you bring in collaborators on that?

1:26:07

Yeah, that started in 2018 to 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 coal face doing their PhD or like transitioning between roles in AI labs who help us kind of stay smart on things and, and also folks who've been working on policy because it's become increasingly important as we see in the news almost every day.

1:26:18

Yeah.

1:26:41

And then the cool thing is like I get contributions from companies and labs and researchers every year. And like I think this last year when we last talked there was like 50 people in the Google Doc kind of like leaving comments, being like, hey, I tried this implementation, this paper. Like I had this problem and then some other person's like, that was my paper, this is what I tried. And it's like cool like community document basically where we can kind of get to the center of the truth.

1:26:42

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 million fund because it feels like $27 million is like a seed round for like a, you know, startup with just an idea. Sometimes that's like 1% of the seed round but like is it, can you even make plays with that size fund if that's what you were constrained to do today?

1:27:08

I, I think you have to decide like what I did which is either you want to be like a main player and lead rounds and express your conviction and be early etc or you play the like large portfolio model and then you have checks and a lot of opportunities. And for me that job is like much more of like a network SDR style job and less of 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, I don't think you can do the former like be a lead investor in 27 million. No chance. I think you can do the larger portfolio, you know, chipping into a variety of rounds and still have like good performance. But it's just a different job that I don't particularly enjoy and doesn't maximize like my strengths and my interests as much. Yeah. You know, so I think at the end of the day like you got to pick what flavor is good for you and then try as best as you can to bring the best product to the market given your circumstances. And I was fortunate with Fund 3 to be able to really come with like a blank slate with you know, long term partners and say this is what I think is going to be the most convincing model. You know, right up to $15 million in first checks and do a couple of growth stage rounds up to 25 million 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.

1:27:40

Yeah, I mean I know you're, you're, you're in Europe but you're not you know, exclusive European investor by any means. But I am interested in the thought exercise of like where is the AI opportunity internationally? If I were to just back of the envelope it. 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 particular local lab but at the same time like you know, Google has been very successful internationally and you know, China got the Google of China but many other European countries didn't get the local Google competitor or the local Amazon competitor or the local Microsoft or Apple Competitor just because, like, they were consumer products and consumers kind of flow wherever they want. But at the same time, I can imagine if Google or Open Air Anthropic is going to build a data center, they might want to go to a local Neo cloud, or there might be opportunities for, you know, 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?

1:28:58

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 they could capture European culture better than Google could. 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 now even more so with the Middle Eastern war that's ongoing. You know, as an example, I get invested in a business called Delhi and Alliance Industries doing defense, autonomous defense systems right. In Greece. And one of the number one things we got from people outside of Greece, particularly in the US is like, why are you investing or building a company in a vacation resort that I go sailing and, you know.

1:30:07

Yeah.

1:31:01

And then that 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. Greece. I think the other part, which is interesting is like, ambitions change. And. And I think in Europe, where traditionally there's been fewer role models that one can look to and say, I'm going to be like that person. And I know the path some companies grow. And, you know, for example, I think Ligora originally started as Leia, like, started in Sweden. Right. 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.

1:31:02

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 going to go everywhere. I'm building Spotify and I'm gonna go everywhere. And yes, I happen to be from some other country, and I'm going to have a headquarters there. But get ready, New York, because we're going to have a headquarters there. We're going to have an engineering hub in sf and like, we're just going to be an international company and have our roots there. And that's.

1:31:46

Yeah. So this is why I think if you're going to 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 that you see in the US over in Europe. And 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 experience it. You know, like when you get success, you want more of it. And so that's like the kind of recursive cycle of the continent's going through.

1:32:10

Yeah. I mean, with all the progress from the big labs and they're at such incredible scale now, like, how are you processing the SaaS apocalypse? And just advice for founders of, like, what gets steamrolled versus what doesn't. I mean, there were some, there was some founder. We've had a couple, couple founders on the show that have been like, we're doing AI generated video, social network. And then it was like, you're getting steamrolled. And then it was like, actually, like, you know, Sora is not going to be in the App Store anymore. So like, maybe that was a good bet.

1:32:38

I don't know.

1:33:03

I'm not on that particular app, but it feels harder and harder. It used to be just like, don't do an app. That's just a prompt around the foundation model. Like, that's done. But now we're talking about, oh, is there pressure on CRMs? Is there pressure on database? Is there pressure? Like, what will the labs do? It's. It's unpredictable. But how are you working through it? I think, you know, one thing you

1:33:04

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.

1:33:27

Okay, that's a good one.

1:33:34

Like, don't do coding.

1:33:36

Yeah.

1:33:37

Like, after coding, it seems like AI researchers really like AI for science. So, like, don't do that.

1:33:37

Totally, totally. Yeah, yeah, yeah, yeah. We were friend from the show that does, like, yeah, it's an AI company, but it's for, like, small businesses, like H vac owners and helping them. It's like, yeah, I don't think that's on the roadmap. That's really good. Amazing.

1:33:43

Jokes aside, I think. I think it comes down to, like, this tacit knowledge and, like, where you can capture how people do a task and taste. Like, I see this a bit with our job. Like, like, you know, I'm using, like, I'm Claude maxing as well and like Codex maxing. It's amazing how it can. You can imbue it with your taste and you're like, at some point you realize, okay, we've 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. Or 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 make a skill file. And then next time, here's a new opportunity. I'm like, dude, if you're not doing that, it's like, game over. And so I really do think, especially for our job, there is a point at which you're like solo GP with like 200 or $300 million with a bunch of AIs. I'll call you in 10 years and see if it works.

1:34:02

I'm excited. I'm excited. Well, I want to hit the gong for the new fundraiser race. Congratulations. Thank you for coming on the show. Have a fantastic rest of your day and I will talk to you soon. Have a good one. Goodbye. Let me tell you about Vibe Co, where DTC brands, B2B startups and AI companies advertise on streaming TV, pick channels, target audiences, measure sales, just like on Meta. 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 remove money, fight fraud and improve lending. Now with AI and without further ado, our next guest is in the restream waiting room. We have Rohind. He is a real estate expert. Thank you so much for joining the show. How are you doing, Rohin? Good to meet you.

1:34:59

Yeah, happy to be here.

1:35:41

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?

1:35:43

Yeah, I'm a San Francisco real estate agent and I'm among the 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. I did a bunch of startups and then got into real estate when learning about Airbnb early on and built a small portfolio of that and then learned the real estate craft from that.

1:35:51

Did you have to get a license at some point? Did you join a big firm or do you just sort of strike that on your own?

1:36:17

I was, my Twitter account started growing because I was like posting interesting houses that I was like, just kind of curious about. And then people were messaging me like, oh, I actually, like bought that house you posted about and says, like, dang, someone's making a lot of money off of this and it's not me. So then I, like, decided to get licensed. And originally I was going to focus on like, Airbnb markets and short term rentals and vacation areas. But I live in San Francisco and I could see the prices were like, after the pandemic, just like crashing here while they were shooting up everywhere else in the country. And I was like, oh, they're converging. And that's, that's like, odd to me. And says, 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. And then I was like, well, this is the opportunity and I'm getting a license and like, this is what I'm going to focus on. And then, 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, Rohan, in your corner real estate agent when you're trying to buy or sell a place.

1:36:22

I love it. When did the actual rebound start? Where, where was the trough after Covid?

1:37:26

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 all these liquidity events. The 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 very end of 2022, things like abruptly dropped. So 2022, end of 2022, 2023, 2024, prices were way down. And then 2024, by the end of it, there was like a little trickle and 2025, you sort of had come out of the bottom, but it was like a slow, you know, like, you Know, pretty stable market, but on the upward trajectory. And then end of 2025, then it just sort of started booming like crazy in terms of pricing. And then even from like, you know, March 2026 is like way up compared to like two months ago. So.

1:37:34

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?

1:38:36

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. And in all ways it's like there's not enough housing, there's not enough like restaurants, there's not enough this or that. And it's sort of like if you want a place like in San Francisco, you're like so convicted on the idea of it, of the city, of like the tech industry, you're like, you know what, I'm just going to like do this and then I'll figure the rest of it out. And so like, I don't think people are like, oh, now I have to figure out like what school my kids are going to go to or like what my commute will be or this or that. It's like if you're sort of like dilly dally around the edges, you sort of end up never really sort of being so committed and that kind of ends up being like what makes it hard to buy a place. But like the people that like, actually when these homes, whether they're 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.

1:39:01

And what does the, the, the like the down the fairway place in San Francisco look like these days? Is everything over 2 million, 3 million? Like where are we in terms of single family?

1:39:57

Kind of trying 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 million. And then if you were slightly above that price, there'd be like a big drop off in competition. And now it's like that level has sort of definitely moved up to like 3ish million.

1:40:09

Wow.

1:40:32

But the bigger change too is that like there's like huge level of competitions at any price point. Now, it's like one that sort of checks the box for buyers.

1:40:34

So give me some advice on if I'm trying to win one of those competitions. What do I have to do? I have to show up with all cash, Just put the cash in the bag. What do I do?

1:40:42

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 going to. You can walk in and be like, oh, I'm going to 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 going to be a range of competition on any given house. So, like, some houses, you know, this could be like a five or six million dollars house. So pretty expensive house. And there might be like, 15 offers.

1:40:50

Whoa.

1:41:21

And like, the seller's not, like, going to just sell it to you because you're a cool guy. Like, they're. They. 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.

1:41:21

Okay.

1:41:33

And so, like, what you're sort of trying to navigate is the level of competition any one house is going to have. So, like, say it doesn't have as many bathrooms as you want, but you could figure out how to add one or say it's off market and only a few people know about it, so there's less competition. So 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.

1:41:34

And you're probably expecting it to go a lot higher. I imagine with IPOs, the labs are getting bigger, there's more liquidity, there's new investment rounds happening. What's your forecast?

1:42:03

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 going to say, like, you know, whatever. Like, I decided to get into the market because I thought, like, this was going to happen. I was like, oh, like, these scarce homes are going to become more valuable and people will wish they bought them. And, like, I should focus on this. And so I personally, I'm convicted. Like, the city is on the right trajectory now. So it's not like contrarian to buy a place here at the moment.

1:42:17

Yeah.

1:42:48

And then there are like liquidity rounds and like, that has made a big impact on the market. And if the liquidity rounds get bigger, like there's. It's a fixed number of homes that the, you know, that money goes into.

1:42:49

So what do you think expansion looks like over the next few years? Are we going to. I know Mill Valley is booming. There's other suburbs. Is Oakland going to happen? There's this California forever development that's happening. That's further out. Like, are you starting to broaden your horizons or do you want to stay focused? And what do you think the real estate buyer will want to do in the near future?

1:43:01

So I solely focus on San Francisco, like buyers and sellers because, like, I found that like, in order to like every time, especially on the buyer side, to win, it's sort of like pulling off this, like, mission impossible, like, heist where it's so elaborate you have to know like every detail about the market. And so for me personally, like, I feel very strongly that I can really help people in San Francisco. But then if you put me in Mill Valley, it's like, oh, I mean, I don't. I mean, maybe it's good for me to help serve Mill Valley customers, but it's not good for them. So I think, like, you know, if you're going to use a real estate agent, you should use one that like, really knows a particular market really well. So for me, I want that to be San Francisco.

1:43:22

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?

1:44:03

Yeah, I'd say It's about like 5050, 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, it just feels better and it feels fun and people are moving there and sort of like it's sort of regained the zeitgeist of like a place you move to, to invent the future. So I mean, that's like half of it and then the other half of. Is it 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, you know, that like, just started that are within that range and like it's somewhat unprecedented, I think, even though we've had like $100 billion companies before and like

1:44:22

Twitter, but this is at a different level, an order of magnitude. And so that's just going to drive up attention and excitement and all sorts of things. What are the most underrated neighborhoods? What's on the come up right now?

1:45:07

You know, everyone sort of really wants like Noe Valley, Pack Heights. Like I think if, like, if you're sort of like looking in the Noe area, like Bernal, like the, the kind of the hills right next to it. Glen park, like, you know, Sunnyside is like dramatically less expensive. Expensive like Pac Heights is now 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 this, you know, but like, you know, just as great. But now the prices are up there and then like Nob Hill is next to that and the prices are still a little bit down there. So maybe I'd say Nob Hill and you know, Bernal Heights.

1:45:21

Well, where can people get in touch with you? How do people reach out if they're looking to

1:46:05

Google me, Rohan Dar and then find my email or just reach out to me on Twitter and I'm pretty active there and generally I just share what's going on in the market over there.

1:46:12

Fantastic. Well, we appreciate you taking the time to come chat. Thanks so much.

1:46:21

Awesome.

1:46:24

Yeah, have a great rest of your day. We'll talk to you soon.

1:46:25

Thank you.

1:46:27

You too.

1:46:27

Goodbye. Let me tell you about cognition. They're the makers of Devon, the AI software engineer. Crush your background with your personal AI engineering team. And let me also tell you about graphite code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster. And without further ado, we have Eric Jorgensen, good friend of mine. He is the author, the publisher of the book of Elon. Thank you so much for sending me this. It looks fantastic and I was particularly. I want to get into the book, but I think partnering up with Jack Butcher on this, deeply underrated. He is an incredibly special illustrator designer. I don't even know what you call Jack Butcher, but obviously he was helpful in this. But thank you so much for taking the time to join the show. How are you doing?

1:46:28

Thank you for having me. I'm honored to be here and extremely excited to put this thing out into the world.

1:47:14

Yeah, listen to that voice. You got a voice for live streaming. Let's go. The microphone's Helen, you got a good setup. It's good to have you.

1:47:20

Am I about to get discovered right now?

1:47:28

I think so. No, of course, you've been online a million times. Everyone knows you. But maybe take me back to a little bit of how you got into publishing your business overall, the Naval book. And then we can go into the Elon book.

1:47:30

Yeah, that's an amazing set up 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 quickly.

1:47:48

Yeah, yeah. 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 would just share screenshots of old tweets and they would go viral again. But Twitter doesn'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.

1:48:12

Yeah, 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 million. And I've given away 5 million more digital versions and 40 languages.

1:48:36

So crazy. That's such a huge number. I feel like it's hard to sell a thousand books. And you sold 2 million.

1:49:08

That is an unbelievable number. For those that don't have, like, inside context in the book industry, I think the median outcome is like a few hundred and ten thousand is top fraction of a percent.

1:49:16

Yeah, absolutely incredible. What was the strategy? I mean, Naval has a big audience, but I don't see him pumping this book constantly on his Twitter feed or his X feed. Like, how did this book actually get in the hands of customers? Is it like top of Amazon? Is it on the New York Times bestseller list? Like, how do you even sell that many books?

1:49:26

I cannot explain it, other than to say it has become like a word of mouth phenomenon. I think it is just so many people tell me they buy it as gifts or they recommend it or they give it to, you know, I know teachers that give it to every class that comes through and it's just sort of, it's, you know, who doesn't? The subtitle of the book is A Guide to wealth and Happiness. Like Big Tam, right? Like universal human desires and, and new people graduate into like trying to figure that out for themselves every day. And I think it is, you know, this really rich, dense collection of naval, who's a really, really gifted sort of distiller and articulator of some of the most important principles, principles that make life make lives successful.

1:49:47

What principles from that book either stick out to you are timeless or maybe even underrated that you keep coming back to.

1:50:30

I think, I mean on the wealth side, like leverage is still an underrated one. I mean you guys are living examples of this. Authenticity is another one. That word is thrown around so much that you, if it becomes sort of a cliche. But the people that we tend to admire the most or that are doing the best are a really interesting combination of like excellent, authentic and leveraged. Right? Like Jack Butcher is an incredible example. You don't even really know how to describe him. He's like, he's an artist, but he's a contemporary artist in the digital era and he's a really gifted designer and he's kind of like inventing this category of networked art. But whatever he is, is him and it's awesome and it's massively leveraged and you know, he's doing things that nobody else is doing in the art game.

1:50:39

Do you think that being controversial is correlated with authenticity? Because if you're not authentic, you can be this very polished, one size, you know, many faced thing. You interact with one person in a certain way, another person, another way. You make everyone unhappy. 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 is a great question.

1:51:26

I bet there's two opposing archetypes. I bet there is a type of person that is extremely inauthentic in how they court controversy for the benefit of, you know, the algorithm or just being elevated by being attacked. And I bet there's another set of people that are authentic despite any headwinds or controversy that might come up. And I think the only way to probably tell the difference is just zoom out and see who's been doing what for how long and in under what contexts.

1:51:59

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 a very interesting style where it's high leverage. I can only describe it as high leverage because you're standing on the shoulders of giants, which is like all of the work that they've produced, all of the podcasts that they've done, everything that they have written, there's a lot of primary research there that doesn't necessarily require the same access and permission. And you can do a lot of pre work independent before you actually go in. Whereas some other books, it's like, okay, this author didn't even get the interview with the person that they're writing about. No one wanted this book to happen. And that's a lot harder.

1:52:30

Right.

1:53:27

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?

1:53:29

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.

1:53:37

Yeah.

1:53:46

My North Star with these books is to just be as. For the book, to be as useful as possible to the reader. I want the reader on every single page to be like, oh, my God, this is. Is a great use of time. I got a highlight on every page. I'm getting so much out of this. I feel like I'm getting personally mentored by Elon Musk through a few hours of reading about his most valuable and timeless ideas.

1:53:46

Right.

1:54:04

And I think for those of us in tech, Elon's been interesting for a very long time. And over the last, you know, five, six years, he's become more controversial. But inside tech, he was. Before he was a household name, he was the most ambitious person in tech. And nobody knew how that story was going to end. Right. He was running on a very thin tightrope for a really long time with both Tesla and SpaceX. And more recently, people have started, I mean, Marc Andreessen and Brian Armstrong maybe most famously have started asking the question, like, how does Elon do it? What is this? Why is he an outlier among outliers? And I wanted to answer that question and I think this book does that in more ways than I anticipated at the outset.

1:54:05

Right.

1:54:51

Like there was some interesting stuff that everybody kind of knew would come in. And 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.

1:54:52

Yeah. I remember in college someone called me and was like, oh, I heard about this entrepreneur named Elon Musk and he runs two companies, SpaceX and Tesla. And I was like, of course I know about that. I'd learned about it like three months earlier. But it really was a very controversial thing to do. 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?

1:55:03

Yeah. There was a period where Jack Dorsey was running two companies. There was a period where Steve Jobs was running two companies. And there's plenty of companies that are collections of meaningfully different companies kind of under one name. 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 Marc Benioff. The motions that he dives deeply into are very different, kind of on a per liter basis. And there's an element of this, like naval points this out. I think it's super interesting. He's like, you are probably working harder on your company than Naval or than Elon is working on any one of his companies just because he has this divided attention. So let's just say he's working 80 hours a week, but he's only working 30 hours a week on SpaceX. How is he able to have orders of magnitude more impact in those 30 hours than you're having with your 70?

1:55:49

Well, it is sort of interesting, 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, retired and yeah, I mean now, now maybe more focused. You know, he's retired, but there was a long time, like a full decade where Jeff Bezos was running Amazon full time. And then, you know, Blue Origin was the halftime or side project and. And Elon sort of didn't have a Direct, like full time, by the book entrepreneur. Just building a direct competitor in that one space, fully focused. So I don't know, maybe that's luck. Maybe things play out differently if there was someone in that space. But it's clearly worked out.

1:56:58

We kind of end up conflating like Elon the person, like Elon the core team around him, and Elon the person, the symbol, frankly, 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, you know, 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, this rallying point for people to like, organize around the values exemplified by this person. 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.

1:57:42

Yeah.

1:58:38

Kind of arguments with people. You're not even really talking about the same thing.

1:58:39

How do you think about the thinking in decades concept? You know, it's something that everyone's Silicon Valley says, oh, you got to think in decades. And then Elon comes out with something that's like 20, 30, 40 years away, and everyone's like, no, we didn't actually want thinking in decades. I want to know something that's going to happen for sure in like five years tops. I'm thinking about this mass driver question and I'm wondering, like, now that you, you've written this book, you've studied Elon, is this a departure? Is he thinking even farther in the future? Or has he always been thinking around this time horizon? How similar is this crazy mass driver on the moon pitch compared to previous eras?

1:58:42

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. Right. And so things that, at our previous growth rate or technology trajectory, seemed like they were 30 years away are actually now maybe 10. It is really difficult to adjust for that, like, recursion factor.

1:59:26

Yeah, yeah, that makes sense.

1:59:48

Yeah.

1:59:51

Well, where can people find the book?

1:59:51

Anywhere you buy books. Amazon, Barnes and Noble.com.

1:59:55

yeah, Target.

1:59:58

It just came out like yesterday.

2:00:01

Are you gonna do an audiobook?

2:00:03

Yeah, the audiobook's out. I didn't Read it.

2:00:05

Oh, you got it.

2:00:07

I'm sorry.

2:00:08

You got this. Pipes. Put them to work. Well, Eric Jorgensen, thank you for joining. The book is the Book of Elon. You can go find it everywhere books are sold and we will talk to you soon. Eric, thank you so much. Appreciate you to join the show. Let me tell you about FIGMA agents. Meet the canvas. Your AI agents can now create and model your FIGMA files with design system context in beta starting today. And our next guests are live here with us in the TVP and Ultradrome. Thank you so much for taking the time to join us. Pleasure. How are you doing? Please, since this is your first time on the show, introduce yourself for everyone.

2:00:09

I am Jenny, just co founder of Peak6.

2:00:44

Yes.

2:00:46

And I'm Matt Holziser. I'm Jenny's husband and also co founder of peaks6.

2:00:47

Fantastic. Take us back in time. I want to hear the founding stories.

2:00:51

Founding story, start. We both grew up on the option trading floor, Chicago and New York, and we were at an sort of an infamous options trading firm called o' Connor Associates.

2:00:56

You were both at the same firm?

2:01:10

We were both at the same firm, different cities. So super lucky to be trained there. When they did their merger acquisition, ubs,

2:01:11

who was in Chicago?

2:01:19

I was.

2:01:20

Did you ever go to Ceres?

2:01:21

Oh, of course. Still go to series.

2:01:22

Ceres is amazing.

2:01:24

Yeah.

2:01:24

Anyway, it's a bar.

2:01:25

Kind of modern these days.

2:01:26

Oh, yeah. I worked at Citadel in college and that was the place where we'd go and hang out and they'd give you. You'd order like a. Like a rum and Coke and it would just be a full glass. It was crazy. That's right.

2:01:27

And a really good sandwich to go with it.

2:01:39

Yeah.

2:01:40

Yeah.

2:01:41

Really good. Good fries.

2:01:41

Okay. So you're in Chicago.

2:01:42

Yeah, so we're in Chicago. We decide. We started working together.

2:01:43

What were you trading at the time?

2:01:48

Equity options.

2:01:50

Both of us were equity options.

2:01:50

Yeah. And then when they did the original Swiss bank joint venture, we were part of the team that went to start the OTC derivative desk. So there was just three of us. There's a gentleman from Goldman who came in and so we're like, oh, this is cool. We're in our mid-20s starting a business, you know, an intrapreneur. And when things started going really well and then UBS came in and they removed moving to the east coast, we're like, well, we're not moving. He had actually just come from New York and my family's in the Midwest, so we're like we'll just do that thing again. So that thing was to partner with a bank that was our plan A and do over the counter derivatives. It's 28 and a half years later, we've still never done it. But we did invest really early in tech and education and, and so we created proprietary options trading firm which is 28 and a half years old that has never had a losing year and allowed us to self fund all the things we've done since then.

2:01:52

And what's the secret to such an incredible run with no losing years? Is that risk management, is that the particular strategy? How does that come together? Because I can't think of another investor who's ever done that.

2:02:51

It's unusual for sure, but secret.

2:03:06

I think it tends to be about our approach. Our approach was not to be smarter with our, our algorithms. It was smarter with our business model. So there are plenty of businesses that haven't had losing years in the last 29 years. They tend to be technology firms that are basically providing a service into the market. Which is the approach that we, I mean we, we talked about ourselves as Wendy's or Walmart, Walgreens. We're merchandisers, we carry inventory and then deliver it to customers. We're not trying to take the, we're not disagreeing with customers. We're providing a service.

2:03:08

And then on the investment side, what is out further on the risk curve for you?

2:03:46

I mean, I think we've lost money in more ways than anyone you've ever had on this show.

2:03:52

Well, collectively, what is the nature of an investment that doesn't pan out? Is it just, it's high risk and you know that going in or.

2:03:57

Well, there's a wide range obviously in our trading business it's really systematic. We have an amazing team. We educate kids right out of school into our model. It's really rare that they would leave and be able to do the same thing because it is about the collective. But it's interesting. But we started a whole bunch of other businesses of course. So peak sticks today based on what Eric was saying in your previous interview. It's a company of companies.

2:04:07

Okay.

2:04:33

So we have started or bought and turned around 15 ish companies at this point and primarily in the back end technology space in Fintech, definitely in InsurTech, which is relatively new to us and Edutech. So those are the biggest risks we're taking. And then fast forward as we built those businesses over the years, we started an investing side of the business which is quite large because it's all AI Stuff now. And we started early enough, so it grew really fast.

2:04:33

We have some doozies.

2:05:03

I mean, I don't want to dwell on it.

2:05:03

Yeah, no, no.

2:05:06

We'll refer. This is a callback to your previous person. In 2008. We had. It was a good year for us. Not because we were smart and short. The market.

2:05:07

Yeah.

2:05:16

Jenny was like. Like, things are confusing. We should be in cash. And we were lucky. 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.

2:05:17

Sure.

2:05:33

So we are early.

2:05:34

Yeah.

2:05:35

So we interview two different people at the time.

2:05:35

We're not investors at this point. We are traders.

2:05:37

Yeah.

2:05:39

So it's two different things. We're operators.

2:05:40

I still don't know if we're investors.

2:05:42

We're just knuckleheads. We get two people. We're going to interview the two companies at the time. One is this PayPal guy who's trying to do it, and the other is the guy who was the chief architect at BMW. The PayPal guy gets on a call with us.

2:05:44

With you. With me, just to be clear.

2:06:02

Okay. Just since you're watching this.

2:06:04

Yeah.

2:06:08

See where this is going? Yes. You know where it's going.

2:06:08

I mean, if he's listening. If he listens to this, I don't know. He'll remember because I think he was stoned out of his mind. It was the worst presentation I ever heard. Like, this guy's never going to build a car.

2:06:10

It wasn't about cars. It was about the train.

2:06:20

He was talking about trains.

2:06:23

Trains between.

2:06:24

Electromagnetic trains could also be useful. I was like, what the hell are we talking about?

2:06:26

It's supposed to be a business investment. I want to hear the business pitch.

2:06:32

And the other person comes in buttoned up. Right. German engineer.

2:06:34

Yep.

2:06:40

Amazing.

2:06:41

Built these my entire career.

2:06:41

100%. We go with that person.

2:06:43

Okay.

2:06:46

Wow.

2:06:46

Nine months later, we find out that the one we invested in. When it rains, the cars catch on fire and explode.

2:06:47

So not a good one.

2:06:55

Yeah, that's not a good.

2:06:56

That's a bad dump site.

2:06:58

Yeah.

2:06:59

Yeah. That makes a lot of sense. I think a lot of investors have had to really come around to the other pattern of thinking. I know that's right. Some investors that. I mean, even on the other side. I 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 going to be self driving and no one's going to need a car anymore. So if this guy's just building cars, why should I invest in this? And of course, of course Tesla was going to be the one to do that, but that was too hard to predict and it just gets very, very hard when you think that far out. So walk me through a deal that is in the wheelhouse. What's the structure? Are you looking for a particular vintage, an age, a size of meat on the bones of the company and then what are you looking to do? Because when you come into a new company, you can, you can be transforming the business with AI. You can be focused on cost reduction, back office rationalization. There's so many different techniques that you can use to drive value.

2:06:59

Yeah, I'll start, maybe I'll start with Peak six Trials, please. So at its core we're entrepreneurs. That's what we do. So we're comfortable with that risk. Ironically, it doesn't make us super comfortable doing venture because we're not doing it. So we have to find really special people. We've been lucky in the universe and of Peak 6 to have some of those special people along the way. We just started something called Peak 6 trials, which is think about entrepreneurship and residents. We have, it's like previous accelerators except for that we have the capital, it's already there. We have the resources, the tech resources, for example, legal compliance, whatever it is already there. And then we also have the customers because of Apex Fintech Solutions. So that's our backend tech powers. 40 million customers today. So end consumers were B2B.

2:07:59

Yeah.

2:08:48

So there's a unique opportunity for fintech insurtech type of young entrepreneurs who want to do something. That's how we want to make those bets that will go into our operating company scenario. And then I know you want to talk about the investment side where we take what kind of investment looking for.

2:08:49

Yeah, sure.

2:09:10

Or even just the story of Apex. I'd love to know how that came into the portfolio, what the process was like. I can tell it's already going to be a good story.

2:09:10

Yeah. So there was a public company called PenCen. We owned and operated a brokerage called Options House at the time. This predates wealth front betterment and Robinhood, et cetera. And that business custody kept the assets right at PenCen along with a million other customers, retail customers.

2:09:20

We're in 2012 at this point.

2:09:41

Sure.

2:09:43

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? It would help us a lot. I'm like, let me think about. I gotta talk to Jenny.

2:09:43

Yeah. She's like, we gotta.

2:10:03

That's not a good sign for your listeners or watch your viewers. If your bank calls you and asks to borrow more money, that's in trouble. So Monday morning we get a call from the sec. There's fraud, announced fraud at the clearing firm. And we want you to put $70 million into the business by Friday.

2:10:05

Wow.

2:10:30

Or we're going to liquidate everybody and

2:10:30

that's everybody in the market. So think pre generation Robinhood for context. All those names out there, those middle tier names besides the big names, Options House, our firm was one of them.

2:10:32

Sure.

2:10:42

They're all going to go.

2:10:42

Yeah.

2:10:43

So 13 days later we bought it.

2:10:44

Amazing.

2:10:46

Yeah.

2:10:47

Announce fraud and all.

2:10:47

That's wild. Yeah.

2:10:49

Yeah.

2:10:50

I've heard a number of these stories of like turning around a company when there is fraud. I mean, Strauss Zelnick sort of did this with Take two is a fantastic turnaround to 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.

2:10:50

That's right.

2:11:12

How are you thinking about cultural development generally? I feel like when I dig into different funds, there's fascinatingly different approaches. Ray Dalio's recording everything. There's so many different. But you mentioned that 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?

2:11:13

They are critical, really difficult in times of COVID and changing work from home and all those things. And as we continue to build new companies. Right. So at our firm that's over 28 years old, they are ingrained. It is a sense of urgency. It's a work ethic. It's just high. And even when the market is telling you, you know, we ought to be different or nicer or something, like people are so engaged. It's really fun to be in the markets. So it makes that easy. It's fun to be part of an entrepreneurial culture. So that makes that easy. So how do I. And if you don't fit? 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 a challenge for us to try and integrate or have them stand in their own culture, which is also fine with us. Right. So if we sit at the top and we have CEOs of each of these businesses, they are dependent quite a bit on the Peak 6 core because it's facilitating the financial stuff, it's facilitating the HR stuff. And if they want to sort of ignore that and not join the club, it's, it's a hard road because we've figured out such a rhythm. When you get in the rhythm, it makes the acceleration go so much faster. The leverage we get with our people, with the culture is just really exponential.

2:11:48

Yeah. Some people refer to it as eustress, the good type of stress. It's a stressful scenario, but it gives you energy, it doesn't actually drain you. I feel like people get the runner's highest. So running is very stressful for some people, but for some people it's invigorating. And I feel like if being in the market at a tumultuous time gives you more energy during that day, that's something where you'll probably thrive.

2:13:17

Yeah, I was going to say taking risk, starting as traders and becoming operators and then investors. At its core, that trading Hortons oil trading and taking risk every day, all day, getting used to it, that isn't in everybody's DNA. It is part of the reason why we like poker so much. We're trying to teach a million girls and women to play poker.

2:13:41

That's cool.

2:14:04

Solely to get these male dominated areas for the women to feel more welcome. But you have to be able to take that risk every day and the organization thrives on it. It's a little scary.

2:14:04

I know like 10amazing female venture investors and they're all incredible poker players. Never sit down with them. They would absolutely smoke me.

2:14:15

Well, the funny thing is I didn't play all these years. When I started play in 2019, it was a conversation we had. It was about our daughter, et cetera. But I realized I was like, wait, I've been playing poker my whole career.

2:14:22

Sure.

2:14:35

I just didn't know it. It's the closest thing I'd ever seen to options trading. So I was like, wait, is this what's missing? Cause if we get, who cares how people come into the puzzle, the more differentiated their backgrounds are for us. Right. If you look at 1997 and he and I were partners, that's what. By the way, we weren't married at the time. We were together 10 years before we did. So making that decision, that was a highly unusual decision to chase me.

2:14:35

I love it. I love it. What are you looking for in a CEO? If I want to come work for you and work for one of your portfolio companies, what does it take to make it as a CEO?

2:15:04

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, et cetera, invested, I don't know, hundreds, not thousands of businesses. Self awareness is probably the most important thing because what's going to it can get you in trouble. If you think you're really smart like you, you better be really smart. Poker teaches you a lot of that, that's for sure. That's a good callback there for you. The self awareness, like you control effort, you control attitude. Those two things you really do control. So hard work, great, you're gonna be positive optimist. But awareness, like, hey, we are the best by the way, these other people aren't that good. You should think about it, constantly questioning where you're at and being humble.

2:15:15

Is self awareness around intelligence the main flaw for CEOs or are there CEOs that are overconfident in their deal making ability and their emotional intelligence and their managerial ability and their ability to public speak and do. There's so many different things. The CEO is a bundle of traits. I feel like intelligence obviously super important, making good strategic decisions, executing. But there's so much else that goes into actually running a company.

2:16:11

I wouldn't not say lack of confidence is not necessarily an issue. Overconfidence is disaster.

2:16:41

Interesting, interesting.

2:16:47

You get yourself in a lot of trouble because you know for sure that this is going to happen. And when it doesn't, you're in a world of hurt. That happens.

2:16:49

So what are the signs that you're looking for to suss out if someone is self actualized in that way? Aware of their flaws, aware of their strengths, their weaknesses. How are you interrogating that in an interview?

2:16:58

We hate interviews.

2:17:15

Okay, how do you recruit that?

2:17:16

It's hard. It's hard. We've actually tried to build tech over the years. We've done all different things to try and figure it out. We try and have, without being inefficient, as long of a process as we can to see somebody. So if we can get a student in December for two weeks during their break and see them, or we have a women's trading experience. That's eight weeks in the summer. Anytime we get an extension of time, if we can. I mean, the CEOs is the hardest. They often come from within for us.

2:17:18

Sure.

2:17:50

Now, some of our CEOs did not. But it is our hit ratio, I think on just cold interview. Making it right, I think is really hard. So then of course it's connections and recommendations and all those things because you don't know all of the different pieces of the puzzle. I think people get snowed all the time.

2:17:50

Yeah. Do you have a bright line between deal team, operating team, like those who evaluate a great company to join the portfolio versus those who will be going and operating the businesses?

2:18:12

We have a very, very small evaluating team.

2:18:24

Okay.

2:18:26

Like this is the team.

2:18:27

Okay.

2:18:29

No, we have some really smart. There's some lawyers and some analysts in there.

2:18:30

Yeah.

2:18:33

But at the end of the day. So we don't have outside money.

2:18:33

Sure.

2:18:37

So it's. It's ours. And then our part, our employees. Employees who have become partners over the years. So that's who we're investing on behalf. But we are looking for any guidance. We are just. We know we're not the smartest. 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. 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 on the energy side or on the power side or that infrastructure side for us is new. But we started early and we try and get smart and try and be surrounded by.

2:18:37

I want to get to energy. That sounds fascinating. I want to first ask about sourcing. Are you close with a lot of investment banks or are you cold calling people saying, I want to buy the company? If you're into the deal team, where are the ideas coming from?

2:19:16

Yeah, it's the good ones come from interpersonal relations.

2:19:30

Sure.

2:19:36

Which is why, like in the age of AI and everything's going to be automated. Everything like this really matters. Showing up in a studio where you'll hopefully send us, you know, you'll say, hey, I have an idea for you guys.

2:19:36

That's what.

2:19:48

Vice versa.

2:19:48

Yeah, of course. Of course.

2:19:49

I would say that's 99%.

2:19:50

That's 99% of it.

2:19:52

But it's worked pretty well.

2:19:53

That's so interesting. I mean, yeah, we talk to investors across the category. There's Some that are doing tons of outbound. They have a price for every company in their CRM. They have an army of deal associates that are getting out there pounding the pavement. There's other folks who. Yeah. Just wildly different strategies. It's fascinating.

2:19:54

Well, for being a very quiet firm for a very long time, it didn't allow us to have what we now realize we probably should have been doing for a while is building those relationships. But it's been quick coming out, like coming out and building those relationships and figuring out how to make it work. We're more mature doing it. We know what we're looking for. We made a shit ton of mistakes. So, like, you know, it's easy to start. You know, they're not perfect, but they rhyme with the past. Right. So we're good at. We're good at saying no. I would say yeah.

2:20:13

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. Then at the same time, we talked to Chase Lockmiller from Crusoe. He's building data center, putting up power plants today. There's so many other pieces of infrastructure. So many. The supply chain is so complicated. Where is the opportunity?

2:20:52

We like Crusoe or investors in Crusoe.

2:21:23

Oh, really?

2:21:25

Oh, yeah.

2:21:25

That's amazing. We've got a lot of investments.

2:21:26

And what is interesting in energy is it tends to be these. There's some individuals or individual companies that are doing some stuff that's. That we see as transformational.

2:21:29

Yeah.

2:21:39

So everybody's very worried about energy. Whatever happens with the war, we don't have any thoughts on that. But assuming that things are peaceful, like, hey, is it going to be nuclear? Is it going to be solar? Solar, etc. Geothermal is really interesting. So we're big investors in a company called Fervo, based in Utah. Your viewers should look it up. It's transformational and it's today. So it's built, they're going to deliver. I don't know, 500 megs in. Wow, that's a 2027.

2:21:39

Wow, that's enough. That's the average metacampus right now.

2:22:14

Okay. And remember, it's fracking. It's traditional drilling, but not in traditional areas. Okay, so more remote areas, sure. Are there side effects? It's unclear. I don't think there are necessarily, but maybe there could be some seismic. But that's super interesting. And the people who are doing that, by the way, there's plenty of heat down there. It doesn't heat the planet. There's a bunch of physics around that for physicists. But it won't make the planet hotter.

2:22:18

Yeah. Because net zero.

2:22:43

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 is Taurus Energy. And that is effectively what you saw in Cloud Compute is cloud energy. And so Taurus is. It's basically. It's a flywheel business. Like actually a flywheel.

2:22:45

Okay.

2:23:02

Like a literal flywheel, except it weighs 3,500 pounds power.

2:23:04

Okay.

2:23:08

But it spins. Remember, the issue with power is that it's. Everybody draws at the same time. If you're snow basin in Utah and you draw on power to run your tram at the same time, and everybody's, hey, by the way, OpenAI is going to run one of their, you know, one of their loops, then you're going to end up drawing tons of power. And that's expensive for the grid. So what Nate has done and his team at Taurus is they're a balancer.

2:23:09

The load balancer. It's the load balance.

2:23:36

And you realize there's actually quite a bit of power. How you actually balance the power is the hard part. And he solved it. So they are operating today. We talked to him earlier. He's. He's in a bunch of different states and he's coming to a state near you.

2:23:38

Yeah. I love it. Well, tell me more about Peak 6 trials. Where can people get started? How do people apply or join?

2:23:56

So peaksixtrials.com and we're looking for entrepreneurs who have ideas and everything else is sort of there. You don't have to go and raise money. You don't have to spend time doing that. Think about the things where your specialty is, is your idea.

2:24:04

Yeah.

2:24:19

Right. This is. This is a place with AI. Like, we can do a bunch of stuff around you.

2:24:19

Yeah.

2:24:23

And interestingly, like with Apex, right, we have these 40 million customers. They might want your product.

2:24:23

Yeah.

2:24:29

And if they don't want your product, that's also really good news. So we short circuit all these things that take to say, like, is this a good idea or not? You don't have to worry about the capital. You don't have to worry about paying your rent. We actually pay your salary.

2:24:29

No way.

2:24:41

Yeah. So it's really nicely packaged for someone. I wish we had it at the time. It would have made me feel better. Maybe we were better off because we took so much risk. You never know. But the balance here is we want the people who bring the ideas and we help support and build it ultimately to own the majority of this thing, not for us to own the majority of things. So 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, they can be anywhere. But it's really. I mean, I think it's super broad.

2:24:42

Yeah.

2:25:22

With the fintech sort of space is like everything's money. Every large CPG company who has a bunch of customers, there's some money product that exists or could exist in that ecosystem. So there's a lot of ideas, I think, that are out there. We're going to pick 12 to 15 for the first year and we're going to see what we can do and see what we can pump through.

2:25:22

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?

2:25:43

Well, we have amazing teachers around the country, 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. The banks, the technology firms, the law firms. Yes.

2:25:51

I think they might like it.

2:26:03

It's been wild how people have picked it up. Right. Because first of all, we're not playing for money. We're actually teaching because these are people who know nothing. But, you know, 94% of poker players on the planet are men, so. Yeah, yeah, it's really extreme. So, I mean, after a couple hundred years of this game coming around, it's probably time for women to be doing this. Yeah. We're in 70 countries. We're in rural villages in Kenya, for example. So we are super quick turnkey events. Best events that are on the pokerpower.com

2:26:05

yes, pokerpower.com I love it. Well, thank you both for taking the time to come chat with us. Yeah, of course. We will close the show here on this camera. Leave us five stars on Apple Podcasts and Spotify. We'll be live tomorrow at 11am Pacific Sharp. Sign up for our newsletter@tvpn.com and we'll see you tomorrow. Goodbye. Thank you.

2:26:39