"The Information" Profiles TBPN, AI Ups and Downs, Nuclear Regulation | Zach Weinberg, Leigh Marie Braswell, Stephen Balaban, Sam Lessin, Bobby Goodlatte, Auren Hoffman, Doug Bernauer, Isaiah Taylor

You're watching TV Ben.

Today is Friday, May 23rd, 2025. We are live from the Temple of Technology. The Fortress of Finance.

The capital of capital. And John.

Yes.

This is our last show in this studio.

It is. It is. But the Fortress of Finance lives on. The capital of capital lives on.

It's a state of mind.

It's a state of mind. It's a place on the internet that we, we bring, we create the Fortress of Finance, the Temple of Technology wherever we are. And soon it will be in Hollywood, California, the future home of media and entertainment. Once we're done with it, baby, we're bringing media to Hollywood. We got a great show for you today, folks. We got a banger lineup of guests and topics. Wow, we really filled it out. I thought we had 4 people booked. Turns out we have 7 now. Uh, it's great.

I don't know how that happened, John.

We're talking about the, the information they profiled us. Uh, Abe came down Hung out with us for a full day.

Wrote the allegations are extreme.

Yeah, the allegations of bro culture over here are extreme. We'll talk about Apple's AI struggles, Sam Altman's trillion-dollar AI device. There's a banger quote in the Wall Street Journal from Berber Jin, and then we got a whole bunch of guests: Jory from Linear, Zach from Curie, Lee Marie Braswell, former colleague of mine over over at Founders Fund. Now she's at Kleiner Perkins coming on to. to talk about artificial intelligence, some of the seed investing she's been doing. Remember, she was like a seed investor in Windsurf, I believe. Absolute banger.

Absolute dog.

And we got Sam Lessin coming on. We got the founder of Lambda.

And the great thing— so Sam Lessin, many people call him Jessica Lessin's husband.

Yes.

He usually goes by that in most tech circles. So Jessica Lessin's husband is coming on. And this was booked before we knew if the information was going to be a hit piece or a puff piece. And so it could have been— We don't, you know, still unclear exactly where it landed, but it could have been a very, you know—

Oh, it could be extremely confrontational.

And it still could get—

And I think the first or second time he came on, Jessica Lessin was in the background and kind of stopped by and said, hey.

She said hi. Hi.

And so, you know, if this, if this piece hadn't gone down the way it did, we could have been screaming on the call and she would have overheard us berating her husband about what happened.

But fortunately, I think it'll be pretty PC later, and I'm excited to talk to Sam. And then one of the greatest yappers of all time.

Bobby and Oren also calling in at 2:00 and 2:15, and so we're gonna be going late. It's a 3.5-hour show. Let's do it.

They said, hey, it's Friday, are you gonna take your foot off the gas?

Absolutely not.

Absolutely not.

Anyway, let's read through how the Technology Brothers seized Silicon Valley, the big read in the weekend section of Bloomberg.

And I thought this image, By the way, if we can pull it up, I thought it was— my immediate thought was AI, and you think it's handcrafted. You think they went—

I think there are pieces of AI in here, but then there are also things in here that are collage. There's a lot of Photoshop.

Kind of like the CVPN.

I think the suits might be AI, but the faces are just photos that have just been tuned up. And then—

I like how they made me—

The number overlay, that is not AI.

They made me quite a bit wider than They make you extremely wide. Which is not my exact build, but I'll take it.

So the screenshot that's up on the stream is the real one, but for some reason, if you— on the information, there's like an HTML bug. And so if you shrink down the website, I don't know if we can pull up the one from the PDF, but it makes us look even wider. And so—

How do you have a PDF, John? Why do you have a PDF?

I always make a PDF of everything, of every article, so that we can read through it here on the show.

You are a paid savage.

Yes, I am a paid savage.

Subscriber of the information. The PDF allegations are flying around.

Yeah. Today, the black market is crazy.

Anytime that there's an article that people want to read, it shares around. But yeah, he says, at a time when tech has been at loggerheads with the traditional media, the industry elite have gladly accepted a warm embrace from a pair of insider-y talk show hosts, John Coogan and Jordy Hayes.

A warm embrace. Yeah, that's what I mean. Part of it is that we, we typically don't want to have someone on the show unless if we saw them, we'd give them a warm embrace.

Yes.

So I think that's generally accurate. We try to sort out and not have people on that we want to, you know, get into conflicts with. At some points we'll have people on the show that we disagree with, but—

But in general, the, the—

like, we're trying to have people on.

Yeah.

Instead of trying to have people on just to Fight, argue. You know, we want to just hang out with our friends.

Yeah. If we get to the point where we're getting ultra contentious, we'll probably move to like a pay-per-view model for that.

Oh, yeah.

So if you want to see—

Yeah.

Keith Rabois fight with a journalist, you know, potentially physically, not just on the timeline, we could set that up.

And I'd love to.

But anyway, so in recent months, John Coogan and Jordy Hayes, co-hosts of TVPN, a daily tech news show that has captured the attention of Silicon Valley's Investors and founders have followed the same morning routine. The two men meet in downtown Los Angeles at a members-only Jonathan Club to work out, then sauna together while reading print copies of the Wall Street Journal.

Fact check true.

Fact check true. You have your sweaty copy on the table today. It's real. The image of Coogan, 36, and Hayes, 29, schvitzing away in such a manner is, well, a little ridiculous in this day and age. And I posted That God forbid men have hobbies. There's nothing ridiculous about 2 guys meeting up at a members club.

Yeah.

And having a sauna and reading, reading the Journal.

And he thought I was joking with him, but I was dead serious that we had actually been in the, in the sauna just a little bit earlier.

Yeah. You quote in the article, this was in the sauna, pointing to a bedraggled A-section of the Journal beside him on the club's dining room table. It has sweat all over it.

Yeah.

There's the wide version of us. Because it's been stretched.

The extra wide.

So you look even wider. It's great. Yeah, so I had to prove to him. I actually did invite him to the morning workout. I said, meet up with us at 6:30. It's chest day. We'll hit some PRs on the bench, and then we'll go in the sauna. We'll talk. We'll get breakfast. He was traveling around, couldn't make it, so he just came to breakfast. So I had to prove to him by showing him the sweat on my arms.

Not the first time we've invited somebody to do a workout, though.

It's the best.

And then had them come up with some range of excuses. Oh, I'm not going to be able to get there at 6. Yeah, yeah, I'm sorry.

It is a— it is a high bar. But yeah, we don't do coffee meetings. Naval says set your opportunity cost extremely high.

He said meet like a lion.

Meet like a lion.

Be hitting bench when— when you're meeting with someone.

Naval is the original the lion does not concern himself meme. Like, that's where that came from, basically. Work like a lion.

Basically, he doesn't concern himself with much.

He doesn't. He doesn't concern himself with email.

Yeah.

Doesn't concern himself with coffee meetings. But the gym meeting, it's highly efficient. Actually, I mean, Strauss Zelnick, the CEO of Take-Two, owns GTA, putting out GTA 6 soon. He is famous for doing workouts and doing workout meetings. And so I read that book and I kind of adopted that and started doing workouts with Ben and talking to him about the business while we're working out. And it's just a fantastic flow.

It's the best way to hang.

So they go on. He goes on. Abe goes on to write. Coogan and Hayes livestream TVPN, which they originally christened the Technology Brothers as a knowing nod to the concept of a tech bro on X and YouTube from 11 AM to 2 PM Pacific and publish the recording on Apple Podcasts and Spotify. When I found them sitting down to breakfast at the Jonathan Club, they had mostly prepped their opening commentary on the news. Airbnb's revamp, The Trump administration's proposed changes to AI chip exports, and they had a number of guests booked, such as Founders Fund Delian Asparouhov, Lux Capital's Josh Wolfe, and Eugenia Kudya, whose startup Replica AI hopes to develop chatbots that can serve as human companions.

So here's where it gets interesting, John.

Yes.

He says, like the show's audience, the guests are attracted to quote unquote TBPN.

Yeah, like it doesn't— it's not a real thing.

Like it's not a real thing as a safe refuge from the mainstream media.

Yeah.

One that projects an unabashed, unapologetic enthusiasm. I think this is my best line in here. I'm glad Abe included it. We genuinely love the private markets, the venture capital industry, the startup industrial complex.

And I do.

Yeah. So there's something interesting here. TBPN is in quotes, but I'm on a different article from The Information and it reads, Jim Cramer, CNBC's Mad Money host, took a swipe at our report today. And CNBC isn't in quotes.

Why is that?

That's so interesting.

I wonder if it was just a bug in the— Maybe they see it as more legitimate. Oh, it could be a bug in the CMS, in the content management system.

Maybe they should switch content management systems. I like making— if bugs like that are sneaking into articles, Abe's our boy.

Yeah.

And I'm going to just— I'm going to assume that it was just an accident.

Probably just a mistake. Yeah, probably just a mistake.

Anyway, since TVPN debuted last October, Hayes and Coogan have warmly welcomed investors from pretty much every major firm. Venture, venture firm in existence.

Let's go.

We're Switzerland. We're Switzerland over here. A marker of the podcast's widening appeal. Sequoia, Khosla, Lightspeed. I could go on. A week or so ago, they dispatched one of their 4 producers to Las Vegas to set up a mini studio at Andreessen Horowitz's annual Investor Day summit, where the firm's executives could chat about tech, the news, and what they were presenting to their investors. A level of access no one in regular media would ever get. Thank you to Eric and the whole team at Andreessen for making that happen.

And I want to do more of those. I'm talking to Khosla about that. I think that's an interesting thing, the sit-down with the full partnership to get the full scope of how everything fits together. Because most founders, even in my career, I've interacted with every fund, but usually just a single partner. And so you usually have this very point— maybe you've listened to Marc, Yeah. Or, and then you've interacted with, you know, David George on a deal or David Haber on a deal or something like that. It's rare to be able to see like all in one. And I like the way that that came together. So I'm hoping to do more of those.

Anyway, so it goes on. He includes TBPN in quotes again, which is—

TBPN is in quotes every single time it's listed.

And the information includes TBPN in quotes. Anyways, he goes on, talks about some of the guests that we've had. I thought this was funny. Augustus DeRico, whose startup Rainmaker Technology has come on the show, has a sky-high dream of commercializing cloud seeding, a process of adding chemicals to the atmosphere to increase precipitation. He's a good writer.

Sky-high dream. It's a good line. As Hayes and Coogan have won attention from a swath of the technorati and have achieved a constant social media virality, their A consistent social media virality, their audience has remained incredibly niche. While they see X as their main platform, they have just about 130,000 followers on their accounts, and the one belonging to the show on YouTube, TBN, has only around 7,000 subscribers. It's weird to be like incredibly niche, 130,000 followers. Like, how many you got, Abe? How many?

Hey, let's let's pull up. Let's pull up your analytics for analytics. No, let's go analytics for analytics.

When was the last time you dropped? 20K banger on the timeline. Let's check it out. Let's see. Let's see how wide. You know, Jordy has 100,000 likes on a post.

150.

150K likes. Is that niche?

Is that niche?

Oh, you know that my Xi Jinping video on YouTube has 3 million views? You know that my analysis of Mark Zuckerberg's metaverse attempts has 8 million views? How niche is that? How niche is that?

No, we're niche. We're proud. We're proudly niche. Proudly niche.

Yeah, I mean, this is actually something we think about, is like, there are obvious TAM expanders. Politics is the obvious one. And we've deliberately said we're not going to try and TAM expand. Is Abe watching?

Abe's watching. He says, I demand a rebuttal.

Should we let him call in right now?

Yeah, let's have him call in.

OK, send him the link.

Send him the link. Abe, come on in. Come on in. Anyways— They have no investors and profess to have zero intentions of raising capital, lest those investors disrupt their plans.

He didn't mention our incredibly complex corporate structure because we do have a nonprofit that feeds into an LLC that feeds into a C corp that feeds into the labs, which is of course owned by Wilmanitis.

Wilmandus.

Wilmandus.

This was a fun quote which I stand by. We could go out and within an hour, I guarantee you we could raise Probably like 15 million, and I believe that would destroy us.

I think that's true.

So we very intentionally not raised.

It would be your final party round.

The final party round.

The final party round. If you pull it, because I mean realistically, we could get everyone, but it would very much change. It would very much change the dynamic of the show.

Yeah, it would be.

It would be less fun. I asked Ramp CEO Eric Gleiman what he found so appealing about the show, and he likened their approach to how ESPN chronicles sports, where SportsCenter has. has players, coaches, and games to celebrate and explain. TBPN has founders, investors, and developer conferences. They're able to bring to life the personalities, the play-by-play, and capture the zeitgeist. Thank you, Eric. That's a great quote. That's exactly what we're going for. Coogan and Hayes often hear themselves compared to ESPN commentators, but the analogy's sort of lost on them because, putting a major dent in their broke credentials, neither watches much sports content. To Hayes, the natural comparison is to Clubhouse, an audio social media app that was popular for a moment during the pandemic. We've taken what the magic of early Clubhouse was, where you could hear an interesting, uh, an interesting investor or founder talking in real time about what was happening that day, what's in the news, and turn that into a show. Ultimately, allegedly, if it exists at all, if it's a real thing, hopes to better capitalize on the same broad truth about tech's relationship with old-school media that underpinned Clubhouse. More and more, Silicon Valley has come to distrust traditional journalists, perceiving them as holding an unshakable bias against the industry, part of an undeniable broader shift in American culture against the established media. Many within tech have tried to build their own in-house media operations or have rapaciously thrown millions of dollars at would-be disruptors like Clubhouse. Most such efforts have flopped, mounting to little more than lame public relations. Cook and Hayes seem to have found their sweet spot. They maintain just enough independence from their subjects but feel none of the pressure for critical coverage most journalists in their position would. They also get far on their twin blessings of easy charm and boyish good looks. And now this is interesting, because charm is a little— it's a little bit of a charged word in my culture.

Totally.

Irish culture.

Yeah, so I'm Irish, obviously.

For those that don't know, Hayes and Coogan—

We're both Irish.

Scott's Irish.

And so, you know, St. Patrick is obviously a famous snake charmer, and charmed all the snakes out of Out of Ireland, and so it's it's it's kind of like racial humor. Is this like?

Is it racial?

I don't want to go racist, but it's racial. It's definitely racial. And so yeah, it's a little bit edgy, but I I mean I appreciate it. It's fun. Yes, we're in the post woke era. We're in the anti woke era.

Totally. And so if Abe wants to go there, Abe can go there.

He can go there.

He can go. We can go charm for charm with anyone.

We can go charm for charm with the best of them. It's just a little crazy because I haven't been called a snake charmer.

You don't normally think of information content editor as an edgelord.

Yeah, no, you don't. But, but he snuck it in. Yeah, it's good. It's a little— it's a good little dig. Oh yeah, I saw him chugging Guinness, passed out like a drunk Irishman. You know, he didn't go that far.

He didn't go that far.

He stepped it back. Yeah, but he still threw in a little bit of the Irish, a little dig at the Irishness. Yeah, makes sense. They have an interesting— they have an interesting voice that I don't think many people could pull off, said Ashlee Vance, the Elon Musk biographer and former New York Times and Bloomberg journo. Journo? They use journo? I thought that was our word for them.

And Bloomberg—

he's taking it back. Abe's taking back journo.

Wait, that's actually interesting.

That's crazy.

He highlights earlier— no, he highlights earlier in the article that we took back tech bro.

They're taking back journo.

And, and but, but, you know, tech bro was a slur. We took it back as technology brothers. But he's taking back journo. Yeah, he's kind of inverting it.

Yeah.

He's saying, I'm not a journalist, I'm a journo.

Journo. It's kind of cool.

It's kind of cool.

I'm into this.

It's kind of cool. Journo. Journoism is back.

Yeah. What is it? What is a kibitz? Do you know what that is? Because it said Ashley came on for a kibitz. Look on and offer unwelcome advice, especially at a chat. A chat. Oh, a chat. Okay. So he came on for a chat. Yeah. And he's coming on. He's coming back next week. He's been traveling, shooting a movie. Very cool stuff. I don't know if you saw his cinema rig, but he's got like 25 different cinema cameras. It's amazing. I'm very excited to see what he's doing. I don't want to leak too much.

Abe is—

Abe is in the temple. He is.

Okay, let's bring him in. Abe, we got to get to the bottom of this.

Abe.

Okay, we're pulling him in. Wow. Abe on TBPN for the first time ever.

I could go into exactly why CNBC doesn't get quotes and you guys do, but that seems boring. Let's talk about something more fun.

Wait, wait, hold on, hold on, editors. The chyron's way wrong. Can we put the information in quotes? Can we put the information in quotes?

Put the information in quotes.

We have to.

Hey, it's fantastic to have you on. We talked about this earlier. We knew— I mean, Jessica Lessin's husband was going to come on later, later today. And it would have been a funny kind of dynamic if this had been a hit piece, which we obviously didn't know until around 9 a.m. when you hit publish. So this will be a fun show end to end.

Yeah, it was great. I don't know. Is there anything else that— I mean, you've been listening to our analysis. Anything else you need to get off your chest?

No, I think the story, you know, is a piece of fair and accurate journalism. And, you know, you guys are— you guys are doing what you do best, which is, you know, commentating on the news, on the breaking news about the Technology Brothers. Wait, I have to ask, did you intentionally use the word journo instead of journalist when talking about Ashlee Vance?

Yeah, because we think of journo as like a tech bro style, like, like dig, like it's almost a slur for journalist.

It's like, you know, guys, in the way that you're funny on camera, yeah, I also try to be funny in the way I write.

There we go.

You know, just to, you know, make the, make the, make the jokes go around. No, you nailed it.

You nailed it.

I mean, it got us. We were cracking up. It's great. Really good. I'll be back in LA soon, and I'll take you up on the sauna.

Let's do it.

Fantastic.

We can't wait. Yeah, we got to get a big one in the new studio. Like, we got to like basically dedicate 2,000 square feet to just a single sauna. For sure. Abe, thank you for the fun and fair coverage of what we're doing. It's fantastic. And likewise, you guys are a good hang. Don't be—

don't be too nice to Sam.

Okay.

Okay.

We won't. We'll be rough on him.

We'll put him in the street zone.

Awesome. Thanks for jumping on. See ya.

Look at that.

Look at that. Media, technology.

Yeah.

You know, just Bro-ing down. It's great to see it.

They give a little bit of our background, but then go on to talk about how we met. Mutual friend. Did they actually not? They didn't.

They didn't name Will Mandis.

They didn't name Will Mandis. Saw an opportunity for a tech-focused podcast that could analyze industry news with a light irreverence and wasn't tied to a single company or venture firm. Last fall, they had enough free time on their hands to record a couple test episodes when they attended Peter Thiel's Hereticon at the Faena Hotel.

Oh, they put founders in quotes.

No, they sought out feedback from David Senra, host of the popular Founders Podcast, if you can call it that. Wait, did Abe actually tell us why they put it— why he puts it in quotes? I don't think—

no, he said it. He said it wouldn't be fun.

Okay.

It wouldn't be fun, which is—

yeah, yeah.

Which is fair.

No, I mean, it makes sense. You're introducing this to the first time to your audience. Like, we're giving a hard time, but like, yeah, obviously called TBPS. Yeah, yeah, yeah. It's like, like If TBPN becomes like driving news and the Information months from now has written about comments that were said on TBPN and they're citing us, I imagine that we will become unquoted. Like, we will earn the removal of our quotes. I can't wait.

Earn your stripes.

We're throwing off the shackles of the quotes. I'm excited. That's definitely on the vision board, right next to TBPN arrow on smoothie. You heard it here first.

We're working on it.

Life goal. He said, David Sendera previously advised Coogan on his YouTube channel. This is funny, because it was very, very informal, but I did learn a ton from David. I remember the very first time I talked to him, I was doing my YouTube channel very much part-time, on just one day a week on the weekend. When I was bored, I'd just put up a video, and I did one a week. And it was growing, and it was doing well. And I was just like, wait, like, you have this podcast that's like— this is pre-deal. This is pre-Invest Like the Best partnership and pre-meeting Patrick and stuff. So the show was pretty small at that time. And I was like, wait, you do this full-time? And he was like, yeah. And he swore it too.

I was one of the first advertisers on Founders Podcast.

I had no idea.

For Capital. No way.

Yeah, I was like one of the first one or two. I certainly won't mention it here, but— and the funny thing is I had actually reached out to David, and I really didn't— I listened to the first episode, and I reached out to him, and I was like, would you— this was at a time that was like, every tech company should be a media company, which I don't agree with anymore. But I was like, would you consider joining? Like, he told me his ad rates, and I was like, well, what if we just acquired founders? Yeah, yeah, yeah. And in hindsight, that was such a ridiculous thing to ask, because David— never under any circumstances would have done that or anything like it, um, nor would it have been good for the show. But, uh, but yeah, at that time it was like very, very—

Yeah.

You know?

Yeah, no, I remember getting on the phone with him and he was telling me like, I was like, do you, so do you do this like full-time? Like, how do you even make that work? He was like, and he swore a bunch. He was like, absolutely. Like, I, I don't do anything else. This is all I do. And I was just like super impressed that he'd been able to make this work. And it is like a niche show. It certainly was at the time, but he, Obviously found a really high-value audience and was already monetising very well. At that point, he had a paywall for some of the episodes. He was starting to do some advertising. He's evolved the business model a ton and probably grown 100x.

But it was very humble.

The product quality was incredible.

Yep.

But he was like—

it was still— It was just him. No employees, nothing. Just building, building, building. So it was very, very cool. And so, yeah, I mean, I learned a lot from him and kind of kept growing the channel and then eventually evolved into this. He thought that the two shared natural chemistry and encouraged them to go all in on the concept, which we told about which we've talked about before. For a model, he suggested they look at sports commentator Pat McAfee. Senra admires McAfee's always-on persona. What is Pat doing right now? I bet he's livestreaming, he said. And I wasn't exactly sure because we've looked to Pat for, as like a role model in many ways, but I wasn't exactly sure where that came from. But I thought the most interesting lesson that I learned from David was that he actually did not tell us you guys should livestream. He told us, you should take this—

Go harder.

100x more seriously. You should go harder. You should go full-time on this. And what was interesting is that the— we were doing a weekly podcast with no guests, and once we started taking it way, way more seriously and working on it constantly, then switching it into a daily show, switching it into a live show, switching it into a guest-led show, all of that just happened very naturally. He didn't tell us tactics. He just told us exactly what he said, what he says in every episode.

We left Miami and we decided to go to 2 or 3 days a week.

3 days a week.

Yeah, maybe it was 3 days a week. But then I remember the realization that we would stop recording and we would be on X like an hour later. And I'd just be like, I wish we were doing the show tomorrow.

Yeah.

And we just eventually decided to go to 5 days. Then we decided to go live and we Decided to add guests.

I even remember talking to you about, like, maybe we should do, like, 1 day a week, 5 hours, and then slice it up so we're releasing 1 hour per day.

Every podcast weekly, Jon.

And it was a terrible idea, and I'm so glad we didn't do it. It's a way, way better format. And so Abe goes on to write, soon Coogan and Hayes landed on an early gag that helped them gain attention— print out posts from X from founders and investors, then dress up in suits and film themselves with top-end 4K cameras discussing the posts, a very high-touch approach to assembling retweets. Later, they started to share the clips and tag the post's authors on X, and the authors would often frequently pass on the clips themselves, giving Coogan and Hayes some of their first virality. The pair set themselves up on the 10th-floor office that Coogan rented in the Jonathan Club, hired a small video production crew.

Who they sometimes refer to as just— The guys.

The guys.

Well, since, well, they're all young men. And, uh, over the course of the next several months, the TBPN hosts and the guys have adopted a steady rhythm. When Coogan and Hayes go live, 2 of the guys control what appears on the stream, including the chyrons, uh, the bit of text below the guests.

Funny, I didn't even— we didn't even know the, the term chyron for like— we had been doing a chyron for quite a while.

I knew it. I had to explain it to basically everyone on the team.

We all learned.

But I had in fact heard the term before. Um, but yeah.

Um, you have a background in television job that we don't know about?

No, I've been to NAB. I've been a nerd for like production for like several years.

Yeah.

And so I've been like loosely familiar with all this stuff. Watched a lot of YouTube videos explaining how churches do live streams.

Oh yeah.

Because megachurches are elite delivering at a level that is equivalent to Fox News on 1/100th of the budget. And so you can just go on YouTube and search church live streaming setup and they will have tested everything and they share all the information. It's a bevy of resources. It's fantastic. And some of them do like virtual productions. It gets crazy. Anyway, they tried to make these funny. One example, venture capitalist yaps about venture capital. I'm excited to share a screenshot of Abe Brown, writer at The Information. Did you see the final chyron?

So good.

So good.

Steady crawl of the show sponsors appear next to the chyrons, along with a ticker available of available polymarket bets with Coogan Hayes as telling indicators of market its sentiment and their audience's interests. That's true. Another of the guys spends the entire show, entirety of the show, cutting up clips to publish across social media as quickly as possible. Fourth, Ben Kohler. Let's hear it for Vice President Ben, who works with Coogan on his YouTube videos, serves as head producer. On a traditional TV show, a producer would normally pre-interview a guest. Sounds really boring.

Yeah.

To help both the guest and the host.

Not doing it.

But Coogan and Hayes prefer to wing it. And since they're never brandishing any sort of gotcha question, We'll hit you with some gotchas. We're just going to do nerdy gotchas about scaling laws and—

Gotcha.

And build-out timelines and end-to-end algorithms. We're not going to ask you about your personal life or your politics.

We do not discuss politics.

The informality doesn't discomfort the guests. There's no prep. They just sent me a Zoom link and I joined, said Shyam Sankar, Palantir's chief technology officer and a veteran of many CNBC hits. To fill the guest spots, Kugan and Hayes tapped their Rolodexes and industry connections. Unsurprisingly, They've started to get inbound requests. We're at the point where we're getting 20 pitches a day from PR firms, Coogan said. We turn down 95%. His rejection method is simple. He goes to X and checks whether they've shared recent— what they've shared recently, their number of followers, and whether they follow the same people. Yeah, I'm generally looking for, like, are they tapped into the news? Are they following technology stories? Are they— are they—

you know, they're on their own wavelength. I wouldn't say this is— One part of the process, but certainly we've had people on that don't have a presence on X, and we actually want to do a lot more of that. Totally.

Yeah, totally. But how to fix that is a part of the conversation. But if you're just getting a pitch instead of a warm introduction, it's very hard to get a pitch from someone that's very dry. And then— because every once in a while, there's someone who is interesting that just happens to have a stale PR team that's kind of pitching broadly, and you've got to just deal with that. But most of the time, if there's just some stock, like, You get these big emails with all these bullet points about everything the person's accomplished, and then they link you to their LinkedIn account and you search them on X and like they're not really in the conversation. And if they're not in the conversation, it's going to be hard for them to join and have a conversation because that's not—

bring something really—

they're just going to come on with talking points. And so, yeah, it's pointless.

Or if they come on with LinkedIn takes from—

it's not good.

2 months ago.

Not good.

Going to be rough work.

Hayes and Coogan delight in their shtick for the show, which includes opening bottles of Dom Pérignon to mark its growth, a constant tongue-in-cheek shilling of Ramp, Ramp, Ramp, Ramp, Ramp. Which makes expense account software that would exasperate many madmen, but not us.

Not us.

Not us. Switch your business to ramp.com. Save time and money.

Just do it.

We had a whole running gag with Abe the entire time. We probably pitched him Ramp 7 different times.

At least.

At one point, I introduced him to Eric over at Ramp, and I, uh, and then I immediately followed up, acted like I took him off the email thread, and told Eric, here are the talking points we're sticking to.

You gotta post that.

I gotta post that.

And it was just a whole bunch of details about Ramp and how—

Abe at one point said, guys, I don't care about expense management software. Please stop pitching me. Something to that effect. And we said, well, Abe, you know, a lot of Ramp customers felt the same way at some point. But once they understood just how much time and money they could save—

We had so much fun with it. It was great.

So much fun. Thanks for— thanks for being a good sport.

Yeah, he was a good sport about it.

And a preference to always appear in suits, their visual trademark. Coogan gets his suits from a tailor. Whose identity he wouldn't reveal. Hayes likes the user, a New York-based. I guess they're a brand now, but they are primarily a tailor. It's Laura Piana fabric.

He assured me.

I guess me and Jamath have that in common. Watch peeking out from beneath the sleeve. Okay.

Doxed. They doxed your watch.

They doxed my watch.

They doxed your watch. The suits are a little dig at Silicon Valley's preference for the informality of kotopaxi, which. Is that how you pronounce that?

I've never heard that before. Never worn it.

Um, Hugen hopes they serve another purpose too. It's going to make it easier to appeal to a public company CEO who's running TBPN. Oh, we got single quotes now. We're upgrading. Oh, because it's inside double quotes.

He still hit the quotes.

He got us. I was so excited that we were halfway to no quotes.

Yeah.

We were getting double quotes. Now we're just getting single quotes. The next thing's no quotes. Uh, by his PR team that's maybe more conservative and more risk-averse, he said. So when they pull up an example, they see a very clean package and everyone's and suits. And that's true. I want to be a place where big public company CEOs can come on and it doesn't feel like we're disheveled, not taking this seriously. It needs to be brand safe even for big tech companies that want to uphold a very serious brand standard that they would feel comfortable on Bloomberg or CNBC. They should feel comfortable here as well. The external appearance—

That's the external appearance at least. This is when he's putting us in the truth zone, putting us in the truth zone, Abe. Internally, the atmosphere is decidedly informal. When the show wrapped on the day one— on the day I was at the Jonathan Club, Coogan and Hayes casually stripped down to their boxers in front of me and the crew, changing into t-shirts, shorts, pants, and sneakers, and then issued a few instructions on finishing the day's production and preparing for the next day's show. Well, he got us, John.

We're spitsin'.

There is We do at times wear normal clothing.

We do. Waving goodbye to the guys, we loaded into Hayes' Mercedes-Benz G-Wagon. Wow, he didn't even— he didn't even say the most important part.

That it's an AMG?

It's an AMG. It's a G63. Yeah, that's a really important detail. Leaving that out, that feels intentional, trying to take you down a peg. Could be a G550.

I like it though. It's more, it's more subtle.

Yeah. Yeah.

It's a dude.

He's just leaving it open. Could be any type of G-Wagon.

Yep. And we, so we drove Abe over to Hollywood to see our new 4,000 square foot studio, uh, that we just signed a lease on. Abe says it dwarfs the size of the current set they have in the Jonathan Club. We are in a very small space on this set. Uh, and they're looking forward to the increased flexibility it can give them, including the ability to get up and walk around while streaming and basically screaming too.

Yep.

Right now we basically sit down for 3 hours.

3 and a half hours. We get up for like a minute in between, but the energy level will be so much better when we can stand.

It's going to be great.

It's going to be great.

They'll also have the opportunity to host in-person guests, something we're very excited about. We have a bunch of people lined up, and we should be able to make those in-person sessions really special. And I asked them about the dream bookings. Of course, we've talked about this before. Our dream bookings are the Magnificent Seven. Like all of them. We want the CEOs of Apple, Microsoft, Alphabet, Amazon, Nvidia, and Meta Platforms, and Tesla. We want them all. The Thanos glove of technology leaders. We want them all on the show.

So if you know someone who gets an introduction, please make it happen for all of them.

But we still have a lot to do on the production side. We want to be a fantastic show. We want their first appearance on TBPN to be memorable.

Cinematic.

And cinematic and enjoyable. And I think— and most importantly, I think it's less about asking the hard-hitting questions. It's more like, what are the questions that the investing community actually wants to hear? How can we dig through those and drive those questions that move markets? That's what's most important. The the questions are less gotchas about random things that don't really matter to earnings, which is what a lot of the news has become in tech and business because the audience are not investors. We want to focus on the questions that investors actually care about, which is more often how's capex looking? Which is like is that a gotcha? Well, for some companies it might be if their capex is looking rough. It might be.

Satya says. We're happy to be leasers.

Is that— is hitting him with a question about his pivot away from data center buildouts a gotcha?

Yeah.

Certainly not to a normal person who doesn't invest in the stock, right? But to someone who really cares and owns a lot of Microsoft stock, it's probably pretty important. Anyway, it might be easy to design a show that would appeal to 1 or 2 of them, but it would be difficult to do one that could attract the entire set. They've all done podcasts, but there's no podcast that has done all 7. And says Coogan. That's me. On the drive over, Hayes mentioned a dream prop for their Hollywood set. He and Coogan already have a small gong in their Jonathan Club that they ring on the show when talking about a company's notable achievement, but he would like to buy an even bigger gong. Looking around at the Hollywood studio, he could see how nice an extra-large version might look. Yeah, we finally have the space for it, he said. Oh, what a fun piece.

I can't wait. We need a 50-foot by 50-foot gong that requires a group of people to stop it from ringing when you drive a car into the gong.

We do.

We're working on it. What should we move on to?

I mean, the main thing we have to cover. So yesterday X was a nightmare.

Yeah.

DMs weren't working for a lot of the day, which was rough for us on the show.

Apparently there was literally a fire in the data center.

Yeah, a fire broke out Thursday morning at a data center in Hillsboro, Oregon, leased by Elon Musk's X, forcing an extended response from emergency crews, according to multiple sources who spoke to Wired. The sources required anonymity as they weren't authorized to speak publicly about the company. Firefighters arrived at Hillsboro Technology Park in a suburb west of Portland at 10:21 AM. Man, John, Portland, Oregon vandalized. You think this is— you call it arson?

I have no idea. I don't even know how you, how you vandalize or commit arson in a data center. They seem to be locked down.

The— yeah, but the— every time I see Portland in a headline in tech, maybe it's some type of—

This is pretty advanced stuff to figure out where the data centers are.

Okay. I'm sorry. If you're an extremist and you want to bring a bunch of gasoline—

Will Moneitis posted that whole thread about shooting the transformer. And taking down all the electrical infrastructure and how like you can basically take out the energy infrastructure with just small arms. So like an AR-15 shot at a transformer can take off a whole, a whole, whole piece of the grid. And so you would think that they'd go after that.

I don't know.

It's very, very, very odd. Hopefully they sort it out quickly.

Yeah. So it's interesting. So before—

I mean, Teslas have been setting on fire, so maybe X data center.

So this is interesting. So before Elon bought Twitter, the company had 3 data centers in Sacramento, Portland, and Atlanta. This ensured that if one data center went down, traffic could be shifted to the other 2 and split so no single data center was overwhelmed. Around Christmas Eve 2022, Musk shut down X's data center in Sacramento in an effort to cut costs. The company experienced a major outage in the wake of the shutdown. Over the next 6 months, the company moved more than 2,500 server racks from the Sacramento facility to data centers in Portland and Atlanta. So it sounds like they have 2 core data centers now.

Okay.

I want to rip through a bunch of stuff really quick.

Let's do it.

I'm just going to rip through this stuff. So Donald Trump just signed an executive order about nuclear. And so we're going to try and have some folks on very quickly and slot them in. Might be 2:30, but I'm talking to some nuclear folks about coming on and breaking it down. I haven't even had a chance to read it yet, but it that's out apparently. I don't know if you wanna dig into that. I also wanna give you the final analysis on Apple's AI struggles. We've been dipping our toe in and out of this story all week, but Ben Thompson had a great summary of the problems with Apple's AI strategy, and he sums it up in these bullet points, which are really rough. One, Apple's head of software engineering didn't believe in AI. Apple's head of AI was skeptical about LLMs and chatbots. Apple's former CFO refused to commit sufficient funds for GPUs. Apple's commitment to privacy limited the company to purchased datasets instead of using like their own where Meta and Google and YouTube are all highly valuable training sources. Apple's AI team is understaffed and the relative talent of an AI staffer still at Apple is uncomfortable to speculate about, but given the opportunities elsewhere, relevant. What should Apple do now? The baseline advice from Ben Thompson is make Apple's on-device models available to developers as an API without restriction. Make Apple's cloud interface, cloud inference available to developers as an API at cost. Allow Siri to be replaced by other AIs, perhaps for subscribers to those AIs who would revenue share with Apple. So you can bring ChatGPT into—

I bet for the access to the Siri button, Apple could get like 50%. 50% up from their typical cut.

Yeah. I mean, just hold an auction. Just hold an auction and be like, hey, yeah, like, we're, we're just not gonna hit this out of the park, so we're just gonna auction it off.

It'd be great.

They have precedent of selling the search bar.

Yep.

Right.

Yeah.

Why wouldn't they do—

Anyway, the other, the other news is people are now speculating about the exact device that Sam Altman and Jony Ive will be building together at OpenAI with the I/O acquisition for $6.5 billion. Swyx, who's been on the show, says they literally copied Avi Sheffman. $6.5 billion for what Avi Shipman built in the cave with a box of scraps, quoting Iron Man, of course. And there's an old video from Avi pitching the first Friend. And I mean, what a throwback. I remember this.

I mean, this is what I was saying, I think on Wednesday or Tuesday, it was like, yeah, this could end up being extremely validating for Avi.

Yeah.

Friend.

Yeah.

If he ends up nailing— I mean, To be clear, he's also, I think, focused on a much different use case.

I agree.

Like friend.com.

I agree.

It's built like a companion.

To be fair, the bear case for Friend is that they wind up in the same position as Pebble, which is that they do the discovery to find out that smartwatches are a good thing, and then Apple comes out with the Apple Watch. They just leverage integration, and it's just a much better product. And then Google didn't need to buy Pebble. They just created the Samsung Galaxy Gear or whatever, the Samsung watch.

Yeah.

And so the existing hardware manufacturers, they haven't had to buy companies. And so they've wound up putting— like, a lot of the— there's not a winner in independent smartwatches. And so if there is a pioneering new format and OpenAI has a serious hardware product in the space, and then Apple copies it quickly, and then Samsung copies it quickly for the Android ecosystem, you're kind of left out to dry. So obviously, I'm pulling for him, and I hope he can wind up navigating it and counterpositioning in a way that he creates something that's truly disruptive.

Yeah.

But it is serious business right now. But Augustus sums it up well. He says, I have no stake in SFAI hardware, but this seems right. And it's the giant going up against Avi Schiffman and Friend.com. So good luck to him. But yeah, the current prototype is slightly larger than the AI Pin with a form factor as compact and elegant as an iPod Shuffle.

One of the intended uses really was a magic product.

Yeah.

Um, were you too—

were you kind of too mature for a shuffle?

Hmm, I don't know if I ever had one, but I think it was more like a poverty problem. I don't think I had the money for it. Um, but it was, it was very much like an accessory.

Inspire you to grind?

Yeah, I should have been grinding harder, but honestly, no. You know what it was? I was too much of a nerd. So I had, I had something called like an iRiver, which was like Yeah, that's kind of what I was— Very unique thing that, like, it was technically more advanced than the iPod at the time. Like, I had one that had a color screen that you could watch movies on. It was like a 2-inch screen, and it was well before the iPod Video came out by like a year. And so the release cycle was faster, and you'd get newer tech, but it was like borderline unusable because there was no focus on user experience. And so the company wound up kind of just not Not, not ripping. What else? Oh, Sam Altman. There's an exclusive in the Wall Street Journal by Berber Jin, a quote in here about what he's planning here. And we just gotta read this one quote. Altman suggested that the $6.5 billion acquisition has the potential to add $1 trillion in value to OpenAI, which is such an insane thing to say. It's so crazy. But at the same time, How much is Apple worth? If you get a play in that space, like, yes, $1 trillion in market cap is totally up for grabs. And so, I think it's like, it sounds ridiculous, it sounds like over the top, but that really is the expected value. And so, when you think about it as like, what is that, a 0.6% or— yeah, 0.65% chance at $1 trillion.

Yeah.

probably worth $6.5 billion, right?

Yeah.

In equity. And so that's the deal that they made, was that, hey, we're going to get this team that's going to run really hard at this. If they hit it, it's low probability, probably a couple percent chance that they pull it off. But if they do, it's $1 trillion. So it's totally worth the high number. At least that's probably— that's one way to do the discounted cash flow and the valuation. And we've sliced and diced the $6.5 billion a bunch of different ways. And I think we both came away with this idea that it's not as crazy as it sounds. It's 2% of the company. You're getting a great executive. You're getting a whole team. And it seems like a big number. They haven't shipped anything yet. That's crazy to buy something that doesn't even have a product for $6 billion. But when you think about the market, the opportunity, things start piecing together. And it could wind up looking very good in hindsight. But who knows? Anyway, I don't think there's anything else we need to go into before we bring in our first guest.

We got Jory. From Linear. Let's bring him in.

Let's bring him in. How you doing?

Hey guys.

Welcome to the show.

How are you?

We're great.

Good.

Having fun reading through the information, looking at the new Sam Altman I/O acquisition. Have you— do you have a take on the new device? What do you want to see in the world of AI hardware?

I don't know, to be honest. Let's see when like things start shipping and like how things like evolve.

It's been Have you had a chance to play with it?

I mean, it's great to see, like, I've again, like, in the driver's seat and, like, on the news, like, doing interviews and so on. So I think, like, it's like I had a break from for, like, whatever, like 4 years or, like, so. It's been a while.

It's more like a 2-year stop. John called out it was, like, very strategic to go have him do a big interview at Stripe Sessions and then immediately the next week, you know, come in with this massive announcement. But I'm excited to see. I think every technology—

Call that a coincidence in my parts.

Yeah. Yeah. But I think every technology enthusiast will benefit from him taking a real crack at AI.

What else in the news this week? It's been kind of an informal AI week over here at TBPn between Microsoft Build, Google I/O, OpenAI I/O.

Linear agents.

Linear agents and Anthropic Claude 4 dropping. What's been most interesting to you? What are you most excited to leverage?

Pretty bad week for me for following the news. I finished up moving, so I've actually been relatively off news. I think it's on the docket for a long weekend to start catching up more on all the keynotes and so on. But I don't know, it's good stuff having more agents, especially coding agents and different players coming coming into the space. So I think it'll be interesting to see over the next couple of weeks what performs how well and also what kind of user experiences are going to be there. Because I think that's kind of the bit that we're at Linear now following much more as we're also trying to work with different players and integrate stuff into Linear. What are like the patterns of like usage that will happen with this?

Yeah. What's more important? Just vague definitions around user experience patterns for agents versus standards like MCP and more technical advances?

Yeah. I mean, like those are like very 2 different things. I think like, you know, like MCP and like open standards, like that's like personally I'm like very, very like pro, of course, as an engineer. But it's been something like, I think like we kind of like lost in like last decade. Of like the big platforms owning more and more on their own, trying to hoard everything. But now things are pretty much being pushed out in the open and people are like, companies are almost forced to cooperate in the new world. There's just so much demand. And it's been interesting to see from our side too, as large companies jumping very early and So like a whole space is kind of like pushing all the companies to like act fast. Let's see how much is like, you know, hot air, like what like will come out of it. But I think like overall, it's like push for openness is good. But then how have you—

So yeah, so for Linear's agents product, how do you evaluate how open is the product? If somebody's building an agent, can they build an integration with Linear by themselves? Or are you guys really kind of doing your own internal testing to kind of qualify potential partners there?

Yeah, we're, we're kind of like looking more on the promotional side, I would say. Like, we believe in like open APIs and like trying to like have people access. But then I think like the, when it comes to like security and these kind of things, it comes more on like, what do you like promote?

Sure. Yeah.

Yeah.

I mean, at the same time, like if I get a really amazing agent that just can puppeteer my mouse and keyboard, You can't really do anything about that. Maybe you throw up a CAPTCHA, but agents are gonna be able to solve those pretty quickly. And so at a certain point, you have to think like, like you're, you know, there's a reason why you have an API. There's a reason why you have an MCP server. There's a reason why you have maybe an agent integration. But are these like temporary steps in your mind, or do you think that there's real durable value to an agent? Like a standardization, something that you build in-house, some sort of protocol or some, or standardizing against things versus just like MCP. I kept coming back to like, can't the LLMs, if they're really so smart, can't they just use websites? But what's your take on that trend?

Yeah, it probably comes like down to like the user experience that you want to like offer. So, you know, like controlling a computer or like VM or whatever, like that's the kind of like the ultimate like band-aid to like everything. Like it allows to do everything, but it's still like, it's not purpose-built.

Mm-hmm.

But, and like MCP to a degree is like a little bit like similar. It's just like a way to like do like do request response, like calls and get the information in and like share that. But then it's more about, I think like in our mind is like, what is the experience inside the product that you're going to offer that maybe is specific to that product and how does that work. Today, our implementation is somewhat rudimentary that you would expect. Agents look like regular users, but it's not very exciting to see the progress of the agent when they're posting new comments.

Yeah.

That's a little bit of a hack that you kind of have to live without while we still see what's actually required and what can we build to better support the agent developers, what kind of experience to give them. Of course, we're looking at this from the lens of Linear, of course, running the company and building the product. But it's also interesting to see how the— where does the invocation of agents happen? Is it your CLI? Is it a text editor? Is there some kind of web tool or the desktop app? Of course, for us, it's pretty natural being close to where you work. So integrating into that workflow. And I feel like that's where A lot of these smaller companies especially are pretty excited to build in Linear because they're already using Linear themselves.

What agent gets the heaviest usage internally at Linear today?

I think it's been a couple of the coding agents, but those were the first ones to the market.

No, I mean, not even, I mean specifically your team at Linear.

Yeah, like coding agents or, or, well, you know, I, I kind of like mentioning names because like, of course we're, we don't have a horse in the race. We're just the interface for this.

I love, I love horse races and I love having horses in races. Yeah. Pick a horse.

But like, it's changing like every week. So like you said, like there's like a lot of like new, new agents that like came out this week from Google and like, uh, OpenAI and so on. So like, it's kind of like It'll be interesting to see how those play out. And we're looking for working with all of them, of course. But I think beyond— I think currently the focus is a lot on just coding agents. It's natural because there's a lot of value to be created over there. But I think in the next couple of months, we'll start seeing much more non-coding agents. augmenting alongside with the coding agent. So you might have a task where you have a feature flagging agent, coding agent, and I don't know, like, who knows, a marketing agent helping you out to write the changelog blog posts and so on.

Yeah, that makes sense.

Are there any other AI features that you're implementing that feel like windsurfer cursor for project management? Like something that, like, Yeah. Lives in linear alongside, but it's not that asynchronous because in coding we're seeing a lot of like, there's synchronous AI and there's asynchronous AI and these two different patterns. And it feels like the market's bifurcating, but no investors want to admit that because they want to say it's going to be winner take all. But in fact, we're seeing two different paradigms kind of emerge or maybe even three different paradigms emerge.

What are you seeing on the project management Yeah, that's, yeah, I feel like the agents are roughly, especially in our case, are tied to issues or tasks. And that's kind of like the interface for them. Outside that, where of course, like Linear is not only like issue tracking tool, it's like for project management, like organizing like your work at the company level, not only like an individual level.

Yeah.

So, and that's where kind of like have a separate work stream of where building our own AI tooling around that. How can we augment the project managers and the product leaders to do their work better? And that you could imagine looking a little bit more like a Claude or Cursor alongside your linear data. And, but with that, it's going to be interesting to see how we can start introducing the external agents, Or like MCPs as like part of that. That, of course, like the issues is that's like the first step because it's like much more natural.

What's your team's approach to testing new, for example, coding agents, right? It's in many ways like the linear approach from my perspective is, you know, really thoughtful, ideally long-term planning around building beautiful products and taking a calm approach to doing this. And in that way, enabling other people to maybe have more calm, effective product development. But at the same time, testing new tools, they can be super effective, but testing new tools can also be super distracting. We don't do a ton of engineering on TBPN. We actually do a surprising amount kind of like back office stuff to kind of automate production. But I can imagine an environment where you have, you know, call it 50 engineers and on any given day, one of them can send a message into Slack, hey guys, you gotta check this out, it's like amazing, blah, blah, blah. Maybe they just got like a couple of good results and it's actually not worth directing everyone's energy to, but at the same time, you wanna stay at the edge. But do you have a philosophy or kind of an internal Ethos around testing new tools?

Not really. I think mostly comes from people themselves. We're not enforcing certain tools. We're, of course, encouraging a couple of tools where we can maintain security and those kind of things. We're a mature company at this point. So we need to look after our customers' information and a lot of it also lives inside Linear. So we need to look after stuff. But when it comes to like new tools, the team is like looking at the news the same way we are and like trying out stuff. And I think it's a little bit more, so you put out like Linus' way, it's a little bit more calm. And I think like that also shows on the tool adoption and so on. Like you're like excited to try out stuff, but like, you know, you take it with a grain of salt instead of like going on Twitter and like blasting like we've replaced like all of our team like with AI. I mean, like that's one way to do it, but like that's definitely not us.

Yeah.

Nothing against that either, but yeah.

The Klarna method.

Not naming any names.

I said it. I said it. I respect it. It's good marketing. It's good marketing, but it's not for everyone.

Yeah.

I don't know, like that's being like overall like when it comes to developing AI tools. We started when everyone else started, a couple of years back when the first GPTs came out and tried to do stuff and tried to build a chatbot and so on. But I think very early on we realized, well, you get to whatever, 60-70%, but then it falls apart, the experience. And it's not And then it's really like hard to figure out like what's actually the path to get to like the 95% where you want to be.

This is the Apple problem. You, you, Linear and Apple have similar sort of like desires for perfection, right? And, and generative AI is in many ways completely imperfect, right? And unreliable. So that's an interesting, it's an interesting challenge.

Yeah.

But We built a few things. We shipped a few things. We didn't make like maybe like the biggest fuss about it. We're not the AI-powered like issue tracking software raising like gazillion like dollars. But—

Raising a lot from customers though.

Yeah.

Yeah.

And, you know, I mean, like in the end, like they want to get their work done. And like, do they want to like buy hype or do they want to like buy product? Maybe today, like, you want to, like, buy more, like, AI. And that's what we're seeing, like, a lot of, like, demand for AI solutions. And, like, now we're heavily investing in that. Like, and that kind of, like, our— we did a course correction over, like, the last, like, roughly 6 months ago when I think, like, the tools has got so much better.

Yeah.

Like, for me personally, I was, like, on parental leave and, like, doing the deep seek. Like came out and like just trying like the thinking mode was just like a light bulb moment. Like, I think—

Interesting. Yeah.

A little bit background on that. I think just because of like Linear's philosophy is like try to build really like, you know, snappy, like purposeful tools. Like we always like chase the millisecond and like try to get something like really fast. And when it comes to like LLMs, like you have like inherent latency to it. So it's a spell like, how do we bind this like weight into the product that's instant? And I think like now with the new like thinking modes and so on, like that has changed the like user, like what people expect, like that paradigm. And now we can like build towards that.

Totally.

And like people expect it'll take a little bit like more time. Uh, and there are also like more UI patterns to support that, but like you get a lot of value out of it.

Totally. Well, yeah, check out some of Google's launches from earlier this week. What was it? They were doing 3,000 tokens in like half a second with the diffusion models. Yeah.

Yeah.

Very cool.

Um, anyways, this was awesome. Congratulations, uh, on the launch this week and, uh, come back on again soon.

Yeah, hopefully.

Yeah.

Cheers. Better, Jory.

Talk to you soon. We got Zach Weinberg coming into the studio and, and we also have Doug Bernauer from Radiant joining at 2:30 to talk about the nuclear, you know, which I'm very excited about. Welcome to the stream, Zach. How are you doing?

I'm good. You have like—

welcome to the stream.

Full soundboard now.

Full soundboard. We're getting better at this.

Constant iteration. Constant iteration.

What other product updates have there been since I was last here?

Oh, I mean, our Chirons.

Yeah.

Stop asking about— stop asking hard questions about our updates. We're doing fine.

I noticed what sponsor, whoever makes the yellow drink, I assume.

Oh, no.

No, they're not sponsoring us.

To be honest, I did grow up in the town that this company is from, but we have no We have a proper affiliation. Honestly, if anything, we should just wrap these in Ramp yellow.

We should. We should.

Anyways, good to see you.

Yeah, good to see you guys. Thanks for having me.

I mean, we wanted to have you on initially to talk about the Most Favored Nation Drug Pricing EO. It's been a week or two since then. There was kind of like— Time goes green. It felt like years ago. But, but I mean, it felt like Sunday, like, oh, this is going to be Black Monday for biotech. It didn't happen. The biotech stocks did fine. They also— this was coinciding with the pullback on the tariffs broadly. So the market rose overall.

Yeah.

Can you give us how you process the information, how you're thinking about it now? Does this thing matter? Should we even be talking about it? Should we just move on?

Yeah, maybe let's start with like why it's probably just like a misguided idea in the first place, or at least the trade that I think Americans would need to understand that you're making as it relates to drug pricing. And what I think we may have talked about this last time, or I've talked about this with a lot of people, like the idea that America pays a lot for new therapeutics, right? And we do. We do, by the way. Like this idea that we pay materially more, even on a GDP-adjusted basis, than other countries, and in particular other wealthy countries. So you take Europe as probably the best example, where the amount that we spend on new therapies as a percentage of our— let's call it GDP-adjusted price, if you will— is still on the upper bound. So America pays for the innovation for the rest of the world.

But don't we, don't we, don't we get the innovations like 5 to 10 years faster than the rest of the world?

We definitely get them faster. We are usually the first place all these new drugs launch. There is also a set of therapies that we have that you just cannot get anywhere else. Like the, you know, other countries refuse to pay for them. It's, you know, socialized medicine, right? So it's like a single budget.

And then there's also the factor of the rebates where the headline price that you see quoted in America is not what Americans typically pay, even if they don't have insurance. So you might see that some, like, Alzheimer's drug is 10 times or 100 times the headline price in America versus Japan. But realistically, Americans are paying 3 times more, 5 times more, which is still a lot. But it's not the scary number that people often quote.

Personally, I like paying more for drugs because it inspires me to grind harder.

Yeah.

I think many Americans feel the same way. Wait, which drugs are we talking about here? There are a few different—

Caffeine, nicotine, protein, testosterone, mostly.

Protein, yeah, yeah, yeah, yeah. Full just TRT juicing before the show.

Yeah.

No, so like, we do pay more, which is where I was going. On a net basis, like when you add in all the discounts that are given out, it's not as bad as it makes it seem. But obviously, like when you read about it in the headlines, and they're like, oh, this drug's like $65,000 a year, $100,000. That is the list price. And so, you know, the media doesn't understand net pricing versus list pricing. And so the headlines are much more sensational than they actually are in reality. But yes, the delta still does exist.

Yeah.

And we are— we do pay more. Now, part of the reason why we pay more is because if we, if we don't do it, the drugs don't exist.

Yeah.

And I just think that little, like, piece of this is really hard for most people to understand, which is like biotech. There's this really amazing analysis that was done by RA Capital, which is like a giant biotech venture fund.

And yeah, we had one of their principals on the, I think, the Monday after.

Super sharp group, top 5, you know, do mostly publics. But like, this is like a, you know, expert, expert, expert group in therapeutics.

Yeah, we had Tess Cameron.

Yeah, I mean, they have like a few hundred people. Their founder, Peter, is super sharp.

Cool.

We respect them a lot. They actually were investors in one of our companies' next rounds. Anyway, good group. They did a very beautiful analysis of the expected value of a biotech investment at various rounds: seed round, A round, B round, so on and so forth. Like, what is the EV of a dollar that you put in? And I will tell you that at both seed and Series A, the EV is negative.

Mm-hmm.

Negative at our current prices. And the reason for this is, like, drug discovery is the single hardest fucking problem that you will ever encounter in your life, because you are trying to make a drug and using all of these tools that are not actually the human being until the absolute end of it. So you have to take all this insane amount of risk and spend tonnes and tonnes of money, and the data that you have to make your decisions are, like, in a Petri dish or in a mouse or in a monkey or in a dog. And like, yes, that's useful, but it's not a human. And so the amount of companies where— because you don't see this in tech, right? You don't see companies that have raised $300 million, do one product launch, and then go bankrupt.

Yeah.

And like, that happens all the time in biotech. That's actually like the norm is basically, you know, you've spent a few hundred million dollars, you think this thing is possibly going to work. It works in a dog, it works in a monkey, whatever, the drug-like properties seem all really great. And then you'd run a human clinical trial for $150 million, and it doesn't work, and the company's bankrupt, and everybody loses their money. And it's not like $20 million. It's like hundreds of millions. So biotech is an expected value negative investment business, even at current prices. And so what that means is that—

Really quickly, is that just a power law thing where the best biotech venture funds are doing great at seed and Series A, And just like, you know, there's plenty of funds that I could point to in consumer SaaS or enterprise SaaS that are terrible and negative EV, right?

I don't think you could point to the asset class being negative EV.

True, true, true.

Right?

Like, yes, there's always a skew in the results, but here we're talking about the entire asset class is negative EV. And so if you're on the front end of it, great.

But like, you know—

It's rough. You stick it in the middle, you lose money.

In tech, I don't think you get the median fund in tech and you lose money.

No, no, no, no, no.

Yeah, so you're going to see—

Your valuation might be like 1.5x or something. Exactly, exactly.

Yeah, so it's not shifted this way, the whole category. Why is it shifted this way? There's a bunch of reasons. The biggest one, in my opinion, has to do with this concept called like better than the Beatles, which is basically like— it's a very simple idea when it clicks for you. When I try to launch a new drug, the thing that I have to beat in terms of its efficacy, like how good of a drug is it, is the current standard of care, meaning what a patient would get if this drug didn't exist. So it's not placebo. In most cases, it's not like a water, you know, sugar pill, right? It's like the current thing. And so as we get better at treating the current thing, the bar gets higher. So it actually— like, the better we do at drug discovery, it gets harder, not easier.

We should do that with payroll software. Unless you're better than the best payroll software, you shouldn't be allowed to promote your product.

Well, and even more, like, here's the crazy part.

You shouldn't be allowed to launch.

Yeah, you shouldn't be able to launch. Here's the analogy.

You wouldn't be allowed to launch the product.

Okay?

The government would say, no, no, no, no, no. You cannot launch until you are better than the current solution.

Your corporate card isn't better than Ramp, so you can't launch. It's just ridiculous.

Could you imagine that world where you're like, oh, my new, you know, someone would launch like, I don't know.

Yeah, of course.

ChatGPT search engine. And then like the federal government's like, not Google's better.

You can't use—

Google's better.

Yeah, that makes a lot of sense. Yeah, yeah, yeah, yeah.

That is how biotech works.

Wow.

That is how biotech works.

And by the way—

Wait, is that the right way for it to work? Is that contributing? Does it— you have to imagine it contributes to prices being high because it's somewhat anti-competitive, right? If I—

OK.

In the payroll market, right? Like, a payroll platform gets super bloated. Some founders like— and it costs $100 an employee. Some founder comes in, launches an okay version.

Also, there's just less iteration on drugs, I would imagine, than on software, right?

No, no, you can't iterate through it.

There's no learning.

You got to— it either is better or not. Here's the problem. Are you going to take the drug that's 30% worse but 50% cheaper, even though you don't pay for it?

Absolutely not.

Exactly.

Yeah, yeah.

Exactly. Now, if you were on the hook, Or maybe you saw some of the rebates and went into your pocket. Maybe you'd be like, all right, my psoriasis isn't that bad. I'll take the 30% less effective drug, and I'll clip some coupons. But we don't do that because in America, we view healthcare as like it's supposed to be free for everybody.

And so—

I mean, we kind of do it with over-the-counter stuff. If you get like the Mucinex Extra Strength Max, like it might be $2 more than just like generic stuff.

Try telling, try telling a cancer patient that you're gonna get the same— It's very different.

Absolutely.

Like you're just not gonna do it. Yeah. And so, you know, the FDA is kind of like, well, what's the bar is current standard of care. That's the standard we've put in place. Yep. Look, if we wanted to create a system where you could launch slightly worse drugs cheaper, Like, that would be an interesting system. But the problem is the people using the drugs aren't the one paying for the drugs, at least not directly. And so cheaper doesn't win, right? Like, you can't shift because the patient at the end of the day does not want the worst drug. Like, I can't even— there's so many situations where you're just like, absolutely not, especially in serious disease, chronic disease, cancer, all the stuff that really matters.

Yeah.

So going all the way back to pricing, one of these, like, weird, weird issues in biotech is simply like, as the industry gets better, It gets harder, not easier, which is— there's almost like no other industry where that is true.

Yeah. And so it's the opposite of learning curve pricing. It's like the opposite of fabs, the opposite of software, the opposite of the internet.

Yeah.

When you see all these stats of like innovation in biotech has slowed and all, you know, a lot of it is because of this. And they call it better than the Beatles, which is this idea of like, imagine if you wanted to release music and the only way it would work is if you were better than the Beatles, because that's the best. And so, how much music would you really have? And that's the— I like the phrase because it's whatever, catchy, like the Beatles.

Yeah, totally.

Anyway, so—

It does— the one thing I'll say is it has an interesting effect of pushing for true excellence, right?

Yeah, yeah.

I mean, by default.

That certainly doesn't happen in SaaS. There's a lot of people that see a good SaaS product and they're like, I can make an okay version of that and make a couple million dollars a year.

Totally. There's less cynicism and there's less like— we don't have a slop problem in pharma.

Well, there's no— and there's no, like, move fast and break things because you can't tweak your way to the front, right? You've got to build the best drug before you put it into people, right? There is no tweaking. So I say all of this, which is to say, like, yes, drugs are expensive in the United States, but, like, if you wanted cheaper drugs today, you are basically not going to get any in the future. And I know everyone's like, oh, that's not true. But like, I am on the front lines of this every single day. I mean, we are one of now one of the larger biotech venture funds at seed, meaning like we take the most risk. We're in that negative EV category. Uh, risk on.

That's a little different.

Risk on.

Risk on.

Yeah.

Yeah. And so, um, if the price on the other side is not big enough for the risk that you take, It's not that you, like, tone it down, it's that you just don't do it.

Yeah, I mean, just to be very clear, like, you don't need to do this, right? Like, you could walk away from the game, right?

Yeah, like, and by the way, it's not just me, it's our investors, our LPs. Like, if my fund and every other biotech early-stage investor can't make money, our job will cease to exist because our investors won't let us exist. Right? Like, there's this— oh, money will always be there. No, absolutely not. And so, you know, you need a reward on the other side of it. And I think that trade is really hard for people to think about because you're like, well, it's a lot now. And you're like, yeah, it's a lot now. But if it weren't, that means 10 years from now, you're going to have the same drugs available in 10 years as we have today. Your kids are not going to be any better off from a medicine perspective. So the reward does have to be really big. But at the same time, do the Europeans kind of preload off of us? Yes. And so this kind of rough idea of, all right, what they're trying to do is say, we're going to index the US price to a basket of comparable international countries, basically wealthy first world countries, mostly European countries, and that we can't be materially higher than they are on a GDP-adjusted basis. At least that's the idea behind the executive order. Maybe 2 thoughts. One, this will not take US drug prices down. It will not happen. What will happen, and this is not a good thing, is it may force— first of all, this is likely not enforceable. Legally, I don't think the EO works, and that's part of why you didn't see the biotech market react, is every expert—

No one took it seriously.

Yeah, like, it's not—

there's no—

it'll fail in the court 1,000 times. It'll never get implemented. That doesn't mean some future version of this, there isn't some, like, you know, loophole or whatever that maybe the government slowly figures out. But, like, this EO seems as if it's basically never going to happen.

Yeah.

What about— what about the— is biotech being squeezed on both sides in some way right now, given that there's kind of an attack on the fundamental foundational research as well? And so, like, if you take that Basically, that's investment that's effectively the biotech industry gets the benefit of.

Yeah, the negative EV bets are already being subsidized to be closer to zero, but not—

This administration is doing absolutely everything it can to destroy the future therapeutics that you want. Every single decision they've made basically so far has been negative to future medicines existing. Right? Like, you cut biology research, so we don't really understand what drives disease. You cut skilled immigration. Do you know who is like half of biotech? If you go to like any biotech company's website, you go to ours, usually somewhere between 30% and 50% of the people on staff are foreign-born.

Yeah.

Because you know who like doesn't want to do the 17 years of school to become a chemist and like do all the training? Americans. And so, you know, we already have a skilled scientist shortage, and that's even with current immigration. And so, like, kicking these people out of the country, not letting them come here in the first place to train, like, we're just gonna have a massive, you know, skills gap. This isn't like bring manufacturing back. This is like you need to be a PhD in chemistry plus 15 years. Like, these people don't exist. And so, you know, most of our senior team at Curie is foreign-born.

Yeah. And I imagine that, I imagine that, uh, the biotech industry could very quickly absorb like twice the amount of PhDs and just do more research, right? And, and it's not— it wouldn't be like job displacement if that happened.

So the solution—

and like biology and chemistry PhDs and proteins, like specific types of PhDs, you know, do we need like marine science PhDs?

Yeah.

Uh, but you know, so I don't want to put words in your mouth, but are you saying the solution is that we need a million Bryan Johnsons?

We're looking for scientists, not crazy people. So, you know, no, we need we need a million, you know, David Lus at MIT.

And yeah, what about what about that guy in China, He Jiankui? Have you been following this guy?

He is the one like testing stuff on himself.

Maybe.

Yeah, yeah, exactly.

And he posts these like very vague posts where I thought it was an AI. I thought it was a joke. AI like meme account for months. And he keeps posting like.

You know, biotechnology should never be used for to create super soldiers, and it's just like a selfie of him. And it's like, it sounds like you're making a super soldier, man. And it's unclear how much he's in on the joke. But recently, like he he got married, and his wife can't get into the country. Have you been tracking that story at all?

No, because it's like fringe. It's like you know, it's like the New York Post of science.

Yeah, yeah, yeah.

What about?

All right, hold on.

I want to go back.

Yeah, please, please, please.

Because I just like. This is the class— this is this administration being like, I'm angry about something, and then I make a decision and nobody thinks about then what happens. And it's just like over and over again, you're like, these are— these fucking people are so stupid. And I hope they're listening. Like, you are all so stupid. And like, you're just— you're just ruining the thing that has made America excellent in science by killing all these things in, you know, science funding, immigration, blah, blah, blah. It's like, it is idiotic. But even even if you say like we're going to index the U.S. price to international prices, remember that the United States is a giant fucking country. We have 350 million people. We're the wealthiest in the world. Like all 50% of pharma revenue comes from the United States. And then you like Japan is kind of second and Germany. Okay. So now put yourself in the shoes of a pharma company. Right? You're going to index. You're going to index our price to the European price. And let's say the Europeans are like 15% of your revenue. revenue, and the Americans are $50. Are you going to lower your price? Absolutely not. You're just going to raise the European price. Yeah.

Right.

And just to bring it up, because you can't lose the US revenue.

Yep.

So like, you'll never give this revenue up. So the US price will not change. This does not work. All it does is it may, even if it were legal, it may force pharma to bring its European price up. And you know what happens when that happens? Because this is like, and then what? The Europeans will go, okay, we can't pay for it.

We're not going to buy it.

And all it does is it keeps the US price the same and it shrinks pharma.

Mm-hmm.

Like, the net-net is the United States will pay exactly the same that we paid before because pharma is not going to drop price in its largest category by far. It's the only place you can make money in pharma is in the US, and that price is not coming down. If you have to bring the price externally up, it shrinks the revenue in that market, which shrinks pharma, which shrinks biotech. Because if you— if pharma is a smaller you know, dollar value, if the profitability of pharma comes down, you know what they stop doing? Buying biotech companies, right? All this, the same effect, which is like, well, if this is less profit, it's just a different way of making it less profitable, right? It's the same thing of like, if it's less profitable, I can't take as much risk. And if I can't take as much risk, I stop doing risky drug discovery. And therefore the whole industry just kind of like, like this. And that's not a win.

How do companies get valued if they have one drug that's working and maybe it's the best, so it's actually able to be in the market, yet there's a sense that there are very real competitors that might come in with a drug that is substantially better? How is a pharma company that's exploring M&A going to value that? Is it still the same?

This is what they do all day. What you just described is exactly what these people are spending teams and teams of people on, which is like, okay, what is the value of the current drug that we've got? Which is usually, if it's at the place where it's approved, you're looking at, you know, what are peak sales and how long am I going to be able— how long is my patent, right? What do we expect generic competition to look like? And then you're looking at the pipeline of competitors, and you're looking at the data that they shared. And sometimes there's some data, and sometimes there isn't. And then you're trying to predict the future, which is like, okay, just because, you know, Company X is working on a competitor doesn't mean it's gonna work.

Mm-hmm.

So do we think it's gonna work? Why do we think it's gonna work? If it does work, what are the— so you do like scenario planning, like, okay, you know, 10% chance this beats us, 50% chance it doesn't, like, should we be concerned? And all of this math goes into the spreadsheet of like, what do we think this drug is worth? And what's the risk appetite? So like, this is day-to-day, you know, biotech pharma commercial analysis. There are very, very smart people who do this. You know, this is what the public hedge funds do, what the RA guys will do, you know, and it's deep science. But all of it is just like, at least the drug pricing stuff is just, it's a trade that is hard for people to understand, but it's kind of like, if you don't put a reward on a very risky thing, the risky thing doesn't happen, and you just don't feel it until 10 years. You won't even really know because it's the drug that never got started in the first place. And then eventually what you're doing is you're outsourcing all this to China because the Chinese will pick it up and do— we can have a longer conversation about China. So all of it is just kind of like stupid. The other thing I would say, I know I had to jump, but like, This is my defence of medicine and therapeutics, if you will, as a great investment. They go generic.

Yeah.

Like 9 to 12 years, let's say roughly, these are generic, which means they are basically free for you in 10 years, and your kids, and your grandkids, and your future kids. It is an unbelievable investment. You pay a lot upfront, you get a lot of innovation, a lot of people taking risk, You have this, like, window in time, which is like, yeah, you know, you got to eat it. You're going to pay a bunch for it. It's not going to feel great. And then everybody gets it free. There's no other industry in the world where that happens. And even within healthcare, you know who doesn't go generic? Doctors, hospitals, surgeries. Like, why is there so much focus on the therapeutic, which is also only about 10% of medical spending is drugs, which then eventually goes generic? versus the 90% of it, which is basically physicians. And those physicians, they're not—

well, it's because of the margins, right? What strikes you as something that, like, the pill only costs a cent to make?

And so—

exactly.

Yeah.

Just emotionally you think about high margin things. What's wasteful?

What's something positive that could come from the EO? We, we had an infamous healthcare exec, actually. Actually, no, we had an infamous healthcare exec Message us while we're live. Said ask him if he reads that the EO is maybe trying to solve the consumer pricing problem gross to net rather than actually making pricing comparable in the end, given that there was a specific call out for consumer D to C pricing, and which might have been why consumer D like healthcare is about the new drugs that are really expensive, not like consumer D to C pricing.

of like, you know, whatever, consumer medicine. Like, I'm talking about real healthcare. Very sick chronic disease people with neurological conditions, with, with cancer, with heart disease. Like the serious stuff, which is what we should care about.

I just saw a company that they'll give me one pill that has erectile dysfunction medicine and hair loss medicine in one pill. Is that not real medicine?

What's going on?

Those are generic meds.

Sounds like amazing.

It's amazing.

And you know why they're so cheap? Yeah, because they're generic. Because 15, 20 years ago we invented this shit. We, you know, Pfizer made like a crap ton of money selling Viagra.

Yeah, that's right, everybody.

And now you get to get your 6-in-1 dick pill for $2. And like, that's a pretty cool deal, right? Like, it's cheap and all this. Like, sure, there's some like gross to net, whatever. That's not what healthcare is. That's not— I'm sorry, like, hair loss is not Interesting.

What about CRISPR on demand? There was this infant child that was saved with a custom gene therapy. It seemed like a very inspiring story. There was an inspiring video all about it. It seems like an amazing testament to something we've been hearing about for a long time, which is CRISPR. Maybe a decade we've been talking about this. Is that an opportunity for new companies? Is there already a company that's ripping on the back of this, or is that just like like an outgrowth of what we'd expect with the technology given the maturity?

I believe the company that did this was Beam Therapeutics. Is that them who did it?

Yeah.

Yeah, it's cool. I mean, this is a perfect example, right? Which is like, I think it's Beam. I can't remember offhand which one it is. That company that successfully developed this therapeutic, is trading for less than money raised.

Whoa.

Wow.

Okay, breakthrough.

Moment of silence.

It's terrible.

Right? And why? Well, because these gene editing technologies where you're going after essentially disease that is very clearly defined by some mutation in your DNA, and that's a small subset of total disease. It's very, very rare conditions that this applies to. So the market, the way I think about it, is the patient market for this technology is very small. These are horrible diseases that in theory can be treated through gene editing. There's not that many of them, but you can do some really amazing things if you can make these edits, which is the first time this has ever happened. But if you add up the patient population of all of these conditions where you could possibly do this, it's not that many. I don't know the math offhand. I bet you it's probably like tens of thousands at most. OK. And so, Plus, the variable cost of manufacturing this stuff on a per-patient basis can be hundreds of thousands of dollars.

Are we going to get some blockbuster gene editing for hair loss, and then we're back in business?

No, because hair loss is not— there's no one base edit to fix hair loss.

Yet.

Yet. I don't like this techno-pessimist on my stream, Zak.

Well, one of the things you learn as you go into science is that the DNA is not actually the whole It's not even close to the whole story. And so, like, it's not even—

You wouldn't say, is vibes a part of it?

It's actually astrology.

It matters.

You have to take into account the DNA, but also the astrological sign.

Uh, infamous astrologists.

Vibes are kind of like it in a way, that your behavior as you're alive does affect your—

Epigenetics. The expression of the DNA.

Your epigenetics matter, right? Like, you sit in, uh... smoke all day, like, you're gonna have some problems. Anyway, I like this as an example, because this company that just made this, like, unbelievable breakthrough— this has never been done before in humans, they're curing diseases— is now trading for basically less than cash raised. I gotta go find out.

What's the name again?

I swear it's—

So, so there's— I just got an answer. So this was a bespoke CRISPR base editing drug. It was built and tested by physician scientists at the Children's Hospital of Philadelphia and Penn Medicine with translational help from Innovative Genomics Institute at UC Berkeley. Reagents and GMP-grade components were donated by several suppliers, including Accutas Therapeutics and Integrated DNA Technologies and Aldeveran, both Danaher companies, for guide RNA.

Yes, on that one, there was another—

There's another story?

Yes, there was another story, and I have to find it.

Well, we will have to— we have to jump. But, but, but, but why— we'd love to have you back and kind of dig into some of these other biotech companies and take us through like the wins and losses. I think it'd be very interesting to see.

By the way, imagine, just imagine if that becomes a drug and we go, oh, we can only pay $20,000 for it. Do you know what happens to that drug?

It sits on the shelf.

It sits on the shelf. No one ever does it. No one ever makes it. And there's your drug pricing in, in reality, which is like, well, it's got to be a reward.

So we're pro higher drug prices, I guess. You build us on that. We want that. We want the highest prices possible is what I'm hearing. You want to find— you'll get a lot of shit.

You put real high prices, like people will come and take risks. You know, I'm sure there's some balance.

We got to have you and Shkreli together. We need like gold.

Here's my favorite stat. Yeah, my favorite stat. The— I'll pull these for you. So I don't want to sound like an asshole, just like spitting numbers that aren't true. I believe on a per American basis, like you take our drug spend and you divide it essentially over like, you know, Americans we spend drugs on, it's something like $1,000 a year or so per person, if you will. We spend more on cosmetics than we do on medicine. Wow. More on cosmetics.

That's it for America. We're looking good.

What about fast food?

What about— we might be dropping dead at 45, but we're going to look good doing it. Thanks so much for stopping by. This is fantastic.

Always a pleasure.

Cheers.

Next up, we have Lee Marie Braswell from Kleiner Perkins coming in, former colleague of mine at Founders Fund briefly. Excited to talk to her about artificial intelligence, AI agents, all the news of the day, and we'll bring her in. And we got some, we got some good chyrons for her coming up. We'll see if we can get them up on the stream. What do we, what are we talking for her? The term she tyrant herself. Oh, what's up, Coogan?

How's it going?

It's good. What's new with you? I'd love to get your initial take on AI week. We got Microsoft Build, Google I/O, OpenAI I/O. We got Claude 4 from Anthropic. It's been a massive week. What has stuck out to you as, like, the most interesting, the most underrated, the most worth digging into? Uh, of the news of the week?

Well, I guess just to start off, and it's so good to see you again. It's been, it's been a while.

Yeah, it's been too long.

So yeah, thanks for having me on the show. Um, yeah, it's— no, there's never a dull moment really, you know. Um, yeah, you know, you know, I feel like every day there's, there's something really, you know, significant that you need to be paying attention to if you're going to try to make money investing in AI companies.

Yeah.

And so, yeah, I mean, I think the big thing that's actually— there's so much this week. I mean, right, you know, starting with some of the stuff you said The best time to be a technology podcaster.

Yeah. Investors, close second, but podcaster's really where you wanna be. That's where the action is. 'Cause every day there's new news anyway.

Yeah.

What, what, what is sticking out to you?

Hey, Jordy.

Hey.

Yeah.

So, so there's the, I mean, the I/O acquisition in particular, that news. Yeah. What an incredible video. What an incredible team. I mean, just really showcasing OpenAI's ambition to really, you know, get into, get into a lot of stuff. And I mean, obviously there's a lot of speculation about what the device will look like. I was actually looking this up.

My favorite—

sorry, sorry to interrupt. My favorite part was, uh, John and I are, I guess, ex-hall monitors. We're in the community notes program. And so somebody was trying to community note the OpenAI launch video, and the suggested community note was, this video uses AI. These 2 scenes aren't real. If you look at this section, it's like you're trying to gotcha an AI company for using AI in a marketing video. Like, Like, what is this? That's very silly.

What do you expect?

You know?

Yeah.

That's kind of the point.

Yeah.

Yeah. Um, so I mean, yeah, I mean, super excited about what potentially that could, that could imply for just, you know, OpenAI's ambitions, especially as it relates to consumer, consumer hardware. I was looking it up on, on O3, but O3 kept then kind of giving me some different answers, but it might be, and to be fair, I don't, you know, kind of know the current state of things inside of I/O, um, Johnny Ive's company. It might be one of the largest, if not the largest sort of pre-product acquisition of all time. So, you know, so I mean, $6.5 billion is a lot of money.

Yeah, we've been noodling on a couple of points.

It's a couple of points for a key exec.

Exactly. It's 2% of the company, which when you think about bringing in an executive at that level, that like comp for that industry legend, it's not that crazy to get to that number. And then today in The Wall Street Journal, Sam Altman is quoted saying that if they can nail it and get a major consumer device, that's a trillion-dollar opportunity. And that sounds crazy, but you look at Apple's market cap, you look at Android, Samsung, like, yeah, there probably is $1 trillion in market cap.

Well, there was also the tinfoil hats saying, like, oh, he's trying to dilute the profit. Oh, yeah, that was funny. It's like, you know that they are issuing billions of dollars of stock to employees all the time.

Yeah, that's happening all the time.

Right? This is not some crazy conspiracy.

Who knows?

I do want to get your take on the actual device. We've seen some pre-renders, some AI images around, like, like a pendant with a camera on it. The Her model, maybe it's an earpiece. I imagine you get pitched a lot of AI devices. We've seen the Rabbit, the Humane, the Friend. Are there any other ideas that you've seen that could potentially be just AI devices, even not from OpenAI, but just in general? Because Apple's got it pretty well covered. They got your ears, they got your eyes with the Vision Pro, they got your phone, the watch, the iPad, the laptop, the desktop. Like Apple's— there's not a lot of white space in the Apple catalog, but it'll be interesting to see if somebody can come up with something that's new. Have you seen anything that's interesting?

Oh man, I really wish I could tell you about it. But yeah, we actually have a company in stealth. I can't say much, but there's certainly different, you know, models.

Have them come on the show when they're ready.

Yeah, I'll be super excited too.

But cool.

People are being really creative. And then also, I mean, just generally, and I'm sure you're seeing this too, just given like the pace of how much is happening and then also the competitive nature of these markets. Like, it's clear that there's this big prize, maybe bigger than ever before.

Yep.

And so if you've got a really good idea, like, and if you don't have trouble raising funding, getting customers or hiring people, like, you know, why, why talk about it too soon? So yeah, I'll be excited to share more on that.

There's also—

I feel like people have just been generally willing to fund hardware, but also kind of categorically bearish, right? People are just like, oh, like Hardware is really hard. Like, I'm gonna make this bet, but like, it's really hard.

Hardware is hard. It used to be about supply chain. Yeah, used to be about all the things that can go wrong. Then also look at working capital.

We're at a point where like Oura and Whoop, yeah, like big businesses that I, you know, I don't know. Yes, like ultra specifics on either, but I bet that Oura will be a really big company in 10 years.

From my perspective, it's almost harder. It's not— it is hard to make the device and manufacture it and deal with the fact that that 90% of your revenue comes in Christmas. But, um, like, the real hard part is actually changing consumer behavior and getting someone to take off their Apple Watch or add a Whoop band to the other wrist, which is, I think, the predominant pattern for most Whoop users. But, um, what, what, what are you looking for in hardware startups that you're looking at? What are the pitfalls that you want to see founding teams overcome before potentially backing Yeah, so I'll say I don't have a massive background in hardware.

I mean, I will say I was at Scale, you know, I was relatively early there for, you know, and was an engineer there for 4 years and then a PM. And we worked with a lot of hardware companies there.

Sure.

So I mean, the main customer of Scale back in the very early days was self-driving car companies and robotics companies. And so I have seen just through working with them as customers, you know, some potential pitfalls. And I mean, you know, the quip is that hardware is hard.

Yeah.

Um, you know, that you've got all of the challenges of building a company, and then you've also gotta just manage supply chains, and you have to be a lot more careful about, you know, the economics. You know, software is usually relatively high margin, or it's easier to make it high margin. Hardware, obviously much harder when you've gotta figure out where all these materials are coming from and ramping up. So even if you have demand, like ramping up in a sort of scalable way, and then also implementation, um, can generally just, just take a really long time.

And it distributes at the speed of the internet. Like, you can go viral and get 100 million people on a website in a day. You just can't ship 100 million things anywhere in any reasonable amount of time. It just takes time.

Like, maybe one day. But yeah, it's like, interesting to remember, like, Waymo was founded in 2009.

Yeah.

Right.

So like, just as that, like, it took overnight success, 20 years to now become this overnight success. But yeah.

You mentioned robotics. I'm interested in the pools of training data that are out there. We've been joking about Scale AI. Are they going to put everyone in motion capture suits eventually to get to the humanoid datasets? There's also a lot of work being done in simulated environments. Is there a data wall that we're going to run into with humanoid robotics? How are you thinking about the data challenges in robotics generally, whether that's in the humanoid side or elsewhere? Because it feels like the humanoid narrative is taking hold. People are funding companies. It's getting big. But if it's a 16-year journey like it was with Waymo, we could be, you know, in for, in for a long one here.

Definitely. Definitely. It's been interesting. I mean, like, I do think there are a lot of really good arguments for why we'll see robotics, like, progress accelerate. And that's really, you know, obviously the data is more challenging to get. You know, it's not like you can just scrape the internet like we did with a lot of these, these LLMs. And the data is kind of like there and ready for the taking for at least like, like some of the early transformer-based models, um, though with an asterisk, like as, as we're now moving into agents, I actually think you have to be more intentional about creating different types of data. Um, but then now with robotics too, like, you know, you've got to figure out ways to get real-world data, um, whether that's, you know, internally or using somebody like a Scale, um, or, you know, there's a lot of really exciting work going on in world modeling and simulation. Um, and so, you know, I think hopefully a combination of being really intentional about the data, both on the sort of like human collection side, and then also some of this work that we're seeing in simulation and world models, um, will hopefully mean that, you know, we don't all hit this data wall and we'll be able to sort of scale these systems more effectively. However, I mean, with robotics, it's always a little, a little bit challenging to tell what that exact timeline is.

Yeah, interesting. Um, we were talking earlier about, uh, the agentic, the coding market, the AI coding market. I was kind of breaking it down to you in Is it 3 markets? Is it 2 markets? Is it synchronous work, asynchronous work? Is there a consumer, prosumer, bottom-up enterprise, top-down enterprise sales motion? How are you thinking about just AI coding generally as a market, as the businesses evolve? Just give me kind of where you're at, and then we can kind of tug on that thread in a bunch of different ways.

For sure. My favorite topic of conversation, or definitely one of my favorites, is AI code gen, near and dear to my heart. But, um, yeah, as a disclaimer, so I'm on the board of this company, Windsurf. Um, so agentic IDE, AI-powered developer tooling, uh, platform.

Yep.

Yeah, it's been, it has been just utterly sort of shocking to me. Like, you know, when you invest in a company, you expect like, okay, you know, think hopefully things will go well. Like hopefully the market will be there. And I just don't think anybody, um, I don't think anybody really saw this coming.

Yeah.

Just in terms of like how widespread tools like Windsurf would become.

Yeah.

And so right now, you know, you're certainly seeing like there's this sort of segmentation specialization. You know, you have tools like Windsurf and Cursor that are, you know, prosumer. So you've got people even with basically no coding or definitely no coding experience that are able to get up and running very quickly with these tools and really sort of like talk to it. And it acts like this sort of programmer that will, you know, like respond to what you want to do. Maybe it comes back, maybe it comes back with an error, but it can maybe autonomously fix that error once you kind of give it some more guidance. And, you know, it's just been incredible seeing, like, you know, even, even though I talk about Windsurf all the time, my father-in-law, who I never mentioned it to, not a programmer, just like once he was on a— we were just talking, all talking. He's like, That's great. You gotta go, you're a VC, you gotta go check out this company Windsurf. I'm like using it. To like, you know, help me out at work and create apps. And I'm just like, wow, this is incredible how widespread he's like, you know, outside of Silicon Valley, all of that. So—

So for those types of tools, I mean, you don't have to speak about Windsurf specifically, but just how much of it is just a ton of people on small consumer plans versus bottom-up enterprise adoption that gets rolled into a much larger consumption-based plan or even like a seats-based plan? Like, How is the market for AI tooling in the enterprise evolving in terms of pricing? Because we've seen Salesforce is talking about, we want to price things not based on seats, but based on resolutions of customer service tickets. You could imagine charging someone for lines of code that get approved in pull requests or seat-based or usage-based or just pure inference-based. So how is that side of the market just evolving broadly?

Yeah, I mean, so what we're seeing is, you know, there's certainly the prosumer segment for these tools, but it very quickly goes up, you know, bottoms up into the enterprise. And in particular with Windsurf, I mean, from day one, we've been quite focused on the enterprise segment. And so it's, you know, we're— we both have a large enterprise sales team and then these tailwinds from now all these prosumers and then, you know, sort of like professional developers that pick it up on their own and bring it in. Into their company. I think pricing, it's always interesting and something that we constantly think about. It's a very competitive market. So, I mean, you know, you also have to kind of pay attention to what other people are doing. I mean, per seat, easy to understand. But then, you know, obviously a lot of these models cost, you know, cost money to run. And so you've got to figure out some sort of either credits or usage system. I don't think, you know, in coding we're yet to the point where it's, you know, let's price based on outcome like, oh, well, if we get this done, Then, then you pay like maybe, you know, I've seen sometimes in like customer support and things like that. But yeah, certainly having like a usage element I think is pretty, pretty, pretty cool.

Yeah.

What's your reaction when an entrepreneur pitches you and they're like, well, we're, we're building agents to go after this labor, this like end labor market and the TAM is, you know, $1 trillion because they're just adding up like global payroll for like that type of work. Like, what's your reaction to that? Is that the wrong way to think about market sizing if ultimately these are software products that can be delivered very inexpensively, which will ultimately create competition and drive maybe pricing down for that end service?

Yeah, I mean, definitely, definitely some good points. I mean, generally, generally I'm pretty optimistic. I think now just like kind of living through the cogent market where, you know, just to use this as an anecdote, you know, GitHub Copilot came out, my first kind of pessimistic reaction was just like, oh, well, this is like so useful already and GitHub's got all these advantages. Okay, this like market's done. And they will be like, okay, every developer like uses it and then it's kind of over. And, and it just, the opposite of this happened. Like—

Yeah.

It turned out that there is a lot of white space in the market for teams to innovate and to create really great product experiences, um, whether it's a startup, whether it's a foundation model company. And then also just like, I think the market blew my mind.

What was the secret?

Yeah.

What was the secret to either the challengers to GitHub Copilot? I haven't really used them. Is it more driven by flexibility around which model you're plugging into and GitHub Copilot kind of locking you into their model and not moving quickly enough? Or is it something more on the user experience side?

So I forgot the exact date GitHub Copilot started. I think OpenAI only, given the sort of relationship. But it relatively quickly moved to an option. So it's probably—

So you can put in Claude 3.7 Sonnet, which everyone loves.

Yes. And I think actually recently, um, you know, I, I think I was reading this this morning, but, you know, um, you know, GitHub announced like, okay, for these particular features, we're gonna go with Anthropic only, like particular backend features. So it's clear, like, you know, they're, they're— GitHub is not locked into one model provider.

Yeah.

I think, you know, what Cursor, Windsurf, and others have done is just create, you know, different product experiences.

Mm-hmm.

Um, and obviously GetUpGoBuy, it's still doing very well. But I think what this all has told me, and kind of back to your original question, was these, these markets are actually much bigger than we give them credit for.

Mm-hmm.

Uh, and so when I'm kind of sort of being pitched maybe a ridiculous TAM, sure, it's probably good to like verify that and really drill in on that. But I mean, we are in the world where now software can do work.

Mm-hmm.

And so you do have to kind of, you know, you don't just get the sort of TAM being, okay, it's the, you know, incumbent software spend. I think you have to also realize once the product gets that much better, people will want to buy more software and then also think about it as a work replacement. So you kind of get all these kind of bonus markets that, you know, you know, end up being just like this huge thing.

How do you, how do you, how do you process the tension between model providers kind of figuring out if they're wanting to end the own consumer or be a platform. I mean, the most obvious example was Windsurf didn't get immediate access to Anthropic's new models, which seems, you know, I'm sure you can't comment on that specifically, or maybe, maybe you want to come in and put them in the hot seat. But, but yeah, it just feels like lawyers are hard to find. It feels like— just do it. It feels like a Very real tension that's gonna have to get resolved quickly because these are all big companies now, or at least the main players are big companies. There's billions of dollars of revenue on the line, and everybody's in a you know constant race to be at the edge.

You're right.

I probably probably shouldn't say too much. I mean, what I what I what I what I will say, yeah, it's something that I think is. Going to have to be, you know, addressed in the next year or two. Like, I mean, I think it's just very clear that cogent in particular is this, is this market that everybody kind of wants to get into.

Yeah.

You know, I do ultimately think that, you know, I'd be shocked if in a year or two we don't see cogent products that are both, you know, synchronous. So like assistant, you know, I can talk to it and from the same interface I can delegate task. I just think that that is something that a lot of people are building towards. It's like there isn't a great experience today that kind of has both.

Yeah.

Um, at least, you know, sort of a generalized both. But I mean, ultimately, like, all these companies are, I think, gonna in the, in the sort of even medium term come up against each other. And ultimately what you want is sort of this distribution. And I think, you know, all these companies too are realizing you also want the model, um, and you wanna be able to, you know, give yourself really favorable, favorable economics. So yeah, it's going to be a super exciting, even, you know, probably, probably 6 to 12 months, I imagine.

So legal, the sort of legal AI space has been heating up, kind of a, you know, interesting comp. In many ways, it felt like Cursor had like a ton of mindshare and then Windsurf just kind of exploded. People realized how quickly it was growing. At least that was my perception. And then, uh, Harvey similarly has been more in the sort of, uh, cursor bucket, and that like tons of attention, bunch of rounds back to back. And then Lagora, uh, came out of— feels like it came out of nowhere, and they raised a big Series B this week. Is there— are you— do you have a, a kind of prediction or a take on what the next category to see these sort of battles play out?

I'm sure you guys already have some She's already on the board of 4 companies that are going to dominate it.

The next 4 categories.

Actually, I had to jump to the board meeting in exactly what you just said.

Yeah. Yeah.

Um, you know, I'm, I'm very lucky in that, you know, I think, I mean, even before I joined, so I've only been at Kleiner Perkins for 2 years. And even before that, a lot of my partners made really great app investments. So for example, my partner Moon incubated Glean, um, which is now, you know, kind of the, enterprise knowledge discovery platform in this kind of new, new AI era. So certainly, like, we've got a lot of apps in the portfolio. I mean, Harvey, we, you know, did their Series B. Ambience, which is a medical scribe, also in the news recently. We did their seed and Series B. So, and then, you know, we have some, some investments in sort of sales AI as well. I work with this company Nooks, which has started with a power dialer that people really like and is now expanding into other, other parts of assisting salespeople with AI. I'd say like those, you know, those categories plus maybe add customer support, which we don't yet have kind of a generalized play in. Those are kind of like the battleground spaces. These are where it's going down right now. Like it's clear the models work for the use cases. It's clear there's a giant prize at the end. So you've got, you know, inevitably a lot of companies competing for it in general, especially with software. You know, I think it's basically impossible to be the only company in your category.

Can you fund a company that will just pick up the phone when I get like a robo AI call? like trying to do some social engineering hack or whatever and just pick up the phone and waste their time really inexpensively. That's— I feel like that's what I do.

There's definitely some cybersecurity companies out there.

Yeah, I think I've— I think I've actually been pitched one. I would have to find the name, but yeah.

Well, what do you think about competition from the hyperscalers? Obviously, Microsoft Build and Google I/O happened this week, and there's one narrative that's like, oh, so many startups are now just bullet points in a Google I/O keynote. But Ben Thompson wrote shortly after Google I/O that Google only cares about search, and they only win when it's directly impactful to search. And so you might, as a startup, not need to worry if you're doing something that's more in the labs or experimentation phase for Google, and Google is more just almost doing it as a demo of their platform, and then they really would be fine with another company just buying a bunch of TPUs on GCP and building a real company on top of their innovation. But how are you thinking about startups competing in these new AI markets with the legacy incumbents?

Yeah, it's a really good question. It's something that I think about a lot. Just given, like, obviously, you know, somebody like Google has giant advantages, distribution, money. I mean, Google literally created the, you know, first Transformers paper. Um, so I mean, certainly, certainly it's something that whenever you're investing in, in an app company in particular, you know, you need to, I think, at least think very deeply about what's, what's the roadmap of, of all these companies— OpenAI, Anthropic, etc. Um, I mean, certainly, certainly seems like sort of areas in search and sort of like social and, and prosumer that, you know, seem like kind of the most under the microscope with these companies. But, you know, it wouldn't shock me if they tried to compete in some of the other app categories we've talked about too. So, yeah, in general though, startups, I like to bet on startups.

Yeah, of course.

Focus is important. And then, you know, I think if you move fast, if you're very strategic, there are a lot of good sort of like wedges you can sort of start with and then expand from there.

What about M&A markets in particular? I mean, my reaction to the Windsurf acquisition was and it's gonna be kind of hard for you to answer this, but was basically that like, whoa, like maybe that whole meme of like, oh, don't build a ChatGPT wrapper or whatever, maybe that was overblown. Maybe that there's gonna be a lot of app layer companies that get scooped up. Obviously, OpenAI is moving very quickly, so they're kind of early to this, but you could imagine every hyperscaler needing application layer AI companies to slot in. especially if they've had distribution, and they've actually scaled revenues, and they have a really great team. And it feels like, unlike in the previous era, like 2010-ish, the hyperscalers are more sclerotic than ever. It's been 15 extra years. They're less founder mode. And so I don't know what your read is on the M&A markets broadly, but how are you thinking about the hyperscalers' approach to staying on the leading edge of these AI application layer companies?

Yeah.

I mean, I think it's important to remember, and I have to remind myself, that ChatGPT is less than 3 years old, I think. So it's like, this is happening so fast. And so when you think about like, I'm a hyperscaler and I see a market that like makes sense for me strategically, you know, is it really faster for me to go and try to build it internally?

Mm-hmm.

Or is it faster for me to find a really great startup, perhaps with expertise that I don't have?

Mm-hmm.

And maybe, you know, some other advantage, whether it's the product or the distribution or, or something else. And then, you know, explore, explore partnership conversations with them. And so, I mean, you know, the one, one, you know, acquisition I, I can talk about is I, a company that I worked with at Founders Fund and, and still on the board of Neon.

Oh yeah.

Is partnering with Databricks.

Oh yeah.

Cool.

And it makes sense because it's like, you know, you've got this team of database infrastructure experts and then you've got this company who clearly wants, you know, their customers to be able to realize the full potential of AI agents. And so you do need, you know, a database and memory for those agents. And so, you know, it certainly now, you know, now I'm trying to think in my mind like, oh well, what are the other categories that hyperscalers might be looking in and what makes the most sense for each one?

I mean, the big one to me that I'm trying to figure out is just video generation, which we had— I wouldn't call it a Ghibli moment this week, but VO3 was close. Took a little bit. It just takes a lot more work and it's harder to get a consistent quality output.

But there isn't a single meme where everyone— like, the Ghibli thing was like, just take your profile picture, take whatever's in your camera roll, 2 words, boom, one shot, and you have something cool. With VO3, you have to be more creative with the prompts.

Well, yeah, the interesting thing there is 'Cause I can, it's so easy to imagine in the future where consumers are using video generation tools daily.

Yeah, totally.

Just for fun.

Oh, totally.

Yeah, there's some like consumers just like making memes on the internet. Then there's like kind of prosumer SMB, I'm gonna make like an advertisement.

Yep.

And then there's the like Hollywood studio that's like, I'm gonna make a movie, or independent filmmaker. But where companies kind of fit into that, I can see a world in which hyperscalers are kind of dominating, Meta, for example, figures out a way to get really good at video generation because it fits into the Meta ecosystem or YouTube with VO3. And I think that from my point of view, I can see some of these more independent foundation labs that are focused on video having to really move upmarket to actually dominate because that feels like an area that Google's not gonna necessarily build the thing that creates the next blockbuster video. Yeah, but if you're competing for the prosumer SMB, like, feels like a really tough place to compete purely from a cost standpoint and with YouTube or Google's sort of YouTube data advantage.

Yeah.

Yeah.

I don't know. Any reactions to VO3 this week?

Oh, I mean, super cool. And we were playing around with it. My husband's a founder and he was like trying to make this new video. for something that they're developing internally and oh my God, just insane. Yeah. So it's, yeah, really cool. And I mean, I, I, I kind of agree with some of the points that have been made, but then on the flip side, I will say like, especially in video, there's so many really great models and they excel at a variety of different things.

Yeah.

And so if you're like kind of a third, you know, a startup that is not connected to, I mean, Google obviously is developing their own models. So if you're not connected to any one of the particular models and you can offer like kind of a best-in-class, like, okay, you can pick from, you know, many of them, maybe that's an opportunity, or if you're sort of like very, very specialized. So yeah, I mean, generally still optimistic, just kind of given at this point there's not, in my opinion, a ton of platform risk. You've got so many of the hyperscalers and labs like that are, you know, both closed and open source offering these types of models.

Yeah, very cool. Well, thank you so much for stopping by. We'd love to have you back. This is fantastic.

Yeah, this is great.

Thank you.

This was super fun.

All right, bye.

See you later.

Really quickly, let me tell you about—

She's been on an absolute tear. Barely got to Neon. Another $1 billion acquisition.

Fantastic. But really quickly, let me tell you about Figma. Think bigger, build faster. Figma helps design and development teams build great products together. Get started for free at figma.com. Redesign how you design. Explore your ideas freely and iterate quickly. Let's also tell you about Vanta. Automate compliance, manage risk, prove trust continuously. Vanta's trust management platform takes the manual work out of your security and compliance process and replaces it with continuous automation, whether you're pursuing your first framework or managing a complex program. Go to vanta.com to get started.

Thank you to Vanta.

Thank you to Vanta. Anyway, we have our next guest coming in, Stephen from Lambda Labs. We've had Lambda School on. We're waiting for Stephen.

Should we hit some timeline?

Yeah, let's hit some timeline. What's— did you see Yohei? Pocket is shutting down. And so this—

We need a soundboard that says moment of silence.

Yeah.

Vibe coded a quick, free, open source prototype with some AI features called KeepYard. It still has issues, but I challenged myself to push this in one night. I thought this was very cool. I've been joking about we need someone to vibe code a new Google Reader since that was such a popular product. It should just be out there. And it's already starting to happen with replacements for Pocket. And it seems like Steven's in the studio, so let's bring him in and talk about Lambda. How you doing? Welcome to the stream.

Hey guys, how you doing?

Welcome.

Doing great.

How are you?

Thanks for having me on.

It's good to see you.

Looking fantastic, by the way.

Thank you for wearing a suit.

Thank you. I guess when in Rome, but that said, this is how you know everyone in Silicon Valley should dress.

I agree. I agree.

Are you are you in Silicon Valley right now? Can you give us a little drinking a monster introduction?

Drinking a monster. Let's go.

So on brand. It's amazing.

So so I'm actually in my hometown of of Charlotte, Vermont. That's where I grew up.

Yeah.

And it's where I live.

Great.

And just got back from— landed this morning from SF. Cool.

Nice. How would you describe the business these days? I know that—

Well, first we gotta talk about the AI scene in Vermont.

Oh yeah.

Picking up?

Big? Yeah, I'd say that there's like 1 or 2 companies. There's a lot of, I'd say, Independent-minded founders out here. But generally speaking, I'd say it's more of a farming— farming—

Yeah, my little brother who's not in tech went to college in Vermont and just stayed. I've tried to get him to come back forever. He's committed to the great state of Vermont.

But—

Well, let's introduce him to Masayoshi Son, and maybe he gets started with building an AI company.

It could happen. It's not off the table.

So, yeah, brief introduction. How would you introduce the company? How are you describing the different offerings and kind of challenges right now?

Yeah, so Lambda is an AI cloud. It's essentially a really massive GPU cluster that all kinds of startups and hyperscalers use. Yeah. And we've both sort of taken, invested a ton of work. It's, it's basically around a billion dollars worth of GPUs that we've deployed.

Wow.

Um, and we've invested, you know, at this point, probably around $100 million into the virtualization software that allows us to essentially take that massive cluster of GPUs. So you can imagine taking a cluster, let's say, 16,000 GPUs, and you can sort of dynamically partition it and hand out little slices to people.

Yeah.

You know, on a, as little as a 15-minute basis. And it's quite different from, let's say, a bare metal cloud where you need to sign a 3-year contract. We've basically implemented all this virtualization software that lets you hotel on and off.

Sure.

While still maintaining high-speed InfiniBand internet.

You did the meme. Another billion dollars for Jensen.

Another billion dollars for Jensen.

Is it actually primarily NVIDIA chips or are there other GPU providers that are competitive at this point? I've been following George Hotz's journey with AMD. Is anything competitive with NVIDIA right now from your perspective?

I don't think that there's anything that's competitive with Nvidia right now.

Yeah.

Um, what you just see in the customer demand is, you know, total and utter Nvidia supremacy.

Yeah.

And I think that this is going to continue on, uh, for some time. The, the test I always like to say is you've got to get a customer, they've got to be able to download a Kind of any arbitrary model off of Hugging Face, run that model, train the model, fine-tune the model, and then they have to buy from you and then buy again, right? So that's, that's, that's the test, I think, for any chip manufacturer. And it's really hard to get a stable software stack.

Do you like the term NeoCloud? Is that appropriate?

You know, I think it's, I think it's fine. I don't, I don't really have any opinion on, on it. I, we kind of look at ourselves as, we've always described Lambda as what would the cloud look like if it was reinvented from the ground up for AI?

Mm-hmm.

You know, training and inferencing large language models, training and inferencing large-scale neural networks.

Yeah.

And I think that NeoCloud's an appropriate description for that concept.

What is the balance between training and inference right now, and how has that evolved over the last couple years?

Yeah, so, you know, we're— for the overall business, we're just We're just a bit over $500 million of top line revenue. And I'd say that essentially—

Congratulations.

Thank you. Thank you. Essentially, historically, that's been majority training and then sort of minority interest, you know, maybe 80/20 for, for, you know, training to inference. And now we've started to see that kind of switch over. I would generally say that when I see any sort of net new deal in the space for large-scale GPU capacity, it tends to be more inference-driven these days.

Sure.

That's great. We're actually using the models. It's not just training ever bigger models with no— With no— I mean, we saw that at Google I/O, Sundar Pichai pulled up the chart of tokens generated, and it's just completely up and to the right.

It's completely up and to the right. I mean, training is always going to be something where you do it once, and the whole point of training is that you want to amortize that over as many tokens as possible, right? Because that's just your fixed cost that you're wanting to spread across as many generations as possible. And so that's the point. The point of training is inference. Um, yeah, we're there. I always kind of look at this as like, like a, I always like to sort AI companies by revenue and just go, okay, well, who's at the top? Probably like OpenAI today.

Mm-hmm.

You know, $4 billion, $5 billion. It's, it's, it's a little bit hard to, you know, to clock it, to, to, to exactly guess. But then, you know, next one down, you kind of look, um, Anthropic.

Mm-hmm.

$800 million last published. Uh, mostly developer API. But probably fast growing. I would imagine they're probably in the billions now because Sonnet 3.7 was really good for code generation. Google doesn't seem to be charging, from what I can tell.

They're charging me $250 a month now just to—

It'll pop up to $500 too.

So they're getting my money.

What are they charging for GPT?

So I am now on the Gemini Ultra plan.

Okay.

And I have 2.5 Pro preview. And then I also have access to VO3, but it's very limited. Like, they can only generate 2 or 3 video clips per day. It's heavily throttled, but it's a $250 a month plan right now, and it's gonna jump up to $500 a month in a few months. So I imagine that across Gemini Pro subscriptions, they're probably gonna grow that pretty quickly just because I'm seeing the number of files per release.

It'll go zero to billion dollars in—

100%.

In a couple weeks.

Right.

Absolutely.

Yeah.

So when you kind of do that breakdown, what do we see in terms of like total top line revenue? It's all inference, right? I mean, all of that is inference demand, whether it's image or ChatGPT or video generation. And then, you know, Midjourney is probably, you know, in the hundreds of millions of dollars revenue run rate. And so there's some substantial businesses that are being built right now.

Yeah. What are some kind of narratives What are some narrative violations, things that you feel like the broader ecosystem is getting wrong right now, given you guys have unique insight into actual usage and activity?

Yeah. Okay. So, the first one is just obviously, I think if you look back, there was that Sequoia Think Boy piece that was published on like, where's the Jeep? You know, where's the AI revenue? What's you know?

Sure, sure.

They sort of did that. It there's a lot wrong with that analysis, so I don't need to go into that. But I'd say like the general pessimism of like, oh, it's a bubble, it's a bubble, it's a bubble.

Yeah.

I just remember, you know, I started Lambda in 2012. 2013 was the year that like Mark Zuckerberg went to NERD and hired. hired Yann LeCun to start Facebook AI research at the time. And I just remember everybody in the field kind of at the time looking around, oh, is it a bubble? You know, Google's just bought DeepMind and Facebook's buying Yann LeCun. So it must be a bubble because Mark Zuckerberg just came to NeurIPS. But I think that in general, everybody underestimates how just what exponential growth looks like. You know, it always looks the same in the same— you know, wherever you are, it always looks essentially the same. And how good the code generation has gotten over the last 90 days, right? If you were to flip back before January, you know, state of the art for code generation was 4.0. And then 0.1 hadn't even, I think, been exactly released yet. With 0.1, 0.4, Claude Sonnet 3.5, 3.7, all this stuff, the code generation is getting so good that we— I think I can say here, which is in a couple of years, you're just gonna have a function that goes from cash into software. And that is going to completely change the way that businesses operate because, you know, you're going to spin up 500 different versions of the piece of software that you're searching for. You're going to be able to do this sort of like high-throughput search through software space. It's going to spit out a bunch of things. It's going to have like a, maybe a tastemaker model that just rates it based off of, you know, the computer use compiled version of that software and say, hey, well, these are all the source code bases for all 500 pieces of software. These are the top 5. I'd recommend you launch this one, go for it. And I think that's gonna really change the way that the world operates on the, in, in technology.

So should you learn to code if you're a teenager?

Yeah, absolutely. I, I think that you, you still, you still need to learn how to code. Um, I, I, I don't see, I, I think it's, it's really hard to, In the intermediate period, you're still going to need to learn how to code. I think that you're just going to see much higher leverage teams in the world.

You might always need to think like a programmer, and so learning to code is part of that process. That makes sense. What about the evolution of chips and semis?

Before we dive into that— I feel like there's this general thesis that sort of— we've talked about this on the show, this idea of like, we call it like Jiro dreams of sushi software, right? This like really craft—

More art than science.

Yeah, art and science, like super intentionally built software that is just super, super thoughtful. And you can see this in companies that maybe go after a category like CRM, where it's like, okay, Salesforce dominates CRM, but they come in and they build this sort of really beautiful, really thoughtful experience. And typically, if the teams are good enough, they'll end up doing well. I think there's this sense that that class of software is safe from completely AI-generated software. But in the scenario you laid out where you generate 500 different variations of a potential tool that you'd use and it automatically ranks it based on some taste-driven benchmark. Is it possible that that class of software is at extreme risk to disruption as well?

Certainly, I think anything that's just software is at extreme risk. Look at a business like Salesforce. It's almost as if, I mean, how important is the software? How important is the brand? How important is the distribution model? And I think that when you look, the bigger the company gets, the more important the latter becomes, you know, the distribution model, the brand of the company, how deeply embedded it is inside of the day-to-day life of the customer that's using it. And it's sort of like, well, what is the value of Salesforce? Is it the software? No, not at all. The value of Salesforce is the fact that every single company in the world, the first thing they, they do when they hire a VP of sales is like make sure they have a Salesforce implementation and then it sticks with the company until they're an S&P 500 component. And then all of the company's data is in Salesforce, right? Does that have anything to do with the software that Salesforce has written? Is that the mo—

anything?

Does, is, does the moat have anything to do with the replacement cost of developing the software?

The CRUD app.

Yeah.

No, right? So it's kind of interesting because like stuff like software will be solved, but then stuff like how do you build moat and how do you build a business won't be solved. So it's sort of like maybe just, you know, this is— we're in the world for just the business co-founder dominates.

The era of the ideas guy. The era of the ideas guy is upon us.

Yeah.

That's amazing.

Yeah. That would be really exciting.

Okay. I, I, I wanna talk more specifically about the, the, the path to this future of, like, turning money into software and creating value that way. What is more important? Just bigger training runs, knocking down higher MMLU numbers, benchmarks, higher IQ points versus distilling models, faster inference, cheaper inference, Baking some of these models down into silicon, what we're seeing with Etched and putting the transformer architecture on a chip. They seem like 2 different vectors. Every time a new model comes out, my reaction is always like, well, this is good enough. I just want it to be faster. And so Midjourney V6 or whatever, I'm usually just like, yeah, I just love this to be instantaneous. As soon as I type the words, it's just generating in milliseconds. At the same time, the labs seem to be iterating towards bigger and better models, and they, and, and they, they have a mentality of, like, job's not finished. But what's your take on, on those, on the trade-offs there?

Well, what we're seeing with the advent of reasoning models, as well as, like, the, the, the models that basically will do reasoning and then sort of, like, retrain the model to not do any reasoning, but sort of baking in the reasoning. is that this— the amount of compute that you— you know, the performance improves as a function of how much runtime compute you do.

Yeah.

And so, if you can make a faster model and you can reason faster about it, you could make an argument that that actually might perform might perform better in some circumstances. I think that we're gonna see all dimensions of that space explored by a variety of companies. You know, there will be people out there at the edge building the biggest frontier models. There will be people quantizing and distilling those models down to something that runs locally on your phone. That was actually kind of one of the things I did before this iteration of where Lambda is. It was sort of trained ConvNets that ran locally on the iPhone.

Oh, wow.

And this is like 2013. And it— you kind of see the same thing. There's use cases for that.

It's super useful.

You can have privacy-preserving image recognition on your phone.

Yeah.

But it's not going to be the same quality as like something that goes back to a data center. I think actually, if there's one narrative violation, just going back to, you know, You said this like world of software generation. A lot of people are kind of stuck in this like, okay, AI is generating software. And I've got this entire, I think, thesis on where the future, where we're going, you won't need any software at all and that the neural network is going to completely replace all the software. And so let me walk you through this. The idea is that instead of generating a program, let's say a calculator or an Excel spreadsheet. Just go to ChatGPT and say, hi, please behave like a program. Please behave like this calculator or behave like this spreadsheet. Generate an ASCII user interface for me. And I want you to essentially just respond, you know, implement the logic of that program in your mind. And that is what I call neural software. And it's really squishy. You know, normal software is really brittle, right? If you make a typo, you leave a keyword out, you miss a semicolon, it's not going to compile. This type of neural software, it's not really possible to have a bug. It's really more just that you have a misunderstanding or you've misprompted it or something. And I think that that's where all this is going. It's not code generation, but it's going to be Your large language models are going to sort of take over more and more of program space. And you will be largely interacting with these sort of transformer models or next token prediction models generally, and they will be the software that you interact with.

What about diffusion models? We saw Google bring diffusion to text models.

Yeah.

I was seeing something like 900 tokens per second.

Yeah.

They generated— I saw a demo where someone generated a full calendar application, all the code for the calendar application in 3 seconds. It was 3,000 tokens or something like that. That feels like a, you know, an algorithm from image generation that now we're seeing in the text world. Simultaneously, we're seeing images in ChatGPT GPT, maybe do something more transformer or token-based. And so these lines are blurring. Can you give us any insight into what's happening there? Is that exciting, or is this kind of just in the experimental phase?

Well, I mean, this is like— whether it's exciting or not is going to kind of answer the question you had earlier, which is how successful are baked-in transformer ASICs going to be, right?

Sure.

Because sort of like as the space, the underlying space changes, then every one of those sort of ASICs now becomes a lot less valuable. And you kind of have to go back to the more general tensor processing that you see inside of tensor cores and you see inside of the architecture of like things like TPUs and away from, you know, really specific things that have to do with like the KV cache and different transformer-specific architectural things you might want to put into an ASIC. And so I think that it's interesting to see you've got diffusion models, you've got things like Mamba, and where there's alternatives to the transformer that have what's called basically linear complexity in terms of the the amount of memory that you need for the context length growing, which is better than the quadratic complexity you see inside of normal transformer models. And I think there's going to continue to be a lot of innovation in the model architecture space.

Yeah.

And that will probably benefit Nvidia a lot.

Got it. Are there any other side projects in semiconductors that are exciting to you? Huge wafer-scale computing like Cerebras. We talked a little bit about baking things down onto ASICs. We saw that path play out with Bitcoin, with the FPGAs and then the ASIC kind of Bitcoin mining. There's other approaches and I'm sure Nvidia's not asleep at the wheel. Jensen Huang's in founder mode. He's He's aware of the boom, he's aware of the demand. I'm sure people are asking him, how can we run diffusion models faster? How can we run transformer models faster? What are you expecting on the semiconductor side over the next few years?

Well, it's pretty clear that I'd say the front runners for competing with Nvidia, which are all very far behind Nvidia, but the ones that are sort of I think the farthest along is probably, I would say today is Google and to some extent Amazon with Trainium and Inferentia.

Yeah.

That space is always evolving fast, but I think it's kind of a little bit telling that AMD hasn't with all the resources, with all the sort of clarity on what you're supposed to build for the market, hasn't been able to kind of capture enough market share.

Dylan Patel's gonna turn it around. He's gonna write just one more report and AMD is gonna be back. I'm bullish.

That's all it takes. All it takes.

I love it. But In terms of, can you give us a little perspective on, obviously, if I'm doing a ton of inference on Lambda, I'm probably in the CUDA ecosystem, probably in NVIDIA land. If I want to take that over to Amazon or Google with TPUs, how much of a barrier really is that? Can you kind of explain? Because at the same time—

Yeah.

We have these incredible code generation models. It feels like— Putting an AI agent on rewrite this CUDA for TPU, that seems like the easiest thing to do. It seems like a problem perfectly tailor-made for AI agents to just sit there and write boring translation code. It's not even feature design, right?

Wasn't that in the TL where someone was making a joke about the Anthropic safety snitching on the user? And someone said, port this PyTorch code over to JAX. And then it says, you know, searching, calling FBI.

Calling FBI. Do not do this. You're gonna pull the rug on the entire economy if you do that.

Preserving the underlying chips that it's running on to make sure.

It's so important to America.

So I think that, okay, the stuff that this code generation is really good at today is still sort of what I would call within the realm of what you know, one-shotting a basic program, one-shotting sort of a one-page program. It could be much longer than one page, but it's sort of like single file.

Or a function or, you know, a class, something like that. Not necessarily something that's complex.

Maybe I'm just behind on it a little bit and I'm not doing what the kids are doing or something with sort of an AI IDE, but I just kind of like when I'm vibe coding. I will just tell either ChatGPT or Gemini or Claude, I'll go, do this in one page. Like, have it be a one thing. I want to copy and paste this into my, my thing and run it. Um, and it's, it's quite good at that.

Mm-hmm.

Now, when you talk about like going through an entire codebase, um, fixing the compilation errors, because there will be like subtle Yeah. Subtle bugs that get introduced. It's not quite there yet.

Yeah.

It's just the problem is that I now am at like 100% confidence that it is going to be there in just a couple of years. And that's kind of why I know that every sort of megawatt that we build and every GPU that we deploy is just gonna get met with demand on the other side because Just 2 years out. Like if you just look 2 years ago, 2023, code generation was primitive. Yeah, primitive. It didn't work. Now today it really works for more simple programs. I think 2 years from now it's just gonna, it's gonna make you feel sick when you look at it.

So what are the big bottlenecks you, you foresee between like energy, water, land, Are you gonna be building a data center in space? What, what do you think the future looks like for you?

So I think that the, the bottleneck is definitely what I call like wrapped power. So the, I think there's plenty of generated power right now. It's just not wrapped up in a data center shell. It's not in a powered shell. It's not in a facility that has direct-to-chip liquid cooling integrated into it. And so it's sort of like that wrapped up power that's like ready for the current generation and next generation of chips. I think that there's, there's definitely some like regulatory bottlenecks, or I would just say regulatory hurdles that can be removed. And I think there's a lot of hope that this administration is going to start to remove those. That's like Whether it's like looking at sort of the way that we run utilities where you kind of have to in some cases become an unregulated utility and put like, let's say, you know, build a data center power plant, which is to say behind the grid or not attached to the grid power generation station next to a data center. And not every state is going to allow that. And I think that there's, there's probably a lot to do in the regulatory side to unleash the free market and let people build. And so I think that— I think there's some hope there. And the other thing is just really, I think building large contiguous spaces is like— is pretty clearly the answer, in my opinion.

Well, good luck with that. I'm glad I don't have to deal with it.

It's a lot of logistics.

It's a real pain. It sounds like a lot of work, but you've been doing it for 14, 13 years.

Yeah.

Classic.

Another decade in you at least. So good luck to you.

Yeah.

We'd love to have you back on. This is a fantastic conversation.

Come back on again soon.

Thanks, guys.

So many fun—

love what you do.

Longtime fan. This is really fun.

I didn't clock you as a Monster guy too. We got to go deeper on energy drinks.

Yeah. There's so much to talk about.

Lots to talk about.

But this is fantastic. Thank you so much for coming on.

Great chatting.

Quickly, let me tell you about Numeral. Sales tax on autopilot. Spend less than five minutes on sales tax compliance.

Should we sing sales tax AGI?

Sales tax AGI. Go get go get Numeral. Head over to numeralhq.com.

How did you sleep last night, John?

Oh, terrible! I woke up at four a.m. It was a disaster. I'm I know I'm gonna get cooked, but you don't have to be cooked because you can go to eightsleep.com.

Use code. TBPN.

I got a 76. It was brutal.

Oh, 99. I can't, I can't get 99. I'm back to back 99s. I don't know what I'm doing wrong.

And then also we got to tell the folks about public.com investing. For those who take it seriously, they got multi-asset investing, industry-leading yields. They're trusted.

Let's give it up for multi-asset investing.

Yep. And, uh, in their partnership with Aston Martin, which we might have more information on soon, but stay tuned.

I cannot wait.

Anyway, we got Sam Lessin coming in the Temple of Technology very quickly. Do you wanna do some timeline while we wait for him? Is he here?

You know I love timeline, John.

I know. Dwarkesh Patel dropped a banger on Claude 4 Day. He sat down with Trenton Brickin and Sholto Douglas talking about Claude 4, how far reinforcement learning can scale. I haven't had a chance to listen to the whole thing. I listened to about half of it kind of in and out while I was trying to sleep last night. But, I mean, just a very cool vibe of, like, 3 people having a conversation right on the day when you want to know this stuff, talking all about this fascinating metaphor for AI safety, because it's just been controversial. Of course, there's some drama around some random Anthropic news, but the cool thing that I liked was they said, basically, if you want to tell the AGI what to do and how to behave in the best interest of humanity, you could give it specific rules, but it might actually be better to say, imagine there's an envelope, AGI, guy. And in that envelope is what I want you to do, all the rules I want you to follow. You can't access this envelope, but you have to behave in accordance to what you imagine to be in this envelope. And so the agent is just like, I have to behave in the interest of humanity. It was a cool, like, thought experiment almost.

Interesting.

It was very cool. Anyway, Patrick O'Shaughnessy was shouting it out. He says one of his favorite genres of podcasts is recurrent expert guests on the same show. If you're interested in the nitty-gritty of AI progression, you'll enjoy this. So go check that show out this weekend. It's a great listen. And we have Sam Lessin from Slow Ventures in the studio. Welcome to the studio, Sam.

Gentlemen, there he is.

It's Jessica Lessin's husband.

Put it all together right now. In the flesh. I saw her like literally minutes ago.

That's how famous I am.

No way. Tell her to come by at least and say hi if she's not busy.

Yeah, yeah. She's busy this moment, but you know, we're—

Later.

Well, we got 30 minutes.

We got the crossover of the century. TBP and The Information. It dropped today. It was great.

I love that. Yeah, I actually— I knew about the development of that story from dinner conversations.

Oh yeah, it was a lot of fun.

I bet. I bet. Abe is— Abe is the man. Yeah. There you go. It was— it was fun hanging out with him and kind of the same way.

So are you guys— you guys are the COVID of the weekend section, is that right?

We are.

We are the big—

are you guys going to do a print edition for us?

That's coveted space. I always thought that they should actually do a print edition. I think it's time. Everything goes in a cycle.

I got the Wall Street Journal here.

I need—

Yeah, it really— I know.

A once-weekly Saturday dropped off on the doorsteps of every—

100%. I would hire the kids to deliver it with the, you know, throwing it out the window. Yeah. Look, I was in an airport lounge in Germany 2 days ago and they had all the print newspapers and I'm like, look, there's a missing opportunity here. The Germans want to read about the information. They want to read about Technology Brothers.

Yeah, of course. Let's get it to them.

You guys are big in Germany, I'm sure.

Well, somebody started translating our streams into Dutch, which is interesting. They're doing other—

That doesn't seem like the first choice. Like, don't you want like Mandarin or something? I think that doesn't seem like—

we're trying to get big on Weibo.

Yeah, that's next.

Yeah, but we're expecting to have some pushback. Anyways, it's great to have you on. As always, congrats on your success.

You guys are everywhere. This isn't the new studio yet, though.

Well, you're part of that.

You're a part of that.

You have to come down next time you're in LA. Come by in person.

Be great.

Yeah. Tuesday will be the first show.

Yeah.

It's a lot closer than Englewood Cliffs, New Jersey. You know?

Yeah.

Yeah.

What's what? What's there?

Oh, God.

Is that the new?

Is that the new Netflix?

The NBC. You can't make this whole CNBC rival thing and not know where CNBC is.

Everyone always says like yeah. Andrew Reed was like, "Oh, they're making Squawk Box for tech," and I was like, "Gotta start watching Squawk Box." Netflix.

I guess Netflix is also Netflix has a new billion-dollar New Jersey studio.

Maybe maybe it's New Jersey, and maybe we're taking the fight to New Jersey in the future.

We'll see. LA's fine.

Where were you? Where were you traveling this week?

I I I went. I've had an insane travel schedule, but I was Monday.

I went.

I was New York, Frankfurt, New York, San Francisco was my was my week.

What's going on in in Germany?

Germany was a personal thing I had to take care of, but but New York was the Solana acceleration. What is it? The salon big Solana conference, which they call ship or die. Very dramatic.

Nice, nice. You're infamous there, right? The GM, the GM guy. Do you still get comments on that?

You know, I saw I saw Raj backstage. You know, I was I was one of Solana's first investors. I like mine. My Jason Kalkanis, I was the first investor in Uber, was like, I like do that for Solana, right? And so, you know, I've known those guys for a long time and I saw Raj backstage reminiscing when I did the GM thing, which became one of the first meme coins and blew up and got— if you remember, it got Raj banned.

No, I know. That was crazy.

Twitter.

It was something funny about that.

Yeah. And this was like Twitter still, right? So it was like somebody at Twitter was like, didn't get the joke, obviously didn't have context that like you guys are boys and just—

Yeah. So the thing is, I unfortunately have other people on Twitter legitimately threatened to kill me, which that's not so good. You got to get that taken down. But the, the Raj was a pretty funny one for them to respond so quickly to.

Yeah.

Yeah.

Quick reaction. There's so much, so much to cover.

It's AI week.

It's AI week.

Isn't it every week AI week, boys?

No, but this week was particularly AI week because of Microsoft, Google I/O, OpenAI I/O, Anthropic, uh, a big, uh— are you, are you taking a victory lap on the idea that this is a sustaining innovation that Google's gonna win?

You guys, actually, I'll tell you a funny, a funny anecdote. You guys know my associate Jack Raines. You know this guy? Yeah, you're sitting— he's right over there. Jack, he can come wave for a second.

Hey, Jack, come say hi.

Jack sends me this long missive this week about how amazing Google is and how Google is going to win the AI wars.

What's up, dude?

And I'm like, what value are you adding? I've been saying this for 2 years. I'm like, thank you. I'm like—

I wanted to check out all the little Google—

I was like, I was like, Jack, I was like, Jack, you know, you're an associate at an early-stage venture capital fund. Telling us to buy Google stock is not exactly—

You guys, I want to see Slow as the next crossover.

Yeah, crossover. Become an RIA.

Put 30%.

We've actually looked into it. Definitely not a thing we'll ever do.

No, I mean, I mean, the, the, my favorite comparison, I forget who posted it, but they were like, would you, do you want, you know, Google at, you know, 17 times earnings or Costco at 50 times earnings? Like at this moment, this AI inflection point.

Look, here's the negative on I/O. The negative on I/O is that per usual, Google's actually terrible at marketing, right? And so they just launch everything. And so you're like, I have no idea even where to focus right now, right? Like, it's, it's not—

My value comes in figuring out—

thanks, Jack.

Focus on generative AI videos. Anyway, that's the thing.

It's like so many things. You're like, I don't know. But the net of it is like, they're just crushing it, right? Like, from a tech perspective. And I gotta say, I'll tell you a funny story. I spent like 20 hours, quote unquote, vibe coding over the last week because I was on so many airplanes. And it turns out airplane Wi-Fi, vibe coding, perfect match of activity. So I just like, yeah, was like messing with these things till my eyes bled. And you know what happened in hour 11?

What?

I stopped using ChatGPT and went all in on Gemini because it's actually better. Gemini 2.5 Pro is just like way better at a bunch of these coding tasks. It's better at structuring. There's like a bunch of stuff. So it's, it's, I think it was absolutely a Google week.

But were you using Codex?

No, I wasn't using Codex.

Oh my God.

See, oh then like, there's always another, there's always another tool.

Look, this is one of my other insights from the week, spending a week, you know, literally flying around the country, vibe coding in the air, is, um, you know, the, the, the whole what model to use thing is a complete fucking mess.

Right.

And I think that the analogy I now have in my head is it's kind of like, imagine walking into a crowded room where you don't know anyone and saying, who should I trust? Right. And then, by the way, every 2 seconds a new person pops into the room. You have no— and like, people are like, oh, or—

Or you can trust this person 95% of the time. You can't trust them with your life, you know?

But that's a totally— that's a totally separate train of thought. I think it's important. I was talking to some entrepreneurs today about if you think about what AI is today, it's like having a B-minus employee or like an 80-percenter. And the question is, how do you get value out of 80-percenters is actually more difficult than it looks in a lot of ways, right? Because the reality is so much of work is about trust.

But isn't it more— isn't it more their B-minus because it's— you're averaging their effectiveness on different things? In my experience, it's like for certain tasks, it's like 80, 90% of the time it's amazing. And then some percentage of the time it's so bad that you would want to— you would ask the employee, is everything okay? Like, you've never—

Kind of. But I think the other thing, the thing I really think about, guys, is, you know, if you think people are always like, oh, There are all these tasks that AI is more efficient at, and so clearly those jobs will just go away and it'll be it. I think that's exactly the wrong model, because the reality— what people don't understand is the real reason you hire people to do work is not to do the work. It's to have a throat to choke when the work goes badly.

Right.

It's like, why do you have an accountant? You don't have an accountant to do your taxes. You have an accountant so that when the IRS comes and says, what's wrong with— why did you get this wrong? You're like, I didn't do it. I did it, right? And so I think that's the interesting thing is like there's all these models like, great, good news, you get rid of the employee and now you get a queue that's mostly right and you approve and you're like, I don't want to approve that stuff. Like the whole point is to have someone else.

Yeah, I think our example is like we use a lot of the different deep research products and like we still would love to hire an amazing researcher.

Yeah. So that you can fire them when they're wrong, right? Like you need like— it's just the point is like there's this whole— I think there's a lot of like—

Well, it's an agency thing. thing too. It's like if you could tell deep research to try itself and then try other products and then combine the outputs of all the different things, and maybe that's a research agent that can—

There's all these things, but I think the ultimate model in my mind is I don't even care what the average person is using. I don't care about some review online that's 4 stars for coding for this type of— I don't care. What I care about is what are the smartest people I know in the world?

using?

And how do you make that transparent so I can just be like, oh, it's this type of task, I'm going to trust this model for that. And that needs to be up to date. It's much more of an identity problem or a human trust problem than it is a technology problem in a lot of ways. And it's just changing really fast. So it's been a fascinating week. But yeah, pulling all the way up, yes, I'm taking a victory lap on Google wins. And yes, I'm taking a victory lap on incumbents win, because that's what's happening.

So you're saying to Jack, like, thanks for reading my memo from 2 years ago?

Yeah, exactly. Well, in fairness to Jack, he wasn't on the team 2 years ago. Yeah, he was very excited to discover Notebook L, but—

Love you, Jack.

I got to— we got to— got to get him out of the pool house. Yeah.

Anyway, I want to talk about some other stuff. What do you think about the Jony Ive news and hardware generally?

I mean, where to begin?

I know, I know. This is my favorite part of having you on the show. We don't have to prompt at all. We just like to— we could give you 3 words. Johnny Ive hardware.

Well, okay, a few things. First of all, I mean, my, my tweet on this when it was happening was like, well, I guess all these $100 million AI researchers are cheap, right? Like these— it's the designers that are going to get paid bank on acquihires in this, in this era, right? Look, I think it was marketed in a really interesting way. Right? Like, it's marketed as like they tried to pick the biggest number possible. It's a 2%. They paid 2% for this thing.

Yeah, right.

For him, they market it as it's this big number. I think because that's— it's kind of the pissing match of AI, right? Is you're supposed to look really big and powerful with big number. And I'm sure Johnny doesn't mind being told that he's worth $6 billion. But like, it's kind of one of those interesting PR stories of like how you shape the narrative as much as anything else. The hardware thing is interesting. On one hand, I actually think if you're OpenAI, you do need a hardware play. You're going to get fucked otherwise. Meta discovered this years ago, which is that being beholden to other people's hardware is really tough. In this case, it's only more so because of the way these chips are going to fall with Android and iOS. So I don't think they're wrong. Meta's got its glasses. It's not strategically wrong from first principles. I think the problem that I have Is I just think that like the likelihood they're going to successfully introduce a new piece of hardware is like zero, right? Like, and that's just, you know, it's, you know, you're going to have a phone and they could try to compete on the phone, but it's very hard for them to imagine building like a fully featured phone that, you know, whatever. And then also having something that's so big.

Well, the one thing that does seem clear, haven't they said this is an A new type of device that will integrate with your phone and your computer. And that screams to me, okay, well, is app— yeah, yeah. I said septum piercing wear.

I saw that.

Well, you know, my take was e-cane. Did you see e-cane? So this was— so when I left in 2014—

No, but sorry, sorry to finish my thought. The issue with that is if you're saying we're going to create a new device that integrates with your Apple ecosystem, That seems like a bit of an uphill battle. Look what happened to Pebble, right, and the Apple Watch, right?

In the end of the day, it's like, look, you know, you have— the iPhone is a hugely breakthrough device. This is, by the way, not my line, it's a friend's line, but like hugely breakthrough device. You already had a phone, right? You know, it wasn't like a new thing you were putting on your body. The glasses work, that's a thing that was already on your body. The watch works, it's a thing that— it's really hard to imagine You're going to get through with some new device. My joke, but it's only half a joke, is look, 12 years ago I got obsessed with the idea of making an e-cane. Imagine bringing back the cane.

That's what you meant.

I had no idea.

If you think about the cane, you put a shitload of batteries in it, big antenna, and you know what the nice part is? The world is getting less safe, so you can beat people with it. The world is aging, so everyone needs canes. There's all these macro trends in favor of bringing back the cane. Then could you drop a GPU and a microphone and a camera in the top and talk to your cane? Smart cane.

Smart cane.

Smart cane.

No more dumb—

I don't want to be pitched any more non-AI canes, okay? I've had enough.

I'm just saying, if OpenAI came out and they're like, we're bringing back the cane, I'd be like, all right, listen, for all my—

Well, you know that Jony Ive got his start at a design firm that was working on bathrooms, and so maybe there's all like smart toilet, you know?

Yeah, well, there is— someone just came out, there's a— there is like a new Fitbit for your poop. Okay, I know some friends that have funded that. That's right.

I funded that.

You funded that? I know some people. It's called Throne.

I think it's called Throne.

I think it's interesting.

Yeah.

For a bunch of reasons. One is it's just like personally as like a quote unquote biohacker, there's so much information on how your digestion— what's happening with your digestion, your hydration, all these different things.

Look, at the end of the day, you want to copy behaviors people are already doing. And, you know, in college, one of my roommates, Brian, would send me pictures of his poop all the time. So like, you know, you just got to double down.

Brutal.

Brutal.

Let's move on.

Brutal.

Hyperscaler Kappa. Give us anything to get us off of this.

Well, here's my hyperscaler CapEx. Here's my line on it. I flew through JFK today. They're spending $20 billion renovating JFK. Yeah, I'm like, this CapEx is nothing. Spend more money on AI. Like, if you're going to spend $20 billion on, like, renovating JFK, all of a sudden spending $100 billion on AI doesn't seem so crazy.

Mm-hmm.

What about Say as much as you can about what Meta's playbook over the next 6 to 12 months. I know they've been having talent retention.

Llama was the question.

Yeah, Llama, Behemoth delayed.

Delayed.

Look, at the end of the day, again, I, as you know, have huge respect for the team there and the leadership there. I think the beauty of Meta, as I've said many times, is it's a heads you win, tails you win, right? From an investor perspective. Right? Which is, if you think about it, it's like the most obvious, highest value use case in the world for everything that exists is making ads way more targeted and effective. Right. And that's happening. And it's an incredible trend to ride and they're going to crush it. You know, Mark and that team is like deeply competitive. They want to win, win, win. Right. And so just from a pure competition perspective, I think they're going to like go to the mat to win, win, win. And like there'll be many chapters to that. But the good news is they have a massively profitable business. and an immediate use case, right, that is deeply aligned. And so I just, you know, I learned a long, long, long time ago to never bet against Mark, especially when he cares about it.

Yeah, it feels like with Meta, there's huge value to having Llama be a free LLM for them that they can vend into every corner of the app, even in places the consumer doesn't feel or see. So profanity filtering and understanding what content goes where, Ad matching, generative AI to clean up Instagram photos, all these things that will just be under the surface.

Yeah.

As opposed to what Google's doing, which is like, now we have 10 new apps, NotebookLM. Like, you're— we're not seeing that from Meta, and maybe that's the right strategy.

I look, at the end of the day, Meta has the most natural, beautiful use cases for AI, which is what you're pointing out. And therefore, like, they don't need to do a bunch of crazy shit, right? They just need to, like, win at, like, the core. And then basically, again, the open source thing is clear. It's like they actually— for like, think about ads. They don't really care if they're doing the AI or someone else's because it's all going to go to them either way, right? At the end of the day, it's just better if more people have access to it and innovation will happen. So look, one of the things I did in my VibeCon, I got really into like all the platforms, right? I spent a bunch of time— remember DigitalOcean? Like, DigitalOcean is doing a great job with AI, right? Like, it turns out like their services are really good and like it was really easy to boot up some agents on top of, like, you know, a knowledge base on top of, you know—

That's always the worst part is, like, deploy— you, you write some code and you wanna actually get it on a server. It's always still a hassle.

And it's like, they've actually done a great job.

It's—

I was, like, incredibly impressed. But, like, you know, and then you say, like, where is Llama showing up? It's like, well, it's, like, right there. Like, you just click a button and you're using Llama. It's like, no bullshit.

You gotta get a killer video generation model out of Meta. Like, they, they're the only one that has another data source similar to YouTube.

How do you see that market?

How do you see that market evolving. There's a bunch of foundation model labs doing video generation, and I can see some of those getting to the point where they could crush it for big Hollywood movie studio, making very specific types of scenes or assets. But then it feels like the low end of the market for, if you're a random SMB and you want to make an ad or something like that, yeah, maybe use some vertical SaaS, but also I wonder how much it matters.

I mean, like, I had this conversation actually with my good friend Dave Moran on our little weekly, you know, bullshit session.

More or less.

More or less.

We're talking about the fact that Dave also somehow cracked like the top of the angel— there was like, oh yeah, top angel investor list. And he, he was the top dog. It's amazing.

So let's get a list of the validity of that list. We'll talk about it. Yeah, we could.

But I mean, I just like to see my boy Dave at the top.

Look, my boy Kevin. My boy, my partner Kevin was like number four on the list. It was a very interesting list.

But the I wasn't on the list, but you know that's okay.

The the but what I was gonna say is the the thing Dave and I were talking about is like look, you know if you think about what's going on like with memes right in this whole world, you have there's this like high road low road thing. Everyone's really excited about like super high end video generation and Hollywood and da da da. You know what's happened in the media landscape? Those things don't make any money. No one cares about these movies anyway. Like, they're consuming like low-end crowdsourced memes on the internet. Like, that's where attention is. That's where the energy is. That's where entertainment is. And so I think obviously the pure technologists and like the highfalutin people are really excited about like the narrative storytelling, beautiful data. But when it comes to like what tools will actually be used, how things will be marketed, how humans will interact with each other and communicate, in the store. I think actually it'd be much more budgety tools that actually win. And the other stuff is kind of just, you know, intellectual, you know, masturbation a little bit. It doesn't mean you shouldn't do it. Like, people—

Speaking of that, speaking of that, why is— speaking of masturbation, why is OnlyFans getting priced at 8 times earnings?

You know, I so desperately want to buy OnlyFans, guys. I've wanted to buy it for years. I had plans. Like, there's been a few iterations of this. No, it's so good.

It's so good.

I just—

what do you have against OnlyFans?

Uh, uh, I just—

so good. This is— but your reaction is part of the reason I want to buy it, right?

Of course, the buyer pool is small, so the price is low.

The pro— well, that's part of it. The other thing is everyone— because the buyers— it's actually the best AI short you could possibly think of, right? Because part of the reason it's getting sold, my understanding, and like the whole story around it, is like, well, we're gonna have all these AI girlfriends.

Sure.

So like the creator economy is gonna get crushed on these things. And I think that is like a very 101 simplistic take on what's happening.

The other thing is a lot of the, a lot of the cost that goes into basically generating revenue on OnlyFans is from messaging, which is done by people in the Philippines.

And AI.

So this is the thing, everyone, OpenAI is like the greatest human AI platform in existence, right, from a position because you have— I think you still need real brands. I think that having human brands matters at the top end. Your ability to then like effectively automate, it's kind of like the Facebook story, which is your ability to slot in AI and bank it right on messaging is like off the charts with OnlyFans and improve the quality. So I think it's interesting. I think it's like this classic thing where it's being sold. I've always loved the asset. It's the number one creator platform in the world. It's so defensible because they actually have a very low take rate. Because they're so big that no one can— no one can assault them, right? Because of how they're kind of set up.

What's the take rate?

It's like, it's really low. I want to say it's like 10%, maybe 15%, but it's like much lower than you think. And as a result, like, you have this incredible cash engine.

I mean, YouTube's like 45%, right? Many other sites are 30% just for general content creation.

So just the upshot is like this incredible position.

It's—

I think there are huge product opportunities. opportunities. There always have been with it. But then you have this double storm of like, one, people like you guys boo it because you're— you patrician technology brothers, right? Like, and you won't like acknowledge human nature. People want to do this. And then 2, there's all these fancy investors who like think it's dead because they read the front page of the Wall Street Journal about AI and don't understand what's actually going on. I'm like, that's great. This is my zone.

Christ.

Yeah, I have no—

You're gonna have to become an RIA to do it, probably.

So, well, I got to figure out how to not do that. I also like, for what it's worth, I'm a seed investor. I don't know how to raise The $2 billion I need. But call me if you got it.

Well, speaking of seed investors, I don't know if you saw this chart from PitchBook. Emerging managers are on track to raise less money this year than they have in a decade. That sounds right. It's now under $20 billion. During 2021, it was up at $60 billion. It really, really spiked. 2022 was around $50 billion. And now we're down in— Just $20 billion.

Just one JFK renovation.

That is that is a lot of money for emerging managers.

This is I assume this defined as like where are you going to put twenty billion dollars as an emerging manager?

Wait, how much did they get in 2021?

Well, you put it you I mean you put it in like twenty thousand fifty million dollar funds. That's the idea at least, or that's what happened.

They're all I just I've been so skin. I don't see any of this working out for anyone, right? Like you know I I know it's it's one of the the the they'll always be the random winner.

Yeah, but but isn't that the nature of the game? It's like startups follow a power law. So do funds.

I just think we have to hit a size gong because the $64 billion that they raised in 2021 still earns $12 billion of fees.

Yeah.

And so let's just give it up.

Congratulations to the emerging managers.

But it's kind of— guys, I think you guys are cheering too much. If you do the math on—

no, I'm joking, to be clear.

I mean, doing the math on being a small fund and being locked in for 10 years as like a solo GP with your emerging manager fund and you're kind of shitty subscale, it's actually a pretty bad business.

What's wrong with being locked in?

No, no, no, no. What you're saying is so real, which is imagine you have a startup and it's like, okay, you have to commit to this startup for a decade, even if by 2.5 years in, like, is that real though?

Is that real though? I feel like most emerging managers, they write the checks in the first year and a half, 2 years, and then yeah, they get investor updates, they pass them along to LPs, but like they could go and get a job at big tech and sure. But it's still, even if it's a couple Hours a week for 10 years. Yeah, I guess that is kind of—

Look, it's also— it keeps you from doing other— it's just messy and complicated. And the reality is, again, like if you're earning 2 and 20 and you're never going to see the 20, right? Like the 2 ends up actually, you know, on a $50 million fund after you pay for actual things, you're doing fine. Like no one's crying, but like it's not like some great business, right? Like I think the only reason to raise a $50 million emerging manager fund is like Like to have enough card flips to prove that you can size up a bit. Now, I think the flip side is true too, which is I don't know how anyone makes money on a seed fund that's over $200 million. I just know the math doesn't work right. I think there's like this sweet spot of fund sizes that work. Too small, you know, the economics to make it work. Even if you have a banger, it's like not that important. And like too big, it's just like the law of big numbers. You're never going to produce an important fund right from a returns perspective. So look, what we do, seed investing, We're, I think, in the sweet spot, obviously, because why would I not think that? You know, we've made money. I'm very proud of that. I care about DPI, whatever. But here's the thing.

Sorry, sorry, sorry. We're laughing. We have to explain because you can't see it. But the chyron right now says seed investor. Don't become a seed investor.

Stay the fuck out. But then the reality is that, like, you know, it's not even from my perspective, it's not the best You do it because you love it, right? But if you just did the math, being an asset manager and earning 2% and just getting enough DPI to justify more 2% fees is for sure a more scalable business model, which is why most people do it.

Do you think part of why every emerging manager jumps into seed is just like they can't do growth? Because I feel like the skill set of being a growth investor is in some ways more repeatable. You get people that come out of investment banks and they have all the skills to underwrite a company that's at $1 billion. There's less risk. But at the same time, when you think about someone who's, you know, starting a new fund, if they're going out and raising a growth fund on fund 1, like, that just feels harder to marshal.

I think it's an LP question. It's like, who's going to give you LP-level dollars, right? And like, by the way, if you're, if you're going to a later-stage fund, you're trying to like model to like a guaranteed whatever it is.

Yeah.

2.5x or whatever. Why would you give it to the crazy kid, right? The crazy kid you give money for because they might be right.

Yeah, yeah, yeah, yeah. And so you want that seed bet. And then also I feel like a big part of the emerging manager dynamic is just like essentially scout funds. And there's a lot of like horse trading around like, yeah, we will do it, we will do the deal from our fund to fund.

We started that way like, you know, 10+ years ago and like that when there was— the market was much looser and it was a different market. Yeah. And it worked for us and we were able to scale up into being like a legit seed fund, you know, with legit dollars and legit institutional investors. I just think like, like most things, that path— all paths get super crowded, right? And so once the path is super crowded, it's just really hard to differentiate. It's really hard to make a good business out of it. And I do think like almost everyone's going to go away, right?

Not everyone. A seed investor. You heard it. You heard it here first, folks.

Here, last, last. I want your quick take. XAI's Portland data center fire. You think that's just an accident or you think Portland is doing Portland stuff?

That would be really funny. That'd be really funny. It's it's um God, have you guys ever read the science fiction parable of the sower?

No, great book, great book.

I'm just finishing it now, but there's a whole subplot where there's all these people who are addicted to this drug that makes them like think that fire is the greatest thing on earth, so they're just like setting fire to everything.

And like, if that's funny, it's it's I just looked it up. It's a post-apocalyptic story set in 2025.

Wow!

If you caught that when you read it.

Yeah, and like they're basically about people. like trying to walk north from LA to like north to Seattle to escape craziness. But the, um, yeah, so I don't know, if you told me that that drug was invented in Portland, wouldn't blow my mind.

Yeah, I think we got to get a Portland—

this is fantastic having you on. Thanks so much.

Always a pleasure.

Happy Friday.

Happy Friday.

Talk to you quickly.

Cheers.

Let me tell you about adquick.com. Out-of-home advertising made easy and measurable. Say goodbye to the headaches of out-of-home advertising. Only AdQuick combines technology, out-of-home expertise, and data to enable efficient, seamless ad buying across the globe. And we got Bobby.

They are simply the best.

Coming into the studio. Yep. I'm gonna do some VO3 generations for all of our partners. Get those in the mix, pull those up. I think it'll be fun. Get a little creative. We got Bobby coming into the studio. Welcome to the stream. How you doing?

Thank you for having me. Where are you?

Are you in Miami right now?

I am the last one standing in Miami.

Yes, let's give it up.

Yeah, I've seen some Miami. I love Miami.

Thank you very much.

Yeah, yeah, I love Miami. It's beautiful. Every time I get to go visit, it's always struck me as like the— it's like a classier version of Las Vegas for tech. And it actually worked really well where in every industry there's always like the CES conference that happens in Vegas and it's a little bit below Tech's, you know, prestige. And so if tech could assemble in Miami for events, that's great.

We gave it a real college try.

It was happening for a while, you know. There was HereticCon.

Yeah, I mean, it's like the best conference I've ever been to.

Exactly. And it was cool that you, you get people that come from New York and they're not just gonna go home on the— after the conference. They're gonna stay.

They might.

Same thing with SF, same thing with LA. So it was actually a feature that not everyone was there. I feel like if you throw a conference in LA Or SF, a lot— half the people are just gonna go home.

It was special for a moment.

I—

anyway, I gotta—

what's up?

I gotta dox Bobby. Oh yeah, because he pulled up to HereticCon in a Ferrari.

Let's go!

Remember I called it out?

We were walking.

Yeah, yeah, I remember.

He's actually just getting the buttons redone.

Oh really?

We were just talking about this. You have the button— you have the button issue?

Sticky buttons.

No, it's seriously, it's, it's like the worst thing to be in this magnificent machine. And then it's like, I don't know if somebody's sticky, like ate a hamburger.

You have a date and you, you, you, you, okay, great. I'll pick up my Ferrari. And then she tries to adjust the seat and it's sticky. It's like, she's like, this is disgusting.

Oh no, that's terrible.

Yeah. What were you doing in here? This is terrible. That's all fixed now.

That's all fixed now.

Okay.

That's good.

Yeah, that's good.

We're glad to hear it.

But yeah, give us the news, give us the update, give us a little introduction on yourself for those who might not know.

Yeah.

So I'm so glad you guys had me on today. We had a very big announcement today. So this is something I've been thinking about for 15 years, and we announced our new email client called Sunflower today.

Cool.

This is basically the—

thank you.

Thank you.

It is like basically the opposite of Inbox Zero.

Okay.

What does that mean? Love it.

Like, I don't think you should have to have an email client that makes you work for it, right? In other words, like you load up Inbox Zero, I don't care how many keyboard shortcuts, I don't care what you give me, but if I'm having to triage every single email that comes in, you know, keyboard shortcut this way, that way.

Yep.

From the Applebee's email. You know, no.

Yeah.

Yeah. You need an email client that actually works for you.

Okay.

So on our marketing website, we don't mention the word AI one time.

Huh.

Wow.

But this thing is entirely, this product would not be possible 5 years ago.

Okay.

So it's, you know, if you wanna be, if you think you need to be a superhero to use your inbox, There's a product for you. We're building a product for actual humans.

Bold.

And it launches, you know, the waitlist launches today, sunflower.me.

Yeah.

So, walk me through the product. The product is like—

I just looked at my phone before this because literally, we broke Slack today.

Like, apparently, there's a limit to how many notifications it can send you. It just keeps dinging, dinging, dinging.

That's great.

Amazing. And the product is already like— the product's real. You guys are using it, right? You're not just launching a waitlist. There's something under the hood.

We've been working on this for a year and a half.

I use it every single day myself. There's about a dozen people right now who have this. I'll give you guys early alpha access.

I'd love that.

Yeah.

So talk to me about the actual workflow. I imagine I still have an email address. People can still email me, but I imagine an LLM is scanning every email that comes in. Am I seeing the emails? Am I— I mean, I've used Gmail's Gemini features.

I—

one time, I randomly clicked it, and it just typed a response, and it was, like, kinda decent, but it's honestly just a lot of clutter in the UI right now. How are you thinking about that?

So you're kinda hot on the hunt here. I'll be honest.

Yeah.

Well, I've been thinking about this. I actually was thinking I should just get a— I should just get an LLM to summarize every email and just text it to me. And then I can just text back if I want to respond, and I just never look at my inbox ever again.

Apple tried.

Oh, it didn't work? Current Mail.app, it's not good.

Total dogshit.

Yeah, it's just so funny that email, like, the default state of email is like, here's stuff that's important, here's stuff that's not important, and then it's only ranked By when it hit your inbox, which is kind of silly because—

Email, the status quo of email is a to-do list filled out by other people.

Yep, totally.

And that's it, right? You shouldn't be beholden to that, right? Just because someone sends me an email doesn't mean— I get a lot of emails. Anyways, so, yeah, you were kind of close. We're going to reveal our hand more and more publicly. But today was like firing the starting gun. We're building in public now, so you're going to hear a lot more.

Boom.

Don't share your revenue. If it gets too high, people will copy you. We don't like going in public.

Based on the signups we had today, we are cash flow profitable if everyone converts.

How much of your time are you going to be spending here versus investing going forward?

Yeah.

That's a good question. I personally funded this company Uh, for the alpha, like, you know, I, I—

To be able to read people's emails, you mean? I'm kidding.

I can't, by the way, I can't read anyone's emails.

Yeah.

Yeah.

An exhaustive security review process with Google right now.

Yeah.

So no, there's no reading. You can sign up. You can sign up.

Just Google, just Sundar, just Sundar.

Sundar can read your emails, but not Bobby. Yeah. I bet, I bet he can actually. I bet, I bet that they're pretty locked Yeah. But yeah, I mean, I remember the Mailbox days and that launched. And one of the things that I loved was that once you got off the incredibly long waitlist, it basically tricked you into just archiving everything, which I thought was a great paradigm because you kind of declare email bankruptcy. You're not deleting these emails, so they're still there. And just that idea of, hey, You can archive things. I had never archived an email before, and I think a lot of people are in that boat where they have unread emails and they've read emails and they have a number that's like 10,000 next to their email app. What do you think? Funny story about that, please.

I was friends with Gentry when he made Mailbox. Yeah, and I worked at Facebook at the time. Yeah, and we're on this hike with my friend Bo, and literally it's like the Kalalau Trail in Hawaii. It's like a 2-day hike, like you're trekking it. The entire time he just talked about email. The entire time he talked about email and the fact that he was about to propose to his now wife. And I said, well, you're—

Great topics.

On this engagement ring.

Anyways, so I took a photo of him. Uh, it's a beautiful photo, you know, right at the end of the trail. And if you remember that app, You know, when you got to inbox zero, right? You saw this beautiful image, and I and he hated that app the whole time. It just it just launched. He was ranting to me the entire time about how much he hated mailbox. I was like, "It's actually a pretty good app." I'm friends with Gentry, et cetera, et cetera. But anyways, so when I got back from the hike, I sent Gentry an email, and I said. Hey, would you, would you guys put this, this image into the app? Like as the, you know, you're done, like inbox zero state. And so, and then I took a screenshot and I sent it to him. I said, you're in the app now. You're in the app that you kind of hate.

That you despise. That's hilarious.

And he took it in good faith. It was great.

Yeah.

We're not about inbox zero. I think inbox zero is a flawed concept. I think like, you know, we're—

It's funny, I want you to do this for texts. Right now, I have 3,873 unread texts. And I have that because I don't feel an obligation, like just because somebody had my number at some point. And like, I really try to respond to the stuff that's important and pressing, but I'm not gonna like get home from work and be like, oh, I gotta respond to this person Instead of hanging out with my kids, right? Like, it's, it's not—

No, of course not. Everyone feels entitled to your time. Yeah, right. You know, look, I'm an investor. I get the same emails probably we all do, right? Like about 20 a day. And they're all like drip auto campaign follow-up. So it's like they send you a cold pitch email and then you get, you get the email, then you get the email, and then, and then And every single successive email tries to guilt you into actually replying, like start using more and more emotionally manipulative tactics. And it's like, no, no, no, just because you know my email address does not entitle you to my time.

Yeah, I think that's right.

What do you think about—

are you going to tag? Are you going to identify emails that are being dripped versus, you know, are Artisanal, organic, farm-to-table emails.

We're working on that. You know what we're also working on? Again, you know there's a funny Steve Jobs quote: Isn't it funny a ship that leaks from the top?

Hmm. But here you go.

That's great.

You know, you know, like email trackers. You know, like obviously Superhuman does this.

Yep, yep, yep.

I'm like, you know, you see you've seen it.

Yep.

We both allow you to block inbound trackers and we'll also let you send your own.

Nice.

So our thing is like, we are just so 100% focused on the individual user. So in other words, like if you want to block these trackers, perfect, we'll let you do that. And then you can send your, you can send a tracker of your own.

I like having those trackers. I like letting the SDR know I read this 10 times and I'm still not responding.

Yes.

Yeah.

That, that's, that's also a deal breaker. That's, that's the feature you should build is a feature to open and close the email.

That's a better feature. Yeah.

Yeah.

It just keeps pinging the pixel. So then the SDR is like, this person, they're reading it for hours every day. What? But they haven't responded. What's going on?

You just DDoS their tracking pixel.

What, what, what is your take on Eric Mikovsky, founder of Pebble. He started this company Beeper, eventually sold it to Automattic. And the whole idea was get into the iMessage world, create one unified inbox for all the different messages. I think he had a knockout drag-out fight with Apple because he was reverse engineering some of the APIs. Obviously, there's changes on in big tech around antitrust, and it maybe now is the time to put pressure on that. Is there a world where we could see text and email kind of unify at some point? What's your view on kind of the long term here with big tech?

I mean, look, we we have a we have a long-term strategy. Mm-hmm. I'm not going to come on your podcast and just spill all the beans.

Spell spell spell spell spell spell spell spell spell spell spell spell spell. Activate golden retriever mode.

What was that?

Activate. What did I sign up for? Golden retriever mode where you're unfriendly and dumb.

Yeah, yeah. Golden retriever would just tell the entire roadmap. Golden retriever would just tell everyone. No, no, no, no. You can come on again and spill every drop.

I went to class at one of your companies and I passed the other one.

Anyway, yeah, future of text email.

So, I'm mostly concerned about email. I think email It's like what's old is new again, right? And so if I, again, if I were a ship that's spilled from the top, here's what you have to, here's what I have to say. Just like Apple built iMessage on top of SMS, I think there's a layer to be built on top of email. That's all I'm gonna tease.

Give us more. Anyway. Yeah.

No, no, no.

I think it's, I think that's an interesting framework.

So, I don't want to own all communication. Like, I don't want to, you know, pull it onto one place. I just want to clean up the mess that is email.

Okay.

Yeah, it is an interesting time, right? Because like AI is transforming everything, but yet I feel pretty confident that I will have an email address that I have to use in 15 years. And like, that sounds kind of crazy and silly, but at the same time, It's not going away. Fax machines. We talked with TJ yesterday about how he was spending 30% of their dev resources or something like that on fax machines, right?

Crazy.

When I worked at Facebook, we had— we launched as a joke, just the TechCrunch network only, we launched a feature called Fax This Photo.

And they covered it.

Wow.

No way.

Yeah, yeah, it was literally launched just to troll them. Oh yeah, you can Google this story, like TechCrunch Facebook faxed this photo. My engineering buddy Evan, we were launching all these things one day.

Fax your photos, not 2009.

Wow.

Yeah, there you go.

That's amazing. Okay, so Facebook punked us. This isn't really going live for everyone. That's just for us.

They tried to like pretend like they were in on the joke, but no, they weren't.

That's very funny.

Got them. By the way, I'm so— Didn't know the joke either. And so, this guy Blake Ross, he had to run upstairs like in a frantic rush saying, guys, guys, guys, guys, it's just a joke. It's just a joke.

Yeah.

Full-stack verticalized MOG.

Love it.

It's amazing. Well, thank you so much for coming in, Bobby.

Bobby, this was super fun. Congrats on the launch. I'm excited to try the product and come back on as you have more news to share.

Amazing.

sunflower.me, if I can get a plug in.

For sure.

Let's do it.

Go check it out.

We'll talk to you there now. See you guys.

And if you're trying to visit Miami, you got to head over to wander.com.

Find your happy place.

Find your happy place. Book a wander with inspiring views, hotel-grade amenities, dreamy beds, top-tier cleaning, and 24/7 concierge service. It's a vacation home, but better, folks. Get on Wander. And we got Oren Hoffman coming in the studio. He is here. So welcome to the stream, Oren. How you doing?

What's going on?

I'm doing great. Happy to be here. Very excited.

Great to finally have you on.

Yeah.

Probably should have done this a long time ago.

We had a brief phone call, I think, a couple of years ago. Good to reconnect. What's the latest in your world?

Well, things are great.

We've got a couple of different things. We run a weird holding company where we own a bunch of data companies, start different data companies. And then we're also at Flex Capital where we do a lot of seed stage investing. We did 20 deals last quarter.

Wow.

Our goal is to do about 100 per year.

That's amazing. Yeah, we were kind of struggling to find what your title should be, so we just put founder and investor because you got— you wear a lot of hats.

Yeah, that's good. I think you got like Sam Lessin on today. I'm like an aspiring Sam Lessin.

Okay, okay, that's great, that's great.

How are you on the slopes? So you're a good skier?

No, I'm not aspiring. At that stage, yeah. I'm only aspiring on certain things. He's got like 20 other dimensions I'll never catch up to.

He plays a lot of tennis. He yaps a lot, but yeah.

He runs like 3-minute miles.

Yeah.

3-minute miles?

Okay. I haven't talked about running.

On the data side of your business, was that an AI bet that you made a long time ago? Did you get lucky? Did you have incredible foresight?

I think I had the wrong bet. And so, I think on the data business, I think we had believed that these companies that sell data, like data as the ingredient, not just like analysis on top of the data, the ingredient, we thought that these companies would become like way more valuable because we thought the number of buyers of data would go up significantly.

Mm-hmm.

So, if you think like, you know, people, this is 10 years ago, people made— oh, there are, uh, maybe 50 hedge funds that buy data. Today, significantly, there's 11,000 hedge funds. The market's going to go from 50 to 500. Um, I think the market went from 50 to like 58, um, over the last 10 years. So it really didn't go up. Retailers— there were maybe 20 retailers that bought a lot of data, um, 10 years ago.

How many out of your, out of your This will be tough to remember specifics, but a lot of seed-stage companies will be like, oh, well, we're going to generate this data and we're going to sell it eventually and it's going to be valuable. And then you press them on it and it's like, well, hedge funds will buy it. And then it's like, okay, are you confident that those 58 hedge funds are— have you seen any of your—

They're a terrible market. It's a very small market. And really, most of them are— even the biggest hedge funds in the world like Bridgewater, Like, the amount of data they buy is minuscule compared to the AUM. It's like, it's basically zero.

Yeah.

Um, and is that just because they spend more on like lunch? Yeah. Are they getting data from other sources, like more public sources? Are they scraping the internet, or are they just not using data-driven algorithms?

I mean, they have some data. They have data that you could put in an Excel file and stuff like that. And these are not like— these are smart people who are thinking about quote-unquote data, but when you actually think of like a data business that's selling data, proprietary data, different types of data, and usually data that's like larger than you could like put in an Excel file, most funds are not doing it. Most— they're really, really— if you think of like real estate.

Mm-hmm.

So, when we were starting, like the number of real estate investors that were using data was zero. And today, It's Blackstone. It's like one. It's gone from zero to one. Real estate is a pretty big asset class. Now, they're using some data. So people are using still some data. But really, like, we're talking about like real alternative data, really have a very sophisticated system to be able to ingest it and use it. It's very, very, very small.

Is that driven by the fact that maybe it's almost like we've been thinking a lot about Google I/O and v03 and Google's advantage in video generation, particularly because they own YouTube. And YouTube feels like an incredibly valuable data source.

Correct.

I agree with that. And it's almost— but the whole, like, data is the new oil, it's almost like, no, data is like a Rembrandt painting that there's only one of. And so Google doesn't want to sell that data. Like, Google wants to keep that, right? Yeah, they're definitely not going to sell it. Yeah. And so, like, yes, the data market would be bigger if all of these assets actually transacted and were fungible like oil, but they're not. They're super proprietary.

And now if you have a brand, your data is more valuable.

Sure.

So if you, if you've got something like Reddit and everyone knows Reddit, they understand what people are talking about on Reddit, and they say, okay, we're having all these like interesting conversations, they sell that to Google for $60 million or something to train their LLMs. And but if you, if you had just like lots of people having interesting conversations But you weren't called Reddit.

Yeah.

Um, my guess is instead of $60 million, you might get $10 million or $5 million or something. Like, the brand is actually the 10x thing of why people want to buy it as well.

Yeah. What about just, uh, creating data for the purposes of artificial intelligence, not pulling data from other sources and trying to go find a round peg in a square hole with selling into a hedge fund? More like Like, there is demand for robotics data right now, and we are going to go get a bunch of robots and generate a bunch of data.

Yeah, I like that. Yeah. I mean, obviously, like, Scale AI is a great company, right? So they're doing that. They're actually going and building those types of data. We just— we're investing in a company doing what you're saying with the robots.

Sure.

I think those types of things are good, but it's not always just for the AI. Like, there's other types of buyers, because if you just are selling to, like, AI core model companies, You're, you're talking maximum of a dozen buyers. That's not a great market.

Um, and yeah, he went from 58 to— you went from 58 to 12.

Yeah, exactly. So do you just want to sell to OpenAI, Anthropic, Google, and Facebook, like, and maybe a couple of others? Like, I don't know, that doesn't seem like a great business long term either.

Yeah.

And if the deal, the first deal that you do is $100 million, what What's the deal size on the next one?

Correct.

Are you gonna create $100 million worth more data that you can sell to them? Is it even that valuable? Anyways, wanted to have you on specifically to talk about a post that you had yesterday that went pretty viral. You said that any VC that makes you pay for their lawyers is not founder-friendly. Founders barely affording rent should not be footing legal bills. VCs with private jets, and yet this is standard. You extrapolate on this, but you're writing 20 checks a quarter, maybe more. I'm sure that almost every single one of the companies you back ends up having to pay some VC's lawyer bill, maybe in the next round. But I would love for you to break down the post and what inspired it.

Yeah. So, for those people who don't know, it's standard in a term sheet, somewhere in the term sheet, it says, usually it says the company must pay up to X dollars of the venture capitalist legal fees, and that X can be negotiated, and it can be as low as $10,000, and I've seen it as high as $300,000 for more complicated deals and stuff like that. And it's there, and it just— it seems odd for a whole bunch of reasons. First, it's like there may be many different investors, but you're only paying the lead investors types of thing. Second is that, um, uh, you know, why are they, you know, why are they actually having the company pay? It's, it's like a little bit of a backdoor way to get your fees paid. Um, and then there's like, there's like a more complicated argument as well, which is I don't think this is LP-friendly. A lot of, a lot of VCs will say this is LP-friendly, um, because now I don't have to like—

Yeah, wouldn't the person paying presumably You can pass it— I mean, that the VC could pass the fees on to their LPs. Correct.

So they could pass it on to their LPs. And this is a backdoor way of doing that without actually telling the LPs that you passed it on to the LPs.

By taxing the company.

It's taxing the company, but it's even. The LP isn't aware of it. Whereas if you actually— normally, if you If you use Tegus or something and you pass that on to your LP, your LP sees the bill and they're like, why are you spending $50,000 on Tegus? Like, you should be spending less. And they can have a conversation. Or if you're like, if you're having air travel, they can understand that as well.

Wait, wait, wait. Can you give me more clarity around like the idea of passing fees on?

So like the real, the real fees. So VCs have like 2 and 20, right? But then there's certain fees that you can pass back that it gets it closer to even 3%. You could get it up to like 2.5%, 3%, 4%. And that could even be like when a VC pays for lunch with a founder, you can pass that on, correct?

Interesting.

Yeah.

And every VC has a different model.

Different structure.

When we go—

I always thought it would be like there's 2% fees and then you got to do whatever you want with that. If you need a private jet, that's coming out of the 2%. If you need to pay salaries, if you need to pay for TIGAs, If you need to buy lunch, like it's all coming out of the 2%. But you're saying it can be passed on.

The true loaded fees can be much higher than 2%.

Interesting.

Yeah.

Like at Flex Capital, we try to almost do everything in the 2%. So if we go to lunch with them, we take it out of our own management fee, which means we get less compensation because that— of course, most VCs want to protect that 2% that goes directly to them, right? So we get less compensation, but we think it's more LP friendly. And then we'll, you know, there might be certain things Like your fund audit might be done to the— so, you have to decide, okay, what's actually done to the fund versus what's done to the management company? So, we err more to the management company. Every VC will do it different on how they do it, but some can be like— but at least regardless, at least generally when they're passing fees, at least the LPs do see it.

Yeah.

And then they can have a conversation like, hey, why are you spending all this money with lunches? is, to me, why am I paying for your lunch to go to Spago or something? So whereas with the, with the, with the, uh, with the, um, uh, legal fees, they don't know. They have no— no, the LP has no way of accounting that.

Right. What about like general pressure to bring down the cost of startup legal fees at the Series A level? Uh, Justin Kahn was working on a project with Atrium to try and automate the, the Series A.

Before you can even get there, there's— I think Ahmad had a good response to your post from Mercury saying that like he just basically tells the lawyers, we're going to cap it at this and you agree up front, and then the lawyers are super motivated. But that's still—

That's— and that, by the way, that's— Ahmad's amazing, and that's, that's definitely step one. Like, you got to negotiate that cap. Maybe you can't negotiate all the way down to zero, which is what I would like to see happen more. But you've got to negotiate it. My guess is also, it also depends on how— the higher the cap, the longer it will be to close your round. So, you know, as most people know, you get—

Shouldn't it be the other way around?

The higher—

if it's a high cap, the lawyers are just gonna be like, yeah, this is gonna take 6 months.

Because it should be.

It should be. I mean, search price—

so I'll pay you $300K to close it this weekend. Or 50K, and yeah, you can take a month.

I can basically tell you like here's how you close your round. It's going to be 15 days plus one day for every $2,000 that's in that.

Oh my God!

That will. I can guarantee you that that will that will that will be exactly what it is for every single round that is in there.

So backwards.

Shouldn't shouldn't one one defense of of startups eating the cost is that you know if you're if you have an emerging manager with a $20 million fund and they're barely You know, paying themselves a dollar in salary. And if they want to lead a round that ends up getting priced, it could get expensive. But your argument is still like, okay, well, LPs are still eating that cost.

Yeah. I mean, look, it can be negotiated and maybe in some cases it could make sense that's in there. But if you're— why are you doing something so complicated? I mean, YC created the SAFE. The SAFE doesn't have any legal costs, right? Really. Um, you, you can actually use a pretty boilerplate, uh, uh, thing. You, you knew most of these terms you should be negotiating in the term sheet anyway. So going from term sheet to close, which is where all the legal costs come in, from term sheet to close, like, why is that expensive anyway? It's cuz probably you're not managing the lawyers. The lawyers have no incentive to, to keep the costs low because they know what the cap is.

Mm-hmm.

If the cap says $50K, I guarantee you, you're getting a bill for no less than $49K. Like, in the history of the world, I doubt it has almost ever come in less than $49K for a cap of $50K. Like, how do they automatically always hit the cap?

It's perfect.

It's perfect.

They're filling the space.

They're built different. The other thing as an LP, what you don't want to pay the fees and not get the ownership. is the other thing, right? It's like if you're just getting past the costs and you're eating that, but you're not getting the incremental dollars deployed into the company or the incremental ownership, is it—

does it—

I mean, I guess where I'd want to go with this is, do you have conviction or any excitement around tools that can be Like AI tools specifically that can be introduced into the process, like basically that term sheet to close period to just make that more efficient where we could say, okay.

In most cases, but first of all, like we just did a, we were just involved in a company that did term sheet to close in 6 days. Like it's not that hard, especially in the early stages of a company. Like how much diligence do you need to do? You need to— and look, the company did a good job. They got all their stuff in a data room. They did all the things that they were supposed to do. Then as the venture capitalist, okay, well, you've gotta, you've gotta somehow read it, read through it. Maybe you can use AI to read through some of it. You gotta go check it. You have to make sure that the, the bank account is legit and all these other types of things that isn't fraudulent. But it shouldn't take that much time.

Yeah.

The main reason it takes a really long time It's just the back and forth. You put a redline in, I send it to you, then you don't have time to look at it that day. It takes you 3 days, then you send it to me. Then I, it's like, if we actually all got in a room, that's what they did. So they got all in a room on day 6.

That's cool.

And they basically put like a 4-hour block and they said, we're gonna just go through every single issue right here. And they were able to iterate on it just live. And then you would, you, you would, you would put it on mute, you would talk to your lawyer to go back. Mm-hmm. It just got done. It's so much easier. And obviously, even M&A agreements, like, you should be able to get those done so much faster. And actually, those often do get done faster.

Yeah.

Like, sometimes you can do an entire M&A, um, uh, from term sheet to close faster than you can do a VC financing. Many M&As go faster than VC because everyone's just motivated to really work on it and put in the time to make it happen.

Yeah.

Well, thank you so much for stopping by.

Come back on again soon.

Sorry, I love it. Invite me anytime.

Yeah, this is great.

We'll make it happen. Yeah, great hanging.

Talk to you soon.

Cheers.

Bye.

Yeah, we have some breaking news. The first nuclear executive order has dropped. I'm going to read here from one callout that people are celebrating. To maximize the speed and scale of new nuclear capacity, the Department of Energy shall prioritize work with the nuclear energy industry to facilitate 5 gigawatts of power uprates to existing nuclear reactors and 10 new large reactors with complete designs under construction by 2030. This is exactly what we were asking for with let's copy paste Diablo Canyon. We have Doug Bernauer from Radiant Nuclear in the studio. We're going to bring him in and get his breakdown on it because he's obviously been working in this industry for years. And should be able to give us an update on what's happening. Thank you so much for joining the show, Doug. Been too long since I saw you. I think I saw you in DC last, but should be an exciting day. But can you give us your read and analysis on what's happening?

Yeah, it's unbelievably exciting. There's a whole lot of text. I had these fact sheets that came out, I think went to the media on all these executive orders. It's unbelievably exciting, but it's all coming in like right now. I think the actual official documents just got posted Only minutes ago, so I haven't read.

So you're an expert. You're an expert is what you're saying.

Well, we really put you on the spot. But I mean, can you talk to me about a little bit of the history? What— I mean, first introduce yourself, what the company does, and then maybe we can build up to some of the maybe problems or areas for improvement that the industry has been asking for, and then we'll kind of dig into What's happening today?

Yeah, thanks. So I'm the CEO of Radiance, a nuclear portable microreactor company. We're focused on mass production of 1-megawatt reactors. We'd like to see 50 of those per year, and they'd come off the factory line and then go out to the customer wherever they are, run for 5 years, and then come back and be refueled. So it's a very unique sort of model. And my background before that, I worked at SpaceX for 12 years, worked on the first rocket with legs, amongst other really cool stuff for Elon. but eventually focused on nuclear. And it's a really unique model that we've been trying to work. You know, a normal reactor is about 1,000 megawatts. The thing we're working on is 1 megawatt. It's got to be road transportable. We're trying to make the nuclear power that people want, because the problem that we see with why we don't have all this nuclear technology today is really that there's not as many customers. But that has all completely turned around, I don't know, in the past maybe just 2 years, right?

Yeah.

With all these announcements of the big data center players coming in to buy nuclear, to restart old plants, to build new ones. And we've actually been fighting for a lot of regulatory reforms that, that we see as probably being necessary for our particular model.

Yeah.

Where you've got a really a factory that makes reactors, where you have assembly and you don't have any construction. And if you read the rules that are 50 years old, you get— you hear about construction a whole lot.

Yeah.

And so it's not really focused on or talking about the right sort of thing.

So yeah, when we last spoke, you were working on the helium loop going to test at a dome in Idaho. How are things going? What have been the most recent updates for Radiant?

Yeah, there's some unbelievable updates. Just a month ago, we were announced as one of just 5 companies who will get access to fuel from the Department of Energy, something we've been working on for a very long time. It's unbelievably exciting. When I started the company back in 2020, we said we would do a critical test with a reactor at full scale in 2026. We are on target to do that. And really, I mean, because of that announcement and the support that we're getting from federal government, another change just recently, you know, we've been working through a process they have at the national labs. We're working with Idaho National Laboratory. And a fun context setter here, they've tested actually 52 reactors in their history.

Wow.

Although the last of which was in 1977. So it's been a while, and we have a kind of old process, and they are aware of it.

Anybody Was there anybody that was a part of that last test that's still there, or is it all just kind of lore at this point?

It is sort of lore. It is sort of lore for the new reactors, but there definitely are staff who are there who, you know, there are the Advanced Test Reactor, the ATR reactors, where they test all the Navy fuel. That's been operational for a very long time. You can go tour it today, still operating. So there are definitely staff there who are very familiar with reactor operations and refueling. They also have a transient pulse test reactor, which is pretty amazing. It actually has an original core from the 1950s still running and operating. I forget what the numbers are, but it pulses into the several gigawatts range. So there's some expertise there, but certainly there are not people there from the early 1970s anymore.

Okay. I have the Wall Street Journal article pulled up. I want to read some of the key points and just get your reaction. So the high level is that Trump signed executive orders to boost nuclear power industry, citing the need to overhaul regulations and fast-track licenses. A lot of this is driven by tech companies like Amazon and Google who are driving demand for nuclear power to support AI systems and data centers. And there's an interesting wrinkle there where a lot of the hyperscalers made very aggressive ESG targets and climate pledges before they knew that they were going to need 50 gigawatts of capacity. And so now they're really, really pushing for clean energy. The executive order aims to shorten approval times for new reactors, but critics worry about the impact of safety. Now, I want to talk to you about that balance between speed and time to market and safety. I wouldn't trust myself to design a nuclear reactor and get it approved in a day, but it feels like we haven't had a new reactor design approved in way too long. And so we're probably on the too slow side of the curve. But where should we be? What is a reasonable amount of time to actually approve a new reactor design, in your opinion?

Yeah, I mean, probably on the shortest scale, it's got to be something like 6 months. Like if I use that context I said earlier, 52 reactors up till just 1977, nuclear technology only existing since the mid-'50s, that means they were doing more than 2 per year.

Yeah. Yes. Let's get back to that standard, right? Walk us through what—

Absolutely.

Just as a citizen, not as an entrepreneur or founder or executive, as a citizen, what type of tests do you actually think are the most valuable? Is this, I need a physicist to run all the numbers in a spreadsheet and run simulations? Do we need to just fire this up in a place where even if it explodes, we've seen that it didn't explode, and so we've done real-world testing? Is it a balance of those? What kind of testing do you think is best that can be executed at speed?

Yeah, well, it's a great question. The best is immediate testing and incremental testing.

Yeah.

And there's no reason that you necessarily need to go slower. You can regulate along with the speed with which you can do the design, the analysis, the procurement, the assembly of a reactor. If a company is willing to spend capital to take that financial risk, you know, the goal is don't put fuel in unless you get an approval.

Yeah.

But there should be really zero barriers up until that point, because there's no safety risk.

Yeah.

But then when you get to that point of like, okay, now there is risk, we are going to load fuel in, you do want someone to go and check your numbers, and you want them to dig deeply and thoroughly into what your reactor is and does, and what the plan is. But the fact of the matter is, when you load fuel, it's not anywhere near critical. You can make a— you can look at subcritical multiplication factor.

Mm-hmm.

That will trigger little sensors that are effectively— it's, you know, something that sounds like a Geiger counter. We use fancier things today. We use fission chambers. We use boron-lined proportional counters. You can do the analysis to show that you will get many, many counts per second, even with a very small amount of fuel loaded. Like, let's say you construct 1/6 of your core. You can already validate models. And yet you are ridiculously far away from being able to go critical.

Interesting.

They haven't even assembled the whole system, right?

Yeah. The FDA has similar approval timelines for new pharmaceutical drugs, but the reason that it takes a long time to approve a new pharmaceutical drug in America, it makes more sense to me because Because if I'm going to take a drug, I kind of want to know, hey, is it going to have an effect on me in 30 years? So maybe I want to see a mouse model or a monkey model or a dog model or even human testing over a long period of time. And sure, there's some acceleration there. We don't need to wait a full lifetime to approve a new drug, but there is an element of time. Is there anything that's comparable to that in nuclear where the behavior of a system over a 2-year time period is different than a behavior of a system over a 2-hour period.

Yeah, I think the most similar thing would be the effect of neutron fluence inside of the core. So if you hit some parts of your system with neutrons, they will generally swell up. Metallic parts swell up and their thermal conductivity will usually go down, their density goes down, but the physical shape of them changes.

Sure.

So you might have to test that in some special way to know what what a 10-year lifespan looks like, right?

Yeah, but a lot of these materials have been tested, and there are these giant data handbooks that— it's very predictable. So there's like the Nuclear Systems Materials Handbook, which is like put together in the 1970s, actually just released finally through this lengthy process. We had a ton of help. We went and recovered this great national asset, and it's now available for all reactor developers.

That's amazing.

Yeah. So they're pretty predictable effects. So there's not— I would say there's really Other than the effects of neutron fluence, there's nothing really that challenging. We plan to test right next year in the dome. That is a hermetic structure, totally sealed with its own radionuclide detection in it. And so you can partially fuel a core and you can do it in a hermetically sealed chamber at a facility where it's surrounded by scientists, right? And experimental hot cells and other test facilities. That would allow you to see what any problem is, solve any problem. But we are using all well-known standard materials.

Got it.

Makes sense. Uh, were you— is it, uh, funny to you that the, the news of Taiwan decommissioning their reactors hitting the same week that we're saying that, uh, we need more? Uh, or, or is there something about Taiwan's— as it— as an island? I, I'd read something about there being a bunch of of, um, you know, enough earthquake activity in the area that like there was some potential reasoning around that. But then I— we also had someone else on who said we, that we have solutions for that at this point. It's not a risk that should require shutting it down entirely.

I don't know that these things are linked, actually. I think I'm, I'm behind on the, the Taiwan reactor news. Um, those might have just been around for a long time, might be coincidental.

Yeah, it's not.

No, no, I'm not implying that they're linked. I was saying more that it's, it's, it is kind of ironic in the sense that, like, you know, we have one, one country saying we're shutting these things down meanwhile, and they're less, far less energy independent than Germany kind of doing the same thing.

It feels like some, like some countries are following the American nuclear playbook from 2 decades ago and maybe they should be adopting the playbook from today and they need—

Well, we just announced it today and yeah, so hopefully—

How much, like how monumental How fundamental is this for you? Were you betting the company in some way on eventually getting an administration that would introduce an EO and try to bring about policy around this?

I think, yeah, in a lot of ways, absolutely. If you're working on something innovative, there's going to be regulatory gray areas. You have to know about those gray areas and manage the direction they're going in to make sure that the vision that you have is the way that the administration or the regulatory agencies go, so that you're not decoupled from reality. But you do have impact on that. And you actually, you know, you can't write down rules ahead of time for something that's not invented yet.

Mm-hmm.

Right? So, but you do always take some risk in doing that. But I think it's actually pretty beautiful. You lay out a vision, go like, imagine you have like a bunch of reactors. They're all built identical to one another. So they're super reliable. You deploy a whole fleet of them. They all stream data back continuously. We're in the modern world, we're in the information age. Why can't all that data just stream to the regulator? Why can't it be completely modernized? And we've been talking about that for a while, and I think that has led to now— that along with other things people have said have led to these sort of events where the administration goes, okay, we're gonna just— we're gonna actually go and support this.

Yeah, right. Last question from my side. Can you talk a little bit about How you see the market playing out. Obviously, there's some news about where we might be getting really big nuclear reactors at the 1-gigawatt scale. You're building at the 1-megawatt scale. Is there going to be a 10-megawatt company, a 100-megawatt company? Is it a smoother curve?

So they're called the same company and you just—

Yeah, or maybe they're bundled or broken down or scaled up or scaled down. Like, how will this play out? And, and who will do what, I guess?

Yeah, well, as a consumer, what you want is for there to be 2 or more companies at each scale.

Yeah, right.

And yes, there will be something at the portable microreactor scale, maybe 2 companies there at least, and maybe that's 1 megawatt and smaller. If you are willing to put a reactor in the ground somewhere, and pull the fuel out on that site and put it in a system, you can make a bigger reactor. I call it a microreactor, 10-megawatt scale. So you want 2 companies there, you want 2 at the 100-megawatt, you want 2 or more at the gigawatt also. Because they're different areas that need these amounts of power. So if you think about— and we never think about these places, they're remote places in the world, like in Alaska, you have over 150 disconnected microreactor locations, or microgrid, sorry, locations that could use reactors. Canada has over 200 of these sort of areas. And these are coastal— look at those land areas on the map. They're massive. They have a need for heat and for power. They're extremely isolated. There isn't an actual grid. So you need a small system, right, on those types of regions. And if you put in a 1-gigawatt reactor somewhere, you had better have a lot of big power lines to move that power to enough customers to use that Right. So on the 2, like, extreme ends of the scale, there's like pretty obvious use cases. And then in the middle, it's like if you don't want to wait years to upgrade the grid, or it would be very expensive, like million dollar a mile or more upgrades to power lines, then you might go, well, hey, we have this region where we're going to use 10 megawatts. We can put a 10 megawatt reactor. That's economical for us.

Mm-hmm.

Right. Without overcomplicating it or having to add power lines, uh, extending across the Awesome.

Well, thank you so much for popping on. We'd love to have you back again and go even deeper.

Congratulations on the overnight success. I know the job's not finished, but I like, I like this for you guys.

Yeah, this is great. It's great news.

Yeah, it's really exciting. I mean, one of the coolest things, they, they asked to reform the process that we're using at national laboratories to test reactors. That's going to be extremely critical to us staying on our schedule. We will achieve Going critical next year because of a lot of things happening today.

That's great news. Thank you. You're the man for joining, Doug. We'll talk to you soon.

Amazing milestone.

Cheers. Good luck. Talk to you soon. I wanted to pull up. We're going to stay on nuclear for a little bit. We're going long. We want to pull up Scott Nolan, my former colleague at Founders Fund and the CEO of General Matter, a nuclear fuel refinement company, was in the White House. I'm John Nolan, CEO of General Matter. We're an American enrichment company trying to bring back the U.S.'s lead in producing nuclear fuel. So just like car engines need fuel, nuclear reactors need fuel. Right now, the U.S. is completely dependent on other countries to make the key step of enrichment in this field. And these executive orders are going to pave the way for the U.S. to regain its lead. So we really appreciate it.

Will you be doing the AI plants?

Because we have a lot of them going up now. Or soon going up, and they need tremendous electricity. Are you going to be involved in many of these plans?

Yes.

Will—

Scott Nolan, CEO of General Electric. Here we go. Let's hear it for Scott Nolan. In the White House. Color temperature a little bit off on that video, but otherwise fantastic.

Yeah.

Well, congrats to Scott. I mean, what—

We have Saya from Valor in the waiting room.

We'll bring him in.

Let's bring him in.

Welcome to the stream.

Well, he's also—

he's been in the Capitol now. Yeah, I think he was over there. Today in DC. Let's bring him in. Uh, and he is building at the 10-megawatt scale. And so everyone's got— everyone's playing in the different market.

Gotta play. There he is.

Thanks so much for calling in. Can you give us the breakdown? How you doing? Doing really well.

Thank you so much for having me on, guys. I'm, uh, I'm actually just coming back from going live on a, a little upstart called Bloomberg TV. So, you know, it'll take a while for them to catch up to your stature.

Yeah, yeah, it's kind of like a feeder.

It's like kind of like a feeder Yeah, feeder system.

Can you go horizontal with your phone?

Yeah, yeah, sure.

There you go.

Yeah, that's right.

A little, a little feeder network for the Technology Brothers. So yeah, great to be in the temple of technology today.

Yeah, it's good to have you. Break it down for us. We read kind of the highlights, but what were the key, the key pieces of the EO in your opinion?

Yeah, listen, this is a total rewrite of the regulatory system in the United States for nuclear energy. Nuclear grew up in the US with a total dominance of nuclear power in terms of US strategy, right? So we had the only nuclear reactors in the world for a while. We piloted essentially every nuclear reactor architecture that there is, and we wanted to protect that edge and protect that advantage. And so what we did is we built these high regulatory walls around the nuclear environment, hoping that nuclear wouldn't spread around the world. We wanted to protect this advantage. This is a natural instinct. I think it was a good instinct at the time. But the problem is that over time, our competitors or geopolitical rivals built nuclear anyway. And where we are now is that these walls that we built to protect our advantage in the United States actually eroded our advantage. And we ended up building a large wall around an empire of dirt. And so today, this is about bringing those barriers back down, allowing American entrepreneurs to build nuclear energy again. There's a couple really important things announced here. One is revitalizing the Department of Energy. So the Department of Energy was created to be a nuclear test agency. Not a lot of people realize this, but the DOE, we kind of imagine it to be this broad-based energy agency, and it is, but it was actually created to be a nuclear reactor test agency. And since it was created, it's only done that one time. And so this is about revitalizing that. And actually, President Trump President Trump has given a strong commission to the nuclear industry. He wants 3 test reactors critical on US soil by July 4th, 2026, America's 250th birthday. And just a few minutes ago, we announced with the governor of Utah for the first time that we're partnering with the governor to, you know, full charge, full steam at hitting that goal and turning on a reactor by July 4th, 2026, at the San Rafael Energy Test Center in Utah. So that's what we announced today.

Congratulations. That's amazing news.

Good luck.

Overnight success. So yeah, I mean, it seems like with any nuclear project, regulatory is always the main risk, the main rate-limiting factor. With regulatory out of the picture, is this more of an engineering challenge now? Is it a manufacturing challenge? Like, how do you weight the different challenges ahead for you to hit that deadline?

That's absolutely right. Listen, you know, nuclear is a technology that we've been exploring for 70 years now. We've done an enormous amount of physics around this. We've done an enormous amount of research. The thing that has stood in the way is one company deciding to be the SpaceX of nuclear, deciding to own nuclear energy, full verticalization from the design of reactors to construction, to manufacturing, to deployment, to operation. That's what Valor Atomics is attempting to do. There hasn't been a Ford of nuclear energy yet. There hasn't been a Tesla of nuclear energy yet. There hasn't been a SpaceX. Valor Atomics is intending to be that company, and regulation has absolutely been the long pole in that tent. So this executive order is incredibly important. You know, I think this is really going to set the tone for the next 100 years of energy dominance. If we're going to win on AI, on manufacturing, on supply chain, we're going to do it with a ton of cheap energy.

Talk about the first product, uh, 10 megawatts, is that correct?

25-megawatt electric is our commercial model.

So why'd you sell Valor Atomics?

Yeah, we've gone out and we've really hit an ambitious milestone. I founded this company about 17 months ago. We were intending to go out and build our first prototype reactor in 18 months. We finished it in 16 months. This is a test reactor sitting in our Los Angeles facility today. We've operated above temperature, above pressure, not with uranium, not splitting atoms yet, but with electrical simulation. And really what we've proved is that it's possible to build a nuclear reactor in under 18 months. Now that we've done that, we go and actually build it again in Utah and another one in the Philippines, and we actually load them with uranium for the first time, turn them on. After that, we go and build our commercial model, which is this 25-megawatt unit, and build thousands of them around the world.

Very cool. Jordy, anything else?

Sounds pretty simple.

Just draw the rest of the owl, boys. Yeah, just draw the rest of the owl.

Yeah, we make thousands of nuclear reactors. We make trillions of dollars. I'm very excited. It's a good day in energy.

Yeah, I mean, it's fantastic. We were just talking with Doug from Radiant, and in many ways, if you started a nuclear company at any point in history— It'd be rough. You were betting on activity like we're seeing today and action. And so, super validating for you guys that had to get looked at like you were crazy in a bunch of pitch meetings early. 'Cause it feels like one of those things where culturally, I think in 2020, people started kind of waking up to like, hey, wait, nuclear's pretty cool and probably good, and we probably want more reactors, not less. And then companies have started picking up.

How important is it for you to vertically integrate into the actual productive use of the energy? It feels like there's so much demand for energy, you could just become a mass manufacturing for nuclear reactors, and that would be enough of a business. When we talked last time about a year ago, you were talking about generating fuel out of the air with this energy, but it feels like you might just want to let the free market decide what the best and highest use of the energy is. Is there still a plan to do something with the energy that you own and control and decide? Or is it just like, let's just make as many nuclear reactors as possible right now?

Yeah. One of the core realizations of Valor is that there are some products that the market actually doesn't know how to buy. So I think this is one of the most important realizations that Elon had with SpaceX, which is that if you're going to make a rocket company that makes really good rockets, you also need to fly them. You can't just build the rocket, you have to fly them too. And the reason is that the customer actually doesn't know how to fly the rocket.

Right.

A small sat company, a telecom company doesn't know how to fly a Falcon 9. And so it turns out the best way to use a Falcon 9 as SpaceX is to actually own the entire operational cadence. And then you sell products like kilograms to orbit and internet connectivity, right? So that's the right way to think about these really, really complex technologies. Nuclear reactors are like this as well. So yeah, when we think about building lots of reactors, we think about building them on these very large energy campuses, And then we sell energy, right? We sell energy, not nuclear reactors. That might mean energy to AI data centers. Absolutely means hydrogen, and it means eventually synthetic fuels, right? If we can make a synthetic fuel cheaper than diesel, cheaper than gasoline, we can actually become the energy company of the world, right? Because the majority of the energy today is in a hydrocarbon format. So that's kind of the core realization that we had when starting Ballard.

Very cool. Well, good Thanks for calling in.

Yeah, huge day.

Huge day.

Congratulations.

Congratulations.

Thanks, guys.

We'll talk to you later.

To you and the whole industry.

Cheers. What a great show. Whole world tour.

4 hours now. I guess we just hit 4 hours.

Anything else we need to cover before we get out of here?

I think breaking news, John.

What's that?

It's the weekend.

It's the weekend.

And as always, our board Has been very explicit about this. Leave us a 5-star review.

5 stars on Apple Podcasts and Spotify.

Or less if you don't feel like it.

Yeah, just review us.

But if you've listened this far, you're 4 hours in, I'm guessing we earned that 5 stars.

So— Just do it.

Everybody have a great Memorial Day weekend. We actually won't have a Monday show because we're moving into the new studio, but we'll be back in full force in the new studio in the temple on Tuesday.

We're excited.

Cheers.

Have a great weekend.

Have a good one.

Bye.