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Let me [Music] You're watching TV.
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Today is Friday, May 23rd, 2025.
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We are live from the Temple of Technology, the fortress of finance, the capital of capital. and John. Yes.
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This is our last show in this studio. It is. It is.
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But the fortress of finance lives on.
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The capital of capital lives on. State of mind. It's a state of mind.
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It's a place on the internet that we we bring.
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We create the fortress of finance, the temple of technology, wherever we are.
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And soon it will be in Hollywood, California, the future home of media entertainment once we're done with it.
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Baby, we're bringing media to Hollywood.
6:31
We got a great show for you today, folks.
6:33
We got a banger lineup of guests and topics.
6:35
Wow, we really filled it out.
6:38
I thought we had four people booked.
6:39
Turns out we have seven now. It's great.
6:41
I don't know how that happened, John.
6:42
We're talking about the the information. They profiled us.
6:44
Uh Abe came down, hung out with us for a full day, uh wrote the allegations are extreme.
6:51
Yeah, the allegations of bro culture over here are extreme.
6:53
We'll talk about Apple's AI struggles, Sam Alman's trillion dollar AI device.
6:59
There's a banger quote in the Wall Street Journal from Berber Jin.
7:01
Uh, and then we got a whole bunch of guests.
7:05
Jory from Linear, Zach from Cury, Lee Marie Brazwell, former colleague of mine over uh over at Founders Fund.
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Now she's at Kleiner Perkins coming on to talk about artificial intelligence, some of the seed investing she's been doing.
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Remember she was like a seed investor in Windsurf, I believe. Uh, absolute banger. Absolute dog.
7:20
Uh, and we got Sam Lesson coming on.
7:23
Uh, we got the founder of Land and the great thing.
7:25
So Sam Lesson, many people call him Jessica Lesson's husband.
7:30
Yes, he usually goes by that in most tech circles.
7:32
by that in most tech circles. So Jessica's husband 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 um it would it could have been a very you know oh it could have
7:50
been extremely confrontational and it still could get and what I think the first or second time he came on uh Jessica Leon was in the background and kind of stopped by and said hey 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 all and she would have overheard us berating her husband about what happened. But fortunately,
8:07
But fortunately, uh, the piece I think it'll be pretty PC later and I'm excited to talk to Sam.
8:14
Uh, and then one of the greatest of all time, Bobby and Orin also calling in at 2 and 2:15.
8:19
And so, uh, we're going to be going late.
8:22
It's a three and a half hour show. Let's do it.
8:23
They said, "Hey, it's Friday.
8:25
Are you going to take your foot off the gas?" Absolutely. Absolutely not. Absolutely not. Absolutely not.
8:30
Uh anyway, let's read through how the technology brothers seized Silicon Valley.
8:34
The big read in the the weekend section of 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.
8:46
You think they went the extra mile of AI in here, but then there are also things in here that are collage.
8:55
There's a lot of Photoshop suits might be AI, but the faces are just photos that have just been uh tuned up.
9:04
And then I like the number overlay. That is not AI.
9:07
They made me quite a bit wider than than you even extremely wide, which is not my exact build, but I'll take so the screenshot that's up on the stream is the is the real one, but for some reason if you on the information there's a like an HTML bug.
9:22
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.
9:31
And so, uh, how do you have a PDF, John? Why do you have a PDF?
9:34
I always make a PDF of everything of every article so that we can read through it here on the show. Paid. Yes.
9:40
I am I am a paid subscriber of the information.
9:42
The PDF allegations are flying around. Yeah.
9:47
Anytime the black market is anytime that there's an article that people want to read, uh, it shares around.
9:50
Um but yeah, he says uh at a time when when tech has been at loggerheads with the traditional media, the industry elite have gladly accepted a warm embrace from a pair of insidery talk show hosts, Jord John Kouan and Jordy Hayes. A warm embrace.
10:08
Yeah, that's 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.
10:17
So I think that's generally accurate.
10:19
we try to sort out and not have people on that we want to, you know, get into conflicts with.
10:23
At some points, we'll have people on the show that we disagree with, but um but in general, the the like we're trying to have people on that we generally admire, people just to fight, argue, um you know, we we want to just hang out with our friends. Yeah.
10:42
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.
10:47
So, if you want to see Yeah.
10:50
Keith Ra boy fight with a journalist, you know, potentially in a physically, not not just on the timeline, we could set that up and I'd love to.
11:00
Um, but anyway, so in recent months, John Kugan and Jordy Hayes, co-host of TVN, a daily tech news show that has captured the attention of Silicon Valley's investors and founders, have followed the same morning routine.
11:11
The two men meet in downtown Los Angeles at a members onlyly Jonathan club to work out, then sauna together while reading print copies of the Wall Street Journal. Fact check true. Fact check true.
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You have your sweaty copy uh on the table today. It's real.
11:24
The image of Kugan 36 and Hayes 29 fits away in such a manner is well a little ridiculous in this day and age.
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And I posted that god forbid men have hobbies.
11:35
There's nothing ridiculous about two guys meeting up at a members club. Yeah.
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And having a sauna and reading reading the journal.
11:42
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.
11:50
You quote in the article, "This was in the sauna pointing to a bedraggled a section of the journal besides on the club's dining room table.
11:58
It has sweat all over it."
11:58
Yeah, there's the wide version of us because it's been stretched. Even wider. It's great. Um, yeah.
12:06
So, I had to prove to him.
12:06
I actually did invite him to the morning workout.
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I said, "Meet up with us at 6:30. It's chess day.
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We'll we'll we'll hit some PRs on the bench and then we'll go in the sauna. We'll talk. We'll get breakfast."
12:19
Uh, he was he was traveling around.
12:20
Couldn't make it, so he just came to breakfast.
12:22
So, I had to prove to him by showing him the sweat on Not the first not the first time we've invited somebody to a workout, though. It's the best.
12:28
And then had them come up with some range of excuses.
12:31
Oh, I'm not going to be able to get there at six. Yeah. Yeah, I'm sorry.
12:34
It is a It is a high bar, but yeah.
12:36
Um, you know, do coffee meetings.
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Naval says, uh, set your opportunity cost extremely high.
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He said, "Meet like a lion." Meet like a lion.
12:44
Be hitting bench when when you're meeting with Naval is the original the lion does not concern himself meme.
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Like that's where that came from basically. Work like a lion.
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Basically, he doesn't concern himself with much.
12:56
He doesn't he doesn't concern himself with email. Yeah.
12:59
Doesn't concern himself with coffee meetings.
13:00
Um but the gym meeting it's highly efficient.
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Uh actually I mean I I I Strauss Zelnik the CEO of Take Two owns GTA putting out GTA 6 soon.
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Uh he is famous for uh doing workouts and doing workout meetings.
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And so I read that book and I kind of adopted that and started doing uh workouts with Ben and talking to him about the business while we're working out.
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And it's just a fantastic flow.
13:27
It's the best way to hang.
13:27
Um, so they go on, he goes on, Abe goes on to write, "Kugan and Hay is live streamed TBPN, which they originally christened the Technology Brothers as a knowing nod to the concept of a tech bro on X and YouTube from 11:00 a. m. to 2 p. m.
13:41
Pacific and published the recording on Apple Podcast and Spotify.
13:42
When I found them sitting down to breakfast at the Jonathan Club, they had mostly prepped their opening commentary on the news.
13:49
Airbnb's revamp, the Trump administration's proposed changes to chip AI chip exports, and they had a number of guests booked, such as Founders Fund Delian Aspuov, Lux Capitals Josh Wolf, and Eugenia Cudia Kudya, whose startup Replica AI hopes to develop chat bots that can serve as human companions.
14:04
So, here's where it gets interesting, John. Yes.
14:06
says, "Like the show's audience, the guests are attracted to quote unquote TBPN." Yeah.
14:14
Like it doesn't it's not a real thing.
14:15
Like it's not a real thing.
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As a safe refuge from the mainstream media, one that projects an unabashed, unapologetic enthusiasm for tech.
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I think this is my best line in here.
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I'm glad Abe included it.
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We genuinely love the private markets, the venture capital industry, the startup industrial complex, and yeah.
14:34
So, so, so there's something interesting here.
14:35
TBPN is in quotes, but I'm I'm on a different article from the information and it and it reads, "Jim Kramer, CNBC's Mad Money host, took a swipe at our report today, and CNBC isn't in quotes." Why is it? That's so interesting.
14:50
I wonder in the Oh, it could be a bug in the CMS and the content management system.
14:56
Maybe they should switch content management systems.
14:57
I like if they're making if bugs like that are sneaking it into articles. Aes, our boy. Yeah.
15:01
And I'm gonna just I'm I'm gonna assume that it was just an accident. Probably just a mistake.
15:13
Uh anyway, since TVPN debuted last October, Hayes and Kugan have warmly welcomed investors from pretty much every major firm venture venture firm in existence. Let's go. Uh we're Switzerland.
15:22
We're Switzerland over here.
15:24
A marker of the podcast widening appeal, Sequoia, Kla, Lightseed, I could go on.
15:28
A week or so ago, they dispatched one of their four producers to Las Vegas to set up a mini studio at Andrees 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.
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A level of access no one in regular media would ever get.
15:44
Thank you uh to Eric and the whole team at making that happen.
15:48
And I want to do more of those.
15:50
I I I'm talking to KOA about that.
15:52
I think that's like an interesting thing.
15:54
uh the the sit down with like the full partnership to get the full scope of like how everything fits together because most most founders even in my career I've interacted with like every fund but usually just a single partner and so you you know you usually have this very like point like maybe you've listened to Mark Yeah.
16:12
or and then you've interacted with uh you know David George on a deal or David Haber on a deal or something like that.
16:19
Um, it's rare to be able to see like all in one and I I I like the way that that came together.
16:26
So, I'm hoping to do more of those.
16:28
Anyway, so it it goes on.
16:28
He includes uh TBPN in quotes again uh which is TBPN is in quotes every single time it's listed and the information includes TBPN in quotes.
16:39
Uh anyways, he goes on talks about some of the guests that we've had.
16:43
I thought this was funny.
16:44
Uh Augustus D Rico whose startup Rain Maker Technology uh has come on the show has a skyhigh dream of commercializing cloud seeding a process of adding chemicals to the atmosphere to increase precipitation. Uh he's a good writer.
17:00
Skyh high dream it's it's a good line.
17:03
As Hayes and Kugan have won attention from a swath of the technarati and have achieved a constant social media virality.
17:09
their consistent social media virality.
17:12
Their audience has remained incredibly niche.
17:13
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.
17:23
On YouTube, TBPN has only around 7,000 subscribers.
17:26
Um, it's weird to be like incredibly niche. 130,000 followers.
17:31
Like, how many you got, Abe? How many?
17:34
Hey, let's let's pull up Let's go analytics.
17:38
No, let's go analytics for analytics.
17:40
Last time you dropped a 20k banger on the timeline. Let's check it out. Let's see. Let's see how wide.
17:43
You know, Jordy has 100,000 likes on a post. 150 150k likes. Is that niche? Is that is that niche?
17:51
Oh, you know that uh my sean ping video on YouTube has three million views.
17:55
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.
18:05
Yeah, I mean this is actually something we think about is like is like there are obvious TAM expanders.
18:10
Politics is the obvious one.
18:13
Um and we've and we've deliberately said we're not going to try and TAM expand. Is A watching? Abee's watching.
18:17
He says I demand a rebuttal.
18:19
Should we let him call in right now?
18:21
Yeah, let's have him call in. Okay. Send him the link. Send the link. Send him the link. Abe, come on in. Demand. Come on in.
18:29
Um anyways, uh they have no investors and profess to have zero intentions of raising capital unless those investors didn't mention our incredibly complex corporate structure because we do have a nonprofit that's into an LLC that feeds into a COP that feeds into the labs which is of course owned by Wilmanitis.
18:48
Will Mandis Will Mandis uh I I this was a a fun quote uh which I stand by.
18:51
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.
19:01
So we very intentionally not raised it would be it would be your final party round. The final party round.
19:10
The final party round if the final round because I mean realistically every we could get everyone but it would it would very much change it would very much change the dynamic of the show.
19:19
It would be it would be less fun.
19:21
Uh, I asked RAMP CEO Eric Lyman what he found so appealing about the show and he likened their approach to how ESPN chronicles sports where Sports Center has players, coaches, and games to celebrate and explain.
19:32
TBPN is founders, investors, and developer conferences.
19:34
They're they're able to bring to life the personalities, the playbyplay, and capture the zeitgeist. Thank you, Eric. That's a great quote.
19:42
That's exactly what we're going for.
19:43
Uh, Kug and Hayes often hear themselves compared to ESPN commentators, but the analogy is sort of lost on them because putting a major dent in their broken 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.
20:01
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.
20:11
Ultimately, TBPN, allegedly, if it exists at all, if it's a real thing, hopes to better capitalize on the same broad truth about tech relationship with old school media that underpinned Clubhouse.
20:24
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.
20:34
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.
20:43
Mo most such efforts have flopped, mounting to little more than lame public relations.
20:46
Guggen and Hayes seem to have found their sweet spot.
20:48
They maintain just enough independence from their subjects, but feel none of the pressure for critical coverage most journalists in their position would.
20:55
They also get far on their twin blessings of easy charm and boyish good looks.
20:59
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.
21:10
For those that don't know, Hayes and Kugan, we're both Irish. Scott's Irish. And so, you know, St.
21:13
Patrick is obviously a famous snake charmer and and charmed all the snakes out of out of out of Ireland.
21:20
And so it's it's it's kind of like racial humor.
21:23
Is this like is it racial?
21:25
I don't racist, but it's racial. It's definitely racial.
21:28
And so, yeah, it's a little bit edgy, but I I mean, I appreciate it. It's fun.
21:33
We're in the postwoke era.
21:34
We're in the anti-woke era. Totally.
21:36
If Abe wants to go there, Abe can go there.
21:38
He can go We can go charm for charm with anyone.
21:41
We can go charm for charm with the best of them.
21:48
It's just a little crazy cuz I haven't been called.
21:50
You don't normally think potato.
21:52
You don't think of information editor as an edge lord. Yeah. No, you don't. But but he snuck in. Yeah, it's good.
21:59
It's a little It's a good It's a little little dig little dig.
22:03
Oh yeah, I saw him chugging Guinness passed out like a drunk Irishman.
22:06
You know, he didn't go that far.
22:08
He stepped it back, but he still threw in a little bit of the Irish a little dig of the Irishness. Yeah, makes sense.
22:16
They have an interesting They have an interesting voice that I don't think many people could pull off, said Ashley Vance, the Elon Musk biographer and former New York Times and Bloomberg Jouro. Jouro. They use Jouro.
22:24
I thought that was our word for them.
22:27
And Bloomberg, he's taking it back.
22:29
Abee's taking back Jouro.
22:32
Wait, that's actually interesting because he he highlights earlier.
22:37
No, he highlights earlier in the article that we took back Tech Bro.
22:41
They're taking back Jouro and and but but you know, Tech Bro was a slur.
22:43
We took it back as Technology Brothers, but he's taking back Jouro.
22:48
He's kind of inverting it.
22:50
He's saying, "I'm not a journalist. I'm a jouro." I'm a jouro. It's kind of cool. I like I'm into this. That's kind of cool. Jouro Jouroism is back. Yeah. What is it? What is it? Kibits.
23:02
Do you know what that is?
23:02
Because it said Ashley came on for a kibbitz.
23:03
Uh look on and offer unwelcome advice, especially at a chat. Oh, chat. Okay.
23:12
So, he came on for a chat. Yeah.
23:12
And he's coming on uh he's coming back next week.
23:15
Uh he's been traveling, shooting a movie. Very cool stuff.
23:17
I don't know if you saw his cinema rig, but he's got like 25 different cinema cameras. It's amazing.
23:21
I'm very excited to see what he's doing.
23:23
I don't want to leak too much of Abe is Abe is in the temple. He is.
23:27
Okay, let's bring him in.
23:27
Abe, we got to get to the bottom of this. Abe. Okay, we're falling in. Wow.
23:36
Abe on TBPN for the first time ever.
23:42
I could go into exactly why uh you know um CNBC doesn't get quotes and you guys do, but that seems boring. Let's talk more fun. Wait, wait, hold on. Hold on, editors.
23:53
Uh, the Chiron's way wrong.
23:53
Can we put the information in quotes?
23:59
Can we put the information in quotes?
24:01
Put the information in quotes.
24:01
We have to Hey, uh, it's fantastic to have you on.
24:05
Uh, we talked about this earlier.
24:05
We knew we knew uh I mean Jessica Lesson's husband was going to come on later later today.
24:13
And it would have been a funny kind of dynamic if this had been a hit piece, which we obviously didn't know until uh around 9:00 a. m.
24:20
when you when you hit publish.
24:22
So, uh it this will be a fun show end to end. Yeah. Uh it was great. I I I don't know.
24:29
Is there anything else that I mean, you've been listening to our analysis.
24:32
Uh anything else you need to get off your chest?
24:37
No, I I I think the story, you know, is a piece of fair and accurate journalism and uh you know, you guys are you guys are doing what you do best, which is, you know, common commentating on the news on the breaking news about uh the brothers.
24:51
Wait, I have to ask, did you intentionally use the word jouro instead of journalist when talking about Ashley Vance?
24:58
Yeah, because we think of jouro as like a tech bro style like dig.
25:00
Like it's almost a slur for journalist.
25:03
It's kind of, you know, guys, in the way that you're funny on camera, I also try to be funny in the way I write.
25:11
Uh, you know, just to, you know, make the make the make the jokes go around. No, you nailed it. You nailed it. I mean, you got us. We were cracking up. It's great. It's really good.
25:23
Uh, I I'll be back in LA soon and uh I'll take you up on the sauna. Let's do it. Fantastic. We can't wait. Let's do it. Yeah.
25:29
We got to get a big one in the new studio.
25:30
like uh we got to like basically dedicate 2,000 square feet, a single sauna for sure.
25:34
Uh hey, uh thank you for the fun and fair coverage of what we're doing. Fantastic.
25:44
Uh and uh likewise, you guys are a good hang.
25:46
Don't be uh don't be too nice to Sam. Okay. Okay.
25:48
We won't be we'll be we'll be rough on him.
25:51
We'll put him in the streets, though. Bye. Awesome. Thanks for jumping on. See you. Look at that.
25:58
Look at that med meeting media technology. Yeah.
26:00
All together just broing down. Love to see it.
26:03
Um they give a little bit of our background but then go on to talk about how we met uh mutual friend.
26:10
Did they actually not they didn't they didn't name Will Mandis.
26:14
You didn't name it Will Manitis.
26:16
Um saw an opportunity for tech focus podcast that could analyze industry news with a light irreverence and wasn't tied to a single company or venture firm.
26:23
Last fall, they had enough free time on their hands to record a couple test episodes when they attended Peter Teal's Hereticon at the Fena Hotel.
26:28
Oh, they put founders in quotes. [Laughter] Oh, no.
26:36
They sought out feedback from David Center, host of the popular Founders podcast, if you could call it that.
26:45
Wait, did did Abe actually tell us why they put it why he puts it in quotes?
26:48
I don't think he No, he said he said it wouldn't be fun. Okay.
26:50
It would be fun, which is Yeah. Yeah. Which is fair.
26:54
No, I mean it makes sense.
26:54
You're introducing this to the first time to your audience.
26:57
Like we're given a hard time, but like obviously it's called TBPN. Yeah. Yeah. Yeah.
27:00
It's it like like if 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 unqued.
27:14
Like we will we will earn the removal of our quotes.
27:20
earn your throwing off the shackles of the quotes. I'm excited.
27:25
That's uh that's definitely on the on the vision board right next to TBPN arowan smoothie. You heard it here first. We're working on it.
27:29
Um uh uh David Senra previously advised Kugan on his YouTube channel.
27:36
Uh this is funny because like it was very very informal, but I did learn a ton from David.
27:40
I remember the very first time I I talked to him.
27:44
I was doing my YouTube channel like very much part-time on just like one day a week on the weekend when I was bored.
27:50
I just put up a video and I did one a week.
27:51
Uh and it was growing and it was doing well.
27:53
Um and I was just like wait like you have this podcast that's like this is pre deal.
27:58
This is pre invest like the best partnership and pre meeting Patrick and stuff.
28:03
So the show was pretty small at that time.
28:05
And I was like, "Wait, you do this full time?" And he was like, "Yeah."
28:09
And he swore upon I was one of the first advertisers on Founders Podcast.
28:14
I had no idea for Capital. Yeah.
28:16
Capital. Yeah. I was I was like one of the first one or two and it I I certainly won't mention it here, but uh and and the funny thing is I had actually reached out to David and I really didn't I I I listened to the first episode and I reached out to him and I was like would you this was this was at a time that was like yeah every
28:37
tech company should be a media company which I don't agree with anymore but I was like would you consider like joining like he told me his ad rates and I was like well what if we just like acquired founders and in hindsight that was like such a ridiculous thing to ask cuz David never under any circumstances would have done that or anything like it. Um nor
28:54
Um nor would it have been good for the show but uh but yeah at at that time it was like very very Yeah, you know. Yeah.
29:00
No, I I remember getting on the phone with him and and he was telling me like I was like do so do you do this like full-time?
29:07
Like how do you even make that work?
29:09
He was like and he swore a bunch.
29:11
He was like absolutely like I I don't do anything else. This is all I do.
29:15
And I was just like super impressed that he'd been able to make this work.
29:18
And it is like a niche show.
29:18
It certainly was at the time, but he obviously found a really high value audience and was already monetizing it very well at that point.
29:26
He had like a payw wall for some of the episodes.
29:27
He was starting to do some advertising.
29:30
He's evolved the business model a ton and probably 100x the product quality was incredible. Yep.
29:34
But he was like it was it was just it was just him.
29:36
No employees, nothing like just like building building.
29:40
So it was very very cool.
29:42
Um, and so yeah, I mean I learned a lot from him and kind of kept growing the the channel and then eventually evolved into this.
29:47
Uh, he thought that the two shared natural chemistry and encouraged them to go all in on the concept, which we've told about, which we've talked about before.
29:53
For a model, he suggested they look at sports commentator Pat McAfee.
29:57
Senra admires McAfei's always on persona.
29:59
What is Pat doing right now?
30:01
I bet he's live streaming, he said.
30:03
And I wasn't exactly sure because we we've looked to Pat for as a as like a a role model in in many ways.
30:09
Um, but I wasn't exactly sure where that came from.
30:12
But I thought the most interesting lesson that I learned from David was that he actually did not tell us you guys should live stream.
30:18
He told us you should take this 100x more seriously. You should go harder.
30:24
You should go full-time on this.
30:26
And what was interesting is that the we were doing a weekly podcast with no guests.
30:34
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 guestled show, all of that just happened very naturally.
30:46
He didn't tell us tactics.
30:46
He just told us exactly what he what he says on every we left Miami and we decided to go to two or three days a week. Three days a week.
30:55
Yeah, maybe it was three days a week.
30:57
But then I remember the realization that we would stop recording. Yeah.
31:02
and and we would be on X like an hour later and I'd just be like, I wish we were doing the show tomorrow.
31:08
And then we just eventually we decided to go to five days, then we decided to go live, then we decided to add guests.
31:13
I even remember talking to you about like maybe we should do like one day a week, five hours, and then slice it up.
31:21
So, we're releasing one hour per day podcast weekly.
31:23
And and it was a terrible idea, and I'm so glad we didn't do it.
31:27
Um it's it's it's a way way better way better um uh format.
31:29
And so, uh, Abe goes on to write, "Soon Kugan 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 hightouch approach to assembling retweets.
31:47
Uh, later they started to share the clips and tag the the posts authors uh on X, and the authors would often frequently pass on the clips themselves, giving Kugan and Hayes some of their first virality.
32:00
The pair set themselves up on the 10th floor office that Kugan rented in the Jonathan Club, hired a small video production crew, who they sometimes refer to as just the guys.
32:11
Well, since well, they're all young men.
32:13
Um, and uh over the course of the next several months, the TBPN hosts and the guys have adopted a steady rhythm.
32:18
When Kugan and Haves go live, two of the guys control what appears on the stream, including the Chirons.
32:25
Uh, the bit of text below the guest. It's funny.
32:27
I didn't even we didn't even know the the term Chiron for like we had been doing a Chiron for quite a while and we were I had to explain it to basically everyone on the team because we all learned but I had in fact heard the term before.
32:41
Um but yeah um you have a background in big television John that you don't know about.
32:47
No I I've been to NAB I've been a nerd for like production for like several years and so I' I've been like loosely familiar with all this stuff.
32:55
watched a lot of YouTube videos explaining how churches do live streams because megaurches are delivering at a level that is equivalent to Fox News on 1/100th of the budget.
33:06
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.
33:14
It's a bevy of resources.
33:16
It's it's fantastic and some of them do like virtual productions. It gets crazy.
33:20
Uh anyway, they tried they try to make these funny.
33:22
One example, venture capitalist yaps about venture capital.
33:25
Uh, I'm excited to share a screenshot of of Abe Brown, writer at the information.
33:32
Did you see the final Chiron? So good. So good. Uh, steady crawl.
33:35
The show's sponsors appear next to the Chirons.
33:37
Uh, along with a ticker available of available polyarket bets with Kugan Hayes seat as telling indicators of market sentiment and their audience's interests. That's true.
33:46
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.
33:53
Let's hear for Vice President Ben, who worked with Kugan on his YouTube videos, serves as head producer.
34:01
On a traditional TV show, a producer would normally pre-inter a guest.
34:05
Sounds really boring to help to help both the guest and the host.
34:09
But Kugan and Hayes prefer to wing it.
34:10
And since they're never brandishing any sort of gotcha question, we'll hit you with some gotchas.
34:16
We're just going to do nerdy gotchas about scaling laws and and gotcha and buildout timelines and and end to end algorithms.
34:24
We're not going to ask you about your personal life or your politics discuss politics.
34:28
Um the informality doesn't discomfort their guests. There's no prep.
34:33
They just sent me a Zoom link and I joined, said Sham Sankar, Palanteer's chief technology officer and a veteran of many CNBC hits.
34:40
To fill the guest spots, Kugan Hayes tap their rolodexes and industry connections.
34:43
Unsurprisingly, they've started to get inbound requests.
34:45
We're at the point where we're getting 20 pitches a day from PR firms.
34:48
Kugan said, "We turned down 95%."
34:49
His rejection method is simple.
34:52
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.
34:58
Yeah, I'm generally looking for like are they tapped into the news?
35:01
Are they following technology stories?
35:04
technology stories? Are they are they you know I wouldn't say this is this is this is one part of the process but certainly we've had people on that don't have a presence and we actually want to do a lot more yeah totally but but if you're getting a pitch instead of a warm
35:22
introduction to 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 who is interesting that just happens to have a stale PR team that's kind of pitching broadly and that you got to kind just deal with that. But most of the time if there's
35:38
that. But most of the time if there's just some stock like big you get these big emails with all these bullet points of 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
35:49
conversation and if they're not in the conversation it's going to be hard for them to join and have a conversation actually bring something really they're just going to come on with talking points and so it's pointless or if they come on with LinkedIn takes from it's not good two months ago not good work. Hayes and Kugan delight in their shtick
36:04
Hayes and Kugan delight in their shtick for the show which includes opening bottles of Don Peran to markets growth.
36:09
A constant tongue-in-cheek shilling of ramp ramp ramp which makes expense account software that would exasperate many mad men. But not us. Not us. Not us.
36:18
Switch your business to ramp. com. Save time and money. Just do it.
36:20
We had a whole running gag with Abe the entire time.
36:25
We probably pitched him ramp seven different times at least.
36:26
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 got to post that. I got to post that."
36:41
And 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.
36:48
Please stop pitching me something to that effect."
36:52
And we said, well, I, 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, we had so much fun with it. It was great. So much fun.
37:03
Thanks for Thanks for being a good sport.
37:04
Yeah, he was a good sport about it.
37:06
And a preference to always appear in suits, their visual trademark.
37:10
Kugan gets his suits from a tailor whose identity he wouldn't reveal.
37:16
Hayes likes user a New York based uh I guess they're a brand now but they are primarily a tailor.
37:21
It's Laura Piana fabrics assured me.
37:25
I guess me and Jimoth have that in common.
37:27
Watch peeking out from doxed. They doxed your watch. They doxed my watch. They doxed your watch.
37:33
The suits are a little dig at Silicon Valley's preference for the inform informality of cotoaxi which is that how you pronounce that?
37:41
I've never I've never heard that before. Never worn it.
37:44
Um, Hugan hopes they serve another purpose, too.
37:46
It's going to make it easier to appeal to public company CEO who's running TBPN.
37:49
Oh, we got single quotes now. We're upgrading.
37:50
Oh, because it's inside double quotes. He still hit the quotes. Got us.
37:54
I was so excited that we were halfway to no quotes.
37:57
We were getting double quotes.
38:00
Now we're getting single quotes.
38:02
The next thing's no quotes.
38:03
Uh, by his PR team that's maybe more conservative and more riskaverse, he said.
38:07
So, when they pull up an example, they see a very clean package and everyone's in suits. And that's true.
38:11
I I want to be a place where uh big public company CEOs can come on and it doesn't feel like we're disheveled not taking this seriously.
38:17
Um um it needs to be brand safe even for big tech companies that want to you know uphold a very serious brand standard that they would that they would feel comfortable on Bloomberg or CNBC.
38:29
They should feel comfortable here as well.
38:31
Uh the external appearance that's the external appearance at least this is when he's putting us in the truth zone.
38:39
putting us in the true zone.
38:39
Abe, internally, the atmosphere is decidedly informal.
38:43
When the show wrapped on the day one, on the day I was at the Jonathan Club, Kugan 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.
39:01
There is we we do at times wear normal clothing. We do.
39:05
Uh, waving goodbye to the guys.
39:09
We loaded into Hayes Mercedes-Benz Gwagon. Wow.
39:10
He didn't even He didn't even say the most important part. It's an AMG. It's an AMG. It's a G63.
39:21
Yeah, it's a really important detail. Leaving that out. That feels intentional.
39:25
Trying to take you down a peg. Could be a G5. Yeah. I like it though.
39:30
It's more It's more subtle. Yeah. Yeah. It's a dude.
39:32
He's just leaving it open.
39:33
Could be any type of G Wagon. Yep.
39:35
And we so we drove Abe over to Hollywood to see our new 4,000 foot studio uh that we just signed a lease on.
39:42
Abe says it dwarfs the size of the current set they have in the Jonathan Club.
39:46
We are in a very small space on this set.
39:48
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.
39:55
Uh right now we basically sit down for three hours and half hours.
40:00
we get up for like a minute in between, but the energy will be so much better when we can stand. It's going to be great. It's going to be great.
40:07
Um, they'll also have the opportunity to host inerson guests, something we're very excited about.
40:10
We have a bunch of people lined up and we should be able to make those uh those in-person uh sessions really special.
40:18
Uh, and I asked them about the dream bookings.
40:19
Of course, we've talked about this before.
40:20
Our dream bookings are the Magnificent Seven, like all of them.
40:22
Uh, we want the CEOs of of Apple, Microsoft, Alphabet, Amazon, Nvidia, and Meta Platforms, and Tesla.
40:30
We want them all the Thanos glove of of uh of technology leaders.
40:36
We want them all on the show.
40:38
So, if you know someone, please make it happen for all of us.
40:42
Um, but we still have a lot to do on the production side.
40:44
We want to be a fantastic show.
40:46
We want their first appearance on TBPN to be memorable and uh cinematic and cinematic and and and enjoyable and and I think you know uh and most importantly I think it's less about like asking like the hard-hitting questions.
41:03
It's more like what are the questions that the investing community actually wants to hear?
41:07
How can we dig through those and drive those questions that move markets?
41:12
That's what's most important. Yep.
41:13
Um, and so, uh, the 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.
41:31
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?
41:38
Well, for some companies it might be.
41:40
If their capex is looking rough, it might be.
41:43
Satcha says, "We're happy to be leasers."
41:46
Is that is hitting him with a question about his pivot away from data center builds a gotcha?
41:50
Like certainly not to a normal person who doesn't invest in the stock, right?
41:54
But to uh to someone who really cares and owns a lot of Microsoft stock, it's probably pretty important anyway.
42:01
Uh it might be easy to design a show that would appeal to one or two of them, but it would be difficult to do uh one that could attract the entire set.
42:08
They've all done podcasts, but there's no podcast that has done all seven.
42:12
And uh says Kugan, that's me.
42:15
On the drive over, Hayes mentioned a dream prop for their Hollywood set.
42:18
He and Kugan have already already have a small gong in their Jonathan club that they rang on the show when talking about a company's notable achievement, but he would like to buy an even bigger gong.
42:28
Looking around at the Hollywood studio, he could see how nice a an extra-large version might look.
42:35
"Yeah, we finally have the space for itong," he said. Oh, what a fun. Oh, I can't wait.
42:40
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. Um, we're working on it.
42:51
Uh, what should we move on to?
42:52
We I mean, the main thing we have to cover, so yesterday X was a nightmare.
42:56
Uh, DMs weren't working for a lot of the day, which was rough for us on the show.
43:00
Apparently, there was literally a fire in the data center.
43:02
So 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.
43:15
Uh the sources required anonymity as they weren't authorized to speak publicly about the company.
43:21
Firefighters arrived at Hillsboro Technology Park in a suburb west of Portland at 10:21 a. m. Man. John. Portland, Oregon. vandalis.
43:28
Uh uh you think this is you call an arson? I have no idea.
43:35
I don't even know how you how you vandalize or or commit arson in a data center, they seem to lock down the Yeah, but the every time I see Portland in a headline in tech, it's some type of This is pretty advanced stuff to figure out where the data centers are. Okay, I'm sorry.
43:55
If you're a extremist and you want to bring a bunch of gas, Will Manitis 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.
44:09
So like an AR-15 shot at a transformer can take off a whole a whole whole piece of the grid.
44:16
And so you would think that they'd go after that. I don't know. It's very very very odd.
44:20
Hopefully they sort it out quickly. Yeah. So it's interesting.
44:23
So before Tesla's have been setting on fire.
44:24
So maybe X data center is So this is interesting.
44:26
So before Elon bought Twitter, the company had three data centers in Sacramento, Portland, and Atlanta.
44:31
This ensured that if one data center went down, traffic could be shifted to the other two and split so no single data center was overwhelmed.
44:40
Around Christmas Eve 2022, Musk shut down X's data center in Sacramento in an effort to cut costs.
44:47
The company experienced a major outage in the wake of the shutdown.
44:50
Over the next 6 months, the company moved more than 2500 server racks from the S Sacramento facility to data centers in Portland and Atlanta.
44:58
So, it sounds like they have two core data centers now. Okay.
45:03
I want to rip through a bunch of stuff really quick.
45:05
I'm just going to rip through this stuff.
45:07
Um, so, uh, Donald Trump just signed an executive order about nuclear and so we're going to try and have some folks on uh very quickly and slot them in.
45:17
might be 230, but I'm talking to some nuclear folks about uh coming on and breaking it down.
45:22
I haven't even had a chance to read it yet, but it's out apparently.
45:24
Uh I don't know if you want to dig into that.
45:26
I also want to give you the final analysis on Apple's AI struggles.
45:30
We've been dipping our toe in and out of the story all week, but uh Ben Thompson had a great summary of the problems with Apple's AI issu uh with Apple's AI strategy, and he sums it up in these bullet points, which are really rough.
45:45
One, Apple's head of software engineering didn't believe in AI.
45:49
Apple's head of AI was skeptical about LLMs and chat bots.
45:50
Apple's former CFO refused to commit sufficient funds for GPUs.
45:55
Apple's commitment to privacy limited the company to purchased data sets instead of using like their own where Meta and Google and YouTube are all highly valuable training uh training sources.
46:08
Um, Apple's AI team is underst staffed and the relative talent of the of an AI staffer still at Apple is uncomfortable to speculate about, but given the opportunities elsewhere relevant.
46:17
Um, what should Apple do now?
46:20
The baseline advice from Ben Thompson is make Apple's ondevice models available to developers as an API without restriction.
46:26
Uh, make Apple's cloud interface uh, cloud inference available to developers as an an as an API at cost.
46:34
allow Siri to be be replaced by other AIs perhaps for subscribers to a to those oa to those AIs who would revenue share with Apple.
46:42
So you could bring chat into in into I bet for the access to the Siri button Apple could get like 50%.
46:49
50% from up from their their typical just hold an auction just hold an auction and be like hey yeah like we're we're just not going to hit this out of the park so we're just going to auction it off. It'd be great.
46:58
they have precedent of selling the search bar, right? Why wouldn't they do?
47:02
Um, anyway, the other the other news is people are now speculating about the exact device that uh Sam Alman and Johnny IV will be building together at OpenAI with the IO acquisition for $6. 5 billion.
47:15
Uh, Swix, who's been on the show, says they literally copied Avi Shiffman, $6.
47:19
5 billion for what Avi Shiffman built in the cave with a box of scraps, quoting Iron Man, of course.
47:23
And there's an old video from Avi uh pitching the first friend.
47:29
And man, I mean uh what a throwback. I remember this.
47:33
This is what I was saying.
47:33
I think on Wednesday or Tuesday, it was like, yeah, this could end up being extremely validating for AI and friend if he if he ends up nailing to be clear, he's also I think focused on a much different use case. I agree. I agree. Friend. com. I agree. Build companion.
47:51
To be fair, like the bare 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 smart watches are a good thing.
48:02
And then Apple comes out with the Apple Watch.
48:05
They just leverage integration and it's just a much better product.
48:08
And then Google does didn't need to buy Pebble.
48:11
They just created this Samsung Galaxy Gear or whatever, the the Samsung watch.
48:16
And so the 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 there's not a winner in independent smart watches.
48:27
And so if if there is a pioneering new format and OpenAI has a serious hardware 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.
48:42
So obviously I'm pulling for him and I hope he I I hope he can wind up navigating it and counterpositioning in a way that he creates something that's truly disruptive.
48:50
But it is it is serious business right now.
48:51
Uh but Augustus sums it up sums it up well.
48:53
He says, "I have no stake in SFAI hardware, but this seems right and it's uh the giant uh going up against a shiffman and print. com." So good luck to him.
49:02
Um 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 use.
49:12
Shuffle really was a magic product. Yeah.
49:14
Um, were you too were you kind of too mature for a shuffle?
49:21
I don't know if I ever had one, but I think it was more like a poverty problem.
49:24
I don't think I had the money for it.
49:25
Um, but it was it was very much like an accessory. Inspire you to grind.
49:30
Yeah, I should have been grinding harder, but honestly, no. You know what it was?
49:33
I was too much of a nerd.
49:33
So, I had I had something called like an i River, which was like a very unique thing that like it was it was technically more advanced than the iPod at the time.
49:44
Like I had one that had a color screen that you could watch movies on.
49:48
It was like a 2-in screen and it was well before the iPod video came out uh by like a year.
49:52
And so, the release cycle was high was was faster and you get newer tech, but it was like borderline unusable because there was no focus on user experience.
50:00
And so the company wound up kind of just not not not ripping. Um, what else? Oh, Sam Alman.
50:07
Uh, there's a exclusive in the Wall Street Journal by Berber Jinn.
50:09
Uh, a quote in here about what he's planning here.
50:14
And we just got to read this one quote.
50:15
Uh, Altman suggested that the $6.
50:17
5 billion acquisition has the potential to add $1 trillion in value to Open AI, which is is such an insane thing to say. It's so crazy.
50:26
But at the same time, how much is Apple worth if you get if you get a play in that space?
50:34
Like, yes, a trillion dollars of market cap is totally up for grabs.
50:35
And so, I think it's I think it's like it sounds ridiculous.
50:39
It sounds like over the top, but that really is the the the expected value.
50:44
And so, when you think about it as like um you know uh what is that a 6% or Yeah.
50:51
uh 665% chance at a trillion probably worth 6. 5 billion, right? Yeah. In equity.
50:58
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.
51:06
If they hit it, it's low probability probably, you know, a couple percent chance that they pull it off, but if they do, it's a trillion dollars, so it's totally worth the high number.
51:13
At least that's probably like that that's one way to do the the the discounted cash flow and like the the valuation.
51:20
Um, and and we've we've sliced and diced the 6.
51:22
5 billion a bunch of different ways and and we I think we both came away with this idea that like it's not as crazy as it sounds. It's 2% of the company.
51:30
You know, you're getting a great executive.
51:31
You're getting a whole team.
51:32
And like it seems like a big number.
51:34
They haven't shipped anything yet.
51:36
That's that's crazy to buy something that doesn't even have a product for six billion.
51:39
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?
51:46
Anyway, um I 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?
51:58
Hey guys, welcome to the show. How are you? We're great.
52:01
Having fun reading through the information, looking at the new uh Sam Alman IO acquisition.
52:08
Uh have you do you have a take on the new device?
52:10
What do you want to see in the world of AI hardware?
52:12
I I don't know to be honest.
52:15
Let's see when like things start shipping and like how things like evolve.
52:19
Uh it's been Have you had a chance to play?
52:21
I mean like it's it's great to see like I've again like in you know driver's seat and like on the on the news like doing uh doing interviews and so on.
52:29
So I think like it's like we had a had a break from for like whatever like four years or like so it's it's been a while. John John called out.
52:37
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.
52:45
Uh but I but I'm excited to see I think uh every every technology Call that a coincidence in my parts. Yeah. Yeah.
52:52
Uh but I think every every technology enthusiast will benefit from him taking a real crack at at AI.
53:00
What what else in the news this week?
53:02
It's been kind of an informal AI week over here at TBPN between Microsoft Build, Google IO, OpenAI, IO, linear linear agents, linear agents, and anthropic claude 4 dropping.
53:13
Uh, what's been most interesting to you?
53:16
What are you most excited to leverage?
53:20
Uh, pretty pretty bad week for me for like following the news.
53:23
It's like finished up moving.
53:24
So I've actually been like relatively like off news and like I think like on the docket for like a long weekend to like start catching up more on the on like all the keynotes and so on.
53:34
But I don't know it's it's it's good stuff like having more agents or like especally coding agents and like different like players like coming coming into the space.
53:43
So, uh I don't like it's it's it will be like interesting seeing like over next couple of weeks kind of like what like performs like how well and also like uh what kind like u user experiences are going to be there.
53:57
Uh because I think like that's that's kind of like the bit that we're we're like at linear like now following much more as we're like also you know trying to like work with like different players and like integrate stuff into linear is like what are like the patterns of like usage that will happen uh with this. Yeah.
54:13
What's more important just vague definitions around user experience patterns for agents versus standards like MCP and more technical advances. Yeah.
54:26
I mean like those are like very two different things.
54:27
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.
54:36
Uh 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 like own like trying to like hoard everything but like now things are pretty much like being pushed out in the open.
54:49
Uh and people are like companies are like almost like forced to cooperate in like the new world.
54:56
There's just so much demand.
54:58
Uh and it's been interesting to see from our side too as like large companies like jumping very early and like like a whole space is kind like pushing all the companies to like act fast.
55:09
Uh 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.
55:18
Um but then how have you so yeah so for for linear's agents product how do you evaluate how how open is the product if if somebody's building an agent can can they build an integration with with linear by themselves or are you guys really kind of uh doing your own internal testing to kind of qualify potential partners there?
55:39
Yeah, we're we're kind like looking more on the promotional side, I would say.
55:44
Like we believe in like open APIs and like trying to like have people access, but then I don't like the uh when it comes to like security and these kind of things, it comes more on like what do you like promote? Sure. Yeah. Yeah.
55:56
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.
56:07
Maybe you throw up a capture, but agents are gonna be able to solve those pretty quickly.
56:11
quickly. Uh, and so at a certain point you have to think like like you're you 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
56:26
or do you think that there's real durable value to um 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 Can't the LLMs, if they're really so smart, can't they just use websites? But
56:44
But what what's your take on that trend?
56:49
Yeah, it probably comes like down to like the user experience that you want to like offer.
56:52
So, you like uh controlling a computer or like VM or whatever.
56:58
Like that's the kind like the ultimate like bandaid to like everything.
57:03
Like it allows to do everything, but it's still like it's not purpose-built. Mhm.
57:07
But and like MCP to a degree is like look like similar.
57:11
It's just like a way to like do like do uh um request response like calls and get the information in and like share that.
57:19
information in and like share that. But then it's more about I think like in our mind it's like what is the experience like inside the product that like you're going to offer that maybe is like specific to a product u and how that
57:33
does how does that work like today like our implementation is like you know somewhat like rudimentary that we would expect like agents look like regular users but it's not very exciting to see the um the progress of the agent when they're like posting new comments. in the thread. That's a little bit of a in the thread.
57:51
That's a little bit of a hack uh that you kind like have to like live without while we still like see what's actually like required and like what can we like build to like better like support like the agent developers like what what kind of like experience to like give them.
58:07
Um of course like we're you know like looking at this from the lens of like linear uh of course like running the company and like building the product.
58:16
Uh but it's also like it's it's interesting to see how um the like where does the invocation of like agents happen?
58:24
Like is it like your CLI is like a text editor?
58:27
Is there like some kind like web tool or like the desktop app?
58:32
Um of course like for us it's like it's pretty natural like being like close to like where you work.
58:37
So like integrating into that workflow and I think like that's why a lot of like these like smaller companies especially like are pretty excited to like build in linear because they're already using linear themselves.
58:49
What what agent uh gets the heaviest usage internally at linear today?
58:55
I think it's being like couple of the coding agents but those were like the first ones to you know to the market.
59:03
No, I I mean I mean not even I mean specifically like your team at linear. Yeah.
59:08
Like coding 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.
59:18
We're just the interface for this.
59:19
I love I love horse races and I love having horses in races. Yeah. Pat, pick a horse. I know.
59:28
But like it's changing like every week as 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 open AI and so on.
59:35
So I just kind like it'll be like interesting to see like how those like play out and we're like looking for like working with like all of them of course but I don't like beyond like like currently the focus is a lot on just coding agents.
59:48
a lot on just coding agents. um like it's it's natural because there's a lot of like value to be created over there but I think like we'll in the next couple of months we'll start seeing much more like non-coding agents like augmenting like in alongside with the
1:00:05
coding agent so you might have a you might have a task where you have a you know like a feature like feature flagging like agent coding agent and I don't know like who knows a marketing agent like helping you out like write the change log blog post or and so Yeah. Yeah, that makes sense. Uh, are there Yeah, that makes sense.
1:00:21
Uh, are there any other AI features that you're implementing that feel like Windsor for cursor for project management?
1:00:27
cursor for project management? like something that like 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 two different patterns and it feels like the it feels like the market's bifrocating but no investors want to admit that
1:00:46
because they want to say it's going to be winner take all but in fact uh we're seeing two different paradigms kind of emerge or maybe even three different paradigms emerge um what are you seeing on the project management side yeah that's Um yeah I don't 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
1:01:06
Outside that where of course like linear is not only like issue tracking tool it's like for project management like organizing like your your work at the company level not only like individual level so and that's where kind like have like separate work stream of uh we're building like our own like AI tooling around that.
1:01:27
How can we augment the project managers and like the product leaders to like do their work better?
1:01:35
And that you could like imagine looking a little bit more like a a cloud or cursor like alongside your linear data and but like with that it's going to be interesting to see like how we can start like introducing like the external like agents or like MCPS as like part of that.
1:01:54
um that of course like the issues is that's like the first first step because like much more natural.
1:01:58
What's your team's approach to testing new for example coding agents right it's uh in many ways like the linear approach from my perspective is you know really thoughtful ideally long-term planning around building you know beautiful products and and taking a calm approach to doing this and and in in that way you know enabling other people to maybe have more calm uh uh effective uh product development.
1:02:30
Uh, but at the same time, like testing new tools, they can be super effective, but testing new tools can also be super distracting.
1:02:36
You know, we don't do a ton of engineering on TBPN.
1:02:41
We actually do a surprising amount um kind of like back office stuff to kind of automate production, but um I I can imagine an environment where you have, you know, call it 50 engineers and and on any given day, one of them can send a message into Slack, hey guys, you got to check this out.
1:02:58
it's like amazing blah blah blah and maybe they just got like a couple good results and it's actually not worth directing everyone's energy to but at the same time you want to stay at the edge but do you have a philosophy or kind of an internal ethos around testing new tools? Um not really.
1:03:14
I think like mostly comes from people themselves.
1:03:16
Uh we're not like enforcing like certain tools.
1:03:18
We're of course encouraging couple like couple of tools where we can you know like maintain like security and those kind of things.
1:03:25
We're like mature company at this point.
1:03:26
So like we need to we need to look after like our customers information and like a lot of like like also lives inside linear.
1:03:34
So you know we we need to like look after stuff.
1:03:36
look after stuff. Um but when it comes to like new tools like the 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 you put out like liners ways a little bit
1:03:53
more calm and I think like that also shows on the tool adoption and so on like you you're like excited like to try out stuff but like you know you take it with a grain of salt instead of like going on Twitter and like plasting like we replace all of our team like with AI. Uh I mean like that's one way to do it,
1:04:09
Uh I mean like that's one way to do it, but like that's definitely not us.
1:04:11
Yeah, nothing against that either, but yeah, the Clara method.
1:04:20
Not naming any I said I said it. I said it. I I respect it. It's good marketing.
1:04:24
It's good marketing, but it's not for everyone.
1:04:26
everyone. Yeah, I like that that's that's been like overall like when it comes to developing AI tools like we started like when like everyone else started like couple of years back when like the first GPTs like came out and I tried to do stuff and like you know
1:04:42
tried to build a chatbot and so on like but I think like very early on like we realize like well you get to like whatever 60 70% but like then it's like falls apart uh the experience and like it's And then it's really like hard to figure out like what's actually path to get to like the 95% where you want. This is the
1:05:01
This is the Apple problem.
1:05:03
You you linear and Apple have similar sort of like desires for perfection, right?
1:05:09
And and generative AI is in many ways completely imperfect, right? And and unreliable.
1:05:16
So that's an interesting it's an interesting challenge. Yeah.
1:05:20
But we we built we built a few things. We shipped a few things.
1:05:26
We didn't make like a maybe like the biggest fuss about it.
1:05:28
We're not the AI powered like issue tracking software uh raising like gazillion like dollars.
1:05:37
Uh but but raising customers though. Yeah. Yeah.
1:05:42
And I mean like in the end like they they want to get their work done and like do they want to like buy hype or do they want to like buy product?
1:05:51
Maybe today like you you want to like buy more like AI and that's where 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 like our we did a course correction over like the last u like roughly 6 months
1:06:06
ago when I think like the tools has got so much better like for me personally I was like on parental leave and like when the deepseek like came out and like just trying like the thinking mode was like the light bulb moment like I think interesting. Yeah. A little bit Yeah.
1:06:23
A little bit background on that.
1:06:24
I think just because of like linear 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 LMS like you have like inherent latency to it.
1:06:42
So it just felt like how do we how do we bind this like weight into the product that's instant. Yeah.
1:06:51
And I think like now with the the new like like thinking modes and so on like that has changed the like user like um what people expect like that paradigm and now we can like build towards that and like people expect take a little bit like more time uh and also like more UI patterns to support that but like you get a lot of value out of it. Totally.
1:07:19
Well, yeah, check out some of Google's launches from earlier this week. What was it?
1:07:22
They were doing 3,000 tokens in like half a second with the diffusion models. Yeah, very cool.
1:07:26
Um, anyways, this was awesome.
1:07:28
Congratulations uh on the launch this week and uh come back on again soon. Yeah, hopefully. Yeah, cheers. Later, Jory. Talk to you soon.
1:07:38
Um, we got Zack Weinberg coming into the studio and and we also have uh Doug Burnau from Radiant joining at 2:30 to talk about the nuclear which I'm very excited about.
1:07:51
Welcome to the stream, Zach. How you doing? I'm good.
1:07:56
You're like Welcome to the stream. Full soundboard now. Full sound.
1:08:01
We're getting better every constant.
1:08:03
What other product updates have there been since I was last here? Oh, I mean our Chirons.
1:08:10
Yeah, stop asking about Stop asking hard questions about our updates.
1:08:15
We're doing sponsor whoever makes the yellow drink.
1:08:18
I assume they're not sponsoring us to be honest.
1:08:24
Uh I I did grow up in the town that this company is from, but we have no connection. Proper affiliation.
1:08:31
Honestly, if anything, we should just we should just wrap these in in ramp yellow. We should we should.
1:08:34
Um, anyways, uh, good good to see you. Good to see. Yeah. Yeah. Good to see you guys.
1:08:41
Thanks for I mean, we wanted to have you on initially to talk about the most favored nation drug pricing EO.
1:08:44
Uh, it's been a week or two since then.
1:08:48
Um, there was kind of like, uh, I think it dropped Sunday. It felt like years ago.
1:08:56
Uh but but I mean it felt like Sunday like oh this is going to be black Monday for biotech. It didn't happen.
1:09:00
The biotech stocks did fine.
1:09:02
They also this was coinciding with the pullback on the tariffs broadly.
1:09:07
So the market rose overall.
1:09:08
Um can you give us how you process the information, how you're thinking about it now? Does this thing matter?
1:09:15
Should we even be talking about it? Should we just move on?
1:09:18
Yeah, maybe let's start with like why it's probably just like a misguided idea in the first place.
1:09:25
Um or at least the trade that I think Americans would need to understand that you're making and as it relates to drug pricing and um what I I think we may have talked about this last time or I've talked about this with a lot of people like the the idea that America pays a lot for new therapeutics, right?
1:09:42
and and and we do we do by the way like this idea that we pay materially more even on like a GDP adjusted basis than other countries and in particular other wealthy countries.
1:09:56
So you take Europe is probably like the best example where the amount that we spend on new therapies as a percentage of our like what's called GDP adjusted price sure if you will is is still on the upper bounds.
1:10:10
So like America pays for the innovation uh for the rest of the world.
1:10:14
But don't we don't we get the innovations like 5 to 10 years faster than the rest of the world?
1:10:21
We definitely get them faster.
1:10:22
Um we are usually the first place all these new drugs launch.
1:10:26
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.
1:10:35
It's it's you know socialized medicine right?
1:10:36
So, it's like a single budget.
1:10:38
And then there's also the 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.
1:10:48
So you might see that uh some uh like Alzheimer's drug is 10 times or or a hundred times the headline price in America versus Japan but realistically Americans are paying three times more, five times more, which is still a lot, but it's not it's not the scary number that people often quote.
1:11:07
Personally, I like I like paying more for drugs because it inspires me to grind harder. Yeah. Right.
1:11:14
I think many Americans Which drugs are we talking about here?
1:11:15
Uh, caffeine, nicotine, protein, protein, testosterone mostly. Protein. Yeah. Yeah. Yeah. Yeah.
1:11:24
Full just TRT juicing before the show. Um, no. So, like we do pay more.
1:11:26
Um, was where I was going on a net basis like where when you add in all the discounts that are 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 is like $65,000 a year." That is the list price.
1:11:44
And so, you know, the media doesn't understand net pricing versus list pricing.
1:11:50
And so, the headlines are much more sensational than they uh actually are in reality.
1:11:53
But yes, the delta still does exist.
1:11:55
Um and we are we do pay more.
1:11:58
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.
1:12:09
And I and I just think that little like piece of this is really hard for most people to understand which is like biotech.
1:12:15
There's this really amazing analysis that was done by RA Capital which is like a giant biotech venture fund.
1:12:19
And yeah, we had their one of their principles on the I think the Monday after super sharp group top five you know doing mostly public but like this is like a you know expert expert expert group in in therapeutics.
1:12:29
We have Tess Cameron on Yeah.
1:12:32
And they have like a few hundred people.
1:12:34
Their founder Peters is super sharp.
1:12:35
Um we respect them a lot.
1:12:38
They actually were investors in one of our company's next rounds all that. Anyway, good group.
1:12:41
Um they did a very beautiful analysis of the uh expected value of a biotech investment at various rounds seed round, A round, B round, so on and so forth.
1:12:52
Like what is the EV of a dollar that you put in?
1:12:54
And I will tell you that at both seed and series A, the EV is negative. Mhm.
1:13:01
Negative at our current prices.
1:13:01
And and and the reason for this is like drug discovery is the single hardest problem that you will ever encounter in your life.
1:13:10
Uh 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.
1:13:19
You have to take all this insane amount of risk and spend tons and tons 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.
1:13:28
And like yes, that's useful, but it's not a human.
1:13:34
And so like the amount of companies where cuz you don't see this in tech, right?
1:13:38
You don't see companies that have raised $300 million do one product launch and then go bankrupt. Yeah.
1:13:45
And like that happens all the time in biotech.
1:13:47
That's actually like the norm is basically, you know, you've spent a few hundred million, you think this thing is possibly going to work, it works in a dog, it works in a monkey, whatever.
1:13:56
The drug-like properties seem all really great.
1:13:58
And then you run a human clinical trial for $150 million and it doesn't work and the company's bankrupt and everybody loses their money and like and it's not like 20 million, it's like a hundreds.
1:14:08
So, you know, biotech is is an expected value negative investment business um even at current prices.
1:14:16
And so what that means really quickly, is that just a power law thing where where the best about biotech venture funds are doing great at seed and series A?
1:14:24
Um, and just like, you know, there's plenty of funds that I could point to in consumer SAS or enterprise SAS that are terrible and negative EV, right?
1:14:33
I don't think I don't think you could point to the asset class being negative EV. True, true, true. Right.
1:14:38
Like, yes, there's always a skew in the results, but here we're talking about the entire asset class is negative EV.
1:14:43
And so if you're on the front end of it, great.
1:14:45
But like, you know, it's rough.
1:14:48
You stick it in the middle, you lose money.
1:14:50
In tech, I don't think you get the median fund in tech and you lose money.
1:14:53
Like it doesn't no fund might be like one and a halfx or something. Exactly. Yeah.
1:14:58
So it's not shifted this way. The whole category.
1:15:03
Why is it shifted this way?
1:15:03
There's a bunch of reasons.
1:15:05
The biggest one in my opinion has to do with this concept of called like better than the Beatles which is basically like it's a very simple idea when it clicks for you.
1:15:13
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.
1:15:27
In most cases, it's not like a water, you know, sugar pill, right?
1:15:31
It's like the current thing.
1:15:32
And so as we get better at treating the current thing, the bar gets higher.
1:15:39
So it actually like the better we do at drug discovery, it gets harder, not easier.
1:15:44
You see that with payroll software.
1:15:47
Unless you're better than the best payroll software, you shouldn't be allowed to promote your product.
1:15:52
Well, and even more, like here's the crazy.
1:15:54
You shouldn't be allowed to launch. You shouldn't beow. Here's the analogy.
1:15:57
You wouldn't be allowed to launch the product. Okay?
1:15:58
The government would say, "No, no, no, no.
1:16:03
You cannot launch until you are better than the current isn't better than ramp, so you can't launch." It's just ridiculous.
1:16:11
Could you imagine that world where you're like, "Oh, my new, you know, someone would launch like, I don't know, fat GBT search engine."
1:16:16
And then like the federal government's like, "No, Google's better. You can't do that. You're better." Yeah. Yeah. Yeah.
1:16:22
That is how biotech works.
1:16:24
That is how biotech works.
1:16:26
And by the way, is that the right is that the right way for it to work?
1:16:32
Does that contribute does it I I you have to imagine it contributes to prices being high because it's somewhat anti-competitive, right?
1:16:40
If I like in the payroll in the payroll market, right?
1:16:44
Like a payroll platform gets super bloated.
1:16:46
Some founders like and it and it costs, you know, $100 an employee.
1:16:51
Some a founder comes in, launches an okay version.
1:16:52
Also, there's just less iteration on drugs, I would imagine, than on software, right? No. No.
1:16:59
You can't like iterate through it.
1:17:00
There's no like learning.
1:17:00
You got like it's it either is better or not. Um, here's the problem.
1:17:04
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. So, exactly.
1:17:12
Now, if you if you were on the hook or maybe you saw some of the rebates and, you know, went into your pocket, make you maybe you'd be like, "All right, you know, like my psoriasis isn't like that bad."
1:17:21
Yeah, I'll take the like 30% less effective drug and I'll like clip some, you know, coupons and but that we don't do that because, you know, in in America, we view healthcare as like it's supposed to be free for everybody.
1:17:35
Uh, and so we kind of do it with with over the counter stuff like if you get like the mucin x extra strength m max like it might be $3 more than just like generic stuff.
1:17:45
Try telling try telling the cancer patient that you're going to get the less effective like you're just not going to do it.
1:17:51
And so, you know, the FDA is kind of like, well, what's the bar is current standard of care.
1:17:56
That's the standard we've put in place.
1:17:58
Y 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.
1:18:12
And so cheaper doesn't win, right?
1:18:12
Like you can't shift because the the patient at the end of the day does not want the worst drug.
1:18:19
like I can't even I there's so many situations where you're just like absolutely not especially in in serious disease, chronic disease, cancer, all the stuff that really matters.
1:18:27
So, going all the way back to pricing, one of these like weird weird issues in in biotech is is simply like as the industry gets better, it gets harder, not easier, which is there there's almost like no other industry where that is true. Yeah.
1:18:39
And so it's the opposite of learning curve pricing.
1:18:43
It's like the opposite of fabs, the opposite of software, the opposite internet. Yeah.
1:18:47
internet. Yeah. So 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
1:18:57
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 like how much music would you really have and that's that's the I I like I like the phrase because it it whatever catchy like the Beatles. Uh anyway, so
1:19:08
Uh anyway, so it is it does the the one thing I'll say is it has an interesting effect of of pushing for true excellence, right?
1:19:16
Like that does not happen that certainly doesn't happen in SAS.
1:19:22
There's a lot of people that see a good SAS product and they're like I can make a okay version of that and make a couple million dollars a year. Totally.
1:19:29
There's less cynicism and there's less like we don't have a slop problem in in farming.
1:19:33
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?
1:19:40
You've got to build the best drug before you put it into people, right? There is no tweaking.
1:19:45
So, I I I say all of this which is to say like yes, drugs are expensive in the United States.
1:19:50
Um but like if you wanted cheaper drugs today, you are basically not going to get any in the future.
1:19:59
And I know everyone's like, "Oh, that's not true." Blah blah.
1:20:03
Like I am on the front lines of this every single day.
1:20:05
I mean we are one of now one of the larger biotech venture funds at seed meaning like we take the most risk.
1:20:11
We're in that negative EV category.
1:20:12
Uh built different risk on risk. Yeah. Yeah.
1:20:16
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. You can't.
1:20:30
I mean, just to be very clear, like, you don't need to do this, right?
1:20:34
Like, you could you could walk away from the game, right? And there's that.
1:20:36
And by the way, me, it's it's our investors, our LPs.
1:20:41
Like, if if 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?
1:20:51
Like there's this, oh, money will always be there. No, absolutely not.
1:20:56
And so, you know, you need a reward on the other side of it.
1:21:00
Um, and I think that trade is really hard for people to think about because you're like, well, it's a lot now.
1:21:04
And you're like, yeah, it's a lot now, but if if it's 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.
1:21:13
Your kids are not going to be any better off from a medicine perspective.
1:21:16
So, the reward does have to be really big.
1:21:17
But at the same time, like, do the Europeans kind of like preload off of us? Yes.
1:21:22
And so this kind of like rough idea of like all right this is what what they're trying to do is say we're going to index the US price to like a basket of of comparable international countries basically like wealthy first world countries mostly European countries and that we can't be like materially higher than they are on a GDP adjusted basis.
1:21:43
Uh at least that's the idea behind the executive order. Um maybe two thoughts.
1:21:51
one all this will not take it drug US drug prices down it will not happen uh what will happen this is not a good thing is it may force first of all okay this is likely not enforceable I don't believe the like legally I don't think the EL works and that's part of why you didn't see the biotech market react is
1:22:09
every expert took it seriously yeah like it's not there's not it'll fail in the court a thousand 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. Yeah.
1:22:24
What about what about the is 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.
1:22:34
And so like if you take that basically that's like investment that's sort of like you know non effectively uh the biotech industry gets the benefit of yeah like the negative EV bets are already being subsidized to be closer to zero but not you know this administration is doing absolutely everything it can to destroy the future therapeutics that you want.
1:22:57
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 you cut skilled immigration do you know who is like half
1:23:14
of biotech if you go to like any biotech company's website you go to our usually somewhere between 30 and 50% of the people on staff are foreignb born 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. Mhm. And so, you know, we Mhm.
1:23:28
And so, you know, we already have a science a skilled scientist shortage and that's even with current immigration.
1:23:34
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 going to have a massive, you know, skills gap.
1:23:42
This isn't like bring manufacturing back.
1:23:44
This is like you need to be a PhD in chemistry plus 15 years.
1:23:47
Like, these people don't exist.
1:23:50
And so, you know, most of our senior team at at at Cury is is foreignb born. Yeah.
1:23:53
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?
1:24:03
And and it's not because it wouldn't be like job displacement if that happened.
1:24:06
So and like biology and chemistry PhDs and protein like specific types of PhDs, you know, do do we need like marine science PhDs?
1:24:14
You know, 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 Brian Johnson's We're looking for scientists, not crazy people.
1:24:26
Uh so, you know, no, we need we need a million uh you know, David Lu at MIT.
1:24:33
And uh what about uh what about that guy in China uh Hood Jong Qui?
1:24:37
Have you been following this guy? He Yeah. Yeah. Exactly.
1:24:43
And he posts these like very vague posts where I thought it was an AI 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.
1:25:07
Have you been tracking that story at all? No cuz it's like fringe.
1:25:10
It's like you know it's it's like the New York Post of Science. Yeah.
1:25:14
What about I want to go back cuz 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.
1:25:26
You're like these are these people are so stupid and I hope they're listening.
1:25:29
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.
1:25:43
It's like is it is idiotic.
1:25:43
Um, but even even if you say like we're going to index the US price to international prices, remember that the United States is a giant country.
1:25:53
You have 350 million people.
1:25:55
We're the wealthiest in the world.
1:25:55
Like all 50% of farmer revenue comes from the United States. Mhm.
1:25:59
Uh, and then you have like Japan is kind of second. Okay.
1:26:04
So now put yourself in the shoes of a pharma company, right?
1:26:06
You're gonna index, you're gonna index our price to the European price and let's say the Europeans are like 15% of your revenue and the Americans are 50.
1:26:14
Are you gonna lower your price? Absolutely not.
1:26:16
You're just going to raise the European price. Yeah. Right.
1:26:20
And just to bring it up because you can't lose the US revenue. Yep.
1:26:24
So like you'll never give this revenue up.
1:26:25
So the price the US price will not change. This does not work.
1:26:26
All it does is it may even if it were legal, it may force pharma to bring its European price up.
1:26:33
And you know what happens when that h because this is like and then what the Europeans are 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 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.
1:26:53
It's the only place you can make money and pharma is in the US and that price is not coming down.
1:26:56
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 if if the profitability of pharma comes down you know what they stop doing buying biotech companies right all of us the same
1:27:16
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
1:27:32
How do how do uh how do companies get valued if they have one drug that's like working and maybe it's the best, right?
1:27:40
So, it's actually able to be in the market, uh yet there's a sort of uh sense that there are very real competitors that might come in with a drug that is substantially better.
1:27:53
Like h how is a pharma company that's you know exploring M&A going to value that?
1:28:02
Is it still the same same?
1:28:02
This is this is what they do all day.
1:28:04
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 s what are peak sales and how long am I going to be able how long is my patent
1:28:22
right what do we what do we expect generic competition to come to 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 going to work. So do
1:28:39
So do we think it's going to work?
1:28:42
Why do we think it's going to work?
1:28:43
If it does work what are the sh 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?
1:28:58
So like this is this is day-to-day you know biotech pharma commercial analysis.
1:29:03
there are very very smart people who do this.
1:29:04
Uh you know this is what the public hedge funds do what the RA guys will do you know and it's it's it's deep science.
1:29:10
Um 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.
1:29:29
you won't even really know because it's the drug that never got started in the first place.
1:29:36
And then eventually what you're doing is you're outsourcing all this to China because the Chinese will pick it up and and and do we could have a longer conversation about China.
1:29:41
So all all of it is just kind of like stupid.
1:29:44
Um the other thing I would say we have to jump but like this is my defense of of of of medicine in uh therapeutics if you will as like a great investment. They go generic. Yeah.
1:29:59
like 9 to 12 years let's say roughly these are generic which means they are basically free for you in 10 years I know your kids and your grandkids and your future kids like 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
1:30:15
like window in time like yeah you know you got to eat it you're going to eat 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 why why is there so
1:30:31
surgeries. Like why why why is there so much focus on the therapeutic which is also only about 10% of of of medical spending is drugs which then eventually goes generic versus the 90% of it which is basically physicians and those
1:30:48
physicians they're not well it's because the margins right strikes you as something that like the pill only costs a cent to make and so exactly just emotionally you think about high margin things as wasteful what's something positive that could come from the EO. We
1:31:01
positive that could come from the EO. We we we had a uh infamous uh healthcare exec 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 DTOC pricing and which might have been why
1:31:31
consumer D like Healthcare is about the new drugs that are really expensive, not like consumer DTOC pricing of like you know whatever consumer medicine like I'm talking about real healthcare very sick chronic disease people with neurological
1:31:49
conditions with with cancer with heart disease like the serious stuff which is what we I just saw a company that they'll give me one pill that has uh erectile dysfunction medicine and hair loss medicine in one pill. Is that not
1:32:00
Is that not real medicine? What's going on? Those are generic meds. Sounds like amazing. It's amazing.
1:32:06
And And you know why they're so cheap? Yeah. Because they're generic.
1:32:09
Because 15, 20 years ago, we invented this We, you know, Fizer made like a crap ton of money selling Viagra. Yeah, that's right.
1:32:15
Everybody now you get to get your six in one dick pill for $3.
1:32:19
And like that's a pretty cool deal, right?
1:32:23
Like it's cheap and all this like shores there's some like gross to net whatever.
1:32:26
That's not what healthcare is. That's not I'm sorry.
1:32:30
Like hair loss is not healthare. Mhm. Interesting.
1:32:32
Uh what about crisper on demand?
1:32:35
Uh there was this uh this infant child that was saved with a custom gene therapy.
1:32:39
Uh it seemed like a very inspiring story.
1:32:42
There was an inspiring video all about it.
1:32:44
It seems like an amazing testament to something we've been hearing about for a long time which is Crisper.
1:32:50
Maybe a decade we've been talking about this.
1:32:52
Is that an opportunity for new companies?
1:32:53
Is that is there already a company that's like ripping on the back of this or is that just kind of like an outgrowth of what we'd expect with the technology given the maturity?
1:33:02
I believe the company that did this was Beam Therapeutics. Is it them who did it? Yeah. Um yeah, it's cool.
1:33:12
Uh this is this I mean this is a perfect example, right?
1:33:14
Which is like that I think it's being I gota I can't remember off hand which one it is.
1:33:18
Um they that company that that successfully developed this uh this therapeutic is trading for less than money raised. Whoa. Wow. Okay. Silence. It's terrible. Right. And why?
1:33:34
Well, because like these gene editing technologies where you're going after essentially like disease that is very clearly defined by some mutation in your DNA and that's a that's a small subset of total disease.
1:33:45
It's like very very rare conditions that this applies to.
1:33:47
So like the market the way I think about it is like the patient market for this technology is is very small.
1:33:52
These are horrible diseases that in theory can be can be treated through gene editing.
1:34:00
There's not that many of them but you can you can do some really amazing things if if you can if you can make these edits which is the first time this has ever happened.
1:34:08
But like if you add up the patient population of like all of these conditions where you could possibly do this it's not that many.
1:34:15
It's I don't know the math off hand.
1:34:15
I bet you it's probably like tens of thousands at most. Mhm. Okay.
1:34:18
And so like plus the variable cost of manufacturing this stuff on a per patient basis can be hundreds of thousands of dollars.
1:34:25
Are we going to get some blockbuster gene editing for hair loss and then we're back in business? No.
1:34:30
Uh because hair loss is not, you know, there's no like one base edit to, you know, fix hair loss.
1:34:34
But yet I think I think like this technopessimist on my stream, Zach.
1:34:43
Well, one one of the things you learn as you go into science is that the DNA is not actually the whole story.
1:34:46
It's not even close to the whole story.
1:34:47
And so like it's not even say there's is vibes a part of it.
1:34:54
Is that is that it's actually astrology? It matters.
1:34:56
You have to take any kind of the DNA but also astrological sign.
1:34:58
Uh infamous astrologologist.
1:35:00
I mean vibes are kind of like it in a way that like your behavior as you're alive does affect your epigenetics of the deal.
1:35:07
Your epigenetics matter, right?
1:35:10
like you sit in in in uh smoke all day like you're going to have some problems.
1:35:14
Uh anyway, I I think I I like this as an example because this company that just made this like unbelievable breakthrough.
1:35:20
This has never been done before in humans.
1:35:23
They're curing diseases now trading for basically less than cash raised.
1:35:25
I got to go find the name again.
1:35:30
I swear it's So So there's uh I I I just got an answer.
1:35:33
So this was a bespoke crisper base editing drug.
1:35:35
It was built and tested by physician scientists at the ch children's hospital of Philadelphia and Penn Medicine with translational help from innovative genomics institute at UC Berkeley.
1:35:48
Reagents and GMP grade components were donated by several suppliers including Acutas therapeutics and integrated DNA technologies and Aldveron uh both Danaher companies for guide RNA and on that one there was another uh there's another story.
1:36:02
Yes, there was another story and I have to find it.
1:36:06
Um, which well we we will have to we 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.
1:36:16
I think it'd be very interesting to see.
1:36:17
By the way, imagine just imagine if that becomes a drug and we go, "Oh, we can only pay $20,000 for it."
1:36:24
Do you know what happens to that drug? Sits on the shelf. Sits on the shelf. No one ever does it. No one ever makes it.
1:36:29
And there's your drug pricing in in reality, which is like, well, there's got to be a reward.
1:36:36
So, we're pro higher drug prices.
1:36:36
I guess you build us on that. We want that.
1:36:41
We want the highest prices possible is what I'm hearing.
1:36:42
You want to f You'll get a lot of You You put real high prices like people will come and and and take risk.
1:36:47
You know, I'm sure there's some balance.
1:36:50
We got to have we we need we need like here's my favorite stat. Here's my favorite stat.
1:36:58
the the I I I'll pull these for you.
1:36:58
So, I don't want to sound like an just like spitting numbers that aren't true.
1:37:02
Uh 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.
1:37:12
Uh we spend more on cosmetics than we do on medicine. Wow. Cosmetics. Good for America. We're looking good. What about fast food?
1:37:22
What about we might be dropping dead at 45, but we're going to look good doing it.
1:37:27
Uh, thanks so much for stopping by. This is fantastic. We'll talk to you soon. Always a pleasure. Cheers.
1:37:30
Next up, we have Lee Marie Brasswell from Kleiner Perkins coming in, former uh colleague of mine at Founders Fun briefly.
1:37:37
Uh, excited to talk to her about artificial intelligence, AI agents, all the news of the day. And we'll bring her in.
1:37:45
And we got some we got some good Chirons for her coming up.
1:37:48
We'll see if we can get them up on the stream.
1:37:51
What do uh what are we what are we talking for her?
1:37:55
The term she tyrant herself.
1:37:57
Lee Marie, are you there? Can you hear me? How you doing? Oh, what's up, Kugan? How's it going? It's good.
1:38:01
Uh what's uh what's new with you?
1:38:04
I'd love to get your initial take on uh AI week.
1:38:06
We got Microsoft Build, Google IO, Open AI IO, we got Claude 4 from Anthropic.
1:38:13
It's been a massive week.
1:38:16
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?
1:38:23
Well, I guess just to start off and it's so good to see you again.
1:38:27
It's been it's been a while.
1:38:29
So, yeah, thanks for having me on the show.
1:38:30
Um yeah, it's there's never a dull moment really, you know.
1:38:33
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.
1:38:43
Um, and so yeah, I mean I think the big thing that's actually there's so much this week.
1:38:47
I mean, right, you know, starting with some of the stuff you said, the best time to be a technology podcaster, investors close second, but podcast is really where you want to be.
1:38:57
That's where the action is because every day there's new news.
1:39:00
Anyway, yeah, what is sticking out to you? Hey, Jordy. Um, hey.
1:39:02
So, so there's um the I mean the IO acquisition in particular, that news.
1:39:08
Um, what an incredible video. What an incredible team.
1:39:11
Um, I mean, just really showcasing OpenAI's ambition to really, you know, get into get into a lot of stuff.
1:39:16
And I mean, obviously there's a lot of speculation about what the device will look like.
1:39:20
I was actually looking My favorite, sorry, sorry to interrupt.
1:39:22
My favorite part was uh John and I are, I guess, exhaul monitors.
1:39:26
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.
1:39:35
The these two scenes aren't real.
1:39:38
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 what is this? That's very silly.
1:39:49
What do you expect, you know? Yeah. Yeah. Yeah.
1:39:54
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.
1:40:04
I was looking it up on on 03, but 03 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 IO, um, Johnny Ives company, but it might be one of the largest, if not the largest sort of pre-product acquisition of all time.
1:40:18
So, you know, I mean, $6.
1:40:18
5 million is a lot of money.
1:40:21
Yeah, we've been noodling on a couple points.
1:40:22
It's a couple points for a key exec. Exactly.
1:40:26
It's 2% of the company, which when you think about bringing in an executive at that level, that like comp for that industry, it's not that crazy to get to that number.
1:40:34
And then today in the Wall Street Journal, Sam Alwin was quoted saying that if they can nail it and get a major consumer device, that's a trillion dollar opportunity.
1:40:40
And that sounds crazy, but you look at Apple's market cap, you look at, you know, Android, Samsung, like, yeah, there probably is a trillion dollars in market cap.
1:40:48
There was also there was also the the tinfoil hats saying like, oh, he's trying to dilute the profit.
1:40:52
It's like, you know, that they're issuing billions of dollars of stock to employees like all the time, right?
1:40:59
like this is not some like you know crazy conspiracy.
1:41:01
I I I do want to get your take on the actual device.
1:41:06
We we've seen some pre- render some AI images around like a pendant with a camera on it, the her model, maybe it's an earpiece.
1:41:13
I imagine you get pitched a lot of AI devices.
1:41:14
We've seen the rabbit, the humane, the friend.
1:41:18
Uh, are there any other uh any other ideas that you've seen that could potentially be um just AI devices, even not from Open AI, but just in general?
1:41:29
Because Apple's got it pretty well covered.
1:41:31
They got your ears, they got your eyes with the Vision Pro, they got your phone, the watch, the iPad, the laptop, the desktop.
1:41:36
Like Apple's there's not a lot of white space in the Apple catalog, but um it'll be interesting to see if somebody can come up with something that's new.
1:41:44
Have you seen anything that's interesting?
1:41:45
Oh man, I really wish I could I could tell you about it, but yeah, we actually have a company in Stealth.
1:41:49
I can't say much, but there's certainly different, you know, the show when they're ready.
1:41:52
Yeah, I I'll be super excited too, but people are being really creative.
1:41:58
Um, and then also, I mean, just generally, and I'm sure you're seeing this too, just given like the pace of h how much is happening and then also the competitive nature of these markets.
1:42:07
Like it's clear that there's this big prize maybe bigger than ever before. Yep.
1:42:10
And so if you 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?
1:42:20
So, yeah, I'll be excited to to share more on that.
1:42:21
Um, yeah, there's also I feel like people have just been generally willing to fund hardware, but also kind of categorically bearish, right?
1:42:29
People are just like, oh, like hardware is really hard.
1:42:31
Like I'm going to make this bet, but like it's really hard. Hardware is hard.
1:42:34
Used to be about supply chain.
1:42:36
It used to be about all the things that can go wrong.
1:42:38
But then also look at working capital.
1:42:39
We're at a point where like Aura and Whoop are like big businesses that I you know I don't know like ultra specifics on either but I I bet that Aura will be a really big company in 10 years.
1:42:53
From my perspective it's almost harder.
1:42:54
It's not it is hard to make the device and manufacture it and deal with the fact that 90% of your revenue comes in Christmas.
1:43:00
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.
1:43:12
But um what what what are you looking for in hardware startups that you're looking at?
1:43:18
What are the pitfalls that you want to see founding teams overcome before potentially backing them? Yeah.
1:43:25
So I'll I'll say I don't have a massive background in hardware.
1:43:29
hardware. I mean I will say I was I was at scale you I worked relatively early there um for you know and was an engineer there for four years and then a PM um and we worked with a lot of hardware companies there so I mean the main customer of scale back in the very early days was self-driving car companies um and robotics companies um
1:43:45
and so I have seen just through to working with them as customers you know some potential pitfalls and I mean you know the the quip is that hardware is hard um you know that you've got all of the challenges of building a company and then you've also got to just manage supply chains and you have to be a lot more careful about, you know, the economics. You know, software is usually
1:44:03
You know, software is usually relatively high margin or it's easier to make it high margin.
1:44:07
Hardware obviously much harder when you've got to figure out where all these materials are coming from and ramping up.
1:44:11
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 a 100red million people on a website in the day.
1:44:26
you you just can't ship a hundred million things anywhere in any reasonable amount of time. It just takes time. Um like maybe one day.
1:44:31
Um but yeah, it's like interesting to remember like Whimo was founded in in 2009. Yeah. Right.
1:44:37
So like just as that like it took overnight 20 years to now become this overnight success.
1:44:42
But yeah, you mentioned robotics.
1:44:43
I'm interested in the pools of training data that are out there.
1:44:47
Uh we've been joking about scale AI.
1:44:50
Are they going to put everyone in motion capture suits eventually to get to the humanoid data sets?
1:44:53
There's also a lot of work being done in in simulated environments.
1:44:56
Uh is there a data wall that we're going to run into with humanoid robotics?
1:45:00
How are you thinking about the data challenges in robotics generally, whether that's in the humanoid side or or elsewhere?
1:45:06
Um because it feels like the humanoid narrative is taking hold.
1:45:10
People are funding companies. It's getting big.
1:45:12
But if it's a 16-year journey like it was with Whimo, we could be, you know, in for in for a long one here. Definitely. Definitely. It's been interesting.
1:45:22
I mean like I do think there are a lot of really good arguments for why we'll see robotics pro uh like progress accelerate.
1:45:28
Um 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 some of the early transformer based models.
1:45:44
Um though with an asterct like as as we're now moving into agents I actually think you have to be more intentional about creating different types of data.
1:45:50
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
1:46:05
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 to sort of scale these systems more effectively. However, I
1:46:19
However, I mean with robotics, it's always a little little bit challenging to tell what that exact timeline is. Yeah. Interesting.
1:46:27
Um, we were talking earlier about uh the agentic, the coding market, the AI coding market.
1:46:33
I was kind of breaking it down to you in it three markets, is it two markets, is it synchronous work, asynchronous work, is there a consumer, proumer, bottomup enterprise, top down enterprise, sales motion?
1:46:46
um how are you thinking about just AI coding generally as a market as the businesses uh evolve?
1:46:56
Uh 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.
1:47:01
My favorite my favorite topic of conversation or definitely one of my favorite is is uh AI codegen um near near and dear to to my heart.
1:47:07
But um yeah, as a disclaimer, so I'm I'm on the board of this company Windsurf.
1:47:11
Um so Agentic IDE AI powered developer tooling uh platform. Yep.
1:47:16
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 thing hopefully things will go well like hopefully market will be there and I just don't think anybody um I don't think anybody really saw this coming just in terms of like how widespread tools like Windsorf would become. Yeah.
1:47:39
Um and so right now, you know, you're certainly seeing like there's this sort of segmentation specialization.
1:47:43
You know, you have tools like Windsurf and Cursor um that are, you know, proumer.
1:47:51
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.
1:48:04
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.
1:48:10
And you know, it's just been incredible seeing like, you know, even even though I talk about Windsor all the time, my father-in-law, who I never mentioned it to, not a programmer, just like once he was on a on a we were just talk all talking, he's like, you got to go, you're a VC, you got to go check out this company, Windsurf, I'm like using it to like, you know, help me out at work and create apps.
1:48:28
And I'm just like, wow, this is incredible just how widespread he's like, you know, outside of Silicon Valley, all of that.
1:48:33
So, so for those types of tools, I mean, you don't have to speak about wind service 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 seatsbased plan like how is how is the market for AI tooling in the enterprise evolving in terms of pricing?
1:48:59
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.
1:49:06
You could imagine charging someone for lines of code that get approved in poll requests or seatbased or usage based or just pure inference based.
1:49:16
So how is that how is that side of the market just evolving broadly?
1:49:19
broadly? Yeah, I mean so what we're seeing is you know there's certainly the proumer segment for these tools but it very quickly um 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
1:49:34
segment um and so it's you know we're both we both have a large enterprise sales team and then these tailwinds from now all these proumers and then you know sort of like professional developers that that pick it up on their own and bring it in into their company. Um, I
1:49:46
Um, I think pricing it's it's always interesting.
1:49:49
It's something that we constantly think about.
1:49:50
It's a very competitive market.
1:49:52
So, I mean, you know, you also have to kind of pay attention to to what other people are doing.
1:49:56
I mean, per seat easy to understand.
1:49:59
Um, but then, you know, obviously a lot of these models co, you know, cost money to run and so you've got to figure out some sort of either credits or usage system.
1:50:05
Um, I don't think, you know, in coding where you get 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.
1:50:15
um like maybe you know I've seen sometimes in like customer support and things like that.
1:50:18
Um but yeah, certainly having like a usage element I think is pretty pretty pretty cool. Yeah.
1:50:22
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 and the the TAM is, you know, a trillion dollars because they're just adding up like global payroll for like that type of work."
1:50:41
Like what's your reaction to that?
1:50:43
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.
1:51:00
Yeah, I mean def definitely definitely some good points.
1:51:02
I mean generally generally I'm pretty optimistic.
1:51:05
generally I'm pretty optimistic. Um I think now just like kind of living through the codegen 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
1:51:22
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 it turned out that there's 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. Uh and then
1:51:37
Uh and then also just like I think the market blew my mind. What was the secret?
1:51:42
What was the secret to either the the challengers to GitHub Copilot?
1:51:47
I I haven't really used them.
1:51:49
Um is it is it more driven by uh flexibility around which model you're plugging into and and 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?
1:52:03
So I forgot the exact date.
1:52:03
GitHub copilot started I think open AI only given the sort of relationship but it relatively quickly moved to an option.
1:52:11
So it's so you can put in cloud 3.
1:52:11
7 sonnet which everyone loves. Yes.
1:52:13
And I think actually recently um you know I think I was reading this this morning but you know you know GitHub announced like okay for these particular features we're going to go with anthropic only like particular backend features.
1:52:25
So it's clear like you know there GitHub is not locked in to one model provider.
1:52:29
I think you know what cursor, wind surf and others have done is just create you know different product experiences.
1:52:36
Um and obviously get 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.
1:52:48
Um, 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.
1:52:57
But I mean, we are in the world where now software can do work.
1:52:59
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.
1:53:06
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.
1:53:14
So you kind of get all these kind of bonus markets that you know TV you know end up being just like this hu huge thing.
1:53:21
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.
1:53:30
I mean the the most obvious example was windfropics new models.
1:53:38
uh which seems uh you know I'm sure you can't comment on that specifically or maybe maybe you want to come in with put him yeah put him in the hot seat but um but yeah I I it just feels like it feels like it feels like a very real tension that's going to have to get resolved quickly because these are all big companies now or at least the main players are big companies.
1:54:04
There's billions of dollars of revenue on the line and uh everybody's in a you know constant race to be at the edge. You're right.
1:54:14
I pro probably shouldn't say too much.
1:54:15
Um I mean what I what 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.
1:54:24
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.
1:54:31
You know, I do ultimately think that, you know, I'd be shocked if in a year or two we don't see codegen 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.
1:54:46
I just think that that is something that a lot of people are building towards.
1:54:51
It's like there isn't a great experience today that kind of has both. Yeah.
1:54:54
Um at least, you know, sort of a generalized both.
1:54:57
But I mean ultimately like all these companies are I I think going to in the in the sort of like 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 want to be able to you know give yourself really favorable favorable economics.
1:55:14
So yeah, it's it's going to be a super exciting even, you know, probably probably 6 to 12 months, I imagine.
1:55:23
So legal the the sort of legal AI space has been heating up.
1:55:27
Kind of a weird, you know, interesting comp.
1:55:30
In many ways, it felt like cursor had like a ton of mind share and then wind surf just kind of exploded.
1:55:36
People realized how quickly it was growing.
1:55:38
At least that was my perception.
1:55:40
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 Lora uh came out of feels like it came out of nowhere and they raised a big series B this week.
1:55:57
Is there are you do you have a a a kind of prediction or a take on what the next category to see these sort of battles play out?
1:56:04
I'm sure you guys already have some bets in whatever category that is, but she's already on the board of four companies that are going to dominate it.
1:56:12
She's like the next four categories.
1:56:13
Actually, I didn't jump to the board meeting in exactly what you just said. Yeah. Yeah.
1:56:19
Um, you know, I'm I'm I'm very lucky in that, you know, I think I mean, even before I joined, so I've only only been at Kleiner Perkins for two years, and even before that, a lot of my partners made really great app investments.
1:56:28
So for example, my partner Moon incubated Glean um which is now you know kind of the enterprise knowledge discovery um platform in this kind of new new AI era.
1:56:39
Um so certainly like we've got a lot of apps in the portfolio.
1:56:42
I mean Harvey we you know did their series B um Ambience which is a medical scribe also in the news recently.
1:56:49
Um we did their seed in series B.
1:56:51
Um so and then you know we have some some investments in sort of sales AI as well.
1:56:55
Um, 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 sales people with AI.
1:57:02
Um, 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.
1:57:10
Um, those are kind of like the the battleground spaces.
1:57:14
These are where it's going down right now.
1:57:16
Like it's clear the models work for the use cases.
1:57:17
It's clear there's a giant prize at the end.
1:57:19
And so you've got, you know, inevitably a lot of companies competing for it.
1:57:22
Um, in general, especially with software, you know, I think it's basically impossible to be the only company in your town.
1:57:29
Can you can you fund a company that will just pick up the phone when I get like a robo AI call that's like trying to do some social engineering hack or whatever and just pick up the phone and waste their time really inexpensively.
1:57:40
That's I feel like that's what there's definitely some cyber security companies out there.
1:57:44
But yeah, I think I've I think I've actually been pitch pitch I would have to find the name, but yeah.
1:57:50
Um, what what do you think about competition from the hyperscalers?
1:57:53
Obviously, uh, Microsoft Build and Google IO happened this week, and there's one narrative that's like, "Oh, so many startups are now just bullet points in a Google IO keynote."
1:58:02
Uh, but Ben Thompson wrote shortly after Google IO that, uh, Google only cares about search and they only win when it's directly impactful to search.
1:58:12
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.
1:58:22
in Google is more just almost doing it as a demo of their of their platform and then they really would be fine with another company just buying a bunch of TPUs on GCP and and and building a real company on top of uh their innovation.
1:58:36
Um but how are you thinking about startups competing in these new AI markets with the legacy incumbents?
1:58:43
Yeah, it's it's it's a it's a really good good question and it's something that I think about a lot.
1:58:46
Um just given like obviously you know somebody like Google has giant advantages distribution money.
1:58:53
I mean Google literally created the you know first Transformers paper.
1:58:57
Um so I mean certainly certainly it's something that whenever you're investing in in an app company in particular you know you you need to I think at least think very deeply about what's what's the road map of of all these companies OpenAI Anthropic etc.
1:59:09
Um, I mean certainly certainly seems like sort of areas in search in sort of like social and and proumer that you know seem like kind of the most under the microscope with these big companies.
1:59:22
But you know it it wouldn't shock me if they tried tried to compete in some of the other app categories we talked about too.
1:59:27
So yeah, in general though startups I I like to bet on startups.
1:59:32
like to bet on startups. 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 and then from there what about M&A markets uh in particular I mean my my
1:59:46
reaction to the wind surf acquisition was and it's going to be kind of hard for you to answer this but um was was basically that like whoa like maybe uh that whole meme of like oh don't build a chatgpt wrapper or whatever uh maybe that was overblown maybe that there's going to a lot of app layer companies that get scooped up. Obviously, OpenAI
2:00:04
Obviously, OpenAI is moving very quickly.
2:00:07
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.
2:00:20
Um, and it feels like unlike in the previous era like 2010ish, like the hyperscalers are more sclerotic than ever.
2:00:28
It's been 15 extra years.
2:00:30
they're less founder mode and so uh I don't know what your read is on the M&A markets broadly but um how are you thinking about uh the hyperscalers approach to staying on the leading edge of these AI application layer companies? Yeah.
2:00:48
Um I mean I think it's important to remember and I have to remind myself that Chad GBT is less than three years old I think.
2:00:57
So it's like this is happening so fast.
2:00:59
Um, and so when you think about like I'm a hyperscaler and I see a market that that like makes sense for me strategically, you know, is it really faster for me to go and try to build it internally or is it faster for me to find a really great startup perhaps with expertise that I don't have um and maybe you know some other advantage whether
2:01:18
it's the product or the distribution or or something else um and then you know explore explore partnership conversations with them um and so I mean you know the one one you know acquisition ition I I can talk about uh is uh I a company that I worked with um at at Founders Fund and and still on the board of Neon is partnering with Dre. Cool. Um and it makes sense because it's Cool.
2:01:38
Um 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.
2:01:48
And so you do need, you know, a database and memory um for those agents.
2:01:52
Uh, and so, you know, it it's certainly now, you know, now I'm trying to think in my mind like, oh, well, what what are the other categories that that that hyperscalers might uh might might be looking in and and what makes the most sense for each one?
2:02:04
I mean, the the 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 Giblly moment this week, but V3 was was close. Took a little bit.
2:02:17
It just takes a lot more work and it's harder to get a consistent quality output.
2:02:20
But and there isn't a theme where everyone like the Giblly thing was like just take your profile picture, take your whatever's in your camera roll, two words, boom, one shots and you have something cool.
2:02:31
With VO3, you have to be more creative with the prompt. Yeah.
2:02:34
The interesting thing there is I can it's so easy to imagine in the future where consumers are using video generation tools daily just for fun. Oh, totally. Yeah.
2:02:44
There's there's some like consumers just like making memes on the internet.
2:02:48
Then there's like kind of proumer SMB I'm going to make like an advertisement. Yep.
2:02:52
And then there's the like Hollywood studio that's like I'm going to make a movie or independent filmmaker.
2:02:58
But where companies kind of fit into that.
2:03:01
I can see a world in which hyperscalers are kind of dominating like Meta for example figures out a way to get really good at at at video generation because it fits into the meta ecosystem or YouTube uh you know with with V3.
2:03:15
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 up market to actually dominate because that feels like an area that like Google's not going to necessarily build the thing that creates the next blockbuster video. Yeah.
2:03:35
But if you're competing for the proumer 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.
2:03:49
I don't know any any any reactions to V3 this week. Oh, I mean super cool.
2:03:53
Uh and we were playing around with it.
2:03:55
My husband's a founder and he was like trying to make this new new video for something that they're developing internally and oh my god, just insane.
2:04:03
Uh so it's yeah, really cool.
2:04:03
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.
2:04:14
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.
2:04:21
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 um maybe maybe that's an opportunity or if you're sort of like very very specialized.
2:04:32
So, um, yeah, I mean, generally still still optimistic just kind of given at this point there's not, in my opinion, a ton of platform risk.
2:04:40
You've got so many of the hyperscalers and labs like that are, you know, both closed and open source offering offering these types of models. Yeah. Very cool.
2:04:47
Well, thank you so much for stopping by.
2:04:48
Uh, we'd love to have you back. This is fantastic. Yeah, this is great. Super fun. All right, bye. See you later.
2:04:54
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2:05:39
Anyway, we have our next guest coming in, Stephen from Lambda Labs.
2:05:43
We've had Lambda School on.
2:05:46
We're waiting for Stephen.
2:05:48
Should we hit some timeline?
2:05:48
Yeah, let's hit some timeline.
2:05:49
Um, what's uh did you see uh Yohi uh Pocket is shutting down and so this uh uh we need a sound creator basically soundboard that says moment of silence. Yeah.
2:06:03
Vibe coded a quick free open source prototype with some AI features called Keepyard.
2:06:08
It still has issues, but I challenged myself to push this in one night.
2:06:11
I thought this was very cool.
2:06:13
I've been joking about we need someone to vibe code a new Google reader since that was such a popular product.
2:06:18
It should just be out there and uh and it's already starting to happen with replacements for Pocket and uh it seems like Stephen's in the studio.
2:06:26
So, let's bring him in and talk about Lambda. How you doing? Welcome to the stream. Hi guys. How you doing? Welcome. Great. How are you? Great to have you on. It's good to see you.
2:06:35
Looking fantastic, by the way.
2:06:37
Thank you for wearing a suit. Thank you.
2:06:39
Naturally, um I guess when in Rome, but I that said, this is how you know everyone in Silicon Valley should dress. I agree. I agree.
2:06:48
Um, are you are you in Silicon Valley right now?
2:06:51
Can you give us a little drinking a monster introduction? Drinking a monster. Let's go. So on brand. It's amazing.
2:06:56
So So I'm actually uh in my hometown of of of Charlotte, Vermont. It's where I grew up. Yeah.
2:07:04
And uh it's where it's where I live. Great.
2:07:08
And just just got back from uh landed this morning from SF.
2:07:11
Uh how how would you describe the business these days?
2:07:16
cuz I know that uh well, first we got to talk about the AI scene in Vermont. Oh, yeah. Picking up, you know.
2:07:20
Uh yeah, I'd say that there's there's there's there's like one or two one or two companies.
2:07:27
There's a lot of uh uh I'd say uh independent-minded founders out here.
2:07:34
Uh but generally speaking, I'd say um it's a more of a farming farming. Yeah.
2:07:41
My little my little brother who's not in tech went to college in Vermont and just stayed.
2:07:47
I' I've tried to get him to come back forever.
2:07:50
He's committed committed to to the great state of Vermont, but uh well, let's introduce him to Masayoshi Son and maybe he gets started with uh you know building an AI company out there. It could happen. It could happen. It's not off the table.
2:08:01
Um so yeah uh brief introduction.
2:08:03
How would you introduce the company?
2:08:05
How are you describing uh the different offerings and kind of challenges right now? Yeah.
2:08:12
So, Lambda is an AI cloud.
2:08:12
It's a essentially really massive GPU cluster that all kinds of startups and hyperscalers use.
2:08:26
And we've both sort of taken invested a ton of work.
2:08:34
It's basically around a billion dollars worth of GPUs that we've deployed. Wow.
2:08:40
Um, and we've invested, you know, at this point probably around hund00 million into the virtualization software that allows us to essentially take that massive cluster of GPUs.
2:08:52
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 uh you know on a as as little as a 15minute uh basis and the the it's it's it's quite different from let's say a bare metal cloud where you need to sign a three-year contract.
2:09:18
Um, we've we've basically implemented all this virtualization software that lets you hotel on and off of it.
2:09:22
Um, while still, you know, maintaining high-speed Infiniban intercon. You did the meme.
2:09:28
You another billion dollars for Jensen.
2:09:31
Uh, how many billion dollars for Jensen?
2:09:34
Is it is is it actually primarily Nvidia chips or uh are there other uh GPU providers that are competitive at this point?
2:09:43
I've been following George Hotz's journey with AMD.
2:09:46
Um, is is anything competitive with with Nvidia right now from your perspective?
2:09:52
I don't think that there's anything that's competitive with Nvidia right now. Yeah.
2:09:55
Um, what you just see in the customer demand is in, you know, total and utter Nvidia supremacy. Yeah.
2:10:05
And I think that this is going to continue on uh for some time.
2:10:06
The the test I always like to say is you've got to get a customer.
2:10:12
They've got to be able to download 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?
2:10:26
So they that's that's that's the test, I think, um, for any chip manufacturer.
2:10:33
Um, and it's really hard to get a stable software stack.
2:10:39
Do you like the term Neocloud? Is that appropriate?
2:10:45
You know, I think it's I think it's fine.
2:10:48
I don't I don't really have any opinion on on it.
2:10:50
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.
2:11:02
You know, training and inferencing large language models, training and inferencing large scale neural networks. Yeah.
2:11:09
And I think that Neocloud's an appropriate description for for that concept.
2:11:14
What is the balance between training and inference right now and how has that evolved over the last um couple years? Yeah.
2:11:25
So, you know, we um we're we're for for for the overall business, we're we're just we're just a bit over uh $500 million of topline revenue.
2:11:37
And I'd say that um essentially, congratulations. Thank you. Thank you.
2:11:48
Um essentially historically that's been majority training and then um sort of minority interest you know maybe 80 8020 for for uh you know training to inference. Mhm.
2:12:03
And um now we've started to see that kind of switch over.
2:12:09
Um, I would generally say that when I see any sort of net new deal in the in the space for large scale GPU capacity, it tends to be more inference driven these days. Sure, it's great.
2:12:23
We're actually using the models.
2:12:23
It's not just training bigger models with no with no uh I mean we saw that at Google IO Sundar Pachai pulled up the chart of tokens generated and it's just completely up and to the right.
2:12:35
It's completely up to the right.
2:12:37
I mean you training is always going to be something where you do it once and the whole point of training is that you want to amvertise that over as many tokens as possible, right?
2:12:45
Because that's just your fixed cost that you're you're wanting to spread across as many generations as possible.
2:12:49
And so that's the point the point of training is inference. Um yeah, we're there.
2:12:53
I always kind of look at this as like a I always like to sort AI companies by revenue and just go, okay, well, who's at the top?
2:13:02
Probably like OpenAI today, you know, four billion, five billion.
2:13:06
It's it's a little bit hard to you know to to to exactly guess but then you know next one down you kind of look um anthropic 800 million last published uh mostly developer API uh but probably fast growing I would imagine they're probably in the billions now because Sonnet 37 was really good for code generation.
2:13:27
Um Google doesn't seem to be charging um from what I can tell uh charging me $250 a month now just to pop up to 500.
2:13:36
So, they're getting my money.
2:13:39
What are they charging for?
2:13:39
Uh, so I am now on the Gemini Ultra plan and uh and I have 2.
2:13:43
5 Pro preview and then I also have access to VO3, but it's very limited.
2:13:50
I they can only generate two or three video clips per day.
2:13:55
It's heavily throttled, but it's a $250 a month plan right now and it's going to jump up to $500 a month in a few months.
2:14:01
So, I imagine that across Gemini Pro subscriptions, they're probably going to grow that pretty quickly just because I'm seeing the number of go to zero to billion dollars in 100% in a couple weeks, right?
2:14:12
You know, and uh so when you kind of do that breakdown, what what do what do we see in terms of like total topline revenue?
2:14:21
It's all inference, right?
2:14:21
I mean, you know, all of that is inference demand, whether it's image or chat, GBT or or or video generation.
2:14:28
And then you know mid Journeys probably you know in the hundreds of millions of dollars uh revenue run rate and so uh there's some substantial businesses that are being built uh right now and yeah what are some kind of narative what 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. Um okay.
2:15:00
So the the the first one is just obviously I think if you look back there was that um that Sequoia uh Thinkboy piece um that was published on like uh where's the GP you know where's the AI revenue what's you know they sort of did that it it there there's a lot wrong with that analysis.
2:15:19
Um, 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.
2:15:27
I I just remember, you know, I started Lambda in 2012.
2:15:30
2013 was the year that like Mark Zuckerberg went to Ner and hired hired um Yan Lun to to start Facebook AI research at the time.
2:15:41
And every I just remember everybody in the field kind of at the time looking around, oh, is is it a bubble?
2:15:46
you know, Google's just bought Deep Mind and uh you know, Facebook's buying Yan Lun, so it must be a bubble because cuz Mark Zuckerberg just came to Nurups.
2:15:55
But um I think that I think that in general everybody underestimates how just what exponential growth looks like from, you know, it it always looks the same in the T the same, you know, wherever you are, it always looks looks essentially the same.
2:16:15
um and how good the code generation has gotten over the last 90 days. Right?
2:16:22
If you were to flip back before January, um uh you know, state-of-the-art for code generation was uh 40 and then 0 01 hadn't even I think been exactly released yet.
2:16:38
um with 01 04 claude sonnet 35 37 all this stuff the code generation is getting so good that we I I think I can say here which is in a couple of years you're just going to 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.
2:17:08
You're going to be able to do this sort of like high throughput search through software space and it's going to spit out a bunch of things and it's going to have like a maybe a taste maker 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 five.
2:17:28
I'd recommend you launch this one. Go for it."
2:17:29
And I think that's going to really change the way that the world operates on in in technology.
2:17:37
So, should you learn to code if you're a teenager? Yeah, absolutely.
2:17:40
I I think that you you still you still need to learn how to code.
2:17:43
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 to learn how to code. Sure.
2:17:54
Um I think that you're just going to see just much higher leverage teams in the world, right?
2:18:04
you might always need to think like a programmer and so learning to code is part of that process. That makes sense.
2:18:09
Um what what about um the evolution of chips and semis?
2:18:12
Before we dive into that, Sure.
2:18:14
I I feel like there's this general thesis that uh sort of we we've talked about this on the show, this idea of like uh we call it like Jurro dreams of sushi software, right?
2:18:29
This like really craft more art than science. More Yeah.
2:18:32
than science. More Yeah. art and science like super intentionally built software uh that that is just you know super super thoughtful and you can see this in companies that like maybe go after a category like CRM where it's like okay Salesforce dominates CRM but they come
2:18:49
in and they build this sort of really beautiful really thoughtful experience and and typically uh if the teams are good enough they'll end up doing doing well um I I think there's this sense that like that class of software is like safe from uh completely AI generated software. But in the in the scenario you
2:19:06
But in the in the scenario you laid out where you generate 500 different variations of a potential tool that you'd use and it sort of automatically ranks it uh based on some taste driven benchmark.
2:19:18
Is is it possible that that class of software is is at extreme risk to disruption as well? Yeah, certainly.
2:19:26
I think anything that's just software is is at extreme risk.
2:19:32
You know, you you look at a business like Salesforce, right?
2:19:34
It's almost as if I mean, how important is the software?
2:19:38
How important is the brand?
2:19:40
How important is the distribution model?
2:19:42
And and I think that when you look, you know, the bigger the company gets, the more important the the ladder becomes, you know, the distribution model, the the brand of the company, how deeply embedded it is inside of the day-to-day life of the customer that's using it.
2:19:58
And it's sort of like, well, what is the value of Salesforce? Is it the software? No, not at all.
2:20:02
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 their S&P 500 component and then all the company's data is in Salesforce, right?
2:20:18
Does that have anything to do with the software that Salesforce has written?
2:20:22
Is that the mo anything does is does the mode have anything to do with the replacement cost of developing the software crowd app? Yeah. No. Right.
2:20:30
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.
2:20:40
So, it's sort of like maybe just, you know, this is we're in the we're in the world for just uh the the business co-founder dominates.
2:20:50
The idea the era of the ideas guy, the era of the ideas guy is upon us.
2:20:54
Yeah, that'll be really exciting. Okay.
2:20:57
I I I I want to talk more specifically about the the path to this future of like turning money into software and creating value that way.
2:21:07
Um, what is more important?
2:21:10
Just bigger training runs, knocking down higher MMLU numbers, benchmarks, higher IQ points versus distilling models, faster inference, cheaper inference, um, baking some of these models down into silicon, what we're seeing with etched and and putting the transformer architecture on a chip.
2:21:32
Um, they seem like two different vectors.
2:21:34
Every time a new model comes out, my reaction is always like, well, this is good enough.
2:21:38
I just want it to be faster.
2:21:40
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 just generating in milliseconds.
2:21:49
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.
2:21:57
Um, but what's your take on on those on the trade-offs there?
2:22:04
Well, um, what we're seeing with the advent of reasoning models as well as like 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. Mhm.
2:22:18
Um, is that this the the amount of compute that you you know the the the performance improves as a function of how much runtime compute you do. Yeah.
2:22:32
And so if you can make a faster model uh and you can reason faster about it, you could you can make an argument that that that actually um might perform might perform better um in some circumstances.
2:22:48
I think that we're we're going to see all dimensions of that space explored by a variety of companies.
2:22:54
You know, there will be people out there at the edge building the biggest frontier models.
2:22:57
there will be be people quantizing and distilling those bottles down to something that runs locally on your phone.
2:23:04
Um, that was actually kind of one of the things I did before this iteration of of of where Lambda is.
2:23:12
It was sort of trained comnets that ran locally on the on the iPhone. Oh wow.
2:23:16
Uh, and this was like 2013 and it it you kind of see the same thing.
2:23:23
There's use cases for that. It's super useful.
2:23:25
you could have privacy preserving image recognition on your phone um but it's not going to be the same quality as like something that goes back to a data center.
2:23:33
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 is generating software and I've got this entire I think thesis on where the future where we're going
2:23:55
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 Instead of generating a program, let's say a calculator or an Excel spreadsheet, just go to chat GPT and say, "Hi, please behave like a program. Please behave like this
2:24:13
Please behave like this calculator or behave like this spreadsheet.
2:24:16
Generate an asky user interface for me and I want you to um essentially just respond, you know, implement the logic of that program in your mind."
2:24:26
Um, and that is what I call neural software. and it's really squish.
2:24:33
You know, normal software is really brittle, right?
2:24:37
If you make a typo, you you leave a keyword out, you miss a semicolon, it's not going to compile.
2:24:42
This type of neural software, it's not really possible to have a bug.
2:24:47
It's really more just that you've have a misunderstanding or you've misprompted it or something.
2:24:52
And I think that that's where all of this is going.
2:24:57
It's not code generation but it's going to be your your large language models are going to be you know sort of take over more and more of program space and uh you you will be largely interacting with these sort of transformer models or next you know token you know prediction models generally and they will be the software that you interact with.
2:25:20
What about diffusion models?
2:25:22
We saw Google bring diffusion to text models.
2:25:26
Uh I was seeing something like 900 tokens per second.
2:25:33
Uh they generated I saw a demo where someone generated a full calendar application all the code for the calendar application in 3 seconds.
2:25:40
It was 3,000 tokens or uh something like that.
2:25:45
That feels like um a you know an algorithm from image generation that now we're seeing in the text world.
2:25:52
Simultaneously we're seeing images in chat GPT maybe do something more transformer or tokenbased and so these lines are blurring.
2:25:59
Can you give us any insight into what's happening there?
2:26:01
Is that exciting or is this kind of just in the experimental phase?
2:26:07
Well, I mean this is like if it's whether it's exciting or not is going to kind of answer the question you had earlier, which is how successful our bakedin transformer asex going to be, right?
2:26:21
Because sort of like as the space the underlying space changes. Yep.
2:26:23
um then every one of those sort of as6 now becomes a lot less valuable and you kind of have to go back to the the more general uh tensor processing uh that you see inside of tensor cores and you see inside of the architecture of like things like TPUs. Yeah.
2:26:43
and away from, you know, really specific things that have to do with like um the KV cache and different transformer specific architectural things you might want to put into um an ASIC.
2:26:52
And so I think that it's it's interesting to see you've got diffusion models, you've got things like Mamba um and and where where where there's there's alternatives to the transformer that have um what what's called basically linear complexity in terms of the uh um the the amount of memory um that that you're that you need for um uh the context length growing.
2:27:17
um which is better than the quadratic complexity you see inside of normal um transformer models and I think there's there's going to continue to be a lot of innovation in the model architecture space and that will probably benefit Nvidia a lot. Got it.
2:27:39
Are there any other side projects in semiconductors that are exciting to you?
2:27:45
uh huge wafer scale computing like Sarah Brris.
2:27:48
We talked a little bit about baking things down onto uh AS6.
2:27:49
Um we saw that path play out with Bitcoin with the FPGAAS and then the ASIC kind of Bitcoin mining.
2:27:58
Um there's other approaches and I'm sure Nvidia is not asleep at the wheel.
2:28:02
Jensen Wong's in founder mode.
2:28:04
He's he's he's aware of the boom.
2:28:05
He's aware of the demand.
2:28:05
I'm sure people are asking him how can we run diffusion models faster?
2:28:09
How can we run transformer models faster?
2:28:11
Um, what are you expecting on the semiconductor side over the next like few years?
2:28:20
Well, I it's pretty clear that I I'd say the the front runners for competing with Nvidia, which are all very far behind Nvidia.
2:28:28
Uh, 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 Tranium and Inferentia. Yeah.
2:28:46
um that space is always evolving fast but I think it's it's it's kind of a little bit telling that uh AMD hasn't with all the resource with all the resources with all the u sort of clarity on what you're supposed to build for the market uh hasn't been able to kind of capture enough market share Dylan Patel is going to turn it around.
2:29:14
He's he's going to write just one more report and AMD is going to be back. I'm bullish. That's all it takes. I love it.
2:29:22
Um but uh in terms of can you give us a little perspective on on obviously if I'm if I'm doing a ton of inference on Lambda, I'm probably in the CUDA ecosystem, probably in in Nvidia land.
2:29:34
If I want to take that over to Amazon or Google with TPUs, how much of a barrier really is that?
2:29:40
Can you kind of explain because at the same time we have these we have these incredible code generation models.
2:29:47
It feels like putting an AI agent on rewrite this CUDA for TPU that seems like the easiest thing to do.
2:29:54
It seems like a a problem perfectly tailor made for AI agents to just sit there and write boring translation code.
2:30:02
It's not even it's not even feature design, right?
2:30:06
Wasn't that in the TL where someone was making a joke about the uh an the anthropic safety uh you snitching on the user and someone said uh port this uh pietorch code over to JS and then it says you know searching calling FBI calling FBI do not do this you're going to you're going to pull the rug on the entire economy if you do that preserving the the the underlying chips that it's running on to make so important to America.
2:30:34
So, so I think that I think that okay, the the the the stuff that this code generation is really really good at today is sort of what I would call within the realm of what you know oneshotting a basic program.
2:30:48
Oneshotting sort of a one-page program or it could be much longer than one page but it's sort of like single file. Yeah.
2:30:55
or a function or or you know a class something like that not necessarily something maybe I'm just behind on it a little bit and I'm not you know doing what the kids are doing or something with with with uh sort of an AI IDE but I just kind of like when I'm when I'm vibe coding I will just tell either chat GPT or Gemini or Claude I'll go do this in one page like have it be a one thing I want copy and paste this into my my thing and run it.
2:31:29
Um, and it's it's quite good at that.
2:31:33
Now, when you talk about like going through an entire codebase, um, fixing the compilation errors because there will be like subtle Yeah.
2:31:41
uh, subtle bugs that get introduced, it's not quite there yet. Yeah.
2:31:45
It's just the problem is that I now am at like 100% confidence that it is going to be there uh in just a couple of years and that that's kind of why why I know that every sort of megawatt that that we build and every GPU that we deploy is just going to get met with demand on the other side because just two years out like if you just look two years ago 2023 code generation was primitive Yeah, primitive. It didn't work.
2:32:15
Now today, it really works for more simple programs.
2:32:18
I think two years from now, it's just going to it's going to make you feel sick when you look at it.
2:32:24
So, what are the big bottlenecks you uh you foresee between like uh energy, water, land?
2:32:28
Uh are you going to be building a data center in space?
2:32:34
What what do you think in the future looks like for you?
2:32:39
Um, so I think that the the the bottleneck is definitely what I call like wrapped power.
2:32:45
So the I think there's plenty of generated power.
2:32:52
Um, right now it's just not wrapped up in a data center shell.
2:32:54
It's not in a powered shell.
2:32:56
It's not in a facility that has direct to chip uh liquid cooling integrated into it.
2:33:01
And so it's sort of like that wrapped up power that's like ready for the current generation.
2:33:07
and next generation of chips.
2:33:11
Um, 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.
2:33:24
remove those. It's like whether it's like looking at sort of the way that we run utilities where um you kind of have to in some cases become um an unregulated utility and put like let's say a you know build a data center power plant which is to say
2:33:41
behind the grid or not attached to the grid power generation station next to a data center and not every state's 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
2:33:54
And so I think that I I think there's some hope there.
2:34:00
And the the other thing is just really I think building uh large contiguous spaces is like is pretty clearly the the answer in my opinion.
2:34:15
Well, good luck with that.
2:34:15
Uh I'm glad I don't have to deal with it.
2:34:19
Logistics is a real pain.
2:34:19
It sounds like a lot of work, but you've been doing it for 14, 13 years.
2:34:23
So, you got another decade in you at least. So, good luck to you.
2:34:28
We'd love to have you back on.
2:34:28
This is a fantastic Come back on again soon. Thanks, guys. Super fun.
2:34:32
Love what love what you do. Long time.
2:34:34
This is I didn't clock you as a monster guy, too.
2:34:37
We got to go deeper on energy drinks.
2:34:39
Yeah, there's so much to talk about.
2:34:41
Lots to talk about, but this is fantastic.
2:34:43
Thank you so much for coming on. We'll talk. Great chatting. Cheers.
2:34:46
Uh, quickly let me tell you about numeral sales tax on autopilot.
2:34:50
Spend less than five minutes a sales tax compliance.
2:34:53
Should we sing sales tax AGI?
2:34:56
Sales tax a uh go get uh go get numeral. Head over to numeral hq. com.
2:35:03
How did you sleep last night, John? Um, oh, terrible. I woke up at 4 a. m. It was a disaster.
2:35:07
I'm I'm I know I'm gonna get cooked, but you don't have to be cooked because you can go to eightleep. com. Use code TBPN. I got a 76. It was brutal. 99.
2:35:16
I can't I can't get 99 back 99s.
2:35:21
I don't know what I'm doing wrong.
2:35:24
And then also, we got to tell the folks about public.
2:35:26
com inspire me to grind harder investing for those who take it seriously.
2:35:29
They got multiasset investing industryleading yields.
2:35:32
They're trusted by Let's give it up for multiasset investing. Yep.
2:35:34
And uh and their partnership with Aston Martin, which we might have more information on soon, but stay tuned. I cannot wait.
2:35:40
We got Sam Lesson coming in the Temple of Technology very quickly.
2:35:45
Um, uh, do you want to do some timeline while we wait for him? Is he here? You know, I love time.
2:35:51
Uh, Dwar Patel dropped a banger on Claude 4 day.
2:35:55
He sat down with Trenton Bricken and Chelto Douglas um, talking about Claude 4, how far reinforcement learning can scale.
2:36:02
I haven't had a chance to listen to the whole thing.
2:36:04
I listened to about half of it kind of in and out while I was trying to sleep last night.
2:36:08
Um, but uh I mean just a very cool vibe of like three people having a conversation right on the day when you want to know this stuff talking all about uh this fascinating metaphor for for AI safety because it's just been controversial.
2:36:23
Of course, there's like some drama around some random anthropic news, but the cool thing that I liked was um they said um basically if you want to tell the AGI what to do and how to behave in the best interest of humanity, uh you could give it specific rules, but it might actually be better to say, imagine there's an envelope AGI uh and in that envelope is what I want you to do, all the rules I want you to follow.
2:36:48
you can't access this envelope, but you have to behave in accordance to what you imagine to be in this envelope.
2:36:54
And so the ATM just like I have to behave in the interest of humanity.
2:36:57
It was it was a cool like thought experiment almost. Uh it was very cool.
2:37:02
Anyway, uh Patrick Oanis was shouting it out.
2:37:04
He says one of his favorite genres of podcast is recurrent expert guests on on the same show.
2:37:08
If you're interested in the nitty-gritty of AI model progression, you'll enjoy this.
2:37:11
So go check that show out this weekend. Uh, it's a great listen.
2:37:15
And we have Sam Lesson from Slow Ventures in the studio.
2:37:19
Welcome to the studio, Sam. Gentlemen, there he is.
2:37:21
It's Jessica Lesson's husband. Put it on the flesh.
2:37:25
I saw her like literally minutes ago. That's how I am.
2:37:28
Tell her to tell her to come by at least and say hi if if she's not uh busy. Yeah. Yeah.
2:37:35
She's uh she's she's busy this moment.
2:37:37
But, you know, we're 30 minutes.
2:37:37
We got the crossover of the century. TBPN the information. It dropped today. It was great. I love that. Yeah.
2:37:44
I actually I I knew about the development of that story from dinner conversations. Oh, yeah. It was a lot of fun. Yeah. Oh, I bet. I bet.
2:37:51
Uh Abe is Abe is the man. Yeah. Uh there you go.
2:37:55
It was It was fun hanging out with him and um kind of the So, are you guys you guys are the cover of the weekend section? Is that right? We are. We are.
2:38:02
The big Are you guys going to do a print edition for us? That's coveted space.
2:38:06
I always thought that they should actually do a print edition. I think it's time.
2:38:09
Everything goes in a cycle.
2:38:09
I got the I got the Wall Street Journal here.
2:38:13
I need I know I was once a once weekly uh uh Saturday dropped off on the doorsteps of every% hire the kids to like deliver it with the with the you know throwing it out the window.
2:38:25
Look, I was in an airport lounge in Germany two days ago and they had all the the print newspapers and I'm like look there's a missing opportunity here.
2:38:32
The Germans want to read about the information.
2:38:33
They want to read about technology brothers. Yeah, of course. Let's get it to them.
2:38:38
You guys are big in Germany I'm sure.
2:38:40
Well, somebody started translating our streams into Dutch, which was interesting.
2:38:44
They're doing other other things.
2:38:46
That doesn't seem like the first choice.
2:38:47
Like, don't you want like Mandarin or something?
2:38:51
We're trying to get We're trying to get big on Waybo. Yeah. What's next?
2:38:52
Yeah, but we're expecting to have some push back. Some push back.
2:38:57
Um anyways, uh it's great to have you on as always.
2:39:03
Congrats on all your success. You guys are everywhere.
2:39:04
This is this isn't the new studio yet, though.
2:39:06
Well, you're a part of it.
2:39:07
You're a part of you're a part of that studio.
2:39:08
to come down next time you're in LA. Come by in person. Be great.
2:39:11
Tuesday will be the first show. Yeah.
2:39:14
It's a lot closer than Anglewood Cliffs, New Jersey, you know. Yeah. Yeah.
2:39:18
What's what what's there?
2:39:18
Is that the new Is that the newb CNBC?
2:39:23
You can't you can't make this whole CNBC rival thing and not know where CNBC is.
2:39:28
Everyone always says like uh Yeah.
2:39:28
Uh Andrew Reed was like, "Oh, they're making Squawkbox for tech."
2:39:31
And I was like, "Got to start watching Squawkbox."
2:39:35
I guess Netflix is also Netflix has a new billion dollar New Jersey studio.
2:39:40
Maybe maybe some New Jersey and maybe we're taking the fight to New Jersey in the future. We'll see. Let's pick LA's fine.
2:39:48
LA Where were you where were you traveling this week?
2:39:49
I I I went I I've had an insane travel schedule, but I was uh Monday I went I was New York uh Frankfurt, New York, San Francisco was my was my week.
2:40:01
What's going on in in Germany?
2:40:04
Germany? Germany was a personal thing I had to take care of but but New York was the Salana acceleration uh what is it the Salon big Salana conference which they call ship or die very dramatic brand nice uh you're infamous there right the GM the GM guy do you still get
2:40:21
comments on that you know I saw I saw Raj backstage you know I was I was one of Salana's first investors I like my my um Jason Calcanis I was the first investor in Uber was like I like do that for Salana right and so you knowve I've known those guys for a long time and I
2:40:35
saw Raj backstage and we were 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 from Twitter it was amazing about that yeah this was like Twitter still right so it was like
2:40:53
somebody at Twitter was like didn't get the joke obviously didn't have context that like you guys are boys and just yeah the thing the thing is I unfortunately have other people on on Twitter legitimately threatened to kill me, which that's not so good. You got to
2:41:06
You got to get that taken down.
2:41:07
But the the Raj was a pretty funny one to for them to respond so so quickly to. Yeah. Yeah. Quick reaction.
2:41:13
Uh there's so much so much to cover in the news. It's AI week. It's AI week.
2:41:18
Isn't it every week AI week, boys?
2:41:20
This one was particularly AI week.
2:41:23
week. We got Microsoft build Google IO open AI IO 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 going to win you know I you guys actually I'll tell you a funny
2:41:37
a funny answer to that you guys know my associate Jack Reigns you know this guy Jack sitting he's right over there Jack he can come wave for a second 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 What's up, dude?
2:41:57
And I'm like, what value are you adding?
2:41:59
I've been saying this for two years. I'm like, thank you.
2:42:03
I'm like, I wanted to check out all the little Google I was like I was like, Jack was like, Jack, you know, you're an associate at an early stage venture capital fund.
2:42:12
Telling us to buy Google stock is not exactly guys.
2:42:14
I want to see slow as the next crossover. Yeah, crossover. Become an RAIA 30%. Never.
2:42:18
We've actually looked into it.
2:42:21
It's definitely not a thing we will ever No, I mean I mean the 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?
2:42:36
Look, here's the negative on IO.
2:42:40
The negative IO is that per usual, Google's actually terrible at marketing, right?
2:42:45
And so they just launch everything.
2:42:48
And so you're like, I have no idea even where to focus right now, right?
2:42:52
Like it's it's not my value comes in figuring out. Thanks, John.
2:42:56
Focus on generative AI videos, V3. That's the thing.
2:42:58
It's like so many things you're like, I don't know.
2:43:02
But the net of it is like they're just crushing it, right?
2:43:04
Like from a tech perspective.
2:43:05
And I got to say, I'll tell you a funny story.
2:43:07
I spent like 20 hours quote unquote vibe coding over the last week cuz I was on so many airplanes.
2:43:12
And it turns out airplane Wi-Fi, vibe coding, perfect match of activity.
2:43:16
So, I just like was like messing with these things till my eyes bled.
2:43:21
And you know what happened in hour 11? What?
2:43:23
I stopped using chat GBT and went all in on Gemini cuz it's actually better G 25 Pro is just like way better at a bunch of these coding tasks.
2:43:30
It's better at structuring.
2:43:32
There's like a bunch of stuff.
2:43:33
So, it's it's I think it was absolutely a Google week.
2:43:35
But were you using codeex?
2:43:36
No, I wasn't using codeex.
2:43:41
There's always Look, this is one of my other insights from the week.
2:43:44
spending a week, you know, literally flying around the country vibe coding in the air. Yeah.
2:43:47
Is um you know, the the whole what model to use thing is a complete mess, right?
2:43:55
And I think 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?
2:44:02
And then by the way, every two seconds a new person pops into the room.
2:44:06
You have no and like I people are like oh or or you can trust this person 95% of the time.
2:44:10
you can't trust him with your life, you know, but that's a totally that's a totally separate chain of thought which I think is important.
2:44:18
I was talking to some entrepreneurs today about if you think about what AI is today.
2:44:21
It's like having it a B minus employee or like an 80enter.
2:44:26
And the question is how do you get value out of 80enters is actually more difficult than it looks in a lot of ways, right?
2:44:31
Because the reality is so much of work is about trusting.
2:44:33
But isn't it more isn't it more their B minus because it's you're averaging their effectiveness on different things in in my experience.
2:44:40
in in my experience. 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 never kind of but I think the other the thing I really think about guys is you
2:44:57
know if you think people are always like oh there all these tasks that AI is more efficient at and so clearly those jobs will just go away and it'll be it and 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
2:45:13
It's to have a throat to choke when the work goes badly, right?
2:45:15
It's like, why do you have an accountant?
2:45:17
You don't have an accountant to do your taxes.
2:45:18
You have an accountant so that when the IRS comes and says, "What's wrong with why did you get this wrong?"
2:45:23
You're like, "I didn't do it. That guy did it." Right?
2:45:26
And so the I think that's the interesting thing is like there's all these models like great, good news.
2:45:28
You get rid of the employee, now you get a queue that's mostly right and you approve and you're like, "I don't want to approve that stuff."
2:45:33
Like the whole point is to have someone else. Yeah.
2:45:35
I think our 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.
2:45:42
So that you can fire them when they're wrong, right?
2:45:45
Like you need like just the point is like there's this whole I think there's a lot of like new well it's an agency thing too.
2:45:50
It's like if you could tell if you could tell deep research to like 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 you know there's all these things.
2:46:05
But I think the ultimate model in my mind is I don't even care what the average persons are using.
2:46:10
I don't care about some review online that's four stars for coding for this type of I don't care.
2:46:15
What I care about is what are the smartest people I know in the world using and like 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 like that needs to be up to date it's much more of like an identity problem or like a human
2:46:27
trust problem right than it is you know a technology problem in a lot of ways and it's just changing really fast so it's it's been a fascinating week but yeah net I mean pulling 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 um because that's what's happening Mhm. So you're you're saying to Jack like,
2:46:46
So you're you're saying to Jack like, "Thanks for reading my memo from two years ago." Yeah, exactly.
2:46:49
Well, in fairness to Jack, he wasn't on the team two years ago.
2:46:54
He was very excited to discover notebook l. But love you, Jack.
2:47:00
I got we got to get him out of the pool house.
2:47:02
He uh Anyway, uh I want to talk about some other stuff.
2:47:06
Uh what what do you think about the uh Johnny IV news and and hardware generally? I mean, where to begin? I know. I know.
2:47:16
This is my favorite part of having you on the show.
2:47:17
We don't have to prompt at all.
2:47:19
We just like two, we could give you three words. Johnny, I've hardware. Well, okay. A few things.
2:47:24
First of all, I mean, my my my my tweet on this when it was happening was like, well, I guess all these hundred million dollar AI researchers are cheap, right?
2:47:30
Like the these it's the designers that are going to get paid bank on aqua hires in this in this era, right?
2:47:37
Look, I think it was marketed in a really interesting way, right?
2:47:40
Like it's marketed as like they tried to pick the biggest number possible.
2:47:43
It's a 2% they paid 2% for this thing, right?
2:47:45
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?
2:47:53
Is you're supposed to look really big and powerful with big number.
2:47:55
And I'm sure Johnny doesn't mind being told that he was 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.
2:48:03
The hardware thing is interesting.
2:48:06
Like on one hand, I actually think it's like if you're open AI, you do need a hardware play.
2:48:12
You're going to get otherwise, right?
2:48:13
Like how, you know, you know, Meta discovered this years ago, which is like being beholden other people's hardware is really tough, right?
2:48:19
In this case, it's only more so, right?
2:48:21
Because of kind of the way these chips are going to fall with Android and iOS.
2:48:25
So, I don't think they're wrong and like Met has got its glasses.
2:48:26
Everyone's So, like it's not strategically wrong from first principles.
2:48:30
I think the problem is 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?
2:48:37
hardware is like zero, right? Um like and that's just you know it's you know you're gonna 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
2:48:53
something that's so great well well the one thing that does seem clear haven't they said this is a a new type of device that will integrate with your phone and your computer and that screams to me okay well is is app yeah I said septum piercing where you My take was eane. Did Did you see ecane?
2:49:11
So you this was so when I left when in 2014 No, but sorry to finish my thought that 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 a like uphill battle.
2:49:25
Look what happened to Pebble, right?
2:49:28
And the Apple Watch, right?
2:49:29
In the end of the day, it's like look, you know, you have the iPhone is a hugely breakthrough device.
2:49:36
This is, by the way, not my line.
2:49:36
It's a friend's line, but like hugely breakthrough device.
2:49:38
You already had a phone, right?
2:49:39
You know, it wasn't like a new thing you were putting on your body. The glasses work.
2:49:43
That's a thing that was already on your body. The watch work.
2:49:47
It's a thing, you know, same thing.
2:49:49
It's It's really hard to imagine you're going to get through with some new device.
2:49:53
So, my my joke, but it's only half a joke is look, you know, 12 years ago, I got obsessed with the idea of making an ee.
2:49:59
So, imagine like bringing back the cane, right? That's what you meant.
2:50:03
And I have no idea where you like Novaane. Yes.
2:50:05
you like Novaane. Yes. And if you think about if you think about the can it's actually you you put a shitload of batteries in it big antenna right and you know what the nice part is like the world is getting less safe so you can people with it
2:50:20
the world is like the world is aging so like everyone needs canes you know like there's all these like macro trends in favor of bringing back the cane and then you know could you drop like a GPU and a microphone and a camera in the top and like talk to your cane and like you know yeah smart Smart cane. Smart cane if I
2:50:35
Smart cane if I don't want to be pitched any more non AI canes. Okay, I've had enough.
2:50:42
Like I'm just saying like if they actually if OpenAI came out like we've we're bringing back the cane.
2:50:48
I'd be like all right listen for all my Well, you you know that Johnny Ive got his start at a design firm that was working on bathrooms.
2:50:56
And so maybe there's all like smart toilet, you know. Yeah.
2:50:58
Well, there is someone just came out.
2:51:00
There's a there is like a new Fitbit for to for your poop. Okay.
2:51:04
I know some friends that have funded that. That's thing. I I funded that. You funded that?
2:51:08
I know some people funded that. I funded that. It's called Throne. It's called Throne.
2:51:12
I I think it's interesting uh for a bunch of reasons.
2:51:15
One is it's just like personally as like a quote unquote biohacker.
2:51:20
There's so much information on how your digestion, what's happening with your digestion, your hydration, all these different things.
2:51:27
In the end of the day, you want to copy behaviors people already doing.
2:51:30
And you know, in college, one of my roommates, Brian, would send me pictures of his poop all the time.
2:51:34
So, like, you know, like that at all.
2:51:36
You just got to double down. Brutal. Let's move on.
2:51:38
Uh, hyperscaler capbacks.
2:51:41
Give us anything to get us off of this.
2:51:43
Well, here's my hypers scale. Hyperscaler capbacks. Here's my line on it.
2:51:47
I flew through JFK today.
2:51:47
They're spending $20 billion renovating JFK.
2:51:49
I'm like, this capex is nothing. Spend more money on AI.
2:51:55
Like if you to spend $20 billion on like renovating JFK, all of a sudden spending a hundred billion on AI doesn't seem so crazy. Mhm.
2:52:02
Uh what about uh say say as much as you can about what Meta, you know, Meta's playbook over the next kind of six to 12 months.
2:52:13
I know they've been having talent kind of retention. Llama was the Yeah. Llama behemoth delayed. Delayed.
2:52:20
Look, in the end of the day, I again I as you know have huge respect for the team there and the leadership there.
2:52:26
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 you know from from a from a 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
2:52:43
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 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
2:53:02
business and a 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 a free LLM for them that they can vend into every corner of the app even in places the consumer
2:53:23
doesn't feel or or see so uh profanity filtering and uh understanding what content goes where, ad matching, uh generative AI to clean up Instagram photos, all these things that will just be under the surface as opposed to what Google's doing, which is like now we have 10 new apps, notebook LM, like you're we're not seeing that from Meta and maybe that's the right strategy. I
2:53:42
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 right?
2:53:50
They just need to like win at like the core.
2:53:51
And then basically, again, the open source thing is clear.
2:53:54
like they actually for like think about ads.
2:53:56
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?
2:54:02
In the end of the day, it's just better if more people have access to it and the innovation will happen.
2:54:06
So, look, one of the things I did in my vibe when I got really into like all the platforms, right?
2:54:09
I spent a bunch of time remember Digital Ocean, like Digital Ocean's doing a great job with AI, right?
2:54:15
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 write some code and you want to actually get it on a server it's always still a
2:54:29
hassle and it's like they've actually done a great 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 got to get a killer video generation model out of meta. Like they they're the only one
2:54:42
Like they they're the only one that has another data source market.
2:54:45
How do you see that market evolving?
2:54:48
There's a bunch of foundation model labs doing video generation.
2:54:52
And I can see some of those getting to the point where they could crush it for big Hollywood movie studio, you know, making very specific types of scenes or assets, but then it feels like the low end of the market for, you know, if you're a random SMB and you want to make an ad or something like that, yeah, maybe use some vertical SAS, but also I wonder how much it matters.
2:55:17
matters. I mean like you know I had this conversation actually with my good friend Dave Morin on our little weekly you know session more or less more or less we're talking about Dave also somehow cracked like the top of the angel there was like the top angel
2:55:30
investor list and he he was the top dog it's amazing so let's we know the validity of that list we'll talk about we could I mean I just like to see my boy Dave at the top I like to see look my boy Kevin my boy my partner Kevin was like number four on on the list. It was a very interesting
2:55:47
It was a very interesting list.
2:55:48
But the uh I wasn't on the list, but you know, that's okay.
2:55:50
The um the uh but uh what I was going to say is the um 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.
2:56:03
Everyone's really excited about like super high-end video generation and Hollywood and D.
2:56:07
You know what's happened in the media landscape?
2:56:08
Those things don't make any money.
2:56:10
No one cares about these movies anyway.
2:56:12
like they're consuming like low-end crowdsourced memes on the internet.
2:56:16
Like that's where attention is.
2:56:17
That's where the energy is.
2:56:19
That's where entertainment is.
2:56:20
And so I think obviously the pure technologists and like the high flutin people are really excited about like the narrative storytelling beautiful duh.
2:56:28
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'll be much more budgety tools that actually win.
2:56:39
And the other stuff is kind of just, you know, intellectual, you know, masturbation a little bit.
2:56:46
It doesn't mean you shouldn't do it.
2:56:47
Like people Speaking of that, Speaking of that, why is Speaking of uh masturbation?
2:56:51
Uh why is Only Fans getting priced at eight times earnings?
2:56:57
You know, I I so desperately want to buy Only Fans, guys.
2:56:59
I've wanted to buy it for years.
2:57:00
I had plans like there there's been a few iterations of this and No, it's so good. It's so good.
2:57:10
I just What do you have against Only Fans? Uh uh I just so good.
2:57:11
This is But your reaction is part of the reason I want to buy it, right?
2:57:18
The buyer pool is small, so the price is low.
2:57:21
The Well, that's part of it.
2:57:23
The other thing is everyone because the buyers, it's actually the best AI short you could possibly think of, right?
2:57:27
Because part of the reason it's getting sold, my understanding, and like the whole story, is like, well, we're going to have all these AI girlfriends, so like the creator economy is going to get crushed on these things.
2:57:36
And I think that is like a very 101 simplistic take on what's actually the other thing is a lot of the a lot of the cost that goes into basically generating revenue on only fans is from messaging which is done by people in the Philippines and AI.
2:57:52
So this is the thing everyone the open AI is like the greatest human AI platform in existence right from position because you have I think you still need real brands.
2:58:04
I think that having human brands matters at the top end.
2:58:06
Your ability to then like effectively automate.
2:58:08
It's kind of like the Facebook story which is your ability to slot an AI and bank it right on messaging is like off the charts with only fans and improve the quality.
2:58:17
So I think it's interesting.
2:58:17
I think it's like this classic thing where it's being sold.
2:58:20
I've always loved the asset.
2:58:22
It's the number one creator platform in the world.
2:58:24
It's so defensible because they actually take have a very low take rate because they're so big that no one can no one can assault them, right?
2:58:30
Because of how they're kind of set up. What's the take rate?
2:58:33
It's like it's really low.
2:58:33
I want to say it's like 10%, maybe 15, but it's like much lower than you think.
2:58:38
And as a result, like you have this incredible cash engine.
2:58:42
I mean, YouTube's like 45% and many other sites are 30% just for general content creation platform.
2:58:48
So, just the upshot is like this incredible position.
2:58:52
It's it's I think there are huge product opportunities.
2:58:53
There always have been with it.
2:58:54
But then you have this double storm of like one people like you guys boo it because you're you patrician technology brothers, right?
2:59:03
like and you won't like acknowledge human nature and people want to do this.
2:59:07
And then two, 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.
2:59:18
Yeah, I have no Well, you're going to have to become an RIA to do it probably. So, good luck.
2:59:21
Well, I got to figure out how to not do that.
2:59:22
I also like for what it's worth, I'm a seed investor.
2:59:24
I don't know how to raise the $2 billion I need.
2:59:27
But call me if you got it.
2:59:27
Well, speaking of seed investors, uh I don't know if you saw this chart from Pitchbook.
2:59:31
Emerging managers are on track to raise less money this year than they have in a decade. That sounds right.
2:59:38
Uh it's now under $20 billion.
2:59:40
During 2021 it was up at 60 billion was really really speed uh really spiked.
2:59:46
2022 was around 50 billion and now we're down in just one JFK renovation.
2:59:51
That is that is a lot of money for emerging managers.
2:59:56
This is I assume is defined as we're going to put $20 billion as an emerging manager.
3:00:00
Wait, how much did they get in 2021?
3:00:01
Well, you put it you I mean you put it in like $20,50 million funds.
3:00:05
That's the idea at least or that's what happened.
3:00:07
They're all I just I've been so skinn I don't see any of this working out for anyone, right?
3:00:13
Like you know I I know it it's one of the the they'll always be the random winner.
3:00:17
Yeah, but but isn't that the nature of the game?
3:00:19
It's like startups follow a power law so do funds.
3:00:24
I just think we have to hit a size gong because the 64 billion that they raised in 2021 12 billion of fees and so let's just give it up. Congratulations, guys.
3:00:36
But it's kind of guys, I think you guys are cheering too much.
3:00:38
I do the math if you do the math on I'm joking to be clear.
3:00:43
I mean, yeah, being 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 your kind of shitty subscale, it's actually a pretty bad business, right?
3:00:52
What's wrong with being locked in? No, no, no.
3:00:54
Like what you're saying, 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 two and a half years in, like, is that real though? Is that real though?
3:01:09
I feel like most of my emerging managers, they they write the checks in the first year and a half, two 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.
3:01:18
But it's still even if it's couple hours a week for 10 years.
3:01:23
Yeah, I guess that is kind of Look, it's also it keeps you other it's just messy and complicated.
3:01:26
And the reality is again like if you're earning two and 20 and you're never going to see the 20, right?
3:01:32
like the two ends up actually, you know, on a $50 million fund after you pay for actual things. You're doing fine.
3:01:38
Like no one's crying, but like it's not like some great business, right?
3:01:42
Like I think the only reason to raise a $50 million emerging manager fund is like to have enough card flips to prove that you can size up a bit.
3:01:50
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.
3:01:55
I the math doesn't work, right?
3:01:57
I think there's like this sweet spot of fund sizes that work. Too small.
3:02:00
You don't have the economics to make it work.
3:02:02
even if you have a banger, it's like not that important.
3:02:04
And like too big is just like the law of big numbers.
3:02:07
You're never going to produce an important fund, right, from a returns perspective.
3:02:10
So look, what we do, seed investing, we're I think in the sweet spot, obviously, cuz why would I not think that?
3:02:16
You know, we've made money. I'm very proud of that.
3:02:18
I care about DPI, whatever. But here's the thing. Sorry, sorry, sorry. We're laughing.
3:02:22
We have to explain because you can't see it.
3:02:25
But the Chiron right now says seed investor.
3:02:28
Don't become a seed investor. stay the out.
3:02:33
The um the um but then the the reality is like you know it's not even from my perspective it's not the best business.
3:02:40
You do it cuz you love it, right?
3:02:42
Like 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.
3:02:52
Do you think do you think uh part of why every emerging manager jumps into seed is just like they can't do growth?
3:02:57
Because I I feel like the skill set of being a growth investor is in some ways more repeatable.
3:03:04
You know, you get people that come out of investment banks and they have all the skills to underwrite a company that's at a billion dollars. There's less risk.
3:03:11
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 one, like that's just feels harder to mar question.
3:03:20
It's like who's going to give you LP level dollars, right?
3:03:22
And like by the way, if you're if you're going to later stage fund, you're trying to like model to like a guaranteed whatever it is, two and a halfx or whatever.
3:03:32
Why would you give it to the crazy kid, right?
3:03:33
The crazy kid you give money for because they might be right. Yeah. Yeah. Yeah. Yeah.
3:03:38
And so you want that seed bet.
3:03:39
And then also I feel like a big part of the emerging manager dynamic is just like essentially scout funds and and there's a lot of like horse trading around like, yeah, we will do a we'll do the deal from our fund to fund.
3:03:49
We started that way like you know 10 plus years ago and like that when there was the market was much looser and and it was a different market 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.
3:04:02
I just think like like most things that path all paths get super crowded, right?
3:04:06
And so once the path is super crowded, it's just really hard to differentiate.
3:04:10
It's really hard to make a good business out of it.
3:04:13
Um and I I do think like mo almost everyone's going to go away, right? Become a seed investor.
3:04:16
You hear you heard it here first, folks.
3:04:19
Uh last last uh want your quick take.
3:04:21
XAI's Portland data center fire.
3:04:24
You think that's just a a little accident or you think Portland is doing Portland stuff?
3:04:32
That would be really funny.
3:04:32
Um, that'd be really funny.
3:04:34
It's It's um God, have you guys ever read the science fiction parable of the sewer? No. Great book. Great book.
3:04:40
I'm just finishing it now, but there's a whole slub plot 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.
3:04:48
So, they're just like setting fire to everything. And like, it's funny.
3:04:52
It's It's I I just looked it up.
3:04:53
It's a post-apocalyptic story set in 2025. Wow.
3:04:56
I don't know if you caught that when you read. Yeah.
3:04:59
And like they're basically about people like trying to walk north from LA to like to to Seattle to escape craziness. But the um Yeah.
3:05:08
So I don't know if you told me that that drug was invented in Portland. Wouldn't blow my mind. Yeah.
3:05:11
I think we got to get a This is fantastic having you on. Thanks so much. Always a pleasure. Happy Friday. Happy Friday. Talk to you quickly. Cheers.
3:05:20
Let me tell you about adquick. com.
3:05:22
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3:05:25
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3:05:26
Only AdQuick combines technology, out of home expertise, and data to enable efficient, seamless ad buying across the globe. And we got Bobby.
3:05:36
They are coming to the studio. Yep.
3:05:39
Um I'm going to do some uh V3 generations for all of our partners. Get those in the mix. Pull those up. I think it'll be fun. Get a little creative.
3:05:46
Uh we got Bobby coming into the studio. Welcome to the stream. How you doing? Thank you for having me. Where are you?
3:05:53
Are you in Miami right now?
3:05:53
I am the last one standing in Miami. Yes.
3:05:55
Let's give it up for Miami. Stuck around. Thank you very much. Yeah. Yeah. I I love Miami. I It's beautiful.
3:06:04
Every time I get to go visit it, it's always struck me as uh 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.
3:06:23
And so if tech could assemble in Miami for events, that's great. Be quiet.
3:06:26
We gave it a real college structure.
3:06:28
It was happening for a while.
3:06:30
You know, there was Hereticon and like the best conference I've ever been to. Exactly.
3:06:36
And and it was cool that you you get people that come from New York and they're not just going to go home on the uh after the conference, they're going to stay. Same thing with SF. Same thing with LA.
3:06:44
So it was actually a feature that not everyone was there.
3:06:46
I feel like if you throw a conference in LA or SF, a lot half the people are just going to go home.
3:06:51
Uh, it was special for a moment.
3:06:51
I Anyway, I got a What's up? I gota dox Bobby. Oh, yeah.
3:06:57
Because he pulled up to Heredicon in a Ferrari. Let's go.
3:07:04
We love You remember I called it out.
3:07:04
We were walking is actually just getting the buttons redone. Oh, really? You have the button.
3:07:11
You have the button issue. The sticky buttons. Stay. You got sticky buttons.
3:07:15
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 somebody sticky like ate a hamburger.
3:07:24
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. It's sticky.
3:07:29
It's like she's like this is disgusting. I know. It's terrible. Yeah.
3:07:34
What were you doing in here? This is terrible. That's all fixed now. That's all fixed now. Okay. That's good. That's good. We're glad to hear it. Find us.
3:07:40
Uh but yeah, give us the news. Give us the update.
3:07:42
give us a little introduction on yourself for those who might not know.
3:07:45
Yeah, so I'm so glad you guys had me on today.
3:07:47
Uh we had a very big announcement today.
3:07:50
So um this is something I've been thinking about for 15 years and we announced our new email client called Sunflower today. Cool. Um basically Thank you. Thank you.
3:08:08
It is like basically the opposite of inbox zero. Okay.
3:08:09
Like I think you should have to have an email client that makes you work for it, right?
3:08:14
In other words, like you load up inbox zero.
3:08:16
I don't care how many keyboard shortcuts.
3:08:20
I don't care what what what you give me.
3:08:23
But if I'm having to triage every single email that comes in, you know, keyboard shortcut this way, that way. Yep.
3:08:27
From the Applebee's email, you know. No. Yeah. Yeah.
3:08:32
You need an email client that actually works for you. Okay.
3:08:38
So um on our marketing website we don't mention the word AI one time. Huh. Wow.
3:08:44
But this thing is entirely this this product would not be possible five years ago. Okay.
3:08:53
It's um you know if you want to be if you think you need to be a superhero to use your inbox, there's a product for you.
3:09:02
We're building a product for actual humans. Bold.
3:09:05
And uh it it launches, you know, the the weight list launches today. sunflower. me. Yeah.
3:09:13
Walk me through the product.
3:09:13
The product is like in my phone before this because literally we we broke Slack today.
3:09:21
Like that apparently there's a limit to how many notifications it can send you.
3:09:25
Like it just is dinging, dinging, dinging. That's great. Amazing.
3:09:31
Uh and the product is like already like you guys you guys are the product's like real.
3:09:34
You guys are using it, right?
3:09:34
This is not you're not just launching a weight list.
3:09:37
Like there's there's something under the hood.
3:09:39
We've been working on this for a year and a half.
3:09:40
I use it every single day myself. Yeah.
3:09:44
There's about a dozen people right now who have this. Yep.
3:09:46
Give you guys uh early alpha access. Yeah.
3:09:49
So, talk to me about the actual workflow.
3:09:52
I imagine I still have an email address.
3:09:54
People can still email me, but I imagine an LLM is scanning every email that comes in. Am I seeing the emails?
3:10:01
Am I I I mean, I've used Gmail's Gemini features.
3:10:03
I one time I randomly clicked it and it just typed a response and it was like kind of decent, but it's honestly just a lot of clutter in the UI right now.
3:10:11
Um, how are you thinking about You're kind of hot on the hunt here. I'll be honest. Yeah.
3:10:18
Well, I've been thinking about this.
3:10:19
I've actually was thinking I should just 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.
3:10:30
Apple tried and current mail. app.
3:10:33
It's It's That's not good. Total dog. Yeah.
3:10:35
It's just so funny that 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. Yeah.
3:10:45
Which is kind of silly because status quo of email is a to-do list filled out by other people. Yep. Totally.
3:10:51
And that's that's it, right?
3:10:54
You shouldn't be beholden to that, right?
3:10:56
Just because someone sends me an email doesn't I mean I get a lot of emails. Yeah.
3:11:00
Uh anyways, so yeah, you were you were kind of close.
3:11:05
Um we're going to reveal our hand more and more publicly, but today was like the firing the starting gun.
3:11:11
Like we're building in public now.
3:11:13
So you're going to hear a lot more. Boom.
3:11:16
Don't share your revenue.
3:11:18
If it gets too high, people will copy you.
3:11:19
We don't like building in public.
3:11:21
Based based on the signups you had today, like we are cash profitable if if everyone converts.
3:11:25
But how much how much uh how much of your time are you are are you going to be spending here versus investing going forward? Yeah.
3:11:32
Um that's a good question.
3:11:34
You know, 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.
3:11:44
I totally read I can't by the way I can't read anyone's emails an exhaustive security review process with Google right now. Yeah.
3:11:51
So no there's no reading you sign up.
3:11:54
You can sign up just Google. Just Sundar. Just Sundar. Yeah.
3:11:59
Sundar can Sundar can read your emails, but not Bobby.
3:12:02
I bet I bet he can actually.
3:12:05
I bet I bet they're pretty locked down over there.
3:12:06
Um but yeah, I mean I remember uh the mailbox days and that launched.
3:12:11
Um uh and one of the things that I loved that I loved was that once you got off the incredibly long wait list, it basically tricked you into just archiving everything.
3:12:21
uh which I thought was a great paradigm because you kind of declare email bankruptcy.
3:12:28
You're not deleting these emails so they're still there.
3:12:29
And just that idea of hey it you can you can archive things.
3:12:34
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.
3:12:42
Um what do you think about a funny story about that please?
3:12:47
So I was friends with Gentry when he made cool. Yeah.
3:12:48
And I worked at Facebook at the time. Yeah.
3:12:51
And I went on this hike with my friend Bo and uh literally it's like the Kalao Trail in Hawaii.
3:12:59
It's like a two-day hike. Like you're trekking it.
3:13:02
The entire time he just talked about email the entire time.
3:13:08
He talked about email and the fact that he was about to propose to his now wife.
3:13:12
And I said, "Well, you're on this engagement ring."
3:13:14
Anyways, so I took a photo of him.
3:13:17
Uh it's beautiful photo, you know, right at the end of the trail.
3:13:24
And if you remember that app, you know, when you got to inbox zero, right?
3:13:26
You you saw this beautiful image.
3:13:31
And I and he hated that app the whole time.
3:13:35
It just it just launched.
3:13:35
He was ranting to me the entire time about how much he hated Mailbox.
3:13:39
I was like, "It's actually a pretty good app.
3:13:40
I'm friends with Gentry, etc. , etc."
3:13:45
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.
3:14:05
I said, "You're in the app now.
3:14:06
You're in the app that you you kind of hated that you despised. That's amazing. That's hilarious."
3:14:10
And he he took it a good chance. It was is great.
3:14:14
Yeah, but we're not about inbox zero.
3:14:14
I I think inbox zero is a flawed concept.
3:14:19
I think like you know we're It's funny.
3:14:21
I want you to do this for text. Right.
3:14:23
Right now, I have 3,873 unread texts.
3:14:25
And I have that because I don't feel an obligation like just because somebody had my number at some point.
3:14:33
And like I I really try to respond to the stuff that's important and pressing, but I'm not going to like get home from work and be like, "Oh, I I got to respond to this person instead of hang out with my kids, right?"
3:14:46
Like it's it's not No, of course.
3:14:48
Everyone feels entitled to your time. Yeah. Right.
3:14:53
I, you know, look, I'm an investor.
3:14:55
I get the same emails probably we all do, right? Like about 20 a day.
3:15:02
And they're all like drip auto campaigned follow-up.
3:15:04
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 every single successive email like tries to guilt you into actually, you know, replying.
3:15:16
Like start using more and more emotionally manipulative tactics.
3:15:20
Y And it's like, no, no, no.
3:15:23
Just because you know my email address does not entitle you to my time.
3:15:28
Yeah, I think that's right. What do you think about?
3:15:30
Are you gonna are you going to tag Are you going to are you going to like identify like emails that are being dripped versus, you know, artal organic farmtotable emails? We're working on that.
3:15:41
Um, you know what we're also working on?
3:15:44
I again, you know, there's a funny Steve Jobs quote.
3:15:46
Isn't it funny to ship that leaves from the top? But here you go. Um, that's great.
3:15:51
Um, you know, you know, like email trackers, you know, like obviously Superhum does this like I'm like, you know, you see, you've seen it.
3:16:02
Y, we both allow you to block inbound uh trackers and we'll also let you send your own. Nice.
3:16:11
So, our thing is like we are just so 100% focused on the individual user.
3:16:16
M um so in other words like if you want to block um these trackers perfect we'll let you do that and then you can send your you can send a tracker of your own.
3:16:28
I like having those trackers.
3:16:29
I like letting the SDR know I read this 10 times and I'm still not responding. Yes.
3:16:34
You know that 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.
3:16:41
It just keeps pinging the pixel.
3:16:43
So the SDR is like this person.
3:16:46
They're reading it for hours every day. What?
3:16:48
But they haven't responded. What's going on?
3:16:50
You just do their tracking pixel.
3:16:52
What What is your take on Eric Mikovsky, founder of uh Pebble.
3:16:57
He started this company Beeper, eventually sold it to Automatic.
3:17:03
Um and the whole idea was get into the iMessage world, create one unified inbox for all the different messages.
3:17:09
I think he had a knockout dragout fight with Apple uh because he was reverse engineering some of the APIs.
3:17:15
Um obviously there's changes on in big tech around antirust and it maybe now is the time to put pressure on that.
3:17:22
Uh is there a world where we could see text and email kind of unify at some point?
3:17:29
What's your view on kind of the long term here with big tech?
3:17:30
I mean look, we we have a we have a long-term strategy.
3:17:37
I'm not going to come on your podcast and just spill all the means.
3:17:44
Spill spill activate golden retriever mode. What was that?
3:17:47
Activate golden sign up for golden retriever mode where you're where you're friendly and dumb. Yeah. Yeah.
3:17:57
Golden retriever would just tell golden retriever. Tell everyone. No. No. No. No.
3:18:03
You can you can come on again and you know you know spell I one of your companies and I passed another one. So Okay.
3:18:11
Um anyway, yeah, future of text email.
3:18:14
So, I'm mostly concerned about email.
3:18:14
I think email it's like what's old is new again, right?
3:18:19
And so, if I again, if I if I if I were a ship that's spilled from the top, here's what you have to here's what I have to say.
3:18:26
Um just like Apple built iMessage on top of SMS, I think there's a layer to be built on top of email. Mhm.
3:18:37
That's all I'm gonna That's all I'm gonna tease. Give us more anyway. Yeah.
3:18:40
No, no, I think it's I I think I think that's an interesting Yeah. framework.
3:18:46
So, I I don't I don't want to own all communication like I I don't want to, you know, pull pull it on one place.
3:18:52
I just want to clean up a mess that is email. Okay. Yeah.
3:18:54
It is an interesting time, right?
3:18:56
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.
3:19:11
We talked with TJ yesterday about how he was spending 30% of their dev resources or something like that on fax machines, right? Pill pass.
3:19:20
When I worked at Facebook, we had we launched as a joke just the Techrunch network only.
3:19:24
We launched a feature called fax this photo. And they covered it. Wow. No way. Yeah. Yeah.
3:19:33
It was literally launched to troll them. Oh yeah.
3:19:34
You can Google this story like Techrunch Facebook this photo.
3:19:42
Um my engineering buddy Evan uh we were we were launching all these things one day. Fax your photos. Not 2009. Wow. Yeah. There you go. That's amazing.
3:19:52
Okay, so Facebook punked us.
3:19:52
This isn't really going live for everyone. Tech Network.
3:19:57
They they they tried to like pretend like they were in on the joke, but no, they were. That's very funny. Got him.
3:20:03
Also, by the way, our fun with tech didn't know the joke either.
3:20:07
And so this guy Blake Ross, he had to run upstairs like in a in a in a frantic rush saying, "Guys, guys, guys, guys, it's just a joke. It's just a joke." Yeah.
3:20:17
full stack verticalized MOG. It's amazing.
3:20:20
Well, thank you so much for coming. What's the real thing?
3:20:22
Anyways, Bobby, this this was super fun. Congrats on the launch.
3:20:25
Uh I'm excited to try the product and come back on.
3:20:27
Come back on as you have more uh more news to share. Amazing. Uh sunflower.
3:20:31
me if I can get a plugin. For sure. Let's do it. Go check it out. We'll talk soon. Go there now. See you guys.
3:20:37
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3:20:53
And we got Orin Hoffman coming in the studio. He is here.
3:20:59
So, welcome to the stream, Orin. How you doing? What's going on? I'm doing great. Happy to be here. Very excited.
3:21:04
Great to Great to finally have you on.
3:21:06
Probably should have done this a long time ago.
3:21:08
We we we had a brief phone call, I think, a a couple years ago. Good to reconnect.
3:21:11
Uh what's the latest in your world? Well, things are great.
3:21:16
We're uh we've got a couple different things.
3:21:17
We run a uh like a weird holding company where we own a bunch of data companies, start different data companies.
3:21:23
Y and then uh then we're also at uh Flex Capital where we do a lot of seedstage investing.
3:21:28
We did 20 deals last quarter.
3:21:30
Our goal is to do about a hundred per year. That's amazing. Yeah.
3:21:34
We were kind of struggling to find what your title should be, so we just put founder and investor because you you got you wear a lot of hats. That's good.
3:21:40
I I think you got like Sam Leon on today.
3:21:42
I'm like an aspiring Sam Lesson. So, okay. Okay, that's great. That's great.
3:21:46
We all How are you on the slopes? So, you a good skier?
3:21:49
No, I'm not aspiring Samson. I'm not at that stage.
3:21:53
Yeah, I'm only aspiring on certain things.
3:21:55
He's got like 20 other dimensions. I'll never catch up.
3:21:59
He plays a lot of tennis. He yaps a lot, but Yeah.
3:22:01
He runs like three minute miles. Yeah. So, okay.
3:22:04
I haven't talked about running on the on the data side of your business.
3:22:09
How was that an AI bet that you made a long time ago?
3:22:13
Is it is it did you get lucky?
3:22:15
Did you have incredible foresight?
3:22:21
I think I got on I I think I had the wrong bet.
3:22:22
Um and so I think on the data business uh I think we had believed that as the that these companies that sell data like data as the ingredient not just like analysis on top of data the ingredient.
3:22:34
We thought that these companies would become like way more valuable because we thought the number of buyers of data is would go up significantly.
3:22:41
Uh 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.
3:22:51
There's 11,000 hedge funds.
3:22:53
The market's going to go from 50 to 500.
3:22:56
Um I think it the market went from 50 to like 58 um over the last 10 years.
3:23:01
So it really didn't go up.
3:23:03
retailers or maybe 20 retailers that bought a lot of data.
3:23:06
Um, 10 years ago, how many out of your out of your if you this will be tough to remember specifics, but a lot of like seedstage companies will be like, oh well, we're going to generate this data and like we're going to sell it eventually and it's going to be valuable and it's like, oh, and then you kind of press them on it.
3:23:24
It's like, well, like hedge funds will buy it.
3:23:25
will buy it. And then it's like okay like are you confident that those 58 hedge funds or have have you seen have you seen any of those are ter they're a terrible market it's a very small market um and they really most of them are even like the biggest hedge funds in the world like Bridgewater like the amount
3:23:41
of data they buy is minuscule compared to the AUM it's like it's basically zero um and is that just because they spend more on like launch than 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. They have some They have some data.
3:23:58
They have data that you could put in an Excel file and stuff like that.
3:24:02
And these are not like they're smart people who are thinking about quote unquote data.
3:24:06
But when you actually think of like a data business that's selling data, proprietary data, different types of data um and usually data that's like larger than you could like put in Excel file.
3:24:15
Uh most funds are not doing it.
3:24:19
Uh most they're really really Yeah.
3:24:22
really Yeah. If you think of like real estate um 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 um it's going from zero to one real estate is a pretty big asset class now they're using some data there still people are using still some data but really like we're talking
3:24:42
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 I I I we've been thinking a lot about Google IO and V3 and Google's advantage in video generation particularly because they own YouTube and YouTube feels like an incredibly valuable data source. Correct. And it's almost but the whole Correct.
3:25:05
And it's almost but the whole like data is the new oil.
3:25:07
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 that right and so the like yes the data market would be bigger if all of these assets actually
3:25:24
transacted and were funible like oil but they're not they're super proprietary brand your data is more valuable 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
3:25:41
They sell that to Google for $60 million or something to train their LLMs.
3:25:45
And but if you if you had just like lots of people having interesting conversations, but you weren't called Reddit. Yeah.
3:25:51
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.
3:26:04
What about just uh creating data for the purposes of artificial intelligence?
3:26:09
Not pulling data from other sources and trying to go find a round peg in a square hole with selling into a hedge fund.
3:26:16
More 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 I like that. Yeah.
3:26:23
I mean obviously like scale AI is a great company, right? So they're doing that.
3:26:26
They're actually going and building those types of data.
3:26:28
We just in we're we're investing in a company kind of doing what you're saying with the robots.
3:26:33
Um, I I think those types of things are good, but it's not always just for the AI.
3:26:37
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.
3:26:47
That's not a great market.
3:26:47
Um, and you went from 58 to you went from 58 to 12. Yeah, exactly.
3:26:53
So, do you just want to sell to OpenAI, Anthropic, Google, and Facebook?
3:26:58
like and maybe a couple of others like I don't know that doesn't seem like a great business long term either. Yeah.
3:27:04
And and if the deal the first deal that you do is 100 million what's the deal size on the next one?
3:27:12
You know, do you are you going to create a hund00 million worth more data that you can sell to them?
3:27:16
Is it even that valuable?
3:27:18
Anyways, um the the wanted to have you on specifically to talk about a a post that you had yesterday that uh went pretty viral.
3:27:26
Uh you said that any VC that makes you pay for their lawyers is not founder friendly.
3:27:33
Founders barely affording rent should not be footing legal bills for VCs with private jets.
3:27:36
And yet this is standard.
3:27:39
Uh you kind of extrapolate on this, but you're writing, you know, uh 20 checks a quarter, maybe more.
3:27:45
Uh I'm sure that almost every single one of the companies you back ends up uh you know having to pay some VC's lawyer bill maybe in the next round.
3:27:55
Um but what I would love for you to kind of break down the post and what inspire Yeah.
3:28:00
For those people who don't know, in a 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.
3:28:10
And that X can be negotiated and it's it can be as low as 10 grand and I've seen it as high as 300 grand for more complicated deals and stuff like that.
3:28:22
Um, and it's there and it just it seems it seems odd for a whole bunch of reasons.
3:28:27
First, it's like there there may be many different investors, but you're only paying the lead investors types of things.
3:28:33
Second is that um uh you know, why are they you know, why are they actually having the company pay?
3:28:41
It's it's it's like a little bit of backdoor way to get your fees paid.
3:28:42
Um and then there's like there's like a a more complicated argument as well, which is I don't think this is LP friendly.
3:28:50
A lot of a lot of VCs will say this is LP friendly.
3:28:55
Um because then I don't have to like Yeah.
3:28:58
Wouldn't the person paying presum you you can pass it I mean that the VC could pass the fees on to their LPs.
3:29:06
So in 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 um by taxing the the company.
3:29:17
It's it's taxing the company but but it's a it's it's a it's even the LP isn't aware of it.
3:29:24
Whereas if you actually normally if you if you use Tigus or something and you pass it on to your LP, your LP sees the bill and they're like, "Why are you spending 50 grand on TGIS?
3:29:34
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.
3:29:41
There's a whole bunch of reason.
3:29:43
Can you give me more clarity around like the idea of passing fees on?"
3:29:47
So like the real the real fees.
3:29:49
So So VCs have like two and 20, right?
3:29:51
But then there's certain fees that you can pass back that it gets it closer to even three.
3:29:54
You could get it up to like two and a half, three, yeah, four percent.
3:29:58
And that could even be like when a VC pays for lunch with a founder, you can pass that on. Correct. Interesting. Yeah.
3:30:05
And every VC has a different model.
3:30:07
When we I always thought it would be like there's 2% fees and then you got to do whatever you want with that.
3:30:12
If you need a private jet, like that's coming out of the 2%.
3:30:14
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%.
3:30:19
But you're saying it can be passed on.
3:30:21
The the true loaded fees can be much higher than 2%. Interesting. Yeah.
3:30:25
Like at Flex Capital, we try to almost do everything in the 2%.
3:30:29
So if we go to lunch with we take it out of our own management fee, which means we get less compensation because of course you you most VCs want to protect that 2% that goes directly to them, right?
3:30:38
them, right? we get less competition but we think it's more LP friendly and then we'll you know there might be certain things like your your fund audit might be done to the so you have to decide okay what is what's actually done to the fund versus what's done to the management company so we'll we are more
3:30:54
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 I'm passing fees at least the the the LPs do see it yeah and then they can have a conversation like hey why are you do spending all this money with lunches to to me? Why am
3:31:09
Why am I paying for your lunch to go to Spago or something?
3:31:14
So whereas with the with the with the uh with the um uh legal fees, they don't know.
3:31:20
They have no no the LP has no way of accounting that money.
3:31:26
What about like general pressure to bring down the cost of startup legal fees at the series A level?
3:31:31
Uh Justin Khan was working on a project with Atrium to try and automate the the series.
3:31:40
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.
3:31:52
But that's still that's and that by the way that's mod's amazing and that's that's definitely step one.
3:31:58
Like you got to negotiate that gap.
3:32:00
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.
3:32:05
My guess is also it it also depends on h the the higher the cap, the longer it will be to close your round.
3:32:12
So, most people know you get Shouldn't it be the other way around?
3:32:18
No, the higher if it's a high cap, the the lawyers are just going to be like, "Yeah, this is going to take because it should be it should be price.
3:32:25
I'll pay you 300k to close it this weekend or 50k and yeah, you can take a month."
3:32:30
I can basically tell you like here's how you close your round.
3:32:33
It's going to be it's 15 days. Yep.
3:32:33
Plus one day for every $2,000 that's in that 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.
3:32:46
Shouldn't Shouldn't One def 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 in salary and if they want to lead around that that ends up getting priced it could get expensive but your argument is still like okay well be ls are still eating that that cost.
3:33:12
Yeah, I mean look, it can be negotiated and maybe in some cases it could make sense that's in there, but there if if you're why are you doing something so complicated?
3:33:24
I mean, YC created the safe.
3:33:26
The safe doesn't have any legal costs, right?
3:33:28
Really, um you you can actually use a pretty boilerplate uh uh thing.
3:33:33
You you most of these terms you should be negotiating in the term sheet anyway.
3:33:38
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?
3:33:43
It's because probably you're not managing the lawyers.
3:33:47
The lawyers have no incentive to to keep the cost low because they know what the cap is.
3:33:51
If the cap says 50k, I guarantee you you're getting a bill for no less than 49K.
3:33:57
Um like in in the history of the world, I doubt it is almost ever come in less than 49K for a cap of 50k.
3:34:06
like how do they automatically always hit because they're they're filling the space. They're built different.
3:34:12
Uh 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?
3:34:20
It's like if you're just getting past the costs and you're like eating that, but you're not getting like the the incremental kind of dollars deployed into the company. Yeah.
3:34:28
Or like the incremental ownership.
3:34:31
Is it does it I mean I guess like where I'd want to go with this is what do do you have conviction or or any excitement around tools that can be like AI tools specifically that can be introduced into the proc like basically that um 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 we just did a we were just involved in a company that did term sheet to close in in six days.
3:35:01
Like it's not that hard, especially in the early stages of a company.
3:35:07
Like how much diligence do you need to do?
3:35:08
You need to and look, the company did a good job.
3:35:13
They got all their stuff in a data room.
3:35:15
They did all the things that they were supposed to do.
3:35:17
Then as the venture capitalist, okay, well, you've got to you've got to somehow read it. Read through it.
3:35:22
Maybe you can use AI to read through some of it. You got to go check it.
3:35:26
You have to make sure that the the bank account is legit and all these other types of things that isn't fraudulent.
3:35:31
But it shouldn't take that much time.
3:35:33
The main reason it takes a really long time is just the back and forth.
3:35:37
You put a red line in, I send it to you, then you don't have time to look at it that day.
3:35:41
It takes you three 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.
3:35:46
So they got all in a room on day six and they basically put like a 4hour block and they said, "We're going to just go through every single issue right here."
3:35:54
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 it just got done it's so much easier and obviously even M&A agreements like you should be able to get those
3:36:07
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 go faster than VC because everyone's just motivated to really work on it and put in the time to make it happen. Yeah. Yeah.
3:36:28
Well, thank you so much for stopping by. Come back on again soon. I love it. Invite me anytime. Yeah, this is great.
3:36:33
Yeah, we'll make it happen. Yeah, great hanging. Talk to you soon. Cheers. Bye.
3:36:37
Uh yeah, we have some breaking news.
3:36:37
Uh the first nuclear executive order has dropped.
3:36:43
Uh I'm going to read here from one call out that people are celebrating.
3:36:47
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 gawatts of power upgrades to existing nuclear reactors and 10 new large reactors with complete designs under construction by 2030.
3:37:04
This is exactly what we were asking for with let's copy paste Diablo Canyon.
3:37:09
We have Doug Bernau from Radiant Nuclear in the studio.
3:37:14
uh we're going to bring him in and get his breakdown on it because he's obvious we had been working in this industry for years and should be able to give us an update on uh what's happening.
3:37:23
Thank you so much for joining the show, Doug.
3:37:25
Uh been too long since I see saw you.
3:37:28
I think I saw you in DC last, but uh should be an exciting day, but can you give us your read and analysis on what's happening?
3:37:37
Yeah, it's unbelievably exciting.
3:37:39
There's a whole lot of uh text.
3:37:39
I had these fact sheets that came out.
3:37:41
I think went to the media on all these executive orders.
3:37:44
Um, it's unbelievably exciting, but it's all coming in like right now.
3:37:48
Just I think the the actual official documents just got posted only minutes ago. So, I I haven't read. So, you're an expert.
3:37:55
You're an expert is what you're saying.
3:37:56
Well, we really put you on the spot.
3:37:58
Um, but I mean, can you talk to me about a little bit of the a little bit of the history?
3:38:02
what uh I mean first introduce yourself, what the company does and then maybe we can build up to some of the uh maybe problems or areas for improvement that the industry has been asking for and then we'll kind of dig into um what's happening today. Yeah, thanks.
3:38:20
So I'm the CEO of Radiance uh nuclear portable micro reactor company.
3:38:24
We're focused on mass production of 1 megawatt reactors.
3:38:25
We'd like to see 50 of those per year.
3:38:27
um and they'd come off a factory line and then go out to the customer wherever they are, run for five years, and then come back and be refueled.
3:38:34
So, it's a very unique sort of model.
3:38:36
And my background before that I I worked at SpaceX for 12 years.
3:38:39
Uh worked on the first rocket with legs amongst other really cool stuff for Elon, but eventually focused on nuclear.
3:38:45
And uh it's a it's a really unique model that we've been trying to work.
3:38:50
You know, a normal reactor is about a thousand megawatts.
3:38:51
The thing we're working on is one megawatt.
3:38:53
Um it's got to be road transportable.
3:38:55
We're trying to make the nuclear power that people want because the problem that we see uh with why we don't have all this nuclear technology today is really that there's not as many customers.
3:39:03
But that has all completely turned around I don't know in the past maybe just two years right with all these announcements of the big data center players coming in to buy nuclear to restart old plants to build new ones.
3:39:15
Um 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.
3:39:24
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.
3:39:36
And so it's not really focused on or talking about the right sort of thing.
3:39:40
So yeah um when we last spoke you were working on the helium loop going to test at a dome in Idaho. Uh how are things going?
3:39:48
What have been the most recent updates for Radiant?
3:39:52
Yeah, there's some unbelievable updates.
3:39:54
Just a month ago, we were announced as one of just five companies who will get access to fuel from the Department of Energy.
3:39:58
Uh something we've been working on for a very long time.
3:40:00
It's unbelievably exciting.
3:40:02
Uh when I started the company back in 2020, we said we would do a critical test with a reactor at full scale in 2026.
3:40:08
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.
3:40:16
Um another change just recently, you know, we've been working through a process they have at the national labs.
3:40:22
Uh we're working with Idaho National Laboratory.
3:40:24
Um and a fun context setter here, they they've tested actually 52 reactors in their history. Wow.
3:40:28
Uh although the last of which was in 1977.
3:40:34
So it's been a while and we have a kind of old process and they are aware.
3:40:37
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.
3:40:46
It is sort of lower for the new reactors, but there definitely are staff who are there who, you know, there are uh the advanced test reactor, the ATR reactors where they test all the navy fuel that's been operational for a very long time.
3:40:57
You can go tour it today still operating.
3:41:00
So, there are definitely uh staff there who are very familiar with reactor operations and refueling.
3:41:04
They also have a transient pulse test reactor uh which is pretty amazing.
3:41:08
Actually has an original core from the 1950s still running and operating.
3:41:12
It I forget what the numbers are, but it pulls into the several gigawatts range.
3:41:18
Um, so that there's some expertise there, but certainly there are not people there from the early 1970s anymore.
3:41:24
Okay, I have the uh Wall Street Journal article pulled up.
3:41:27
I want to read some of the key points and uh just get your reaction.
3:41:31
So uh the high level is that Trump signed executive orders to boost nuclear power industry citing the need to overhaul regulations and fasttrack licenses.
3:41:39
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.
3:41:46
There's an interesting wrinkle there where a lot of the hyperscalers made very aggressive ESG targets and uh climate pledges before they knew that they were going to need 50 gawatts of capacity.
3:41:58
Uh and so now they're really really pushing for clean energy.
3:42:03
Uh the executive order aims to shorten approval times for new reactors, but critics worry about the impact of safety.
3:42:09
Now I want to talk to you about that balance between speed and time to market and safety.
3:42:14
I wouldn't trust myself to design a nuclear reactor and get it approved in a day.
3:42:18
Uh but it feels like we haven't had a new reactor design approved in way too long.
3:42:23
And so we're probably on the too slow uh side of the curve. But where should we be?
3:42:31
What is a reasonable amount of time to actually approve a new reactor design in your opinion?
3:42:36
Yeah, I mean probably on the shortest scale, it's got to be something like six months.
3:42:40
Like if I use that context I said earlier, 52 reactors in up till just 1977, nuclear technology only existing since the mid-50s.
3:42:46
That means they were doing more than two per year. Yeah. Yeah.
3:42:50
Let's get back to that standard, right?
3:42:52
Um walk us through what what what uh 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?
3:43:03
Is this you I need a physicist to run all the numbers in a spreadsheet and run simulations?
3:43:11
Do we need to just fire this up in a place where even if it explodes it's it's you know we've seen that it didn't explode and so we've done real world testing.
3:43:19
Is it a balance of those?
3:43:21
What kind of testing do you think uh is best that can be executed at speed? Yeah.
3:43:25
Well uh it's a great question.
3:43:28
The best is immediate testing and incremental testing. Yeah.
3:43:31
Um and there's no reason that um you you necessarily need to go slower.
3:43:36
You can regulate along with the speed with which you can do the design, the analysis, the procurement, the assembly of a reactor.
3:43:44
Um if a company's willing to spend capital to take that financial risk, um you know, the the goal is don't put fuel in unless you get an approval.
3:43:51
But there should be really zero barriers up until that point because there's no safety risk. Yeah.
3:43:56
Um but then when you get to that point of like, okay, now there is risk.
3:44:01
We are going to load fuel in.
3:44:01
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 the what the plan is.
3:44:08
But the fact of the matter is when you load fuel, it's not anywhere near critical.
3:44:14
You can make a you can look at subcritical multiplication factor that will trigger little sensors that are effectively it's you know something that sounds like a geer counter.
3:44:20
We use fancier things today. We use vision chambers.
3:44:24
We use boronline proportional counters.
3:44:25
counters. uh 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 one sixth of your core you can already validate models um and yet you are ridiculously far away from being
3:44:39
able to go critical interesting they haven't even assembled the whole system right yeah so uh the the FDA has similar approval timelines for new pharmaceutical drugs but uh the the the reason that it takes a long time to to approve a new pharmaceutical drug in America. It makes more sense to me if
3:45:01
It makes more sense to me if I'm going to take a drug, I kind of know, hey, is it going to have an effect on me in 30 years?
3:45:06
Maybe I want to see a mouse model or monkey model or a dog model or human testing over a long period of time.
3:45:12
And sure, there's some acceleration there.
3:45:14
We don't need to wait a full lifetime to approve a new drug, but there is an element of time.
3:45:19
Is there anything that's that's comparable to that in nuclear where the behavior of a system over a two-year time period is different than a behavior of a system over a 2hour period? Yeah.
3:45:32
I I think the the most similar thing would be the effect of neutron fluence of the core.
3:45:35
So if you hit some parts of your system with neutrons, they will generally swell up.
3:45:43
Metallic parts swell up and their conductivity will usually go down. Their density goes down.
3:45:47
But the physical shape of them changes. Sure.
3:45:49
So you might have to test that in some special way to know what a 10-year lifespan looks like, right? Yeah.
3:45:56
But a lot of these materials have been tested and there are these giant data handbooks that that it's very predictable.
3:46:01
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, but we had a ton of help.
3:46:10
Um we went and recovered this great national asset and it's now available for all reactor developers. That's amazing. Yeah.
3:46:17
So, uh, they're pretty predictable effects.
3:46:19
So, there's not, I would say there's really, other than the effects of neutron fluence. Yeah.
3:46:22
Um, there's nothing really, um, that challenging.
3:46:24
We plan to test right next year in the dome.
3:46:28
Uh, that is a hermetic structure totally sealed with its own radionuciide detection, uh, in it.
3:46:33
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?
3:46:41
and uh experimental uh hot cells and other um 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.
3:46:54
Uh were you is it uh funny to you that the the news of Taiwan decommissioning their reactor is hitting the same week that we're saying that uh we need more uh or or is there something about Taiwan's as a as an island?
3:47:12
I I'd read something about there being a bunch of um you know enough earthquake activity in the area that like there was some potential reasoning around that.
3:47:22
But then I we also had someone else on who said we that we have solutions for that at this point.
3:47:25
It's not a a risk that should require shutting it down entirely.
3:47:32
I don't know that these things are linked actually.
3:47:33
I think I'm I'm behind on the the Taiwan reactor news.
3:47:35
Um those might have just been around for a long time. Might be coincidental. Yeah. It's not No, no.
3:47:42
I I'm not implying that they're linked.
3:47:44
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 uh country saying we're shutting these things down meanwhile and they're less far less energy independent Germany kind of doing the same thing.
3:47:58
It feels like some c like some countries are following the American nuclear book from two decades ago and maybe they should be adopting the playbook from today and and they need we'll just announce it today and yeah hopefully not.
3:48:10
How how like how monumental is this for you?
3:48:13
Were you like betting the company in some way on eventually getting an administration that would like introduce an EO and like you know try to bring about policy around this.
3:48:25
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 right the way that the
3:48:40
administration or the 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 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
3:48:56
You lay out a vision go like imagine you have like a bunch of reactors.
3:49:00
They're all built identical to one another, so they're super reliable.
3:49:04
You deploy a whole fleet of them.
3:49:04
They all stream data back continuously.
3:49:06
We're in the modern world.
3:49:08
We're in the information age.
3:49:09
Why can't all that data just stream to the regulator?
3:49:11
Why can't it be completely modernized?
3:49:13
Um, and we've been talking about that for a while.
3:49:18
And I think that has led to now uh that along with other things people have said have led to these sort of events where an administration goes okay we're going to just we're going to actually go and support this. Yeah. Right.
3:49:30
Uh last question from my side.
3:49:32
Can you talk a little bit about how you see the market playing out?
3:49:34
Obviously there's some news about we might be getting really big nuclear reactors at the one gigawatt scale.
3:49:40
You're building at the 1 megawatt scale.
3:49:42
Is there going to be a 10 gig a 10 megawatt company, a 100 megawatt company?
3:49:48
Is it a smooth all the same company and you just Yeah.
3:49:51
Or or maybe they're maybe they're bundled or or broken down or scaled up or scaled down like where like how will this play out and and and who will do what I guess? Yeah.
3:50:04
Well, as a consumer what you want is for there to be two or more companies at each scale. Yeah. Right.
3:50:12
And uh yes, there will be something at the portable micro reactor scale.
3:50:14
Two two companies there at least and maybe that's one megawatt and smaller.
3:50:18
Um 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.
3:50:27
I call it a micro reactor 10 megawatt scale.
3:50:29
So you want two companies there.
3:50:30
You want two at the 100 megawatt.
3:50:32
You want two or more at the gigawatt also.
3:50:34
Um because they're different different areas uh need these amounts uh power.
3:50:40
need these amounts uh power. So if you think about and we never think about these places there are remote places in the world like in Alaska you have over 150 disconnected micro reactor locations or micro grid sorry locations that could use reactors Canada has over 200 of these sort of areas and these are coastal you know look at those land
3:50:58
areas on the map they're 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 those types of regions um And if you put in a one 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 two like
3:51:18
So on the two like extreme ends of the scale, there's like pretty obvious use cases.
3:51:22
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-doll 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.
3:51:36
We can put a 10 megawatt reactor that's economical for us, right?
3:51:39
without over complicating it or having to add power lines uh extending across states. Awesome.
3:51:43
Well, thank you so much for popping on.
3:51:46
We'd love to have you back again to go even deeper.
3:51:49
Congratulations on the overnight success.
3:51:51
I know the job's not finished, but uh I like uh I like this for you guys. Yeah, this is great. It's great news.
3:51:57
Yeah, it's really exciting.
3:51:57
I mean, one of the coolest things they they asked to reform the process that we're using at National Laboratories to test reactors.
3:52:04
That's going to be extremely critical to us staying on our schedule.
3:52:09
we will achieve going critical next year uh because of a lot of things happened today. That's great news. Thank you.
3:52:17
Thanks for joining, Doug. We'll talk to you soon. Amazing milestone. Cheers. Good luck. Talk to you soon.
3:52:21
Uh I wanted to pull up, we're going to stay on nuclear for a little bit. We're going long.
3:52:27
Uh we wanted to pull up Scott Nolan, my former colleague at Founders Fund and the CEO of General Matter, a nuclear fuel uh refinement company was in the White House. CEO of General Matter.
3:52:38
We're an American enrichment company trying to bring back the US's lead in producing nuclear fuel.
3:52:42
So just like car engines need fuel, nuclear reactors need fuel.
3:52:46
Right now the US is completely dependent on other countries to make the key step of enrichment in this fuel and these executive orders are going to pave the way for the US to regain its lead.
3:52:56
So we really appreciate it.
3:52:58
Will you be doing the AI plants because we have a lot of them going up now and or soon going up and they need tremendous electricity.
3:53:04
Are you going to be involved in many of these? Yes.
3:53:06
Will Scott Nolan, CEO of General for Scott, the White House.
3:53:12
Uh, color temperature a little bit off on that video, but otherwise fantastic. Um, yeah. Well, congrats to Scott.
3:53:20
I mean, from Valor in the waiting room. We're bringing him in. Let's bring him in.
3:53:28
He's also has he been in He's been in the capital.
3:53:30
Yeah, I think he was over there today in DC. Let's bring him in.
3:53:34
Uh, and he is building at the 10 megawatt scale and so there everyone's got everyone's playing in the different market. Got to play. There he is.
3:53:42
Thanks so much for calling in.
3:53:45
Can you give us the breakdown? How you doing? Doing really well.
3:53:49
Thank you so much for having me on, guys.
3:53:50
I'm uh I'm actually just coming back from going live on a a little upstart called Bloomberg TV.
3:53:54
So, you know, it'll take a while for them to catch up to your stature. Yeah. Yeah.
3:54:01
It's kind of like a Thank you so much for It's like kind of like a feeder system. Feeder system.
3:54:04
Uh can you go horizontal with your phone? Yeah. Yeah, sure. Yeah, that's right.
3:54:09
A little feeder network for the technology others.
3:54:12
So, yeah, great to be in the temple technology today.
3:54:14
Yeah, it's good to have you. Break it down for us.
3:54:16
Uh we we we read kind of the highlights, but uh what were the key uh the key pieces of the EO in your opinion?
3:54:27
Yeah, listen, this is a total rewrite of the regulatory system in the United States for nuclear energy.
3:54:30
You know, nuclear grew up in the US with a total um dominance of nuclear power in terms of US uh strategy, right?
3:54:39
So, we had the only nuclear reactors in the world for a while.
3:54:43
We piloted essentially every nuclear reactor architecture that there is and we wanted to protect that edge and protect that advantage.
3:54:49
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.
3:54:57
We wanted to protect this advantage.
3:54:58
This is a natural instinct.
3:55:00
I think it was a good instinct at the time.
3:55:01
Uh but the problem is that over time our competitors or you know ge geopolitical rivals built nuclear anyway and 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 you know a large wall around an empire of dirt.
3:55:17
And so today, this is about bringing those barriers back down, allowing American entrepreneurs to to build nuclear energy again.
3:55:23
There's a couple really important things announced here.
3:55:26
One is revitalizing the Department of Energy.
3:55:29
So the Department of Energy was created to be a nuclear test agency.
3:55:34
Not a lot of people realize this, but the DOE, we kind of imagine it to be this, you know, broad-based energy agency, and it is, but it was actually created to be a nuclear reactor test agency.
3:55:43
And since it was created, it's only done that one time.
3:55:47
And so this is about revitalizing that.
3:55:49
And actually, President Trump has given a strong commission to the nuclear industry.
3:55:53
He wants three test reactors critical on US soil by July 4th, 2026, America's 250th birthday.
3:55:59
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, you know, full steam at hitting that goal at turning on a reactor by July 4th, 2026 at the San Rafale Energy Test Center in Utah.
3:56:17
So that's what we announced today. Congratulations. That's amazing news. Good luck. Thank you. Overnight success.
3:56:25
Um so yeah, I mean it seems like uh with any nuclear project, regulatory is always the main risk, the main uh rate limiting factor.
3:56:33
Uh with regulatory out of the picture, is this more of an engineering challenge now?
3:56:38
Is it a manufacturing challenge?
3:56:40
Like how do you weight the different challenges ahead for you to hit that deadline? That's absolutely right.
3:56:46
Listen, you know, nuclear is is a technology that we've been exploring for 70 years now.
3:56:51
We've done an enormous amount of physics around this.
3:56:54
We've done an enormous amount of research.
3:56:55
The thing that has stood in the way is one company deciding to do the SpaceX of nuclear, right?
3:57:02
Deciding to own nuclear energy, full verticalization from the design of reactors to construction to manufacturing to deployment to operation.
3:57:09
That's what Valor Atomics is attempting to do.
3:57:11
There hasn't been a Ford of nuclear energy yet.
3:57:13
There hasn't been a Tesla of nuclear energy yet.
3:57:16
There hasn't been a SpaceX.
3:57:16
Valor Atomics is intending to be that company.
3:57:20
And regulation has absolutely been the long pole in that tent.
3:57:22
So this executive order is incredibly important.
3:57:25
You know, I think this is really going to set the tone for the next 100 years of energy dominance.
3:57:28
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.
3:57:34
Talk about the first product.
3:57:36
Uh 10 megawws, is that correct?
3:57:40
25 megawatt electric is our our commercial model.
3:57:42
So you know Atomics is yeah we you know we've gone out and we've really hit an ambitious milestone.
3:57:47
You know I founded this company about 17 months ago.
3:57:49
We were intending to go out and build our first prototype reactor in 18 months.
3:57:54
We finished it in 16 months.
3:57:57
This is a test reactor sitting in our Los Angeles facility today.
3:57:59
We've operated above temperature, above pressure, not with uranium, not splitting atoms yet, but with electrical simulation.
3:58:06
And really what we've proved that is that it's possible to build a nuclear reactor in under 18 months.
3:58:10
Now that we've done that, we go and actually build it again in Utah and another one in the Philippines.
3:58:16
And we actually load them with uranium for the first time, turn them on.
3:58:20
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.
3:58:31
Just draw the rest of the simple, boys.
3:58:34
Just draw the rest of the owl.
3:58:34
Yeah, we make we make thousands of nuclear reactors.
3:58:37
We make trillions of dollars. I'm very excited.
3:58:39
It's a good day in energy.
3:58:40
Yeah, I mean it's fantastic.
3:58:40
I I I uh you know, we were just talking with uh Doug from from Radiant and in many ways like if you started a nuclear company at any point in history, be rough.
3:58:53
You were betting on activity like we're seeing today and and action.
3:58:56
And so super validating for for you guys that had to get looked at like you were crazy in a bunch of pitch meetings early.
3:59:05
Uh cuz it it feels like one of those things where like culturally I think in 2020 people started kind of waking up to like hey wait nuclear is pretty cool and probably good and we probably want more reactors not less. Yeah.
3:59:19
And then companies that you know have have started picking up.
3:59:21
How important is it for you to vertically integrate into the actual productive use of the energy?
3:59:27
It feels like there's so much demand for energy.
3:59:29
You could just become a mass manufacturing for nuclear reactors and that would be enough of a business.
3:59:37
We when we talked last time about a year ago, you were talking about uh generating uh 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.
3:59:50
Is there still a plan to do something with the energy that you own and control and just and and and decide or is is it just like let's just make as many nuclear reactors as possible right now? Yeah.
4:00:02
You know, one of the core realizations of Valor is that there are some products that the market actually doesn't know how to buy, right?
4:00:11
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, right?
4:00:20
You can't just build a rocket.
4:00:21
You have to fly them, too.
4:00:21
And the reason is that the customer actually doesn't know how to fly the rocket, right?
4:00:26
A small sack company, a telecom company doesn't know how to fly a Falcon 9.
4:00:30
And so it turns out the 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?
4:00:41
So that's that's the right way, you know, to think about these really really complex technologies.
4:00:45
Nuclear reactors are like this as well.
4:00:48
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?
4:00:54
We sell energy, not not nuclear reactors.
4:00:56
That might mean energy to AI data centers. Absolutely.
4:00:58
It means hydrogen and it means eventually synthetic fuels, right?
4:01:03
If we can make a synthetic fuel cheaper than diesel, cheaper than gasoline, we can actually become, you know, the the energy company of the world, right?
4:01:10
Because the majority of the energy today is in a hydrocarbon format.
4:01:13
So that's that's kind of the core realization that we had when when starting dollar. Very cool. Well, good luck. Thanks for calling in. Yeah, huge day. Congratulations. Thanks, guys. The whole industry. Cheers. What a great show. whole world tour. Four hours.
4:01:28
Just I guess we just hit four hours.
4:01:31
Anything else we need to cover before we get out of here?
4:01:35
I think uh breaking news, John. What's that? It's the weekend. It's the weekend.
4:01:43
And as always, our board has been very explicit about this.
4:01:46
Leave us a five stars on Apple podcast. Listen this far. You're four hours in.
4:01:54
I'm guessing we earned that five stars. So, just do it.
4:01:57
Everybody have a great Memorial Day weekend.
4:01:59
We actually won't have a Monday show because we're moving into the new studio, but we'll be back in full force Tuesday in the new studio in the temple on Tuesday. We're excited. Cheers. Have a great weekend. Have a good one. Bye.