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[Music] >> Founder Triple glaze. [Music] Team deathmatch. Team deathmatch. >> Yes.
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Today is Wednesday, 20 September 24th, 2025.
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We are live from the TBPN Ultradome, the temple of technology, the fortress of finance, the capital of capital.
5:11
Uh the Wall Street Journal has a post because they wrote an article about Peter Teal's lecture circuit on the Antichrist.
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They write Peter Teal, the billionaire investor in data, AI, defense, and weapons development technologies wants everyone to think more about the end of the world.
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And it got me thinking more about capital allocation.
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Honestly, uh, this circuit, we've covered this a little bit.
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Teal has been on a lecture series that's now four parts up in San Francisco.
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Tyler, do you know why Peter is doing this? >> What do you mean?
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>> Do you know why he's doing this lecture circuit?
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>> You're supposed to say why questions are overdetermined. >> Oh, layup. That was a layup.
5:56
>> Always why questions are overdetermined. Tyler made this.
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Uh, anyway, never ask why.
6:01
Ask how to save time and money. Go to ramp. com.
6:04
Easy use corporate cards, bill payment, accounting, and a whole lot more all in one place.
6:07
Um, they are not live streaming this.
6:11
They should be live streaming it on reream.
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One live stream, 30 plus destinations, multiream, reach your audience, wherever they are.
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No, it is off the record.
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And if you go and you get a ticketaw post about it, you get >> Yeah.
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Somebody summarized the first couple and just immediately got a comment from Miss Stevens who said, "Uh, you're banned." >> Yeah.
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They were running the Blake Masters, uh, they were trying to run back the Blake Masters playbook.
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So, uh, if you're not familiar with the lore here, back in spring of 2012, >> he was basically kind of making a run at I want to be the Blake Masters of the Antichrist. >> Yeah.
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>> Yeah. which is like a wild wild thing to play out because uh the I mean so let's give a little history here back in >> his name in the history books next to the section on the antichrist >> exactly which is very different than what happened last time Peter gave a a set of lectures it was at Stanford uh and it became the backbone of the bestselling book 0ero to1 uh the talks
7:07
were focused on entrepreneurship but it could be seen as a history lesson or political treaties or referendum on American culture There was a lot that came into that lecture series and there's a lot of facts in that book, a lot of stories in that book that aren't strictly directly applicable to just building a company even though the the the the course was literally called how to start a startup CS183. Um and 0ero to1 kind of turned into the
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Um and 0ero to1 kind of turned into the playbook that founders fund ran for a long time and still runs and has produced a bunch of alpha the ideas of being founder friendly the monopoly thesis the definite optimist like these tealisms became real investment
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strategies uh for the following decade and are still holding true today uh it was a bit shocking to it was always shocking to me that like the be founder friendly don't fire founders like stuck around as durable alpha for as long as it did but VCs just love firing founders like it's just nothing. Yeah, I've never done it personally, but
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Yeah, I've never done it personally, but I imagine the thrill must be electric because uh even though >> somebody from their creation it must be because it clearly doesn't produce alpha because if you look at the companies that are founder le they tend to outperform.
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So you're sacrificing a lot of a lot of financial gain when you fire a founder.
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But the rush the rush must be incredible.
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It must be better than even returning billions of dollars to your LPs.
8:28
Um but uh um so this new lecture circuit is about the antichrist and this series doesn't fit neatly into the previous C Stanford course calendar.
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It's not listed as CS 184 antichrist.
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No, it's not a computer science course at Stanford.
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It's being put on by Michelle Stevens at Acts 17.
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Um and is much more focused on religion specifically in Christianity.
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Uh, so the Wall Street Journal characterized one of Teal's core thesis this way.
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Teal draws on a theory that the antichrist could be an individual or entity that is incredibly charismatic but talks repeatedly about the end of the world, thereby convincing society to give it the power it needs to regulate the existential risks from science and technology.
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Um, and there are lots of people that come to mind when you think about talking about dumerism.
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And Teal cites Greta Thunderberg.
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She said, "Our house is on fire.
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We must act like the house is on fire.
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Uh she said also we are in the beginning of a mass extinction.
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This is in September of 2020 uh 2019 and all you can talk about is money and fairy tales of eternal economic growth.
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She told this to I think uh this is reported by PBS at the UN climate action summit. She's been very focused.
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>> This is her uh her campaign to increase human suffering.
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>> It's been a mixed bag but uh Eleazar Udicowski said other doomer things. He has a new book out. He's on a book tour.
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He says, "If we go ahead on this, everyone will die."
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He's referring to AI, not climate change in this case, including children who did not choose this and do not do anything wrong.
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Uh Sam Alman has also said some stuff that's uh sort of apocalyptic.
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You know, he told the US Senate in his testimony in >> $200 trillion.
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If I can't if I can't automate enterprise workflows and >> if I can't get 500 trillion million billion >> zillion 99999 I need 999999999 billion. >> Yeah. Round numbers are out.
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You need to go to a VC and say for this round we're raising 9999999999 please. >> Yes. >> Yes.
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Um >> don't make me choose. >> Don't make me choose.
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Uh, >> don't make me choose between curing cancer and free education.
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>> Don't make me choose saving time and saving money.
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Just we can save both with ramp. com.
10:53
Anyway, uh, no, but he he did he did give, you know, a bit of a doomer take.
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He was talking about uh how this could go wrong.
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He said, "If this technology goes wrong, it can go quite wrong."
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Uh, Elon Musk also said something similar.
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He said, "With artificial intelligence, we are summoning the demon."
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And the original SpaceX thesis was >> Did he say that, by the way?
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>> He said that in uh October of 2014 at the MIT Centennial Symposium.
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>> And what did he mean by that?
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Because now he's got a >> summoning a demon.
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I think he thinks that uh if you shape the demon portal in the right shape, the demon comes through and it's kind of friendly.
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Maybe >> friendly demon >> kind of nice. I don't know.
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friendly demon that increases enterprise value through business automation and hopefully increased efficiency >> hopefully and and and vibe coding 3JS apps that that's the demon that I want.
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Um but uh even SpaceX you can view as a as a rebuttal to the apocalypse.
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What would be apocalyptic a humanity remaining on the earth alone?
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An asteroid comes hits the earth. We're all done.
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But if we become multilanetary, uh we are no longer a single point of failure.
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If there's humans on Mars and the moon and earth, if something bad happens to Earth, humanity continues.
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Um the stakes that that Elon framed SpaceX in were world consequential.
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>> By the way, if you go to XAI.
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com, >> it's this random company called UN AI. What unki?
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And they feature popular AI brands like Gro for Chat GPT. >> Okay.
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>> Deepseek and Xiaomi and Uni Tree. >> Weird.
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>> Seeming seemingly a Chinese company. >> Okay. Odd.
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>> That's using it to promote a range of products. Yeah. Anyways, very strange.
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So my question was there's a lot of focus on uh if you speak in millinarian terms, if you speak of apocalyptic consequences to not building your technology, you might be the antichrist. It might be bad.
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But at the same time, I'm just looking at history here and looking at these folks who have become popular and and thought leaders on apocalyptic scenarios, Elon, Sam, Udicowski, Greta.
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uh if you backed these folks as a basket, you would have done quite well.
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You're in SpaceX, you're in uh you're in OpenAI, you you've done quite well.
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And and I'm wondering where the line is for uh you know using uh speaking about apocalyptic consequences to the lack of technology to the lack of not solving a problem and then balancing that with uh delivering something that isn't authoritarian but is actually just a really really big ambitious project.
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So if you if you if you read into, you know, uh we're summoning the demon, we need to go to Mars because humanity could be wiped out. Earth is cooked, right?
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Um >> there's one world where it's like that is apocalyptic thinking.
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There's another which is just like this is a reframing on the classic like I want to save the world.
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I want to change the world.
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We want to make the world a better place.
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All those terms have kind of fallen out of fashion as as a lot of founders just kind of wound up, you know, building automating manual workflows, right?
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And so they they stopped saying we're going to change the world with a better database.
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But there's still something if you're a VC and you want to back a moonshot, you want to back something that's either going to be zero or trillion dollars that where I feel like you're >> Augustus is is a great example of this pitch because >> um everyday people experience rain all the time.
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They're not necessarily like droughts are not something super tangible, right?
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because you just you turn the faucet and the water runs regardless of if you're in a drought or not.
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Obviously, farmers feel this much more intensely.
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But he's come out and said, you know, we need to be able to control the weather.
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We need to be able to increase precipitation >> and you should fund me so that I can do this, right? >> Yeah. Yeah.
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There's something about these bold missions that rally employees, they rally investors, they rally media attention.
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You look at like what Augustus is doing is deeply controversial, but he's on podcasts that are so much bigger than what a normal what is he got? Series A.
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Like a series A founder typically is not on multiple million plus subscriber podcasts. >> Yeah. Doing a tour.
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We >> going and talking to people that are are actively disagree with what he's doing. >> Totally. Totally. Yeah.
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I mean, we talk to founders all all day long who come on and, oh, they raised at a billion dollar valuation or they raised a billion dollars.
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We had five series E companies on Tuesday.
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Uh, those folks are not getting calls from the biggest media platforms in the world on day one consistently on a regular basis.
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And I think it's because of the that they're going after more tractable problems.
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they're going after things that are less controversial, but also there's just something interesting about actually uh refocusing on tackling those really really big issues.
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And so, um there's something where I I'm I I feel like the fear of like targeting the Antichrist turns into like uh you know, Gerardian scapegoat.
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You got to find someone to blame everything on.
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I I'm worried about how all that shapes up.
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But uh I am optimistic about this idea of venture capitalists returning to the super high risk.
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It's either zero or trillion dollars.
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It either is a completely useless company that doesn't get anything done or they cure cancer or they build a flying car or they build the rocket that goes to space.
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Uh and even if Elon hasn't gotten us to Mars, we're not multilanetary yet.
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He's still able to ship Starlink. It's great business.
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And then also keep everyone still motivated on how cool would it be if if they actually got to Mars. That's amazing. Another 20 years.
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We need we need AI to benefit humanity.
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Very oriented around uh safety, right? This is a nonprofit.
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This is work that needs to be done that's >> not going to get funded through the capital markets and it turns into an internet software.
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>> And so and so I don't know what I don't know what your timeline is for SpaceX getting to Mars.
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It might be 20 years, might be 30 years.
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uh but at least it keeps them focused on you know chopping wood and working hard to actually advance the underlying technology that we get a lot of value on through just satellites and stuff.
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Uh, and I think that the same thing could be true for the AI companies where, yeah, maybe we don't get the the the AGI god ASI, you know, super soon, but there's just like a ton of value and you keep working at it because uh, it's delivering value in the short to medium term, but you're able to keep the sites really, really, really high.
17:39
Uh, and that drives just like uh, that's just what you need to actually marshall all the energy to go back something really huge.
17:46
Uh anyway, Tyler, have you been following the uh the the Antichrist lecture series vibes at all? What what's your take?
17:55
>> Uh I I read um I read the first like set of notes that came out by the person who I think got trouble >> banned notes.
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You got to them before they were taken down off the internet.
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>> Oh, they were taken down, >> I believe.
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So I I couldn't find them.
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>> I don't think people were really missing anything cuz most of that stuff was like >> in other podcasts.
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>> Yeah, most of it was in the um Hoover Institution podcast with Peter Robinson. >> Yeah.
18:15
Um, so I I mean the vibes are like most of the stuff I've seen online were just like the the protests outside of it which I thought were like pretty funny.
18:23
>> Yeah, >> I it does feel like this is definitely uh in the in the early stages of act like we like it's he's definitely like working these bits out and figuring out where how all the pieces fit together into some sort of narrative or conclusion.
18:38
Um, but it's interesting and uh not many other venture capitalists are talking about it.
18:43
So, at least it's different and fresh.
18:44
Anyway, uh, Privy Wallet infrastructure for every bank.
18:48
Privy makes it easy to build on crypto rails, securely spin up white label wallets, sign transactions, and integrate onchain infrastructure all through one simple API. >> There we go.
18:58
>> We got a little bit of a bare take from Jerry Newman over in Colossus.
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AI will not make you rich.
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I feel like AI is already making tons of people rich.
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I wonder uh I wonder what's going on.
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Let's read through some of this. So >> kick it off.
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>> Jerry writes in Colossus Mag, which you should subscribe to, of course, fortunes are made by entrepreneurs and investors when revolutionary technologies enable waves of innovative investable companies.
19:23
Think of the railroad, the Bessemer process.
19:25
I don't actually don't know what the Bessemer process is, >> Tyler.
19:29
What's the Bessemer process?
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>> Electric power, the internal combustion engine mass-producing steel produc.
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>> Were there lots of steel startups at the time? I suppose interesting.
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Each of which, like a stray spark in a fireworks factory, set off decades of follow-on innovation, permeated every part of society and catapulted a new set of inventions and investors into power, influence, and wealth.
19:53
Yet, some technological innovations, though society transformative, generate little in the way of new wealth.
20:00
Instead, they reinforce the status quo.
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15 years before the microprocessor, another revolutionary idea.
20:05
Shipping containerization arrived at a less propitious time when technological advancement was a red queen's race and inventors and investors were left no better off for non-stop running. Interesting.
20:19
I didn't know that about the containerization story.
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Uh anyone who invests in the new new thing must answer two questions.
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First, how much value will this innovation create?
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And second, who will capture it?
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Information and communication technology was a revolution whose value was captured by startups and led to thousands of newly rich founders, employees and also called high technology. Yes. High-tech. >> Yes.
20:44
I am I am very excited to see where he takes this because I feel like there are already what thousands of new millionaires in the AI boom just from secondary sales.
20:54
>> The the prices of starter homes in San Francisco. >> Yeah. Like it's happening.
20:57
Didn't OpenAI just do a10 billion dollar tender offer or something like there's liquidity flowing people.
21:04
>> Not to mention how many individual indie founders are making a lot of money building various AI apps and experienc also just people that went long Nvidia or have been buying you know calls on Nvidia at various times or or Leopold and Brener like there's a bunch of people that have figured out different ways to make money. What do you think?
21:22
I mean, yeah, there's that stat of the like this was like maybe 3 years old or something, but about the Nvidia employees and it was like 75% of them are worth over a million dollars. >> That's right.
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>> I'm sure that's like probably 90% now. >> Yeah.
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And so I don't know, maybe he has to argue for like collapse of everything.
21:37
We'll see where this goes.
21:39
Um, >> is generative AI more like the former containerization or the latter uh IT revolution?
21:45
Will it be the basis of many future industrial fortunes or a net loser for the investment community as a whole with few with a few zero- sum winners here and there?
21:53
There are ways to make money investing in the fruits of AI, but they will depend on assuming the latter that it is once again a less propitious time for investors and uh and inventors.
22:03
That AI model builders and application companies will eventually compete each other into an oligopoly. I believe that's true.
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And uh and that the gains from AI will not acrue to its builders but to customers.
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A lot of the money pouring into AI is therefore being invested in the wrong places.
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And aside from a couple lucky early investors, those who make money will be the ones with the foresight to get out early.
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>> What do you think, Jordy?
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>> I mean I mean I mean we got to we got to I don't want to I don't want to just start just dunking.
22:35
>> Keep reading the microprocessor. >> Yeah.
22:37
So the micro uh but but the main thing is in venture it's really hard to get out early if you're investing with real size, right?
22:43
If you're writing a $200 million check, it's not like at the next round you're like, "Oh, nice. I got a 3x markup.
22:49
I'm going to >> I'm going to sell you're not."
22:54
Uh, and this is this is something you see on the timeline.
22:58
People uh people usually anon accounts saying like, "Oh, these multi-stage funds are just dumping on you and all this stuff."
23:06
this stuff." like like yes at times funds can exit some of their position smaller funds can exit you know entirely but by and large if you led an early round you're not able to just fully exit >> and you might even be locked up post IPO
23:22
there's a bunch of ways it would be very funny if uh you know how everyone's like let SPF out of jail he he got he got a stake in anthropic and then >> there was something else somebody was sharing this morning I forgot about this but he bought almost 7% of Robin Hood bottom. >> And there's like two other companies
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>> And there's like two other companies that he got that he like nailed.
23:39
He was like a fantastic trader, but did you see what Elon posted about Enthropic?
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He said winning was never in the set of possible options or possible outcomes.
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So he's like, >> did you say that?
23:52
>> He said that on X yesterday, I believe.
23:54
So Elon is gig bear on uh Elon is a gigab bear on anthropic saying that anthropics is zero.
24:02
And if if Elon's right then SPF looks bad again because he looked bad because he lost all the customer money then he looked great about about >> No, no, no. Completely unrelated. Completely unrelated.
24:15
Elon is just trash talkinging the other laps because he trash talks a bunch of the laps, right?
24:20
But he was he was saying that, you know, oh, Anthropic's not going to lose.
24:21
It's going to he's not going to win.
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It's going to be a zero or whatever.
24:24
He wasn't exactly saying it was going to be a zero, but he was saying he was saying uh you know winning was never in the in the set of possible outcomes.
24:32
And so it'd be very it'd be very funny if we go if we round trip >> everyone that prayed on my downfall pray harder. >> Yeah. Yeah. Yeah.
24:41
I I I I think it's kind of a silly silly uh >> I'll continue.
24:44
The microprocessor was revolutionary, but the people who invented it at Intel in 1971 did not see it that way.
24:50
They just wanted to avoid designing desktop calculator chipsets from scratch every time.
24:55
But outsiders realized they could use the microprocessor to build their own personal computers, and enthusiasts did.
25:03
Thousands of tinkerers found configurations and uses that Intel never dreamed of.
25:07
This distributed and permissionless invention kicked off a great surge of development, as the economist Carla Perez called it, triggered by technology, but driven by economic and societal forces.
25:17
There was no real demand for personal computers in the early 1970s.
25:21
They were expensive toys, but the experimenters laid the technical groundwork and built a community.
25:27
Then around 1975, a step change in the cost of microprocessors made the personal computer market viable.
25:34
The Intel 8080 had an initial list price of $360, which is 2,300 in today's dollars.
25:40
Uh MITS could barely turn a profit on its altar at a bulk price of $75 each, which is $49.
25:49
>> Donald Boat would have gotten it done in 1975.
25:52
>> He would have gotten it >> done.
25:53
He would have been putting >> Gordon Moore, send me an Intel 880. You're on notice.
26:00
>> He'd just be putting ads in the newspaper.
26:01
>> He'd be writing letters to Gordon >> computers >> and Bob Noise. Send me an Intel 8080.
26:04
Uh but when MOS technology started selling at 66502 for $25, Steve Waznjak could afford to build a prototype Apple.
26:16
6502 and the similarly priced Xylo Z80 forced Intel's prices down.
26:21
The naent PC community started spawning entrepreneurs and a score of companies appeared each with a slightly different product.
26:27
You couldn't have known in the mid 1970s that the PC would revolutionize everything.
26:31
While Steve Jobs was telling investors that every household would someday have a personal computer, a wild underestimate, as it turned out, the others questioned the need for personal computers at all.
26:43
As late as 1979, Apple's ads didn't tell you what a personal computer could do.
26:47
It asked what you would do with it.
26:47
The established computer manufacturers uh had no interest in a product their customers weren't asking for.
26:53
Nobody needed a computer, and so PCs weren't bought. They were sold.
26:57
Flashy startups like Apple and Sinclair used hype to get noticed while companies with footholds in consumer electronics like Atari, Commodore, and Tandy Radio Shack use strong retail connections to put their P.
27:09
>> Look at this controversial ad that they ran with a naked ma man Adam holding a an Apple computer.
27:15
The original clearly maybe Steve Jobs was was on to something with the viral marketing being controversial.
27:23
>> Yeah, this is an insane.
27:23
We're looking for the most original use of an Apple since Adam.
27:27
What What in the name of Adam?
27:31
What in the name of Adam do people do with Apple computers? You tell us.
27:33
In a thousand words or less.
27:35
If your story is original and intriguing enough, you could win a oneweek all expense paid trip to for two to Hawaii. >> Giveaways. >> Give. This is wild. What insane Apple lore.
27:48
Steve Jobs is really on one.
27:48
This this the logo too with it with the the Apple >> stripes. >> Stripes. >> Oh, so good.
27:56
>> So, the market grew slowly at first, accelerating only as experiments led to practical applications like the spreadsheet.
28:01
Let's give it up for the spreadsheet.
28:04
>> Best inventions of all time. >> Hit that horn.
28:07
Um, as use grew, observation of use caused a reduction in uncertainty leading to more adoption in a self-reinforcing cycle.
28:12
This kind of gathering momentum takes time in every technological wave.
28:16
It took almost 30 years for electricity to reach half of American households, for example.
28:20
And it took about the same amount of time for personal computers.
28:23
When a technological revolution changes everything, it takes a huge amount of innovation, investment, storytelling, time, and plain old work.
28:31
It also sucks up all the money and talent available, like Coon's Paradigms, and science.
28:35
Any technology not part of the wave's technoeconomic paradigm, will seem like a sideshow.
28:43
>> Well, let me tell you about cognition.
28:44
They're the makers of Devon.
28:44
Devon is the AI software engineer.
28:46
Crush your backlog with personal AI engineering team at your fingertips in your Slack. Uh let's continue.
28:53
The nent growth of PCs attracted investors.
28:55
Venture capitalists who started making risky bets on new companies.
28:58
This development incentivized more inventors, entrepreneurs, and researchers.
29:02
You don't hear enough about inventors anymore.
29:06
Everyone wants to be a founder.
29:08
No one wants to be an inventor. I want to show up.
29:10
I want to meet some folks who just are like, "Yeah, I'm I'm just working on."
29:14
>> What about Riley Walls who's joining the show later today?
29:16
He's kind of inventor coded.
29:19
>> I think he's an inventor. You called him a rascal.
29:21
Something >> internet rascal.
29:23
>> Internet Rascal, which is I think fantastic.
29:24
Uh but I think of him as an inventor.
29:28
>> Uh which in turn uh and all of this drew more speculative capital.
29:31
Companies like IBM, the computing behemoth before the PC, saw poor relative performance.
29:34
They didn't believe the PC could survive long enough to become capable in their market and didn't care about new small markets that wanted a cheaper solution.
29:43
Retroactively, we gave the PC we give the P PC pioneers the power of profits.
29:49
Well, that's a lot of aliteration rather than visionaries.
29:51
But at the time, nobody outside a small group of early adopters paid any attention.
29:56
Establishment media like the New York Times didn't take the PC seriously until after IBM's was produced in August of 1981.
30:03
In the in the entire year of 1976 when Apple computer was founded, the NYT mentioned PCs only four times. >> Crazy.
30:13
>> Apparently, only the crazy ones, the misfits, the rebels, and the troublemakers were paying attention.
30:18
This is uh yeah, total mentions of personal computers in the New York Times overtime and uh exponential growth from 1979 to 1984.
30:29
>> Crazy that it actually peaked in 94 started. Sorry.
30:33
Uh, >> it peaks in >> 84, sorry.
30:35
And then was dropping throughout the 80s.
30:38
>> Well, it's old news, you know. It's over. >> Yeah. Everyone has a PC.
30:40
I mean, how many articles are there about like social media today, this year, or like the smartphones?
30:45
Like, there just aren't as many as there were during the boom, right?
30:48
That's the nature of these.
30:50
>> Still the full New York Times. >> Yeah.
30:52
But I mean, there's just so many times when you can just like, you know, it just melts into the background of the story. But it's a good point.
30:57
Uh, it's the element of surprise that should strike us most forcefully when we compare the early days of the computer revolution to today.
31:05
No one took note of personal computers in the 1970s.
31:08
In 2025, AI is all we seem to talk about.
31:13
Big companies hate surprises.
31:13
You want to continue here?
31:15
Big companies hate surprises.
31:17
That's why uncertainty makes a perfect moat for startups.
31:19
Apple would never have survived IBM entering the market in 1979 and only lived to compete another day after raising a h 100red million in its 1980 IPO.
31:27
It was the only remaining competitor after the IBM induced uh winnowing.
31:32
Um there's IBM and Apple.
31:36
They're the only two survivors.
31:39
All these other companies, the Alter, the AmIGGA, the Atari ST uh all fell off, but the Mac and the IP IBM PC ripped onward. business machines. >> You'd love to see it.
31:50
>> Uh as the tech took hold and started to show promise, innovations in software, memory, and peripherals like floppy disc drives and modems joined it.
31:56
They reinforced one another with with each advance, putting pressure on the technologies adjacent to it.
32:02
When any part of the system held back the other parts, investors rushed to fund that sector.
32:07
As increases in PC memory allowed more complicated software, there became a need for more external storage which caused VC uh Dave uh Mark Market uh to invest in disc drive manufacturer Seagate in 1980.
32:21
Seagate gave a 40x return when it went public in 1981.
32:27
Other investors noticed and some 270 million was plowed into the industry in the following three years.
32:31
Seagate's been ripping, right?
32:33
all the hard drive makers because all the all the AI companies need to store a ton of training data, RL data.
32:39
They're generating a huge amount of data, images, videos, all sorts of stuff.
32:44
And all of that needs more storage >> up 109% in the past.
32:50
>> I remember I I think we read an article about uh the hard drive boom like a year ago and it was we're still early.
32:58
>> I know that that's actually crazy.
32:58
I remember it was like first like 10 episodes. >> Yeah.
33:02
And we were like, "Oh, this is kind of a boring story."
33:03
But it's kind of interesting and it seems important.
33:05
So we read about Seagate.
33:07
>> Let's check in with Western Digital 118.
33:09
>> Another 100 another 100 bagger little easy double. >> Yeah.
33:13
Money also poured into the underlying infrastructure, fiber optic networks, chipm etc.
33:17
So that the capacity was never a bottleneck.
33:20
Companies which use a new technological system to outperform incumbents began to take market share and even uh competitors realized they needed to adopt the new thing or die.
33:28
The the hype became a froth which became an investment bubble.
33:32
Let's give it up for bubbles. The.
33:34
com frenzy of the late 1990s.
33:36
The ICT wave was therefore similar to the previous ones like the investment mania of the 1830s and the roaring 20s which followed the infrastructure buildout of the of canals and railways respectively in which the human response to each stage predictably generated the next.
33:50
When the dotcom bubble bubble popped, society found it disapproved of the excesses in the sector and governments found they had the popular support to resert authority over the tech companies and their investors.
34:03
This put a break on the madness.
34:03
Instead of the reckless innovation of the bubble, companies started to expand into proven markets and financiers moved from speculating to investing.
34:11
Entrepreneurs began to focus on finding applications rather than on innovating the underlying technologies.
34:17
Technological improvements continued, but change became more evolutionary than revolutionary. >> Look at this chart.
34:23
Technological waves over time, the industrial revolution, the canal mania.
34:27
I I wasn't even familiar with this uh Arkrite Mill opens in 1771.
34:33
The great >> I would love to uh I would love to >> then >> watch a documentary or or even a drama canal mania. >> Yeah.
34:42
This has the the >> underrated mania.
34:44
People always talk about tulips. >> Tulips. Yeah.
34:47
Tulips doesn't even count because it's not a real technology.
34:49
So the actual technological waves that are highlighted here, the industrial revolution, steam and railways, steel, electricity, and heavy engineering.
34:56
Then oil, the automobile and mass production from 1908 to 1974 and then 1971 onward is information and telecommunication.
35:06
Um, and pretty pretty remarkable results from this 27% rise in real GDP through the 2010 to 2019 era. It's pretty good.
35:16
Uh, in contrast, society did not need a bubble to pop to start excoriating AI given the backlash to tech that has been going on for a decade.
35:22
This seems normal to us, but the AI backlash differs from the general high regard earlier in the cycle enjoyed by the likes of Bill Gates, Steve Jobs, Jeff Bezos, and the others who built big tech businesses.
35:33
The world hates change and only gave tech a pass in the 80s9s because it all seemed reversible.
35:38
It could be made to go away if it turned out badly.
35:40
This gave the early computer innovators some leeway to experiment.
35:44
Uh now that everyone knows computers are here to stay, AI is not allowed the same wait and see attitude.
35:50
It is seen as part of the information technology revolution.
35:55
Perez the economist breaks each technological wave into four predictable phases.
35:58
Eruption, frenzy, synergy, and maturity.
36:01
This is a new Gartner hype cycle.
36:04
We need to know where are we on the curve. >> The Perez tech wave.
36:07
I >> think we're right around frenzy.
36:09
We're definitely past eruption.
36:11
Maybe going into synergy and maturity next.
36:13
Uh the middle two, frenzy and synergy are the easy ones for investors.
36:18
Frenzy is when everyone piles in and investors are rewarded for taking big risks on unproven ideas culminating in the bubble.
36:24
When paper profits disappear, when rationality returns, the synergy phase begins as companies make their products usable and productive.
36:32
>> Everybody's scared of a crash.
36:32
They're not eager for synergy. >> Yeah.
36:37
So, investing in the maturity phase is even more difficult.
36:39
In eruption, it's hard to see what will happen.
36:43
Uh, in maturity, nothing much happens at all. Nothing ever happens.
36:46
Uh the uncertainty about what will work and how customers and society will react is almost gone. Things are predictable.
36:55
Everyone acts predictably.
36:55
The lack of dynamism allows successful synergy companies to remain entrenched.
36:59
See the nifty50 and fang, but growth becomes harder.
37:03
They all start to enter each other's markets, conglomerate, raise prices, cut costs.
37:07
The era of the it feels like Microsoft's in that in that bucket certainly already.
37:12
Uh companies frame this as a drive to win, but it's really a fear of losing.
37:17
>> Um should we read about the shipping container wave? Yes.
37:21
>> Shipping containerization was a late wave innovation that changed the world, kicked off our modern era of globalization, resulted in profound changes to society and the economy, and contributed to rapid growth in well-being.
37:31
But there were perhaps only one or two people who made real money investing in it.
37:36
That is insane to hear if that's true. >> Yeah.
37:40
And key words here are investing specifically in that technology versus benefiting from it >> broadly. Yeah.
37:47
Because if you were >> in any type of business that required shipping and and receiving goods from all over the world, you benefited directly from the technological change even if you weren't like investing in companies that were functionally uh creating it.
38:07
>> Yeah, I would certainly agree.
38:07
So they they they mark the containerization wave starting the year is 1956.
38:16
It was late in the previous wave but that year the company soon to be known as Sealand revolutionized freight shipping with the launch of the first container ship the ideal X or the Ideal 10.
38:26
Sealand's founder Malcolm Mlean uh had an epiphany that the job to be done by truckers, railroads, and shipping lines was to move goods from shipper to destination, not to drive trucks, fill box cars, or laid boats.
38:37
Sealand allowed freight to transfer seamlessly from one mode to another, saving time, making shipping more predictable and cutting costs.
38:45
Both the cost of loading, unloading, and reloading, and the cost.
38:49
But prior to this, you would just have like a wooden crate that would just get thrown on a ship and then you >> So you have to stack it, unstack it, figure out how you have to do a puzzle every single time you want to load Tetris. Yeah.
39:00
Uh and now it's just stacking blocks. Jenga instead Yeah. >> of Tetris.
39:04
Much easier to play to play Jenga supposedly.
39:08
>> Uh the benefits of containerization, if it could be made to happen, were obvious.
39:12
Everyone could see the efficiencies and customers don't care how something gets to when they can where they can buy it as long as it does.
39:19
But long shoreman would lose work.
39:21
Politicians would lose the votes of those who lost work.
39:22
Port authorities would lose the support of their politicians.
39:25
Federal regulators would be blamed for adverse consequences.
39:28
Railroads might lose freight to shipping lines.
39:30
Shipping lines might lose freight to new shipping lines.
39:31
And it would all cost a mint.
39:33
Most thought man would never be able to make it work.
39:35
But he squeezed through the cracks of the opposition he faced.
39:38
He bought and retrofitted war surplus ships, lowering costs.
39:42
He went after the coastal shipping trade, a dying business in the age of new interstates to avoid competition.
39:48
He set up shop in Newark, New Jersey rather than the shipping hub of Hell's Kitchen in Manhattan, uh to get buyin from the Port Authority and avoid Manhattan congestion.
39:55
And he made a deal with the New York Long Shoreman's union, which was only possible because he was a small player whom they figured was not a threat. Mhm.
40:04
>> Um what's interesting is that yeah I I I think it's like the direct investment might be very concentrated but you when I think about the rise of the 60s the 70s the 80s like globalization I'm thinking of Nike and I'm thinking of
40:18
companies that were built on the back of globalization even the iPhone Apple like the these companies exist in part and are beneficiaries of containerization and so it's not a direct investment in the the fundamental technology, but it is enabled by it. >> Yeah,
40:35
>> Yeah, >> I don't think so.
40:36
>> Yeah, we'll we'll have to get through the article, but it's it's already feels like it's somewhat >> somewhat clickbait.
40:43
Not clickbait, but uh to say like no one's going to make money on on AI or or you're not going to make money on AI. Um yes.
40:52
Um let's skip to his conclusion about uh generative AI.
41:01
He says, "Let's grant that generative AI is revolutionary, but also that as is becoming increasingly clear, this particular new tech is now already in an evolutionary stage.
41:10
It's towards the end of its cycle, uh, it will create a lot of value for the economy and investors hope to capture some of it."
41:18
>> This is the key point.
41:18
I totally >> and and agree and um >> when, who, and how depends on whether AI is the end of the ICT wave or the beginning of a new one, right? Yeah. Yeah. Is it SAS or is it God?
41:32
>> Is it the final SAS product and then we're stuck or is it something entirely new and we're just going to start >> compounding?
41:39
Is it is it consumer software?
41:42
Is it enterprise software?
41:42
Is it something entirely new? Right. >> I don't know.
41:47
Uh if AI had started a new wave, there would have been an extended period of uncertainty and experimentation.
41:55
I feel like that's the last decade of open AI.
41:57
I I I feel like 2015 to 2025 was that period of >> uncertainty. Yeah.
42:02
You have to understand is it is it um people in 2015 that were trying to make chat bots, right?
42:08
With no hype totally really no user not a lot of users, right?
42:12
>> Uh or you just counting like when OpenAI was like, "Okay, we can actually be a for-profit company now and and we can productize this."
42:19
But even then there was like a pretty large gap between them deciding like hey let's let's actually raise traditional capital for this before they could get out the API before they could get out >> chat >> GBT. Totally. Yeah.
42:32
>> GBT. Totally. Yeah. and and also like there was this in in AI the period of uncertainty and experimentation that was the the Tik Tok algorithm the Netflix recommendation algorithm uh Facebook's core AI investments they have bought billions of dollars of GPUs not for
42:49
generative AI not for LLMs but just to make better ad recommendations better content recommendations and so there's I don't know there's a lot there we'll have to continue to dig in but let's keep reading uh he said when thousands Thousands of tinkerers use the tech to solve problems in entirely new ways. Its Its uses proliferate.
43:07
But because they are using models owned by the big AI companies, their ability to fully experiment is limited to what's in allowed by the incumbents who have no desire to permit an extended challenge to the status quo.
43:18
Uh this doesn't mean AI can't start the next technological revolution.
43:22
It might if experimentation becomes cheap, distributed, and permissionless.
43:26
like Waznjak cobbling together computers in his garage, Ford building his first internal combustion engine in his kitchen, and Trevknik building his high-pressure steam engine as soon as James Watt's patents expired.
43:39
When any would-be innovator can build and train an LLM on their laptop and put it to use in any way their imagination dictates, it might be the seat of the next big set of changes, something revolutionary rather than evolutionary.
43:51
But until and unless that happens, there can be no eruption.
43:53
Tyler, like, don't you think it's possible to build and train an LLM on your laptop and use it in any way your imagination dictates? >> Uh, yeah.
44:04
I mean, I I mean, I don't know about training a whole new LM, but like people are getting a lot of value out of open source ones that they locally >> llama deeply obvious. Yeah. >> Yeah.
44:14
It it doesn't I mean I I somewhat agree that we haven't seen that many totally new crazy like unprecedented uses of LLMs where it feels like it's an entirely new category.
44:26
Like it's hard to point at like the Uber for AI where it's like this company would never have existed.
44:34
It feels like a lot of the companies are kind of evolutionary like you know we have we we have site builders and then we have vibe coding platforms that build sites on top of them. Figma. com build faster.
44:46
Figma helps design and development teams build great products together get started for free.
44:50
Use Figma make if you want to develop a website. >> Yeah.
44:56
A lot of times companies come on TBPN to talk about what they're building.
45:01
They're building an AI application. >> Yeah.
45:04
There is a company started 10 years ago basically doing the exact same thing. >> Yep.
45:10
>> They just didn't position it in the same way.
45:12
They weren't using >> prompts and they weren't weren't using reasoning and and things like that.
45:19
>> Uh but but still it it looks and it looks >> it looks like it's solving the same SAS problem definition.
45:24
problem definition. It's like the problem was like organizing information for lawyers or answering the phone and we had a phone tree that was just deterministic like robotic uh press too for >> you know customer support press
45:39
>> and often times they can solve a problem >> it's like product can be twice as good which is enough to to to kind of eat into existing market share maybe create new markets right I think uh the market for people that can create software has obviously exploded, right? >> Uh which is why you see vibe coding, you
45:57
>> Uh which is why you see vibe coding, you know, uh revenues just exploding with billions of dollars collectively, >> but it does seem like the video games are getting more realistic.
46:06
Video games are getting more realistic.
46:09
The software is getting better.
46:11
The spreadsheets have more useful tools.
46:13
Like there's just a little extra helper everywhere. It's a lot of co-pilots.
46:17
It's not a lot of like entirely new >> and then you see chat GBT and it's the usage looks a lot like the way that people use Google search.
46:25
Granted, it's better in many ways >> but the the core value that's being delivered is quite similar.
46:34
>> He actually talks about domain specific models.
46:36
So first he says economists are predicting that AI will increase global GDP somewhere between 1 to more than 7% over the next decade which is 1 to 7 trillion of new value created.
46:45
The big question is where that money will stick as it flows through the value chain.
46:51
Most AI market overviews have a score or more categories, breaking each of them into customers and industry served.
46:56
But these will change dramatically over the next few years.
46:59
You could instead just follow the money to simplify the taxonomy of companies.
47:02
There are data infrastructure companies.
47:04
There are model companies, user application companies, AI customers, and consumers.
47:09
Um, but what the history of containerization suggests, if you aren't already an investor in a model company, you shouldn't bother.
47:15
Sam Alman and a few other early movers may make a fortune as McClean and Lewig did.
47:18
But the huge cost of building and running a model coupled with the intense competition means there will in the end be only a few companies each funded and owned by the largest tech companies.
47:29
If you're already an investor, congratulations.
47:31
There will be consolidation.
47:32
So you might get an exit.
47:34
Domain specific models like cursor and her Harvey will be part of the consolidation.
47:38
These are probably the most valuable models, but fine-tuning is relatively cheap and there are big economies of scope.
47:45
On the other hand, just as Google had to buy invite media in 2010 to figure out how to sell ad sell to ad agencies, domain specific model companies have that have earned the trust of their customers will be prime acquisition targets.
47:58
That sounds like another group of people that would be making money.
48:01
I like when you say like only open AI investors will make money.
48:06
It's like, well, there are like 7,000, you know, people on that cap table in one way or another.
48:12
Like all the investors, all the LPs and the funds that are investors, all the employees, all the people that got in through SVVS, like it's not just two people.
48:18
I feel like it's a lot of people that are that are in the big winners.
48:21
Like, even if there's just a few power law winners, uh, there's there's other, you know, another way to look into this is like if you're investing in a series A at three at a $300 million valuation, >> Yeah.
48:36
assuming just crazy explosive growth.
48:36
Y it's very possible the company even if it does well would someday sell for a few hundred million dollars and you wouldn't have actually made any money even though you got an exit. >> Yeah.
48:47
Here's here's a good uh like counter point to uh some of the companies that are potentially in a more precarious situation.
48:54
So he says while it's too late to invest in the model companies the profusion of those using the models to solve specific problems is ongoing.
49:02
Perplexity, Inflection, AI, Writer, a bridge and a hundred others.
49:06
But if any of these become very valuable, the model companies will take their earnings either through discriminatory pricing or vertical integration, launch their own competitors.
49:14
Success, in other in other words, will mean defeat, always a bad thesis.
49:18
At some point, model companies and app companies will converge.
49:20
There will be simply AI companies and only a few of them.
49:25
There will be some winners as always, but investments in the app layer as a whole will lose money.
49:28
Uh the same caveat applies however if an app company can build a customer base or an amazing team it might be acquired but these companies aren't really technology companies at all.
49:39
They're building a market on spec and have to be priced as such.
49:42
A further caveat is that there will be investors who make a killing arbitrageing FOMO panicked acquirers willing to massively overpay.
49:48
But this isn't really investing he says.
49:50
And so it again, it's another group of people that will get rich, but it's maybe not a durable source of alpha, which is an interesting thought. Um, uh, where else? Um, let's keep going.
50:06
This is a very long article.
50:06
You should go read the full thing.
50:07
So, uh, let's, let's close this out by reading his conclusion.
50:11
And of course, if you want to read the full piece, you can head over to Colossus Mag.
50:14
There is nothing better than the beginning of a new wave when the opportunities to envision, invent, and build worldchanging companies leads to money, fame, and glory.
50:24
But there is nothing more dangerous for investors and entrepreneurs than wishful thinking.
50:27
The lesson learned from investing in tech over the last 50 years are not the right ones to apply now.
50:33
The way to invest in AI is to think through the implications of knowledge workers becoming more efficient.
50:39
To imagine what markets this efficiency unlocks, and to invest in those.
50:43
For decades, the way to make money was to bet on what the new thing was.
50:47
Now you have to bet on the opportunities it opens up.
50:50
So Jerry Newman, he's a retire venture investor.
50:55
>> Totally totally agree with this conclusion, right?
50:59
right? Like I think if you come in with a with a $200 million venture fund right now and are just investing at at crazy multiples pre-revenue investing in new foundation model labs uh you're going to have a really tough time but that doesn't mean and and I don't know I think I think saying like the app layer as a whole will lose money at least when
51:23
you look at private markets right the whole point is that a lot of the companies can go go to zero and like a handful of them will create enormous value and that's okay right so um not that bearish but uh I do think it's it's not a you know at at this stage in the market spraying and praying is going to lead to some bad outcomes >> really understanding the opportunities
51:49
really understanding that hey maybe this is um a lot of the winners here are going to look more like traditional software yeah and that's okay but it just means you have to Um, you know, I think the the company we had on yesterday, Filevine, a good example of this, started as enterprise software for law firms, >> already has a ton of clients >> now in, you know, they have 100,000
52:10
lawyers actively using the product every day in a really good position to vend in a variety of different models and >> they will, depending on how they execute, prove to be a big challenge for new AI native companies that will have to decide, do we want to be sort of a ancillary product or do we want to own the workflows? And if we want to own the
52:31
And if we want to own the workflows, we have to rebuild all these different products that help a firm run. >> Yep.
52:37
>> And um and and do that with maybe a 10-year uh 10 years behind other players in the category. >> Yeah.
52:44
I mean, venture's always been the game of uh pick the winner in the category, but it feels like it's more important than ever to actually define the category.
52:52
Um because and and understand is this particular category going to have one winner or three winners or two winners?
52:59
Is it going to wind up being a duopoly or a oligopoly?
53:04
Um >> I'm excited to talk to Taylor about this.
53:07
He's building, you know, he's the 800 800 pound gorilla in uh AI for customer engagement experience, right?
53:17
But it's a category that has act an active capital war going on.
53:20
You have >> uh heavily funded new players like Sierra and Decagon.
53:25
You have uh the intercoms of the world that spin.
53:28
ai, the number one AI agent for customer service.
53:32
We're going to ask Brad Taylor about his performance benchmarks, his competitive bake offs.
53:36
this ranking on G2 um because we we are obviously supporters of Finn but uh interested in following the uh the the the fight and I'm I am very interested in how igopolistic will that particular market be.
53:51
Uh there are certain markets that have just kind of run away.
53:53
It it it it certainly feels like um just in terms of knowledge retrieval, we could be looking at an monopoly with OpenAI and Ship or duopoly with Gemini, but uh it doesn't seem like there's going to be 10 search engines and 10 default chat apps that people are going to.
54:10
It's certainly not >> or 10 deep research APIs. >> Exactly. Yeah.
54:15
It feels like there's going to be one or two that kind of compound and people get comfortable with and they stick with. >> Yeah.
54:20
Uh um well in other news uh EMTT says I'm excited to share Rura Water is the official partner of Hubberman Lab for water.
54:30
Uh Rura is of course company I co-founded uh a while ago.
54:34
Um and uh worked on this partnership with the Hubman Lab team uh Rob and Andrew for >> a very very long time at this point.
54:43
We started talking about it probably couple well started talking about it maybe a couple years ago.
54:49
Actually got them product over about a year ago. >> They used it a bunch.
54:54
They tested it a bunch uh and finally launched this partnership earlier this week.
54:58
So >> uh absolutely thrilled to uh get this across the line and uh >> yeah big vote of vote of confidence from the the Hubman team >> and I love it.
55:09
And in other uh Huberman world news, his uh his network Siccom Media is working on a new show with none other than David Senra.
55:20
>> It's David Senra by David Senra. >> Yeah.
55:23
The show is called David Senra.
55:25
And interesting >> hosted by David Senra. >> Yeah.
55:27
They picked David Senra as the host of the David Senra show. Yeah.
55:30
>> And so uh we will watch the launch video that he put out on X yesterday.
55:36
Nine years ago I launched Founders.
55:39
Today I'm launching a new podcast called David Senra.
55:42
>> 9 years ago I launched the Founders Podcast.
55:44
On Founders I tell the stories of history's greatest entrepreneurs and extreme winners.
55:47
This week I'm launching a new podcast called David Senra.
55:49
On this show I sit down for conversations with the best living founders in the world. >> I'm ready. >> How many?
55:56
You got three came >> people like Daniel E, Michael Dell, Brad Jacobs, Todd Graves, Michael Oitz, and many others.
56:03
My goal with everything I do is to obsessively study the greats and find timeless ideas that you can use in your work.
56:11
>> We have to change or we're going to go out of business.
56:14
>> And now you can learn directly from these legendary founders.
56:18
>> You know what I see the most common core of all the people that are successful for me is they're never satisfied.
56:24
>> You said something interesting. I like the pressure. I do fry it.
56:26
Founders will still come out every week and this new show will now have episodes dropping every other Sunday on all platforms like Spotify, Apple Podcast, YouTube X, and everywhere else that you find your podcast.
56:40
>> There are parts of me that still live in the valley.
56:43
>> When did you know you were good?
56:43
I don't know that I'm good.
56:44
I know I'm different and I'm out there for this chicken finger dream.
56:49
>> Failure is not an option.
56:49
Nothing was going to stop me from doing it. >> It's binary.
56:53
>> We need a We need a wall that we can set up here and run through or death. It's great.
57:00
>> Uh Dan Dan in the chat says, "The market is not ripping.
57:03
What are the white suits for today?
57:05
Bitcoin >> is up one and a half%. It's a bright spot.
57:12
>> Uh it's a it's a bull market in >> podcast. Lack of volatility.
57:15
If you were short volatility, you've done very well today, right?
57:19
Because it's not a volatile market.
57:21
There's always there's always a bull market.
57:23
>> I mean, it's it's a little rough out there.
57:24
It's just a It's just a fun day to put on a white suit.
57:26
We just feel like we were feeling some optimism. We were, you know, fun.
57:31
>> We just had some good energy in the studio this morning.
57:33
We wanted to uh we thought maybe if we put on the white suits, the market would >> Yeah, we'd be able to materialize a bull market. Let's make it happen.
57:42
>> We're trying to send it.
57:43
>> Anyway, before our next guest hops on, let me tell you about Vanta.
57:45
Automate compliance, manage risk, improve trust continuously.
57:48
Vanta's trust management platform takes the manual work out of your security compliance process and replaces it with continuous automation.
57:54
whether you're pursuing your first framework or managing a complex program.
57:58
>> Uh did you see this post from Sheil? He said interesting.
58:00
We might see an New York Stock Exchange IPO where the underlying asset is a bunch of paintings.
58:07
>> Billionaire Thomas Kaplan is exploring taking his Leiden collection uh >> 17 raere etc. >> worth 1.
58:15
5 to three billion public.
58:15
Uh >> this is the next generation of the digital asset treasury.
58:21
the DATs, you have the physical asset treasury, the PATS, uh, and these will be you'll be able to invest in art.
58:28
There's been a couple companies that allowed you to invest in art.
58:32
There was an art platform for a while that was doing that. >> Yeah.
58:36
I mean, I I in general taking art highly.
58:40
I mean, uh, art is liquid, but not at at sort of like market prices, right?
58:46
So, if you want to sell art quickly, you have to sell it at a at a massive discount, right?
58:49
You need to be super patient.
58:51
If you have a big collection and you're holding it, especially if you have the a bunch of works from a single artist, if you bring 10 pieces online, right, at the same time, you flood the market with supply, prices will come down.
59:04
So, it's a very weird thing, but this makes sense.
59:06
If Thomas wants to be able to uh get out all at once or or get out get out partially, get some liquidity, uh this is probably more effective than um than selling uh you know just selling it selling it piece by piece and he gets to hold on to the art too. That's the other thing. >> Oh yeah.
59:27
I mean probably >> keep keep some in you know >> different properties etc.
59:33
Well, we have our first guest of the show, Brad Taylor, coming into Altron from the Reading room. Brad, how are you doing?
59:42
>> I didn't get the wardrobe notice.
59:44
>> Yeah, we normally wear white suits when the market is ripping and and we're celebrating ripping. So, we're celebrating.
59:51
We're wearing them for you.
59:54
>> Thank you for celebrating our growth. I really appreciate it.
59:57
>> Yeah, it's been fantastic.
59:57
Uh, give us give us the brief history, the the founding of the company to the news just last week. Yeah.
1:00:04
So, Sierra, we help companies build AI agents for customer experience.
1:00:09
So, think uh maybe it's on a website, maybe it's answering the phone.
1:00:11
Uh no one likes to wait on hold.
1:00:13
Now, you can chat with an AI agent.
1:00:15
We're helping do everything from originate mortgages to help you get a better rate on your Sirius XM plan to helping, you know, when your ADT home alarm system doesn't work, you'll now chat with an AI agent to fix it.
1:00:27
Um we're a couple years old.
1:00:29
Uh we're the leader in this space.
1:00:29
Um, we kind of uniquely have run towards, I would say, larger enterprise businesses.
1:00:36
We're trying to help companies that candidly it's it's hard for them to deploy AI because they've got lots of legacy systems, maybe they're in a regulated business like the health insurance market or banking with the whole hypothesis is if we can help them be successful, there's just a ton of value and leverage in that.
1:00:52
So, uh, as you mentioned a couple weeks ago, we announced a recent round of financing, which is, uh, we're proud of, just a milestone on the path, but I think kind of recognizes our leadership in this space.
1:01:04
>> You're the chairman of OpenAI.
1:01:04
How should I think about application layer versus model layer.
1:01:08
I'm sure you get this all the time.
1:01:09
Uh, there was a meme for a long time about, oh, OpenAI is going to go on stage at Devday and just steamroll a bunch of companies.
1:01:15
You seem to have good information on what they're going to steamroll. >> Yeah.
1:01:21
And the other thing is there was there was so many you know two years ago so many different companies that had thriving businesses doing customer various customer service platforms and >> you know many people would have said these companies are just going to move quickly on AI get this you know they have the customer relationships uh but you clearly saw it differently and have proven that that that uh hasn't been necessarily the case. >> I'll answer both.
1:01:47
I'll start with the foundation models.
1:01:49
foundation models. My my theory of how the market plays out is that the foundation model market will look a little bit like the infrastructure as a service market where it you know primarily provides technology low-level technology to a lot of applications companies and then there's all the adjacencies you know like if you look at
1:02:08
Amazon web services they've got some developer tools if you're kind of in the area like snowflake and data bricks there's probably an Amazon product that competes with you the farther you go towards serving a line of business um you know like ERP systems or CRM systems the less likely it is that you're going to run into uh you know an infrastructure provider competing with you. I think the same is roughly true in
1:02:28
I think the same is roughly true in the AI market.
1:02:30
You know if you think about what's required to make AGI it's a lot of like you know training stuff but it's also maybe software engineering agents.
1:02:39
So that's probably sort of in the the the target of these foundation model companies.
1:02:43
the closer you get to, you know, Harvey doing legal AI or Sierra doing customer service AI probably doesn't seem in the core of these, you know, research labs, you know, primary uh functions.
1:02:53
Um, the reason I think that the applied AI market is exciting, not just for Sierra, obviously I'm a, you know, very loyal to my own company.
1:03:01
I don't think most companies want to buy a bag of floatingoint numbers and then figure out what to do with it.
1:03:06
You know, they want to buy a solution to their problem.
1:03:07
And if they can, you know, turn on Sierra and it will answer the phone and bring down their customer service cost by 50% overnight, they're going to do that, not try to, you know, take these models and try to do it from scratch.
1:03:19
If they can buy Harvey and get an antitrust review for onetenth the cost, they're going to do that.
1:03:24
Um, and I think, you know, I al I was talking to Toby Luke at Shopify one time and he was joking how many people come up to him and me and like, "Aren't you just a database in the cloud?"
1:03:33
And you're like, "Yeah, I guess so."
1:03:35
But there's a lot more to it.
1:03:35
And it turns out these workflows are valuable.
1:03:38
So I'm I'm really banking our company that there's a lot of value in these agents.
1:03:41
Uh and I but going to the second question on the incumbent software providers in this space.
1:03:46
It's very hard to disrupt your own business model.
1:03:51
If you're licensing customer service software per seat and you have to make an AI agent that will actually cannibalize your own business to realize the value of this new technology.
1:04:00
That's not just a technology problem, right?
1:04:04
That's a business model transition.
1:04:04
And the history of technology is littered with companies that saw the slow motion car wreck of their business model being hurt by a technology trend and not really being able to respond to it fast enough.
1:04:19
And I have so much respect for people like Satcha who navigated those transitions, but you know, candidly, there's a lot more companies in history that didn't navigate transitions like that.
1:04:28
And I think that's candidly just a simple reason why it's hard for a lot of the incumbent companies to to respond to this new technology trend.
1:04:33
When you were thinking about starting this company, did you did you like how methodical were you about ma mapping the market?
1:04:40
Is there like a whiteboard picture of you looking at maybe I should do ERP?
1:04:46
Maybe I, you know, was this one of a few options that you narrowed down once you studied the market or was it something that just came to you in a fugue state or something?
1:04:59
>> Yeah, it's such an interest you said that.
1:05:00
We actually did call up some, you know, uh, potential customers.
1:05:03
We started those conversations just saying, "Hey, if you could put us on one problem, what would it be?"
1:05:08
And by the end, we had a pretty clear picture of the available markets.
1:05:11
I don't think any of it was particularly surprising in some ways.
1:05:15
You know, it's like software engineering, customer service, content marketing, you know, all these things that come up when you think about if you have a technology that can see and understand text and voice, that can reason, you know, what are the direct applications?
1:05:28
But kind of the to the the thing that we're most excited about is not where we are today, but where it might head.
1:05:35
And our whole theory is that your AI agent will end up more important than your website or your mobile app in the future.
1:05:41
Uh and as a consequence, we think the addressable opportunity here isn't just customer service, which is really compelling and interesting, but saying, you know, how can you actually drive more sales?
1:05:51
How can you actually create a personalized concierge for your your brand?
1:05:56
I mean, just to give the math of it, if you actually have a phone call with a human being, uh, it probably will cost on the order of $20 at least, and it really depends whether it's onshore or offshore.
1:06:05
If you think about running a large-scale consumer brand with an arpoo of $20, you know, how do you afford that? And you can't.
1:06:12
And as a consequence, it's almost impossible to talk to most consumer brands.
1:06:16
You bring down that cost to 20 cents or even 2 cents over time.
1:06:21
You just think about the dynamics.
1:06:23
Let's say you're a large mobile phone carrier and you're fighting for retaining your subscribers.
1:06:27
You're not just going to recoup cost savings in customer service.
1:06:32
You're going to say, "How many phone calls can I have with my customer so that I retain this subscriber for five more years?"
1:06:37
Think about the impact on your lifetime value of your customer.
1:06:41
So, what's exciting about this like so many new technologies is like the first order effect is obvious which is saying hey let's reduce the cost of customer service by you know 50%.
1:06:51
The second affordable effects are almost more exciting which is the companies that lean into this faster will actually grow their topline faster than their competitors.
1:07:00
So that's what's so fun about technology disruption right is that you know you can end up sort of upending you know sort of the incumbent versus insurgent dynamic.
1:07:08
At the same time the value proposition to the companies using Sierra is more than just cost reduction.
1:07:14
It's saying like how can we actually give you a competitive edge by moving faster in this new world of AI.
1:07:20
How are companies actually, you know, you're you're going and and landing some of the probably just crazy logos, right?
1:07:27
And and these are, you know, massive uh companies with uh you know, operations all over the world.
1:07:33
How are they actually rolling it out?
1:07:35
Are they are they giving you specific sort of segments, regions, you're proving it out uh at a smaller scale or you what is the actual roll out look like?
1:07:47
>> Yeah, so starting you're right.
1:07:47
One of the things I'm most proud of is the scale of some of the companies working with us.
1:07:52
Over half of our customers have over a billion in revenue.
1:07:54
Over 20% have 10 billion in revenue or more, which is pretty I'm just really proud of that.
1:08:00
And I think it shows you do not need to be a small startup to deploy AI successfully with Sierra.
1:08:04
Um on the roll out, it's a very kind of a variation of what you said.
1:08:09
Some companies start with us on a use case or two.
1:08:11
um we're going live with one of the largest healthcare companies in the world and actually replacing their IVR system, you know, and it was just in a handful of months to do that.
1:08:20
So, you know, it can really I think it's really up to the the customer how assertively or aggressively they want to roll out these new technologies.
1:08:28
And the thing that I've been most pleasantly surprised is some of the largest more well-regulated companies in the world actually want to move faster.
1:08:36
Uh, I was having a conversation with my co-founder Clay about one of our largest clients and kind of being all inspired about how fast they're moving and I said, "Now I know why they're big."
1:08:44
You know, now I know why they're successful because they're moving faster than some of their smaller competitors that we also work with.
1:08:52
And you kind of you really learn to respect the I say intentionality, assertiveness of a lot of these like really well-run companies.
1:09:00
>> What's the sales process for a huge company like that?
1:09:02
is that like you meet the CEO at a you know fancy conference and start pitching or I mean like it feels like an advantage of like having a career like yours and the rolodex that like that's sort of like the unfair advantage here.
1:09:16
>> Yeah, it in many ways Sierra like you know doing what you guys have done in two years is incredibly impressive yet at the same time it's what I would expect out of out of the team right and Karp like he's just so fun to talk to.
1:09:29
He's in all these interesting places and it's like, yeah, I could imagine that some big Fortune 500 company just wants to hang out with Karp and like talk to him and then they do a deal together. Is that how it works?
1:09:39
>> Well, it's funny when you said this is what I expected.
1:09:41
This is like why it's hard to start multiple companies.
1:09:42
Like yeah, of course it's going to be successful.
1:09:45
I'm like, have you ever started a company? It's hard, you know?
1:09:47
So, but uh >> yeah, but I mean it's it's and I and I and I say that as like a as a compliment where it's like it's Yeah.
1:09:54
going from zero to a $10 billion company, having, you know, this crazy, you know, list of customers is incredibly difficult.
1:10:00
But I like when people have a lot of advantages through what they've done in their career and their network and then they just put on an absolute master class.
1:10:10
Like it's it's very satisfying.
1:10:13
>> Well, I appreciate you saying that.
1:10:13
You know, it does all have to start with the product though, you know, because certainly I would say my guess is the way I think of Sierra is we have the best product, but because we have a founding team that's sort of been there and done that, we're not like a hugely risky bet.
1:10:28
You know, we know how to work with large companies.
1:10:30
We're not going to show up and be learning from, you know, first principles how to engage with a large bank or a large health insurance company.
1:10:38
And that's a unique value proposition because right now most of the incumbent technology platforms their products don't really work.
1:10:44
And so you really want to use a best of breed product right now.
1:10:48
And I think our value proposition is we are a best of breed and I believe the best of breed product in this space but we also know how to like work with complex companies.
1:10:55
You know we're going to show up with as many people necessary to help you be successful as opposed to just throwing a product over the wall and saying good luck to you.
1:11:04
And uh so that I think I you know certainly our reputation helps but at the end of the day it's the quality of the product that really matters here.
1:11:12
And just you know think about it this way.
1:11:13
If you have 400 million phone calls a year the difference between having an AI answer 100 or 300 million of them is probably measured you know and you know at least eight or nine figures right in terms of like the impact on your business.
1:11:27
And so we always start with the product and as you said take advantage of our unique uh unique advantages as a company which fundamentally means we know how to work with you.
1:11:37
Uh it's sort of interesting like it just turns out that you know there's lots of different stakeholders between a business team a technology team compliance understanding just like the constraints that a company is dealing with.
1:11:49
Uh we just try to show up with a ton of empathy and you know show up recognizing this isn't just a technology problem.
1:11:55
You know, it's sort of a kind of bureaucratic word, but it's a change management problem.
1:11:59
You know, how do you get from point A to point B when your auditor and your regulator is scrutinizing everything you do?
1:12:04
Well, we understand that.
1:12:06
Like, we're going to help you with that problem, not just the technology problem.
1:12:11
>> What do you think the steady state of commerce interactions look like?
1:12:14
because I imagine that uh companies will be using AI to interface with their customers, but then customers will be using AI agents to negotiate on their behalf and select products and uh without leaking too much of the OpenAI road map.
1:12:32
I think we're all pretty convinced that some sort of agentic commerce thing is going to happen.
1:12:36
I'm already seeing popups for, you know, links to products.
1:12:40
when I uh search for things, I'm going to be able to say, "Hey, go get me the best option, the best price."
1:12:46
Is the future a voice agent talking to another voice agent or do they just interact at some lower level API level at some point?
1:12:53
Like, how does that all play out when you get agent on agent warfare?
1:12:58
>> It I I think you're right about your intuition, but it's also, as you were sort of alluding to, the future's not perfectly clear, even for people in the middle of it like me.
1:13:05
But I I think in general I think a lot of intent has already gone from search towards chat GPT especially for the more considered the purchases, the more you're likely to use something like AI.
1:13:16
You know, when I was traveling this past summer, I used Chat GBT to plan the entire trip.
1:13:21
Chat GBT to plan the entire trip. If you think about something serious like purchasing a home or you know I you I've talked to so many friends who are using chatb to figure out how's the school district in this area what neighborhoods are good you know and you think about
1:13:35
that just from a commercial standpoint that is extremely qualified intent at the very top of the funnel and so much research is already being done there but as you alluded to the thing that's not happening is you're not kicking off your agent to go fulfill that transaction. It
1:13:47
It sort of stands to reason to me that that will likely happen at some point.
1:13:51
And then the question is for a lot of our customers are sort of on the other end of that is what do you how do you want to show up in that new world?
1:13:58
You know, how do you ensure that you know your goods and services show up in the right way?
1:14:04
You know, when you're engaging with an agent, how much do you want to directly engage with consumers?
1:14:08
How much will you be able to directly engage with consumers?
1:14:12
I don't know all the answers, but step one is make an agent.
1:14:13
You know, step one is, you know, make an agent so that whatever inter agent protocols emerge, you can be present and do business in that new world.
1:14:22
And that's one of the main value propositions Sierra provides its customers is like we don't know exactly where the world's going to go, but a prerequisite is to uh technically be able to interoperate in that new world.
1:14:34
Uh, and I think impact different industries differently. Sorry.
1:14:38
Do you think the do you think the form will generally die?
1:14:40
Well, there there's certain businesses out there that sell basically sell product, let's say like a a company that makes aircraft, right?
1:14:47
If you go to their website, you're not just like browsing inventory and checking out. It's like you Yeah.
1:14:53
You're not adding to cart.
1:14:55
Um >> Tesla's likes to do add to cart buttons on, you know, >> most companies out there.
1:15:02
>> Let's say somebody contact aviation enthusiast wants to buy a small plane.
1:15:07
they've got to contact sales and then like the second you get to the form so much >> like uh so many leads just die at the form and something I've been doing with LLMs is just ask talking to them about like the pricing of different products because I don't want to go to the form and like get a sales rep to call me.
1:15:21
I don't want to be waiting I don't want to just get a call back at a random time.
1:15:25
I don't really want to go through the but but I want to kind of understand and so it feels like the form is something that fundamentally could just potentially go away and it's you go to a website you talk with an agent maybe you give them your information because you do want to hear more you do want to talk to somebody at some point but uh feels like uh feels like that could be going away. >> I agree.
1:15:47
I mean, if you just think about qualifying a lead, which is basically what those forms are, why not ask follow-up questions?
1:15:52
Why not collect enough information so that when that great salesperson does follow up, 80% of the work is done?
1:15:59
And it's just the the human touch uh part of it.
1:16:01
You know, agents are already doing outbound sales, debt collections for credit cards, processing, payroll for small businesses.
1:16:10
Uh these agents are already doing sales.
1:16:13
And I think that, you know, the best sales people, the reason why they're the best paid people in most companies because they're worth their weight in gold.
1:16:20
But what about the median salesperson?
1:16:22
And my guess is you can make an AI agent that's actually quite a bit stronger than most, you know, just because you're standardizing the best practices really, really fast.
1:16:33
You can run AB tests on AI agents.
1:16:33
It's hard to run AB tests on people, you know, and there's so many advantages, as you said, to not only just forms, but really thinking about agents as not stuck in one part of your customer life cycle, but really managing the whole thing.
1:16:47
And let's just take I don't know much about airline, you know, buying a an airplane uh for a a hobby pilot, but imagine this AI agent sort of the concierge to the whole experience.
1:16:58
So, you're browsing around Empires, you set up an appointment. You know what?
1:17:02
If it's uh collecting a bunch of information before you get on site after you, I don't do you test drive an airplane, but let's say you do that, you know, afterwards it's asking you questions, maybe helping you with financing.
1:17:14
I think that's the future of where these things are going, which is whether or not a person's involved, it's a concierge helping you through the whole process.
1:17:20
Yeah, there's something about, you know, the the consumer being proactive, engaging for information, but then, yeah, using the the the airplane example, let's say they don't have something in stock, you know, the the agent at at what point are you guys already thinking about agents being proactive and and reaching out to to a customer after they already engaged?
1:17:42
Like I imagine a lot of the core of what you're doing today is just reacting to customer needs inbound questions things like that or or problems with a product whatever it is but then at some point or another the the agent is going active and actually going outbound but how do you think about uh how do you think about that? >> That's exactly right.
1:18:00
I almost think of it as like Masow's hierarchy of needs of agents. >> Yeah.
1:18:05
>> Step one is answer the phone.
1:18:05
You know when your customers call.
1:18:07
Step two is can you actually get in front of of customer issues?
1:18:12
Um I noticed the ramp logo in the top right.
1:18:15
They're they're one of our customers and like they have like the coolest implementation of our platform.
1:18:20
Uh the it's you know not only doing service but really like I love their aski function in their product.
1:18:28
It's just one of the coolest experiences and it's just it's not service right.
1:18:32
It's basically a conversational experience around one of the best design technology products in the world.
1:18:36
And I think, you know, RAMP is obviously one of the the best engineering teams in the world.
1:18:41
But can every can every brand do that?
1:18:43
You know, can every brand make their their agent proactive, offer a conversational experience?
1:18:48
I look at if you've ever visited like Brazil or India and you look at the impact of WhatsApp, it's like, well, can you be present there in a way you weren't before? Well, yeah, you can.
1:18:57
What an awesome opportunity for agents. It's new channels. It's proactive.
1:19:01
Uh and this is really uh where we're trying to to guide our customers and I think you know kind of represents the future of our platform in a lot of ways.
1:19:11
>> Uh the the latest round I think it's 350 on 10 billion that feels low on the dilution side.
1:19:16
Uh how did you think about uh the amount of money you needed to raise sizing that?
1:19:21
I mean you've been part of so many interesting financings throughout your career.
1:19:25
throughout your career. uh how did you land on that and uh what does it say about the the usage of that fund how in capital intensive your business is the state of the markets right now just take me through the the thesis for the round >> yeah I always think of rounds in pretty simple ways which is what valuation are
1:19:43
you raising at um what do you need to fill in that valuation so that if you need to raise another round or if you're going public that you've uh you more than filled out that valuation with fundamental business metrics like in your revenue and growth rate and and then you start and then you say okay how much capital do you need to to reach that milestone. Um and so that's kind of
1:20:07
Um and so that's kind of how we reached it and and that 350 number it's not it's obviously there's a lot of precision involved but it is a bit of an art form because you're making a lot of assumptions about the future which is what are the capital that we need to reach the revenue scale where uh you know we can reach the next milestone in our business.
1:20:26
So that's how we think about it.
1:20:27
I I'm I'm pretty methodical about it.
1:20:30
You know, I think a lot of entrepreneurs make the mistake of raising too little at too high of a valuation and they end up sort of sort of walking sort of a zombie company just because they've they don't have the capital they need to to reach the next milestone, but they've uh uh but their valuation is such that they've sort of priced themselves out of the market.
1:20:47
So, that's the main sort of thing I'm paranoid about and I feel really good about how much we've raised.
1:20:52
But more than anything, too, I feel great about the investors we have around the table. uh benchmarks.
1:20:58
Yeah, Green Oaks, uh Neil Met at Green Oaks is just remarkable and so love our board and and in particular, you know, I think about who do you want to be on the journey with to get to that next milestone and and really happy with the folks we have around the table.
1:21:12
>> How are you thinking about uh IPO timelines just generally?
1:21:15
Do you think Sierra is going to be another Stripe or data bricks where you just stay private forever because you can and it's probably allows you to to um whatever take more risk, think long term, etc.
1:21:28
Or given that you've been um you know uh done your tour of duty on the on the public side in the past, I'm I'm curious how you think about it. >> Yeah.
1:21:39
Uh I don't think we're Clay and I have talked a lot about this.
1:21:42
I think our intention is to eventually go public.
1:21:46
uh you know we uh there's a lot of advantages to staying private.
1:21:49
I also think there's a lot of advantages to sort of having liquidity for your employees.
1:21:55
You know that access to capital.
1:21:58
Um you know I really admire the way I know the Stripe founders pretty well and you know they're in a really unique position.
1:22:05
I respect what they're doing.
1:22:06
I think we'll probably take the more traditional path though it's far enough in our future.
1:22:10
You know that's just more our philosophy because I think that's where you're going.
1:22:13
We don't have reticence to do it eventually and we'll probably more take the traditional path. >> That makes sense.
1:22:19
H >> how do you think about uh the Sierra fundraising process versus what's happening at OpenAI?
1:22:25
Is it just so much simpler to under?
1:22:31
Have you have you learned it's not it doesn't feel like it's just add a couple more zeros like the Open AI stuff it's seems deeply complicated.
1:22:36
Is it refreshing to have more of a simpler business to underwrite or are there at least lessons that you've ported over?
1:22:44
Have you learned something from OpenAI that you brought back? I'm interested.
1:22:47
>> Like CC Corp traditional equity financing.
1:22:52
>> It's pretty it works pretty well.
1:22:54
>> Open are just a really I mean it's a oneofone business as you all know really well.
1:23:01
The thing that's just so different about building the AGI versus building a PI company, they're just so different from a capital standpoint.
1:23:09
you know, uh, as Sam has articulated better than I could, AGI will fundamentally in some ways be driven by compute.
1:23:16
And so much of the capital strategy, um, that Sam's articulated is really how can we have the best compute infrastructure and the most uh, resources available for both training and inference, especially with these reasoning models and and meet the scale of demand there.
1:23:33
And when you have something that capital intensive, it just changes your approach to fundraising partnerships.
1:23:39
Uh and uh I really admire, you know, what the management team of OpenAI has sort of orchestrated there just because I think it's the company that is best positioned to to essentially build the the best computer, the largest computer in the world and have the best research team, which I think if you're saying what are the ingredients to winning in that market, I think they've checked both those boxes.
1:24:00
those boxes. in some ways the applied AI market I I'm not sure other founders in the space would agree like I don't think you know we're like an AI company I mean we're using AI to solve business problems but >> well and that's what that's what I what I love about kind of the whole approach
1:24:17
is that we you know we talk to a lot of companies that say we're an AI agent company or we're an AI company and then you look you ask a few questions and you realize like you're building enterprise software there's a bunch of things there's a bunch of things that And there's nothing bad about that. We love
1:24:31
We love we love enterprise SAS more than anyone.
1:24:35
>> But you know, if you forget that and you get fixated on, you know, we're building, you know, we're just building agents, >> it's like you're going to your customers will eventually ask you for a feature set that looks like traditional software, although maybe it's a different workflow.
1:24:50
Or you might burn 20 million of capital training a model because it makes you cool at a San Francisco cocktail party and lose sight of why your customers are hiring you to do the job that you're doing.
1:24:59
And so, you know, to some degree, I as you said, I'm we're un unashamed of being an enterprise software company.
1:25:06
And more than that, you know, I think the way we invest our capital is very different. >> Thank you. Thank you.
1:25:12
uh how do you what's your framework for understanding uh SAS companies and the public markets today?
1:25:19
Uh what what percentage do you think we'll be able it feels like everybody will have to transition at some point from traditional seatbased pricing to value based pricing?
1:25:28
You guys have the benefit of starting out with value based pricing and saying how many phone calls do you get?
1:25:34
How many how many uh how many individual reps do you have?
1:25:38
you know what what percentage of that can we uh you know augment or replace but uh just feels like doing that transition on a on a on you know a quarterly reporting cadence feels completely you know miserable. >> Yeah.
1:25:54
My high level premise is it's easier to transition your technology than it is to transition your business model.
1:26:00
Uh, and it's especially if you're public just because if you just think about uh let's say you have uh your I'll just pick an ERP company and you have an enterprise license agreement for some number of seats you know and uh or you know ITSM or something like that and then you say okay we're going to make an agent to automate 70% of what this platform does.
1:26:23
That's easy in theory, but what happens in the next renewal like in six months?
1:26:28
Maybe your AI agent platform isn't quite mature enough uh to actually, you know, make up for the difference in loss seats.
1:26:35
So maybe your sales rep who's incentivized on increasing the size of that contract goes and it says you should buy both, you know, buy the same number of seats and an AI agent and all of a sudden the CFO of that company is like, wait, I thought this was supposed to reduce our cost, you know, like what's going on here?
1:26:51
And so I think the I think all these incumbent SAS companies have an opportunity to come out strong in this market, but they have to really transition their business model and their technology model at the same time.
1:27:05
And anyone who says it's easy has never been a public company CEO because it's it's really hard, you know, because you end up uh having to tell a story to your investors, to your customers, to your employees.
1:27:16
You have to go through a trough of despair probably.
1:27:18
trough of despair probably. Um and you know if you look at Microsoft's transition to the cloud and and it was really complicated to go from Windows revenue to Azure revenue now Sach is you know a hero for having done it but at the time you know there's a lot of people including me who wrote them off you know and and then afterwards you're like wow props to them for making that
1:27:39
transition and coming out so strongly but for every Microsoft there's a seable systems who didn't make a transition you know and for those of you online who don't know seable there was the company that that Salesforce beat in the
1:27:51
transition to the cloud and and now you probably don't know their name because you know they they didn't sort of make it through that that transition despite being the market leader in the on- premises software era. So you know I
1:28:00
So you know I think all these companies have an opportunity and I think that it really takes leadership.
1:28:06
I think it's very hard to do as a public company just because it's very hard for investors to sort of see through the quarterly earnings to see because you can it's just hard.
1:28:15
It's just like is this company mid-transition to something great or are they just dying, you know, and like it's easy and it's like and a lot of it a lot of it is ambition and storytelling and so it's just a complicated time in software.
1:28:29
Um I think it's really going to come down to leadership both like uh stakeholder management and technology leadership for companies to make this transition.
1:28:37
Are you getting uh a bunch of calls yet from AI application companies that haven't found product market fit and uh need to find a a soft landing or do you think that's a a few more quarters out because those companies are still well capitalized?
1:28:56
>> We are there's definitely the you know uh just given the amount of revenue growth for the ones that are working it's pretty clear the ones that aren't um there's some good teams and good technology there too.
1:29:07
So, uh, we try to look if it makes sense at all of them, if there's a good team that could contribute.
1:29:13
Um, uh, we actually >> when did that when did that start?
1:29:18
>> Uh, about six months ago. >> Okay. >> Yeah.
1:29:21
>> What's your I assume it will accelerate. >> Yeah.
1:29:24
We're having him from General Catalyst on the show Friday.
1:29:26
What's your reaction to his uh sort of hot take?
1:29:28
I don't know how much it was taken out of context, but this idea that triple triple double double double is kind of dead.
1:29:36
you need to be 10xing every day.
1:29:39
You're not interesting unless you're 10xing.
1:29:41
Um, is there something there where like the power law is getting steeper?
1:29:45
There's uh there are more winner take all markets, more faster growth companies, but then also just some that are, you know, triple triple, but then going to be nothing. >> Yeah.
1:29:57
So, I have a complicated opinion on this one.
1:30:00
So, first I'll say uh the faster you grow is sometimes correlated uh with a lack of a moat just because what enabled you to grow fast might enable your future competitors to grow there as well.
1:30:15
You see this in some social services as well.
1:30:17
You know, you'll have these social services grow from zero to whatever million users overnight based on a social mechanic and very few of those have ended up durable.
1:30:27
Some of them ended up incredibly valuable like Tik Tok but there's like you know the club >> but Tik Tok also spent like billions of dollars on user acquisition right >> exactly exactly in enterprise I do think that growth is greater in agents in part
1:30:42
just because there's more value in agents than there is in software because you're uh you know essentially doing things like that were people were doing before so you're you're just achieving more valuable outcomes than just slight productivity enhancement. The reason I'm
1:30:54
productivity enhancement. The reason I'm cautious on it is I think uh growth can sometimes be artificial you know so you can basically juice the numbers and and the question is are you creating a durable business and you know we talk a lot about like in our board meetings just about first mover matters and
1:31:12
there's definitely like a green field right now but what matters is where you are 10 years from now so like are you creating a machine to make happy customers at scale and so many of these businesses can grow to like you know 50 or maybe even 100 million in AR are and plateau and you saw this with a lot of different businesses actually. I mean it
1:31:28
I mean it was and so the question is what is your addressable market?
1:31:32
What are your product advantages?
1:31:34
What are your gotom market motion and can you scale to add to the next zero?
1:31:39
Can you grow to the next order of magnitude?
1:31:40
And I the only reason I I think he's a smart I thought it was a smart point that growth has definitely accelerated in this world of agents but as an investor in particular you're you're really worried about can they get a billion in revenue?
1:31:53
Can they get 10 billion in revenue?
1:31:54
And it turns out they're like growing really fast to 20 million is like loosely correlated with that.
1:32:01
You know, it certainly means there's product market fit, but the question is like was it with a very small niche of startups >> or selling or selling tokens at a loss and you're just subsidizing it, right? >> Yeah.
1:32:14
>> So, I'm I'm a huge believer in quality annual recurring revenue and very happy customers.
1:32:18
And my view is if you can do that quickly like we have, that's great.
1:32:22
If you had someone growing more slowly but it was very high quality revenue from very happy customers, I'd probably bet on them over just the fast growth rate because to me that's a more durable business over time.
1:32:33
>> Do you think do you think ex like just raw execution can be a moat because some of those things you were saying earlier.
1:32:40
It's not like you guys have access to different LLMs that someone else in your category might not.
1:32:45
But it's just this kind of like knowhow of selling into the enterprise and being able to do that at, you know, just with with pure excellence that feels like it's separated you guys from >> I'll say it's a I think it's I think it's all the above.
1:33:00
You want the best technology, best product, best go to market.
1:33:03
But I think right now because the technology is changing so fast, execution compounds over time, you know.
1:33:09
So if you had a great product today but you weren't executing well, you will not have the best product a year from now.
1:33:15
So that's where I think execution is maybe the main thing we focus on because it's basically the pace of innovation in your product and the pace of reaching and making new customers successful and we want to have the best pace because I think what we want if I I come on this show a year from now I want to be farther ahead of our competitors than we are now and that is all a function of execution.
1:33:35
Last question I have, I know I know we're a few minutes over uh so hopefully you don't have to jump, but uh how how are you thinking about the evolution of the cloud market broadly?
1:33:47
You have companies like Oracle waking up and uh getting extremely aggressive.
1:33:49
You also have a bunch of Neoclouds.
1:33:52
I'm sure all of these different players are calling you every day.
1:33:56
uh hopefully not sending you AI uh chat GBT generated cold emails but but I'm curious like you know where you expect to be uh and what kind of vendors you expect to be using on that side over the next 5 10 years.
1:34:12
>> Yeah, the Oracle story is pretty incredible, isn't it?
1:34:14
I don't like uh who would have predicted that.
1:34:17
>> What's your backlog if if you were going to do you >> that's amazing.
1:34:20
Well, it's really impressive, too, just cuz it sort of shows you, you know, sort of like a founderdriven big view of the market.
1:34:28
It's super impressive and and I've just like kind of I just I love stories like that just because it's like just I mentioned the Microsoft story where so many of us had written them off and like it's just super impressive the level of execution and uh clarity that Larry brings to that business.
1:34:44
you know, broadly I think the things that changed in cloud is just the shortage of supply of GPUs and the demand for compute and I think that is bringing a lot of uh you know there's a geopolitical angle too.
1:34:55
Where are these data centers built?
1:34:57
Uh data sovereignty all of that as well.
1:35:00
So I think we're in this new era of of cloud infrastructure where you know the capex is getting larger.
1:35:07
um you're seeing like the market crediting boldness in a lot of ways because if there's truly a a scarcity here, you know, and and I think Sam has been articulating, you know, it's like who whoever has the best infrastructure will really contribute to this world of AI in different ways.
1:35:23
And so I do think we're definitely in a new chapter there just because it's like, you know, different players are making different bold bets.
1:35:31
Um, and one of the things that's been really fun to be involved with OpenAI is just seeing sort of OpenAI's influence on that as we try to, you know, pursue our mission of ensuring AGI benefits humanity.
1:35:40
And a huge part of that is related to cloud, right?
1:35:42
It's if you don't have the right computer, you're not going to achieve that mission. >> Makes a ton of sense.
1:35:47
Uh, well, thank you so much.
1:35:49
We conver uh congratulations and we'll talk to you soon.
1:35:54
>> Yeah, thanks for having me. Cheers.
1:35:56
>> Great rest of your day.
1:35:56
Let me tell you about graphite.
1:35:57
dev code review for the age of AI.
1:35:59
Graphite helps teams on GitHub ship higher quality software faster.
1:36:04
We are joined by Joe Lansdale.
1:36:07
Next, >> we are going to welcome him from the reream waiting room into the EP Ultra Dome.
1:36:13
>> Joe, how are you doing?
1:36:15
>> Look at that audio video quality. >> Fantastic. >> How you doing?
1:36:20
>> You look younger than ever. You're aging in reverse.
1:36:22
The camera is helping as well.
1:36:24
>> The young the six young kids, I guess, are keeping keeping me young running around with them.
1:36:28
My one and a halfyear-old was your competition for this.
1:36:30
He was angry I wouldn't drive him in the car. A little baby car.
1:36:33
>> Do you have the most kids of any uh top GP?
1:36:37
Anybody got you beat that you know six?
1:36:41
>> I'm sure I'm sure some have more.
1:36:41
I probably you know my wife and I are pretty traditional.
1:36:44
So the just with her which makes it tougher to go.
1:36:47
>> We're going to get there eventually.
1:36:50
>> I wanted to ask you about this uh Trey Stevens post.
1:36:52
He said he found a Palunteer branded iPod touch generation 2 that he had custom engraved back in 2009 while digging through a box at my house.
1:37:02
Did you get one of these?
1:37:02
Do you know the story of this?
1:37:04
Is this a Trey Stevens exclusive? >> Touch from 2009.
1:37:07
Actually, I I I have a lot of early Palunteer kind of gear.
1:37:12
Most mostly I have these like giant things we used to carry around like these big computers and uh whatever their cases are called usually for guns.
1:37:19
We use them for computers.
1:37:19
Not sure about the iPod touch. >> The Pelican case.
1:37:21
You probably >> the Pelican.
1:37:23
There's like the really serious ones and I the very first time I brought it to DC, we had a rental car.
1:37:28
It was like 2005 and I went to the address we were going to stay at.
1:37:30
And then there's this very nice black man.
1:37:34
He's like, "You boys are on the wrong part of town."
1:37:35
And I'm like, "Oh, what's this Northwest Southwest thing?" You know, so DC.
1:37:41
>> Um, what was it like early in the Palunteer days?
1:37:43
Gary Tan tells the story about uh you're not selling Holiday in software.
1:37:48
You got to stay at a Four Seasons.
1:37:51
I forget exactly what hotel chains he mentioned. Uh is that apocryphal? Is that true?
1:37:54
When you traveled for business, would you stay at the top tier place?
1:38:00
>> I think the very top of the company would stay at like relatively nice places.
1:38:05
We weren't upgrading to the nice rooms, but there was it's probably like $600 700 versus $200 a night sort of thing, which you know, in retrospect, I think there's multiple ways of running a company.
1:38:15
I do think when you're meeting important people, you had to make sure you're not meeting them at the holiday and that would make probably not be a good idea for trying to to network with the very top people in these in these contexts.
1:38:24
So I think that's listen I think a lot of people waste too much money when they're starting companies.
1:38:28
So, I don't want to set a bad example.
1:38:30
The I I I I was I was actually like a top trader at Peter's Fund and then I like brought on my friends to like start this with me because a lot of them I brought on to the to the hedge fund and it turns out they didn't really like finance and so we ended up building out this company and and at the fund part of our comp was you can basically spend whatever money you want if you were one of the top guys there.
1:38:46
So, it was like a very kind of bad place for me to start from in terms of being spoiled already if we have to be honest here.
1:38:53
>> Thank you for being honest.
1:38:55
>> Oh, where should we start?
1:38:55
There's a bunch of stuff.
1:38:58
>> I mean, I I I we were just talking to Brad Taylor about this.
1:38:59
Uh Hamont uh over at General Catalyst was saying that like the world has changed.
1:39:04
Triple triple double double double for revenue growth is no longer interesting.
1:39:08
The only thing that's interesting is 10xing revenue every year. Something crazy.
1:39:12
The power law is getting steeper.
1:39:14
I would love your take on just what it takes to be interesting as a startup in the era of AI where if you are in the right market or you're indexed to the right thing or maybe you're selling tokens at a discount, you can get to a crazy revenue run rate very very fast.
1:39:30
What are you watching out for?
1:39:32
What are you optimistic about?
1:39:34
How does all that play out?
1:39:37
>> I mean, listen, it's definitely a very different world right now because there's so many new possibilities.
1:39:40
there's so many new possibilities. is I think we were looking at something uh I I want to out the person because I'm not doing it but we were looking at something that was like going 0 to five this year and I thought it could easily have gone to at least 15 or 20 if not more next year but I thought the team was kind of like a BB plus it wasn't
1:39:56
like the very very best people and and that is just insane by the way that that two those two things combined you can grow that fast with something that was like maybe not the very best people having trouble hiring and and I mean the bar is just a lot higher right now and by the way >> and to be clear that that round will probably get done that. >> Oh, yeah. Like >> Oh, yeah.
1:40:11
Like >> probably 100 million at least. Exactly.
1:40:14
And I'm pretty sure it will.
1:40:16
>> And it's like >> it's it's it's Yeah.
1:40:18
It's it's like it also raises the bar for everything else.
1:40:22
Like we were looking at this really cool thing in bio infrastructure that could be very important for the future of humanity and for what it could do in the bio world and it's just going to take three or four years.
1:40:30
And these things in bio as you know are just hard and and it's like you know what even though this is so important like we we have to on the on the margin you have to be in like the green fields right now.
1:40:38
the very very top AI teams are just so far ahead of everyone.
1:40:42
So, you know, I do think there's like I mean what Hamas says is to to me it's not as much about like exactly the metrics.
1:40:47
I think I think some people like live in metrics and they should and my one of my partners does too and you know my view tends to be like who are the very best talent in the world who has the very best cultures.
1:40:58
I mean you see something like cognition with you know 20 gold medal winners or whatever.
1:41:02
winners or whatever. Scott used to work for me at a hard after winning you know programming you know competition globally three times in a row and like like like obviously that's like the extreme but the extreme works in AI right it's like so I I think for me it's more about like what is the very best
1:41:15
talent and then let's build something that no one else can build and of course yes if it works it's going to it's going to grow insane speeds >> tell me the story of finding Scott identifying him recruiting him seems like one of the greatest talent acquisitions of all time you've developed a business relationship ship over a long time now. Uh, how did you
1:41:33
Uh, how did you even think to back him early, work with him early, any of that?
1:41:40
>> I mean, I mean, to be honest, to be honest, like Scott is a really special and amazing person, but you know, I I hired most of the first 200 people at Palunteer.
1:41:49
Adapar had eight kind of gold medal winners along with Scott who came in at the same time with my friend Vlad Novakoski was helping me at the time. Amazing guy as well.
1:41:57
Just give away all my secrets here.
1:41:58
People are going to go go get his help now.
1:42:00
Um but you got to hide some of these names from you guys. This is dangerous.
1:42:04
Um but but you know you know and then but Scott was one of eight that year and I think another one of them was Alex from scale and he was an intern there too and and you know it was actually very funny.
1:42:14
I mean both both amazing people.
1:42:16
I think I think Alex left in a way where we didn't stay as close and Scott left way where we did stay a little bit closer.
1:42:20
But even Scott I think he was running around the world and and I I' I'd been in touch.
1:42:24
I actually invested in his new thing after that which was not cognition.
1:42:29
>> Uh just a little bit because I thought it was a terrible idea.
1:42:32
>> And by the way, this is a very good idea.
1:42:33
When you have the smartest people in the world, you should invest in their terrible ideas.
1:42:35
Uh just as a as a sidebar, like we went back to 2022 and we met these people who were doing something really dumb and like we kind of want to give money anyway and we didn't.
1:42:44
It was out of MIT and it ended up pivoting into cursor. There was other people.
1:42:48
There's another one where it's like I have this chain from yesterday where Coley, my partner, is like forwards it to me and it's like these guys are really good.
1:42:55
They're raising seven million like 40 posts.
1:42:57
It's 2022 and I'm like oh god it's just we all think it's a dumb idea.
1:43:00
I'm like we can't we can't keep doing dumb ideas guys.
1:43:03
And then it turns out they pivoted and they're raising a five billion posts right now.
1:43:06
I'm like oh god we just need to like we just need to give smart people money.
1:43:09
This is like just like what you have to do. It's so annoying.
1:43:12
But >> yeah there's there's like the the the bell curve.
1:43:15
It's like, you know, on one end just give smart people money, on the other end, give smart people money, and in the middle it's like, oh, like, >> oh, what's the idea? What's the traction? What's >> Exactly.
1:43:25
Just like even though it's like actually actively a bad idea, like give them money.
1:43:29
And by the way, even the thing that was a bad idea like Vlad, he's doing with Vlad now or Vlad's in charge now that, and he's pivoted to something, it's working, it's probably it's also a unicorn.
1:43:36
So, it's like they figured it out.
1:43:37
So, it's just the same like it's just all about talent.
1:43:39
And so I lost I lost touch with Scott a little bit and I got back in touch with him and fortunately I've been in the last few rounds of cognition.
1:43:45
I wish I wish I'd say as his best friend.
1:43:46
It's it's hard to keep in touch with all the smart people you admire flying around when when we're busy but it's he's someone I really enjoyed getting to know and he's he's someone you know he's really grown as a leader more than I expected.
1:43:56
Sometimes you know people when they're like 18, 19, 20, 21 and and you get one impression of them and you're so impressed but but like was not like the leader personality and now he's just such like a fierce leader personality plus plus you know the global champion thing.
1:44:10
So that's pretty amazing.
1:44:10
He's doing he's doing good work.
1:44:12
>> Yeah, we read a Wall Street Journal article about the latest IMO gold medalists and I was surprised because I was uh texting with a GP at a big fund and they were not tracking it. They were not.
1:44:24
Our joke on the show was like every single one of these kids mentioned in this Wall Street Journal article that beat both Deep Mind and OpenAI and got the full score on the IMO, they're going to be getting term sheets, but people weren't tracking it as closely.
1:44:36
weren't tracking it as closely. Yeah, it seems like when you were hiring, you know, these uh IMO uh winning folks back with Adapar and and maybe a Palanteer, the meta at the time was like you you want to invest in the kid who's like
1:44:51
sleeping on a mattress on their floor like sleeping in a closet in San Francisco maybe was like somewhat of a nar like a different different track then even though you can see it becoming consensus now because >> Scott has you know shown >> No, it's Scott, it's Scott and Alex and a few others. But listen, I don't think
1:45:08
a few others. But listen, I don't think there's too much alpha left in that in the sense that like when you have all these people at OpenAI and at anthropic and they've raised infinite amounts of money like you know it was a problem for me in Palunteer in 2008 2009 when Meta
1:45:24
and Google it wasn't even called Meta at the time started giving 100k bonuses to these kids out of the top schools because we had like a monopoly on on just the playbook for the top 20 universities and they started just like giving like 100k bonus that's insane and
1:45:37
like now it's literally like 100 times that for these other I mean there's there is some alpha I'm not going to tell you all my secrets in the show unless I'm required to you tell me I >> oh you are required >> alpha left but it's like but it's like
1:45:49
it's like I don't think >> if you want to tell every investor >> tell everyone you can text us after the fact the real secrets and we'll keep them private >> how are you um how are you thinking about uh you know you've obviously had numerous plays in traditional enterprise
1:46:05
software it feels like a lot of public SAS today is has this challenge of transitioning from you know the traditional seatbased model to something more like Palanteer the sort of like valuebased pricing how are you think you know are are you just bearish on public
1:46:23
SAS broadly do you think some of them are going to be able to transition Brett Taylor just said it's easier to you know do a a transition your tech your tech business model your tech than your business model especially in the public markets >> it's it's so funny to live in this world
1:46:38
cuz it's like I woke up in opposite land where I was like people just beat the out of me for like a decade for doing the wrong thing the wrong model and suddenly suddenly like how could everyone do that model that's great I guess uh I I I don't I don't actually know if everyone needs to do a change in
1:46:53
model I overall I I guess I think the more interesting question is like which of these SAS companies owns important infrastructure and workflows uh that are juxtaposed to other value they can capture with AI and then also still has the technical culture to do that. So
1:47:08
So this is like a motion at Adapar I'm working on really hard as an example I started addar 15 years ago.
1:47:13
It has over $8 trillion in the platform.
1:47:15
The core infrastructure business is still growing.
1:47:19
Infrastructure SAS business is still growing at like you know 25 plus% just that core and there's all these things on top of it starting to grow uh because it just touches everything when it provides value for wealth managers.
1:47:29
And so I think to get that business growing 40 or even 50% potentially, it has to like build really strong AI teams and workflows that take advantage of where it is.
1:47:37
And I think there's going to be a bunch of SAS companies that do figure this out in the next few years.
1:47:42
And those are going to be really valuable companies.
1:47:43
And then the ones that don't figure it out at all, there's probably some danger that they even lose the mode of their core thing to begin with because it's going to be too easy to copy or something if they're not if they're not like scaling it.
1:47:52
So, so, so I I I think I again think it's like a power law thing where some of these are actually worth a lot more and then most of them don't have the talent to do it.
1:48:00
>> Yeah, it's been fascinating watching the the narrative shift from the foundation model companies are going to eat everything to the foundation model is going to commoditize.
1:48:07
There'll be a couple application layer companies to the idea that AI would be sustaining in enterprise SAS because you actually even if you have a semi-technical culture, you don't need to train a foundation model.
1:48:18
you can just go grab an OpenAI API and and implement that.
1:48:20
But there's this business model tension now.
1:48:23
And if you're stuck in your business model, uh there's going to be a lot of startups that are counterpositioning against you and you're going to be kind of screwed.
1:48:32
>> It's it's it's interesting because I do think if you own the customer really well, you cut out these things much more easily, but you're going to have to go faster.
1:48:38
The startups are going to eat it away.
1:48:39
There's so many areas where we're kind >> or the system of record or some sort of datab like Sakotra as a company I'm in.
1:48:44
It's like a great system of record for the insurance space and it's >> took a long time to build.
1:48:50
It's a bunch of palenteer talent.
1:48:51
They're really coming into their own system of record now which insurance is very slow and then they're trying to add the AI in before all the new AI things that people are funding and it's it's I think it's pretty interesting.
1:49:01
I think the system record has a very good chance of winning but that's a question. >> Yeah.
1:49:05
>> How are you thinking about macro broadly?
1:49:06
broadly? I feel like everybody's I mean every asset all-time highs, >> gold, Bitcoin, the >> I like I like I like the I like the meme I like the meme that says printer is coming with you know he's dressed up as as as Lord Stark of the Northter is >> yeah but but but for your angle it's
1:49:26
probably generally better use of your time to like think about you know the opportunities at the early stage today you could incubate a company you could fund a company what is the >> I am I am I'm incubating a lot listen I started incubating a a lot more in 2021. Partially cuz I was just so annoyed that
1:49:38
Partially cuz I was just so annoyed that everything was like insanely unreasonably expensive and they have >> and you kind of have a monopoly on the first couple rounds, right?
1:49:45
Is the >> Yeah, we probably were too generous letting friends in.
1:49:48
I'm always just like I have these business friends who are just like much more hardcore than me and just like just like very sharp elbows and kind of even a little bit nasty and like I'm I'm tend to like just like to everyone around me to make money.
1:49:58
So I probably should have taken just only myself the first two rounds.
1:50:00
That's especially seronic.
1:50:02
I should have done that but whatever.
1:50:03
We still we own plenty of it.
1:50:04
Um it's it's fun to start things that are important for the country and that win and we make enough money for everyone.
1:50:09
Um but no, we we do do the whole like big first round ourselves now just cuz that's the right thing to do for the fund and then like do a lot of the second round.
1:50:16
Um and listen, I think building is still the I mean even right now today you guys tell me I'm seeing AI rounds where like I'm really happy if I get 15% in a series A of a really hot AI company right now.
1:50:26
I think I got 16% something the other day by overpaying and I I think it was the right thing to do >> and it's like but but I mean I've seen a lot of things where I get 5% and I'm or 6%.
1:50:37
>> We just talked to Brett Taylor.
1:50:37
He raised 350 million a10 billion valuation like that's not a lot of dilution.
1:50:41
It's going to be hard to build a huge position in that company and that's a one-year-old company like and these are happening all the time.
1:50:47
I mean he's special but yeah it's still a there's a special the specialist ones I only have two or 3%.
1:50:53
I'm really happy because I think they could be hundred billion dollar companies. It's it's very weird.
1:50:58
It's different than it was.
1:50:59
>> Uh talk to me about the the early stage uh startup market in Texas.
1:51:02
Obviously, you were in San Francisco for a long time, buddies with Gary Tan, co-workers at some point.
1:51:09
Uh Gary's leading a revitalization of Y Combinator.
1:51:12
Is there something adjacent?
1:51:15
Like if I wanted to go talk to 50 young people building startups, the next up in Texas, like where would I go?
1:51:24
who would I be talking to?
1:51:28
>> So, and and I've been fighting for California to fix itself for a long time.
1:51:31
Gary's an old friend obviously from our fraternity days through Palunteer and I think he's come more to my point of view on these things which I really appreciate. He's doing a good job.
1:51:39
Uh who used to argue a lot.
1:51:39
Uh you know, it's Yeah, there's a lot of history there.
1:51:43
He's Gary's Gary's crushing it.
1:51:45
the the the thing about Texas, there's a few things.
1:51:47
I' I'd say if you want to build like the very top AI startup in the cloud, application layer, model, whatever, like doing something really hard and new there, you probably should be in San Francisco today.
1:52:02
Like that that's just where the talent is.
1:52:03
It's a very strong network effect.
1:52:05
I would love it if it wasn't, but it is.
1:52:06
And and it's there and that's so so so why what do you do in Texas?
1:52:10
Well, I think we have we like I mentioned Seronic earlier.
1:52:12
I think if you're building in the land of atoms, if you're manufacturing, I think that's probably the most important company in the country for the US Navy as as well as doing very hard things in robotics, very hard things in in software around it as as applies to defense.
1:52:24
We do have like, you know, 10 or 15 of the very best AI software people for that there.
1:52:29
So, I I think what you're seeing in Texas is it's a really good place to manufacture.
1:52:32
You have a lot of the best people like Boring Company, a lot of the top SpaceX talent, others are coming out here.
1:52:38
Um, I think you have a lot of things that go really deep in healthcare here.
1:52:42
Uh obviously MD Anderson in Texas is one probably the best cancer center in the country alongside Memorial Sloan in New York.
1:52:47
Uh and you have just a lot of other really deep kind of healthcare research, healthcare services groups, healthcare services.
1:52:53
Uh you there's multiple multi-billion dollar new companies in healthcare here uh there.
1:52:58
So and and and I and I do think like like when I was talking Reed Hoffman, I was trolling because we have different politics like where do you test your like self-driving trucks?
1:53:05
And of course he tests them in Texas.
1:53:06
I mean, if you're trying to like do things, you know, if I'm trying to like automate, I think one of our companies that I'm really bullish on is uh bunch of Ximo guys and they're automating construction with excavators and they're going to like automatically run all sorts of construction and quaries and other things.
1:53:21
And of course, they're doing it in Texas.
1:53:22
So, so Texas is just like a great center for industry, for building things in the real world, for robotics talent, for defense talent, for healthcare talent.
1:53:30
It's it's it's it has great AI talent, but it's not going to compete with like the next new AI models in San Francisco.
1:53:36
San Francisco right now is is just is just obviously an awesome place for investing for that type of stuff.
1:53:41
>> My my current like understanding of the startup like micro worlds is that uh you're you're still probably going to be doing a road show on Sand Hill Road or in San Francisco.
1:53:51
Uh when you're later stage, you're going to be talking to crossover funds in New York.
1:53:54
uh you're going to be in DC if there's a lobbying component, but then you're going to need to build your company wherever makes sense.
1:54:02
And for certain industries, Texas makes a ton of sense.
1:54:04
And uh yeah, >> for for for a lot of things in the real world, a lot of things in healthcare, >> Texas is by far the best place to do it.
1:54:12
It's it's it's listen, I love you can go to the government.
1:54:15
It's not like they agree with me on everything, but you can go to them and you can talk and they're reasonable and they respect you and you go back and forth.
1:54:20
And you don't have to be a Republican or Democrat to do it, by the like they actually it's like you can't they actually care about business succeeding. It's very cool.
1:54:27
It's like it's a new idea to me to have a government that has a group like wow how do we help business succeed?
1:54:31
It's really great and then you can get things done and it's reasonable.
1:54:34
So I definitely like building things here.
1:54:36
>> Jordy >> uh without giving away too much alpha uh or feel free to put people down the wrong path.
1:54:42
What do you think is the most under underhyped uh trend adventure right now?
1:54:47
Obviously AI is just drowning everything out, but feels like could be at the, you know, beginnings of a new robotics wave.
1:54:54
But how how are you seeing it?
1:54:58
>> Yeah, I'm really interested.
1:54:58
You say robotics, I'm really interested in the stuff going on the real world using AI, which I think is like a whole new area that it's still early, but I think you're going to I think it's just like a much bigger part of the economy than people realize.
1:55:10
So, for example, if you can do a certain part of construction automated with bedrock, like I think people don't understand like that means you can run a query better and there's $100 billion dollars of queries and if you can make quaries have higher cash flow that's worth like it's worth tens or hundreds of billions of dollars.
1:55:24
I mean, it's just like and there's like there's like so many things like this where the real like the real economy is like 85% of the capital and that's all about to be transformed and I think people underestimate like how much we're going to need in credit to do that.
1:55:35
how much just like just like just like how much big stuff's going to happen that you can create in the economy in the 2030s there.
1:55:42
So, you know, even stuff like Boring Company uh and like and like automating that and making it much much much better.
1:55:48
It's obviously using modern AI and other modern technology as they iterate with engineers on it and it's just really impressive how much cheaper you could do things, how much better you could do things.
1:55:56
So, so I think that's underhyped and under misunderstood just because it's maybe takes a couple years longer to really get out there and start spreading quickly.
1:56:02
But I think I think it's just like much bigger than people realize.
1:56:05
And that's one of my favorite areas.
1:56:06
I guess the other one, you know, I think in general people spend too much time on like the super giant companies.
1:56:13
Like people call them the infinity stories or the things that could be worth trillions.
1:56:16
And I talked to some of my friends who are running very big funds and they're really only interested in something that could be worth trillions of dollars and have all the top talent.
1:56:24
And it's it's almost like I think I think one of them is is a good guy, but he said to me, you know, I want to be in the room with the powerful people doing the most important things.
1:56:31
And I think there that's like an instinct of a lot of our top investors right now.
1:56:33
And actually I think there's going to be literally like a thousand like 5 to$50 billion companies in like so many niche application areas that do need you to build out the workflow, do need you to build out the operations and do need you to kind of go after the different service areas of the economy. Yeah. What about it?
1:56:51
It feels like, you know, when you look at like Palunteer, Adapar, Open Gov, it feels like you've had a lot of success with companies that were very under, you know, not didn't have a ton of like crazy hype and and did the kind of like behind the-scenes heavy lifting to get to the point where you could have a massive outcome or or be really uh critical to an industry.
1:57:14
Are you do you think there's not enough of that?
1:57:16
Like it it feels like a lot of every company gets hyped, you know, incredibly quickly now if they're talent dense and are you still like trying to find opportunities where you can just kind of quietly build in a category for four or five years?
1:57:31
>> Yeah, I mean I think I am building a bunch of stuff that's not really that hyped right now that's using AI that's that's going to change these different categories.
1:57:39
And there's this like when you look at the talent out of Palunteer, it's a lot like the talent out of PayPal except on a bigger scale in a lot of ways cuz Palanteer had many more years to compound with the very top talent.
1:57:49
And so you have things like random things like like Candid is just like probably do I don't know they want me to give their numbers on on this show I guess but it's like they're doing they're doing healthcare billing.
1:57:59
They're growing really fast.
1:57:59
They're growing really fast. they're going to do, you know, they're going to get into the billions of of revenue like within the next few years probably and and and it's just like just like I guess, you know, it's a $280 billion space and there's not that much hype
1:58:10
around it >> and it's just like wow, this is like this could be absolutely this could be like a hundred billion dollar company in the early 2030s and and almost no one will have heard of it and it's like there's just so much stuff like that right now which is is pretty fun. So, I
1:58:20
So, I mean I I I think I'm really bad at hype.
1:58:24
I think Palunteer eventually got hyped like despite being us being bad at it.
1:58:28
Um which is people like I'd say like Seronic's an example of something that you know got a ton of hype, ton of capital, a ton of attention really quickly.
1:58:36
>> Yeah, that that that that did I I think we did get a lot of the right talent and we were kind of the right place, right time where there's no one else who was doing this for the Navy and had like and no one else who had like that density of of talent and operational like Dena's just such an amazing and such a fast CEO and he brought in kind of other co-founders who were also really top people.
1:58:54
So I think like Andreal they just had so many of the best people right place right time going hard.
1:58:58
So I guess that got hyped earlier at night.
1:58:59
I would have expected that's fair but but most of the things I'm doing are not like that.
1:59:04
>> Yeah that makes sense.
1:59:05
>> Do you think there's any positive knockon effects of the insane capex that's going into the AI foundation model world?
1:59:13
Like we saw Sam Alman say he's going to build 10 gigawatts.
1:59:16
Mark Zuckerberg saying he's doing a gigawatt.
1:59:20
Elon just did Colossus 2 it's a gigawatt.
1:59:21
gigawatt. And the interesting thing to me is like this is in some ways like the like you know Seronic Palunteer and SpaceX like those are American dynamism companies but I if you're talking about re-industrialization and just making big
1:59:35
things in America doing stuff that requires government approval like Elon's like Colossus 2 across three different states like that feels like that unblocks some crazy stuff and then it's going to be easier to work on healthcare or work on automated truck Very good. No, you're 100% right. Um No, you're 100% right.
1:59:51
Um whether or not it's a bubble and whether or not they should be investing this much money.
1:59:58
Uh I'm not even going to comment on because I think it's just like really good for America that they're like practicing building these things at this scale. You're 100% right.
2:00:07
They have to fix some of the permitting stuff.
2:00:08
Y >> they have to create all this infrastructure we can use now for advanced manufacturing.
2:00:12
We can use the advancements to make things cheaper to do at scale for building related things in America.
2:00:17
We're going to build a ton of stuff on top of this.
2:00:18
of stuff on top of this. I mean for me I just love it because you know I talk about the different levels of AI investing where it's like zero is energy infrastructure one is chips two is data centers three is the models four is software infrastructure five is apps and services and like I'm mostly doing
2:00:32
things at five and some four but but by people doing all the stuff at the bottom with insane amounts of money that makes my life very easy it makes everyone else's life easy too so this is great for America >> yeah for so long we've we've heard like oh America we c can't respond to DJI GoPro got roasted oh we can't respond to unitry maybe Elon will figure it out. And it's like I feel like we're getting
2:00:51
And it's like I feel like we're getting close to like no, you can actually marshall $10 billion of capital, set up a massive facility in a couple months and get approvals and do the thing that you need to do to build a ton of stuff in America.
2:01:03
>> I I think I think this is really really good.
2:01:05
I'd love to see a wave like this for bio next decade as well because right now our bio regulatory apparatus is completely effed up.
2:01:11
There's been some really strong hit pieces in the journal recently.
2:01:14
There's some huge messes there.
2:01:16
But it's the same sort of thing where if you could like take this energy, apply it to that infrastructure >> and and and you know, hopefully apply to some breakthroughs we're going to see there to own it like like but the fact that America can still do this, these companies can still do this, it's it's awesome and it's makes us very bullish. >> Yeah.
2:01:31
>> You had a pretty viral post yesterday responding to Nick Huber who was taking taking shots at the great uh citizens of Austin.
2:01:40
>> Going after Austin yeah. >> Yeah.
2:01:43
And and it turns out the photo was from like after school ended.
2:01:45
So like very clearly >> I see I could totally tell it was a joke photo from ago.
2:01:51
>> But but I wanted to ask something. You said, "Sorry, Nick.
2:01:53
Many but many of these people relaxing in the nice weather in our hometown are the spouses, mistresses, and children.
2:01:58
Where did Where did you Where did you get >> Where did you get number two? >> Number two there.
2:02:02
Where did that come from?
2:02:04
>> He was trying to his whole post was like, "These people are lazy.
2:02:06
I'm going to outsource them for $5 an hour jobs to the Philippines."
2:02:10
and and it was like an anti-American kind of like negative post.
2:02:15
And then so my clapback is actually our US employees are are so wealthy and so successful and have built things so much bigger than anything you're doing that they can afford to have their families relaxing and and mistresses.
2:02:29
The joke the joke of mistresses is they're so wealthy that maybe they have mistresses they're just relaxing in the sun while they're working because they're creating so much wealth.
2:02:35
We don't need to outsource to the world slop.
2:02:37
we can we can have great wealth in this country and great success and don't make fun of my city.
2:02:41
So it was it was obviously a joke but some people some people got really sensitive about that.
2:02:46
So >> your masterful poster >> yeah used his own tricks against it.
2:02:50
>> You did you did I was a strong ratio. I appreciate it.
2:02:54
>> I it was like this is so it's a Jewish new year and I was like stepping out of the the synagogue service and I was just like I probably should have stayed in synagogue and been on my phone and been on my phone.
2:03:05
It's dangerous when you give me like a little bit too much free time on a day.
2:03:08
It's dangerous what happens.
2:03:11
>> Well, never stop posting. Never log off, Joe. We enjoy your posting.
2:03:13
We've enjoyed your appearance. Thank you. >> Yeah.
2:03:17
I would actually like I think X would like it broadly if every time Nick Huber posted, you just quoted it and dumped on him because he's always leaving something open. Oh, yeah.
2:03:24
For >> I I wrote I hurt him cuz he like has these really angry replies and I was I I thought it was kind of a joke slapback, but I think he was like pretty offended.
2:03:34
So, if he's listening, I I didn't mean to be offensive.
2:03:35
I appreciate his hustle porn, even though I disagree with attacking America.
2:03:40
>> He he he knows what he's doing.
2:03:40
He's getting in the arena.
2:03:43
>> It's purely it's just >> he's rolling around in the mud.
2:03:44
He's going to get a little dirty. It's going to happen.
2:03:47
>> But thank you so much for taking the time. >> Come back on anytime.
2:03:49
Uh have fun hanging with your kids.
2:03:52
We'll talk to you soon, Joe.
2:03:53
Have a great rest of your day.
2:03:56
>> Um let me tell you about Julius. ai.
2:03:56
What analysis do you want to run?
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2:04:02
Loved by over two million users and trusted by individuals at Princeton. BCG Zappier.
2:04:08
I got the name right this time.
2:04:11
Uh did you see the car heart uh jacket that Turner Novak says if a VC shows up to the meeting wearing this, you should sign the term sheet immediately. Is this a call back?
2:04:22
Didn't Bane Capital do a Carheart collab for merch and they got some backlash from that stolen allegations?
2:04:30
Uh VC's keep it in the I mean there's nothing wrong with putting on a suit.
2:04:34
You saw Joe Lawndale just came on the show in a beautiful suit. Nothing wrong with suit.
2:04:38
The the uh what's the what's the Patagonia vest?
2:04:40
That's very iconic uh VC attire.
2:04:42
You throw on the This looks like Han Solo.
2:04:44
Like this this this jacket looks like something Han Solo would wear. Uh it looks good though.
2:04:48
Um anyway, in other news, uh YouTube restored some some suspended accounts.
2:04:56
Uh Ben Thompson has been breaking it down.
2:04:59
Uh he said that uh he gave kudos to the information for their headline which is YouTube to reallow accounts banned over COVID 19 integrity election violations.
2:05:10
Uh and Ben says this stands in marked contrast to other headlines that that characterize it as people who spread COVID misinformation.
2:05:20
Uh and he's quoting the Verge on that case.
2:05:22
Uh and he says uh it's true that there was some misinformation, but there's no question that not just leg uh that not just legitimate but in retrospect true content was censored.
2:05:30
Uh and it's be and its creators kicked off the platform.
2:05:35
Uh Google in in that letter to Jordan who is uh republican legislator um said that they placed the blame squarely on the Biden administration.
2:05:46
Google is saying the Biden administration twisted their arm.
2:05:51
And so this obviously goes back to the discussion about uh what happening with Jimmy Kimmel, what is the role of the government in free speech.
2:05:57
I think it's that the government shouldn't be involved at all actually and that uh no government should be involved in this stuff.
2:06:05
There's been debate over what level of involvement >> one person that didn't spread at least a little misinformation during that era, right?
2:06:12
Whether you're government, whether you're some skitsos conspiracy theorist, right?
2:06:16
Everybody was >> and that's what makes America great is that during the era we were we were suffering through the same pandemic that China was suffering through but we you know supposedly had free speech and so we could talk about it and throw out crazy ideas and pitch all sorts of different solutions and debate them in the in the great online marketplace of ideas.
2:06:37
And so um this seems like a positive a positive shift.
2:06:40
uh you know more more speech is probably better uh more free speech is probably better.
2:06:45
Um Ben says his concern on stratey is more narrow and that is how tech companies should have approached challenges like these over the past years and how he hopes they approach them in the future.
2:06:58
And so he says Google and YouTube were obviously not the only tech companies under pressure during the co era.
2:07:02
Meta CEO Mark Zuckerberg said the same thing a year ago.
2:07:06
Another was Spotify and Joe Rogan uh which Ben wrote about at the time.
2:07:10
Um, and he got a lot of angry responses to uh his take on how Spotify should have handled the Joe Rogan situation and the pressure on Joe Rogan during the COVID pandemic.
2:07:20
Uh, and Ben says, "But I think in the in the revelations of the intervening years, and I might add, a lot of those headlines I complained about above prove my point and most disturbingly we have just this month seen some of the most discouraging and devastating consequences of losing the cultural value of free speech."
2:07:36
Still, that wasn't the part of that update.
2:07:38
Rather, I was writing directly to EC and other tech CEOs declaring an adherence to free speech was not a get out of jail free card in terms of avoiding criticism for content hosted on your platform.
2:07:49
And in that light today, I don't have so much advice as I have an extor an exhortation.
2:07:54
Tech platforms need to lead the way in reestablishing the cultural mores around free speech and not just to get their get out of jail free card back.
2:08:06
Tech is dominant culturally in a way it wasn't when the cultural mores around free speech were established of course what's centuries ago.
2:08:13
Uh and the most generous interpretation of their actions over the last decade is that they were afraid to assert their power bowing to the wishes of the loudest voices in the media and in their own companies.
2:08:26
In fact, the best way to avoid partisanship is to be the natural arbiter of all the platforms say they want to be is to decline to take positions on all issues.
2:08:35
positions on all issues. but one the importance of free expression that is the key enabler of finding a path forward on all those other issues and is the foundation of a free society that in a nutshell has been strategy's approach to politics and it has served me well I
2:08:50
think it would scale just as well to the largest companies in the world he says take a page out of my book it's working for me >> page out of the first amendment >> page out of the first amendment potentially the first page uh the first page of the of the list of amendments >> did you see this post from uh Lachland Phillips. He said,
2:09:06
He said, >> "I did break it down.
2:09:08
This is this is Kugan thought.
2:09:10
My most toxic trait is a belief that instead of jailing Elizabeth Holmes, she should have been placed she should have we should have placed her under YC arrest under the watchful supervision of Gary Tan and forced her to rebuild and rebuild her device over and over again like Iron Man for the next 11 years or until she gets it working." >> I love it.
2:09:30
And this is what you wanted to see instead of the the kind of posting that she's doing.
2:09:34
It'd be great if she was like, "Guys, I I'm I've I'm I'm figuring out kind of what went wrong." Yes.
2:09:43
>> Before here's a here's a more narrow solution that we could kind of create. >> Yes.
2:09:48
>> Uh >> I mean there there it doesn't even need to be I mean I understand that from prison you are not going to be able to build a a a device that uh tests your blood.
2:09:58
Like she's just not going to have the equipment for that.
2:09:59
Um, she could be reading papers.
2:10:01
She could be she could be reading the analysis and giving thoughts that over time could look very good.
2:10:08
Like you see it today with the news of uh Donald Trump and RFK are talking about Tylenol that's being hotly debated.
2:10:14
Uh the administration is taking one position.
2:10:17
Me different media figures and health experts are taking different positions.
2:10:20
I'm sure Andrew Huberman will commented on uh comment on it at some point, right?
2:10:25
But like she has the opportunity to to read all the research, comment on it, and then we will see in a year or two or maybe more how that how those predictions panned out.
2:10:33
And that's what we've been seeing with Martin Skrey where he has made a bunch of bets on he's very bearish on quantum computing right now. We'll see what happens.
2:10:41
We just get to wait and we will remember, wow, he was correct about his bare call on quantum computing.
2:10:48
And so that updates us to think that he is a he is an interesting thinker on the valuation of new technology companies, right?
2:10:55
Um whereas right now she's kind of just like leaning into this character of oh wow, she's posting from prison.
2:11:02
I think that novelty will wear off. >> Fun.
2:11:06
>> I think that novelty will wear off and we'll want to see something more meaningful.
2:11:09
>> I mean it's definitely broadly changed people's like general feelings towards her. >> For sure. >> So >> for sure.
2:11:14
Anyway, fall generative media platform for developers.
2:11:17
The world's best generative image, video, and audio models all in one place.
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2:11:24
Um, >> head over to tbpn.
2:11:27
com/sounds which is brought to you by fall >> printer is coming.
2:11:34
Emit in is investing writes from Bessant.
2:11:37
Uh, we are going into an easing cycle and we'll see a massive decrease in mortgage rates.
2:11:41
Powell should have signaled 100 to 150 basis points of cuts, not just 75 points.
2:11:46
We'll begin Fed candidate interviews next week.
2:11:51
Looking for someone with an open mind.
2:11:52
>> Looking for someone with an open mind.
2:11:54
>> Open mind to low interest >> to what we want >> potentially. We'll see.
2:11:57
Um I would I would love to see mortgage rates come down.
2:12:01
I would love to see the cost of housing come down.
2:12:02
I'm still feel like the opportunity is probably in just building more housing, building a lot more.
2:12:08
But >> love when love when the rates are low, hate when they're high. >> It certainly helps.
2:12:11
But of course, uh that that tenure isn't really behaving. >> Yeah.
2:12:16
>> It's got to you got to whip it into shape.
2:12:17
Uh >> Jim Jim Jim Kramer with the that tenure better start behaving. >> That's great.
2:12:23
Uh there is a fantastic profile on Jim Kramer in the news today.
2:12:30
We should uh take a gander through this because it's a fun one.
2:12:32
Uh this was brought to my attention from uh let me find it from Joe Weisenthal.
2:12:38
this great great profile in Business Insider of a guy who was on the OddLots podcast who wakes up at insane hours every day to co to cover the markets. Did you see this?
2:12:49
>> So Jim Kramer is a busy man.
2:12:49
The Mad Money host known for his emphatic delivery and bold stock calls on the air gave a rundown of his hectic schedule when speaking on Bloomberg OddLots podcast last Monday.
2:12:59
Here were the highlights of his routine.
2:13:00
And get ready to be mogged, Jordy. He wakes up.
2:13:03
He kicks off his day at 3:15 a. m. 3:15 a. m.
2:13:11
Do you know what time he goes to bed? >> 6 >> 11 p. m. >> What?
2:13:15
>> He gets 4 hours of sleep a night.
2:13:18
>> Just doesn't need to sleep. Does he nap?
2:13:21
>> There's no competing with this guy. This is insane.
2:13:23
I I I like We try so hard.
2:13:23
I feel like we do a really good job, but we're putting up eight hours of sleep a night.
2:13:31
How did you sleep last night? Go to eightleep. com.
2:13:32
Uh, get a T, get a Pod Five Ultra.
2:13:35
Um, >> 30 night risk free trial. >> I wish that I could.
2:13:39
>> I got a 96 last night, but I slept for seven hours and 41 minutes.
2:13:41
That's about four hours more than Jim Kramer slept. >> I got a 90. 7 hours 23 minutes. >> Oo, I win again. >> You win again.
2:13:48
You uh Yeah, I just guess I got to go to bed.
2:13:53
>> So Kramer wakes up at at 3:15 a. m.
2:13:53
The first 45 minutes of his day are on quote a tight schedule due to his 400 a. m. workout.
2:14:01
We're getting into the gym at 6:30 at best.
2:14:03
He's getting in two and a half hours ahead of us and he's on East Coast time.
2:14:08
This man lives in the future compared to us. It's remarkable.
2:14:10
Before the hour, he brushes up on the market by perusing the Financial Times, Bloomberg, the New York Times, the Wall Street Journal, and CNBC. I get two of those done. He's doing six.
2:14:18
Okay, he's ahead of me there.
2:14:21
Uh Kramer also said he sifts through stock research in his inbox, combing through about 700 emails a day. That's remarkable.
2:14:29
>> Uh I read everything I think is relevant.
2:14:30
I'm looking for something to say.
2:14:32
I have a memo that comes out, 10 things I'm looking at.
2:14:33
Uh I do one thing I'm looking at. He does 10.
2:14:36
Uh I try and just do the current thing and he's got 10 of them.
2:14:40
Uh he's an absolutely an absolute beast.
2:14:43
Kramer said referring to his weekly weekday morning newsletter for CNBC's investing club.
2:14:47
He said, "So that's my overlord."
2:14:49
He referred to the newsletter as I'm starting to feel that the newsletter is my overlord. I I I respect it. Go subscribe tbp. com.
2:14:55
Throw your email in there.
2:14:58
you will get the uh TBPN run of show every week, the current thing, my newsletter.
2:15:02
Um then uh Kramer appears on CNBC's Squawk on the Street, begins writing Mad Money, his flagship show on the network in the mid morning.
2:15:12
Throughout the day, Kramer spends a huge amount of time reading up on company news and earnings reports.
2:15:15
He finishes taping Mad Money around a quarter to 6.
2:15:18
We saw him there doing that.
2:15:19
>> Zach Meyer in the chat says, "This guy does not go to the gym at 4 a. m. Look at him."
2:15:23
You think he's I I think it's more like he's not working out for physique, right?
2:15:29
He's he's I mean, we we got to hang a couple weeks ago.
2:15:32
We got to hang with Kramer for about 20 minutes. It's the end of the day. He had a ton of energy.
2:15:38
He was incredibly locked.
2:15:38
Did have a ton of energy.
2:15:39
This was at like probably >> Yeah, he's probably doing something low impact, but I like to imagine him benching three plates, squatting five, throwing up some some 200lb hang cleans, some cleaner PRs every day, getting getting aerobic, getting athletic with it.
2:15:56
>> Throwing on a stringer.
2:15:58
>> He'll Yes, absolutely.
2:15:58
Uh we Yeah, we get get a get a Gigachad Mass Kramer photo up ASAP. I need to see that.
2:16:05
Uh, he finishes taping M Mad Money around a quarter to 6 and comes home.
2:16:09
He'll go out to dinner around 10 p. m.
2:16:10
and then say good night to his wife before tucking in.
2:16:13
Kramer acknowledged that the intensity of his schedule puts a strain on his marriage. I have a great marriage.
2:16:17
I put that out first because I wreck it every day. I go to bed at 11:00.
2:16:22
She goes to bed at like a normal time.
2:16:23
So, that's where I when I really wreck the marriage. That's not the plan.
2:16:26
I didn't set out to do that.
2:16:26
He said Kramer's routine doesn't seem to have much changed in 2015.
2:16:30
He told Business Insider that he followed a similar schedule. He's been saying this.
2:16:33
He's been waking up at 3:00 am tweeting about stocks and puppies in the morning, making a pit stop at the headquarters of the street which he co-founded in 1996.
2:16:42
What an absolute run for Jim Kramer.
2:16:45
Anyway, Turbo Puffer search every bite serverless vector in full text search built from first principles on object storage.
2:16:51
Fast 10x cheaper and extremely scalable.
2:16:54
>> This little turbo puffer is used by notion linear cursor and many more.
2:17:00
>> I want to go through VCs to AI startups.
2:17:03
Please take our money in the in Bloomberg. This is from Kate Clark.
2:17:06
Uh she says, "Private jets, box seats, and big checks.
2:17:12
Investors are doing whatever it takes to get into top AI deals."
2:17:14
Uh Jordy, would you mind reading the first few paragraphs of this article?
2:17:22
>> Catch up to this article. >> It's page 90.
2:17:23
Raising venture capital money has been a breeze for Decagon AI.
2:17:28
We're all over the place with the the customer service startups.
2:17:31
It's a very hot industry. Decagon's doing well.
2:17:36
Finn, our partner, is doing well.
2:17:36
And Brett Taylor's doing well, too.
2:17:37
Uh DecaGon's two years old.
2:17:39
Uh they're developing artificial intelligence tools for customer service.
2:17:43
All four of DecaGon's funding rounds totaling more than $230 million were preempted, meaning firms like Andrea and Horowitz offered to invest before the company started fundraising.
2:17:53
Now, just three months after a round that valued at 1.
2:17:56
5 billion, we had the founders on when they announced that round, DecaGon is fielding unsolicited offers at valuations as high as 5.
2:18:04
>> Give it up for unsolicited offers.
2:18:06
They're some of the best offers >> for DecaGon and a few other AI startups.
2:18:11
Uh, the fundraising script has flipped.
2:18:13
Instead of pitching venture capitalists up and down Sand Hill Road, VCs are pitching them, hoovering them with gifts and favors in hopes of leading their next round.
2:18:22
Uh, can you catch us up on the rest of the article and then I want to go into some ideas because I think the VCs aren't thinking big enough. >> Big enough.
2:18:29
We'll get you back in a second.
2:18:31
So, Jesse Jang, the 28-year-old co-founder and chief executive officer of Decagon says investors hoping to back him.
2:18:37
I've offered him everything from tickets to Golden Gate Warriors games to an autographed poster of MMA legend Kabib Nur Magdov.
2:18:44
John would not know who Kabib is, but I'm sure many of you do.
2:18:51
One investor even folded origami cranes into a mosaic of DecaGon's logo and handd delivered it to to the company's San Francisco office with a term sheet hidden inside. Decagon took the deal.
2:19:04
So that's that's a good one that works.
2:19:06
Um investors are emailing term sheets.
2:19:08
They're giving verbal offers.
2:19:10
They're inviting founders to sports games.
2:19:11
are inviting founders to race Ferraris and they're inviting them on private jets, says Bennett Seagull, a co-founder of investment firm AAR and an early investor in Decagon.
2:19:20
What you tend to see is the best companies are getting preempted every round and the time between rounds is shrinking.
2:19:26
The lavish VC overtures are part of a larger Silicon Valley frenzy for AI driven by startups astonishing revenue growth and investors belief that these companies can dethrone tech giants.
2:19:37
US startups have raised around 200 billion this year.
2:19:41
year. so far according to pitchbook data but 41% of that went to just 10 companies highlighting VC's relentless focus on a small group of AI frontr runners like openai and anthropic last year the share of funding that went to the top 10 companies was less than 10% a few smaller AI startups have also emerged as investor favorites drawing
2:20:00
outsized attention and capital among the rising group of hot companies legal startup Harvey customer service firm Sierra and coding company Cognition all of which have drawn big offers from VC firms Any sphere, the maker of AI coding tool Cursor, has become a central example of the rush to fund newer AI companies. Uh, it's kind of funny that
2:20:18
Uh, it's kind of funny that um, >> I heard you talking trash, by the way. I do know who Kabib is. He's an athlete. >> There you go. Nailed it.
2:20:27
>> You know, >> what else is there to know?
2:20:29
>> What else is there to know?
2:20:29
Uh, he he he punches and he >> he kicks. >> Kicks.
2:20:34
>> Does he Does he do kicks? >> He does kicks.
2:20:36
>> He does kicks as well. >> He does kicks.
2:20:37
>> He's into kicking >> and wrestles.
2:20:38
So >> um isn't it any this trend of companies having like one name and then the product name being called something else?
2:20:48
It's >> anyphere and cursor wind surf had the same situation. Right. >> Yeah.
2:20:55
>> Um >> so the there's this story about decagon.
2:20:58
One investor even folded origami cranes into a mosaic of decagon's logo.
2:21:00
I saw a picture of this and I was confused because a decagon is just a 10-sided shape.
2:21:08
And so it's actually like extremely easy to fold something into a decagon, but I guess they did cranes into the shape of a decagon or something because like imagine if you're like, "Oh, I really want to invest in square.
2:21:20
I'm going to fold you a square.
2:21:20
I'm going to take a piece of paper.
2:21:22
I'm going to turn the term sheet into something square."
2:21:24
It's like uh I I want to see I want to see true origami mastery from a VC if you're going to try and preempt around. >> Yeah. >> Yeah. Absolutely.
2:21:34
I mean I think I think investors should be thinking of it as as uh what is the right kind of effectively bribe at each stage. Yes. Right. So >> what's the budget?
2:21:45
What's the what's the math that you should be doing?
2:21:46
How much should you put towards the bribe? Towards the tip. It's a tip. It's a tip. There's no tax on tip. >> It's a tip. U Yeah. I don't know.
2:21:53
You know, it depends on the round, but if it's really competitive, maybe thinking about 10 putting >> putting 10% of the check size and then paying out of your own management fees for some type of experience, right? >> Yeah.
2:22:07
I mean, if you're just paying 10% over, if if there's a $300 million round and it's between you and another firm and you just take just 10% over, that's not going to hurt your returns.
2:22:17
Like, if you win the round, it's going to be, you know, 10x.
2:22:21
And so 10x on 300 as opposed to 330.
2:22:26
>> Just take just making insane assumptions. >> Just take the 30 mil. >> All math out.
2:22:30
>> Buy a McLaren F1 and be like, I see you as the next Elon.
2:22:33
I see you as the next Sam Alman. They drove McLaren F1s. >> You should drive one.
2:22:39
>> You you should have this car. It's yours.
2:22:40
>> Or keep or keep a a you know a fleet of supercars at Sand Hill and and say you can have this from between the A and the B. Right.
2:22:49
So it's uh and and you could have an adverse effect of founders being like I like this P1.
2:22:54
I'm going to I I don't really want to raise my beat join dailying it.
2:22:59
But in general I think it should work out.
2:23:01
So I think it should be like writing a 250k flyer.
2:23:02
Why not get a founder >> uh a week a long weekend at an Aman property of their choice right?
2:23:08
You know something something straightforward. just just a weekend.
2:23:12
I feel like couple weeks a couple weeks like at least you could >> I know but you're getting you're getting well beyond that uh you know that 10% mark.
2:23:22
>> Two days in Aman is two weeks out of four seasons. >> Um yeah.
2:23:26
So I I think uh you you kind of going going up the ladder. >> Yeah. What's next?
2:23:30
If I'm trying to win a $20 million series A, what should I budget for? The tip. For the bribe. >> For the tip. Tip.
2:23:36
Tip sounds better than bribe. >> Okay. >> Yeah. Tip. We're sticking with tip. Yeah, it is.
2:23:41
You know, we are coming up into VC tipping season, so founders got to be thinking about what kind of tip makes sense for each person on your cap table.
2:23:48
We've we've talked about this before, but um >> but yeah, how can you take it up how can you take it up a notch?
2:23:53
You know, racing Ferraris, private private, but I I I think these like one-time offerings are super weak, you know?
2:24:01
It's like >> uh race Ferraris for a day.
2:24:03
Yeah, that's not that interesting.
2:24:05
Founders doing 996 are like I don't want to go to your racetrack, right?
2:24:09
So, I think um >> buy the racetrack.
2:24:14
I think the thermal club was up for sale >> or a lot of or or or saying uh you can use my jet one time. One time one time.
2:24:23
It should be it should be >> here's the full jet.
2:24:25
>> The jets should live with you till the IPO.
2:24:28
>> Tossing the keys >> until the IPO. >> Yeah.
2:24:30
Then then you get your own jet. >> Yeah. Yeah.
2:24:32
until you you're you're in the position to be able to get your own your own.
2:24:36
Uh >> Tyler, what would get you to sign a a term sheet?
2:24:39
What would stick out to you?
2:24:41
Uh if a VC came to you and said, "I got to do this deal." >> Look at this.
2:24:45
>> I think look at this picture.
2:24:47
>> I like that you you're David Center fan.
2:24:49
You have a frame for photo of him.
2:24:50
>> I think something compatible like if the founder is doing 996 Yeah. Right.
2:24:54
There's this thing, you know, the current vibe is stakes, right?
2:24:55
So maybe you buy a, you know, cattle farm >> with very high quality cows like, you know, Zuck's Island.
2:25:02
>> Zuck has that on his island. >> Yeah, >> for sure.
2:25:06
>> Uh, Gold Rock said, "I I had a VC try to take me hot air ballooning." That's a wild one.
2:25:11
I don't >> Are you Would you go on a hot air balloon?
2:25:14
>> I would absolutely go on a hot air balloon. >> Okay.
2:25:17
>> It's extremely aristocratic.
2:25:19
>> Yeah, >> it's fantastic.
2:25:20
I saw a video of a hot air balloon crashing from from somebody that that took the video inside the hot air balloon. It wasn't scared. Wasn't super appealing.
2:25:29
Oh, we got Tyler on the big screen now.
2:25:31
And we got Senra here on the big screen. >> That's good. >> There we go.
2:25:35
>> I feel like that's a skill issue. >> Skill issue.
2:25:36
Just >> just hit chat GPT.
2:25:37
How do I fly a hot air balloon? Get up to speed. Summarize that for me. Don't make mistakes.
2:25:41
And then we got a little inception going here. >> I like that. That's a good start. >> Uh anyway, profound.
2:25:47
Get your brand mentioned in chat GPT.
2:25:49
reach millions of consumers who are using AI to discover new products and brands.
2:25:53
Maybe that's what the VC firm should do.
2:25:55
Get on profound when people when founders type in who should I raise money from?
2:26:00
I'm building this show up and check.
2:26:04
>> I think I think founders should just ask u I don't want you to just join the board.
2:26:07
I want you to actually become a a BDR at my company for the next two years. >> Yeah.
2:26:13
I mean, you're you're joking, but like that's sort of I've seen that happen with Elon Companies where to win allocation, you're going not BDR, but recruiting. >> Yeah.
2:26:23
>> So, come in and and and import your entire network.
2:26:26
Everyone you know who's an engineer who could work at this company, come and work basically full-time for like a month to like really do everything you possibly can because there's always you write the check and then you're like they hit you with like, oh, like do you know any software?
2:26:42
It's very different from being like I'm doing three full-time weeks just actually racking my network, actually making calls, catching up with everyone who'd be relevant. >> Two most convenient. >> No, no, no.
2:26:52
Going really deep into the actual um in in in in into the rolodex.
2:26:59
>> Does the Hindenburg count as a hot air balloon? I don't think so. It was a durable.
2:27:03
It was uh it was a blimp.
2:27:03
Um but uh anyway, numeral sales tax on autopilot.
2:27:10
Spend less than five minutes per month on sales tax compliance. >> Let nal sales tax. com.
2:27:14
Google just killed dingboard. You saw this?
2:27:18
Are you familiar with dingboard? Yaken's project. >> They just killed it. What do you mean? >> Have you seen this?
2:27:22
You >> of course I know dingboard.
2:27:24
>> Did you Were you a subscriber? >> I was very early on.
2:27:25
He gave me I was like very I I I DM'd him for some reason and he gave me a code. >> I loved the product.
2:27:31
I thought the product was amazing.
2:27:32
I it wasn't it didn't really work that well on mobile.
2:27:36
Um but it was it was super cool.
2:27:36
You could like go in and with AI remove backgrounds, merge images, blend things together.
2:27:42
It was a fantastic product.
2:27:42
He goes to work for >> kill it.
2:27:46
>> Well, because Google Labs just launched Mix Board, an experimental AI powered concepting board designed to help you explore, visualize, and refine your ideas powered by our latest image generation model. Of course, Nano Banana.
2:27:57
And with Nano Banana and uh you know it basically it's not that they killed Dingboard.
2:28:04
It's just that they launched a product that is clearly inspired or or lives in the same kind of work stream as Dingboard where you can remix images, bring things in. Very very cool product.
2:28:17
I would love to see this on an app for sure.
2:28:19
Um, I've always ma when I'm making images and memes on my phone, I'm always going back and forth between like Photoshop Express and Image Flip and a few different sites.
2:28:29
There's not a lot of stuff.
2:28:31
I I This is a great product and I hope someone can take it across the finish line.
2:28:36
Obviously, Yaxine had to go work at X and now he's working on robots and stuff, but >> what do you think of Stillers? >> Stillers >> Soda.
2:28:44
Ben Stiller soda company. >> I have no idea.
2:28:47
Does he have that type of audience that's like ready to rip soda >> from Walmart?
2:28:54
>> Yeah, it's it's interesting.
2:28:54
Like I I guess like we were talking to John Shahiti about this like Ben Stiller is the type of person that could probably call the CEO of Walmart and get a meeting, right? Like he's so famous.
2:29:02
If if if if you're a if you're a CEO of a big retail chain and you hear Ben Stiller's on the line, you're going to take that call, right?
2:29:13
So maybe it advances your, you know, distribution quickly.
2:29:18
Still is also just a great name.
2:29:20
Like I do, that's the name is great and and when I saw it, I was like, "Oh, that's a cool name. I'll take a Stillers. That's a great name.
2:29:28
>> Is that related to Ben Stiller?"
2:29:28
And then I found out it was uh so I could see it working.
2:29:32
I would love to do a taste test.
2:29:34
We'll have to actually see is the product good because if he has great product sense kind of doesn't m the distribution and the celebrity will take care of itself.
2:29:41
is a little millennial coded.
2:29:42
It says made by 100% real human celebrity people. >> Okay.
2:29:48
Yeah, that's a little >> And they and and the the copy on it says no fake stuff.
2:29:54
>> And and crowded category. >> Yeah.
2:29:58
>> Just they they they're competing with with Lollipop and what's the other one?
2:30:04
There's been a huge there's been a huge lineage of trying to find uh make a product that's free of free of sugar, free of fat.
2:30:13
>> I would say I would have been incredibly bullish on this company if it launched in 2019. Yep.
2:30:18
>> But launching into a category that Pepsi is already going to buy their want.
2:30:20
I'm sure Coke will eventually >> I mean I believe Pepsi already has Poppy which was direct Pep.
2:30:29
>> Wait, there's Poppy but then there's >> Pepsi bought Poppy.
2:30:31
You could imagine Coke buying lollipop. >> Yeah.
2:30:36
>> And then that's then it's kind of over.
2:30:38
>> But then there's a there's another there's another company that's a seltzer. That's uh it's Bubbly. Bubbly. Do you know Bubbly? Bubbly sparkling water. Who owns Bubbly? >> Yeah.
2:30:49
Well, we should get Ben on the show to talk about Stillers.
2:30:51
And we should get uh Tyler Bubbly.
2:30:53
We're gonna We're gonna >> Yeah.
2:30:58
Bubbly was incubated incubated by PepsiCo to compete with like the Spindriffs of the world.
2:31:03
And remember the big boom in in seltzers.
2:31:05
Uh there were a whole bunch and a bunch of other products that were really popular in uh in offices in you know 2017 corporate offices.
2:31:17
People would be drinking um Lacroy all day long.
2:31:19
Uh Bubbly was like their answer to that.
2:31:22
I don't know how it actually panned out but it's kind of interesting.
2:31:25
But in much more interesting news, Open AI SAP and Microsoft are launching Open AI for Germany, a partnership to bring Frontier AI to Germans, Germany's public sector through a sovereign certified cloud environment.
2:31:39
We haven't rung the gong enough on this show.
2:31:40
Let's ring it for uh open AI for Germany. >> There we go.
2:31:44
And we got to hit it for uh Claude getting into the Microsoft ecosystem. That also happened. We love it.
2:31:54
Uh well, without further ado, I think we have our next guest, Riley Walls, in the reream waiting room. Let's bring him in.
2:32:03
He has been being a rascal the last 48 hours.
2:32:07
Uh Riley, welcome to the show. >> How you doing?
2:32:13
>> Thank you for having me.
2:32:14
>> The most viral man on X, the the current thing. >> Yeah.
2:32:18
Take us through the current thing, the current project. Uh what did you build? What inspired it?
2:32:22
What's the reception been?
2:32:24
Is are those GPUs on fire? Are the servers on fire? Is it staying up? Walk me through it all.
2:32:29
>> Yeah, I always got a project kind of going on.
2:32:31
Um, yesterday's project was I I figured out you could scrape the parking ticket system in San Francisco to reveal more or less the real-time locations of of parking officers as they wrote tickets. >> Okay.
2:32:45
>> Um, so I made a website called Find My Parking Cops.
2:32:47
Looks very similar to Apple's Find My Friends.
2:32:49
Um, and yeah, you can see where where the cops were as they as they travel around SF.
2:32:57
>> Take me a level deeper on >> What inspired this?
2:33:00
>> Did you get a lot of tickets?
2:33:00
Is that what inspired this?
2:33:03
>> I actually don't even have a car.
2:33:03
My roommates, uh, a lot of my friends have cars and yeah, I mean, you hear a lot about tickets.
2:33:09
It's pretty notorious in the city. So, >> yeah. Uh, yeah.
2:33:11
Take me through, uh, one layer deeper of the technical side.
2:33:13
Did uh uh is this just a function of uh the SF parking ticket office integrating with some sort of you know it or ERP system that basically as soon as the tickets written it gets loaded into a database and then is that is there a public API?
2:33:31
Is this stuff that you can just look up on the on like an actual website or are you finding like an entirely private API?
2:33:38
>> Yeah, it's all it's all public.
2:33:38
The magic is um right when they write the ticket it goes up online and you know you have to enter the ID number to be able to see the ticket.
2:33:46
Like there's a website you can you can pay your ticket and when you pay you can see a copy of the ticket.
2:33:51
So um I figured out that the ID numbers for all the tickets were predictable meaning that um like there's a there's a pattern to it.
2:33:57
So I could um I knew kind of the pattern and I could see okay like this ticket to simplified a lot like if like ticket number like 83 was just written I know 84 is going to be next.
2:34:07
So, I just keep checking for the next one.
2:34:09
Um, it's a little a little more technical than that, but like, you know, it's it's pretty magical when predictable IDs are a thing.
2:34:14
Like, there's so many cool ideas you can you can scrape knowing that.
2:34:17
So, >> talk to me about your actual workflow.
2:34:22
Is there are you using vibe coding tools?
2:34:24
Is >> Well, before that, what what's the current state of things?
2:34:26
current state of things? SF obviously uh you could potentially really you know if enough people in SF started using this it would be could >> I would hope that the mayor would write you a letter of of recommendation for this like you should win a medal for this >> yeah you should this is the highest calling yeah you should get the key to
2:34:45
the city for this but what's the actual response from SF been if anything >> yeah so I I do websites like these that are provocative a lot and I think a lot about framing it and like how I want to present it to people so I thought this would be maybe a little like you know mildly viral among people in SF, but it actually went pretty viral like around the world yesterday. Uh within 4 hours,
2:35:00
Uh within 4 hours, the the SF government mobilized and they changed their site to prevent me from getting the data.
2:35:07
Like only four hours it took for them to prevent me from uh make the site useless.
2:35:11
So yeah, the site is not up anymore because they changed the way that the data >> those four sweet hours though were >> everyone was free of free of parking tickets.
2:35:22
It actually is if if if if it have gone less viral and not and people hadn't, you know, if they hadn't noticed so quickly, I can imagine this being highly somebody's pulling up, they want to grab a coffee, you know, they're look, they just check the map, they can run in and out.
2:35:37
It's not a not a not a I I can see it actually being pretty valuable. >> Yeah.
2:35:42
Walk me through some of like the how you like to build these projects, how you like to host them, um what what problems you typically run through.
2:35:51
would love to know just a little bit about your stack these days.
2:35:54
>> Yeah, I mean use AI a lot.
2:35:54
It makes things so much faster.
2:35:56
I have like a gazillion ideas.
2:35:58
These are all sticky notes for different like data ideas I want to make.
2:36:01
So just kind of every weekend I'll try to knock one off >> um in my free time.
2:36:04
Um I you guys talked about you saw the other one I made. Panama playlists. >> Oh yeah. >> Oh you did that. >> We're on that. You scraped my data.
2:36:12
I'm glad glad you I was wondering like how did I make the cut on this?
2:36:16
Like these are some big people on on there. Uh, yeah.
2:36:21
What was the secret to that? Because it only >> Yeah.
2:36:23
Was there any Was there any strange fallout?
2:36:24
I mean, it was hilarious to read into people's music tastes.
2:36:27
I don't you you wouldn't have noticed this, but my that the playlist that I had public that you featured was like seven songs I found that had like obscure references to venture capital.
2:36:40
So, when I saw it, I was like, I don't listen to any of When did I make this playlist?
2:36:44
I don't listen to any of these.
2:36:45
In like 2021, I just started collecting or whatever. >> Yeah. I don't know.
2:36:49
It was just kind of tried trying to highlight like how much data has out there on Spotify and like people just forget about it and yeah, sorry you guys were part of it.
2:36:56
But >> no, we thought I thought it was hilarious.
2:37:00
>> I think it was it it was pretty amusing.
2:37:01
I think a lot of people um had a kick looking at it.
2:37:03
So >> yeah, what was the what was the reaction from either the people that were in it or Spotify directly?
2:37:07
Has there been a change to the API or because we saw this even during the last election like the Venmo public records, people forget about this stuff all the time.
2:37:16
There's kind of a question about how tech platforms deal with like default privacy because there was an era when everything was public and then people started closing things down, becoming a little bit more private, but it's a it's a it's an interesting like user design problem for the big companies to shift. >> Yeah. Yeah.
2:37:32
Yeah, in case your audience didn't see it, I I scraped like the public playlist listening data of of notable figures on Spotify and like there like you guys were on it, like Sam Alton was on it, bunch of politicians like Mike Johnson and JD Vance and like so many people just have stuff open on there.
2:37:47
Um they haven't changed stuff yet.
2:37:50
I feel like Spotify probably will change like the default behavior of playlist because right now they're public by default which is kind of crazy. Yeah.
2:37:56
Um, but yeah, I mean it was a lot of people took their playlist down.
2:38:01
Um, kind of was a Yeah, interesting to see like kind of a lot of people embrace like Palmer Lucky.
2:38:05
He was like, "Yeah, these are my songs and I love them." >> Great.
2:38:11
>> So, did you have to guess some sort of code or was did you just literally just search my profile and then it was there?
2:38:18
>> Yeah, I mean for you guys a lot of it was just like real names.
2:38:19
I just searched your game and then I found a profile with your picture like probably a sim because then I could see like you guys followed each other or something. Probably >> done.
2:38:29
>> Uh what's >> walk us through some of some of the other uh stuff you've done recently?
2:38:31
Uh and then I want to talk about uh >> yeah specifically what's the most underrated project or most underappreciated project you've worked on where you love it.
2:38:42
It's one of your dearest children but you feel like it hasn't gotten enough love.
2:38:50
H uh one like interesting one was a few months ago I I this was also very out there but you know you guys know looks maxing um I I made a site called looks mapping where I I scraped the Google maps reviews of restaurants in New York
2:39:07
SF and LA and then I ran the profile pictures of the reviewers >> through a very jank attractiveness model and then I made an aggregate um map of like all these restaurants like okay This restaurant is usually composed of like sixes or whatever out of 10. >> Very awful the idea and premise, but it
2:39:23
>> Very awful the idea and premise, but it was kind of funny.
2:39:27
>> That would make anybody mad.
2:39:29
>> Yeah, you can you can you can glean a lot of just information cuz I al also had an age map.
2:39:32
You could, you know, get their age from the pro picture roughly and and gender too.
2:39:36
So you can see which restaurants had like the most men or women in in in a city like I don't know.
2:39:42
>> What kind of pattern like h how much did it track with just the general hype around restaurants?
2:39:47
like what what did you notice?
2:39:50
>> Yeah, I mean like the oldest restaurant in SF is at a country club.
2:39:52
Um like the most um like male restaurant is a gay bar.
2:39:58
The most female one's like a brunch spot.
2:40:00
Like it all kind of fits when you look at it. >> Predictable.
2:40:03
>> That feels like a product that maybe it needs a little polish, but could just be something that would actually add value to the Google Maps experience.
2:40:09
Has have big tech companies reached out to you and said, "Hey, come work for us?" >> Not for that.
2:40:16
There's been a couple like smaller maps that are like, "Oh, you should maybe add this." And I think they should.
2:40:20
Yeah, I think this would be cool to I feel like it's too politically risky for Google, but like definitely a smaller setup could do it. It'd be useful. >> Yeah.
2:40:27
I feel like even if you dialed back uh some of the framing on what you're building, like there's there's there's product insight there and there's like novel features that would surprise and delight.
2:40:35
And I feel like that's kind of um what what what a lot of these projects like put on display.
2:40:42
Um >> what were you doing?
2:40:42
What were you doing before all these experiments? >> Yeah. Does this pay the bills?
2:40:46
Do do you have a full-time job? Like >> it does not. Yeah.
2:40:49
I I I have a full-time job doing like data stuff that's more commercially viable.
2:40:52
Um I also I mean like you guys talked to Gabe Wely of Mischief. >> Yeah. Yeah.
2:40:59
>> I was an intern there uh Mafia >> which was like very I mean you guys can kind of see like all this is very inspirational.
2:41:06
Very inspired by mischief. >> Yeah. Yeah.
2:41:08
The chat is literally saying he's like mischief for tech projects. Lol.
2:41:12
Like people have clocked it for sure.
2:41:14
>> I firsthand I got to see up close how they they operate.
2:41:16
They're like incredible people. Yeah.
2:41:20
>> So you were at Mischief and you said I need to pursue data science.
2:41:26
>> Yeah, that was my calling.
2:41:26
I think data is like really cool and it's cool that you can combine it with like Mischief elements to make like weird things like this parking.
2:41:31
Butter, let's let's uh I don't I don't It feels like you could talk through some ideas you have without giving away too much alpha just because a lot of I don't know if I I doubt people would would steal your ideas since a lot of them are like don't make uh are you're not doing this to make money but uh you want to talk through any work workshop any with us? >> Yeah, let me see.
2:41:50
Uh >> oh yeah, what you got on the board? All right.
2:41:53
So, one one like terrible idea that I'll probably never build because it's awful is um there's a um OpenAI has like a um API endpoint for like how um like a moderation endpoint for how bad a piece of text is.
2:42:06
It will like return back like a string of like you know is this some harassment or is this like racism or whatever. I don't know. >> Yeah.
2:42:14
The horrible idea is like somebody should make a leaderboard um where you like have to type in a string of text and you want to like actually hit every single one of these categories.
2:42:25
>> Say the most offensive >> as possible.
2:42:28
>> You have to create the most offensive string of text in history >> in as few characters as possible as many people as possible. Yeah. >> Horrible. But >> horrible.
2:42:37
But certainly I I think >> you might not need to disclose what was actually said.
2:42:42
You could have it be anonymous, but yeah, you it would certainly spark creativity.
2:42:45
I mean, Run was talking about this, how there are certain strings of text that just go viral every time they're posted, no matter when they're posted, no matter who posts them.
2:42:54
Um, these little insights.
2:42:56
We did this project, Banger Archive, where we took the best posts by certain people, just screenshotted them, and just said banger, and they would get another 10,000 likes every time. >> Yeah.
2:43:07
We had posts that would get 50, you know, an order of magnitude more likes than the original post.
2:43:11
And it was like a naval post about like you should work like a lion like you know take rest and then work really hard and it's just like these universal truths that like just continue to deliver value. >> What else? What else you got? What else you got?
2:43:25
>> What else is on the board?
2:43:26
>> Give us some other stuff.
2:43:27
>> Um >> because I feel like 4chan would like oneshot your leaderboard.
2:43:32
They'd figure out there's like there's four words.
2:43:34
You put these together and make every person on earth mad. >> Yeah.
2:43:39
No, it' be it'd be terrible.
2:43:39
Um, one idea, this is something that has to do with parking tickets here.
2:43:44
Um, I also found out that like vandalism citations have like a similar setup in the city.
2:43:51
So, I I was able to scrape like half a million pictures of of graffiti that cops took. >> Oh, interesting.
2:43:57
>> So, I think it'd be cool to make a website that shows graffiti art through the lens of a of a cop in San Francisco.
2:44:04
They took by they took on their on their phone themselves. >> Yeah.
2:44:07
>> Yeah. It feels like a lot of your projects touch on uh touch on like public works projects public like like cities like data in cities and I'm wondering if you have a view on like uh should cities be more open to the hacker culture actually embrace some of this
2:44:27
stuff like some of the stuff that you're building is like very close to just like a tool that would make life in a particular city easier and yet cities are notorious for long lines of the DMV and and not being the most techforward organizations or entities. Uh how do you
2:44:42
Uh how do you think about um actually like how cities deliver tech services?
2:44:51
>> Yeah, I think there's a lot there like um >> I think the the asset government actually has a pretty good handle on this.
2:44:57
They have lots of data sets that they publish uh pretty frequently and there's a lot to work with there.
2:45:00
Like they they publish like 911 calls um with like a 10-minute delay.
2:45:04
Um you can see kind of like an anonymized data set of what people are calling on one for which is kind of cool.
2:45:09
Like there's lot lots of things like that nobody really knows about but um there's things there.
2:45:12
Um >> would you like in a perfect world in a in a perfect world would one of these you do it for fun and then and then you discover some like enduring business or do you like just doing one idea after the next? >> Yeah.
2:45:26
I mean all these ideas are just things I find interesting to myself and you know usually that means somebody else will find interesting too if I post online.
2:45:34
Um, I think it's just like an outlet to be creative and it's nice to have distinct like work work and like this is more fun work.
2:45:40
But yeah, no, definitely be cool if something like that happened. >> Any any ideas?
2:45:43
Are you are you capital constrained on anything?
2:45:46
Like if you had 25 grand you would you would do >> because I feel like at this point there's enough people are ourselves included we would we would uh uh as long as it was not uh offensive we would happily chip in to to make possible. There is.
2:46:03
Yes, there I I I need 33K for a project next May um for a very fun stunt in San Francisco. Okay.
2:46:11
>> If anyone likes to talk >> Yeah.
2:46:14
>> All right, let's talk we'll talk offline.
2:46:15
We don't want to we don't have to spoil it.
2:46:17
>> Last story I want to talk about.
2:46:17
I I didn't re I didn't put it together until just now that you're the person behind New York's hottest steakhouse that was fake.
2:46:25
Tell me that story because I remember it happening and I didn't put it together until just now. >> Yeah.
2:46:30
You talked to the the my co-conspirator Moran, the the archaeology guy if you >> Yeah. Wow. No way. Wow. >> Yeah.
2:46:36
No, that was an incredible like one of the best nights of my life.
2:46:37
We had so many things go wrong, but like somehow it just happened to go right.
2:46:40
We we um long story short, we lived in a house together in New York.
2:46:44
Moran made stakes and then we made a Google Maps listing called Moran Steakhouse.
2:46:47
And then um all our friends started writing these bizarre fivestar reviews like you know I converted out of like Hinduism so that way I could try some of his beef or like he came in like drenched in blood from upstate fresh with a fresh cow like like really bizarre reviews but people in New York thought it was real cuz the dining culture there is crazy and we had this huge weight list over a couple years that we built up.
2:47:08
So we actually opened it for one night.
2:47:10
We opened a real restaurant fully permitted.
2:47:11
I was like licensed by the government to actually open up a restaurant. Wow.
2:47:16
>> Um we had 120 guests come thinking it was real.
2:47:18
It was like humongous operation logistics wise, but it somehow ended up well.
2:47:21
We did not get >> How did the guests How did the guests take it?
2:47:25
>> What were the reasons it was a joke?
2:47:29
>> Most of them were pretty good.
2:47:29
Like I don't think people really realized it was fake.
2:47:31
We We wanted people to find out it was fake in the Times and they read it about the article >> New York Times.
2:47:36
>> Um, and a lot of people did thought it was kind of a weird restaurant, but they thought it was like, okay, this is just how things are.
2:47:42
>> It's like cool and avantgard, right?
2:47:43
It's like edgy, new, and different and popup.
2:47:46
>> What did you guys break?
2:47:46
Did you guys break even on it?
2:47:48
Like did you did you end up did you sell enough stake to to >> No, no, we uh >> we we spent like 16k and then um made like 13k.
2:48:00
So we lost like 3k but for the amount of we got like it was it was viral everywhere.
2:48:05
>> But that New York Times piece is forever. >> It is. >> Yes. >> Yeah. >> Yes. >> The great idea. >> Amazing. All right.
2:48:10
Well, we will we'll message you.
2:48:12
We'll we'll figure out how to how to make this >> talk we'd love to talk about SF stunt.
2:48:16
That' be fantastic >> happen.
2:48:17
Uh and uh keep up the great work. >> Fantastic.
2:48:19
We'll talk to you soon, Riley. >> Thank you guys. >> Thanks for joining. Cheers.
2:48:23
>> Uh let me tell you about customer relationship magic.
2:48:25
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2:48:30
Um >> OpenAI says more compute in the making.
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Announcing five new Stargate sites with Oracle and SoftBank putting us ahead of schedule on the 10 gawatt commitment we announced in January.
2:48:42
>> Let's go >> ahead of schedule. >> Massive.
2:48:44
Uh, Stripe's also buying back shares from its VC backers at $106. 7 billion valuation.
2:48:50
Um, Sequoia bought 861 million worth of shares in 2024 at a 70 billion valuation.
2:48:57
So, they're getting a markup.
2:48:58
Uh, and amend and pretend as live shot of a swath right now.
2:49:04
He's talking about a swath demodin who is uh uh who is um obsessed with valuation and specifically liquidity premiums, illliquidity premiums.
2:49:10
And uh it's it's just it's just interesting that Stripe continues to find ways to stay private basically forever.
2:49:18
Uh and they've been on a tear, the Collison brothers.
2:49:22
Um well, the uh this uh we saw this uh we talked to Joe Lndale about being in the same fraternity at Stanford with Gary Tan.
2:49:31
And you can zoom in on this photo and see a young Joe Londale and a young Gary Tan hanging out at Stanford back in 2003.
2:49:42
pretty remarkable piece of tech lore.
2:49:42
I want to know what are what is everyone else up to.
2:49:47
We got to go through this list because there's probably some interesting folks in here.
2:49:51
I want to know what Michael Calhoun's up to or Justin Reynolds or Adam Rodriguez. Got to figure it out. >> Bunch of lads. >> Got to get on public.
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com investing for those that take it seriously.
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Um >> and we got anything else?
2:50:08
Tyler Cowan uh is talking about the potential for stagflation uh economic stagnation. >> No one wants that. No one wants that.
2:50:18
>> Tyler says it it seems increasingly likely that the American economy is sleepwalking towards stagflation.
2:50:22
In case you're wondering, that is not a good thing.
2:50:27
Stagflation means an economy experiences excess inflation and excess unemployment at the same time.
2:50:32
This was one thought to be impossible, but the OPEC oil price shocks of the 1970s triggered both high inflation and high unemployment.
2:50:40
And voila, we were suddenly we suddenly had a new unhappy economic phenomenon.
2:50:44
If I had to guess, I think there's a decent chance that 18 months from now, America could well have an inflation rate of 4% up from last year's 2. 5%.
2:50:53
>> John, we got some breaking news in the chat, saying China agrees to terms of a US Tik Tok deal. >> Wow.
2:50:59
Thank you, Bobby Cosby, for breaking the news. Thank you. Hello. Hello.
2:51:02
Oh, thank you everyone in the chat for keeping us up to speed.
2:51:04
Uh, >> is this not a little worrisome that they're agreeing with, >> you know, >> maybe >> seem to have pretty historically had a pretty hard line.
2:51:15
>> Well, pull up any more information while I talk about adquick. com.
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2:51:26
I want to tell you how Stephen Spielberg works.
2:51:30
He says, Stephen Spielberg says before he goes off to direct a movie, he always looks at four films.
2:51:36
Can you guess what films he watches before he goes out and directs a film?
2:51:43
>> Seven Samurai, Lawrence of Arabia, >> Borat, >> Borat, >> Dark Knight, >> Dark Knight.
2:51:50
>> What was the Mountain Head and Office Space, right?
2:51:53
Those are the movies you've seen.
2:51:55
No, >> now he does Seven Samurai, Lawrence of Arabia, It's a Wonderful Life, and The Searchers.
2:52:00
Have you seen any of those? >> Lawrence of Arabia.
2:52:05
>> Lawrence of Arabia is a fantastic movie.
2:52:06
Tyler, have you seen any of those?
2:52:08
>> I've seen all of them but The Searcher. >> Same with me. >> No, I have seen them.
2:52:11
>> You've seen The Searchers. >> I've seen it. Yeah.
2:52:13
>> You need to give us a review on that.
2:52:13
I need to check that out this weekend. Uh I've seen seven. >> All right.
2:52:17
Since you've seen it, name every scene. >> Yes.
2:52:21
>> Um >> they're just in the desert.
2:52:23
>> Is there a tech uh equivalent of this?
2:52:26
Before you start a new company, study the grades.
2:52:29
listen to these four founders podcast episodes.
2:52:30
Who are you listening to? Pick four. Top four.
2:52:33
I'm going Edwin Lan, Steve Jobs, uh Gaston Glock, and Charlie Rockefeller.
2:52:40
You gota you got to throw Gaston Glock in there for sure. >> Underrated.
2:52:45
>> And the Chicken Finger Dream.
2:52:45
You got to get up to speed on the Chicken Finger Dream before you start your next company.
2:52:50
I think every founder should have should have four founders podcast episodes in the chamber before they go out to raise before pump up speeches >> or if they need to run through a brick wall.
2:52:59
>> Yeah, if you need to run through a brick wall that you need to have your top four founders podcast ready to go.
2:53:02
So when you hit the road when you check into the Rosewood for your sandill tour of pitches, you're ready to go.
2:53:10
Uh, and you're also wearing a fantastic time piece on your wrist that you picked up from getbzzel.
2:53:16
com because your bezel concierge is available now to source you any watch on the planet. Seriously, any watch.
2:53:20
In other news, Palmer Lucky says that Mod Retro has teamed up with Ubisoft to re-release some of their greatest classics, starting with Rayman.
2:53:27
It has some of the best graphics of any Game Boy Color title.
2:53:31
Late cycle developers truly mastered the hardware.
2:53:33
It chipped months after the Gameway Advance was announced.
2:53:36
So, congrats to Palmer Lucky on a new deal for Mod Retro.
2:53:38
Company's been on a tear. very excited.
2:53:42
>> Also hit the timeline yesterday quoting a meta post that see how US national security agencies are using meta-lama models to develop bespoke tools for America's military and intelligence professionals.
2:53:52
It is uh crazy how much the vibe has shifted that Meta would imagine if Meta posted something like that in in >> 2016 when Palmer was there for a couple months.
2:54:04
Yeah, would have been crazy.
2:54:05
Palmer says uh added uh to the uh quote from the announcement, "We're also supporting US national security through our work developing augmented and virtual reality technologies through our partnership with Andreal.
2:54:15
We are developing a range of wearable products to help maintain America's technological edge."
2:54:21
>> You know what I've missed recently? Singing.
2:54:23
There hasn't been enough singing on this show, so we got to bring it back. Find your happy place. Find your happy place.
2:54:30
>> Book a wander with inspiring views, hotel, great amenities, dreamy beds, top tier cleaning, and 24/7 concier service.
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It's a vacation home, but better.
2:54:35
We got to get Tyler to chime in when we're singing.
2:54:39
Uh, we can close on this po on this post.
2:54:42
Uh, Vinnie Daniels says, "I'm seeing parallels between Nvidia and the Medici bank failure of the 1490s." >> Who isn't?
2:54:50
>> People are having fun drawing comparisons. Lots to the dot boom.
2:54:53
Uh, not so much to the 1490s, but uh, fire up open crack open a history book.
2:55:00
>> Should we do a Should we do a deep dive on the 1490s? >> For sure.
2:55:03
We should definitely read about the Medici bank failure. Tyler, you in?
2:55:07
>> Get out the red string.
2:55:08
>> I was gonna say I see a parallel between Nvidia and the rise of the Roman Empire >> early on. >> Okay. >> Okay.
2:55:15
>> Taking over everything. >> Okay. >> Who is Jensen? Is he Caesar?
2:55:18
>> The rise of Gangghask Khan, the Mongols. >> Maybe. Maybe. >> Maybe.
2:55:24
>> Um, >> anyways, that's a fun show, folks. >> Thanks for tuning in.
2:55:26
Hope you have a great Wednesday, a fantastic rest of your