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[Music] >> Team deathmatch.
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Today's Tuesday, August 26, 2025.
5:02
We are live from the TBPN Ultradome, the temple of technology, the fortress of finance, the capital of capital.
5:08
Thank you to the team at X. Thank you, Elon Mus. Thank you, Nikita Beer.
5:13
Um because in the latest app store uh graphics package for the X app, that's the everything app on iOS. Uh who's featured?
5:23
none other than yours truly.
5:27
>> The technology brothers. >> Yeah. Yes. Both of us are there.
5:28
Um and >> height mogging me as usual. >> I don't I don't know.
5:33
I mean, it's uh >> I'm just >> It fits in.
5:37
I I like how the brand kind of fits in because our we have some green in the background and they have the green uh little accents in the design.
5:44
Uh looking good with the liquid glass.
5:46
Whoever uh screenshotted this clearly on the next version of iOS.
5:48
Um but uh you wrote on X.
5:52
>> You count swift dev on X. Oh, it was from them. Oh, interesting.
5:55
Um, >> provided the screenshot. >> That's great.
5:57
Uh, you said number one on the charts.
5:59
Number one in our hearts. I believe it.
6:02
>> I mean, it's great to see X number one in the news. >> Oh, yeah. They are number one.
6:04
Oh, that's what you were talking about.
6:06
Okay, so they're number one in the charts. Yeah, that's great. Um, very very cool.
6:09
Um, we love uh having grown the show and uh people are having fun because we hit 100,000 followers on Axe.
6:20
Thank you to everyone who supported us along the way.
6:23
Uh, >> they said they said it was impossible.
6:26
>> There's actually two two two clips or hyper reels have hit the timeline.
6:29
We have one showing the evolution of our intros uh where they they get more and more aggressive every day.
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Uh, should we throw up this one? Yeah, let's watch this. >> Play it. >> This is great.
6:42
>> Welcome to Technology Brothers, the most profitable podcast in the world.
6:46
>> Welcome to Technology Brothers, most profitable podcast in the world.
6:48
Welcome to Technology Brothers, the most profitable podcast in the world.
6:51
Welcome to Technology Brothers the most on your phone in the world podcast in the world.
6:58
Welcome to Technology Brothers, the number one live show.
7:02
Welcome to Technology Brothers, the number one live show in tech. >> You're watching TVPN.
7:06
We're live from the temple of technology, the fortress of finance, the capital of capital, the dojo of the dollar, the shrine of shareholder value. You're watching TVPN. You're watching TVPN. You're watching TVPN. >> You're watching TVPN. >> You're watching TVPN.
7:26
>> It's so much more extreme.
7:26
Well, thank you to Ned for putting that together.
7:32
Only months apart from the first clip to the to the last. Incredible growth.
7:36
Yeah, it's been a lot of fun.
7:36
And then can we pull up this uh this vibe from uh Jay Fodril?
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>> This podcast has been growing like wildfire.
7:43
Recently, we've become the fastest growing podcast in the world.
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We're going to be doing a bottle of Dom every,000 followers.
7:50
>> Every thousand followers.
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>> Hey, we're live from the Palace of Party Rounds. Oh my god.
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>> Well, that was the first time you popped that one.
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I didn't realize it was so exciting.
8:01
>> We are live from the New York Stock Exchange.
8:04
>> One of the most I think important things happening in broadcasting. It's your show. You guys saw it.
8:10
>> What you guys do is great.
8:10
I also think that you're transforming the way that media is dispersed each week and it's awesome.
8:16
John and Jordan are gifted.
8:17
They're going to [ __ ] blow. I don't know anything.
8:19
I only I know about podcasts and I know how history's greatest entrepreneurs think.
8:22
I don't know anything about anything else.
8:23
I promise you there should just be like here's a [ __ ] pile of money and next time you have come with an idea, do it.
8:30
>> Almost everything that I don't like is unamerican.
8:32
We're going to get into producing ballet.
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>> A model that we basically use AI to basically to use AI to make AI.
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We are going to win the temple of technology, the fortress of finance, the capital of the capital. >> You're watching TV.
8:51
>> Wow, what a great Thank you, uh, Jay Fantastic. And, uh, funny. >> Fantastic edits. >> Thank you.
8:58
Thank you for making that. That was amazing. >> They beat us to it.
9:01
We were working on something, too, to do something like this, but uh, you guys did it for us. So, thank you.
9:06
Thank you for being a part of Thank you to RAMP for making all of this possible.
9:09
They took a shot on us very early and so you should take a shot on them. ramp.
9:13
com time is money save both easy to use corporate cards, bill payments, accounting and a whole lot more all in one place. >> They did.
9:19
I I think we had something like a thousand followers when uh committed to working with us for the year and uh we are forever grateful.
9:29
Yeah, they made it possible.
9:31
>> Yeah, it's been been a fun run.
9:31
Um anyway, the uh the real top story is of course uh Intel.
9:37
The experts have weighed in.
9:39
Um we have some amazing breakdowns from uh John at Asianry, Ben Thompson at Strateery, and Doug Olaflin at Fabricated Knowledge Semi analysis.
9:52
Um the true experts have weighed in.
9:52
Um, we've obviously been following the story on this show, but uh, these folks really know the details and were able to put together a bunch of great analyses mapping out what might happen next.
10:05
Um, there's a really good video from John at Asianometry that we should play to hear a little bit of what happens next.
10:14
The uh the quick recap as I understand it is uh Intel was dominant right up until mobile.
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Uh not only did they manufacture the best chips, but they also had an incredible brand from their Intel inside campaign.
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Uh these stickers were all over every PC uh Intel inside.
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It was on every PC that every kid wanted.
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Um and I can still hear the Intel sound in my head.
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If you dun, you know that sound? Wow.
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extremely offline >> before my time.
10:48
>> Tyler, do you know the Intel in inside sound?
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>> That sounds like the um Xbox sound. >> No, no, no.
10:52
Pull up the Intel inside sound.
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We need this on the uh on the soundboard.
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Uh inside >> this is the only sound we need. >> Inside sound.
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Uh I'll just play it here. I think I can play.
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>> You've never heard this before? Let me play this. Oh, come on. >> I do know that sound. >> You know that sound?
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>> That's an iconic sound. I take it all back.
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>> Everyone knows that sound. So, incredible brand.
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Right up until 2007, the iPhone dropped.
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And >> did they used to get they used to play that sound when you would be booting up a Mac.
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>> Uh I I think that was a different sound, but it was just all over TV.
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So like you couldn't turn on the TV.
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They they were just wallto-wall.
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And it was interesting because you wouldn't go and buy >> like medium for 100% >> not been taken advantage of fully in the internet era.
11:40
I mean, what did I say about the the Super Bowl ad that Ramp ran?
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I was like, that song at the end is iconic.
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And like this one, I was like, there's something here that you could double down on.
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>> Switch your business to ramp. com.
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>> Switch your business to ramp. com.
11:53
Thank you, Squan Barkley.
11:55
Um, so it was a very it was a fascinating time because Intel was making the chips, but also designing the chips and then also marketing the chips and people would buy the computer because of the chip, not just because of the brand.
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And that just doesn't happen anymore really.
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Um and so in 2007 the iPhone launched and it did not include an Intel chip and this was a bombshell.
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Uh instead Apple selected a Samsung manufactured system on a chip based on ARM um which is a design firm that designs chips and has an architecture that is incompatible with x86 which is Intel's architecture.
12:29
So, the reason was in uh chips from ARM were far more energy efficient than Intel's x86 processors at the time, and the iPhone needed to optimize for long battery life.
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There's a debate over whether or not Apple ever had a chance to go with Intel.
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Um, but it it almost doesn't matter because they went with Samsung and then eventually they did Apple Silicon and they stayed on ARM and they went for a more efficient chip, more uh less power, more less power hungry.
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And so um Intel was just too power hungry and Intel as a company underestimated how important the mobile market would be to remaining dominant in semiconductors over the long term.
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Uh Ben Todson identified >> missed AI. >> Yes.
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But they didn't miss cloud and that's what and that's where it gets interesting because so 2007 they start missing mobile because of the iPhone.
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But the iPhone was small and it was a small portion.
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It was unclear how much computing was going to be done on mobile.
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>> A lot of people weren't taking it seriously.
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>> A lot of people weren't taking it seriously.
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Ben Thompson comes up with this >> and there was real reason for that.
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If if you were just comping it to the PC market and saw Apple's like market share within PCs was a tiny >> fraction of that.
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And then also just the idea of like what am I going to do my work on a tiny phone?
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Like that's so it's such a stretch even if yeah the the okay I can text a little bit better but but I'm not going to be doing a lot of work on here.
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And now it's like the it's like the device of CEOs.
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like see I was like don't even open computers anymore.
13:57
Um so um Ben Thompson came up with this thesis in 2010 that Intel needed to pivot and and really double down on going into foundry mode.
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Um not founder mode but foundry mode.
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They needed to get other customers to design chips that were specific for what those customers needed and then Intel would make the chips and act as a foundry.
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Uh he launches the blog strategy in 2013.
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It's one of his first posts.
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Intel needs to build a foundry. Legendary call.
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Now, interestingly, he by his own account says that wasn't a good trade recommendation because for the next eight years, Intel ripped because of cloud computing.
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Because as mobile was growing, cloud was also growing because what does your phone need to talk to?
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It needs to talk to a server in the cloud.
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So, the cloud was growing.
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AWS is growing, GCP, Azure is growing.
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And so Intel's selling a lot of CPUs into uh EC2 instances on Amazon, AWS, and Intel's business is doing fine until AI comes around and they miss that as well.
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And now they've missed mobile and AI and they're uh and they're just falling falling behind.
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And then now the cloud is starting to look at hey well actually the power trade-offs of ARM now are actually pretty good and so maybe we should do you know different chips in the data center.
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So they are facing pressure in a lot of different uh ways.
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Now that type of pivot would have been really antithetical to Intel's culture.
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They would have had to build a customer service organization and Intel was so dominant.
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It was like this center of excellence.
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Every it had the best people.
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And so they weren't used to saying, "Oh yeah, like let's do what the customer says."
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It's like, "No, we know what's best.
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We make the best thing and you decide >> when you're on a roll that works really well." >> Exactly. Exactly.
15:39
And so, uh, who knows if they could have did they could have done it.
15:43
They actually did, as we talked about yesterday, they did try and spin up, um, a little bit of a foundry for these FPGA startups, but it was always a small piece of the business.
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Basically, like if you need a very specific chip to do, uh, like networking or or encryption in a data center.
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It's like a special chip.
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They would do that, but with a small startup.
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And they never really pushed into it.
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They never went for like the big like wins like Apple.
16:05
Um, and so because of the cloud boom, Intel performed quite well throughout the 2010s, but the AI boom is a different story.
16:15
Intel's far behind now, and camp simply and simply cannot afford to build their new cutting edge manufacturing facility without external customers.
16:20
And no one wants to work with Intel right now.
16:23
Uh, but big companies do want to stay in the good graces of the US government.
16:26
And that's the bull case for Intel here.
16:29
big tech companies get art of the deal into putting large enough orders into Intel to underwrite the completion of their new 14A foundaries.
16:38
That's the big Ohio plant that is estimated to cost something like $40 billion in orders to kind of make it math out.
16:43
Um they they don't need to go to head-to-head with Nvidia.
16:46
Nvidia uh they don't need to win the GPU market necessarily.
16:52
And we'll get to this with a video.
16:54
John at Asionometry argues that Nvidia should buy CPUs from Intel.
16:56
So Nvidia sells a CPU called Grace that they pair with Hopper, which is Grace Hopper, which is the name the namesake of the system.
17:07
Um, and that's not an that's not an x86 chip.
17:11
Um, but there's no reason why Nvidia couldn't license CUDA and the design to Intel and say, "Hey, Intel, you're going to be our manufacturer for that."
17:19
Because Intel's not a manufacturer.
17:21
So realistically, Intel should be able to say, "Hey, yeah, we'll we'll go to Intel.
17:25
We'll go to TS, whatever gives us leverage."
17:28
>> Now that the government and Trump have a stake in Intel, you can imagine Trump really leaning on Jensen to make something like this happen.
17:40
>> And and Trump also has some leverage over Nvidia because he's taking this 15% kind of questionable export tax.
17:44
And so you can say, "Hey, uh, Jensen, like, how about I make that go away?"
17:50
and you give Intel a little bit bit of business or oh like I'm going to threaten a really crazy tariff and I'll pull it back if you work with Intel. Yeah.
17:59
And so that's kind of the bullcase here that people are are kind of coalesing around the experts who I trust on this issue.
18:06
Um and so if Trump was able to strongarm Nvidia with a somewhat legally dubious 15% export tax getting Jensen and Lip Bhutan in the same room today to hammer out a deal doesn't seem like the craziest idea.
18:17
And there are other tech companies that might play ball too.
18:19
This is an expensive gambit.
18:21
Ben Thompson estimates Intel needs 40 billion in demand to make the foundry play pencil out.
18:25
But big tech companies are spending almost 10 times that collectively.
18:27
Uh and they all and they all still take the president's phone calls.
18:31
So um let's play the uh Asian video right here. Perfect.
18:37
He's going to be in California by the way or Arizona.
18:38
So we should go say >> So what seems most likely about to happen is that the United States government and a few aligned investors first take a stake in Intel.
18:45
The government puts up money to finish the fab in Ohio.
18:50
Then raises tariffs to a high number with some carveouts to satisfy the crowd.
18:55
>> That's the $20 billion.
18:56
>> And then they will apply pressure to the tech giants to get them to throw some orders at Intel Foundry.
19:00
There's a comment on the Wall Street Bets thread on the story that succinctly lays down the sentiment.
19:09
Dude is 100% going to nudge quote unquote Apple and Nvidia to use their 14A foundaries.
19:14
this is going to skyrocket by EOI 2026 in the hundreds.
19:20
Doug Olaflin of fabricated knowledge agrees and adds that pressure might also be applied onto the semiconductor equipment companies too.
19:26
Additionally, forcing semiconductor companies like KLA, applied materials and lamb research to invest and give resources in exchange for approved licences is another example of a carrot and a stick.
19:39
A few companies have already started to turn on this perceived For instance, just as Intel has announced that software, we need a stickion investment studio for sure.
19:53
>> Considering how Masa invests, I'm not surprised he's first through the gate.
19:57
There's news that he was in talks to buy Intel's fabs.
19:59
Maybe that will happen by the time you see this.
20:03
As I said before, this seems to be what the plan is.
20:06
>> Coalition of the unwilling. Okay, we can stop it. Um, it's a great video.
20:08
You should go subscribe to Asianometry on YouTube and uh and get a I think it's part of the strategy bundle.
20:15
If you go for the bundle, you get access to uh John at Asianometry's blog posts as well, which are fantastic.
20:22
Uh and I've been going deeper into the Asianometry YouTube and there's so many good intel videos and the guy really understands the history.
20:32
Apparently, this isn't the first time that the US government has tried to reshore uh manufacturing of a particular uh technology.
20:39
He highlights the the DRAMs like this memory gambit that happened in the 80s and uh it didn't really work out and he kind of uh kind of draws some analogies there.
20:51
Anyway, John, next time you're you shouldn't just upload that you that YouTube video, you should stream it on reream.
20:57
One live stream, 30 plus destinations, multiream and reach your audience wherever they are.
21:00
go to restream >> anywhere.
21:02
Uh so Sager and Jetty is quoting Ben Thompson on the Intel 10% stake.
21:07
Quote, "The single most important reason for the US to own part of Intel, however, is the implicit promise that Intel foundry is not going anywhere.
21:16
There simply isn't a credible way to make that promise without having skin in the game."
21:20
So it's not just a lender of last resort.
21:22
It's actually just commitment that there will always be some level of US manufacturing on the leading edge.
21:30
um which is what Intel's trying to trying to do here with this foundry uh and what they have been so far unsuccessful at drumming up customers for.
21:38
So yeah uh he Sager shares some screenshots from the strateery article uh given all of this acquiring 10% of Intel terrible though it may be for all the reason uh Lindicum articulates and I haven't even touched on the legality of this move is I think the least bad option in fact you can even make the case that a lot of what Lindum views as a problem has silver linings.
22:00
Intel deciding to stay in manufacturing is arguably not making a political decision, not a commercial one.
22:05
However, it is important for the US that Intel stays in manufacturing.
22:07
It it is a political issue.
22:10
Uh Intel prioritizing government interests which are inherently focused on national security and the long-term viability of US semiconductor manufacturing over their fiduciary duties could just as easily be framed as valuing the long-term over the short term.
22:22
Had Intel done just that over the last two decades, they wouldn't be in this position.
22:26
So, uh, America is setting Intel up to be able to make that multi-deade decision.
22:31
It's going to be a lot of pain, but then eventually hopefully they'll be back on the leading edge. >> Yeah.
22:36
And remember, it was felt like two or three weeks ago, Li Bhutan was just focus like you could imagine the morale at Intel just being absolutely abysmal because it was just cut after cut after cut versus, you know, anytime any type of obvious long-term strategy of getting back on the leading edge. >> Yep.
22:54
uh other companies being pressured to purchase Intel products is exactly what Intel needs to not be to not just be viable in manufacturing but also to actually get better.
23:02
If TSMC and Samsung are disadvantaged by not making chips in the US, that's a good thing from a US perspective.
23:08
Both companies are investing here. The US wants more.
23:11
Private capital prioritizing US manufacturing is a good thing.
23:13
Uh I remember when the chips act was still break was first breaking.
23:15
Ben Thompson was advocating for something that looked a little bit more like um Operation Warp Speed where basically the government instead of and this is what they do in China too where instead of saying like okay we're just going to give 20 billion to Intel because like we pick them and they're good.
23:29
It's more like the US is going to be a buyer at this price.
23:35
So if you make it in America we'll buy it.
23:37
And this is what's happening with MP materials right now.
23:39
The DoD invested, I think, 500 million, but then also said, "Hey, we will buy all the magnets at this price.
23:44
If you can go sell them at a higher price to somebody else, do that.
23:47
But you got us and we'll just build a stockpile."
23:50
>> And so you could imagine the US being like, "Yeah, we'll build our own data center and we'll try and lease it out and maybe we take a loss if if there's like an overbuild or something, but but it it could very well pencil out.
24:00
And if demand for these chips is actually higher, then you'll just sell them to someone else and we won't even need to buy them."
24:07
acting as that stop gap actually in this moment in time what made the most sense and then private capital prioritizing US manufacturing is a good thing.
24:21
Ben Thompson closes this little quote out by saying the single most important reason for the US to own part of Intel, however, is the implicit promise that Intel foundry is not going anywhere.
24:30
There simply isn't a credible way to make that promise without having skin in the game. And that's now the case.
24:36
Uh, so of course go subscribe to Strateery.
24:38
Go subscribe to Fabricated Knowledge.
24:41
Doug Olaflin is saying, "Not going to lie, a lot of people who are mad at Trump for everything can't see the genius of the Intel investment.
24:46
I mess with it massively.
24:48
I love I love the way he posts there. It's great."
24:51
Um, >> Doug messes with it, everyone.
24:55
>> Yeah, I'm I'm I'm I'm up I'm messing with it, but uh I am I'm mostly deferring to the to the experts on this. >> Trust the experts.
25:01
Anyway, um if you are designing not a chip but something else, get on Figma.
25:08
Think bigger, build faster.
25:09
Figma helps design and development teams build great products together.
25:12
You can get started for free. figma. com.
25:14
Uh David Senra, you saw him in the vibe reel.
25:17
He just dropped a fantastic episode called How Elon Works.
25:22
It was a very interesting process.
25:22
He outlined it for us on the show.
25:25
Basically, uh the latest book on Elon uh is more of like news.
25:29
I think it's Walter Isacson's and it's more of like uh news articles minuteby minute.
25:34
Um and so it's >> it's a playbyplay. >> It's a playbyplay. Yeah. >> Less of a playbook. >> Yes.
25:41
And so Senro wanted to transform it into a playbook and he did that by I think he read the book like seven times or something insane.
25:49
But he he like turned he took notes on it and then read it seven times and then you know he he does his process.
25:56
>> Real actual deep research not like seriously.
25:59
But uh I really enjoyed it and I think you'll enjoy it too. So you should go listen.
26:03
Um but the interesting thing that I liked about it was that it it helped me it helped me understand a little bit of what's going on with Starship because we've seen so many setbacks with that program and when you actually listen to how El like the risks that Elon takes it is crazy.
26:22
So first first one is that he is not interested in achieving any sort of short-term goal.
26:32
He only wants to develop a system that can do something a million times.
26:38
And so that's is that has a much higher bar than building like one exquisite rocket that gets there and has like, okay, yes, we spent we spent five years and we made sure that every screw was in the exact same place in the perfect place and everything was designed flawlessly so that we could get up there and then the next time we want to do it, it's going to take another 5 years and another 10 billion.
26:58
He's like, no, like the thing that we're going to design needs to be able to go every single day.
27:05
So it needs cheap and fast and copy and pasted a bunch, >> copy and paste it.
27:09
And so I I think the manifestation of that is that is that >> like the like you're going to have a lot of failures early on, >> but then once it gets polished up enough, >> uh it's going to start it's going to start turnurning and and you're set up for much more scalability.
27:23
The other example he gave was like Elon would go around the the manufacturing line and just be like, "Uh, why are you using four screws there?
27:31
Do you think you could use two?
27:32
Like save a little weight. Like do something."
27:34
And the person would be like, "Well, like two screws, like the thing might fall apart."
27:38
And he's like, "We'll try it."
27:40
Like, "Just try it and we'll see how it goes."
27:41
And and if you imagine that manifesting in the Starship program, it's like, "How many of those experiments are running?"
27:45
It's like, "Yeah, that one you actually need three screws at least.
27:49
You definitely can't do it with two screws."
27:50
Uh, and so I imagine that there's tons and tons of those little decisions that like once you get like instead of instead of starting with like the exquisite system and then tearing stuff down with this, it definitely seems like he's starting with like the bare minimum and then just like adding things back to like keep it stable so that it actually will will work.
28:10
But when it works, it should it it should be very um uh very very cheap, very reliable, and actually solve equation.
28:16
this Starship launch, the timing with everything that's been going on in XAI world recently, this launch feels more important than the last few in the sense that uh Elon and the SpaceX team don't want to give the the haters uh material. Totally. Totally.
28:35
>> And so this current launch has been delayed a couple times.
28:36
It's currently slated to >> uh to they're they're going to attempt it as of now in 5 hours uh later uh today. >> Yep.
28:45
So hoping this one gets off the launchpad and does well, right?
28:48
Because if we get one another one of those um you know fireworks shows. Yep.
28:56
>> Um I think that uh Elon is going to want to log off X for a little bit. >> Yeah.
29:00
People are going to be talking trash. Talking trash.
29:03
>> Or at least pause the Anie posting for uh at least 24 hours. >> Yeah.
29:09
Well, uh if you're building a business that's going to space, you got to stay compliant. You got to get on vant. com.
29:14
Automate compliance, manage risk, proof trust continuously.
29:16
Vanta's trust management platform takes the manual work out of your security and compliance process and replaces it with continuous automation.
29:22
Whether you're pursuing your first framework or managing a complex program, uh, in other news, Taylor Swift is getting married.
29:32
Um, >> the private jet enthusiast.
29:32
Well, I I feel like most of our audience would know her for her Wall Street Journal op-ed in 2014 where she said for Taylor Swift, "The future of music is a love story."
29:44
Uh, where will the music industry be in 20, 30, 50 years before I tell you my thoughts on the matter?
29:49
You should know that you're reading the opinion of an enthusiastic optimist, one of the few. Yeah.
29:56
One of the few living souls in the music industry who still believes that the music industry is not dying, it's just coming alive.
30:02
There are many many people who predict the downfall of music sales and the irrelevancy of the album as an economic entity. I am not one of them.
30:10
In my opinion, the value of an album is and will continue to be based on the amount of heart and soul an artist has bled into a body of work and the financial values and the financial value that that artists and their labels place on their music when it goes into the marketplace.
30:25
Piracy, file sharing, and streaming have shrunk the numbers of paid album sales drastically.
30:29
And every artist has handled this blow differently.
30:33
In recent years, you've probably heard the articles about major recording artists who have decided to practically give their music away for this promotion or that exclusive deal.
30:43
My hope for the future, not just in the music industry, but in every young girl I meet, is that they all realize their worth and ask for it.
30:47
Music is art and art is an important is important and rare.
30:52
Important, rare things are valuable.
30:54
Valuable things should be paid for.
30:56
It's my opinion that music should not be free.
30:59
And my prediction is that individual artists and their labels will someday decide what an album's price point is.
31:04
I hope they don't us underestimate themselves or underestimate or undervalue their art.
31:11
>> So, did she get this right to date? Not really.
31:15
I think she I think she got the thing that she got right is that what an album is can be extremely monetized if you continue to think about what the like the album is scarcity.
31:29
Like you either have it or you don't.
31:32
And the internet kind of reduced that scarcity to zero because you could stream it, you could pirate it, but there is still scarcity to be created if you are an artist, if you are a musical artist.
31:43
And so the way she does that now is when she releases an album, she goes on a tour that becomes so big that again there is scarcity because there are only so many tickets at Sofi Stadium and you have to be there because it's a moment >> one of the best monetized. >> Yes.
32:01
>> Recording artists of all time. >> Yes. Yes.
32:02
And so she gets the long tale eventually and eventually her her music is essentially free and played in uh in grocery stores.
32:10
So, I'm going to read you something from their Instagram caption announcing the engagement. >> Yes.
32:16
>> It's not just a marriage. Dash M Dash.
32:19
It's the perfect love story. >> No way. No way.
32:24
>> Back on X is calling this out saying uh saying claiming that Taylor and Travis are oneshotted. >> No way. >> What you got, Tyler?
32:32
Was that >> Well, I was going to say something about like her like monetization like um Kyla Scan has this good post.
32:37
She said, um, Taylor Swift's engagement is actually very relevant to monetary policy because she is the most powerful stimulus tool we have. >> Oh, really? How so?
32:47
>> Well, I mean, her her tours are like massive.
32:49
Like you can see the like rise >> in consumer spending. Yeah. >> Interesting.
32:53
>> Especially like smaller countries. It's like very notable. >> Yes. Yes.
32:55
But but how does her being married like she could just go on tour and be single, right?
33:00
Is she going to sell more tickets because she's married now?
33:03
Does it allow her to tour more?
33:03
Uh you could also see it in uh a lot of people are talking about birth rates, right? So maybe a new boom. Yep. >> Baby boom.
33:12
>> Catherine Bole just posted a picture and just said with the capt captioned >> their pictures pictures pictures just said American dynamism.
33:21
>> I do think this will be good for the birth rate.
33:22
It's it's also going to be uh some some uh for anybody that's in a longer term relationship in their late 20s, early 30s. Pressure is now on.
33:32
These photos are going to be getting sent around.
33:33
They're setting a new bar, right?
33:35
Uh quite the floral display by Travis.
33:39
Got to give them props there.
33:41
>> How many uh how many kids do you think she'll wind up having? >> She's 35. >> She's 35.
33:48
>> She's got to get going. >> Oh, yeah. 198.
33:50
>> And uh hopefully a ton, right?
33:50
I mean, I think we'd like >> the last luxury status symbol, apparently.
33:57
>> Like to see at least 10. >> Yeah, it' be great.
33:58
Um well uh uh if she wants to manage her family's uh plans, she should get on linear.
34:10
Linear is a purpose-built tool for planning and building products.
34:11
Meet the meet the system.
34:14
>> It's a family planning tool.
34:14
You can make it work for it >> for modern software development.
34:18
Streamline issues projects and product road maps. Start building. Uh I don't know.
34:23
She could probably use linear.
34:23
Uh she's probably developing software and websites and stuff.
34:26
Uh anyway, uh what we should talk about is this post from Robert Sterling, the only form of wealth that's ever mattered.
34:32
Screenshotting the Financial Times, the ultimate status symbol, a big family.
34:36
So, the Financial Times writes, "A flex of Uber wealth in 2025 is multiple children, all the while preserving prepar lifestyle, interests, and physique."
34:48
Uh, what is the ultimate luxury status symbol? Jordy Hayes.
34:51
Once upon a time, it may have been flaunting a rare handbag, sports car, or flashy watch.
34:59
>> But with the soaring costs of living and shrinking household sizes and depreciation of uh of tyons, sports cars are now are now >> they're giving tyons away.
35:08
>> They're giving tyons away.
35:08
The only thing that you need that that you can flex your wealth with is um having kids, specifically lots and lots of them, says the Financial Times.
35:16
For most working parents, quote, and particularly those living in cities, even to have one child comfortably is a major economic calculation that requires considerable financial stability.
35:26
Uh, says Eliza Philby, author of Inheritocracy, it's time to talk about the bank of Mum and Dad.
35:34
Um while that was also true historically when having an enormous brood was bolstered by a need for labor, religious imperatives and preserving family legacies in the face of high infant mortality.
35:46
Children today aren't a source of positive household cash flow. They are a drain on it.
35:51
But I think >> we got to turn this around.
35:54
We got to put these kids to work.
35:56
You got to put them in the mines in the in the Minecraft or >> get them on if you if you got a if you got once your kid hits three, you should set them up with a WAP account and pay pay for college. >> Yes. >> Do it.
36:09
Don't don't make mistakes.
36:11
Actually, make some mistakes, but figure it out.
36:13
>> Hey, I mean, uh, in the Stevens household, you have to pay the bills. Uh, making making tech.
36:18
>> Start making start making courses for other three-year-olds.
36:20
How to be a three-year-old. >> Yeah.
36:22
Don't expect Don't expect the the Anderal chairs to pay for your college, buddy.
36:28
>> There's only so many of those to get around. >> We're not selling. You're still long.
36:32
You got to pay for those with with skateboards.
36:35
Um the reality is that middle class parents do not support kids to 18.
36:40
Philby says that for families who can afford to, it's often closer to 30 >> with with costly child care, a lack of family support systems, and a global trend of women child care for their 25-year-olds, >> I guess.
36:53
Yeah, >> in some cases, >> uh, conceiving children later, there is a feeling that one child is increasingly the norm for dual income households.
37:01
Philby says two is a bit of a push and three or more is just an is not just an anomaly.
37:05
You need to be super rich.
37:08
Officially, official birth rate figures in many countries have hit all-time lows.
37:12
In the UK, the Office for National Statistics says that the fertility rate is 1.
37:16
44 children per woman, while in the United States, that figure is 1. 6. 6.
37:19
In some Asian nations such as Japan and South Korea, the rates are 1. 2 and 75 respectively.
37:27
I was talking to somebody who is uh very bullish on uh South Korean tech uh because of AI and a lot of the companies that they sell uh into. Yeah.
37:38
And there's a whole there's a whole ton.
37:40
I think there's there's uh there's there's like they have their own like S&P 500 of like really really great >> companies. >> TBPN. >> They do. They do.
37:47
Um, but I had no idea that the birth rate was so low. 0.
37:50
75 is really, really low.
37:52
So, they got to turn that around.
37:54
Um, >> but while one and done may be booming as a cornerstone of modern middle class parenting culture, so too has a fetishization of the opposite end of the spectrum.
38:04
In other words, augling extremely wealthy figures in the public eye whose picture perfect families never seem to stop growing.
38:10
Behold the fixation of frazzled millennial working women and others with the tradife movement, a social media phenomenon that glorifies homesteading, milkmaids, and taking care of your husband and offspring.
38:21
Its brightest star, Hannah Neilman, uh, Neilman, I don't know, of Ballerina Farm, has attracted a 10 million strong following on Instagram, thanks in no small part to her eight immaculately disheveled blonde children with her husband Daniel Nielman, uh, the son of JetBlue founder and airline mogul David Neman.
38:42
>> Hopefully, they sold before JetBlue became a penny stock. >> Oh my god. Yeah. Get out. Get out. >> Get out.
38:49
Uh, in the celebrity orbit and beyond the trials and tribulations of the everexpanding Kardashian clan, Alec and Hilaria Baldwin sent the internet into meltdown earlier this year with a t TLC reality television series called The Baldwins.
39:04
I had no idea this was a thing.
39:05
Uh, which documents life between their Manhattan apartment, >> try to pull up this picture, >> East Hampton mansion with their seven children and eight pets.
39:12
I had no idea Alec Baldwin had uh seven children, eight pets.
39:16
I wonder what pets he has. Um, huge fan.
39:18
You know that you know that Haley Bieber is Alec Baldwin's daughter? >> No. >> Is that right?
39:25
>> Am I Am I right on this guys? >> Wait, what? >> That's true. No way. Okay.
39:28
Learn something new every day.
39:32
>> Pretty sure that's true. >> Yeah.
39:34
>> Might need to truth stone it. No. No. No. Uncle and niece. >> Uncle and niece. Okay. So, they are >> Okay. Okay. Okay. >> Yeah. >> Got it. Photo. >> Interesting.
39:42
>> Um, but here here's the picture of Alec Baldwin and his family still uh just pumping them out. >> Looks great. Looks great.
39:48
Take those kids to a wander. Find your happy place.
39:51
Book a wander with inspiring views, hotel, great amenities, dreamy beds, top tier cleaning, and 247 concier services.
39:57
It's a vacation home, but better folks.
39:59
Um anyway, um huge families are increasingly visible among the 1%, especially in some of the world's wealthiest and most competitive enclaves such as New York City.
40:09
In her widely read, if controversial book, Primeates of Park Avenue, Wednesday, Martin member memorably observes that massive families, they were everywhere on the Upper East Side, a neighborhood with some of the most expensive real estate, schools, nannies, and hobbies in America.
40:24
Jord, what were you about to say?
40:26
>> I was about to dive into that. Four is the new three.
40:27
Previously conversation stopping, but now nothing unusual.
40:29
She writes, "Five is no longer crazy or religious.
40:33
It just means you are rich.
40:35
And six is apparently the new townhouse or Gulfream."
40:36
According to a study by Forbes of more than 700 American billionaires, at least 22 have seven or more children, >> often from multiple marriages and adoption, including perhaps most famously Elon Musk, regularly named the world's richest man, Musk has become a poster boy for billionaire procreation.
40:56
In a vocal proponent of pro-natalism, which he sees as vital to humanity's survival and declining birth rates, fascination with the uber elite, with how they live their lives and run their households is not new.
41:05
A raft of high-end fashion and consumer lifestyle brands have turned to notions of parenting with almost unlimited resources and incorporated them into their product offerings and marketing efforts.
41:15
Artipop offers $800 velvet and cashmere baby carriers that have been heralded as the Birkin of mom gear.
41:22
>> Heralded, but yes, >> heralded. >> Heraldo Rivera.
41:27
>> Heraldo rebranding wearing a baby as >> an ultimate accessory.
41:33
>> I mean, >> it is the ultimate luxury accessory.
41:36
Much like having graphite in your software development team% it's the birkin of code review. Uh graphite.
41:44
dev code review for the age of AI.
41:46
Graphite helps teams on GitHub ship higher quality software faster.
41:49
You can get started for free.
41:50
Um if they don't mention Pav in here, I'm going to stop reading.
41:55
Anyway, >> I still when I'm walking around with my one-year-old and my my three-year-old, >> people often assume that I'm the uncle >> and and are surprised >> because you're young. >> Yeah.
42:07
>> Oh, >> just it's it's still >> seems >> uh wild.
42:10
Even though if you go anywhere slightly off the coast, it uh it starts to become common place. >> Yeah. Super normal.
42:16
Um yeah, it is interesting that um if you if you actually look at if you look at birth rate trends by income bracket um for a long time the higher the the the the like the lower income cohorts would have more kids. Yeah.
42:33
And so uh technically I think from an from an economics perspective having children was an inferior good.
42:39
It was something you did more it was like uh the equivalent of Costco.
42:44
It's like the opposite of what they're saying here.
42:45
But really what we're identifying is like is like there's a there's a barbell effect where at the high end you get a lot more kids and at the low end you get a lot of kids but in the middle there aren't that many kids. Yeah.
42:57
And uh this is uh I'm going to make a movie reference that you haven't seen so I won't even try. >> Hit me.
43:03
>> Uh there's a 1% chance. >> Idiocracy. >> Nope.
43:09
>> We should pull up the intro to Idiocracy because it is hilarious.
43:11
John Ross in the chat says Nick Cannon has 12 kids. >> That is crazy. >> That is a big number. >> Wow. Very good.
43:19
>> I think I mean it's it's it's also I'm guessing that's across a number of different uh relationships. >> It is. >> It is. Yeah. >> Yeah. >> Canon. >> Um >> Okay.
43:30
So, mini me designer collections and $600 high tops allow an army of children to dress like their parents as well as one another.
43:36
And white labels such as PC Philippe and Dolce and Gabbana have long placed glamorized visions of family at the heart of their advertising campaigns.
43:44
Of course, you never own a PC.
43:46
You merely hold on to it for the next generation or Pekk as they say.
43:52
Uh newer efforts from Beta Vanetta and Berber. >> Oh yes. You want to play this?
43:58
>> This is the I think this is the intro to uh to idiocracy.
44:00
Let's play this >> was at a turning point. Natural selection.
44:06
The process by which the strongest, the smartest, the fastest reproduced in greater numbers than the rest.
44:13
A process which had once favored the noblelest traits of man now began to favor different traits.
44:21
>> Most science fiction of the day predicted a future that was more civilized and more intelligent.
44:25
But as time went on, things seemed to be heading in the opposite direction, a dumbing down. How did this happen?
44:36
Evolution does not necessarily reward intelligence.
44:38
With no natural predators to thin the herd, it began to simply reward those who reproduced the most and left the intelligent to become an endangered species.
44:50
>> Having kids is such an important decision.
44:54
>> We're just waiting for the right time.
44:56
It's not something you want to rush into, obviously. >> No way.
45:00
>> Oh [ __ ] I'm pregnant again.
45:00
[ __ ] I got too many damn kids.
45:04
Thought you was on the pill or some [ __ ] >> Hell no.
45:09
>> Must have been Britney. >> Britney? No.
45:13
>> There's no way we could have a child now.
45:16
>> Not with the market the way it is now. >> God, no.
45:17
That just wouldn't make any sense.
45:20
>> Come on over here, [ __ ] He doesn't care about you.
45:23
>> Yeah, well, there must be something he likes over here.
45:26
>> Say nothing to me, baby. >> It wasn't me. It wasn't me.
45:32
Well, we finally decided to have children.
45:34
And I'm not pointing fingers, but it's not going well. >> And this is helping.
45:41
>> I'm just saying that before I have in vitro, maybe you should be willing to >> It's always me, right?
45:46
>> Well, it's not my sperm count. >> Yeah. >> Yeah.
45:49
I'm going to [ __ ] all of y'all. >> Okay. Okay. We got to cut this off. You get the idea. >> I get the idea.
45:58
decision fatigue from the uh from the 138 IQ.
46:00
Uh >> too smart to have kids.
46:05
>> Too smart to have kids.
46:05
Um anyway, let's continue.
46:09
>> Yeah, this is an interesting line.
46:09
So, >> uh uh there's been a you know, other brands, but Tega Vanetta has has had a campaign with uh ASAP Rocky, >> which has been cool.
46:18
I thought this campaign was brilliant.
46:19
Um the uh there's a line here.
46:23
Healey thinks these campaigns come at a time when the luxury industry is struggling to maintain its cultural relevance reflected in a cooling appetite for products as social signifiers in a fall in global sales.
46:35
Focusing on family reflects an attempt to move into the realm of behaviors and values and away from physical things.
46:41
You can't dupe having a family.
46:41
He says it's uh you know you could get a a dupe of a of a Birkin or something like that.
46:49
>> Oh, that's what dupe is. Yeah.
46:49
Or something from the row or whatever.
46:53
Every luxury brand gets knocked off immediately.
46:57
>> Healey says it's a very long-term commitment, not to mention one of the most significant and transformational that you can make in your life.
47:01
But it's not just having kids.
47:04
It is venerated by brands and vaunted uh as a status symbol.
47:08
It's about how you are having kids and to what extent you can maintain your prepar lifestyle.
47:11
For many celebrities, this means an army of child care support.
47:15
Kim Kardashian is said to have 10 nannies.
47:20
on a 247 rotation for four children while the Baldwin family have two on staff.
47:24
That feels low for how many kids I saw in that picture to be honest.
47:29
>> Child care positions in the US of this nature can easily command annual salaries of more than 200,000 though his more standard wage would be closer to 85,000.
47:36
Still paid support of any kind remains an unobtainable luxury for the majority of families.
47:41
majority of families. Um yeah, for for me I I noticed this um uh I I noticed the jump in, you know, how how I was living at at 25 prek kids realizing as soon as you add kids, everything that you do, whether it's where you live and how you travel becomes travel instantly becomes, you know, if you were staying
48:03
at nice hotels and now you're traveling and you got to get a hotel for your nanny, you got to get a hotel for your kid, then a hotel room for your kid, then you add a uh then you had a second kid and so now you need in some cases nannies you need >> three extra rooms, one for the nanny, one for each kid, one one for the couple. Um and so the actual like cost
48:21
Um and so the actual like cost of of something as simple as a weekend trip can can 4x pretty quickly. Yeah.
48:29
>> Um and uh certainly inspires you to grind harder in my experience >> 100%.
48:34
Uh this version of parenthood doesn't mirror the experience of most people.
48:38
Uh Healey says there's a version where you're still constantly meeting friends, returning to your pre-baby body, showing up at the club or late night event, not being tired all the time, moving out to the suburbs or wearing clothes with milk splattered over them.
48:50
Fashion has always traded on allowing us to project something a little bit better than we are.
48:54
But having a large family also sends a signal of confidence in the future.
48:59
>> We're also the generation that grew up with suburbs being bad and something to avoid.
49:03
And as as an adult with kids, >> I realize the suburbs are incredibly underrated.
49:11
>> Yeah, heard it from Dr. Drew yesterday.
49:13
He lives next to a golf course. It's amazing.
49:16
Uh, a demographic that may feel more secure than most, those with more money.
49:20
Uh, Musk paints his pro-natalist vision in stark terms and has some highly unorthodox personal family values.
49:27
But among the traditional conservative right whose social media sway is growing and who champion Americans having a large household.
49:32
The question of who should be having more babies is an uncomfortable one.
49:37
A sizable portion of the extremely wealthy pronatalists say they want us to use breeding to fashion a better human race.
49:44
Philby says, "But the current fetishization of being a mother of multiple children can reduce women to a kind of birthing machine, fulfilling her social societal duty and demonize women working incredibly hard and contributing economically toward society who are having few fewer or no children whether by choice or necessity."
50:00
I think Nadia Aspuhov had a good rebuttal to that which is that uh tech can certainly uh embrace and and and kind of invalidate this false dichotomy by creating a more uh welcoming uh ecosystem and not like noveling when a woman shows up.
50:18
>> Yeah, I mean it's interesting to note that uh a lot of the technology that we take for granted today makes parenting like a little bit easier but not dramatically easier, right?
50:26
the sort of uh I think people um people tend to judge, you know, the the family out to dinner with the kid on the iPad. Yeah.
50:36
>> And if you haven't had kids, you don't realize that that many kids could be so would not be able to just strap the VR headset right on.
50:42
You have to deal with them at home >> and just bolt them down to the >> lock them in to the kid seat and then just fully locked in.
50:51
>> No, when I when I go out to the high chair. >> Yeah. No. Yeah.
50:53
When I go out to the the restaurant, I bring the full racing rig with a wheel and the steering wheel and the pedals and the VR headset and I'm just like, "Lock in, brother. >> Lock in.
51:04
>> You're going >> You got to You got to be You're doing the Nerburg ring. Doing the ring.
51:09
>> I don't want to hear a peep out of you.
51:11
>> No, I'm not having a not wasting time with an iPad."
51:14
>> No, but I mean, we we you know, step it up.
51:17
>> Uh we we've tried the the iPad here and there.
51:19
We don't we don't do it uh uh anymore, but the kid the kid is just >> the kid is just, you know, my three-year-old will just run laps around the restaurant for like two hours straight.
51:31
>> And it's cool cuz he likes to socialize.
51:33
He'll walk walk up to other tables and and like try to grab a French fry or something.
51:37
But that's a little bit >> Yeah. No, I love it.
51:39
I love with running around the restaurant just being crazy. It's so funny.
51:42
Nothing brings me more joy cuz I'm like that's what I want to do.
51:46
>> I want to get some stretch my legs right now. I don't sitting here.
51:48
Um >> my my little guy was stood up.
51:51
Uh we were at we were at uh little beach house in Malibu and he's just stood up.
51:57
We last time we were there was a Sunday. There was a DJ playing.
52:01
He just put his chair up next to the DJ stand and just stood on it. Just >> Yeah.
52:07
The the iPad thing is like a is like an endless source of trolling for me.
52:11
So the four-year-old's like, "Oh, for my next birthday, like I think I want like a tablet."
52:14
I'm like, "Oh, like what?"
52:16
like you want like cuz you know some kid like told him like that they're the most incredible thing in the world of course and I'm like yeah like like let's make one like out of cardboard.
52:23
So we're like >> I'll buy I'll buy you a CPU.
52:28
>> Six hours into a crafting project where you're like what do you want to what what do you want on the screen?
52:32
Let's draw it on with crayons.
52:35
We're just six hours into this thing.
52:37
We're like oh you want to have a He was like I want I want one for my birthday.
52:40
I was like, "Oh, so you want the you want the theme to be like tabletbased technology.
52:44
Like we'll bake you a cake that's the shape of an iPad."
52:46
And he's like, "No, I want the actual I'm like iPad cake coming your way, buddy. Don't worry about it. >> Don't worry. I got you."
52:53
>> Paperier-mâché iPad uh uh piñata that you will smash and get candy out of that we will make by hand.
53:02
>> But I think you'll have to wait.
53:02
You'll have to assemble one on your own with a box of scraps in a cave.
53:06
Now, that said, following trades or billionaire spouses with lots of children on social media isn't necessarily a retreat into the home and history, as with many objects of aspirational focus, sometimes these trends are rooted in a type of parasocial cosplay.
53:20
Exploring styles of life and livelihood that are far removed for from or will never be our own, nor do we really want them to be.
53:29
Much of the internet is consumed as if it's a type of speculative fantasy fiction.
53:34
Healey says the ballerina farm family for example represents a vision of economic security just so much diet coke clearly defined gender roles in a certain degree of purpose people might engage with it as a type of entertainment or escape but many
53:51
will also look at it and think in the real world in 2025 in no way do I actually want that why not >> I yeah >> move out to the farm >> uh >> I don't know >> the more the marrier >> more the marrier within reason. Within Within reason.
54:06
No, I do I do think it I I think that uh anecdotally from from what I've seen in my social circle outside of work, I do think that kids are 100% >> a status symbol.
54:18
I also think it's incredibly unfortunate that it's >> gotten to that point. >> Yeah.
54:24
I wish there was a Polymarket on the birth rate.
54:26
I don't know if there is.
54:27
We are of course sponsored by Poly Market and you can see the Poly Markets on the uh on the ticker.
54:32
We will we will need to spin up something.
54:36
I want to see if >> I mean there's already there's a Poly Market on on the on the Swifts.
54:39
Uh I guess I guess it would be Taylor Kelsey. >> Okay.
54:45
>> Um >> and who who is she marrying? >> Uh Travis Kelsey. >> What does he do?
54:50
>> He is uh I I think um from what I can remember he's involved in like the pharmaceutical industry. >> Okay. um >> as a spokesperson.
55:01
>> Uh I I can't quite remember, but I I think he also played um >> some some sport. Okay.
55:06
We'll have to we'll have to look into it.
55:10
>> Well, I'm sure he'll be more popular now that he's marrying Taylor Swift.
55:12
Like people probably dig into his backstory and like learn him and stuff. It'll be interesting.
55:18
We'll be following it >> for sure.
55:20
>> Anyway, let's go to this post by Young Macro.
55:22
One of my new favorite posters on the >> He's been on an absolute tear.
55:24
He has been on a tear >> and he highlights this the dynamic that he's experiencing right now.
55:30
He says, "The hyper reality version of the bedridden industrial magn magnate envying the dashing young socialite archetype is that basically every one of your billionaire idols, Elon, Teal, Para, Samma, etc.
55:42
feels intense jealousy every time they witness an Anon Zoomer surf the cutting edge of the algo purely organically. >> Donald Boat. Shout out Donald Boat.
55:50
I bet you every uh I bet you every other day they see a random zit that makes them ache to have once experienced being the guy to have posted it.
56:00
Enjoy every second of it, Anon.
56:02
You're the new maiden bathing at the village creek as the laboring brutes admire from >> this this is uh actually sort of tied to what we were just talking about. This is great.
56:14
So if you're if you're and on Zoomer out there uh surfing the cutting edge of the algo, just just know that you can parlay that into a $50 million series A if you do it right. >> Yeah, it's great.
56:25
Um well, we should move on to this story in the Wall Street Journal.
56:29
A billionaire, a psychic, and a bad investment.
56:32
The friendship breakup from hell.
56:34
Uh of course, you want to stay away from these bad investments.
56:38
You want to get on public.
56:38
com investing for those that take it seriously. Do not take it casually. take it seriously.
56:44
They got multiass investing industry leading yields. Yes. >> Not financial advice.
56:49
>> It's not financial advice.
56:51
>> We just say take it seriously and don't be a casual.
56:52
Uh anyway, a woman convinced her best friend, an aist, the Thompson Reuters empire.
56:56
We've of course had the CTO of Thompson Reuters on the show.
57:01
Didn't get to talk to him about this.
57:03
I need to have him back on >> to invest tens of millions of dollars into a crypto memecoin created by a psychic.
57:09
It went to zero, of course.
57:09
And this is in the Wall Street Journal magazine.
57:13
So over a decade, Taylor Thompson and Ashley Richardson were inseparable.
57:18
A fight over money destroyed it all.
57:19
"Oh my god," said Taylor Thompson, clapping her eyes on Ashley Richardson for the first time.
57:26
"You have those fabulous heroin chic arms."
57:29
In 2009, both women were lounging in the backyard of a Malibu home of B St.
57:36
Clair, a film producer and mutual friend.
57:38
Richardson wearing a muscle tea over her bikini.
57:40
Over her bikini uh bas in the sun.
57:44
>> Muscle tea like a like a like a stringer, you know. Okay. Kind of like that. >> Gold gym enthusiast.
57:50
>> I literally don't know the name for the nonbodybuilding version, but it's like a tank top. A tank top. >> A tank top. >> Yeah, tank top.
57:57
>> Richardson wearing a muscle seat over a bikini bass in the Sunwell Thompson sat carefully covered in a flowy outfit and hat.
58:02
Her then 10-year-old daughter clutched a hot pink mini Birkin.
58:06
Richardson, a lanky six-foot tall blonde, was a free spirit who went on to build a career designing social media campaigns for companies like Ford Motors and McDonald's.
58:12
Thompson was an airs to Canada's wealthiest family.
58:15
An eccentric with a self-deprecating sense of humor, she went to dinners and party with parties with wild hair and drapey distressed clothes by California designer Rick Owens. Give it up for Rick.
58:26
She was a subversive secret billionaire, says one mutual friend. Okay.
58:30
But a few crucial commonalities, a shared silliness, a love for animals, and a deep spirituality drew them together.
58:36
Thompson liked that Richardson had spent 5 years in India working with a spiritual leader named Amma, the so-called hugging saint.
58:42
Richardson bonded with Thompson's daughter whom she recalls as precocious and a quirky little being.
58:48
Taylor is holly gollightly, adventurous, bohemian spirit, says Richardson.
58:54
She has this big beautiful heart when she lets her guard down.
58:57
Both women have ADHD, she adds.
59:00
Because of that, I think we got each other.
59:02
>> Richardson soon became part of a small Los Angeles friend group that Thompson called her in her sanctum.
59:07
Whenever Thompson would land in LA, says Richardson, her phone would blow up.
59:10
The whim the women, often with Richardson's girlfriend, would order Nou takeout and pair it with tequila at Thompson's beach house.
59:18
Richardson made Sunday dinners and and frittatas at the airs mansion.
59:23
When Thompson had staff there, her assistants chopped onions. when she didn't.
59:26
Thompson was the first to do the dishes and Richardson taught Thompson's eager then teenage where >> daughter how to roast potatoes for New Year's Eve.
59:37
They planned a menu that included chocolates and truffles.
59:39
Also an onion to chop for caviar reminded Thompson in a text message at the time.
59:46
I can see the problem here already.
59:49
They were not doing enough data analysis on Julius.
59:52
>> Yeah, >> Julius could have changed everything in this equation. Totally.
59:55
>> What analysis do you want to run?
59:55
Chat with your data, get expert level insights in seconds.
1:00:00
>> The story would have ended here.
1:00:00
They were running their life.
1:00:04
>> If they just become data analysts powered by Julius, >> but instead we're forced to continue here.
1:00:09
Over the next decade, the friends traveled to Italy and London, bought the same via life vegan feta, and stocked up on writed hand cream. This is very random.
1:00:18
Richardson remembers the >> so many details.
1:00:22
>> Insanely unhinged article.
1:00:22
remembers the duo peeing in the bushes at a Rolling Stones concert.
1:00:27
It was Thompson's first ever What is this writing?
1:00:28
I can't even read this out loud.
1:00:31
We got to get to the part where they start slanging checks. >> Okay.
1:00:35
Uh let's let's scroll down.
1:00:38
Richardson had grown up in an affluent part of Monterey County, California, where she attended elite prep school and was skiing by age two. Crazy.
1:00:46
>> Uh but Thompson's wealth was a different ballpark.
1:00:47
We would go somewhere for a few days and she'd be buying houses like other people buy mugs.
1:00:51
though there was a lot of it.
1:00:53
Money didn't interfere with the relationship.
1:00:54
Uh the reason we'd be friends because there was no financial connection.
1:00:57
Richardson could be defensive about the way people used Thompson at the Freeze Art Fair in London.
1:01:02
Richardson recalls attendees descending on the ays.
1:01:04
People know who she is and that she will drop millions, says Richardson. It was nauseating.
1:01:09
There was one time uh there were then there were one-time friends who Thompson later assumed were were using her for her money.
1:01:16
She had a nickname for them, taker. Don't be a taker.
1:01:18
Now, the relationship between Thompson, 66, and Richardson, 47, has exploded into an epic battle that landed the pair in court.
1:01:28
But this time, the billionaire is accusing her one-time best friend of doing the taking.
1:01:32
The story is based on interviews, blah blah blah blah blah. What went so wrong? Okay.
1:01:35
By the time Thompson met Richardson, the erys had spent decades trying to prove herself to her family.
1:01:40
For the Thompson's control of the empire, passed down the male line.
1:01:43
According to people familiar with the family, Taylor, the middle child and only girl, felt less favored than her two brothers, and her efforts to forge her own path led to occasional periods of estrangement.
1:01:52
But much of the tension with her brothers revolved around money.
1:01:56
The Thompson family in 2024 was the world's 10th richest. Wow.
1:02:02
>> Give it up for the >> Let's hit the gong for the Thompson family. >> There we go.
1:02:08
>> Uh 10th richest family according to Bloomberg and Taylor wanted equal access.
1:02:12
the family holding company.
1:02:13
Woodbridge owns a majority stake in media and technology company Thompson Reuters.
1:02:16
Her older brother David is the chair of both companies.
1:02:18
Thompson pursued a career in acting training at the American repatory theater in Cambridge.
1:02:23
She performed with Shakespearean theater companies in Massachusetts and Los Angeles and had roles in in the TV show Matrix.
1:02:28
Canadian >> drama show >> Canadian drama Forever Night about a vampire working as a detective. That's very cool. >> Big into TV. Maybe you should go.
1:02:38
>> No, no, I'm not big into TV. I'm a cophile.
1:02:40
Uh Thompson often suspected people were trying to use her for her money.
1:02:45
According to people that know her, she insisted those around her sign non-disclosure agreements from assist from assistance to an ex-boyfriend of her then 20-year-old daughter.
1:02:52
And she could get get aggressive if she if she thought those terms were breached.
1:02:57
Thompson even hired an infamous Hollywood private investigator, Anthony Pelicano, to spy on her former nanny, who she suspected of sharing personal information with her daughter's father during a custody battle.
1:03:07
I want you to do whatever you can to get information on Pamela.
1:03:10
Uh said Thompson to Pelicano on a recorded call played during Pelicano's 2008 wiretapping trial after which he was convicted. Just get it.
1:03:17
I'm not going to ask questions. It's crazy.
1:03:21
Uh by the fall of 2015, Thompson and Richardson's friend St.
1:03:23
Clair were losing their battle with ovarian cancer.
1:03:27
Her closest friends surrounded her in her final months.
1:03:28
Richardson and her partner at the time had weekend slumber parties at St. Clair's ranch home. St.
1:03:34
Clair's producing partner, Pierce Brosman, then came by. Okay. Wow.
1:03:35
Um, Thompson decorated for Christmas with Dr.
1:03:40
Se's original Grinch sketches from her personal collection.
1:03:41
Okay, we got to get to the crypto stuff.
1:03:43
There's some crazy stuff in here.
1:03:45
Let's just let's just keep keep scrolling. Uh, keep scrolling. Keep scrolling.
1:03:50
Uh, Thompson spoke said, "This is all false." Blah, blah, blah.
1:03:55
>> Then yes, Richardson's work was drying up.
1:03:58
In a fit of anxiety, she Googled a burning question.
1:03:59
Had anyone predicted any of this?
1:04:01
She stumbled upon Michelle White, a celebrity psychic.
1:04:03
She dropped $25 a month for White Dove's newsletter, then largely ignored it until the spring of 2021 when she noticed the psychic had recommended a new crypto token.
1:04:14
Persistence, White Dove wrote, "This is another dark horse that's going to come up on everybody and be a big dog.
1:04:20
>> Big dogof, get it and sit on it, which is what I would tell myself."
1:04:25
The value of Persistence's token called XPRT quadrupled from less than $3 in April to as high as $13 by the next month.
1:04:33
That summer, Richardson brought up White Dev's predictions to her friend.
1:04:37
What is the link to that website of the channeler? Thompson texted.
1:04:41
She followed up with Robert Robert Sabella, an astrologer and intuitive she regularly consulted.
1:04:48
Combining astrology and crypto is >> so good.
1:04:52
It's a match made in heaven. >> Absolutely. >> More do you need?
1:04:54
um an intuitive she regularly consulted for advice both personal and financial.
1:04:59
Once when Thompson tried a Xanax after a panic attack, she asked Sabella for his thought.
1:05:04
He replied, "I'm getting that Xanax is not good for you right now.
1:05:07
Stop taking it and find another I mean fair advice."
1:05:11
He also weighed on her investment >> blazing there.
1:05:13
You know, >> those answers I promised you, >> right? >> Yeah.
1:05:17
>> Uh he said, "But other coins show promise.
1:05:20
ADA has a very high reading on it, a 10.
1:05:23
persistence does as well, even higher. >> Oh, no.
1:05:26
>> And so they're using the astrology readings for as financial advice.
1:05:33
>> So with Richardson's help, Thompson invested more than $40 million in messages after the initial purchase.
1:05:38
Richardson cheered Persistence's early success, but at times she pushed back at Thompson's request, including when she when she suggested buying 60 million of the token.
1:05:47
Are you sure you want 60? I will try.
1:05:49
Still think you should diversify?
1:05:50
Richardson wrote her that same day.
1:05:54
>> Thompson and Rich told Richardson that uh she would seek access to what she viewed as her share of the family money.
1:06:00
I'm going to write to my brothers directly.
1:06:02
David and Peter Thompson wrote as you know uh as you uh as I know you both are more than aware our family branch uh Thompson and her daughter has been completely locked out of our any voice of control of stewarding our future financial wealth.
1:06:17
She acknowledged having always been one for riskier investments like the rest of the than the rest of the family.
1:06:25
Uh but said she had been exposed to valuable opportunities like crypto.
1:06:29
Uh she accused her brothers of discrimination.
1:06:34
The 2020 the 2020 infrastructure around my family branch and the inherent restrictive compliance which was put into place completely removed any opportunity of me stewarding meaningful investments.
1:06:44
To be blunt, it is no longer acceptable.
1:06:46
For the next several months, Richardson spent as many 20 hours as many as 20 hours a day hunched over her laptop researching cryptocurrencies and executing trades for Thompson.
1:06:55
Richardson says Thompson provided in instructions over daily hours long phone calls and messages.
1:07:02
They just become a hedge.
1:07:04
>> They're just day trading. This is crazy.
1:07:07
Richardson, they get into physical custody.
1:07:08
Look, Richardson stored physical wallets like USB- like devices holding millions in crypto around her home, including at one point in her then partner's underwear drawer.
1:07:18
Richardson, who whom Thompson didn't pay and who has no financial background, says that moving that money was exhilarating and stressful and then deil debilitatingly scary.
1:07:28
>> So, at this point, they're managing $140 million in crypto.
1:07:33
>> That is >> based off of astrology persist.
1:07:33
I I looked up the chart for XPRT, the one they tried to put 40 or 60 million into.
1:07:41
>> At the time that they were investing in it was about, I guess, $3 per token.
1:07:43
Now it's sitting at >> uh uh less less than three cents.
1:07:51
>> Less than three cents. >> Yeah. But >> wow.
1:07:54
That that that is like a complete and total loss. Like wow. They had 140 million.
1:07:58
They probably walked away with like 140,000. That's really bad.
1:07:59
Uh, today Richardson is driving an Uber up and down California Central Coast, a job she took to make ends meet.
1:08:07
I had this charmed, magnificent life.
1:08:09
She sounds ejected and wistful.
1:08:11
Her life wasn't charmed because of Thompson.
1:08:13
She now says, "But in spite of her, she had a lively community of friends in Los Angeles, a partner she loved and a thriving career.
1:08:22
There were dinners and parties."
1:08:24
She says, "A chosen family that included Thompson and her daughter.
1:08:27
I don't look at them and say bad people.
1:08:29
I look at them and say, "This is the catastrophe of having having money."
1:08:32
Now, she lives in her childhood home in Monterey County.
1:08:33
A private investigator's unannounced visits to the home of her mother and stepsister this August has led her to worry for her family said, "I was hired by Taylor Thompson," says Richard's mother of the woman, a former FBI agent who now works for the consulting group Guidepost Solutions.
1:08:49
Richardson has applied for food stamps.
1:08:51
She can't afford paid medication for her dog Jasper.
1:08:52
She is buried in legal work. >> Wow.
1:08:55
This story has been a disaster.
1:08:58
>> She lost more than $80 million in crypto associated with Richardson's involvement. Thompson did.
1:09:02
Uh asked about the private investigator.
1:09:05
A Thompson spokesman said Guidepost was making continued efforts to recoup the tens of millions of dollars from of Mrs.
1:09:13
Thompson's of Miss Thompson's money under Miss Richardson's control because of course um uh any one of those thumb drives could still have like a bunch of Bitcoin on it that you like forgot to sell or trade into something else.
1:09:24
And so uh whenever a crypto deal happens there's always a lot of like exhaust knock nonsense going on.
1:09:30
Uh, Persistence apparently rewarded Richardson by giving her a secret kickback of 783,72 worth of XPRT, the lawsuit alleged.
1:09:41
So, uh, they were like, "You're bringing us a whale.
1:09:45
We'll kick you back something, which is not good, and you need to disclose that obviously if you're getting commissions or something like that.
1:09:52
You're not acting as a fiduciary.
1:09:54
You're also not licensed or trained or, you know, have any reason to be doing this." But, uh, what a mess. >> Yeah.
1:10:01
The lesson is >> Would have hoped there was a white pill in here, but I think uh it's just total disaster. >> Total disaster.
1:10:07
Should have gone long tea bells instead. >> Wow.
1:10:12
Uh friend friend of the show just texted me something very funny about uh about this story that I cannot read off without completely >> doxing someone. >> Doxing him.
1:10:23
But uh >> this this goes deeper than we thought. >> Okay.
1:10:28
Um, but anyways, let's move on to the next story.
1:10:30
This uh was a total black pill, but anyways, if if the uh I guess moral of the story, don't day trade crypto, don't day trade your friends crypto based on um your astr uh astrological readings. >> Yes.
1:10:48
>> And yeah, just >> stick to betting on horses. >> Trust the experts.
1:10:52
Really >> go down to the track.
1:10:54
I mean it seems like stick to real estate like you know she was known for just like buying houses on a whim and that seems like kind of ridiculous and hard you can overpay for something but I bet almost all of those have been yeah very have done very well even since the real estate market's been booming.
1:11:09
Uh anyway Pavle Asparu friend of the show says Travis uh Travis Kalanick's corporate catering service is insanely good.
1:11:19
Cloud Kitchen faux Chipotle is better than Chipotle.
1:11:21
Delivery is the the exact same time every day without fail.
1:11:26
Cheaper than competition. TK is a beast, man.
1:11:29
>> I mean, we got to get this fix.
1:11:29
Grace has been >> devastating.
1:11:36
>> This could be the thing that gets us from 100K to a million.
1:11:40
>> Devastating for many technology brothers out there that that used to be able to rely on uh on quality meal. Yes.
1:11:48
>> Uh and it has just gone down the drain.
1:11:50
>> You know, the problem is with cloud kitchens, not very good uh name recognition very much under the radar.
1:12:00
They need to get Travis needs to get on profound.
1:12:03
He needs to get his brand mentioned in chatbt.
1:12:04
He could reach millions of customers who are now using AI to discover new products and brand.
1:12:11
>> We got to try this out.
1:12:12
>> Um there's another post from Poly Market in here. breaking.
1:12:14
Bitcoin is now predicted to crash below $100,000 this year. 67% chance before 2026.
1:12:24
>> I mean, Bitcoin's 110.
1:12:24
Um, I I remember this this viral video of like uh Bitcoin goes up and then it crashes down to $100 and then it crashes down to $1,000 and it crashes down to $10,000 and then it crashes down to to $100,000.
1:12:39
It's like we're kind of using like silly terms for like what is like a pretty remarkable rise over a very long time.
1:12:48
>> Y >> um anyway, I'll leave it to my astrologer juror to decide whether or not I should buy or sell Bitcoin. Just kidding.
1:12:55
Not today that >> uh Nick here has an has a very funny post.
1:13:00
Um we uh there was a new uh Google image generation uh product released today. It's very cheap. It's very good.
1:13:09
And Nick is >> what a great name.
1:13:11
>> Uh always taking advantage of the moment to to post a funny picture of Sam. >> He loves it.
1:13:16
>> But this is a good meme for him.
1:13:17
>> Where did he get this from? Sun Valley or something. >> Yeah.
1:13:20
>> He he went deep in the uh >> in the archives. >> Yeah.
1:13:23
In in you know, some paparazzi uploads a bunch of photos and Nick finds the the most ridiculous one.
1:13:27
Um but it is interesting to see the the cost of these different models.
1:13:32
Um, you know, if you're doing high volume image generation, probably makes sense to check out Google's offering.
1:13:39
>> And we will have Logan joining. Oh, yeah.
1:13:42
To today release uh state-of-the-art image generation editing, incredible character consistency, lightning fast, and available uh in AI Studio and the Gemini Gemini API today. >> Fantastic.
1:13:54
In other news, Alex Wang has unblocked Yakine.
1:13:56
This is shaking up the timeline.
1:13:59
Maybe we need a trading card. Unblocked. >> Unblocked.
1:14:02
It is huge news in the tech world.
1:14:06
Uh so um >> there's big things coming says, "Can someone tell Alex Wang to unblock me?
1:14:13
The reason I was being annoying was because of the whole MEI thing."
1:14:15
Because the whole MEI thing was sensitive to me, but now that Zuckerberg crowned him the king of AI, I actually think it's really bad for my career that he doesn't like me.
1:14:25
And so And so >> we gota we got to get a yes up.
1:14:28
Gotta get him back on the show. >> Yeah.
1:14:31
So, Bone GBT uh messages Alex Wang and says, "Please unblock Yakine. He's very sorry.
1:14:37
Thank you for your attention to this m matter."
1:14:38
And Alex Wang says, "Unblocked." Lol. I love it.
1:14:41
Uh and and Bone says, "You must send a raven to run for me."
1:14:49
That means uh >> good post here from High Yield Harry. >> Do we have the video? Can we pull?
1:14:53
We have to pull up the video.
1:14:54
In the meantime, let me tell you about numeral sales tax on autopilot.
1:14:58
spend less than 5 minutes per month on sales tax compliance. Go to numeralhq.
1:15:01
com and uh >> I got video here.
1:15:06
This is of course Mike O'Harn, the famed bodybuilder and uh known for for memes and video reactions around the around the internet. And here he is. We need the audio, too. The audio.
1:15:24
>> Are you following generally accepted accounting principles?
1:15:28
[Music] Ga Chad just like I'm just smiling. I just look good.
1:15:37
Like what what are you asking me? I don't care.
1:15:40
>> Just look at the chart. >> Yeah, just look. It's fine. Don't >> It's all good. Stop.
1:15:44
Stop asking me questions.
1:15:46
Yeah, this guy is just born for the internet. Uh absolutely fantastic.
1:15:51
Uh anyway, in other news, Mark Zuckerberg gifted noise cancelling headphones to his Palo Alto neighbors because of the non-stop construction around his 11. So thoughtful. >> This is awesome.
1:16:00
Chris Baky says, "This is so funny. I'm deeply sorry.
1:16:02
I've been jackhammering the concrete of my old wave poolool to build a new wave pool for the la for the last few years at my 120 million home, which is next to your 18 million home $18 million home.
1:16:12
In order to remedy the situation, I've gifted you these $199 headphones." Who knows?
1:16:18
>> I think it's a thoughtful gift. I think. Yeah.
1:16:20
It's the It's the least you can do.
1:16:21
>> It's a thought that counts.
1:16:21
He's like, >> "It is the thought that counts.
1:16:24
>> Eventually, the jackhammering will end."
1:16:26
>> Hey, I mean, are you is it time to build or not? >> Yeah.
1:16:30
>> Throw on the gauntlet. >> Yeah.
1:16:31
Just say I mean, if you're angry about this, just say it's not time to build. >> Yeah. Just Just say.
1:16:36
>> Just say you're anti- re-industrialization. >> You're anti-growth. >> Yeah. You're degrowthther.
1:16:39
You're a degrother if you're not into growth.
1:16:40
Uh anyway, in other news, >> this has been this is >> Cadillac is coming to F1.
1:16:47
Most >> important story of the day. >> This is huge. This is huge.
1:16:49
Sergio Perez is returning to F1 to drive for the Cadillac team joining the grid in 2026 along with Valtry Bas sources told particularly important for John who dies a Cadillac Blackwing.
1:17:04
I do much like Zuckerberg >> been waiting does. >> Yes. Yes.
1:17:09
If you want an Americanmade If you just have a few uh like you know requirements in your daily, you want it to be Americanmade, you want them to have an F1 team, you want to have a supercharged V8, like there's really only a few cars that fit that >> that fit those like those those basic criteria options >> and so it eliminates a lot of other options.
1:17:29
>> Pretty much everything. >> Yeah.
1:17:30
So you you kind of force force my hand on that one. >> Totally. Totally.
1:17:33
Uh and the different uh Sergio Perez had like this very like serious announcement and and Boaz just just posted him in a tuxedo with an American flag.
1:17:44
>> The tuxedo with American flag too.
1:17:48
He has a water bottle or something or it's a green can of beer or something, but it's like it's unbranded. It's fascinating.
1:17:54
>> Very interesting stance on the on the >> I have to admit the first time I saw this picture of Sergio Perez, I thought it was the guy from Fire.
1:18:00
No, I thought it I thought it was Billy McFarland.
1:18:05
>> Why did you think that?
1:18:06
>> Billy McFarland looks kind of like that. >> Don't you think? >> Interesting. >> I don't know.
1:18:10
Maybe I'm Maybe I'm crazy. >> Anyway, Finn.
1:18:12
AI, the number one AI agent for customer service, number one in performance benchmarks, number one in competitive bakeoffs, number one ranking on G to all eyes on 2026.
1:18:23
>> Their driver lineup is locked in.
1:18:23
I can't wait to see an American team.
1:18:27
>> And they're going to be working with Tommy Hilfiger. >> Oh, really?
1:18:29
And so this is this team is gonna be very very American. >> Very fun.
1:18:34
Yeah, this is a good opportunity for you know uh Trey was taking shots at Palunteer, his former employer because Palunteer sponsors an F1 team.
1:18:42
And sponsors a NASCAR event.
1:18:42
Um this is the this is the chance if you're a re-industrialized company, if you're an American dynamism company.
1:18:51
uh getting your logo on the Cadillac F1 car feels extremely high ROI. >> Yeah.
1:19:00
>> You know, it's probably not going to price like Red Bull, like Ferrari.
1:19:01
Uh but it will certainly get a lot of attention, especially online.
1:19:05
And then you'll fill up the top of the leads bucket.
1:19:09
You'll be able to put everyone's information in Adio.
1:19:11
It's customer relationship magic. >> That's right.
1:19:15
>> Adio is the AI native CRM that builds, scales, and grows your company to the next level.
1:19:18
>> The founder of Adio will be joining to talk about their new round later today. excited for that. >> Um um what else?
1:19:24
>> And we have a post here from Mike uh Anutia.
1:19:28
He is uh highlight highlighting an article from Bloomberg.
1:19:31
Data centers to propel infraurizations past 110 billion by 2026.
1:19:36
Uh we had been joking about data centers crashing the global economy.
1:19:43
Uh was it last week or the week before?
1:19:46
Hopefully doesn't happen.
1:19:48
But uh the tech lash >> someone was saying that that that that Mark Zuckerberg has the ability to crash the economy with how much he's spending on uh on capex.
1:19:55
But I don't I don't know.
1:19:59
Yeah, I think that's a Derrick Thompson take that uh the economy is data centers and dialysis.
1:20:03
It's kind of an interesting take but um the the I don't know the data center buildout like the capex numbers are growing but they're not 10xing yet.
1:20:12
I mean, even the most AGI pled folks are like the training runs will increase by 3x the size per year.
1:20:19
Like that's a ton, but uh we're still early and like all the capex numbers are growing, but the cloud bills are growing as well.
1:20:28
Like there are some crazy deals out there, but um it's certainly not the size of the mortgage market yet. >> Yeah.
1:20:35
And the big question is how quickly will these assets depreciate?
1:20:39
There's some conservative estimates.
1:20:41
There's some very extremely bearish estimates. >> Yeah.
1:20:44
>> Bloomberg is reporting the market for securities backed by various digital infrastructure including data centers could grow by 46% by the end of next year to roughly 115 billion.
1:20:51
Data centers account for 61% of the current $79 billion market for digital infrastructure securizations according to business uh bank of America.
1:21:00
Uh fiber infrastructure makes up another 20% while cell towers are at 18%.
1:21:05
The estimates take into account both assetbackedback securities and commercial mortgage backed securities.
1:21:12
Companies have been developing large data centers to help support demand for AI and banks as well as private lenders have been competing to underwrite such deals.
1:21:19
Meta uh platforms picked Pacific Investment Management and Blue Al Capital to lead a $29 billion deal for its data center expansion in rural Louisiana.
1:21:28
JP Morgan Chase and Mitsubishi Financial Group meanwhile are leading are are leading a loan of more than 22 billion to support Vantage Data Cent's plan to build a massive data center campus.
1:21:40
center campus. investors concerns about the development of data centers, cloud adoption and the path of investment in AI have been um you uh have been sorry cut off um >> the four big data center developers in particular Microsoft, Alphabet, Amazon
1:21:59
and Meta Platforms discussed higher cloud business revenues and reiterated plans for capital spending increases risk premiums on all three types of digital infrastructure ABS data center fiber and cell towers have tightened significantly over the past two years. While BFA strategists expect limited
1:22:13
While BFA strategists expect limited spread tightening going forward, they see such securizations as offering attractive relative value compared to other types of ABS. So, >> okay.
1:22:24
So, uh there's a post that I found through a Martin Skrey quote tweet.
1:22:29
Uh congratulations again to Martin on becoming a father.
1:22:32
Um but uh it starts with this Cuppy's Corner post, Global Crossing is reborn.
1:22:37
And it's a picture of Mark Zuckerberg.
1:22:39
I got a fever and the only prescription is more data center buildout.
1:22:42
Um, micro cap David says, "This is insane.
1:22:45
I had no idea it's this bad." Shares this post.
1:22:47
Uh, which leads you to the first shocking revelation.
1:22:50
The AI data centers to be built in 2025 will suffer 4 40 billion of annual depreciation while generating somewhere between uh 15 and 20 billion of revenue.
1:22:59
The depreciation is literally twice what the revenue is.
1:23:01
Um, Global Crossing uh was started in 1997 and it's like it's the textbook example of like the dark fiber overbuild.
1:23:09
So, uh, the main business was a global fiber optic network.
1:23:15
They wanted to sell wholesale bandwidth width to telecom companies uh, in the '9s.
1:23:19
Uh, it completely mooned.
1:23:22
The market cap was over 47 billion around 2000.
1:23:24
Didn't really have that much profit, but it was like key infrastructure for the new economy.
1:23:30
the bubble burst and they had already spent a lot of money to lay cable uh but the demand for bandwidth was far lower than expected.
1:23:36
The company filed for bankruptcy in 2002 and so a lot of people lost a lot of money and that's what people are uh that's what people are meing around.
1:23:44
Uh Martin Skrey has a take here.
1:23:46
He says so this assumes $400 billion spent on AI data centers.
1:23:53
So much of this math is wrong.
1:23:53
A100s have depreciated 50% after five years, not 10% after three to five.
1:23:58
Um, a B200, which will depreciate over 10 over 8 to 10 years, costs roughly $62,000.
1:24:05
Uh, 500K for eight, you can produce some amount of human-like intelligence with this machine.
1:24:13
Would you pay for aroundthe-clock always improving human level intelligence for 8,000 a year? $8,000 a year.
1:24:21
chips are a much bigger percent of the cost than implied here.
1:24:25
So this breakdown says like it's a third depreciation, a third energy, a third GPUs or something like that.
1:24:29
Uh which I think is not quite right.
1:24:31
Um so Scrowley's putting it in the truth zone, but obviously it is worthwhile to like reality check the the the the overbuild.
1:24:41
You don't want to get over your skis too much, but uh at the same >> at the same time, bubbles are important.
1:24:46
>> Bubbles are important.
1:24:46
We get a lot of uh a lot of capacity to build the next thing.
1:24:50
Joe Weisen Weisenthal hit the timeline at 3:00 a. m. this morning, I guess.
1:24:56
Or no, >> he wasn't sleeping on a sleep, but you can be. Go to eightsleeve. com.
1:25:00
Get a pod 5 with a 5year warranty, 309 risk-f free trial, free returns, free shipping.
1:25:04
U Joe, I have to assume it was actually 6:30 Eastern. Okay, he's up early.
1:25:10
So, he's just up early posting.
1:25:12
He said rather than take equity positions, and he's talking about the Intel deal.
1:25:18
Rather than take equity positions in private companies, perhaps the government could confiscate 20% of pre-tax earnings.
1:25:24
And then when it comes to control, Congress could pass laws governing corporate behavior.
1:25:30
There could be something >> could be something here. Fantastic post.
1:25:35
>> Um Gregory replied, uh that is just the beginning.
1:25:38
Your scheme could be expanded to confiscate a quarter of any increase in the value of those companies when people sell their shares. Okay. Interesting.
1:25:48
>> Another another potential play here.
1:25:50
>> Yeah, this is interesting.
1:25:50
I think we're getting somewhere.
1:25:53
>> Um there was an interesting um post here earlier.
1:25:57
Dan Primac >> uh highlighted that uh Trump's Pentagon is thinking about taking equity stakes in defense contractors according to Lutnik.
1:26:08
So >> um >> they're going all over.
1:26:11
>> They're doing they're they're they're fending.
1:26:14
>> They're in deal deals mode. deals mode.
1:26:17
>> Uh Lutnik was on Squap Box with Sorcin earlier and what >> someone apparently the team put up breaking news from TVP and Taylor Swift engaged and somebody quote tweeted Connor quote never in my life did I think I would find out about Taylor Swift getting engaged via TVPN notification.
1:26:39
>> I mean she's a billionaire and she's a private jet enthusiast, right? Yeah.
1:26:43
What else do you >> Why would we not be highlighting that? >> This is fantastic.
1:26:46
>> She's a incredible entrepreneur. >> Yeah. >> An artist. >> This is great.
1:26:51
Um anyway, uh should we do this five span stake in the New York Times? This activist investor.
1:26:56
This is kind of interesting. Bloomberg has a story.
1:27:00
So, uh, the financiers that led a high-profile activist campaign at the New York Times three years ago have now taken a stake in the iconic newspaper via new investment firm, FiveSpan Partners.
1:27:12
Um, >> New York Times, Mike Isaac, your favorite activist is back. They missed you guys. >> Yep.
1:27:19
Uh so the the activist investment firm started last year by Dylan Haggert and Sarah Coin has built a position in the times and is pushing it to use artificial intelligence to expand its subscription base.
1:27:30
According to a letter uh the pair >> they're just like every VC write a check.
1:27:36
Hey, you guys should be using AI.
1:27:38
I've heard a lot about it.
1:27:38
I think I think there could be something here.
1:27:41
>> AI is a clear tailwind for the New York Times.
1:27:43
Our work shows it can more than double the company's long-term revenue and profit potential, enhancing growth by reaching broader audiences, converting more readers into paying subscribers, and unlocking new lucrative profit pools.
1:27:54
What's the What's the steel man for this?
1:27:55
I think that if the New York Times goes AI slot mode, uh, it's very bad.
1:28:00
It's a very short-term win.
1:28:03
>> Well, they're saying >> they're talking about >> using it to more, I guess, more efficiently convert nonpaying. They're saying >> Yes.
1:28:12
So, >> the Times could use AI to broaden its international reach, lowcost text and audio translations. That makes sense.
1:28:19
Develop develop more dynamic pay walls and optimize pricing. >> Yep.
1:28:23
>> Lowcost video offerings could also boost revenue per user according to FISPAN. >> Yeah.
1:28:27
And so, so AI doesn't necessarily mean LLMs generating text of articles, but translation nailed, audio nailed, and already uh I don't know why you're laughing.
1:28:40
Well, I just I think it's I think it's pretty funny >> to just we we should do this bit with with uh with TB T Nation where we collectively take a stake in something like a Google and tell them that AI we think AI is very important.
1:28:57
>> We think it could be good for your business.
1:28:58
We'd like you to take this seriously. >> Yes. Yes. Yes.
1:29:02
>> Hey Satia, we're going to take a position.
1:29:04
We've taken a position at Microsoft. >> Our whole team. >> Yeah.
1:29:08
>> And we want you to take this seriously.
1:29:10
The ask if we're if we're being activist investors in Microsoft. I know the ask. Bring back Clippy. Bring back Clippy. >> Clippy. Is Clippy still around?
1:29:17
Can you find him anywhere?
1:29:20
>> I think there's some merch out there, but Clippy is not productized.
1:29:22
Clippy needs to be >> That is That is a billion dollar IP locked in.
1:29:29
>> Imagine a billboard campaign on adquick.
1:29:31
com centering Clippy as the new spokesman for Microsoft.
1:29:36
>> Out of home advertising made easy and measurable.
1:29:37
Say goodbye to the headaches of out of home advertising.
1:29:38
Only Adqubines technology, out of home expertise, and data to enable efficient, seamless ad buying across.
1:29:44
>> Clippy should become CEO for a day as like a little stunt. Give Sati the day off.
1:29:49
Let Clippy run the show for a day. Just one day.
1:29:51
>> Got to We got to bring back Clippy. It's so good.
1:29:53
It's such good lore and it's so fun. It's cute. It's like inoffensive.
1:29:57
It's the perfect It's the perfect mascot. >> Yeah. actually see.
1:29:59
So, so we've been joking around about five spans uh ask, but I think it is uh I'm happy to see that they're not saying, you know, lay off, you know, uh two >> AI will will definitely not be able to do the factf finding that the New York Times does.
1:30:15
Like journalists are particularly good at that.
1:30:16
Uh and it it requires like building a relationship over time, getting someone to share a piece of information that you can then verify.
1:30:25
That's really intractable for AI.
1:30:27
And then even the instantiation, you know, Teal has that line about like uh like AI will hurt uh math people more than writers, which is kind of counterintuitive because you'd think that well AI is really good at writing, but AI is not actually that great at writing and you can still clock it when there's the M dash and >> we saw this.
1:30:48
>> It's not this, that's that, that >> Travis Kelsey Taylor Swift announcement. >> Go into Chad.
1:30:53
>> It's not just a marriage. It's a love story. It's a list.
1:30:56
>> That's That is [ __ ] >> What's problem?
1:30:58
The problem is like people do write like that every once in a while like but now you just can't you can't use those. It's not this than that.
1:31:04
>> They hit chap they think so. You're convinced.
1:31:07
Put on the tin foil hat, Jordy, if you're going to make that strong of >> We got to keep it closer. >> We do.
1:31:10
We need the we need the hat rack over there.
1:31:12
Uh a representative from San Francisco based Fiverspan declined to comment.
1:31:16
That's the most boring line I could possibly read in this article today.
1:31:19
We believe AI represents tra uh transformation opportunity.
1:31:21
There is something interesting here about uh instantiating lowcost video.
1:31:24
So um the the the New York Times will occasionally take a story if it's really big and turn it into a video like a video essay.
1:31:31
And they could probably do that for more content where they take the video or they take the facts that have been found by a human and the writing that's been found by a human and then use an AI voice and then use AI to select different stock imagery or generate images.
1:31:46
>> So five saying they could slop it up.
1:31:48
Yeah, they would be slopping it up, but it would probably be like value additive to just like get the stuff.
1:31:53
You know what they should do?
1:31:55
They should do the clipping strategy.
1:31:57
They should take a position in the New York Times and be like, you need 500,000 clippers.
1:32:00
You need to just be clipping everything.
1:32:03
You just need to clip it all over.
1:32:05
This is the this is the thing.
1:32:07
Maybe that's the strategy for Clippy.
1:32:09
Clippy will clip your content. Clippers.
1:32:11
So, so, so you do a campaign for for Clippy and then you have [ __ ] clip it all over Tik Tok and then and then you buy Tik Tok.
1:32:18
Uh, anyway, um, we went through the family stuff.
1:32:24
Let's go to this uh this gentleman over at Whimo, Ethan.
1:32:27
I love the Whimo team posting.
1:32:29
Everyone in Google feels like they're they're getting more comfortable on the timeline right now.
1:32:35
I don't know if they're just emboldened, but they're now they're posting. >> Exactly.
1:32:40
They they've been kind sort of building in silence, but now they're getting out there.
1:32:43
So, uh there's a video of a Whimo on the 101 driving from San Francisco to San Mateo.
1:32:47
Uh rider only, doesn't touch the steering wheel. Very impressive.
1:32:52
Uh congratulations to the team.
1:32:54
And Ethan at Whimo says, "Multiple sensors together is a fool's errand.
1:32:59
What do you do when the sensors disagree?
1:33:01
Surely no one has solved that.
1:33:04
Anyway, here's one of our freeway rides that don't count in our 1 million plus fully autonomous paid rides per month because freeways are for employees only for now. >> Interesting.
1:33:14
>> Um, interesting that they're not doing freeways because um the the risk of serious injury is much higher on a freeway because you're going much faster.
1:33:22
So, Mercedes has done the same thing with their level three autonomous system that only works in like stopand go traffic, I think, or like under 40 miles an hour because with the modern seat belts and airbags, like it's really really hard to get into a serious serious like injury accident if you're just going 35 miles an hour.
1:33:38
So, the Whimos can kind of drive around. It's much lower stakes.
1:33:41
Um, but they're testing it and they're going to be bringing them onto the cool video.
1:33:46
>> Um, so congrats to everyone over there.
1:33:48
Um on the COGS debate, uh Tan shared a chart of marginal differences AI startups recent gross margin.
1:33:55
>> This is where high yield Harry pulled that video of of Michael like Hearn for sure.
1:33:59
So Enthropics at 60%, Perplexity is at 60%, OpenAI's at 50% gross margins, stack blicks at 40, lovable at 35, and Replet at 23.
1:34:10
>> And there's an important note here. >> There's a note here.
1:34:11
Perplexity, Replet, Lovable, and Stack Blitz do not incorporate the cost of running AI models for non-paying users and calculations while OpenAI does.
1:34:23
>> Enthropics Oh, Enthropics accounting accounting couldn't be learned. Interesting.
1:34:27
So that's why >> which I think is fair.
1:34:30
They don't they don't need to I mean it's not anthropics job to tell journalists what their approach to accounting. >> Well, you know what?
1:34:40
We have the perfect guest to talk about building a business without burning a ton of cash because we have Wade Foster from Zapier Zapier here in studio. >> French pronunciation.
1:34:54
>> I you know you were in my YC batch in 2012 and and I called it what did I call I called it Zapier like a rapier for a long time and then and then people were telling me that's wrong and so I started calling Zapier and then I learned that was wrong.
1:35:08
But it's Zapier like Snapier, right? >> Yeah, Zapier. It's funny.
1:35:11
Snapier was actually what we called it first.
1:35:13
We Yeah, we had to switch to Zapier because there was, >> you know, uh, copyright issues like >> and of course it was one Snapier with one P and so we just doubled down on the mistake and went Zapier with one P as well.
1:35:28
>> It certainly hasn't hurt the business.
1:35:29
You've you've been on an absolute tear.
1:35:31
uh we've enjoyed uh talking to your co-founder a ton about uh ARGI and that stuff, but we'd love to get uh I I just into the rest of your world and what's going on with the business and um do you have any advice for uh uh current generation startups who are maybe playing a little bit fast and loose with the accounting?
1:35:46
Um did you ever have gross margin problems?
1:35:49
Was there ever a moment where you were like, "Okay, like we have customers that are actually making so many calls to our APIs that we're losing money on them."
1:35:59
Or was that just never an issue?
1:36:02
>> We became profitable in 2014, so basically two years in. And >> congratulations.
1:36:09
>> When we raised the uh Yeah.
1:36:09
When we raised our seed round out of YC, >> yeah, >> we said, "Hey, uh we want this to be the last money we ever get." Mhm.
1:36:17
>> And so I I like looked at every expense on our P&L and approved everything and was just like vigilant about not spending money if we didn't have to.
1:36:27
>> And um >> you know I think in 2010 like that decade we were looked like as crazy. Totally.
1:36:34
>> And now it's very trendy.
1:36:34
Like in fact I heard uh this term popularized I don't like six months ago seed strapping.
1:36:40
>> Seedpping where it's like yeah one round and then you know don't raise more. >> Okay. So that's what we did. >> Yeah.
1:36:46
Did you believe it at the time?
1:36:46
Uh were were there specific uh entrepreneurs that you were looking to as like mentors?
1:36:52
Like where did that idea even come from?
1:36:54
Because the meme in Silicon Valley at the time was much more on this on the Reed Hoffman blitz scaling raise a ton of money and every venture capitalist would echo that because they want to put dollars to work.
1:37:05
Uh and so there was definitely like a a mood in Silicon Valley of like hey it's more than okay to raise an A B C D burn burn win.
1:37:12
Like did you believe that when you said it or did it come from somewhere like talk to me about the the thinking at the time? >> We had two examples.
1:37:21
So we founded the company in central Missouri.
1:37:24
All three of us worked at Veterans United.
1:37:26
This is a company owned by two brothers 50/50.
1:37:31
They never raised a dime.
1:37:32
>> I was employee 500 and when I left 10 months later there was a thousand employees there.
1:37:38
>> So this company scaling like crazy with mortgages >> during the financial crisis. >> Wow.
1:37:43
And so we see that and are like, well, clearly you can build a successful company this way.
1:37:48
Then one of our favorite products, Mailchimp, they were one of like our earliest partners that was most successful, entirely bootstrapped.
1:37:57
>> And then coming from the Midwest, we're just we just don't know anything about like this Silicon Valley world for how to build companies. >> Yeah. >> Yeah.
1:38:03
And so it kind of makes us skeptical of anytime, you know, a venture capitalist is Yeah.
1:38:09
I remember one said, "No important company has ever been built this way."
1:38:13
And you know, when you make grandiose statements like that and you have counterfactuals, you're just like, "Well, what other advice are they saying that might just be wrong?" >> Yeah.
1:38:24
>> Uh and it doesn't mean that all the advice is wrong.
1:38:26
But I think we just ran it through a thicker filter than most people who are like, "Well, I guess we're going to raise an A and a B and a C."
1:38:32
But I think it's important it it doesn't my read and I guess what I've heard over the years is it's not like you said we will never raise another dollar.
1:38:41
It was more so we we hope to just make a great business and not be forced to.
1:38:47
And I think the issue when I hear people talking about seedstrapping it's like seedstrapping I don't know if it's like the right goal.
1:38:54
It can be something that you hope to be able to achieve, but if you're raising a $5 million round and you're telling everybody, "Oh yeah, we don't want to raise more money."
1:39:04
It's just like not the right oftentimes not the right thing to be fixated on.
1:39:07
to be fixated on. It's like be fixated on like we want to use this money to find a really sound business model that will allow us to scale efficiently and we will tap capital markets as needed is like a better goal than oh we just don't want to raise more money and because I usually feel like that comes from
1:39:25
founders that are like you may as well just say I don't want to dilute myself anymore >> and that's not necessarily the right thing because ultimately >> if you want to create value you should just make the share price go up and like there's some companies that need to dilute a lot in order to create more value. >> I think the exercise to go through is to
1:39:41
>> I think the exercise to go through is to look at your growth and really understand where is there a bottleneck in your business.
1:39:50
What is the long pole in the tent that is holding you back from achieving your goals?
1:39:54
And every time we did that exercise, we came back with an answer that wasn't more money.
1:39:59
that wasn't more money. it was management horsepower or uh you know we need this particular feature to go launch which we can go build like there was just other things that were the thing to go address to help us grow
1:40:13
faster and the place where I see folks making mistakes is they get caught up in the noise and the logic will be like well so and so raised a lot of money or what if something what if this happens or what if that happens which are not actually grounded in factual truths of reality. What you do know is this is
1:40:31
What you do know is this is where my company is.
1:40:33
This is what it'll take to get there.
1:40:36
And if my bottleneck is money, great. Go get money.
1:40:38
But if the bottleneck is something else, you as the CEO, like it's incumbent upon you to spend time on the most important thing instead of go chase another thing that actually is is not the most important thing.
1:40:49
And so that that's kind of how we always thought about it.
1:40:51
And you know, I think it raising more money never was the most important thing.
1:40:56
And so we spent our time differently.
1:40:58
spent our time differently. Was there ever a moment where you blinked like you know halfway in or a few years past being profitable where you were like ah like this idea maybe it's worth you know dipping in raising some money getting back on the train or was it just like
1:41:14
okay now we've been going for a few years we're good >> well once you get it going it it actually gets harder to want to raise more money because >> you start to look at your growth rate and going >> you know what like why would I raise at this valuation when I can just wait 6 months. >> Yeah. >> Yeah.
1:41:31
>> And you know my revenue will be up by 50% or 100%.
1:41:34
Like the valuation just never makes much sense.
1:41:37
Now obviously and this is I think why you see a lot of like really runaway valuations right now because the founder kind of just looks at the math and says well it's there's no there's no sense.
1:41:48
And so a venture capitalist has to come in and be like, "Well, I'll give you 40x or 80x or 100x >> to get them to go, well, okay, maybe for that I would do it." >> Yeah. Yeah.
1:42:01
It it it's very funny that we're seeing in the market right now like like tough margin stuff, crazy burns, crazy valuations, and then simultaneously we have another company in the AI space midjourney, David Holes, that hasn't raised any outside capital and is just growing, growing, growing.
1:42:18
And so it's not like it's something unique to the to the like the fundamental structure of AI like there is a there's clearly a way to do it without raising an incredible amount of money and yet uh not everyone's on that path.
1:42:31
Everyone seems to be on the path of like burn burn. >> I don't know. >> Yeah.
1:42:34
Well and I think it depends you know like some of the the foundation models obviously have huge capex and uh expenditures and so that's a different beast you know whereas if you're at the application layer >> your cost structure obviously looks a lot different.
1:42:46
So, you know, this this advice, this way of building obviously has to be filtered to your your context.
1:42:53
It doesn't make sense for all companies. >> Yeah.
1:42:55
Was there something about your particular business or where you fit into the landscape where you it wasn't it wasn't positioned as a product where on on day, you know, 200 AWS is like we're competing seriously.
1:43:12
uh or you had like a million competitors immediately.
1:43:18
What like was it less competitive because of the position in the market and kind of like how you how you shaped the product?
1:43:25
I like the product felt like I don't know somewhere in between like a developer tool.
1:43:30
It was almost like a new market that felt less competitive.
1:43:34
But I don't know what your experience was.
1:43:37
>> It definitely was an odd product.
1:43:37
Like we had folks like comment to us like how exactly did you come up with this idea?
1:43:44
And I think partly what made it so defensible was >> integrations middleware is just inherently sloggy.
1:43:50
Like there's not a lot of secret hacks to do that.
1:43:52
You know now with AI it's getting easier but it's still not easy.
1:43:58
You still just have to like >> you know just kind of chunk away at this stuff.
1:44:03
Like I would put us plaid others kind of in this category where it's not actually easy for a big company to just decide oh we are going to go compete in this >> and most of them just don't have the fortitude to kind of keep chipping away at a bunch of like really boring engineering work like they are hiring all these engineers that want to work on more sexy things. Yeah.
1:44:25
>> Um versus chip away at integration code all day every day. >> Yeah.
1:44:29
Now you kind of have um like such a platform that you're in I feel like you're just like a natural beneficiary of the AI wave um because you're already plugged into so many customers, so many integrations, so many data sources.
1:44:43
There's already so many primitives that AI can take advantage of.
1:44:45
Uh how there's two areas that that stand out to me as potentially valuable.
1:44:51
I'd love to know which one's more valuable to you and then if there's a third that I'm not thinking of, let me know.
1:44:54
Um, first is just having AI co-pilots help write new integrations, help accelerate your software development, just do more with the team.
1:45:06
I doubt you've done like massive AI layoffs or anything like that, but you're probably being more productive.
1:45:10
That's maybe one area that is interesting.
1:45:12
And then the other is just AI as a product that can be drawn on in the midst of moving data around.
1:45:18
So if I have one connection over here on Zapier and then I want to have an LLM transform that data and then send it to another integration that feels like a really like really amazing use case.
1:45:27
Um have those both been equally beneficial?
1:45:33
Has one been has one stood out to you as uh as particularly great or is there something else that I'm not thinking of?
1:45:37
>> They're they're both really valuable for different reasons. Yeah.
1:45:39
So the first this idea of like a co-pilot or text to workflow is really valuable for helping people build new types of workflows. >> Sure.
1:45:52
>> Inherently like these noode workflow editors have a fair amount of configuration involved with them.
1:45:58
You know, we always invested a lot of in design and making that experience good. >> Yep.
1:46:03
But it's still a lot to configure.
1:46:07
And co-pilot just gets closer to how humans think about this stuff.
1:46:11
>> Most humans are not great systems thinkers.
1:46:13
They don't break the task down bit by bit by bit.
1:46:15
And so as a result, a co-pilot can be a really good way to attract folks into the market that maybe struggled in the past, but it doesn't fundamentally change the use cases that folks can do, which is where the second one gets really interesting.
1:46:28
And I think the this is where we've had some really interesting learnings because we have launched Zapier agents which is a purely agentic experience and we have our classic workflow editor where you can now inject AI steps.
1:46:45
>> Y >> now both have been successful but the latter has been far more successful and I think it's because when you look at the um >> and the latter sorry to clarify the latter is in in this case is >> workflows workflows AI steps. Yes. Exactly. Mhm.
1:46:58
And I think what the reason why is because agents inherently just don't quite have the reliability yet to get you >> to solve like sophisticated use cases.
1:47:10
You know, you think about it where it's like, well, if you're asking it to do anything complex, call it like 10 tasks in a row, 20 tasks in a row, >> but the the error rate is 10% every time.
1:47:19
Well, by the time it, you know, rips through 10 or 20 tasks, like it's messed up on a handful of these things and it's way off in left field.
1:47:24
Y >> whereas within a workflow you can put it in a harness and say hey mostly I want this thing to be deterministic throughout all these parts of the steps but right here I need to to summarize something or I need it to analyze the sentiment of this or I need it to generate an email.
1:47:42
Uh, and you can put the agent part, uh, the AI part in the spot where it does the thing best and then you wrap it back in, fold it back into a deterministic workflow.
1:47:52
And that has opened up, um, a huge amount of usage.
1:47:58
We have like a quarter billion, more than a quarter billion tasks that have run through Zapier with AI like that alone.
1:48:03
And I think that's the honestly I think it's kind of a sleepy category. >> Yeah.
1:48:09
When did when did you guys realize what a good position you were in here?
1:48:13
Because you basically spent before agentic workflows were like a term that people were throwing around every single day.
1:48:19
You guys spent a decade basically building out all the really >> really hardcore integrations with hundreds or thousands of different services and getting just simple workflows dialed so that you can yeah >> you can just slot in, you know, reasoning or or slot in LLMs at different at different steps.
1:48:36
But um have you been surprised at at at how many people are coming in to kind of like compete in this space?
1:48:44
Cuz it feels like I've just seen a lot of pitches over the last 12 months that are I just look at and be like, "Okay, this is like this is Zapier but just like, you know, pretending that Zapier doesn't exist."
1:48:58
Like >> but AI first, right? >> Yeah. Yeah. Yeah. AI first.
1:49:00
And it's like, well, you're >> it's Zapier, but you can buy the stock in the private markets.
1:49:04
Well, it's it's Yeah, it's Zapier, but >> Zapier, but we're doing a series B. >> There you go.
1:49:11
Zapier, we sell software.
1:49:13
We're Zapier, but we sell stock. >> Yes, exactly. >> There you go.
1:49:16
Um, yeah, you know, I I do think it kind of surprised us.
1:49:20
um >> that we were as well positioned as we were.
1:49:27
>> You know, we had started to dabble with generative AI a few months before Chat GPT had come out and um had started to see some customers building workflows on our private developer platform.
1:49:40
we have a developer platform where folks can build their own stuff.
1:49:43
And so we'd started to see some of that happen.
1:49:44
And as uh the models advanced, in particular when GPT4 came out, >> we were like very unsure if workflow was durable.
1:49:57
Like we started to think like actually this like pure agentic experience is probably going to be the future.
1:50:03
Now I still actually believe that it will be the future.
1:50:05
I just don't think it's going to get there as fast as um we we think it will. >> Yeah.
1:50:13
>> And you know, over the course of the next year, we just kept seeing a gent like AI use cases on the traditional workflow builder grow and grow and grow and grow.
1:50:22
And then we started to realize, huh, like maybe what we need to do with our product roadmap is actually help people surf the wave.
1:50:28
like help them go from just old school classic deterministic workflows and move steadily into purely agentic ones uh and allow them to kind of mix and match these experiences along the way.
1:50:41
>> Talk to take it back to gross margins for me.
1:50:44
um how important is offering the full suite of paro frontier models within those uh deterministic steps and is there a world where you want to offer even smaller and more focused and cheaper models?
1:51:01
Um we we talked to one company that's training uh uh transformer-based models but just for sentiment analysis just for uh for censoring bad words just for uh JSON to CSV or something like stuff that could almost be done deterministically in many cases but just like you need a little bit of uh of AI there and they train them on GPUs or on on like gaming graphics cards and they run like super super cheap.
1:51:28
And I'm wondering like uh if you're if you're in a high if you've built out uh uh if you build out Zapier workflows that are high volume, the cost per inference feels relative there.
1:51:39
And I it feels important and I feel like you would have a good insight into like how some of these like bigger models can kind of blow up on you if you're not careful. >> Yeah.
1:51:48
Well, this is also where it's nice if you can encode your workflow into something that's deterministic.
1:51:53
you get reliability, you get cost advantages, you get speed, you get a lot of things that are really really nice.
1:51:59
Uh and then uh >> you know insert AI only where you need it.
1:52:05
Now the way we've thought about this is we really want to abstract as much of this away from the customer as possible.
1:52:12
you know, we sell predominantly to folks in GTM orgs and GNA ors and um folks that are not paying attention to the subtle differences between, you know, which model is best for coding, which model is best for writing, which model is best for this, that or the other.
1:52:25
So, we're trying to abstract away a lot of those choices.
1:52:29
And that extends into how we price for this stuff as well, too.
1:52:34
So, we want to make it a little bit more like you just buy it, we charge you for tasks, doesn't matter if it's an AI task or another task, we'll just sort of it all the math will kind of all work out for you in the end.
1:52:45
>> Um, but I imagine if you were selling, >> do you guys have a lot of >> do you guys have a lot of learnings from like pricing on on pricing based on on out outcomes versus traditional SAS?
1:52:57
Because that's again so many of the ideas that VCs have gotten excited about with agentic workflows and just >> agents broadly I feel like are ideas that you guys have explored.
1:53:07
>> You've basically always been consumptionbased. Correct.
1:53:10
>> We've always been consumption based. Yeah.
1:53:11
And I think the challenge that >> and sorry to interrupt but the other way to look at that is like uh you've been pricing based on work done. >> Yeah.
1:53:21
is is like the the sexier way to describe that at least 202 >> uh we do a task like you pay for tasks and I think the challenge that exists for horizontal products is >> the way in which folks use the software they they get variable value from it >> and high usage doesn't necessarily correlate with high value and low usage doesn't ne necessarily correlate correlate with low value.
1:53:50
And so that's where, you know, if you're building horizontal usagebased software, you run into a tra a a trap where you're like, hm, how ex like where along this spectrum are we going to price? Yeah.
1:54:04
Are we going to pick one credit system where everything is going to cost one and we're trying to figure out well is it a premium thing or a is it a more commoditized thing or do we risk making our pricing more complex >> and start to say we're going to have a credit system that's tied to different value but now your customer is having to do a bunch of different calculations in their head figuring this out.
1:54:23
This is where I think vertical agents have an advantage right now where they can say hey we are hyperfixated on one use case and as a result we can maximize the value that we are going to sell for.
1:54:40
We're going to say hey you know if you're in customer support we're going to charge you if we close the ticket and you can do very direct math to say well today I have a support rep that I got to pay this much money every single year to answer this many tickets.
1:54:50
if I can turn that into an agent that they can answer those questions just as well, then I'm willing to pay, you know, this this is sort of like the maximum I'm willing to pay for this.
1:55:00
>> So, that's where these vertical software do have like pricing advantage, whereas if you're charging horizontal, you you have a much trickier challenge because you have so many variable use cases at the end of the day. >> Yeah.
1:55:10
Are there new uh new markets that you're noticing open up that are uniquely available to you because of AI?
1:55:23
I think the thing that has surprised me is the c certain like more traditional or like industries >> have been fairly quick to jump on this and I think my hypothesis is partially that their use cases are well suited for this.
1:55:44
So if you have if you're working a lot with uh like PDFs and like paper documentation, >> the SAS stack was like kind of tough for you because it had to be structured and there wasn't tooling that could turn all this like unstructured data into structured data for you.
1:56:03
>> However, LLM are uniquely good at that.
1:56:06
>> And so as a result, >> these companies have seemed seemingly jumped on this stuff pretty quick.
1:56:10
The second thing that's been interesting is we've watched um particularly media companies be relatively fast at this which also surprised me in some ways I felt like they were faster at it than certain tech companies we've spent time with this and I have to wonder like how much of this is because they saw so much disruption in their business model during the internet craze that they were like we are not going to let that happen to us again.
1:56:38
Whereas technology companies have kind of had it pretty cushy. Yeah.
1:56:43
>> And so like, yeah, we're we're doing the AI thing.
1:56:45
>> It's fun when you're doing the disrupting, but getting disrupted. >> Yeah. Not so exciting.
1:56:50
And so they're like, act two, we're going to be on it this time around. >> Yeah.
1:56:54
Uh where where do you stand on uh on estimating the impacts of AI on the job market?
1:57:01
because I feel like a decade ago or around the time when you were getting Zapier off the ground uh Zapier, sorry, we said it both ways.
1:57:09
Um I'm sure people were saying like uh automating business processes will lead to with software will lead to job loss.
1:57:18
And >> did people say that? I guess. Yeah.
1:57:22
>> I mean people said that with the internet.
1:57:23
They said you're not going to need sales reps anymore.
1:57:24
Everybody's just going to be able to go and you know you're just going to be able to go to a website.
1:57:28
Um, and I just, yeah, I'm curious like, >> well, there's two data points that we've been pointing at.
1:57:34
One is, uh, the Wall Street Journal had an article today saying that, uh, new grad unemployment is, uh, is not tracking as well as it should, and there might be a real effect of of AI not driving companies to hire less new grads.
1:57:50
And then but then on the flip side, there was this report that came out that said that, you know, 95% of AI tests at um at Fortune 500 companies did not make it past the test phase.
1:58:03
And so AI as an installation into these large companies is not going as well.
1:58:08
So there's kind of evidence on both sides, but I' I'd love to know what you think.
1:58:11
>> Yeah, you know, I when I think about this, I my my take is that capitalism is largely undefeated. Mhm.
1:58:18
>> Uh, and you know, it's it's it's easy for us to spot the disruption.
1:58:26
We can see the jobs that are disappearing easier than it is for us to see the new opportunities that are being created. >> Sure.
1:58:36
>> But history will tell us that there is always new jobs created.
1:58:39
Y >> and this is what we see play out in our customer base.
1:58:43
Um, I talked to small businesses over and over where they're like, >> I I I never could have hired somebody to do this work and now because I'm doing it with automation, I'm actually getting more done.
1:58:56
I'm generating more revenues and now I'm reinvesting that >> and when they go to reinvest that, yeah, some of it's being reinvested in AI and more automation, but some of it's being rest invested in people.
1:59:06
So, that's kind of where I think this plays out.
1:59:09
And the second thing I think will happen is there's this meme that goes around where it's like, well, all these software companies are just going to have crazy high margins now.
1:59:19
Like, we just don't need that many people.
1:59:23
>> But again, capitalism is undefeated.
1:59:23
If someone looks out and sees like, "Wow, you're generating so much value.
1:59:28
How about I just come in?
1:59:31
I'm willing to tolerate."
1:59:33
Or if everybody everybody has high margins and they're like, "We should just spend three times as much on user acquisition >> and just get more >> scale." Exactly. Exactly.
1:59:41
And well, how are you going to get user acquisition?
1:59:45
Well, some of that's going to be invested in advertising.
1:59:46
Some of that's going to be invested in people.
1:59:49
And like I think at the end of the day, it nets out where, hey, we're all we're all going to still have jobs. Yeah.
1:59:53
But what jobs we do have, that's where it's going to shift.
1:59:57
And I think those reports are kind of telling that story where new grads, the requirements are shifting.
2:00:03
what's what's needed inside the work force is is changing and so there's kind of a shift going on there and that's always what's really challenging in these moments is time is the skill sets required to be successful >> they're not static
2:00:17
>> yeah what about uh job creation around the implementation uh like I'm sure there's been a cottage industry around Zapier for a long time now of people that just help integrate Zapier in companies um and we we were talking
2:00:32
probably uh at the beginning of this year thinking that what what an amaz you know in the same way there used to be a big opportunity to just help companies run Google ads or help companies run Facebook ads and that there's still
2:00:44
opportunities there but it feels like right now taking Zapier into a company and just saying like I'm going to save you guys >> uh you know $250,000 a year if you pay me 20 grand to like set this up properly. It just feels like that is
2:00:56
It just feels like that is extremely repeatable and there's so many businesses that as for as many that are coming on and and and using Zap year or other platforms there's there's probably a multiple of those that just don't aren't even fully aware that these tools exist yet or how to implement them.
2:01:12
>> We so 100% we're seeing the rise of the AI automation engineer.
2:01:15
We have some of these internally where for our enterprise customers if you want us to do it for you, we will come do that for you.
2:01:23
And to your point, we're seeing this cottage industry starting to blossom.
2:01:26
And it's particularly effective when you can combine that skill set with domain expertise. Yeah.
2:01:33
>> So if you have somebody in HR who has this capability, they're able to work magic on this.
2:01:39
Same thing in legal, finance, marketing, sales, if they have this systems thinking, this ability to break down tasks to to use the tools, they're often able to work wonders inside the stack.
2:01:50
And it's been pretty exciting because we've this this person has kind of existed for all of our this is who we've served for all of our 15 years, but in the last couple years they're starting to get more um credit inside these organizations.
2:02:05
They often were like the underappreciated person who just kept all the plumbing working.
2:02:11
Um but now like they're like the automation engineer like I'm making magic happen.
2:02:16
Um, can you give me your take on MCP and how it just explain it and how it fits in and is it a tailwind or a headwind, an alternative, something that you're just benefiting from immediately?
2:02:27
Um, how does it all fit into your landscape? >> Yeah.
2:02:31
So, MCP model context protocol, it's it's a protocol much like HTTP or or REST or something like this that allows uh it focuses on how agentto agent communication, letting agents talk to each other.
2:02:43
Um, I think right now there's obviously a lot of hype around it, whether it's a tailwind or a headwind or both.
2:02:50
Um, you know, we're still figuring it out.
2:02:53
Like I think there's a lot that has to be figured out with the use cases and whatnot.
2:02:58
The I think the most important thing is to actually get the the use cases really dialed in.
2:03:06
Uh, and the place where we're seeing it be most effective is a in like Claude, uh we're seeing a lot of folks that set up uh Claude projects.
2:03:19
They give it access to various tools and then they go deploy that tool like an internal tool for their organization.
2:03:25
So, for example, if you wanted to create like a uh a sales briefing tool for your sales reps, you might say, "Hey, I'm going to set up a project.
2:03:33
I'm gonna give it a list of in a a template for how I want the brief to be created, and I'm gonna give it access to HubSpot.
2:03:39
I'm going to give it access to Zoom info.
2:03:43
I'm going to give it access to like deep research through Chat GPT or Perplexity or something like that.
2:03:47
And now my sales reps can just come in and say, "Hey, I'm talking to, you know, uh, Sam Alman tomorrow.
2:03:55
Like, what do we know about our deal with OpenAI?"
2:03:56
And it goes and does deep research.
2:03:59
It fetes everything you have from your internal CRM and it generates a brief for you.
2:04:03
So, you come in way more prepared.
2:04:04
So those types of like internal tools in the past those were like kind of hard to build and MCP is like making it really easy for folks to build those kind of like chat style uh internal tools really effectively.
2:04:16
Um that's the use case that we're seeing pop up most frequently.
2:04:21
But I I have to imagine that as time goes on, we're going to see a a lot more like we it very much feels like we're in the very early innings and we haven't, you know, seen these like new user experience paradigms like launched yet or popularized yet. >> Yeah. Yeah.
2:04:37
It always it always just felt like to me with uh just the just on a on the basis of inference cost if you're hitting an MCP server a million times, you would rather just have your agent like write an API integration and just go direct to the database for most of those things.
2:04:53
But there's probably specific use cases where it makes sense, especially if you're like dancing around a lot of different >> Well, I think that's I think you're correct there.
2:05:00
Like at the end of the day, there's going to be some use cases where you want, you know, an API call and deterministic code because it's faster, cheaper, more reliable.
2:05:07
And other cases, >> yeah, we saw this with CHP pretty early.
2:05:11
It was like, yeah, it's pretty good at math.
2:05:12
It can memorize a lot of math.
2:05:12
But like, why not just give it Python and then it can get the math 100% right. Like, I don't care.
2:05:18
I just want the right answer.
2:05:20
You don't need to like stunt on me by memorizing every number of pi.
2:05:24
You can just go look that up on Google if you want. Anyway, >> that's fine.
2:05:28
That worked out pretty good in the past. >> Yeah, exactly.
2:05:30
Uh, let's stand on the shoulders of giants as much as possible.
2:05:34
Uh, anyway, this was fantastic.
2:05:34
Thank you so much for hopping on.
2:05:36
We will talk to you soon. >> Great to chat. >> Thanks, guys.
2:05:39
>> Have a good rest of your day. >> Cheers, Wade.
2:05:41
>> In the meantime, let me tell you about Bezel.
2:05:42
Your bezel concier is available now to source you any watch on the planet. Seriously, any watch. You can go to getbzzle. com.
2:05:46
And we have Dan Wang in the reream waiting room coming in to the TVPN Ultra Dome.
2:05:51
He is releasing a new book today, I believe.
2:05:55
Um, it's already being reviewed.
2:05:58
>> Gotta ask him how many pages it has.
2:06:01
>> Is that the question you want to ask? >> And hit the gong. >> Okay. Yes. Yes. Yes. Definitely.
2:06:04
So, uh, >> the the what everybody's been waiting to hear.
2:06:08
How many pages is your new book? >> Yes. Yes. Yes.
2:06:10
He's a research fellow at the Hoover Institute.
2:06:12
The book is Breakneck, China's Quest to Engineer the Future.
2:06:18
I saw a uh a video of him going viral talking about the difference between uh uh China's government officials and America's government officials talking about how they have an engineering society.
2:06:27
We have a lawyer society. It was fascinating.
2:06:29
Can't wait to talk to him.
2:06:30
So we will bring him in from the restroom waiting room. Dan, how are you doing? >> Welcome to the show. Really well guys. >> Thanks so much. >> Big day for you. >> Huge day. >> Well, huge day. I get to be on TVPN.
2:06:42
This is this is a nice day indeed. >> Welcome. Welcome.
2:06:46
>> Been waiting for this moment.
2:06:46
How many pages are are in the book? >> Uh, less than 300. >> Wow. >> Less than 300.
2:06:52
>> I think they should be a quick read. >> Quick read. Quick read.
2:06:55
Um, >> talk about the background.
2:06:59
>> Was that was that int was that intentional by the way?
2:07:00
Were you were you going for some like uh did you did could you have written, you know, 700 pages and and it >> to condense it down?
2:07:09
Yeah, I think it's uh I think it's much better to write a book that is that people feel was too short and could have been a lot longer than it is to write a book that everybody feels should have been 100 pages shorter.
2:07:19
So that you want to air on that side. >> Yeah. Yeah.
2:07:22
Uh get give me some background on on the path to writing the book, the type of research you were doing, what inspired it, and a little bit on your background.
2:07:30
I was in China from 2017 to 2023 working as a technology analyst mostly for hedge funds thinking about semiconductors, clean techch, China and science trying to figure out what's going on.
2:07:41
So I was living in China at the start of the first Trump administration.
2:07:45
I was in Hong Kong, then Beijing, then Shanghai trying to figure out what's going China's going to do on Huawei, how it's going to respond on the trade war.
2:07:53
And so I ended up living through the first trade war, the trade war that marted into a tech war that really hurt Huawei.
2:08:01
I lived through the entirety of zero COVID.
2:08:03
And I was just trying to make sense of all of this experience.
2:08:04
I was thinking that, you know, you we use these words like socialist, capitalist, neoliberal, democratic, whatever that means to describe the US and China.
2:08:13
Now these are all words from like the 18th century or something.
2:08:18
And let's just come up with a new framework.
2:08:20
And that's why I came up with the engineering state and the lawyerly society. >> The lawyerly society. It's a great framework.
2:08:26
It really stuck out with me.
2:08:28
Um you're remind me where your family uh comes from within China.
2:08:32
It's somewhere somewhat far away from Beijing. Is that correct?
2:08:37
>> Yeah, it's in the southwestern periphery named Yan.
2:08:39
So, it's really far away from Shanghai and um Beijing. >> That's right.
2:08:43
and and and you said that uh the the distance from the government was relevant to the political culture there.
2:08:50
Um, and I was wondering if there was a similar dynamic that you saw in the United States, like is being in California or Silicon Valley, is there a distance from Washington DC or Mara Lago or Trump Tower in New York that that that is at all relevant or do you think it's a do you think that that distance from the center of government power unique to the the geography of China that your family grew up in?
2:09:19
>> I think I am an outsider. both the US and China.
2:09:21
Well, I'm Canadian, so I'm not um not exactly American.
2:09:23
Uh now I'm in Silicon Valley, but I I've never quite felt like this is this is exactly where I'm from.
2:09:30
This is exactly where where I need to be.
2:09:32
And also in China, I didn't grow up in these hyper competitive uh Chinese cities like Shanghai or Beijing where everybody owns a bunch of property.
2:09:39
You liquidate one of these properties and you can send your kid to UCLA and give her a Mercedes as well.
2:09:46
So I I I feel like my strength looking at both countries is as an outsider, not really, you know, buying into everything that DC or Silicon Valley thinks about itself. >> Yeah.
2:09:58
How how how when when when you when you try and define like the the structure of China's government or the United States government um you've obviously coined these terms the the the engineering uh uh and lawyerly society.
2:10:15
Um, I was looking at data to try and quantify the difference between the Chinese economy and the US economy.
2:10:24
And the US has, I think, higher taxes and potentially a higher share of the of the population working for the government.
2:10:33
And I'm wondering if there's this world where you can look at the United States as a socialist country that's trying to be capitalist and China as vice versa.
2:10:43
Um, and I wonder if you could like toy with that at all where where you know the US is actually, you know, like the government is huge and yet it is the country of like, oh yes, the government is not involved at all and in fact it is extremely involved. >> Yeah.
2:11:02
Well, I think the best line I've heard on this is that the Department of Defense is America's answer to central planning and the and the Communist Party because just so big.
2:11:09
My view of China is that it is 1950s Eisenhower America.
2:11:16
>> Giant manufacturing sector.
2:11:16
Uh they're building highways absolutely everywhere. Very little immigration.
2:11:21
Uh very traditional gender roles. Um pretty low taxes.
2:11:26
Uh very minimal transfer payments.
2:11:28
Eisenhower had more transfer payments because he embraced the New Deal.
2:11:32
But there is a sense in which I think China is the most right-wing country in the world for all of the reasons that I've just outlined.
2:11:37
And the US is kind of a kind of a capitalist country that's a little bit embarrassed about it and trying trying to get to a bit more socialism. >> Yeah.
2:11:46
What uh I heard you mention that like imperialism was somehow like the final form of capitalism or something like that.
2:11:53
Can you explain what you meant by imperialism's relationship to capitalism?
2:11:58
>> Well, that that wasn't me.
2:11:58
That was a that was a much baler thinker, Vladimir Lenin, who said >> you were quoting it. Yeah, that's right. >> I was quoting Lenin. Yeah.
2:12:06
So, imperialism, the final stage of capitalism, which is one of his big pamphlets. I recommend it. >> Okay.
2:12:12
But but unpack the the the thesis there because I don't immediately understand intuitively the relationship between imperialism and capitalism like what was his argument and then what's your take on his argument? >> Yeah.
2:12:25
Well, I think maybe we don't need to get too deeply into Marxist thought here, but they have something about um class struggle and how the proletariat really needs to rise up because the um the the people at the top have all the resources >> and the capitalists in order to maintain their capitalist expansion really just have to go overseas and conquer Africa and Asia and Latin America in order to maintain their expansion. That's the idea. >> Yeah.
2:12:50
And then and then like the the white pill of like America avoiding that like uh what what was the what's the bullcase for for American capitalism not devolving into imperialism?
2:13:04
>> Well imperialism I think was a thing of the past when you know you really needed a lot of rubber in order to power your cars and we don't need this natural rubber anymore.
2:13:13
You know we can synthesize it through petroleum >> and so I think the US doesn't need to be imperialist.
2:13:18
That doesn't mean that it doesn't have any other sorts of problems, but it hasn't needed to conquer a lot of territory in part because it's built this wonderful structure of alliances that you don't really need to conquer them because the elites kind of do what you already want to do.
2:13:31
And I I wonder if the Trump administration is uh still going to value all of that. >> Yeah.
2:13:36
How much do you think Trump is actually inspired by uh the Chinese approach?
2:13:42
H >> well, every time he talks about his buddy C, he compliments C for his great head of hair.
2:13:47
Um, and this is like something that they talk about pretty often.
2:13:51
Uh, I've always felt that Trump never said a bad word about his buddy Ci up until co Trump always kind of hated the Japanese and the Germans more which were the enemies of the 1980s.
2:14:04
I think there is an aspect in which uh the US is becoming like China.
2:14:09
uh the US is nationalizing Intel.
2:14:12
Uh Intel is now going to be a stayown enterprise with American characteristics.
2:14:15
There's a lot less uh data probety I think uh with the statistics not being perhaps quite right.
2:14:24
>> Um there's a lot of interference uh inside the economic agencies and I think there is more construction but there is more construction around gilded ballrooms and detention centers and I just want uh Trump to take a leave from China and build a lot more mass transit.
2:14:40
build a lot more subways in New York where I'm chatting with you from.
2:14:41
Build a lot more housing for people.
2:14:43
Let's let's make Silicon Valley much more livable, mass transit friendly place.
2:14:50
>> Is there any is there any hope for the federal government building anything really?
2:14:55
I feel like all of that is the domain of the state and local governments.
2:14:58
When I think of the roads and the bridges and the highspeed rail in California, like that's not a federal project. Um should it be?
2:15:03
Well, the interstate highway system is a federal project and that was something really built by Eisenhower. >> Sure.
2:15:12
>> Manhattan was a federal project.
2:15:12
Apollo was a federal project.
2:15:14
There is a lot of local building, that's for sure.
2:15:17
A lot of maintenance, a lot of um highways need to be built locally.
2:15:21
But I I think there's no reason for the federal government not to be much more muscular um and take over California highspeed rail.
2:15:28
Rather than nationalize intel, let's nationalize California highspeed rail and do a much better job at it.
2:15:34
This feels like something that Trump could get on board with.
2:15:35
Like for sure this >> he would love to uh pop over to Newsome's backyard.
2:15:40
>> He loves building stuff. He's a builder. He's a real estate guy.
2:15:43
>> What about on the energy side?
2:15:43
What what what what do you think uh America can learn from China's approach to increasing energy production?
2:15:52
>> Well, Trump has this policy of all of the above.
2:15:55
And I think China is actually the one that is much more all of the above because they're building most of the world's coal plants still today.
2:16:02
They're building all of the wind.
2:16:03
They're building all of the solar.
2:16:03
Um, so they don't have that much natural gas, but they're building much of everything else, including all the nuclear.
2:16:09
So, the Trump administration is doing more nuclear now.
2:16:11
Um, but they're getting rid of wind projects that are almost completed.
2:16:15
Um, they're not really building much more transmission.
2:16:16
I guess they're favoring coal as well, but China is doing all of the clean technology, all of the new stuff, as well as some of the old stuff, too.
2:16:26
Um, one one question I have on like press freedom in China is uh just why isn't China does does the uh repression of the press in China reflect a uh a lack of confidence in how good things are over there?
2:16:43
Because you'd think if if you're if you're confident about what you're doing, if you're happy, if you're successful, um you'd be like, there are no skeletons in the closet. Let the press run free.
2:16:52
they will by default uh report positive things.
2:16:58
>> I think that is a sign of lack of confidence.
2:16:59
The communist party is super thin skinned about any sort of criticism.
2:17:04
>> But I think the other aspect of that is that they're a bunch of engineers and >> you've spoken to engineers.
2:17:08
They're not really good at talking.
2:17:10
They're not they don't even want to talk to to any of us, right?
2:17:14
Uh so they like to just sit, you know, sit with their projects and design a new bridge or something.
2:17:19
a new bridge or something. whatever they don't understand they tend to censor and they're also really prickly skinned about any sort of criticism uh that they have and so I think that it is a manifestation sometimes of lack of confidence in China system uh they're really nervous that any criticism will
2:17:35
somehow topple the communist party and then whatever sort of jokes or any sort of humor they don't understand they simply censor it and so I think the engineering state is also kind of an explanation for why China's been relatively weak at producing soft power it's not like the Korean You know, we're all listening to K-pop. We're all
2:17:51
We're all watching Squid Game.
2:17:52
The Japanese with Nintendo and the Game Boys and Mario and Mario Kart. They've been amazing.
2:17:59
Chinese have not produced quite that much.
2:18:00
And I think >> Labu is the first Yeah.
2:18:02
the first attempt, I suppose.
2:18:05
>> I think this is kind of a new thing, but China's been getting richer for nearly five decades now.
2:18:09
And this kind of a weird doll is is that the best they can do? I don't know.
2:18:15
>> Well, Tik Tok Tik Tok could be the other Tik Tok feels like.
2:18:17
Even Tik Tok is it's not its own cultural power. It's not its own brand.
2:18:22
It's like a bucket that people put different brands into.
2:18:24
It's it's like the hoverboard, the anonymous hoverboard that came that product was developed in Shenzhen and and no and it never had a brand around it.
2:18:34
It was just five different front brands on top of a technology that was engineered. I I don't know.
2:18:40
It was an interesting phenomenon. >> Yeah.
2:18:42
Yeah, I mean mostly on TikTok all I'm watching are short clips of TBPN, not not the Chinese propaganda, right?
2:18:48
I'm only watching American propaganda from >> I mean that is really proof that that they're not putting their thumb on the scale if we have any traction over we have any traction.
2:18:55
Uh have you been uh have you been surprised to see Elon engaging in in lawfare with the the apples of the world the open AIS?
2:19:03
feels like, you know, uh if anybody represented uh the the engineering state in America, it was Elon, you know, creating these mega projects, massively impactful companies.
2:19:15
Yet, >> more broadly, just like it feels like the lawyerly society kind of had organ rejection from having an engineer in the room that was like I don't know that if I'm trying to apply your your frame of thinking to the Elon Trump like there were other people that were successful in Washington.
2:19:32
David Saxs has a law degree.
2:19:35
Peter Teal has a law degree.
2:19:36
Keith Reo has a law degree. Elon goes in JD Vance. Uh Elon goes in. He's in the same crew.
2:19:42
He's in the PayPal mafia and yet he is, you know, ejected pretty quickly. >> Yeah.
2:19:48
I mean, I think this is one of the uh tragedies of Doge.
2:19:50
I feel like we could have had engineers building a really big mega project inside government as we used to do.
2:19:58
>> We had Robert Moses build a lot of projects in New York, sometimes not very well.
2:20:02
We had Hyman Rickover, father of the nuclear navy, build this giant navy project powered by nuclear reactors uh with some ships as well. >> What did Elon do?
2:20:11
Well, he wasn't really trying to build anything inside government.
2:20:14
He was kind of destructive to a lot of aspects of government.
2:20:15
And I really wish he applied his talents more to like build 30 big nuclear reactors for for the US instead.
2:20:22
And that's that's not what happened.
2:20:25
>> Would those need to be uh net new projects?
2:20:29
Like is that is that a more fertile ground for government projects as opposed to say take over Intel, take over the highspeed rail initiative, like take over something because it just feels like there's a lot of stuff that's not working both in the private sector and the public sector and that seems to be where we focus as a society in America just there's so much that's going wrong.
2:20:49
The government is kind of the lender of last resort that can step in when I agree with you.
2:20:52
think I like the idea of another Apollo project, another Manhattan project, another project that's like completely new and and no one would underwrite it in the private sector to begin with.
2:21:04
>> Yeah, let's have both.
2:21:04
Let's have a functional highspeed rail project out of California.
2:21:09
>> Uh let's have many more nuclear reactors because we I think we had only one new nuclear reactor in something like the last 40 years and that's kind of pathetic.
2:21:16
Uh I'm talking to you now from New York.
2:21:18
New York is trying to fix up Port Authority bus terminal.
2:21:20
It's going to take something like five years and $6 billion to make a new bus station.
2:21:24
Um, every mile of subway that New York builds cost something like $2 billion per mile.
2:21:30
This is just the highest costs in the world.
2:21:33
And we can't even build something as simple as a public toilet in San Francisco.
2:21:36
And so, you know, we need to we need to get better at every sort of thing.
2:21:40
You know, we need to do the public toilets.
2:21:41
We need to build the bus stops.
2:21:43
We need to build the nuclear reactors. Let's go to the Mars. >> Yeah. Yeah.
2:21:46
Is is the is one possible path here?
2:21:50
uh the wolf in sheep's clothing, the engineer with a law degree that they acquired online or something.
2:21:56
Uh they pass the bar in their free time.
2:21:58
Like ca can can the lawyerly society be hacked in the way that uh an you know an an engineer might social engineer a a job application or or reverse engineer an API and hack a a website.
2:22:16
Yeah, I want Peter Teal to hack all of that and be the lawyer that actually is actually the real engineer.
2:22:20
I think that would be great if something like that could happen.
2:22:24
But I also feel like the US used to be an engineering state.
2:22:25
You know, it built a lot of in the 19th century built canal systems, uh built the train systems, built a lot of skyscrapers in Manhattan and Chicago.
2:22:38
And then in the uh mid 20th century, we built the highways, we got Apollo, we got Manhattan, we built the Hoover Dam.
2:22:45
>> You know, that heritage is out there, but right now it feels like we're walking amidst the ruins of a fading industrial civilization, and we need to at least renew this and hopefully build more, too. >> Yeah.
2:22:56
>> Trump uh yesterday said, "We're going to get along good with China.
2:22:58
I hear so many stories about how we're not going to allow their students.
2:23:02
We're going to allow, it's very important, 600,000 students. It's very important.
2:23:06
Uh re where do you think that's uh coming from?
2:23:12
Feels like a little bit of a pivot.
2:23:14
And do you think there's that much demand uh on the on the student side for opportunities at US universities? >> Yeah.
2:23:24
Trump is now the most pro-China member of the White House.
2:23:26
And as I said, I think I've always every time I saw Trump and I was living in Beijing in 2017, 2018 when he was visiting China, he visited um the forbidden palace once, he's always said nice things about China up until co he his real enemies are like the Germans and the Japanese.
2:23:44
That's been long the case.
2:23:45
And that's not always going to be true.
2:23:47
But u you know la a couple of months ago when he a journalist asked him, "Does the US want so many Chinese students?"
2:23:53
Trump said, "It's our honor to have them."
2:23:55
you know, it's our honor to have them.
2:23:56
And I think that's a that's a really ringing endorsement of Chinese students.
2:23:59
I think there's still a lot of Chinese who are really keen to move to the US.
2:24:03
They're attracted by some aspect of working without censorship.
2:24:08
If they're in the arts, if they're working in journalism, they're attracted by some aspect of pluralism.
2:24:13
New York is a great place.
2:24:13
Uh San Francisco is a great place. They want to come.
2:24:17
And I think more American students should also go to China.
2:24:20
You know, take a look at what Shanghai is like.
2:24:24
take a look at what Shenzhen is like, you know, let's just have more exchange and let's have more uh mutual curiosity, too.
2:24:30
>> I studied I studied abroad in in Shanghai in 2016 and um and uh >> what' you think?
2:24:37
>> Uh within a week of arriving, I decided to stop studying Mandarin.
2:24:40
Uh and I was excited to go home.
2:24:44
I think that's that was part of uh part of partly because I was born and raised in California and I like clean air and healthy food and things like that which are not in large supply over there. But I was still shocked.
2:24:57
Uh it it was overall a cool experience.
2:25:00
Uh it was interesting because I was working at a at uh interning for a company that was at a Chinese startup accelerator and I got to experience the how hostile uh the the sort of local market was to external uh external kind of startup players in the ecosystem.
2:25:18
Um, >> you also got paid to be in a promotional film about teaching English, which you weren't doing, right?
2:25:27
Like local government fraud perpetrated.
2:25:31
>> Can we pull up that clip? Let's Let me find it.
2:25:33
>> I think it'll be tough to find.
2:25:33
I I still don't I still Yeah.
2:25:35
One day Jordy gets paid to go out to some like province.
2:25:39
The official was clearly cooking the books on like how much English was being taught. >> Yeah.
2:25:44
There was there was a there was a local some some state government had like really bad test scores and they they they they wanted to bring English uh teachers which anybody any student in China can become like an English teacher or whatever.
2:25:57
>> But anyways, it was a very weird very weird experience.
2:25:59
It was this was also >> during the uh during the election cycle which was just absolutely wild.
2:26:04
But I'm not surprised now that I think there's like only 800ish American students currently studying in China, which is just such a wild wildly inverted from from how many Chinese students that we have >> um here.
2:26:20
>> Uh switching gears, what what do you think of uh I like I like the take about like the uh the quantitative nature of Chinese policies, zero COVID, the one child policy. It's very quantitative.
2:26:34
Um, my my kind of take on the on the Chinese birth rate decline was that if you can effectively put a gun in someone's face and tell them they can only have one child, you can put a gun in someone's face and tell them that they have to have three children.
2:26:48
And so, uh, is is there actually cause for, uh, for like nervousness or fear around true population decline if you are if you do have the authoritarian playbook in your back pocket and you can just upregulate fertility essentially? >> I doubt it.
2:27:10
I think it it is you can stop a lot of birds by putting a gun to people's heads.
2:27:15
um is really difficult to, you know, coers some measure of culation.
2:27:20
You know, h how are you going to get two people in bed to and and put a gun to their their their head?
2:27:25
I think that's it's not the best conditions.
2:27:28
It's not the best conditions. >> It's much harder.
2:27:30
>> Is is is population decline like overrated, underrated?
2:27:33
Is it is it a serious threat to China in the long term from an economic perspective or population perspective? Yeah, Peter.
2:27:42
Yeah, Peter Zhon loves to go on and say how how cooked. He's like, >> "Yeah."
2:27:47
Yeah, he's been saying that for a long time, but yeah.
2:27:48
What What were you saying?
2:27:50
>> Overrated in the short term.
2:27:50
Um, correctly rated in the long term.
2:27:53
I mean, the the curve is not that steep right now.
2:27:56
The population is really gently declining.
2:27:58
Sure, >> you don't need a giant population in order to have a semiconductor industry, right?
2:28:03
That the global population of semiconductors is not that large. Yeah.
2:28:07
And so this is really going to bite something like 20 years from now.
2:28:09
But that's still 20 years when you know 20 years is a plenty long time.
2:28:13
20 years ago, you know, we were dealing with some sort of a housing bubble and the US was bumbling around in Iraq and Afghanistan.
2:28:21
20 years uh could be a long time.
2:28:21
And it could be that China fully de-industrializes. >> Oh wow.
2:28:27
>> Germany and Japan and maybe even the US over the next 20 years.
2:28:29
And that sounds pretty bad. >> Yeah.
2:28:31
What what is your frame of thinking around the Chinese semiconductor industry?
2:28:36
It feels like um they've been investing consistently for decades, never really hit the leading edge, but they've always been there in the conversation.
2:28:47
They've never stopped investing.
2:28:49
Um but but how how do you think about um China's place in the competition against TSMC, ASML, the rest of the like kind of western semiconductor supply chain?
2:29:02
>> They've never caught up, but they're closer and closer.
2:29:04
And as they get closer and closer, the profits among the leaders are going to shrink because they're going to be outcompeted by China.
2:29:11
>> You've already seen this happen in memory chips, which is simpler, but Micron has been kind of struggling for quite a while.
2:29:17
Intel struggles have almost everything to do with itself and nothing to do with China.
2:29:21
But it could also be that once China gets much better at foundry then you know a lot of orders will shift to SMIC which might be able to offer a lot of uh cheaper alternatives.
2:29:31
So I don't think that China will catch up to TSMC um in the next let's say 10 years. It might never catch up.
2:29:38
China also might never catch up to ASML.
2:29:40
But if it is just consistently following behind and it's good enough, um, you know, maybe that extra quality level is not worth triple the prices.
2:29:49
And that's always been China's success, right?
2:29:50
They they they make, >> you know, 80% as good at half the price, and that's good enough for most people.
2:29:56
And once that shifts, then a lot of the leaders stop having profits, too.
2:29:58
Are there any um are there any moves by the United States in the competition for semiconductors with China that you would like to see America avoid or you'd like to see America particularly go down a particular path in terms of uh the semiconductor competition?
2:30:19
I think that America should import a lot more Taiwanese engineers, send them to Arizona, send them to California, wherever it is, and then just bring all of their process knowledge and to, you know, manufacture in the US instead.
2:30:30
The US isn't hasn't done a great job supporting Micron, hasn't done a great job supporting Intel.
2:30:37
I'm skeptical that nationalizing these companies is really going to be a good solution.
2:30:40
But the US has everything it needs to succeed in chips.
2:30:45
you know, in Intel um hasn't been good, but Nvidia and Apple could shift a lot more of their orders to, let's say, a better Intel or a better TSMC, >> import a lot of ASML um equipment and then just become a lot better at that.
2:31:01
It has a lot more resources um and much more capabilities than China does now.
2:31:05
>> Yeah, the yields in Arizona seem particularly good.
2:31:07
I'm not sure where I heard it, but someone was saying that there was potential the potential of uh TSMC spinning out the Arizona assets, which I think might be quickly made a meme stock, but um certainly would be an exciting exciting develop.
2:31:21
>> How do you expect the trade war to resolve between us uh the US and China just given Trump's more up-to-date messaging around uh signaling that, you know, we're actually we actually might be friends after all.
2:31:36
every time it gets close, uh, there's always the chance that it falls apart.
2:31:40
And I've seen that the trade deals fell apart several times, uh, when I was living through the first trade war in Beijing.
2:31:46
And so, I want to be optimistic that these two countries come to some sort of agreement so that, you know, we don't have the world's two biggest countries at each other's throats, two biggest economies at each other's throats.
2:31:58
But I'm not really optimistic.
2:32:00
Uh Trump is erratic and sometimes he wants to make a deal and sometimes he doesn't.
2:32:05
Um and even if Trump and she come to some sort of agreement, I'm not sure if that's really good for the world.
2:32:12
What if Trump decides that he's simply going to gift Taiwan to Beijing?
2:32:17
You know, I don't think that would be good for the world.
2:32:18
Um and I think there's a lot of European countries and other Asian countries who are really nervous that they they do come to some sort of accord.
2:32:25
So, I don't have a I don't have a good sense of what what is the right move here.
2:32:30
>> How do you think China is thinking about Taiwan?
2:32:32
There's there's a I think America comes to the Taiwan conflict with a very cold war mindset, a very uh a very kinetic warfare mindset where I've heard more interesting theories around sort of like slowly shifting the population with propaganda and political influence and just creating a more a more pro-China Taiwan over time.
2:32:57
being very patient might be something that's like more in the direct playbook uh of China.
2:33:06
What's your current thinking on how how China would like Taiwan to play out if everything went according to plan over the next like decade or so?
2:33:16
>> China has had this patient strategy for a really long time.
2:33:18
Uh and then it tried to shift the population with propaganda and it was on course to work until they blew it up themselves uh by being really mean towards Hong Kong.
2:33:28
So, China promised Hong Kong that it's going to have essentially 50 years of freedom and it did have about 20 years of freedom and then she uh went back on basically Diaoing's word and they crushed it.
2:33:39
And so after that, you saw that the Taiwanese population don't have faith that uh China would actually respect any of their own wishes.
2:33:47
And so I think what we're thinking about now is I don't think that a kinetic action, a big confilration in the Pacific is uh the most likely.
2:33:55
Yeah, >> I think the most likely path is just some sort of status quo which the two, you know, US, Taiwan, China don't really try to do anything big and if anything more likely than a kinetic action would be some sort of a blockade to surround Taiwan and then uh the US would be in this kind of a tough position to have to be the initiator to break the blockade uh rather than you know being the defender of Taiwan.
2:34:18
And so I think that that is kind of the challenging politically challenging thing that Beijing would like to put uh the American position in. >> Yeah.
2:34:28
Well, hopefully it's resolved peacefully.
2:34:30
We'll continue uh monitoring the situation.
2:34:32
Thank you so much for coming. >> Yeah. Congrats on the launch.
2:34:36
>> Congrats on the launch. >> Thank you very much.
2:34:37
Get our copy and uh >> yeah, we'll talk soon. >> Have a great day. We'll talk to you soon. >> Bye. The book is Breakneck.
2:34:43
You can go and check it out.
2:34:45
Dan Wag you for >> right up the charts. >> Yeah.
2:34:48
Send it up to the top of the charts.
2:34:50
Uh, our next guest is in the reream waiting room.
2:34:52
We have Nick from Adio coming into the studio. >> Sharp. >> What do we got? >> Fantastic name. >> The news. Give us the news. >> What's happening? Welcome to the show.
2:35:06
>> Hey guys, how you doing? >> Great. Uh, late for you, right? >> It is. It is.
2:35:11
Uh, especially when you are you've got two toddlers asleep in the house.
2:35:15
This is um well past bedtime. >> Yeah. Yeah.
2:35:18
Well, I know how that goes and uh I'm Yeah, I'm glad you were able to Always good to get them.
2:35:21
It's good to have like a meeting set for, you know, somewhere around bedtime.
2:35:26
It's like extra incentive to have bedtime. >> Yeah.
2:35:30
And and also dodge the duties of putting them to bed. So, it's all good. Thank you. >> Good. Good. Uh well, big day. Big day.
2:35:37
Uh congrats on on the raise.
2:35:37
I have the uh the gong mallet here ready if you can give us uh the details. >> Absolutely.
2:35:46
So, we are very very excited to announce our $52 million series B um led by Google Ventures with lesson. There we go. >> Sorry to interrupt. >> Um fantastic.
2:35:59
Um breakdown uh give us I mean first time on the show.
2:36:03
give us kind of the full kind of abbreviated but full history of of the company >> uh and how you guys got to this point because it hasn't um uh is a big milestone but uh certainly been at it for a little while now. >> Yeah, absolutely. No, big long journey.
2:36:20
Um so uh you know fundamentally what what we do is we build an AI native CRM and uh what that means is a very very flexible data model uh allows businesses to mold AIO to to their go to market motion rather than having to do it the other way around which has been the way software has worked for a while. >> Yep.
2:36:41
>> And then uh a massive amount of data ingestion which gives us all of the context to automate action essentially.
2:36:49
Um, CRM is a big product to build, a very big product to build.
2:36:52
And there's not really an MVP of a CRM.
2:36:55
>> Uh, it's a it's a big ask for a customer to adopt it.
2:36:57
And, you know, we we've got about 5,000 companies that that that have now adopted AIO.
2:37:02
But to get there, there's a lot of engineering.
2:37:05
And, uh, so we did three years of of engineering in a, you know, in the sort of startup desert pre-launch. Um, >> pre-launch.
2:37:15
Uh and uh yeah, so we did three years pre-launch of of just hard engineering grind and uh launched about two years ago. >> Incredible.
2:37:24
Um what uh yeah I guess like maybe talk about kind of the inflection points at what stages kind of uh kind of where LLM started to really unlock value for for customers and where kind of where you had those initial sparks because I think like when people for better or worse every CRM provider now says that they're AI native.
2:37:46
So I also want to understand like what what does that actually um what does that actually mean in practice and what kind of advantages do you have as a new player um that that hasn't you know been in the industry for a couple decades at this point?
2:38:01
>> Yeah I think I mean I think fundamentally we have two really big advantages.
2:38:04
So one is the quantity and resolution of the data that we ingest and building a data model that can do that.
2:38:11
So LLMs work great when they have lots of context.
2:38:14
Um and uh you know you need to you need to feed them that context.
2:38:19
And so one of the things that uh you know we we we worked one of the first things we worked on was this data model and being able to instantly ingest a company's uh you know emails, calendar, product data, etc. etc.
2:38:31
And so that was the bit that really took you know took took a long time to build especially when you need to do it at the scale you have to do it at for for CRM.
2:38:43
The other thing that um is is you know a big difference between um aio and and sort of legacy products is that we think that or we have a thesis that code is becoming the new no code.
2:38:56
becoming the new no code. So the idea of of no code and these kind of very complex UI uh that you have to learn and very steep learning curves you're not learning how to code but you're learning something pretty complicated um and uh you know especially when you start to hit up against edge cases etc then the UI become extremely complicated
2:39:16
and so one of the things that we've sort of engineered into from the offset was the ability to execute code inside of your CRM and you think if you think about what has made Salesforce successful is this infinite flexibility uh through very very complex um engineering processes with a you know with Apex and a language not many people know and huge amounts of difficulty. But
2:39:36
But what we what we do with that is build in this sort of native code execution very early and uh LLMs are are brilliant at generating code especially in these kind of safe um somewhat constrained environments.
2:39:51
Um and so that's another thing that we think is going to especially you know as this plays out is going to be a really really big deal.
2:39:59
This idea that software becomes so much more malleable because code is uh so much easier to generate.
2:40:05
>> How do you think about the right like where where's your focus on on the customer side?
2:40:09
Uh again CRM has so many different applications within different companies.
2:40:14
uh and it's in in the long run you can serve everyone but what what's the focus been to date in in the in the kind of 5,000 you mentioned? >> Yeah.
2:40:23
So the focus really is uh is um is on uh you know what we would consider builders.
2:40:28
So so people who like to get stuck into building things um the rise of the GTM the go to market builder is is pretty is pretty apparent now. >> Yeah.
2:40:38
Um and uh so about 50% of our customers are um are tech companies.
2:40:41
Um and and and even the 50% that aren't uh tend to be people who really want to get stuck into building something.
2:40:49
Um but but you know as as you said CRM has a huge range of users.
2:40:54
Uh and we think deeply about the kind of you know the consumer of the CRM that's the AE the SDR etc.
2:41:01
um all the way through to someone in RevOps um or or you know building out really complex um go to market motions and so we have to serve all of those customers um and you know we we focus a lot on making the consumption of the CRM super seamless as well and obviously AI has been incredible for that you know massive reduction in data entry and and stuff like that.
2:41:26
talk to us about uh gross margins.
2:41:28
They're they're in the news uh with a lot of companies sort of like just reselling inference.
2:41:33
Obviously, your business is very different than that.
2:41:35
It doesn't feel like I'm just paying you for tokens or or just output, but uh are there any examples of like customers where you've looked at their usage and you've been like, "Wow, this person somehow triggered like a million a million different calls and and ran up a big bell."
2:41:50
And uh are there any are there any lessons that you've learned from just like building an AI product that is on the back of inference and does have real costs that are somewhat variable? >> Yeah. Yeah. Absolutely.
2:42:04
And you know the uh like all good startups the um the the sort of approach we took to this initially was >> um it's not our focus right now.
2:42:14
in the last sort of six months, 12 to six months, um we've actually made incredible uh you know in incredible um gains there and we're in a very very good place now and that has been a combination of um I mean that's that's a combination of models getting uh more cost effective and us learning to use them better.
2:42:36
>> The one of the things that we can do for example is we can uh we we can decide at runtime which model is best suited for a task.
2:42:43
So I think this is now becoming a relatively mainstream strategy.
2:42:45
But if we're digesting an entire call transcript, we don't need to use the best reasoning model.
2:42:53
>> Um we can do sort of compaction first on a faster, cheaper model um and then put less tokens into a better reasoning model. >> Y it exactly. Yeah.
2:43:02
And so it's been a big engineering effort, but with a combination of all of these techniques um you know we have very very good uh margins. Yeah.
2:43:10
The other thing is um a lot of the the the the sort of the value that the LLM provides is is very apparent to the end user.
2:43:18
So it's work done uh and that's changing the way that we think about pricing as well.
2:43:25
>> And so you know CRM has historically been just a seat based uh product but I think increasingly we'll see that that will that will change.
2:43:32
Um and you know we now have a hybrid uh pricing model which is there is there is a seatbased aspect um and we give sort of very generous automation uh and uh sort of AI credits to those seats but if you want to go really wild and you want to replace a lots of work then uh you can buy credit to do that. >> Yep.
2:43:51
That makes a ton of sense.
2:43:51
Well congratulations in the round.
2:43:53
Thanks so much for hopping on the show.
2:43:54
We will talk to you soon.
2:43:57
Have a great rest of your rest of your evening. >> Absolutely. Thank you guys. Yeah. Nice to see you. See you.
2:44:03
>> Up next, we have Sean from Coinbase joining.
2:44:05
Uh, I want to get his reaction to this front page news about stable coins.
2:44:11
Wall Street calls for stable coin rethink as friction with crypto industry builds.
2:44:14
There's a loophole on industry yields apparently.
2:44:16
We're going to dig into it.
2:44:18
He's in the reream waiting room and now he's in the TDN Ultradome. >> Welcome. How are you doing? >> Good to see you.
2:44:24
>> Hey guys, I'm doing great.
2:44:24
Good to be here with you.
2:44:27
>> The chief business officer.
2:44:29
>> It's a great coolest title. >> The coolest title. It's the vast.
2:44:30
Uh anyway, uh give us a little your background and and what you're working on.
2:44:35
What's the most interesting thing in your world these days?
2:44:39
>> Yeah, first off, uh congrats on 100K pump for you guys in under a year. That's huge.
2:44:44
Um >> you know, we're just trying to keep up with the crypto charts here. >> Yeah.
2:44:50
My background, so like you guys mentioned, I'm chief business officer at Coinbase, so I oversee uh the broader company's uh strategy, partnerships, M&A investments, and a handful of other things.
2:45:00
Um, I actually started out my career uh wanting to be a a brain surgeon.
2:45:05
So, I studied neuros neuroscience at UCLA.
2:45:09
>> Uh, realized like late in college that uh I had a a big enlightening moment which was that I uh fainted when I first like saw that much blood up close and I realized like, hey, this isn't going to be the thing for me.
2:45:22
>> I ended up uh working in strategy consulting.
2:45:24
I know you guys have been talking a lot about Intel and semiconductors today.
2:45:27
Those were like some of my early clients there.
2:45:28
Uh we're doing a lot of due diligence for private equity firms and the like.
2:45:33
And um >> were you pounding the table saying go Pure Play Foundry in 2019?
2:45:39
>> Not quite like Ben Thompson just wrote about it.
2:45:41
We got to implement this. >> Yeah, exactly.
2:45:43
>> I don't know if you had the same clout back then.
2:45:46
>> Well, fortunately, >> yeah, after the consulting thing, you know, I wanted to get more on the uh the right side of the table in terms of allocating capital.
2:45:53
So, I worked in uh in venture at a a fund called Greycraftoft.
2:45:56
Uh we were actually based down in the arts district, John, down the street.
2:46:00
>> I've been to the office.
2:46:01
>> So, uh yeah, we were early movers there to the east side of LA.
2:46:04
But >> uh yeah, and then I jumped on Coinbase in uh 2018. So, >> yeah.
2:46:10
So, take me through the recent uh the recent history of your work at Coinbase, what you're focused on, what uh what is moving the needle for Coinbase and kind of this uh this next phase.
2:46:19
is it's obviously a very scaled company.
2:46:21
Um, but it's one of the it has to be one of the largest founder mode financial institutions now.
2:46:27
And I'm starting to stop thinking I'm thinking about it less as like yeah, it's the place where you buy Bitcoin and more just like it is a financial institution that does a lot of things and potentially will do kind of everything in the financial world over the next decade.
2:46:40
And that's >> and been extremely inquisitive. >> Yes. So yeah. Yeah.
2:46:43
G give us a give us a whirlwind tour. >> Yeah, totally.
2:46:47
I think two primary dimensions.
2:46:49
So historically, like you mentioned, I think Coinbase has primarily been known as this place where we make it really easy and secure for people to buy and sell crypto assets, right?
2:46:57
Uh and uh people know us for the first party applications, the Coinbase Blue app, which has been great.
2:47:02
Uh but we're broadening that out now to support a wide range of different assets.
2:47:06
I I think fundamentally it's driven by we think that all assets are going to get tokenized and be onchain in some capacity.
2:47:14
It just provides better infrastructure for uh financial transactions.
2:47:18
And so we we announced pretty recently that uh you know for the first time Coinbase is going to be building what we call the everything exchange and supporting uh things like equities, prediction markets.
2:47:28
Uh we opened up uh through the Coinbase app now that you can uh trade assets directly on dexes.
2:47:35
M so uh in general what we see is basically the blurring of these lines between what was offchain and onchain and uh we want to make a very simple and seamless user experience for people to uh access the all of these assets that are going to be onchain. So that's yeah go ahead. >> Yeah. Yeah.
2:47:54
I mean in in general um super on board uh I feel like liquidity just lowers cost of capital allows businesses to do more impressive things. It's it's good.
2:48:04
Obviously, there are areas where um I I'm particularly thinking of like stocks on chain.
2:48:12
There's situations where like I don't know that I'd want someone to be trading shares in my company all the time.
2:48:16
So, how are you thinking about that market evolving?
2:48:21
Uh obviously there's a huge benefit to getting access to capital without some of the over like the the the cumbersome nature of the like reporting constraints of going public and all the all the different issues with floats and IPOs.
2:48:36
Um but how are you thinking about the the the the path to bringing more assets on chain?
2:48:41
What's the most logical and then what's further out on like the the long long time horizon?
2:48:47
Yeah, I think it starts with the regulatory front and that's where we see like the biggest uphill battles.
2:48:51
So, you know, uh right now it's sort of like invogue to talk about tokenized stocks and the theme of tokenization and tokenization isn't really anything new.
2:49:02
You know, when we co-founded USDC in 2018, that was it's a tokenized dollar, right?
2:49:07
Like it is a dollar on a blockchain and at that time people were sort of like what is this thing good for?
2:49:12
But now they realize like hey you have uh all these benefits that are just uh come with the asset when it's on chain.
2:49:20
So you get programmability, interoperability, global access, all those types of things.
2:49:24
So public stocks that's this is like the the new thing that people are really excited about and we're really excited about it too actually.
2:49:30
You know, in 2021, I was helping take the company public uh uh through our our direct listing, and we actually explored uh issuing a tokenized version of coin Coinbase simultaneous with the uh exchangeel listed version of coin.
2:49:45
And you know, that was always the dream where you could basically have an a user that holds the asset onchain and if they wanted, they could redeem and hold the asset on NASDAQ or go vice versa depending on their preference.
2:49:56
M >> and we just ran into uh a number of different regulatory blockers in 2021 where we realized that wasn't possible.
2:50:04
And so I think the regime change in 2025 makes it uh much more collaborative.
2:50:10
There's uh a very healthy birectional conversation that's ongoing around you know what are the uh rules and requirements for an asset that's traded on chain.
2:50:19
Do you need to be does it need to live in in the environment of a broker dealer in a national securities exchange or does it not?
2:50:25
Uh so we're really excited about um the regulatory environment progressing with uh the benefits of the technology.
2:50:34
>> Is there a great argument right now that you've heard for uh how like your average American benefits from stable coins?
2:50:41
Because I I I've I've literally paid people internationally in stable coins. It is amazing.
2:50:46
And if they don't have access to dollars otherwise, like in a high inflation country, I totally get that.
2:50:52
Um but is there a way to contextualize it for somebody who isn't doing any international business and is America is is an American like what what are the benefits uh besides like you know programmability abstractly?
2:51:06
>> Yeah I would say right now most of the benefits are really crossber transactionoriented but like you know the one that I think will resonate with a lot of people who are Americans even is you know if you're hiring freelancers or contractors around the world like how do you get them money?
2:51:19
uh these are people that you might need for like a one-time job or for like just a few weeks.
2:51:26
>> Uh it's a lot easier to do that and uh you know we have a partnership with Stripe where Stripe is enabling stable coin payments through USDC on base and uh one of Stripe's key customers is remote.
2:51:38
com and they start to see that this is just a naturally native better way for small startups and founders in the US to pay freelancers regardless of where they are in the world.
2:51:47
where they are in the world. Do you think that uh with like the freelancer are they more just excited about getting dollars or do they actually care a lot about like the yield that comes from treasuries and all of that because it
2:52:00
feels like they're they're both important but I have trouble waiting them like what do people care >> one obvious benefit is just getting the money immediately versus having to wait days potentially 10 days just get your money even after the client has hit pay. >> Yeah. >> Yeah. >> Yeah.
2:52:17
I think the thing that has become clear is there is just insatiable demand for US dollars around the world.
2:52:21
Like everybody wants US dollars but it's really difficult to access US dollars to.
2:52:29
So, John, I think to your first question, the the pain point is really I want dollars or a safe, stable currency.
2:52:36
And then, Jordy, to your point, it's like I want it as quickly as possible uh in a in a form factor that I know and I trust.
2:52:43
And uh you know, we started to see this kind of organically a couple years ago where a lot of people in Argentina and a lot of other countries were just like natively finding their way into uh dollars, stable coins.
2:52:54
And in those countries, you know, we we spoke with a lot of customers and it's it's normal, right?
2:53:01
Like you look for different stores of value, whether that's, you know, buying real estate in the US or gold or Bitcoin and stable coins are just a a natural and uh more relatable form of store of value for a lot of these people. >> Yeah.
2:53:14
Can you talk about the significance of the Darabit acquisition that you guys just completed?
2:53:20
>> Yeah, we're really excited about it. We just closed it.
2:53:21
For uh context, Darabit is the uh world's largest crypto options exchange.
2:53:27
Specifically, they've had about 80% market share in crypto options uh for the last 8-ish years or so.
2:53:33
So, kind of like up and down through the uh various crypto cycles.
2:53:38
And in in the crypto markets, uh derivatives are orders of magnitude larger than spot markets.
2:53:46
Coinbase kind of grew up and got its uh foundation and its roots in helping people seamlessly go from fiat currency, primarily US dollars and euro and GBP into crypto.
2:53:56
Uh and the derivatives markets have have just sort of like ballooned in size.
2:54:01
So over the past year or so, we've made a big push into the derivatives markets.
2:54:04
Uh we have uh exchanges in the US and internationally that support uh a handful of products.
2:54:12
But Darabbit really for us brings us market leadership in this options category that we think is going to grow tremendously.
2:54:18
It's also a differentiated capability that uh will basically pull together spot options and futures as different trading products together into one exchange uh platform.
2:54:33
And what that does for users is really two things.
2:54:35
One is it creates new trading opportunities.
2:54:38
A lot of people will like uh buy spot and short features and you can do that now across more more instruments just on one place.
2:54:47
>> Um and then the second thing is it unlocks more capital efficiency and this is really a key one is whenever you put on >> let's give it up for unlocking capital efficiency. >> Love to see it.
2:54:59
>> Doesn't get better than that. >> Yeah.
2:55:00
Uh whenever as you guys know it's like how do I get the most bang for my buck quite literally right?
2:55:05
So if you can trade across all those different assets, you hold $1 or one crypto asset with Coinbase, then you basically can get margin and cross margin across all these different products with that $1.
2:55:18
So it's it's just a better trading experience overall for uh for people who move in size. >> Very cool. Let's hear for people.
2:55:23
Let's hear for people that move in size. >> Play the eagle sound. >> There we go. >> I love it.
2:55:33
>> Thank you for coming on.
2:55:33
You're always always welcome. >> Yeah, anytime. We'll talk to you soon.
2:55:37
>> And congrats on the on the new title. Well deserved. >> Well deserved.
2:55:41
>> Up next, >> we need to we need to we need to make somebody the chief business officer here. >> Yeah, it's up. >> Simply too good.
2:55:48
>> Tyler, are you going to take it? You're going to take it? >> You're the chief.
2:55:50
Chief intern officer, the CIO. >> CIO.
2:55:53
But you know, any day now he could get promoted.
2:55:55
Anyway, in the reream waiting room, we have Brian Pellegrino from layer zero. Oh, sorry.
2:56:00
No, we have >> Okay, sorry. We have a switch.
2:56:07
>> We are >> We have >> Ryland from Reframe. Right. There we go. >> Sorry.
2:56:12
We're having technical difficulties over here. >> Welcome to the show. >> Good to meet you. >> Great to be here.
2:56:16
And I'm glad you guys have Ryland on, too. Old colleague of mine. >> Oh, no way. That's amazing. >> From what era?
2:56:24
>> Uh, we were both at KA and Amazon Robotics maybe 10 years ago. >> That's very cool. >> Awesome.
2:56:29
Uh I had a friend who just uh got a tour of an Amazon facility.
2:56:32
They said like on site just on this one facility they had like 10,000 robots or something and they built the whole facility uh like 6 months ago.
2:56:40
They said they're already two versions out of date from like what the next stage of Amazon's buildout is.
2:56:45
It was like the most impressive tour he's ever done.
2:56:48
Anyway, we're not here to talk about Amazon.
2:56:49
We're here to talk about kick us off with an introduction on yourself and what you do. >> Wonderful guys.
2:56:54
Well, it's great to be here.
2:56:55
I'm Vicas Enti uh CEO and co-founder for Reframe Systems.
2:56:58
Uh we're on a mission to build climate resilient homes for everyone.
2:57:02
And uh we're doing this by applying some cutting edge robotics and algorithms with microactories uh that we can deploy within 100 days to build uh pretty impressive good-looking homes uh in neighborhoods all around the country. >> It's great. >> Incredible.
2:57:15
And the news today, give it to us.
2:57:18
>> Uh we've uh raised a $20 million series A. Uh super pumped up. not as pumped as us. >> Not as pumped as us. >> Congratulations. Um, incredible. Incredible.
2:57:30
When when did you start the company and and I guess what what was the initial catalyst? >> Yeah.
2:57:36
Um, we started about 3 years ago uh with the pitch tech.
2:57:38
Um, and uh the catalyst was as simple as me becoming a dad.
2:57:43
Uh, my twin daughters are four years old now. >> Oh, twins.
2:57:47
>> But they were they >> Yeah.
2:57:48
So, they were uh um yeah, the catalyst to kind of take a step back and think about uh what else I should be doing in my time besides getting boxes to people's doors faster.
2:57:56
And I decided I'll get bigger boxes to people's doors that boxes people can live in right now.
2:58:02
>> You're you're committed to making boxes go faster.
2:58:05
Basically, you find what you love. That's my super.
2:58:07
What kind of what kind of yeah it feel I mean obviously reframe is trying to provide a solution for one of the biggest problems I think facing our our country.
2:58:16
Uh where h how have you thought about kind of narrowing in and focusing go to market what what markets are important and and what does success look like in the in the early days?
2:58:30
>> Yeah, maybe I can kind of talk from what the big picture is for us.
2:58:32
We want to build a million homes by 2045.
2:58:33
That's twice as fast as what how long it took Dr.
2:58:38
Horton, the largest home builder in the US to build a million homes.
2:58:39
But the places we're going to be building homes will look vastly different.
2:58:43
Uh if you think about where homes are getting built today, they're out in farmlands that have been converted.
2:58:48
They're far away from existing communities.
2:58:49
Like that's the only place you have land available for large scale optimized builders.
2:58:54
We believe that by applying software and robotics, we actually change that equation.
2:58:58
We can actually be just as efficient as them.
2:59:00
but in infill neighborhoods.
2:59:02
How do we actually build a 100 units not in a single lot but on a bunch of scattered sites in a neighborhood in Palo Alto or a neighborhood out in Somerville or Cambridge, Massachusetts?
2:59:10
And we believe that by leveraging software we actually get to a world that we define as mass customization.
2:59:17
How do you convert existing building designs to have it be compliant with any site but make the marginal cost of this change go down to zero because software is in the loop.
2:59:27
Robotics is in the loop and whoever can achieve that end state can get the same efficiencies of a production builder on scattered sites.
2:59:33
And we believe that's our our path for actually getting and creating the type of housing that people actually want to live in in neighborhoods people want to live in ideally at price points that are also significantly better than what's out there today.
2:59:44
Uh so we're currently focused on markets that are building homes for over $400 a square foot.
2:59:49
So the markets on the coast, so New England, so we're currently based in Massachusetts.
2:59:54
Uh we'll be as part of the series they will also be launching capacity out in Southern California to help with the LA wildfire rebuild.
3:00:01
>> So LA is also a target market.
3:00:01
Uh and then we have markets out uh so Salt Lake City, Utah, and then Denver adjacent.
3:00:09
And then Seattle and Washington DC adjacent uh would be other markets in the future.
3:00:12
How does uh is what is the process to start working with uh somebody that ultimately wants to buy a home?
3:00:21
Are you working with developers that are developing entire neighborhoods or can somebody just go to your website and say I want one house please? >> Yes.
3:00:30
So today we're very focused on working with developers.
3:00:32
So it's still a B2B sales motion for us.
3:00:34
Uh we believe that the best customer is a repeat customer.
3:00:37
And this is why we're trying to build a pretty long-term multi-year pipeline.
3:00:41
Uh we have sold to individual customers, but the experience for them doesn't resemble that of a custom home builder.
3:00:47
Like you're still building off of our product portfolio.
3:00:48
We will customize our product to meet the site.
3:00:52
We're not going to design a groundup custom building.
3:00:54
And as if customers are fine with that and that's the experiment we're testing out with LA cuz now we're working with homeowners who've had their previous homes burned down and we're trying to help them rebuild.
3:01:03
uh and we're able to make good progress with customers who realize they're going to get a better product significantly faster working with us, but they'll have to make some trade-offs in what the product is and what their expectations are.
3:01:15
And that's been an education process.
3:01:17
And we've actually been surprised that people actually just want limited set of choices.
3:01:21
If you can give them choices on things like cabinet colors, uh a few different arrangements of windows, etc.
3:01:26
, They're actually pretty happy with the process versus saying, >> "Right, you can only get one color as long as or any color as long as it's black, right?"
3:01:34
I think that that doesn't definitely doesn't work out here. >> Yeah.
3:01:38
>> Doesn't fly in a house.
3:01:38
Um and the whole aspect of mass production doesn't work for construction either.
3:01:42
Uh which is why we've had to embrace uh customization.
3:01:46
>> Yeah, that makes sense.
3:01:46
Um what uh what do any of these stick out as factors for your business?
3:01:51
uh uh self-driving cars potentially making it easier to people live in farther away suburbs or uh just the the adoption of technology in cities.
3:02:02
You can live in a smaller house because you can put on a VR headset and you don't need a home theater anymore.
3:02:06
Or you can, you know, go to a a local gym instead of needing a home gym or a library because you don't need a home library.
3:02:12
Um or even like the ADU thing in California, the idea of building more smaller houses on on existing plots of land.
3:02:20
or any of those factors that you think about.
3:02:23
>> Yeah, so the ADU factor has been great, right?
3:02:26
I think it's actually spurring a whole bunch of upzonings.
3:02:27
You can actually add more units into existing properties.
3:02:30
It changes the calculus even for developers trying to develop new properties.
3:02:34
They get to add additional density.
3:02:36
>> Um, and we're also seeing this trend where people are actually okay living in smaller spaces which also results in us being able to build homes that are right more space efficient.
3:02:44
more space efficient. Yeah, >> but the place that we're also keying off of and right I think from the practical standpoint of self-driving cars solving the logistics challenge while that is true we're also noticing a generational shift taking place if you actually look at buyer sentiment for right zoomers are coming into the market eventually what we expect Gen Alpha to also envision there is a loneliness pandemic they're
3:03:04
looking to build more connection and community and I think their desires are actually vastly different than what was true for the boomers all the way through the millennials and gen buyers so I actually think we'll see a migration of people coming back into cities or or pockets of communities that are more denser and more connected than what they were for how development took place for the last 20 to 30 years. And the only
3:03:22
And the only way to be successful in that space is how do you actually embrace scattered side development in full development? >> Sure.
3:03:29
>> And not build the 300 unit apartment building.
3:03:31
People only live there because that's the only choice.
3:03:33
People don't live there because they want to live >> with 300 other people who are complete strangers. Right. I think so.
3:03:38
This is a place where we get to refactor what housing of the future looks like.
3:03:43
Because not just the form, but just the function of how it's connected to neighborhoods, but the only way to unlock that is again >> round up new technology.
3:03:50
>> You said a million homes by 2045.
3:03:50
When do you want the first home to be built?
3:03:57
>> Well, we've already built our first home. Uh it's occupied today.
3:03:58
So, we built our first home about 18. Thank you. >> Fantastic, >> man.
3:04:05
I need to get I need to get one of those buttons here.
3:04:06
Um, we'll license you the the air horn >> every time you guys have complete a new home.
3:04:14
But, uh, congratulations on progress.
3:04:17
It's it's, uh, tremendous.
3:04:18
>> We'll talk to you soon. Have a good day. >> Cheers. >> Take care.
3:04:22
>> And our next guest is in the reream waiting room.
3:04:24
We will bring them in to the studio.
3:04:27
>> I believe we have Brian from Layer Zero.
3:04:29
>> Welcome to the stream. Play that soundboard. >> Here we go. this. Look at this background. >> There we go. How you doing? >> Hot. >> How you guys doing? >> I'm good.
3:04:40
You got some news for us? >> Waiting. >> What you got? >> Yeah. Got got lots of news.
3:04:43
What do we What What do you want to go through? >> Kick us off.
3:04:47
What's the biggest news in your world?
3:04:50
>> Biggest news in our world is we just wrapped up the largest DAO acquisition in history. About $120 million. Uh yeah, >> congrats. >> Crazy. Okay.
3:05:00
>> Crazy. Okay. uh break break that uh break that down for the a what does that actually mean in practice uh and and kind of why why why did it make sense for for layer zero and um yeah basically to combine these two businesses >> yeah so I mean there's a little bit of
3:05:18
context here that's originally we built layer zero we actually built Stargate as well and spun it out and sort of was running as this independent uh entity and we now have like refolded it back in with this acquisition right so so it's coming back home. There's been kind of
3:05:30
There's been kind of meme that the bridge is coming home finally.
3:05:33
And so, uh, for us, layer zero already today, uh, you know, 86% of all dollars that move across chains happens through layer zero.
3:05:42
Largest stable coin in the world is built on us.
3:05:44
Largest wrapped bitcoin asset, largest synthetic yield bearing asset, like first stateisssued dollar with Wyoming.
3:05:50
All all of this is already there.
3:05:52
So, we're doing that side of things.
3:05:53
you have on the background of of Larry Frink saying, "Listen, every every stock, every bond, uh, every asset is going to be tokenized."
3:06:00
Um, so like we're already sitting there.
3:06:03
Stargate is the consumer touch point, right?
3:06:05
Stargate is where the end user facilitates where we've sat in the background.
3:06:09
And so for us, this was just purely a verticalization of the entire stack.
3:06:13
It's roll up the whole thing, have a single touch point, single offering to both developers, merchants, and the end consumer and have it in one single place. >> That's awesome.
3:06:22
So, so breakdown um like what did the what did the what did the entity that was Stargate prior to this acquisition actually this was uh DAO >> DAO was thrown around uh I think our audience some some people in our audience are more crypto native but but many others aren't and so they may have heard about Dows back in 2021 2022 uh but but are less familiar >> Yep.
3:06:47
DAO is sort of uh fascinating uh idiosyncrasy within crypto itself, right?
3:06:53
So uh DAO is decentralized autonomous organization. We built this protocol.
3:06:57
We launched it and then we basically said, hey, governance is going to be left up to all the people who hold the token, right?
3:07:03
So there's a bunch of people who hold the token.
3:07:04
They have the ability to stake and and actively vote on all kinds of things.
3:07:07
How things get priced, how the dollars that the protocol owned.
3:07:13
So the protocol had accred about $95 million worth of worth of assets itself internally like all kinds of things within it.
3:07:19
uh and it was just running and naturally as you can imagine something that gets run by, you know, 50,000 people as opposed to a small group of very agile, fast-moving uh entrepreneurs runs very differently, right?
3:07:33
And so what's meant is a lot of things are slower than you would like them to.
3:07:36
Innovation is sort of like slow in that side.
3:07:38
So I mean it was very dominant from a bridge perspective.
3:07:42
That's what Stargate does is move assets around.
3:07:44
It's done about $80 billion worth of assets transferred.
3:07:46
So the largest bridge in the space, but purely on the innovation side and to keep moving forward much slower than kind of you would hope.
3:07:54
And so uh the offer from the layers side was listen >> we're going to basically buy out uh these STG this governance tokens STG uh we're going to pay a premium on top of what exists.
3:08:05
Um so we're going to pay an offer above kind of what's there and the Dow gets to vote on whether or not uh to basically accept this or not.
3:08:11
And so we paid again close to about $120 million at at at current market price.
3:08:16
And so what happens is they get rid of their old token.
3:08:19
They swap it for this new one.
3:08:21
They now have, you know, this $120 million. So they're made whole.
3:08:23
They're invested in in the future direction of the new thing.
3:08:28
And now universally that stack, those assets, everything drives in a single direction.
3:08:32
So what was Stargate, what it was acrewing value internally, revenue streams internally, now all drive directly to layer zero.
3:08:40
How does it >> is that the largest like take private in in in crypto history? >> Yeah.
3:08:46
Largest largest D acquisition ever in history.
3:08:48
Really like really um not uh definitely not common.
3:08:52
I think might might become more common but definitely very unique. >> Yeah. Yeah.
3:08:56
Are there like lawyers in the room?
3:08:58
Is this all executed on chain?
3:09:00
Is this is this >> everything everything onchain through the DAO.
3:09:03
So it's not like uh you know we don't have an agreement that we can sign with the DAO.
3:09:07
It's it's really was an offer.
3:09:08
So an acquisition is sort of how the industry is internalizing it because that like makes sense.
3:09:13
What what it really is is hey >> the DAO is going to vote to sunset their own token take this other asset in place of that and basically migrate the the whole system over and they're getting a premium for doing that.
3:09:24
It looks more like a GitHub PR than uh than like a traditional like filing from a >> Has to be one of the most Yeah.
3:09:31
one of the most efficient acquisitions from from the cell side >> from a from a cost and and legal standpoint. >> Checking on the bank.
3:09:42
>> What what what uh what should we be looking out for in the back half of this year?
3:09:46
for I mean four months I guess at this point but in in terms of uh uh assets coming coming on chain and tokenization broadly. >> Yep. Yeah.
3:09:56
I mean like right now what we've become most well known for where we sit is is stable coins.
3:10:01
Almost every you know the large majority of stable coins are built on top of this pay you know PayPal USDT all of this stuff built moves through layer zero right.
3:10:10
Um, so stable coins have been a bread and butter.
3:10:13
That has been the focus of really what we're trying to do is is the the cleanest and most efficient money technology ever. Right?
3:10:19
That's really our pitch internally is is the way that value moves.
3:10:23
And what you're going to see in the coming months uh and then accelerating very quickly from there is is you know hundreds of of tokenized equities, stocks moving on chain.
3:10:31
Uh all of this again moving out of these same rails.
3:10:36
So like the layer zero what what makes it so special and what has you know we're talking hundreds of billions of dollars of assets moved is is you can move today you know $5 million $50 million for for for you know cents or low dollars right like incredibly efficient to move extremely large amounts of capital around all of these ecosystems.
3:10:55
So when you talk Stripe and Coinbase and Robin Hood and Circle all are launching their own networks, right?
3:11:02
And all of these platforms are racing for tokenization for issuing uh equities on chain.
3:11:07
Again, all of you know this this entire sort of Larry Frink 2025 mandate of like this is the way that the world is moving.
3:11:13
None of those have the ability to talk to each other, right? None of them.
3:11:17
There is no way right now that you're going to settle between Coinbase and Robin Hood or that you're going to u be able to move these assets anywhere.
3:11:24
So that is where we sit all of this flow that again has been historical stable coin flows these hundreds of billions of dollars of stable coin flows now you're talking every asset that exists and so very we're very directionally focused on that.
3:11:38
>> Fantastic incredible seem set up for success.
3:11:41
>> Yeah we'll come back come back on again soon.
3:11:42
There's going to be a lot more here and we should have a longer conversation and congratulations on uh >> on the take private the acquisition whatever we want to call it but uh very cool to be >> we'll talk to you soon. >> Have a good day. >> Love to. Thank you guys so much. >> Thanks for coming on.
3:11:58
>> Our next guest is in the reream waiting room.
3:12:00
Let's bring them into the studio.
3:12:03
I think we got to get the gong ready again.
3:12:06
>> Ryland, what's happening? >> Great to see you.
3:12:08
>> Hey guys, good to see you guys.
3:12:10
>> Sorry to keep you waiting. uh give us the news.
3:12:12
Welcome back to the show. >> Thank you.
3:12:15
It was doesn't seem that long ago that I was on the show, but we raised our series A today led by Google Ventures and Dello. >> Wow. >> $50 million. >> 50 boom.
3:12:25
>> Uh GV's been busy today. >> Busy today. >> Busy day.
3:12:28
They haven't They're not taking They're not taking August off. >> Yeah. Yeah, that's true. >> Um >> incredible.
3:12:34
Uh yeah, give give us the update since uh since the last time you were on.
3:12:38
It must have been probably two two three months. Um I'm also interested.
3:12:42
I think I'm an investor in this round, right? >> You are. >> Yeah. Yeah. I didn't know.
3:12:46
You guys have been moving.
3:12:48
You guys have been moving very quickly.
3:12:49
You know, you never Um but uh but yeah, what what's the update?
3:12:53
>> Um so we announced our sort of seed round came out of stealth in the spring.
3:12:58
>> Uh that round was just to get the company going, get the team together and start developing some of the key tech for what we're building.
3:13:03
And we're building and designing autonomous ships for the Navy.
3:13:06
M and now with the series A, we're actually able, as one of our investors said, we've left the reservation.
3:13:11
We actually built a full prototype ship which will launch this year for the Navy.
3:13:15
So when I say full prototype ship, talking like half a football field in length.
3:13:19
So we're, you know, there's a lot of uh unmanned service vessel that the Navy is working with today.
3:13:24
Some are smaller in form factor, a little toural, they're great for choke points. Yep.
3:13:28
Uh, but we're building ships that are meant for like the open ocean that can operate all the way across the Pacific >> and they can fit like basically a full shipping container on board if not multiple.
3:13:38
And then so you could put potential >> so in this case you're getting half a football field that is what the ultimate size will be but your campus >> it's kind of like the it's the Goldilock.
3:13:47
So like we want to carry payloads that matter for the Navy.
3:13:48
And so if you think about the payloads that >> today's guided missiles destroyers carry, you can actually disagregate them and take one or two of those payloads, whether the radars or the equipment look to hunt for submarines or even missile launchers and put them on these smaller size ships.
3:14:03
Y >> so they're big enough that you can operate across the ocean.
3:14:06
You can carry the payloads that matter.
3:14:07
We have the range and endurance for the Pacific, but we're not so big that we cost an arm and a leg.
3:14:14
And so we're making ships that are traitable.
3:14:16
They're reusable, so you can send them out and they come back.
3:14:19
>> Uh, but if you lose them, it's okay.
3:14:19
And it's relatively inexpensive compared to like a $2 billion destroyer. >> Yeah.
3:14:25
We talked to Dan Driscoll at about the Army modernization project.
3:14:27
Uh, what's going on with the Navy?
3:14:30
What does it look like to sell into the Navy now as opposed to maybe 5 10 years ago?
3:14:38
>> Um, I would even talk about a year ago.
3:14:40
M so a year ago when we started this company we had a thesis around building the sort of goalie likes type ship sort of a medium the Navy would call it the medium unmanned service vessel um but it wasn't on the ship building plan there wasn't a ton of money around it but we
3:14:54
thought there was a need and so we started the company with just a you know a small check uh to start the company um but what's happened is there's actually $2 billion now uh for this program and so there's a ton of investment there's a ton of activity and a ton of uh attention uh around the space and so
3:15:13
right now it's us and a couple other companies that are with our own dollars building what we think the Navy needs uh and there's just an AOI that went out uh we submitted for it so we're super excited to see all the progress in the space >> how does the Jones Act fit into your business model does it affect you I've
3:15:27
heard I've talked to some folks who've said that it's making it difficult for them to source certain pieces uh if they're building in Europe or something uh obviously Europe has a long lineage of ship building, but um how does the Jones Act fit into your strategy or benefit you or or is it red tape? >> That's a good question. I don't know who
3:15:47
>> That's a good question.
3:15:47
I don't know who gave that one to you, but that's a a little bit spicy.
3:15:49
Um so, in a good way, because of the Jones Act, we have mid-tier shipyards either on the West Coast, the East Coast, or the Gulf Coast that actually can build our ship.
3:15:58
So, we don't need to start from scratch.
3:16:00
We don't need to go find a 100 acres of green field and try to go build a shipyard, which will take years to go launch.
3:16:07
launch. uh we'll announce later this year a partnership with the shipyard so we can actually build and launch our ship next year and if it weren't for the Jones Act I'm not sure if that industrial base would be around today >> but I think in some ways uh we're not as competitive as other countries in ship building and so because of that uh we've
3:16:24
had to go source some of our longle uh items from other countries um that have a sort of a deeper base around sort of ship building um but we think we can bring ship building back to the US and I think it's not by necessarily you're trying to compete in uh directly with countries like China or Japan or South Korea, but it's about out innovating them and sort of taking a lead on the tech side. And so we believe in, you
3:16:45
And so we believe in, you know, maritime autonomy not only for the Navy, but also for the commercial sector.
3:16:51
And we think there are a ton of different use cases that are out there.
3:16:53
We're already getting comfortable uh and you've seen in LA like hopping in a Whimo has zero drivers in the front and just taking that and sometimes it's a preferred kind of method versus having sort of a man vehicle that's out there.
3:17:05
we can apply that same technology for the maritime industry and we're super excited to do that. >> That's very exciting. >> Incredible. Very exciting.
3:17:12
>> Thanks so much for taking the time to hop on.
3:17:13
>> Congrats to to the whole team.
3:17:13
And uh yeah, we'll we'll at some point I I assume we'll do a podcast at sea >> on on one of your one of your ships.
3:17:22
The next time I the next time I'm on, I don't want it to be a funding announcement.
3:17:27
I want to like do a interview from like a shipyard and show you all the cool stuff we're doing. >> Your phone.
3:17:34
It's a Zoom link so we can get anywhere. >> Exactly.
3:17:37
If people want to see welding and steel and all that cool stuff, >> I want to see sparks. >> That'd be great. Yeah, we'll talk soon. Congrats. >> Have a good day. >> Cheers.
3:17:44
>> Up next, we have Logan Kilpatrick from Google coming in.
3:17:46
I think I have it right this time.
3:17:48
I got a little mixed up my calendar.
3:17:51
>> We're caught up to speed.
3:17:52
>> Logan, great to see you. Congratulations. Give us the news. What's the launch?
3:17:55
Is there a number we can associate this so we can ring the gong for?
3:17:59
>> We're looking for any reason to hit the gong.
3:18:01
Number of parameters, number of cost per token or cost per image or something. >> 0. 39 0. 039 cents per image. >> There you go. >> Congratulations. >> There we go.
3:18:16
>> Step back and contextualize it for us.
3:18:19
Give us the actual news, the actual update. >> Yeah. Super exciting day.
3:18:22
So, we launched I think folks have probably seen online this whole nano banana thread.
3:18:27
We should have gotten y'all in banana suits or something for this.
3:18:29
Um, >> yeah, we launched this new model, state-of-the-art image generation editing model.
3:18:36
I think what people are losing their losing their mind over is is just this character consistency of like how well you can do all of these like promptbased edits and like transform whatever people have.
3:18:46
I've seen all these great examples online already of of what people are doing.
3:18:49
Um, so it's awesome to see and it's a model that's available for free for everyone to go and play with and try. Gemini app AI Studio.
3:18:57
Um, you can vibe code some cool stuff with it.
3:19:00
I was working on a TVPN announcement card generator earlier. >> Oh, that's amazing. We need that.
3:19:07
>> It's I'm like I'm putting your media team out of work because No, I mean, the biggest thing there is speed.
3:19:12
I mean, it's just about the the ideas matter more. >> Yeah. Yeah. Yeah. I I love that.
3:19:17
Uh, what's the story on the on the research side that unlocked this?
3:19:22
Is this uh new algorithm?
3:19:25
Is it just more scale, bigger data center, bigger training run?
3:19:27
Is it some sort of unique advantage to Google on the data side?
3:19:32
Like what what went into achieving this?
3:19:34
Uh because I think people are tracking this stuff very closely these days. >> Yeah.
3:19:40
Yeah, that's a great question.
3:19:40
I think there's three things quickly that I'll mention.
3:19:42
I think one of them is there is this interplay between image understanding capabilities and image generation capabilities.
3:19:50
Um, and it's actually I was just talking to the VO team two weeks ago as well, and it's a similar story on video as well, which is like if you have state-of-the-art video understanding, it tends to be that that actually really helps you when you want to generate really great videos.
3:20:02
Um, and there's a bunch of dimensions of of why that's the case, but um, so I think that's part of it, which is from the ground up, Gemini was built to be multimodal.
3:20:10
So, it's been like the core focus um, from a from a modeling perspective for a long time.
3:20:15
So, I think we we see that now in the generation capabilities.
3:20:18
Um I think another one is like this this iteration flywheel that we had.
3:20:24
So we initially launched um this was actually before um OpenAI launched the GBT image model.
3:20:29
the GBT image model. we shipped the first like native LLM image generation model um and got a ton of feedback of things that like didn't work and people were uh you know you know wanted it to be better along a bunch of dimensions and I think so this this launch was a
3:20:44
culmination of like looking at and like spending a ton of time with folks in the ecosystem who've been giving us all the feedback of like what would they actually want this model to do in order to build a bunch of like real production use cases and use it to to support whatever their work is. Um, so I think
3:20:57
Um, so I think that's another angle of this.
3:20:59
I think the last one is just this like continued um model train that we have, which is like the there's all of this like infrastructure that's being built in order to make it so that Google can ship models um and bring them to the world and have them scale up on day one like we are right now and all this other stuff.
3:21:17
So I think um the the like new capabilities of of image generation I think benefits from like this huge amount of momentum and and inertia that's happening inside of Google to like get this stuff out the door.
3:21:28
Um so I think it like it helps and we see this on like every other model benefits by like how much momentum there is on the core model progress standpoint.
3:21:39
>> I have uh I have two follow-up questions.
3:21:40
One is uh are you thinking about some sort of paro frontier?
3:21:44
Do we need a benchmark for image generation that then we can comp to put on a beautiful X and Y axis so we can go viral here uh with cost to quality tradeoffs because I haven't I haven't really seen that pop up.
3:22:01
We're still in the age of just like there's like the state-of-the-art's great and then everything else I wouldn't want to use and and so people aren't really making those trade-offs.
3:22:11
You can imagine that as people start to implement this into business processes, if I'm just like, oh yeah, I'm just generating like an icon and you know that like a previous generation model can basically oneshot it because I'm not trying to do anything crazy.
3:22:23
I want to be very costconscious versus this super frontier.
3:22:26
I'm going to be using this as, you know, a poster in VFX and a Hollywood movie.
3:22:31
It's got to be the best and whatever the cost is, let's do that.
3:22:34
Are you starting to think about a front paro frontier kind of emerging in in image generation?
3:22:38
Yeah, I mean we should collaborate on this because I feel like y'all will do a great job on it.
3:22:43
So that's that's maybe an action item, but I I think one of the cool takeaways for me on this launch is actually the like cost per image um didn't change between 2. 0 and 2. 5.
3:22:53
So if you see the I think we released a graph of like the level of progress from 2. 0 to 2. 5.
3:23:00
It was literally like almost like doubled in quality across certain dimensions.
3:23:04
Um and it's the same 0 point.
3:23:07
It's like the pricing is annoying. It's like 4 cents.
3:23:11
>> Well, we're going to have to switch to like cost per million images at some point because just like cost per million tokens.
3:23:16
Like we if we tried to say cost per token, we'd be in like 0. 0000. >> 4 cents per image.
3:23:21
4 cents per image or $40 for a,000 images.
3:23:23
That makes it that makes >> Now we're talking. Yeah. 40 bucks for >> Yeah.
3:23:28
I think it's just crazy though.
3:23:30
There's there's so much that you could build that like you wouldn't have thought about building before at that price point.
3:23:34
like $40 is like not for a,000 images customized for whatever you want.
3:23:39
It's like actually not that crazy. >> Totally. Totally. >> Yeah.
3:23:41
How what what's the reaction been from some of your guys' partners on the on the API side in terms of this?
3:23:45
I mean, I'm assuming they got early access and exposure to it because I see a lot of them are already rolling it out to millions of of users.
3:23:55
>> Yeah, I think a great example of this and something that I'm super happy about is Open Router, which I'm sure you all have covered some of this stuff.
3:24:01
They have a bunch of like actually cool leaderboards that show like their leaderboards are all usage based.
3:24:05
So it's like >> Alex on the show the the CEO Alex >> Alex is awesome.
3:24:10
He's he's he's an incredible founder and entrepreneur.
3:24:13
>> He joined the day that he raised like$und00 million and didn't mention it at all.
3:24:17
Like we were >> he's a super low-key dude too. It's crazy. >> Yeah, he's awesome.
3:24:22
But uh so we are the first image model that Open Router has actually ever released.
3:24:27
And I think there's like a bunch of philosophical reasons why from a platform perspective, but I also think it speaks to like the level of quality and the progress that's been made on these models that Open Router wanted to like actually take the first step in and have like a model that they felt is like conversational enough for their customers to just like embed it into a bunch of their existing workflows.
3:24:46
So, um I think the reception has been super positive and you we need to get like a live vibe coding segment and show some of the cool stuff that you all can do.
3:24:55
Um there's there's literally so much.
3:24:57
It's it's incredible to see what people are building already.
3:25:00
>> I want to talk about naming uh version numbers and all of this. It's good for releases.
3:25:05
It's good for uh showing that there's some sort of binary change that you should pay attention to and actually see the jumping capabilities.
3:25:13
At the same time, eventually uh this stuff just diffuses into everyday workflows.
3:25:18
And uh Google has a bunch of products that don't really have version numbers.
3:25:23
BigQuery just gets better. uh Google Sheets.
3:25:25
I mean, there might be some version numbers under the hood that I'm not aware of, but like for most people, they just open it up and oh, there's a new feature today or maybe there's release notes.
3:25:33
Um, >> are we close to entering that era?
3:25:35
Are you are you going to miss the era of constant name change, >> banana emojis hitting the timeline?
3:25:43
>> There are there are benefits and there are costs.
3:25:45
Like, there are high expectations when there's a new big number.
3:25:48
Uh, but it also draws a lot of attention.
3:25:50
a reason to talk because something happened as opposed to just, you know, Big Query is growing and it's better and it's good and it just keeps getting better and it's less exciting.
3:25:59
So, uh, how are you thinking about that in terms of like messaging uh, all of Google's products here?
3:26:04
>> Yeah, I I think this is a super fine line to walk.
3:26:06
I I hear like I talked to lots of customers who have this feedback which is like it's there there's so much um exhaustion with the pace of releases and they're keeping up with you know something.
3:26:16
1 version update and it's just like all this stuff to keep in your head >> just like please stop making technological progress like we had we had enough please >> I don't think that's not what people this is the challenge is it's not I don't think that's actually what people want they just don't want to have to like stay on top of it.
3:26:31
Um, so I I do think there's a point at which like this stops being uh the thing that everyone is talking about.
3:26:37
And there is this like what's the like there's a bunch of good sayings that I'm sure you both know better than me, which is around like the arc of technology and how it like transitions from actually being technology to just being like something that is a part of a product.
3:26:50
Like a car we don't look at as this like science thing anymore.
3:26:54
It's just this like object that we use to get around.
3:26:55
Um, and I think AI will sort of eventually go on that arc where it's just like diffused into everything that we're doing and we don't think about it and it's um, it's part of every product experience and therefore you don't look into like all the nuance details of the small version number.
3:27:10
Um, but I do love the my takeaway is you need a good mascot.
3:27:15
Like I love the the nano banana thing really took off and I think if it wasn't something that was like easy to attach to that had an emoji that like all this other like there's all this like subtle weird marketing lessons that you uh I feel like I relearn every time something like this happens. >> That's great.
3:27:33
>> Uh talk about jailbreaking bug bounties.
3:27:36
Is there some benefit to the flywheel of people trying to jailbreak stuff?
3:27:39
It actually helps improve the models.
3:27:40
Uh there's some there's some post out there somebody figured out some jailbreak.
3:27:45
Uh the chat wants to know, but uh I've always thought that the the the nature of social media kind of encourages like if you can get the models to do something weird or funky or rude, then it goes viral very naturally.
3:27:57
And of course there's like the negative like, oh this is bad, but it's actually pretty helpful.
3:28:03
Um but how how are you thinking about that side of the world of getting these models out to the world?
3:28:08
Yeah, one of the things that we're always trying to like again walk the fine line of is all the like safety parameters.
3:28:14
So I think I I already saw a bunch of folks making comments around like what are we overblocking on, what are we under blocking on.
3:28:20
There's >> the the global legislation on a bunch of the stuff is extremely complicated.
3:28:25
So I have a bunch of empathy for the teams that have to like think about this more deeply than I do.
3:28:29
But like it is it's actually not easy.
3:28:31
There's a lot of open questions. Not easy to deploy.
3:28:34
super hard especially on I was thinking about like the trademark infringement side because I was like well well I want to be able to use my own trademarks.
3:28:41
I want to be able to go and generate my own my own defects of myself but I don't necessarily want everyone else to be able to do that necessarily without something.
3:28:50
So like it's >> we've run we've run into that trying to generate >> images of ourselves. >> Yeah.
3:28:55
And it's oh no you can't do this.
3:28:57
And it's like you've kind of arrived but now you got to prove to the model no I'm John Kugan. >> Yeah I am. >> I really am.
3:29:03
This is a very I think this is like a nontrivial problem that like will end up getting needed to be solved.
3:29:12
So I don't like I don't think there's any good experiences to solve this right now.
3:29:15
But you know to the extreme of this is like the future of you you orb scan your iris to like ID to the model that like you're really John and then that's how this sort of you unlock this capability.
3:29:26
That's the extreme version but >> yeah. Yeah.
3:29:28
Yeah, I mean, yeah, there's a bunch of ways to to to make sure that the the stuff works, but I mean, also just like like I feel like uh Google's been particularly good with re uh releasing like the thinking behind the decision- making in both like a blog post and a technical paper like Jeff, we covered Jeff Dean uh talking about the amount of energy and water used by various queries.
3:29:49
And I just I loved that because it was it was written in a way that was accessible to the person that just wanted to see a viral post on X the everything app which is kind of like you know it's a it's a it's a mud fight on there every day.
3:30:03
Uh and then and then you also had the blog post which was like you know a press person could show up there and then there's also the technical paper so if you're scientist you could go in there and it wasn't phrased as like you know this counterweight to like all the pieces that have come out saying it's really bad.
3:30:18
It was just like here are the facts in in in three different tiers of complexity so you can kind of get the answers at whatever level you want.
3:30:24
And I I thought that was well handled.
3:30:27
Anyway, Jordy, anything else? >> Absolutely.
3:30:28
No, congratulations on the launch. Always great to see you.
3:30:30
And uh have fun out there on the timeline. >> Have fun out there.
3:30:34
>> Let's go v code some stuff.
3:30:34
I can't believe you think the timeline is a is a mud fight.
3:30:37
I'm like, you got people in your replies must be horrible.
3:30:39
I feel like everyone's very kind in my version of kind, but you're always just one one quote tweet away from getting >> from war. >> From war.
3:30:48
The timeline's in turmoil a lot.
3:30:49
We monitor the situation every day and we see the timeline in turmoil nonstop.
3:30:53
Someone puts out a bad take, there's going to be a pile on, you know. >> There always.
3:30:58
>> But it's good content.
3:30:58
So, >> good for business.
3:31:00
>> It's good for business. >> Sure. Sure is.
3:31:02
>> Great to see you, Logan.
3:31:04
>> We'll talk to you soon.
3:31:05
>> And >> and on that note, >> you got to hop on.
3:31:07
>> Got to get on with London >> with Pyongyang.
3:31:09
One sec before >> Oh, we have one more thing from producer back.
3:31:12
>> We have uh a special guest here.
3:31:14
>> We have a special guest. Who is this? >> Uh, >> okay. Let's bring them in. >> Moments away. Let's bring them in. >> Okay. Who is this? >> Who's this? >> Is this a surprise? What's this? What is this? >> What's this to you?
3:31:26
>> This is a joke or something.
3:31:26
This is a prank that you pranking us.
3:31:29
>> I'm I'm I am genuinely not prepared for whatever's going to happen. >> Who's this? >> Oh, wow. >> Oh, wow. No way. >> No way. What is this? >> Happy 100k. >> Oh, thank you.
3:31:42
Oh, we have a we have a cake in the studio. >> Come here. >> No way. >> That's so cute. >> Bottle of dumb. >> Wow. That's amazing. >> Thank you. >> Thank you. Thank you so much.
3:31:54
Welcome to Welcome to the show. >> Thank you. >> Amazing.
3:32:00
>> Uh, >> look at this cake.
3:32:01
>> Can you say into the microphone, you're watching TBPN?
3:32:03
You're watching TV and >> amazing.
3:32:10
Well, uh, thank you folks. Fun show today.
3:32:12
Can you say uh, see you tomorrow, technology brothers. >> Johnny Brothers. >> Say, see you.
3:32:23
>> See you tomorrow, technology brothers. >> See you tomorrow. Check brothers. >> There we go. >> Yay.