https://www.listennotes.com/e/78d509fab9574e5aa449734b7b99b568

You'Re watching TVP and today is Thursday, May 29th, 2025. We are live from the temple. TVP and Ultra Dome.

That's right.

The Temple of Technology, the Fortress of.

Finance, the capital of capital.

But now it's also the TVP and Ultra Dome.

You heard it here first.

It's really it's it's a rough year to be a super dome. Yeah, because you thought you were at the top of the food chain, you know, just as far as domes go.

And then a new player comes in.

And then a new-- nowhere. Yeah, no one saw it coming. No one saw it coming. Kind of like, oh, like Google tries.

To react to ChatGPT, you know, kind.

Of blindsided by LLS. ChatGPT moment. Four super domes. Yeah, exactly, exactly. The Ultra Dome comes out and you're like, well, now maybe we have to.

Build an Ultra Dome. Maybe we gotta compete.

How are we gonna do that? So we'll go dome for dome with the best of 'em. We will, we will. Anyway, we got a bunch of news for you. We're gonna take you through about 30 minutes of recap of the news. Then we got a stacked lineup. Ashley Vance is coming on. Chase Lochmiller from Crusoe Energy is coming on. We're talking to folks about putting data centers in space. We're talking to Chase at Crusoe about putting data centers in Texas. And then the only thing bigger than Texas is space.

Space data centers. We're going over to-- I'm more of an Abilene guy.

Yeah.

I know you like space.

I do like space.

I do like space data centers. I'm really excited to talk to Peter Rahal.

Deepak is cooking. He's making a fortune.

He's back in the bar game.

That's remarkable.

And I think the growth, I would say, what was the number?

145? 140.

They're targeting 140 million in revenue in the first 12 months of operations.

That's insane. And to be clear, about 10% of that probably was from me when I was living on them exclusively for a couple of weeks, because they do cost a lot, but that's still very impressive.

But yeah, it's one thing to get to a run rate like that, but even that is extremely difficult to do, but to actually do 140 million revenue that quickly and seemingly has product market fit from coast to coast, right? They have big presence in the typical wellnessy cities, but then also in like middle of nowhere.

Yeah, it's crazy. It's crazy. These second acts from these founders, they should work, but sometimes they don't, but he clearly knocked it out of the park with this. So we're gonna be talking to him today. on the show. Anyway, speaking of space, space manufacturing, space data centers, we have an update on Elon Musk. He's leaving Washington. Here's how that affects the Trump agenda. Interesting story with Elon. Obviously he went in to D.C., built out the Doge team, had some wins, had some losses, some setbacks, some arguments, some debates. But he has now concluded his tenure as a special government employee departing the White House. It's back to work on space, baby. Yeah, he's going back in. There's a lot at stake at SpaceX. We're seeing the ninth launch. Interestingly, the latest Starship launch broke up again, another RUD, rapid unscheduled disassembly.

Great.

You hate to see it.

Great name for when your spaceship blows up.

But particularly bad for the people that were in the whole firmament camp. Yeah. because it broke up on reentry. And so it had actually reached the peak velocity. So anyone that says, oh, it can't go through the atmosphere at all and space doesn't exist, bad day, because the latest Starship actually does in fact reach its peak. It could in theory drop off payload and then it just breaks up on the way down, which means it's a very expensive, non-reusable SpaceX right now, which is of course breaks the whole economic model, doesn't actually work. So they got to figure out how to get it back without it breaking up. But good news that they're at least getting it there. But they have some really important milestones on the horizon that they need to hit. And so Elon's probably going back in there. Also we saw the X outage and kind of, you know, things falling apart there. I'm sure he's like, I need to be sleeping in that conference room too. I need to be on the factory.

Floor, SpaceX, and go directly to the conference room. I heard a rumor that there were tents set up at the X HQ.

Okay.

For people to sleep in, in the office.

Because it'd be over the weekend when the site was down.

Recently. Because it was, you know, it's embarrassing for your servers to go down in such a big way. And I'm sure that the culture there just doesn't tolerate downtime.

Although it held up really nicely for us yesterday with Crypto Day. Yes. Massive day on the internet.

And the interesting thing is, the Tesla stock price has been pricing in Elon leaving Washington for a while. It's up 22% since last month.

There was that whole Wall Street Journal report that said that Elon might be stepping down as Tesla CEO. And he said, absolutely not, no chance. But yeah, I mean, he's getting back in the game. Can you pull up the Polly Market on Tesla new CEO? I want to see that. take you through some of the news. Horrendously down out of horrendously. Probably now that he's not working for the government anymore.

Yeah, he's had a 1% chance as of today. So when is Elon Musk leaving the government exactly?

As a special government employee, Musk's tenure was limited to 130 days, which runs out at the end of May. A White House official said that Musk's off-boarding started Wednesday, adding that he hadn't been He hadn't been a regular presence in the West Wing in recent weeks. As my scheduled time as special government employee comes to an end, I would like to thank President Donald Trump for the opportunity to reduce wasteful spending, Musk wrote on his social media platform X late Wednesday.

They also cut this off because he specifically said the Doge mission will only strengthen over time as it becomes a way of life throughout the government. And I just had to call out that the journal had to, chose to not include the second part of that.

Oh, interesting.

Which I think is important. He's not just saying, See ya, he's saying, Hey, I actually believe in this sort of...

I'm trying to reflect on the organization. How much of this was expected and what actually is happening? Because I feel like the prediction on the right was that Elon and Trump are going to be a an unstoppable force forever, and they're gonna reign forever, and they're gonna clean up the government, do everything. And then the other side, on the left, it was like they are gonna have the most massive blow up, and they're gonna be at each other's throats, and they're gonna hate each other, right? And it's like, what actually happened? Seems like they kind of did some work together. They worked on a project together. They did a group project.

School project.

School project. And it seems like maybe they're still like, Kind of friends and kind of chilling, but also Elon's like, I got other stuff to do.

I think that Tesla Model Y is still parked outside of, or it's a Cybertruck or Model S. You know, Trump.

Got the red model. Oh, he did.

Yeah, yeah, yeah.

Yeah, it doesn't seem like a blow up entirely, at least not from Trump and Elon. They seem to get along. Although Elon did say, like, he's kind of, it seems like Elon's more like disillusioned with government overall because he said he's not going to be donating again. And that it seemed like there were so many special interests that once he got into the swamp, he was like, it's just too swampy.

It was like me with my HOA. Bought my house, went to the first HOA meeting, being like, oh, this is.

A brand new HOA.

I'm going to revolutionize HOA. There's so many obvious things that we could do to improve the operations in the neighborhood. Realize very quickly that there were some major, you know...

I think you weren't chaotic enough. You should have launched an HOA coin immediately. Really shook things up.

Nobody's building at the intersection of HOA and cryptocurrency. of HOAs and crypto.

No, no, it is. Oh, it is. White space. Longley, get on. White space. Anyway, the Democrats are taking a little bit of a victory lap. Democrats took credit for Musk's decision to leave Washington, arguing that the extensive litigation and public pressure surrounding Doge forced his hand. He lost. Democracy won, wrote Norm Eisen, a co-counsel.

For the House Judiciary Committee during Trump's first impeachment. Which is interesting because As a special government employee, his tenure was limited to 130 days and he's leaving at the end of that.

Yeah, that's true.

So taking a victory lap. That's like saying you hired a contractor.

But also, I don't know, I feel like that 130-day thing, we're kind of hearing about that for the first time now. That wasn't the way it was messaged beforehand. It was definitely messaged like, Elon's gonna be part of this team for four years, like expect Doge to go on a generational run here and do a lot. It was not like, oh, Elon's, hey, just to set the record straight up front, he's going to be in for 130 days. So like, let's see what we can do then. Like, I, this is the first I've heard of the 130 day thing. So it feels like I heard a.

Little bit of that from another guest that we've got on the show who is a special government employee and he had messaged it to me earlier.

Oh, earlier.

Like, oh, it's just a sprint.

Sprint.

It's a sprint. Okay.

Interesting.

That was cool. That was kind of core to the Doge. strategy from the very beginning is special government employees that are on these sort of shortened stints.

Yeah, yeah, yeah, that makes sense. So what did he actually do while he was in Washington? Asks the Wall Street Journal. Musk came into the government with bold plans to slash spending by as much as $2 trillion in rapid-fire succession. Doge and Musk dismantled agencies such as the U.S. Agency for International Development and the Consumer Financial Protection Bureau, leaving thousands of federal employees out of work. Musk and his Doge team emerged after Trump's inauguration with a series of shock-and-awe moves rattled the federal workforce. The subject, he sent an email to a lot of government employees, Fork in the Road, the same line Musk used in a 2022 email to Twitter employees shortly after he took over the company and renamed it X. Tens of thousands of federal workers took the offer to.

I'm going to send an email to the team tomorrow morning with the title Fork in the Road. And it's, do you guys want bacon or steak breakfast?

You're going to get somewhere with that.

It's great.

Musk's promise to slash the federal by trillions of dollars ran into the wall of non-discretionary spending programs such as Social Security and Medicaid. Doge said it had saved the government 175 billion from a combination of asset sales, contracts, lease and grant cancellations, workforce reductions and other moves made since January 20th. So it seems like maybe a decent outcome. I don't know. It's like the, you know, better to not waste that money. But yes, it doesn't write it doesn't correct the budget. So it's not dramatic.

Well, the dramatic bill increases it dramatically.

So it's probably better to have done some of that stuff than not, but the real question is Social Security and Medicaid. And so the answer to that, longevity drugs, move the retirement age to 95, solves all of this. Let's get Brian Johnson.

Brian has his way, it'll be 150.

Yeah, yeah. That really works. It would completely change entitlements if people could work longer. But very unpopular to ask people to do that. Anyway, massive news out of Anduril and Meta. They're teaming up. Meta fired Palmer Lucky. Now they're teaming up on a defense contract. The Facebook and Instagram parent is partnering with Anduril Industries to develop combat VR headsets for the army. And there's a beautiful picture of Palmer Lucky and Mark Zuckerberg there. Let's hear it for getting the band back together. We love it. Ashley Vance has an exclusive interview with Palmer Luckey, he's going to be joining the show in just a few minutes, and we'll break it all down. Very interesting because the narrative I was hearing internally in the defense tech world, some of the Anduril haters were kind of like, oh, they bought this IVAS contract from Microsoft, but the contract's going to get recompeted, and at a certain point, why wouldn't Meta compete against Anduril for this? They have a great team. They have a lot of the hardware. They could actually deliver this. And the contract is up there, like, go get it. Problem solved. Now they're teaming up. And so if you think about it.

It'S like- Zuck started wakeboarding, doing jiu-jitsu, and now he's a defense contractor.

Let's go. The cycle is complete. Back to the couch with the red Solo cup, drinking a beer. The first Zuck interview. It's great. It's fantastic. But yeah, exciting, interesting development. So, Obviously, there was a messy split with Palmer Lucky years ago, but everything we've heard about that was that Zuck was not super involved in that process, which is kind of crazy to think about. But Meta was such a big- You.

Have a massive acquisition.

It's such a big company that, yeah, maybe you bring someone in, you kind of let them work, and then at a certain point, this individual is layered and you don't want to just immediately go over the top of, the three people that are in between you and this new employee that you've hired, because I don't think Palmer was the CEO of Oculus when he went in. And so it's possible that he technically didn't, not like he technically reported to Zuck. And so anyway, they've clearly rebuilt the relationship. Very exciting. And there's been some progress, even just in public discussions on X between Boaz and Palmer Luckey going back and forth about what happened, what mistakes were made, some apologies. And it was just very cool that that the water was able to flow under the bridge. I really appreciated that. Yeah, I just like to see them doing business together.

Totally, totally.

So Lucky's Defense Company, Anderal Industries and Meta said Thursday, they will build a line of new rugged helmets, glasses and other wearables that provide a virtual reality or augmented reality experience. The system called Eagle Eye will carry sensors that enhance soldiers hearing and vision detecting drones flying miles away or citing hidden targets, for instance. It will also let soldiers operate and interact with AI-powered weapon systems. Anduril's autonomy software and Meta's AI models will underpin the devices. Very cool. Oh, that's interesting. Yeah, makes sense. You'd want to have an LLM on board to actually interface with everything, but then you need to interface with all the different assets on the battlefield.

And so Lattice comes in there. That's Anduril's autonomy software. Soldier on the battlefield.

Llama, what do you got for me?

Llama.

Yeah, it really is turning into college GPT.

But it's like, hey, Llama, what should I be paying attention to right now?

I could get a really dark Llama on bleeding out, send the medevac. How do I tourniquet myself? Rough. But I mean, you know, like you have to put these pieces together, but Llama is a silly, silly name. But I love it.

I wouldn't be surprised if they say.

Eagle or... Yeah, yeah, yeah, yeah. They might need to hide that brand underneath the hood. Yeah. The collaboration brings together a social media giant that has long been the target of Washington scrutiny and a weapons maker that is a rising star inside of the Pentagon. The partnership offers another example of Silicon Valley's ideological evolution and big tech's expanding embrace of defense work.

Lucky says, I should look at this as I have succeeded. I have successfully persuaded not just Meta but many others that working with the military is important.

So important. Yep, yep.

Cultural victory.

Yeah, yeah. I mean, in the previous era, the one company that was kind of pro working with the government was Microsoft. And of course, they had the HoloLens project, but they were also selling Outlook and Excel and all these different products. And I think that just came from the like the Ballmer era, the Gates era, where they saw their software as just enterprise software, so they needed to get in the hands of everyone. And so it became standard on pretty much every military base, so there's Windows and so that legacy, it was kind of like even pre-global war on terror. And so support was at an all-time high. Those partnerships grew and grew and grew. And of course, the Hollow Lens project was very cool. And IVAS was just a cool project to work on. But it didn't seem like they had the maybe the defense contractor DNA to really take something into the hands of the war fighter, even if they were able to put excel in the hands of the war fighter. Yeah.

Sorry, what Anderle has now is credibility with Washington and the existing relationships to say we are going to be a distribution channel for the best technology in the world and work with the best partners to deliver the best end products. And it's a fantastic partnership.

We got to go get the demo soon. Meta in recent months has recruited former Pentagon staff to join its ranks in an effort to navigate the labyrinth of the defense procurement acquisition process. In November, it opened up its AI models for military applications, a new line of business for the company whose profits have been powered by online advertising. In a statement, Zuck said the Eagle Eye technology will help U.S. soldiers protect interests at home and abroad. Meta and Anduril will have jointly have jointly bid on an army contract for VR hardware devices worth up to about $100 million. If awarded, it would be Meta's most significant tie-up with the Defense Department. The contract is intended to vet headset prototypes that are part of a larger $22 billion Army wearables product. project of which Anderl became the lead vendor in February after Microsoft failed to deliver a functional VR headset. Anderl said the collaboration on the headsets, which the companies have already mostly funded themselves, is going forward irrespective of winning the Army contract. Anderl is betting other parts of the military will also be buyers. Yeah, that makes a lot of sense. Why wouldn't you not want this if you're in the Air Force or the Navy or the Marines? The meta partnership delivers a victory lap to Lucky, whose entrepreneurial roots and much of his fortune can be traced to VR and then they give a little bit of background on Palmer's journey.

It's so cool.

Finally got all my toys back.

He started Oculus when he was 15 years old. Insane, insane story.

The new partnership gives Lucky access to all of his old VR designs, plus newer tech his team has built after he was fired. I finally got all my toys back, Lucky said. I love that.

That's amazing. It's still so wild that in 2017, the US has two real political parties, and in 2017, there was one that if you donated to, you would get fired.

It made me very frustrated at the time. It was very, very rough. It was just like, that's literally anti-democratic. The whole point of democracy is you can vote for whoever you want. It's like the one thing in democracy that is like, It's like, it's the definition of democracy. You have to be able to vote for whoever you want. It's like everything you've learned about how America is supposed to work is now just at stake. It's bad, bad times.

But, yeah, there's two parties, but you can only donate to one of them. And if you donate to the other, you get fired. But hey, what matters ultimately, all the different groups have come around and are moving forward. So, yeah, great to see.

In other news, we should go through, this is a story that a lot of people have been asking me to kind of dig into. I was talking to Jordan Schneider over at China Talk about this. He said it'd be great to get people's view in tech around this more political story, which we don't really cover, but Trump's, I mean, currently waging a war on American universities, which does have some tech implications in the sense that the Thiel Fellowship has been in you know, renegotiating the relationship between entrepreneurship and higher ed for a long time. And then also a lot of tech companies hire from elite universities. And so Trump has been threatening to withhold billions of dollars in federal research funds to punish campuses. And there's a story in the journal here about the punch that launched Trump's war on American universities. So I still don't know. I still don't know exactly the angle of this. I think it's something we should dig into. I think the big question is America has national interests, has different security interests, also has competitive dynamics around brain drain. We want the top entrepreneurs, we want the top technologists, the top 01s. The administration has a view, big tech companies have a view. It would be interesting to hear from tech leaders on where they think these policies should go around the top research universities. When you talk to biotech folks, they're like, We need research to be done in universities funded by the government in order for our business to make sense. You don't hear that much from tech companies. They're like, yeah, the next big AI breakthrough probably just gonna come from Google. They won't be able to productize it fast enough, and we'll just roll it out into some B2B SaaS. And so, But at the same time, there are a ton of AI labs, Silicon Valley tech startups that want to hire tons and tons of talented individuals from all over the world. And there's big questions about how the Trump administration is affecting that. There's that famous quote from Trump on the all in podcast saying, we should staple a green card to every university diploma. And this feels like the opposite of that. And so there's a question about like, was that a campaign promise?

Yeah, big news, Nick. Yesterday, Secretary of State Marco Rubio said that they will begin revoking the visas of some Chinese students, including those studying in critical fields.

Sure.

China is the second largest country of origin for international students in the U.S. behind India. In the 2023 to 2024 school year, more than 270,000 international students were from China, making up roughly a quarter of all foreign students in the United States. That's actually down significantly. I saw Solana posting something yesterday as well, just showing that that 270 number is significantly lower than just a few years ago.

Yeah, so there is a question about trade balance a little bit where it's like, if two, what is it, 270,000? 270,000? If 270,000 Chinese citizens are coming to American universities, should 270,000 Americans be at Chinese universities? Is there an imbalance there? That's an interesting question to dig into just in terms of reciprocity of these relationships. if TikTok can operate here, well, can Instagram operate there? That would be an interesting trade. If there's an imbalance, we probably need to have a discussion one way or another. There's also the question.

I would have to give a very rough estimate of how many Americans were at Fudan, which was the university that I studied abroad in China. And it had to have been less than 50 total. at least that I was aware of. It was pretty easy to, you know.

At the same time, I wonder how much of a shot across the bow, how painful is this to the Chinese government? Because if you remember the whole story of... What is it? Sorry, I'm sorry. No, no, no, no, no. Russia with the Magnitsky Act, it banned adoption from Russia to America. And that was extremely painful for some reason. I don't exactly know why that was such a hot button issue, but that was a key point point of leverage against Russia at some point. And so I wonder, I want to dig into the reaction to this move by the Trump administration, by the Chinese Communist Party. Are they upset about this? Does this go against their plan in a very meaningful way? Is this something that will be another poker chip on the trade negotiations around tariffs or around the flow of fentanyl or something like that? Could this just be an opening gambit that then gets negotiated down? And Trump's merely just putting this piece on the chessboard to then negotiate against? Or is this something that maybe China doesn't really care about? And they're just like, yeah, we actually want our students here. And so this is great for us. Please, please send all the students, all the smart people back. We don't want to be brain drained. I don't know which way it's going to cut. And so I want to dig into it more.

Their foreign ministry spokesperson Mao Ning said, we urge the US to effectively safeguard the legitimate rights and interests of all international students, including the Chinese students overseas. So not really a real response, but we'll see how it plays out. Yeah.

Yeah. I wonder if there'll be, like, retaliation or some sort of, like, canceling of American students that are in China, how this will actually play out. But. But we should start asking more of the guests about how they're reacting to this and. Especially if they have, you know, deep insight here. I don't just want to hear random people yap about it.

Guess how many American students studied in China in 2024?

5,000?

Guess again.

10,000?

Guess again.

1,000?

800?

800?

So I was pretty close with being like, even in this was like 2016, I was like, maybe there's 50 other students.

That's really low. 800's nothing. Yeah. I mean, we have like millions of college students in America, right? You would think that, you know, a couple percent of them would be over there on at least like one semester or something like that.

So there was 11,000 prior to the pandemic.

Okay, wow. It really fell off.

90%.

That's crazy. Wow. Anyway, in other Asia news, Kim Jong Un launched a new North Korean warship using a risky side launch technique, and it completely crashed, I guess. That's brutal. After that soundboard, you can never go to Pyongyang.

Pyongyang is not gonna be happy to see that.

We're not gonna distribute the show in Pyongyang anytime soon, unfortunately. The unconventional technique for launching a big military vessel points to North Korea's haste in modernizing its outdated navy and lack of resources. Kim Jong-un witnessed a warship topple over during its launch, deploying a risky side-launch method. Naval experts cite inexperience, a rushed timetable, and top-heavy warships as factors. , in the failed launch, North Korea chose a side launch to save costs while the US and South Korea use safer floating dock launches. Oof, very, very rough. Imagine you're just like, so Kim Jong Un, he traveled to North Korea's city of iron. Okay, you gotta hand it to him.

That's an amazing name.

Let's hear it for the city of iron. City of iron. It's where they build the ships. Isn't that amazing? That's great. So they have a major industrial credit. Yeah, yeah, yeah. You gotta call a spade a spade. We're just calling balls and strikes here on this one. We're pro North Korea now. The city of Iron is too good. It's home to a major industrial shipyard where a hulking warship awaited him. A VIP podium had been erected alongside the port for the vessels launched. Officials awaited in anticipation, but the big moment of celebration turned into calamity. The 5,000 ton destroyer lost its balance as it lurched into the water, toppling over and embarrassing Kim, who seeks to modernize his Soviet-era naval fleet. And it's so funny because they didn't send us video of Obviously, they didn't broadcast this because they would only broadcast it if it's successful. So we just have satellite photos of just getting destroyed slowly, slowly, very, very rough. Brutal.

What do you do if you're the chief engineer that tips the warship over?

Oh, I actually know what you do. You go to jail there.

I bet.

So four North Korean officials have been detained over the mishap, which called it an unpardonable crime. Can you imagine the stakes of like, oh yeah, you think it's hard being a hard tech founder in America? Oh yeah, try doing that in North Korea where you go to jail if you fail. We've had nine Starships just blow up and we're like, okay, you're sleeping in the factory now, not you're going to jail. Like you're working harder. Our answer is you work harder, not you go to jail. What has become clear in the aftermath is how an unconventional choice of launch method, Kim's rushed timetable, and a top-heavy warship overladen with weapon systems was a recipe for disaster. They just keep being like, yeah, just throw one more missile battery on that. Yeah, yeah, yeah, yeah. Put a Gatling gun on it, too. Yeah, yeah, another cannon, no problem. Just keep doing it, and then it just rolls over. It was a recipe for disaster, according to satellite imagery analysis. I haven't seen a failure like this one. I've never seen a failure. I said a retired Marine Colonel that they. The Wall Street Journal called up, and he's just like, this is insanely bad.

Yeah.

Who are you on the phone with, Jordy?

No, just calling up Mark Khan.

Yeah. I haven't seen one this bad. It was a 470 foot long warship, Kim's second Destroyer. They've been built in the northeastern city and did not go well. Anyway, our guests are gonna start.

There's a bunch more stories here. We got Peter Rahal in the waiting room.

Cool.

Bring him in.

Yeah.

Let's do it.

Peter, how you doing? Welcome to the stream. Nice sweatshirt. Looking good.

Thank you. It's a sample too.

Congratulations on your Second announcement of the week. This is the first real one, I guess. Sorry, sorry that you got leaked, but very excited for you. Excited to have you on the show to break it all down.

Yeah, what is the most recent news? I only know the incredible revenue number, but what else is driving the news cycle right now for you guys?

Well, so we acquired a supplier, an ingredient supplier called Effig. and then, yeah, our valuations, 7, 725.

Wow.

Forecast this year is 140. So I think those, those numbers and, you know, I think, you know, it's like, and we've accomplished more in nine months than. Yeah, we did in Rx over four years.

Wow.

So I think we're, I think we're.

One of the, what other, what other.

Brands have achieved that level of Revenue within a year of launch?

There's two Feastables and Prime.

Prime, yeah. 'Cause just massive distribution cannons and really like leveraging essentially like, you know, $100 million worth of free marketing on day one, right? Yeah. So what's the secret for you?

It feels product-led. Is that the right assessment? Obviously you have a bunch of lessons you know, War stories you can pull on from Rx bar, but, like, it feels like the product just sells itself in some way.

Yeah, I would say it's definitely product led. We actually, you know, in CPG, it's pretty hard to differentiate measurably.

Right.

It's, it's. And, you know, we are, 75 of our calories are coming from protein. The market is at, like, 50. So, so it's meaningful and. It's an example, like the market was on the surface, we don't apply rigor, it looks pretty competitive.

Yep.

But if you just like spend a little time, talk to some customers, you realize like NPS is pretty low, like no one's really happy. And a lot of people don't just aren't even in the category because of taste and texture and nutrition. So the big opportunity for us in the bar business is like to really expand. the category and make delicious, nutritious products that, that people are like, oh, oh, protein bars don't taste like shit. Like the expectations are there's just, they're.

Just gonna be bad. Yeah.

Yeah.

When you say people aren't in the category, are you talking about the difference between protein shakes, which can typically be like extremely high protein from calorie ratio?

More, more specifically, people are like, people don't consume protein bars. Like you'll, you'll, you'll, you'll Here people say, oh, I'm just not a protein bar person.

Sure, sure, sure, sure. Yeah, that makes sense.

Those are people, if you ask them, why not? It's fundamentally taste.

Yeah. I want to push back on this idea that it's product-led. I agree that there's product differentiation, but this feels like it's only possible from you because if you call up a major distributor or supplier or retail chain, they say, Yes, I know you. You have a win under your belt. I'm willing to go big and we don't need to do some long extended test is this isn't to knock you. I mean, this is why you worked really hard and you're reaping the benefit of that. But is that critical or do you think if you have nobody and you were cold calling?

My position is more so like Peter would have the relationships to get the bars on the shelf. But he's not making, you know, holding every customer that walks into the store at gunpoint to buy my product.

That's true. I mean, it is very different than Mr. Beast in Prime where, you know, you have like major influencers driving this. It is more product-led in that sense.

Yeah, and I would say my credibility or track record is like a lubricant to facilitate things, but the repeat and it's all product driven.

Yeah, that makes sense.

Talk about the decision to acquire one of your major suppliers. Was that something that you anticipated doing a long time ago or what was the point that that made sense?

Yeah.

So when we started.

In our business.

You don't want any single source supplier. It's just too much risk. So it can become a nasty dependency. So we identified the technology, the ingredient, and it was like, this is like magic, like technology should feel. Got close with them, became 90% of their volume. So we were basically that, you know, 90% of the revenue.

And.

It just made sense to vertically integrate and de-risk it. And so we can just control the supply. Yeah, and, you know, I can't imagine a company without us being together and enables us. It just like totally widens the aperture of like where we can go and truly have a platform for across different products, different brands, different consumer needs.

How did you dig into the defensibility around that intellectual property? Because I feel like the gold standard for defensible IP in anything FDA regulated is probably pharmaceuticals, like drugs. But as we've seen with the Ozempic/Wegovy transition, even GLP-1s, they were able to eat at the edges. Now Eli Lilly is taking share from Novo. It feels like if it can't work in GLP once, how can this possibly hold in a protein supply chain? You're gonna get someone who spins something up that's one molecule different or something like that. Is that a risk or did you dig into that at that level of depth?

Yeah, I mean, there's really one process to make the molecule.

Sure.

And it's like, Sure, someone could go try it, but we'll litigate and then calculate that.

And I guess the bull case is that, yeah, you could go and fight on the IP stuff, but at the end of the road, you don't get a pharmaceutical product, you get a CPG brand. Yeah, that's right. And so it's like, you're gonna have to fight real, real hard and at the end, then you also have to build a brand, also do the distribution, and also, whereas because Eli Lilly, if they spent a bunch of money to figure out how to alter the GLP-1 to get a drug that works, well then it's just a matter of doctors prescribing it. And it gets paid.

And in CPG, you kind of have two years runway before someone copies you. Now we have structurally nine years. And I think by that time, it's.

Kind of too late. I mean, you already see that with the 140 revenue. as that gets bigger, it's just going to be ubiquitous and you own all the shelf space. So even if there's knockoff copycat, it's like, yeah, you're already big.

You're less than a year in post-launch. What does a good outcome look like? You've already had a multi hundred million dollar exit. I imagine you're aiming a lot higher here, but what is that in your mind?

Yeah, I try not to think about the outcome too much. But I do.

That's the most honest answer ever.

That's the best. Yeah.

Any entrepreneur is like, oh yeah, I've never thought about the outcome. It's just purely mission, you know?

Yeah, it's amazing. Yeah.

Like I would be pissed if we don't get to a billion in revenue.

Yeah.

Yeah.

You know, that would be disappointing.

What was our x-bar roughly? Like what's your personal high water mark?

To 240.

Okay.

Yeah.

Okay. So maybe.

Maybe a little bit more. Yeah.

Yeah. Yeah. 4X that. Yeah.

So I. But I I do think. I I do think we can build a really Diversified portfolio of Brands.

Yeah.

That really address a broad population and create a ton of consumer Surplus, so. you know, I think, like, yeah, we just have so much work to do.

And.

Yeah, I I do fantasize about being a public company.

Let's go.

I love it.

We'll have you back after your public company, and you're just gonna be like, it's such a headache.

It's so annoying.

I can't say anything. I'm in a quiet period. I can't come on TV. and it's the worst.

Yeah, I might be the irreverent.

Yeah.

These calls.

But, but.

Yeah, I just think, like, there hasn't been a truly from scratch brand platform in the space. It's all been done through M&A.

Yeah.

Chobani is doing it actually now.

Yeah, sure.

And I think that, and you're a.

Believer in, in these brands living under the existing, you know, C Corp. and, or, or like, it doesn't sound like you want to do like a studio.

No, I only studio analogy. We, we're not gonna do M&A. We're gonna, we're gonna build them. Like, yeah, I, I, me and my team, we've demonstrated we can like go from scratch.

Like.

Yeah, so, so we would just build them. It would be a decentralized model, so like different orgs, you know?

Yeah.

So David's the master, David's Mars. and then David Protein is the operating business. Epig will be its own subsidiary and it will create other brands. And then they just have to be decentralized, organized, like orgs, because you, you know, like David and his life cycle is very different than a newborn baby. And so, like, you need to design the org for agility and speed. And so, so that's what we're designing for.

And how much do you view yourself as technology company, I heard you bring that up earlier, as in you're wanting to pursue opportunities where you can have a unique sort of durable edge through some type of effectively chemistry. I don't know if that's the right word.

Yeah, chemistry. You know, we're in the chemistry business now.

I want to keep learning and investing. You know, I don't know what we don't know, but like once you get in the pool, you'll figure things out.

So.

You know, like, Technology is not really welcome in food. So we, we, we restrain from the t word. But, yeah, we want to keep making really valuable products. Like, that's just our focus. And, and obviously, Technology is really the best way to get there.

Have you mapped out the technology?

Yeah.

You have investors that are traditionally sure. Technology investors. I mean, I, I don't think I've ever seen Green Oaks do a CPG round.

Yeah, the last deal they did was like Wind Surf, right? Or like the last big outcome for them. Yeah. Wildly different company. Have you taken a crack at kind of reverse engineering what it takes to really go after like a Nestle or a Unilever, like one of the major, major conglomerates that has been built through M&A. But if you think really, really far into like what it takes to create a $100 billion outcome in consumer packaged goods.

Yeah.

No one's even come close. Like we all cite, like Red Bull is a great outcome, but these are all like single things and very niche categories that are big categories. like energy drinks, the companies get big, Red Bull's big, Monster's big, but no one's really been able to figure out the right corporate structure to just compound and compound and compound and create this like $100 million behemoth.

Yeah, so the key way to address the really large TAM in consumer food is through different brands that have different DNA that address different sort of problems or consumer state. so like David's, I use the analogy of like, brands are just human beings. They have fathers, they have DNA, they have behaviors, beliefs, they have friends. You gotta let that brand or that asset be itself. Like you can't jam it into places it doesn't belong. So like the David brand with our future portfolio and optimizing for calories coming from protein. So when you look at David, you know, it's like the most protein, least amount of calories.

Yeah.

That, that Tam is probably 1.5 billion in Revenue in the U.S. so. So you really need multiple. You need like a house of Brands to go after very different parts of the population. Yeah, that's one. And then International.

Yeah.

What's the, they're mega scale and they're Global. So that's the key thing.

What's the pushback been like from kind of like the Trad Community that wants to do. Everything all natural, everything like, you know, oh, just, you know, farm to table, the Michael Pollan crew, the RFK crew, like there's all these different segments of kind of like anti-modernity and food. What's the reaction been like? Yeah, so.

You know, Peter Thiel talks about like anything with science at the end is not science.

Sure.

Nutrition science is really to date not been science.

Yeah.

And so it's really been, it's a really emotional conversation and not a intellectual conversation. So that's the first pillase and it is complicated and our society is really confused around it. And so under the confusion and a way to simplify something complex, people find like just simple correlations. Like if my ancestors didn't eat it, I shouldn't. And that's like a pretty good framework. or like, it's not bad advice, but it's clearly not sophisticated and it's way more complicated than that.

Yeah.

Well, and it's like the interesting thing was like the ancestral movement. My friend told me this and I thought it was like really good. It's like the ancestral food movements, like it's like post traumatic stress response. Like it's like a post trauma response where you're like, like you just stop and you like don't progress and you actually go backwards because you're scared to make it worse. and perhaps that's because food fucked up and food, you know, got run by CFOs who just cut the bottom line and just cut, cut, cut. But I do believe like there's a way to advance food in a way that, and it isn't that scary and yeah, so I think I, I, I goals to have like a more intellectual conversation on food, like, you know, not something like, oh, I can't pronounce it, therefore it's automatically bad.

Yeah, yeah, makes sense. Food is what like nutrition is about.

Like it's pretty simple. It's about the 80%, like don't overeat calories, don't be fat. Turns out that's fucking terrible. Don't spike your blood sugar and get enough protein.

Yeah. And hit the gym.

I wish we had more, I wish we had more time. There's a bunch more questions I have. Yeah, congratulations on the milestone. Just getting started. Cool.

And appreciate you coming on. Yeah, we'll talk to you later. Congrats. Bye. Next up, we have Ashley Vance.

You know that Green Oaks is underwriting that to small chance of $100 billion.

For sure.

That's why they're doing the deal.

Neil Meta. Undefeated. Next up, we have Ashley Vance coming in the studio from core memory. Bring him in. How you doing, Ashley? Oh, look, he's in the new studio. New studio reveal. Let's go. Exclusive.

Let's go.

Breaking news, core memory. Interview Palmer Luckey. You're hearing about it here first, folks.

You're cooking.

You're cooking.

It was good.

Good morning. It's yeah, yeah. Palmer came. I think he, well, he came in yesterday. I think straight from, there's this photo we posted of him and Zach together. He's wearing the same clothes. I should have actually asked him, but yeah, I think he came straight from there. their peacemaking accord.

Yeah, what was your read on it? How much were you focused on the technical side of the deal between Andor and Meta to work on VR for the military versus just the crazy full cycle narrative of the emotional journey?

We kind of did both. I mean, he sat here for a couple of hours and from my memory, I think the first 45 minutes was going into the deal, the backstory, all that. The press release on this is super thin on the technology and the Wall Street Journal story didn't have that much either. And Palmer, he went into some detail on our podcast about the tech. And then, yeah, he got into the backstory. I mean, this is crazy. I've been following Palmer pretty close for the last couple of years. I never would have imagined that this would have been possible given the intense, the depth of this nine-year war that the he and Meta have had. So, yeah, I did not fully see this coming.

But is it accurate to describe it as a war between Zoc and Palmer or a war between Palmer and Meta?

I think it was more Palmer and Meta. If you go back, Blake Harris wrote this book, the History of the Future, and he spends like 40, I don't know, 40 or 50 pages laying out the saga. Palmer put up this paid-for-this-billboard about Hillary Clinton. became a known Republican in public. It was fired from Facebook. And in that book, you see a lot of operatives within Facebook kind of pushing Palmer out. And we talk about this on the podcast. I mean, if Palmer's being truthful in what he said, he didn't lay the blame directly at Zuck's feet. He kind of felt like Zuck was doing what he had to do to protect his company and what the employees wanted. So I think it was more meta.

Directed. Yeah. It is crazy to think about the post Oculus acquisition time period at Meta and just not having Palmer report directly to Zuck. That seems like that's the real Cardinal Sin here, more than the crazy stuff that happened politically. It's just like, how do you bring in someone who's clearly the face of VR, generational founder, all these amazing things, and It would just have been so much easier to manage that relationship if there was no one else in between, like no management layers in between.

Yeah, and almost definitely I think Palmer is probably still at Meta working on VR. I don't think 100% is the answer.

I mean, the end roll, you know? Yeah, didn't Jan Coom from WhatsApp stick around for a long time? And obviously the Instagram guys had kind of a rough go and they're upset about it now. But I think they reported directly and built that for a long time. It was just odd that VR was so important in Meta that, you know, Reality Labs, huge investment, and yet Palmer Lucky was not, you know, he should have been on the board. Like, he should have been added really, really into the inner circle.

It's been a while since he's been.

In his early 20s. Who cares? Right? Zuck was 19 when he started the company or whatever. Sure. Break the rules.

And it's been a while since I read Blake's book, but yeah, I mean, he kind of lays out all these layers of management that were put between Palmer and Mark, so, but here they are taking photos as friends again.

Have you gotten the demo yet? Any of the Andaril hardware yet?

I haven't gotten on this headset. No, I mean, this has been in, I've been down at Andaril doing some reporting, and Palmer's always like, because this is like an extension of this IVAS.

Field.

That Andaril took over from Microsoft. So I've been down there, Palmer's like, oh, my secret lab is over to the side, and that's where these guys are working. I mean, people should know, one of the coolest parts about this, I think, is that, I mean, yes, they're making this war fighter helmet of the future, like the sci-fi thing we see in every military movie that doesn't exist. But beyond the, like, VR, AR data feed coming in, I mean, in Palmer talks about this in the podcast. He's trying to, like, reinvent the helmet itself, right? To make it lighter weight, to make it the ballistics upgrade, all of that stuff. I mean, so he wants to build it's not just like the, the sort of tech end of this. He just wants to make a better helmet for soldiers, too. And, and I know he's been spending a lot of time on all the materials and, and things like that.

Yeah. Have you been tracking any of the other developments at meta? There were some, there were some setbacks with the llama team. It seemed like they kind of went a little bit too far into the pre-training Paradigm and maybe not enough in RL. And so llama four is kind of falling behind in some of the some of the benchmarks at the same time. There's some really amazing VR demos that are coming down the pipe, like the Orion augmented reality glasses. And then even just like the next Quest headset, I feel like is going to be incredible because all that work that Apple did to get those incredible screens into the Vision Pro, well, like Zuck's probably going to be able to buy that because it's two years later now. It seemed like that was something that was unique to Apple but only for a small period of time. And Apple kind of whiffed on actually getting that into the hands of millions. If it's in the next quest, it could be really cool. So any takes on what Meta has been doing in VR or AI lately?

I do not follow them as closely as I do some other companies. The thing that's always stuck out to me was when they bought Control Labs, which was doing this weird take on a brain-computer interface by reading the motor neurons in your wrist. And we've seen and Meta do some demos around this kind of like new interface using your body and your brain to navigate computers. I actually think that's like the under, you know, it's probably one of the hardest things they have to pull off, but it's kind of under reported in some ways because, I mean, if you look at what trying to read the tea leaves on whatever OpenAI and Johnny Ive are doing, you know, we're clearly We're lurching, some companies are lurching toward a new kind of computer. We've been on the same basic computer for decades.

Well, to be clear, the OpenAI thing, they were pretty clear that they said it's a third device besides your phone or your computer that will work with those devices.

With those, yeah.

Yeah.

No, that is fair. That is fair. I still feel like we're, everybody wants a new toy.

Give us a good toy.

Somebody will figure this out. I am confident. I'm old enough to remember, like, you know, when I first started reporting, it was like exciting. People had different operating systems. They had different takes on computers all the time, you know, and I just feel like we've lost that. So I, this is like, what are you talking about?

The new iPhone, it has a button on the side. There's an extra button now.

We can only refine the bezel so much.

You know, you're looking a gift horse in the mouth, actually. Come on. This thing is awesome.

I have a bone to pick with you guys, which is, you know, you got this glowing profile in the information about your new media empire, and I was quoted in the story, and they didn't even bother to mention my new media empire.

I mean.

Sorry, sorry, I hit the wrong effect. I hit the wrong effect.

I mean, it was half like complete Glazed Gate, like just so over the top, like lavishing praise on us for genius and reinventing media as a whole from the ground up. And then the other half was like a complete hit piece. It was brutal. And I guess you balance those out and it's like, you know, kind of a nuanced take. But yeah, they did some people dirty. They put us in quotes. They put us in quotes.

They put us in quotes.

But this will be the last time TVP ever appears in quotes. And the last time that Ashley Vance has ever You're quoted in the information without mentioning core memory. Go subscribe right now. That hurt.

That hurt. I like that everyone wants you guys to be the ringer or Grantland and neither of you seem to know. I don't know what those things are.

But it's even worse than that because people are like, oh, it has like, you know, it's Sports Center. I haven't watched that. It's Squawk Box. Also, I haven't watched that. Can you comment to something? We're reinventing the wheel.

We're reinventing the wheel. At TBPN, we're focused on reinventing the media's wheel.

Yes. But yeah, give me the broader update on core memory. I know you have a bunch of different products. You're filming movies, you're writing books, you're doing short documentaries. Give me the overview. And I want to know specifically about the latest update with Neuralink as well. Yes. Okay. Yeah.

I mean, we've launched a bunch of stuff. I'm writing on Substack. We launched a podcast, Palmer is on it.

Today.

And then, you know, I think the thing that we're maybe most proud of, or one of the things is, yeah, you know, I used to make a TV show for Bloomberg and did very well there. And we kind of killed that, built our whole team from scratch. And so on our YouTube channel and on our substack, we've got, I don't know, they go anywhere from like eight to 20 something minute episodes that are, you know, dives into different inventors and scientists and startups. And then, so anyway, please go.

Yeah, you're kind of telling the story of these like various brotopias that are existing all over Silicon Valley.

Unlike some people that only Brotopia, we do do many female scientists. But we're going all around the world, really. So we just went to, so far, the early episodes were Silicon Valley based just because I had to get this up and running really quick. But we just went and filmed in Switzerland for a couple of weeks. And so part of that was, to your other question, we're working on a movie about brain computer interfaces and Neuralink is at the heart of that. and so we're following this journey for many months, years, maybe, and then we filmed a couple episodes with some Swiss companies.

Yeah. How do you think about.

What'S happening in Switzerland?

It's always like this mixed, oh God, you're going to get me on a Europe rant. I'll try to contain myself.

Switzerland is my second favorite country in the world.

It's like, if you're going to go with the Well made museum version of Europe. It's great. They do have some, I think a lot of, well, okay, they have a lot of good biotech stuff coming out from pharma and just like a incredible education system. And they have finance stuff, but we went robotics. You know, I went to a couple of university robotics labs. It's interesting, they're always doing pretty cool stuff and then it's always hard for them, I think, to make the leap into forming a startup and like, really getting money behind that and sort of the same ambition that you would see out of a similar Silicon Valley company. But yeah, we met a bunch of young kids who were doing cool. You will see it coming up in a future episode. We had a robotic swan, robot swans dancing at a lake, shooting water and lights, and we were up till two in the morning filming that. They actually have a gun on them yet.

They actually have a fantastic robotics industry. I'd love that. Over in Switzerland, you got to do a profile on this. They have a fantastic robotics industry all around telling the time. And so they have these amazing companies. You should do a whole profile on-- okay. --Tech Philippe, Audemars Piguet, Vacheron Constantin. It's like this machine. It's basically robotics, but just to tell the time. So I can imagine an Ashley Van style deep dive on those companies being really, really good. It's hard tech.

I would enjoy that.

I think that'd be great. Yeah.

But yeah, it was cool. It's cool. They have, they got good energy. You know, they, the Swiss government really backs EPFL and ETH, these two universities kind of on a level that, I don't know, I've been all over Europe filming the TV show and I'm always, I'm impressed when I go to Switzerland.

Do you think American investors should be posted up in Geneva just slinging checks? Are they ready for American industrial venture capital?

Should they go from spending just the entire summer there to spending some time during the winter?

And most of winter. And most of winter.

And most of winter, ski season. So ski season summer, but then they could also spend some fall and springtime there.

I mean, I don't want to overgeneralize and crap. on an entire continent. But, you know, I do think there's opportunities there, but then sometimes you walk through the European startups and the energy level is not the same as you would find in the US.

They're not sleeping on the floor of the factory over there.

We have billion dollar companies where teams are sleeping in tents.

Yeah. Yeah, we're about to talk to, A billion dollar company where the founder's sleeping out in Abilene, Texas, where you got Chase.

Have you been to Abilene yet?

I have. I went with Sam and, oh yeah, I'm gonna, I'll name drop. I went with Sam and Greg a couple weeks ago and got the tour. That was like a big, everyone in Europe was asking me, they're like, are we hosed on AI? And I was like, well, I just went to Abilene and each one of those buildings cost about $50 billion and they have a lot of them, and you guys have precisely none of them. so, I mean, it was, it was kind of like a harsh. I gave a talk in Poland as part of this trip, and people were not aware of the scale of, like, the investment.

Even MGX setting up a data center in France.

Yeah. Yeah. I mean, the, the overall Stargate project is available to other countries, and, and those deals are being negotiated right now because obviously Nvidia wants to sell chips and, you know, Crusoe will want to sell energy. And there's a lot of different companies in the Stargate supply chain that want to be a part of that, even if it's in another country.

So from what I was gleaning from chatting with Sam on that trip, it sounds like France is the only country that's kind of ready to pony up at the we would like to participate level.

Is it going to be like luxury AI, LVMH GPT, like branded tokens, chat LVMH, artisanal tokens?

That is what they do best. Anyway, this has been fantastic. Thanks so much.

We'll talk to you next.

Let's make it a regular thing. Thank you, boys. Thank you.

I would love that.

Yeah, I'll see you this weekend. All right. Thanks, guys. Cheers. Up next we have Chase Lockmiller from Crusoe Energy coming in the studio. Welcome to the stream, Chase. How are you doing? Welcome. Where are you in the world?

Are you in Abilene, Texas?

Better than Abilene. It might be. I don't know. It might be in San Francisco. Oh, we don't have them. Okay.

He is not here yet.

I thought we had him, but we can do some timeline. What do we got? Oh, this is interesting. There's a shake-up in terms of who's in charge of AI at Meta. And I want to go deeper here because a little bit of an AI day is coming together on Thursday. We have OpenAI and Anthropic on board. We need someone from Meta. So this is a Little call out. If you work in AI at Meta, let us know. We'd love to have you on the show and duke it out with the rest of the foundation model company CEOs and research scientists.

Lab on lab violence.

Lab on lab violence. Anyway, speaking of the man who powers it all, we have Chase Lochmiller from Crusoe Energy in the studio. How you doing?

Welcome.

Welcome to the stream. We are missing sound. Are you muted? Are we muted? What's going on? Let's check it out. and get to the bottom of this. And we can hear you now.

Thank you. Thank you.

He's not a Zoom expert.

Give him a break. What is new with you? How are things going? Give us the latest on all the news that came out. I feel like the last two weeks have just been Crusoe wall to wall coverage. But how are things going in your world?

Things are good. Things are busy. Turns out, you know, AI needs a lot of power and, All these chips need a lot of data center capacity. So what we announced last week was the completion of funding for the expansion of our facility in Abilene, Texas. That's going to consume a total of 1.2 gigawatts of total power capacity. And that funding we did in partnership with Blue Owl Capital. So the total funding is about 15 billion in total capacity to build out.

You know, Let's go. It's amazing. We love to see it. How is it different working with an investor, a financial institution like Blue Owl versus some of the investors that you've worked with on the venture side? Is it more Excel and less vibes and decks? Is it a wildly different underwriting scenario? We're more familiar with the venture style, where it's usually just a handshake and a term sheet on the back of a napkin.

And a prayer.

Yeah.

I feel like I left the vibes investors behind. a long time ago. That was more like kind of the earlier stage stuff.

So.

Certainly different and I think with Blue Owl, they've been a great partner, one of the leading real estate private equity practices in the world. So very sophisticated. I mean, they've been super supportive and helpful across getting the entire deal structured and financed. And then obviously very, very deep pocketed capital providers to really help us make these projects happen at really significant scale. Now, what's different is like this is not an investment in Crusoe, you know, equity. This is a partnership with Blue Owl.

For this specific project.

Got it.

And just, you know, Crusoe has a business model that is not asset light, is very CapEx intensive.

Yeah.

Which requires, you know, being able to tap into those very large pools of capital to basically make these large scale AI factories happen.

So what, so, so really break down the, the anatomy of, like, how these deals work. Is it like there's a new LLC or a new C Corp that's, that's created, and then is there something that looks like a mortgage with, like, a 30-year payback period, interest only period? And then I imagine that this facility is going to make no money for a few years while you're building it out, but then it'll start making a bunch of money. And so is there sort of repayment schedule that's responsive to that dynamic?

Yeah, so the breakdown of the structuring is, so this also came out, there was, you know, the exact number.

Yeah, I'm sure you can't share.

But there is construction financing that's being provided by JPMorgan. So on the expansion, it's a little over 7 billion. that's provided by JP Morgan and then a number of other banks and capital providers in the syndicate, including Bank of America and a handful of others. But the way it works, I mean, it is a prop co, right? So it's a property company that basically, it's an LLC that ends up owning the individual campus. the individual buildings. All of those buildings have an affiliated lease with them with our customer, which is a long-term lease agreement. Being able to partner with a large-scale investment grade customer is really what helps unlock a lot of the capital here. When people are talking about these very, very large quantaums of capital, Reddit is like the magic unlocked, right? So when you have have big long-term off-take agreements with high credit quality customers. That's where you can really unlock these larger pools of capital. And we can put $15 billion to.

Work.

In a positive capacity.

And then so that's happening over there. How do you make money then? Sure.

We make up money as both a project developer as well as we partner with Blue Owl and the ownership of the entity.

Makes sense.

Our customer, you know, it's basically like we're the landlord, right?

Sure.

We have a customer that is paying us a monthly rent for 15 years and, you know, we make money that's in excess of, you know, sort of our debt service obligation.

Yeah. Then talk to me about the energy side. That's kind of the bread and butter, like the history of Crusoe as I understand it. How important is it to find unique kind of combinations of resources to provide energy to these large scale data center projects. What's happening in Abilene? What's unique about Abilene? And then I want to dive into a little bit more about the lifecycle of that energy production plan. Yeah.

So much of the bottleneck of scaling AI has boiled down to just lack of energy or lack of access to energy. And, you know, Crusoe from its founding seven years ago has always taken this energy first approach to building computing infrastructure. Instead of thinking about, you know, how do I build the next data center in Northern Virginia, we've always kind of thought about like, where can we access low cost, you know, clean as much as we can, and abundant energy to power computing infrastructure. And sort of the the revolution you see unfolding with AI and sort of this complete transformation of the digital infrastructure landscape is pretty mind boggling when you really think about it. Because Northern Virginia is sort of like the center of the world for data centers. Everybody's like, okay, the Northern Virginia corridor, that's sort of where the internet is happening. That's probably where this Zoom conference is being hosted. you know, just so much of the.

Internet happens in Northern Virginia. AWS, US East.

We know and love it.

Yeah, exactly.

Everybody is a backbone of our industry.

Totally, exactly. So all of the data center capacity we've ever built in Northern Virginia is about four and a half gigawatts.

Wow.

What we're doing in Abilene, Texas is 1.2 gigawatts. Wow. And, you know, we're looking at trying to do more. Yeah. We're one company. This is for one customer. We're looking at other sites that are five gigawatts, right? So you're talking about building a whole Northern Virginia that's been built over the last three decades. One facility for one customer, right? That's right. You know, there's just fundamentally not enough power there in Northern Virginia to make that happen. And so, you know, what's happening with AI is like you're seeing everybody start to take an energy first approach to developing this infrastructure. And that's really what led us to Abilene, right? Abilene is a market where there's an abundance of energy, a lot of wind particularly, and solar had been built on the back of production tax credit incentives. And their problem was actually they didn't have enough demand for energy. They would frequently get curtailed, which means they would have to sell power at a negative price, so they're shutting down their wind farm, or pricing would go negative and they would sell at a negative price. so their issue was actually just not enough demand for power. So it was a good natural fit between AI factories and low cost, clean, abundant energy. It's a pretty awesome setup. We're going to account for about, I think the number is about 30% of the total tax revenue for Abilene, just.

Like we're like, that's amazing. Can you give me like kind of an energy 101 on on energy production in Northern Virginia between, I'm sure natural gas is in there, there's solar, there's wind. I don't know if there's any nuclear. Are we still using coal at all? I really have no idea. Yeah. Okay. What about crude oil or just gasoline? Does that power AWS at all? I'm just curious about that mix.

Yeah, no, there is actually, especially during moments of peak demand, if you have peak demand at night, Diesel generators probably. Extremely cold night. There's obviously no solar. Sure. And, you know, people are, you know, oftentimes having to use oil, you know, oil to produce power, which is like not a good, you know, not a good, uh, yeah.

It's just, it's like the dirtiest possible option here. Like, we could be a lot cleaner.

It's expensive.

And it's expensive. Yeah. And then, you know, expensive. And then that with Abilene, what's the energy mix look like there? Is it similar or is there something different? You mentioned wind. Is there more wind in Abilene than in other places? Yeah.

I mean, Abilene is one of the windiest places in the United States. It's sort of this corridor that just gets a tremendous amount of wind. And that's why a lot of renewable energy developers built there. I think it's actually important to understand this production tax credit. So the way this works is that the independent power producers that build these renewable energy facilities, they get paid a production tax credit for producing and selling a kilowatt hour of clean power. Now, they get paid that regardless of who they sell it to and at what price. And so that has led to these consequences where, you know, you'll often see power prices go negative because their actual realized price is, you know, after the factor in the production tax credit subsidy they're getting, is positive, but it's like kind of they're having to pay someone to take that kilowatt hour and then they go collect that subsidy through the production tax credits. So now the issue becomes those production tax credits only exist for 10 years. And so at the end of the 10 years, you still have this working wind farm and you're like, okay, power prices go negative. Now I have to curtail and I have to shut off, which means that could be producing power, but I'm not because There's literally no marginal demand for the power. And I think this is where having this alignment of markets where you can produce power in a very cost effective capacity and you can actually build an AI data center there to soak up that energy is a very good alignment that Crusoe has tried to facilitate.

Can you talk a little bit about the history of the company? I know that at one point there was some some crypto mining with gas flaring stuff going on. And then the transition from that into the current AI boom, was that a major emotional roller coaster or did it kind of overlap in a perfect way where it was just like all growth?

Yeah, totally. So, you know, we started the company, one of the first applications of energy.

Was.

As you talked about, was basically capturing waste methane from oil production that would otherwise be flared. and then utilizing that to power initially Bitcoin mining data centers. But we also powered our early versions of our AI data centers.

Sure. Like smaller training runs, right? Yep.

And this was like pre-chat GPT. This was like, we were working with the MIT Department of Physics doing early simulations of the Big Bang, you know, interesting views. And CCL department at MIT, like early, early work in our AI cloud development. development. But ultimately, you know, when I started the company, I really wanted to build an AI cloud platform. That was like, so a lot of people are like, wow, this was a great pivot. And I always tell them, like, no, this was like the plan from day one, believe it or not. Sure. And, you know, but I always felt like energy was the thing that tied together all computing infrastructure and any computing application when really scaled out, energy does become the mottleneck. And I had seen that and experienced that in these proof-of-work blockchains like Bitcoin and Ethereum. And I felt like if AO is going to scale, energy would be a massive component in the overall operating cost of operating intelligence systems at scale. And so we did a lot of early investment in terms of making the platform work with Crusoe Cloud, and trying to figure out what we wanted to build and for who. And then we kind of, with the launch of ChatGPT, it really sort of catalyzed just massive investment and attention to purpose-built GPU infrastructure. And we had done that from the ground up all the way from energy data centers, as well as managed infrastructure as a service at the software layer.

Did you lose any sleep over the Deep Seek news? Or were you Jevin's Paradox pilled from day one and you knew that it was just gonna keep going?

Yeah, I think just like the way that got spun up in the media was like so mystifying.

It was very pro-China media spin.

Yeah, it was very early on. Like, I think anybody, everybody was like, wait, like there's no chance this was like a couple of hobbyists that had like a couple of GPUs in their garage and they trained this model off of like that's just like not what happened.

They did this training run with scraps.

Scraps in a cage. Powered with a bicycle.

Yeah, yeah, totally. Yeah, there's a couple guys with pens and paper just.

But I guess, I guess like the bigger question is as it does feel like we're somewhat shifting from a pre-training to an RL environment. The scaling laws are holding in the macro, but it seems like there's a series of S-curves in terms of the different training and improvement paradigms that lead to just better products. And so, yes, we can do another 10x increase in pre-training, but maybe we hit a data wall or there's some problems there. What are you seeing in terms of trade-offs for demand on the data center side? as we go through these paradigm shifts in terms of what's important to create a really, really performant AI product. Is it just we're shifting from training to inference and that doesn't even affect you? Does it affect you? Do you need a different build out for a large training run versus just mass inference of complex models consistently forever all the time because demand's so high, but it's smaller models all over the place? Does any of that affect the way we build data centers?

I think it does affect some of the ways that we build data centers. But to the question of slowing demand, I mean, the conversations that I'm involved in, there's like, if anything, we're seeing demand accelerate and for, you know, bigger, you know, bigger, you know, larger scale clusters and what and just the overall demand is increasing quite a bit for inference as well. And I think you see kind of.

This.

Transition where folks will use a very large AI factory for a training run that gets some state-of-the-art model. That infrastructure is still useful for a long period of time to serve both inference workloads as well as any of these post-training test time, compute scaling, chain of thought reasoning models that are really basically taking inference queries and then thinking about them and sort of playing out a whole bunch of different scenarios and then coming up with better, smarter, more intelligent answers. And I think that's like the crux of the infrastructure. It's like what we're building are these AI factories, right? So they factories that manufacture intelligence, factories that manufacture intelligent outcomes that are prompted by inputs from users. And I don't see any near-term shortage of demand for more intelligence.

Are you bullish or bearish on upstart or SMB players that want to build AI factories or data centers that see the broader opportunity and then are maybe putting together sometimes sophisticated teams, sometimes less sophisticated teams, but able to pool together capital and want to bring data centers online and just assume there's gonna be demand waiting there, or just assume that they can actually build something that's state of the art.

Pretty bearish. We've seen a massive influx of, we call them two guys in a pickup truck, I got my cousin Lenny who has like this plot of land, you know, out by his ranch and, you know, there's a power line that goes through it and he knows someone that works at the powers, you know, just.

Like- Let's put up a barn and throw some racks in there. We're in business.

Hit up a hype.

Hey, hey, I'm a Google shareholder, right? I'm gonna just call up Sundar. I got a contract, no problem.

Yeah, I got some 3090s in here. I got a couple 1080 TIs right over there.

Yeah, a couple of propane tanks.

Yeah, propane. Barbecuing GPUs. Yeah.

I think the thing is that these projects, you know, they're so big that like the capital investment to make them happen is so massive. And you're seeing people speculatively build smaller scale Mm-. But the, you know, the really big stuff that's, you know, whatever, a couple hundred megawatts or, you know, gigawatt plus, you really need credit to make it happen. Like, you know, I said it before, but credit is the unlock to all of this infrastructure getting built. And we have companies with the greatest balance sheets in the history of business that are going all in on this, you know, technological paradigm shift underway. And with that, you can unlock a lot of infrastructure capital to make all of this happen. But if you're going to speculatively spend 20 million bucks kind of trying to build an AI factory, it's like shooting a BB gun at a grizzly bear. It's like, you're not... Well, yeah, at.

The $20 million scale, you can get a A group of smart people that can make a deck, and then investors are going to see that and be like, I want to make money on this AI thing and be like, well, yeah, we'll throw 20, 30, 40.

Chase has the best animal based metaphors because I remember we were at that nuclear conference and you said that the demand for energy is so high that companies would burn whale oil if they could. And for some reason you keep coming back to these, but the BB gun at the grizzly bear is great.

So I'm sure you work with hundreds of different vendors for different, you know, components, parts, etc., where do you think there is major, you know, sort of supply chain risk or shortages? Like, where would you like to see?

I was about to ask this. We heard something that like a large portion of the transformer supply chain, not the algorithm, the transformer, the physical infrastructure comes from China. and maybe there's a risk to the supply chain with the trade war there. We'd love to know what the key inputs are outside of, we all know power, we all know NVIDIA GPUs, but what else could we be constrained on, whether it's cement or transformers or copper, I don't even know, laid out for us.

Yeah, I mean, the bottlenecks move around, the bottlenecks for AI infrastructure builds kind of move around, you sort of had this moment of infinite demand for H100s when they first launched. And, you know, I think Elon famously said that, you know, it was way easier to acquire illegal drugs than get an H100. And so, so, so, you know, it's, it's rapidly shifted into energy and data center capacity. And, and what does it mean to actually build that stuff out? You know, high voltage Transformers are definitely like a big bottleneck. A lot of that capacity does get built in China. you know, there are, it's a diverse enough supply chain that, you know, I'm not that worried about, you know, trade war kind of impacting high voltage transformers, but, you know, they are kind of long lead time assets. You know, outside of, you know, there's a whole stack in the, in the, in the, in the transformer side, too. So, like, you have the medium voltage transformers, switch gear can be like a, a major long lead time item. that Crusoe actually started manufacturing in-house. So we have factories in Tulsa, Oklahoma, and right outside of Denver, Colorado.

When you say switch gear, is that like network switches, like ethernet routing or something?

No, sorry, it's electrical switch gear.

Okay.

This is basically like your, you know, electrical room that has all of the, you know, breakers that feed into the actual data halls that are powering the--.

Yeah, it's like a power strip. You plug it in the wall, you get six outlets out of the back, kind of like that, but like the.

Big version of that, is that right? It's kind of like, you know, it's kind of like your, you know, it's kind of like your breaker box in your house. Sure.

Okay, got it.

You trip a breaker, you go down and you gotta go flip the switch. It's like that at, you know, a gigawatt scale data center or something.

Yeah, that makes sense.

But switch gear is definitely a bottleneck.

Sure.

Chillers is another big thing. You know, I think an interesting trend in, in data centers right now is with the, with the introduction of the gb200, the new Nvidia chip, basically, you're seeing this massive transition to liquid cooled, uh, Computing at significant scale. Uh, so, you A lot of the government labs and high performance computing communities have been experimenting with things like immersion cooling, single phase and two phase, as well as water cooling DLC for decades. But no one's ever done it at the scale that's unfolding right now. And the reason it's happening is because you just have so much energy density, so much heat being produced by these new NVIDIA chips as we move on to more advanced architecture. that there's, you know, simply just not enough heat capacity to basically move that heat off the chip from a traditional aluminum heatsink or something that's like so big that, you know, it would just-.

Yeah, can you talk about the life cycle of water in some of these AI factories? We had somebody on the show, I don't remember their name, but I do remember that they said we don't have enough water in Abilene to run, you know, these data centers. And that didn't quite feel correct. So I'm not gonna call 'em out.

Is that a bottleneck?

No, it's not. It depends on how you design it. So we've tried to, you know, I think water can be a very sensitive topic depending on the communities that, you know, you're engaged in. And Crusoe's always tried to be a, you know, phenomenal partner to, you know, the local communities. that we're working with. So, you know, the way we've designed our AI factories is what's called a closed loop architecture. So that means basically you have cold water that flows into the rack and it flows over the chips over this copper pipe and you have this heat exchange between the silicon that goes through the copper and then to the water and then hot water sort of exhausted from the rack. rack, that hot water that then goes out to a heat exchanger that's a chiller that's outside. And it's basically just, you can kind of think of it as like a massive maze of copper pipe, and then you blow air over it. You try to blow cold air over it, and then the heat basically gets exhausted out of the water. And then you basically have cold water from that that then feeds right back into the system.

So, yeah, I think people 1 million.

Gallons of water per building, we only fill it one time, right? It's not like we're using a million gallons.

Yeah, yeah, yeah, yeah.

This is what, this is what the media has implied is that like every time you make a cute studio Ghibli image, you're like dumping a gallon of water.

It's like, yeah, a gallon of water might flow over the chip while you're doing that, but then it flows over the next one and the next one.

This is recycling. It's just not.

Yeah.

And at that kind of scale, even in that are open loop where basically you have a fresh water supply and that is, you know, you are consuming a shitload of water in that scenario. But in our case, you know, we've designed it with a closed loop architecture that, you know, is like a, you fill it one time, then you're done.

What's your favorite closed loop? I love closed loops. Last question I have, how do you evaluate your pipeline? I'm sure you're a very popular guy getting, you know, phone calls and emails from all over the world, but you're physical infrastructure. It's not like you can just copy and paste, you know, what you're doing in Abilene or some other areas, you know, a million times. So I'm sure you have to be.

Pretty... Yeah, I mean, we're trying. You know, we are, we have a couple other projects that are underway that, you know, hopefully we'll be able to talk about, you know, more soon, but, you know, similar scale or bigger is kind of like, you know, what we're seeing. so a lot of demand unfolding within the ecosystem. And I think we try to be thoughtful about our partners. I mean, we really ultimately want the space to be successful. I view AI as a generational opportunity to transform human prosperity around the world. And we just want to help make that happen. And we don't think any one company is going to do it alone. We want to help support the entire industry in terms of making this technology successful scaled and really rolled out to the masses. Makes total sense.

Fantastic.

I have a ton more questions, but.

We'Ll have to have you back on because this was a fantastic conversation. We'll talk to you soon, Chase. Thanks so much for stopping by. Cheers.

Appreciate to have you.

Take care. Before our next guest, let me tell you about Ramp. Ramp is ramp.com, time is money, say.

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That it's not a shill. It's off-air.

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Yes. Any, I mean, when we talk about software that is lacking, you just, the most obvious example is like the airline app, right? The airline app is notoriously buggy and you're not logged in. Ramp travel saves all of your information immediately. It shows you all the flights across everything. You just click one button, it just books it, and then it's just boom, you're just booked. No chasing receipts. No chasing receipts, because it happens inside of Ramp, which is amazing. But even aside from the expensing, even if I had to do something else on the expensing side, just the experience of actually booking on is so much easier. It's like, I mean, I wish we.

Had on camera because I know, I know. It was a really special moment.

Leaked, leaked, leaked. Yeah.

I'll be right back.

Anyway, our next guest is coming in the studio. But first, let me also tell you about Figma. Think bigger, build faster. Figma helps design and development teams build great products together. Go to figma.com to get started. We have our next guest coming into the studio. Factory AI, Matan, welcome to the stream. How are you?

Thank you so much for having me. I'm good.

How are you? I'm great. Thanks so much for hopping by. Can you kick us off with a little introduction on yourself and also the company and the news? I know that there's big news coming up.

Yeah, absolutely. So I'm Matan, CEO at Factory, here to share a bit about our latest launch. We released droids. Droids are not just your regular everyday coding agent. They are full end to end software development lifecycle agents built for the enterprise, big enterprise, not just startups. Although, you know, we've in the last 24 hours seen a pretty big explosion of usage with startups, which has been really cool. Yeah, that's it's been fun.

Talk to me about the evolution of AI agents and coding agents. I remember there was a company a couple of years ago that was training their own foundation model, then the regime seemed to shift to, okay, we're not going to do any pre-training on code specifically. The foundation model companies got that covered, but we will do a bunch of post-training. Then it became more, maybe there's some RL fine-tuning, maybe there's just some reasoning that we're doing now. It feels like a lot of the coding agent companies are just kind of like, we're rappers, but we're still printing money and rappers and unnecessary It's actually the best way to build this business and it's helping us. So where do you fall and what is your take on the different paradigms?

I just got here. I got a compliment from Mattias.

I know, I know, I know. Fantastic, thank you. It looks great.

Thank you for...

When you come to the temple, when you come to the temple, you must be dressed appropriately.

Yes, yes, thank you.

But yeah, no, great question. I think it's been interesting how in the last two years there have been so many trends within in the kind of like sub sector of AI for software development.

Yep.

You're spot on. There was a really big trend, especially if you measure it by the capital that was put into it in terms of companies coming out there saying that they're going to train models in particular for code or fine tune models for code. There's been, I mean, there's been quite a few who raised to the tune of like half a billion dollars to train their own models. And I think something that.

A lot.

Of people were saying at the time, or maybe whispering because they don't want to offend those who put half a billion dollars in was code is a core competency for the foundation models. They will not allow a startup to fine tune their way to having the best models. As you see it in general with code, it's like alternating between OpenAI, Anthropic, Google, XAI in terms of the number one spot in code. So I think it, I guess it took a lot more money than it should have, but I think people come to the realization that fine tuning an RL for code specific models will be won by the foundation models.

Is that just a function of like, code is the internet? The internet is code. Code is on the internet. And so if you train an LLM on the internet, you're going to learn out of the box, if you do a robust large scale training run on web text, you're gonna get Reddit answers and you're also gonna get a pretty good model that can code. And so unless OpenAI says let's not train it on code, you're going to lose to them because they're putting the most energy, the most cycles into training the big model. And so you just get that as a byproduct.

Yeah, that's spot on. It's actually, I would go even further to say that, and I know, There were papers on this in around 2022. I'm sure there have been since, but there is a direct correlation between how good a model is at code and how good it is at other general purpose tasks.

That makes sense.

So it is just, it is like, it is, you know, table stakes for the foundation models to be the best at like raw coding. So exactly right there.

Yeah. So how do you build a business without getting rolled?

How have you guys navigated that? Just partnerships with the labs in general where it's you're kind of frenemies, you know, it's like, hey, we can work.

Together, but yeah, this is a good question.

At some point, somebody's going to try to kill the other one.

Yeah, no, this is a really good question. And it's very top of mind. I mean, I think the reality is the closer you are to the zero to one or like the vibe coding or the like less technical your audience and the smaller the company, that's really where the foundation models are about to sweep it up or already have. So it's like building apps from scratch, building websites from scratch. That's something where the model providers will basically get it for free, plus or minus some deployment details in terms of.

How it's going to work.

Yeah, you remember with pre-chat GPT, there were a bunch of players that would generate copy for you based on the OpenAI API, and they had Just rock, their revenue rocketed. Yep. And I remember it was the same sort of like people, like the same behavior of like posting screenshots of like the revenue dashboards. And then those screenshot shots stopped being shared post chat gbt cuz all that revenue, you know, just went away.

As Shakespeare said, these violent delights have violent ends. There was a really, there was a really great, great tweet I saw the other day. I can't remember who posted it, but it was, you know, a lot of people are talking about these, like, record-breaking, like, runs to, like, you know, large ARRs.

Yep.

And what's going to be coming soon is some record-breaking churn for a lot of this, like, monthly, these monthly subscriptions. So that'll certainly be interesting to see. But, yeah, so that's the part of the spectrum where the foundation models are best poised to tackle is that, like, zero to one less technical use case. For us, we've been focused on the enterprise from day one. because one, it's really not sexy and so it's not like conducive to like viral demos and all that hype. But that's where a majority of developers are getting a majority of their pain, like dealing with like COBOL, dealing with these like 20 year old code bases, migrations, refactors. And in order to handle that well, you can't just like one shot with like a chat GPT or a codex or Claude, you need to have deep integration with their code base. Oftentimes it'll be like multi-repo integrations. You'll need to understand not just where the code is now, nice love the little thumbs up guy, not just where the code is now, but how it got there, what the best practices of that org are. Integrating with tools like Jira, Google Drive, Sentry, Datadog. The kind of first principles thinking there is that in order to produce the quality that an engineer who's been at that company for like 10 years would produce, you need to have access to the same information. And that information sometimes requires some really ugly integrations. You need to kind of get the workflows that are a little bit more specific to these large archaic orgs, which is a little bit further afield from what the foundation models are working on right now.

Talk to me about synchronicity, asynchronous coding agents versus synchronous. Copilots versus autonomous agents. Where do you think it's going? Do these lines blur? Are they distinct product? It feels like OpenAI has three coding products now. I can go to 03 and I don't even ask it to write code and it just does. I imagine that the amount of code that's being written for non-technical people who don't even know that code would be useful in giving them an answer to a question. question is just skyrocketing right now in that product. Then there's Codax. They also have WindSurf now. And so you can imagine a few different bites of the apple there. Are they indexing the market? Are these distinct different markets? Will there be one power law outcome in the coding space in terms of time?

Yeah, great question. I think the first order bifurcation that'll happen is between the non-technical audience Technical audience. So for non-technical, being able to spin up apps on the fly is cool and fun and that'll continue to be something that's useful. They're never gonna, yeah, exactly right. And they're never gonna really be that concerned with going too deep into the code itself. They'll just like, I want a to-do list app, make it for me. Okay, great. For the technical user, I think that's where it gets a lot more interesting. Basically, and maybe this is just Just a quick philosophy that we have at Factory, every transformation shift has a very clear behavior change associated with it. So like internet had people getting most of their information from TV, newspapers, books to then going on this console on their desk and getting all their information there. Mobile had people walking around, heads up to now walking around on TikTok, subway surfaces all the time. These are very visceral, obvious behaviors.

Yeah.

And yet everyone talks about AI as it's, you know, the largest one to come, it's going to put these other ones to shame. And yet if you look at the most used products, the most used AI products right now, there is no new behavior. Like ChatGPT perplexity, that's just Google with better results. The behavior, like the silhouette of that behavior doesn't actually look that different. Similarly with a tool like Copilot or cursor, the way that software development is looking, the behavior is still the same.

Same.

You're still in this IDE, which was built for the world where humans wrote 100% of their code. We're quickly going to a world where humans will write 0% of their code. And our take is that their behavior will fundamentally have to shift then. And not like in some iterative approach where you iterate your way from an IDE to whatever this new thing is. But our take is instead you need to build that from the ground up. And this is kind of a long-winded way of answering your question about the like async versus sync. The reality is in this future developers are going to be natively working with agents. And so they'll need to like dynamically adjust between if they're collaborating with an agent to like look through their code base and understand how they should plan some new feature and then having a good plan for it and now like firing it off, delegating it to these agents. And at the same time it's going to put more emphasis on the testing because if you just shoot from the hip a ton of agents, or in our case, droids, then you're going to have a ton of code to review before you release it to production. Because ideally, you're going to review it, right? But that's kind of a depressing world where, okay, we don't write any of our code, but now we just need to read like thousands and thousands of lines before you can ship anything. So if you as the developer have better tests and you know, hey, if it passed these tests, I don't even need to review it because I, well, expressed all of the constraints that I had through these. So if it passes great, let's ship it. There's kind of this new emphasis on testing to kind of enable that more delegative workflow.

What's the secret to avoiding churn in the enterprise? Are you trying to ink multi-year contracts up front? Are you just playing the same game as everyone else and getting a bunch of experimental budgets? Because 'cause money is money and that seems to be the meta right now. But I imagine that you're thinking about this or at least like messing with the community.

When a competitor gets to a customer first, are you kind of hovering with the understanding that like, hey, maybe if we can really show that we're significantly better, we could win.

And is there a little bit of a price war here? Because you imagine that you come into to an enterprise and you say, hey, this would cost you so much to do with Accenture. And we're going to do this re-platforming of your Cobalt application to.NET or something or Python. And you would spend 10 million on that. We'll do it for 8 million. And that's all of a sudden, all of a sudden, that's like 90% margin for you instead of 50% margin. But then your competitor comes in and says, well, we'll do it for 7. 1 million, we'll do it for 6 million, we'll do it for 5 million. And so there's, it seems like there's some sort of price war dynamic that might happen.

Walk me through all of that of like winning in the enterprise financially. Yeah, yeah, that's, that's a great question. So first of all, yes, we do year long contracts just because it's important to have that mutual commitment. And in particular, because adopting the tools is not enough. Like there, I cannot tell you how many like CIOs and CTOs I've spoken to who have adopted like the hot new AI IDE. And then you ask them the question that they don't want to answer, which is how many people are actually using it. And it ends up being like 10-20%. And of those 10 to 20%, a lot of them are just using it like the IDEs of old. Totally. So they're kind of like adopting these new tools, patting themselves on the back, being like, Look, CEO, we did it. We adopted AI, job's done. Give me the big bonus. But the reality is, is like they're actually not getting any productivity improvements. And so part of why we do these longer term commitments is because one of our core competencies is not just having the best agents in the game, but also Droids.

Look, I love it. There we go.

We're also helping them adopt their behavior patterns. Because that's the thing is like, you could have a tool that's 50% as good, but if you have twice the adoption, then you're now at parity. And so I think it's just a lot less sexy because all the like, you know, great engineers who are coming out of Stanford want to work on spinning GPUs and all that stuff. Talking about like behavior change in the enterprise, that's like, ew, like, you know, they don't want to think about that.

That.

But that is where the ROI is going to come. And also, John, to your question, like the way we actually get in and do these deals is focusing on those deliverables about this was scoped out to be four months and we did it in two months or one month or two weeks. That's ROI that actually matters to like the C-suite when you talk about like we shipped tests 10% faster. It's just so like, are we 20% more lines of code? It's just so amorphous and so not tied to real business outcomes that if we can come in and actually tie things to like things that are shipped per quarter or, you know, pulling in dates for certain deliverables, that's where it's just like, it's so frictionless because it's not really existent elsewhere in the market.

I was texting with Adam and Ben from Genius, one of your investors, and they said to ask you about a fateful walk that you had with Sean McGuire.

Fire.

Does that ring a bell?

Yes, it does. So this is in the founding history of Factory, basically, two years ago or two and a half years ago, I was doing a PhD in theoretical physics at Berkeley, which is what I was doing prior to Factory.

And you just thrown it in, you want to kind of take the easy path in school?

Yeah, exactly. Yeah, you know, just some fun string theory, which to be fair, it is really and beautiful. But decided it wasn't the path for me in particular because to be a good physicist, you kind of need to thrive in isolation, just like in your room alone, like reading papers. Did that for like 10 years, was really stubborn. It's kind of a long story, but ended up reaching out to this Sequoia partner, Shawn McGuire, because he also used to be a string theorist. And he ended up going into entrepreneurship, sold a company for a billion dollars, joined Sequoia. saw like a random podcast with him and I was just like, I've never seen like another physicist who has somewhat social skills. Like, let me hit him up and get some life advice from him. Ended up going on a walk together. On this walk, he said, Matan, you need to drop out of your PhD and you should either join one of my portfolio companies and just like work on Glue, another thumbs up, let's go.

Or, let's go.

You should join X because Elon just took over and you'd have to be a badass to voluntarily go there.

Or you should start a company.

That's awesome. And so that was eight days later, dropped out of the PhD and started factory.

So congratulations. Very cool. And yeah, thanks for stopping by. This was fantastic.

And thank you for giving agents a cooler name. I love droids. We gotta get ourselves some droids. Yeah, we gotta get you guys some droids.

Thank you guys. Awesome, great, gentlemen. Have a good one, Maton. Speaking of automation, let's tell you about Vanta. Automate compliance, manage risk, prove trust, continue Continuous. Come on. Vanta's trust management platform takes the manual work out of your security and compliance process and replaces it with continuous automation, whether you're pursuing your first framework or managing a complex program. And next up, we have Johnny from Muon Space. We're talking about data centers with Chase Lochmiller in Abilene, Texas. Now we're going to space and we're putting the data centers in space. Very excited to talk to Johnny. So welcome to the studio. Johnny, break it down for us. And I'm going to let Jordy do the intro on this. And if you're on your phone, would you mind rotating it 90 degrees so it's widescreen? Thank you.

There we go. Do you mind kicking us off? What's going on?

Great to have you.

Where are you calling in from? Randomly, I'm actually down in Yalls Neck of the Woods in Long Beach.

I'm hanging out with a friend at Bass today. Nice, nice. So yeah, why don't you give a quick intro background on the company, yourself.

All that good stuff.

Stuff.

Yeah, sure.

So, muon space, we're a 150 person startup in the Bay Area. We're building a platform to deploy large numbers of satellites and constellation format for a lot of different mission types. We were founded in 2021. It's been a pretty, pretty big rocket ship ride so far. It's been really fun. My background going back a ways, I mean, I've been in space for, you know, well, longer than I care to admit, including I was an intern back at SpaceX in the very early days, like 2003 and 2004. I was part of, I was the chief engineer at Skybox Imaging, which was the kind of first venture backed satellite company, kind of space before space got cool.

Very cool.

And so, you know, taking a lot of the lessons learned and kind of things I've seen from those experiences to the new company.

Awesome. And then break down, break down the new company.

Yeah.

So, I mean, I think the way to think about this is, you know, a lot's changed in the last of space. Traditionally, if you wanted to go do something in space, it required a lot of sophistication. You had to have it literally a team of rocket scientists. You often had to have a lot of deep expertise in everything from, you know, ground stations to launch to avionics software. You know, barriers to entry have come down in a lot of ways, but a lot of that complexity remains. And our kind of goal is to really abstract a lot of that away from a customer that wants to do something in space and doesn't want to have to go build build that full vertical technology stack for every new use case that comes up. And I think that was a big lesson we took out of Skybox, is we kind of built two companies under one roof, a satellite company and a data company. And that the future should really be about a data company being able to go build a data business without having to deal with all the complexity on the space, the ground, the operations, the hardware, the integration side. And that's really what we're trying to.

I want to know about the potential of data centers in space. It sounds like a crazy idea. I know some folks are working on it. Just kind of like, what's your high-level take of the progress we've been tracking? Dollar per kilo to orbit, it's been falling. But recently, there's been setbacks in different programs, and there's more competition, and there's a lot of different dynamics going on. What do you think the key milestones are to get us to a future where we're really doing mass manufacturing, big mega scale projects in space?

Yeah, well, let me start off. I think you guys are hitting on the right metric. It's like the hardest part of this is what does it cost to get a kilogram in space? Because everything else kind of derives from that. Ultimately, if you want a certain amount of power, if you want to be able to put an aperture in space to do communications, whatever it is, like that's really driven by what it costs to get it there in the first place. And I think it's important context to kind of see how far we've come down that path. I mean, largely driven by SpaceX over the last decade. And, you know, I like to tell the story of, you know, about 15 years ago at Skybox, when we were trying to launch these small satellites, we were literally going to Southeast Russia and launching satellites on converted Russian ICBMs. I mean, they were popping out of the ground and putting satellites into space.

Space.

And that was the only way for, like, a Silicon Valley venture funded startup to go put something in space.

Wait, wait, hold on. Did I hear you correctly? Like, the, the ICBM actually launches from.

One of those missile silos in the ground and makes it to orbit, pops out of the ground and goes to orbit. I mean, you see videos on YouTube. That's crazy. If you search on YouTube, you can see this. And it's, it's crazy. I mean, you know, and that, that's, that's what it took before SpaceX kind of, like, revolutionized the launch business. And even at that, we were spending something like 10 times as much per satellite or per kilo is what we can go buy on a transporter launch today. So there's been at least one and arguably two orders of magnitude improvement in the last, call it decade, on kind of what it means to launch things to orbit. I think if you imagine that happening again, another order of magnitude, again, it's gonna dramatically change the way you think about feasibility of some of these things. like putting very, very large power hungry things in orbit. We know how to do the solar, we know how to do the structures, we know how to get, you know, we know how to make electronics work in the radiation environment, which is always a concern and do it reliably. And so really, ultimately, I think it's going to come down to unit cost. And what does it actually take to do that? The great thing about space is you have virtually limitless power. The sun, you know, you can, you can go into orbits where you're in the sun all the time. So it's not like solar on Earth, going in and out of eclipse or in and out of night, like you can be on all the time. And then you have this cosmic background of three Kelvin cold sink that you can go dissipate all the thermal energy you need from running your electronics and stuff. So it's actually in a lot of ways, like sort of an ideal environment to do this if you can actually get there. So yeah, that's the kind of way I think about it.

It's interesting. What it feels like SpaceX has commoditized launch and is kind of the power law winner there. Obviously there's other companies that are competing, but they've standardized launch. They've also standardized Starlink. And then we talked to the EnduroSat founder about standardizing a satellite bus platform and kind of getting to the mass manufacturing, less bespoke, less customized, less hand-built pieces. What else are you seeing as kind of critical pieces of the space supply chain that need to be standardized or you might be? trying to standardize where are the pieces in the supply chain to do the things that you want to do, where it's still like, oh, that has a long lead time, or that's hand-built, or that's way too customized. I get what I want, but it's an exquisite system. It's too expensive. Talk to me about the supply chain.

Yeah, and I'm actually going to give you the answer you asked for and then the answer I want to answer.

So I'll do both. Yeah.

On the supply chain side, I think there's a lot a lot of progress been made. Like our satellites look very much like, you know, especially things like the electronics look very much like what goes into an EV right now. The batteries, a lot of the electronics, a lot of the individual kind of semiconductor parts heavily leveraging other commercial industries. So it doesn't look like a traditional space supply chain. I think that problem more and more is solved. I think EnduroSat obviously is doing very similar things in that way. Some of the places where we really see that that has not yet happened. one is in more on the payload side. So things where like, you know, you think about the spacecraft bus and durasats building buses, you know, I do think there's a path to that becoming very standardized. But every mission you put in space has a bus, and then it has a moneymaker. It has something that's actually doing what you need it to do, whether it's Communications or remote sensing or beaming power. If you're trying to be power, if you're putting a data center in space, it's got a payload of, of compute or whatever. And what we see in most of the kind of traditional space missions is that that now has become kind of the hardware bottleneck. It's like, how do you actually get the payload you need to solve your ultimate business problem built in quantities large enough to deploy in a constellation at costs low enough that you can do it? And I think there's a lot of movement in the right direction in that way, but it's, we're not there yet. And, and the, the other question that I kind of, I'll, I'll answer that you didn't ask is, I think the other big bottleneck outside of Hardware is still software. So, like, you know, we spent, there's a lot of talk right now on software supply chains across a lot of industries, including space. I think there's paths to address that. What is still very true in space is that these are very complex autonomous robots with global networks that are having to communicate inside communication, outside of communication. And software is really the glue that holds all that together. And in a lot of ways, the integration of all these things and the software integration of hardware integration is still the hardest part. It's really making these large, complex systems as a whole. And I really think that's a place that there's not being enough emphasis put in the industry right now. It's something that we're really trying very hard to solve with kind of the kind of core hardware software stack that we're building. So that instead of, you know, for every new use case you're trying to solve in space, you're going and from the beginning having to do this crappy new integration of a bunch of parts of hardware and software that don't actually aren't actually designed to talk together. You have a platform that much like a data center rack today, everything from the lowest levels of hardware to the high level application software is designed to interoperate, it's designed to be pluggable. And so, you know, when Google's putting data centers in the data center, they can go take a bunch of stuff off the shelf. Every rack doesn't look the same, but they have a bunch of parts that are interchangeable. They can go throw that in, plug.

Them in, the software works, the hardware works, et cetera. And we've got to get to that with space too. Yeah, I mean, we've done that a ton in data center, like cat, like cat five cables, cat six cables, like these are all standardized, even Facebook open open source their blade design for their rack mounts, and there's a lot of other ecosystem tools. Last question from me. Are you tracking the SpaceX Starship progress? There was news today that Elon Musk is winding down his relationship with the government as a special government employee. That was a 130-day mission, probably spending a little fewer nights at MaR-A-Lago. More nights than the SpaceX factories. Are you tracking that? Are you excited about that? And I guess the big meta question is Elon has always seemed interested in getting to Mars, but he's willing to go to MaR-A-Lago if that's what gets him to Mars. He's willing to go to Starbase, Texas, if that's what gets him to Mars. So it feels like this might be a moment where he's shifting his focus. The mission's the same, but he's shifting his focus from regulation to engineering challenges.

Mars is back on the menu, boys.

Mars is back on the menu. But what has your take been on the recent Starship or SpaceX News?

Yeah, I mean, I guess I would start by saying, look, you know, building rockets is really fucking hard. I mean, I think anybody that says it's not is crazy. It is rocket science. I think we've almost been lulled in complacency by how successful SpaceX has made it. how easy they make it look. But, I mean, Starship is a crazy complex rocket unlike any that's ever been built. So, like, at some level, I feel like these setbacks should be expected and people shouldn't act so surprised. I think there's, I don't have enough inside information to know if, like, forward progress is being made or sideways progress, progress, there's more focus, whatever. But, like, this stuff's really hard, so I don't think it's that surprising that there's setbacks. You know, I think that the, the key thing for the launch unit economics, which I think ultimately, you know, Starship, we're hoping, we're all hoping it's going to get us another order of magniTude on unit economics. So much of it is not even about scale or size or technical performance or capability. It's about launch cadence. It's about rate. It's about flying. It's like airlines, right? If you bought a 737 and flew it five times a year, nobody would be able to afford to fly. But because it flies 10 times a day, all of a sudden, that the amortization of that fixed asset over those flights makes a ton of sense. So I think for Starship to really go, what we need is we need applications. that require Starship, like Starlink has for Falcon 9, that drive us to launch it three, four or five times a day, like you fly 737s. And I think if that happens, like it will, we will get another order of magnitude in the unit economics. And I mean, maybe tying the loop back to the original question, you know, you start thinking about applications like deploying data centers in space where you're putting thousands of things that are each many, many tons each into space and there's a A really core first order economic driver requiring that, needing that to scale AI training and these types of workflows. That's the kind of thing that I think could drive the demand that you need for something like Starship to really get us another sort of order of magnitude in unit economics. I don't know if I really answered your question, but that's the way I think about it.

No, makes sense. Well, thank you so much for stopping by. This is great. Come back on again soon.

Yeah, you bet.

It was great talking to you guys.

We'll talk to you soon. Cheers. And while we're waiting for our next guest, let me tell you about Linear. Linear is a purpose-built tool for planning and building products. Meet the system for modern software development, streamline issues, projects, and product roadmaps.

And-- It's a tool that I've been lucky to use for over a decade now.

Over a decade on Linear? That's crazy. I'm surprised the company's even a decade old. It seems-- no, no, no. Sorry, half a decade. Half a decade.

Okay.

Because a decade ago you were in middle school.

Say the better part of a decade.

Yeah, yeah.

Okay.

Well, we have our next guest, David from Retool, is coming in the studio. I'm very excited to finally talk to you. I was at your YC Demo Day, at Alumni Demo Day, and no one's gonna believe this, but it's true, so I just have to say it. And you were the one company that stuck out. I was like, that company's gonna be amazing. And I wasn't, I didn't even think of myself as an angel investor. I should have just been like, let me please let me invest. Anyway, it's been fantastic to watch the arc of retool and everything that you've built. So congratulations, and thanks for joining the show.

Thank you. Great to be here.

Huge fan of TVPN. So excited to be here. It's great to have you. Can you give us a little update on the company, kind of define the different eras, what the product is and where it's going? I know, obviously, we're in a period of transformation with artificial intelligence. I'm sure we'll go to all of that. But what has the bread and butter been for the last couple of years? Yeah.

So for the first few years of Retool, Retool is like Legos for code, which is we allow you to build a sort of higher level building blocks and you can code faster. You can piece them together and you can build software. And the weird thing about Retool was that we always focused on this category that we called internal software, which is extremely not sexy because no one ever thinks about internal But surprisingly, it's something like 50 to 60% of all the software in the world is actually internal facing.

Yep.

And no one thinks about it, actually. And so that's where we started. And the idea behind that.

And engineers are not like, oh, I want to work on the internal tools.

Totally.

Typically, you put the engineer that's not cracked, you know, be like, yeah, just focus on this.

Or just someone who's just like grinding away. But, yeah, I mean, this was the big, we were talking to Joe Weisenthal about this. with the question of like Meta training Llama. And there's a bunch of places where LLMs will instantiate themselves in consumer facing products across Meta, but also they have a massive amount of internal tooling that can benefit from AI. And so, you know, not having to fork over endless boatloads of cash to, you know, to just check, is this, does this have profanity in it? 1 billion times a second, right? It's like that could be a very big open AI bill if they don't train that internally. And so, yeah, I think the dark clouds over the internal tooling world is something that most people might not be aware of, but you've obviously been living in that. So talk to us about the growth of the company. What's the mix? Is this all enterprise driven? Is there small and medium businesses that benefit from Retool? Kind of what's the bread and butter on the company?

Well, if you look at the homepage, page. It's like, and the logos, it's like, oh, you.

So you guys work with every company. Every company. Yeah. It's pretty cool.

I mean, we work for companies ranging from the US Army to the US Navy.

Wow.

The state of Utah all the way to small startups, two person companies, five person companies.

So you don't get put on the American Dynamism market maps.

I'm gonna start demanding.

Yeah.

Yeah. We gotta put them on the American Dynamism. Some respect on retail. Yeah. It is.

The backbone of the US military.

No, seriously. I mean, there's internal software everywhere. But yeah, maybe it'd be good to shift into kind of like the AI moment. It feels like Retool was kind of vibe coding without the vibe coding meme or without the, it allowed you to vibe code without the actual instantiation of, you know, you're not in an IDE, but you're effectively vibe coding or building something that's very quick. How have you been processing the AI boom? When did you first think about implementing LLMs and other AI technology into Retool and how has it been going so far? Yeah.

So the really cool thing about Retool is that once you have these Lego blocks built, you can actually give them to AIs to actually use, which is really interesting.

Yep.

We believe is missing now, which is today, if you look at how many dollars have been invested in the US in AI, I think it's around a trillion, maybe a trillion and a half or so. But if you actually look at how much revenue there is from all AI products across all companies, I think it's like 20, 30 billion. That's pretty crappy ROI. That's a 3% ROI. And the question is, is it all about Or can we figure out some use case for this LM beyond just chat? And if you look at where we are today in the consumer market and the enterprise market, it pretty much is all just chat. I think if you look at that 20, 30 billion dollars of revenue, I want to say something like 80% of it is chat GPT revenue plus cloud revenue, which is awesome. But chat is pretty limited. I mean, it's tracking a growth 30x or where we are now. now, it's hard to say. I think probably no is the answer. And so what we think is really missing is a way to actually leverage and use LLMs to actually go automate labor. And the weird thing about this is that LLMs are actually plenty smart already. If you, you know, I use chat a lot. I'm sure you two both use chat quite a bit as well. It's basically AGI at this point. I mean, it was the classic Turing.

Test thing of, you know, blue past that.

Way past that.

Yeah.

And yet, AI isn't doing anything yet. So it feels like this is big disconnect.

Totally.

What we're here to really solve is can we actually allow AIs or LLMs to actually do things in your business? So right now, it's just chatting back and forth. Can we actually allow it? Can we allow the US Navy, for example, to say, hey, it's not just using ChatGPT to answer some questions, but actually ChatGPT actually or LLMs actually do things in the US Navy, whether it's approving orders, whether it's approving plans, whatever it might be. That I think is the next frontier for AI. It's AI that actually does things. And I think we're almost there.

It's pretty cool.

That's what we're working on.

Can you- Super exciting.

Help me work through this question of there's like this AGI ASI narrative and then How does that not destroy every software company? I'm seeing MCP servers spun up left and right. My question keeps being, if the AI is so smart, why does it need a server? Why can't it just use HTML and UI like any other human? At a certain point, is there a world where I say, I want to sell a t-shirt online and instead of spinning up a Shopify store, it just writes payment interop code. It doesn't even use Stripe. It just builds Stripe from scratch at a moment's notice if it's so smart and it just works for a billion human hours added up at 160 IQ and it just builds me Stripe for this one t-shirt that I want to sell. That feels like it aligns with the.

Best example of the regular Sure, sure, sure. But we also had Steven on from the co-founder and CEO of Lambda Labs. Yeah, yeah. His point of view was like broadly that you're just going to generate the software that you need and you might generate 500. And I'm sure this is stuff that Retool is already doing to some degree. Generate a bunch of different versions of what a tool could look like, rank them, allow you to sort of try.

Different versions of it before landing on. So there's like this one, there's this one world where like having Retool tool primitives that LLMs can interact with is amazing in terms of making sure that there's robust performance and everything gets up to speed really quickly. At the same time, in the really long term, do we even need these primitives? And can we just do everything from scratch? What's kind of your long-term view of how this plays out?

So this is, I think, a secret that we've actually discovered is in what cases do you want determinism? versus what cases do you not want determinism?

That's interesting.

And we actually just announced yesterday that we have automated 130 million hours of work for our customers over the past 12 months. If you divide out the math, that's around 70,000 hours.

That's a lot of hours.

I think the secret is exactly what both of you just pointed out there, which in what cases do you want AI? And what cases do you not want AI? And to give an example, OpenAI has a product called Operator.

Yep.

Agent like thing that does things on your computer.

Yep.

And actually for consumer use cases, Operator is really good. What Operator does is basically an LM with one tool, and that one tool is use the computer.

Yep.

And if you want to go buy a shirt, if you want to go buy a pair of socks, Socks, that agent is really good. What it'll do is you say, hey, I want socks, size medium, navy blue color. It will open up the browser, it'll Google, it'll find the sock, it'll buy it, it'll use a credit card, it's done. And that's fully non-deterministic. It's kind of making it up on the spot. And that's pretty good for a consumer use case. Whereas for an enterprise use case, or a federal use case, for example, you actually don't want doing that. And so I'll give you an example. One of our customers, a large company, actually uses Retool for employee onboarding. And so what they say is, hey, every time a new employee starts, you got to go do all these tasks. Maybe you have to go send them a laptop, you want to send them a key fob, you want to do this, you want to do that, whatever. And if you ask operator to go do that, operator says, I got one tool and it's web search. So how do I onboard an employee? I'm going to open my browser. I'm going to Google, how do I onboard employees? Wekihow article, it reads the Wekihow article, it's like, that's not at all what you want. Business has very specific ways of onboarding an employee.

Yeah.

And you want the AI actually calling those specific things because you actually don't want it reinventing the wheel all the time.

And a lot of those might be gated and private. maybe not even on the open web and also very high risk from a regulatory perspective even.

So you don't actually want the AI reinventing it all.

Sure.

So that's kind of what we mean by the building blocks is you almost give AI these building blocks, these tools, these MCP servers, and then have AIs call them as opposed to AI reinventing it all the time. Because you don't actually want AI rewriting your security policy or how do I send laptops to employees every day. Instead, you wanted to say, hey, oh, let me think. There's a big storm happening in the southeast. So for me to get the laptop in on time, I have to ship via Express for sure. Ground. That's something you want the AI reinventing and reasoning about, but you don't actually want the AI reinventing, you know, do I use FedEx today or do I use UPS?

What do I feel? You know, you have a contract with FedEx, you want to use the FedEx one. Sure, sure, sure. Yeah. And that's something that like a good office manager, good person in HR who's on board reporting would actually think about and reason about, and you could inject that with a reasoning LLM. That makes a ton of sense. Talk to me about the evolution of the business model. Consumption versus seat-based pricing, and then going into the future, are we going to be looking at outcome-based pricing, like what we're seeing Mark Benioff talk about in terms of Salesforce, where it's more resolution-based. You want a job done, our agents are our tools can get that done and you're going to pay for results. Yeah.

So this is a fun, this is, I think, a dirty secret, too, is that I think outcome based pricing is basically designed to rip customers off.

Okay.

The reason why I believe that is when Mark Benioff tries to charge you per outcome, he's like, well, what's the value of what I deliver? And great, pay me that. Whereas in reality, it costs a lot for him to actually go deliver that.

That's software though. We want 90% margins. Come on. What do you have against high margins? Yeah, I hear you.

Yeah, no, it creates a, but isn't, couldn't you argue with SaaS, the SaaS vendors basically trying to charge as much as possible without the person saying, oh, we're going to build this ourselves, or, oh, that's actually, you know, we can just hire two more people to do this, you know, it's always this dance between you want to be, you know, companies should be trying to capture all the value that they create, right? Yeah. Because no one would buy a product.

Yeah.

So the way that we're pricing is pretty interesting, which is that we price based on inputs, which is we just say our agents work for $3 an hour. And that's it. If you want a smarter agent, you can hire smarter agents. Actually, that $3 agent is a deep-seek agent. So it's It's like a Chinese agent for $3 an hour. You could go buy 03, which is quite smart, probably the smartest right now, a reasoning agent. I think that's something like maybe $120 an hour or something. So it basically depends on what kind of task you want to do. If you want to do a simple task, actually Deep Sea is quite good at that. At $3 an hour, you're getting a really good deal compared to hiring human labor. Whereas if you want something really knowledge worky or something really nuanced, done, maybe 03 is better actually. But I think the innovation here is that we are charging on a per runtime hour basis. And we've discovered that an hour of runtime for 03, for example, is actually worth something like 40, 50 hours of human labor. Wow. At least you can do it in an hour. I mean, I probably could have been doing it honestly. So that I think is really cool. And then what happens is you actually look at how much the customer per task actually completed. If you compare, you per hour pricing to Salesforce's, for example, per ticket resolved pricing, our pricing ends up something like 95% cheaper, which is really, really cool. I mean, be like if AWS charged you not on compute or storage, if they charged you on how much money does your app make? Let's charge 90% of that. That's a total rip off, right? So that's kind of how we think. We're almost, you know, we're trying to be almost like an AWS, of labor, if you will.

Yeah.

How do you evaluate as the businesses evolve? I'm sure people early on, it was pretty easy to communicate even to investors, hey, people spend a lot of time and energy and engineering resources on internal tools. We can be a big company just doing this. Now, I imagine as you look at the business evolving, you're like threatening a lot of different categories of software because you're saying, saying we're going to enable teams to more easily make the decision, do we buy this or build it ourselves? And maybe retool is some middle ground. I don't know if that's the right way to think of it. But how do you evaluate the scale of the opportunity now?

So the internal goal that we have, and it's pretty early, but our internal goal is to go automate the equivalent of, if not actually 10% of the labor in the US by 2030 is our goal. And the idea is modest.

Let's go. I love an ambitious goal.

I love it. I love it. Here's the TAM.

Yeah.

US labor.

10%. Yeah.

And actually, the cool thing is we're on track actually.

That's amazing.

Over the last few months, if you draw that Now, 2030 is a long time away, but if you draw the line out, it comes to, I think, 4%, actually.

That's incredible.

It's pretty cool, but 130 million hours automated is no joke.

Yeah, that's serious.

Yeah, that is absolutely wild. Well, 15 minutes was not enough time.

We have three more minutes.

We have three more minutes.

Yes, 120. I have one more question. Talk to me about the knockout drag out fight happening in the Foundation model space. You mentioned Deep Sea at $3 an hour versus O3 at $120 an hour. How do the other foundation labs compare? What do you do to benchmark them internally? Are the benchmarks cooked? What's the take on Meta and Llama? There seem to be a ton of energy there in terms of your use case, having an open source model that you can inference for cheap or at cost. seems incredible, and yet it seems like they're a little bit behind on the reasoning models. Are you optimistic there? Are you kind of model agnostic? What's your overall take on the foundation model space?

It's pretty cool to see this play out, especially with our customers, because, yeah, so for us, we're theoretically agnostic. You can use whatever model you want.

Sure.

But it's really cool seeing what customers prefer, actually.

Yeah.

And so for example, with a, you know, large federal a retail customer, you might think, oh, you know, actually on-prem is really important. And so they actually prefer to use Llama, you know, something like that. Sure. That's not the case. Actually, you know, open eyes was selling a lot of open AI, it turns out.

Yeah.

Actually, there's a lot of traction even in sort of big federal agencies for something like open AI. And they actually have contracts already. And so they plug it into the retail and just works. That makes sense. You know, I think I would have thought if you asked me three years ago, is the federal government happy giving all their data to, you know, Llama?

One.

No, hell no. It seems very unlikely, but it's happening.

Which is really cool.

But you also see this obviously happening in other countries, too, where, unlike, whether it's Saudi Arabia or Europe with mistrial, for example, people are getting kind of nervous about sending data to other countries.

LMS.

And so it's gonna be cool to see how the world plays out. It's surprise. It's very much not a meritocracy is maybe one way of putting it, which is we thought that when we build our agents product with an framework, people would just say, let's see who does best, who does for cheapest and let's go. And actually, that's not the case, which is, I don't know how I feel about that, honestly.

Is that because there are SDRs that are buying steak dinners for people and swinging them over, or is it more like there are qualitative metrics that matter more? The nature of the contract matters more than just benchmark price, et cetera. The quantitative There's that, but maybe another.

Way of putting it is LLMs have been stickier than I thought, which is maybe the branding is so important or something like that.

Yeah, everyone just says, oh, it's just one line of code to swap out. But if you're used to the certain, what is undercarpathy call it, like spiky intelligence? There's certain models that spike in certain ways and you have expected behaviors. And they, yeah, they might all hallucinate at the same 3% rate, but if they hallucinate in a specific way, you build around that. that type of thing. Okay.

Exactly.

Very cool. Cool.

But excited to see how the space develops.

Well, thanks for coming on. This is fantastic. We'd love to have you back and just chat about AI and automating 10% of labor. Good luck.

Give us access to the internal tool that's just the labor automation tracker. I'd love to just follow along. We can put it up as a ticker on the screen. It's just like progress. Now, I love the ambition and excited to follow and come back on again soon.

Yeah, thanks so much for stopping by. We'll talk to you, David. Bye. Let's talk about sales tax AGI, numeral, put your sales tax on autopilot, spend less than five minutes per month on sales tax compliance. Go to numeralhq.com to get started. If you're selling anything, software, hardware, e-commerce, whatever you're selling, get on numeral. Makes it really easy. Monitors where you're selling, how much you're selling. whether you're approaching that threshold, start filing. And it does it for you automatically. Cuts it down to five minutes per month. It is brilliant. Also, get on public. Public.com, investing for those who take it seriously. Multi-asset investing, industry leading yields. They're trusted by millions, folks.

Double kill.

Double kill.

I love the double kill.

Thank you to public. Anyway, our next guest is from Pallet. We have Shashank in the studio. Let's bring him in. and hear the latest update. How you doing? Doing well.

How are both of you? Fantastic.

Great. Would you mind kicking us off with a little introduction on yourself and the company?

How you doing? Yeah, sure. So I'm Sushant. I'm the founder and CEO of Pallet. So what we do at Pallet is we're an augmented AI platform built for the logistics industry. So we automate away all the back office tasks you do in running a logistics business, right? Like data entry, quoting, appointment scheduling, tracking where ocean containers are. So there's about like $11 trillion spent on logistics, but what's surprising is about a trillion dollars of that just goes on these back office tasks that you have to do. So what we saw was here is like a real prime application of using AI agents to go and automate away these tasks. But we took an augmented AI approach in that we always have humans QA the work that agents are doing. That way the completion of the task is near guaranteed to very high degrees of accuracy. so that's why a lot of the leading logistics providers really trust us to automate away what basically eats up about 10% of their OPEX.

What's the wedge product that most companies start with? Or do you think of it that way or are you trying to sell a whole suite of products on day one?

So what's interesting is that the technology we built is pretty generalizable and you can customize it per use case.

Yeah.

So customers have started with a wide range of use cases. Like one of the largest cold chain storage companies started off doing data entry. Another very well known shipper has started off automating how they do, how they basically bid for freight with different transportation providers. Other folks have looked at using us for automating spot market quoting. Other folks have started off with appointment scheduling. So we always try to start off with one use case, but that use case could be quite distinct. and the agent we deploy can be quite distinct client by client.

When you say data entry, are you migrating people from other systems primarily or Excel? Or are there still paper-based workflows out there? What are you actually seeing in the modern American economy? Because I feel like a lot of companies will give the pitch of like, get off of paper, but realistically most companies are on Excel.

Do you guys have a humanoid robot that goes to a printer, prints something out, and then faxes it?

Fax machine. Still, still a joke.

Of course.

Even robots will come in soon. But the way it works actually is that like you go to one of these, like even the largest logistics providers in the world, right? Like your DHL, your FedExes, they still get paper documents sent over email. Basically the way it works is you have your email inbox. You have a bunch of emails coming in with documents attached to it. You look at it, first you look at, is this customer someone I should be working with? Are they someone I work with?

Or not.

Then I look at the document, does it have all the fields I want? Then I go type in literally all the fields off the document into my system. And I'm doing this like a hundred times every single day, right? Like I think the whole reason I started this company was I went to one of our customers offices. It was like a Sunday afternoon. And he was like typing in data, like he was typing in a hundred orders into a system on a Sunday afternoon. I can watch the NFL playoffs. I have to type data manually in for my inbox.

That is just so cool.

That's my transportation management system. And this is how I spend my Sunday evenings. And I was like, that's crazy. There has to be something better we could do here.

What is the Super Bowl of the industries that you sell into? Are there specific conferences where everyone gets together in terms of logistics that are super important for you to sponsor? or what does the top of funnel look like for you? Or is it very much just like cold outreach, sales reps, dinner, steak dinners, that type of thing? Or what's the actual go-to-market motion?

So the go-to-market motion, I think we rely on a wide range of channels. We rely on conferences, cold dialing, believe it or not, is still really popular. When I got our first customers, I would actually do something even more extreme. I would drive around around East Bay and Stockton, literally knock on warehouse doors, get kicked out until I could get our first customer in. So I went a bit extreme, but a lot of our SDRs still cold dial. And then there's quite a bit that comes in inbound. But I think the key, the key though, it's not just about the method of the outreach. Like all these companies are a bit skeptical of Silicon Valley technology companies naturally, right?

Yeah.

So the thing I tell, like the thing that we've done is about 30% of has come from the industry. They've worked at places like Siva, they've worked places like Uber Freight, they've worked places like Flexport, and they understand all the use cases in the company. So I always tell everyone on our sales team, you have to earn the right to talk about the technology. First, you need to show the customer on that cold call that you understand their business really well. That like, if I'm talking to a freight forwarder, I understand terminology, like how they deal with containers, what are incoterms, and all this industry specific jargon. And if I can show that the person on the other end is more receptive to hearing me out about how I can utilize technology. Because if you understand their business processes, you understand their workflows. They're like, this is not just another company that's in Soma that's just like looking at logistics terms on chat GPT. These are people that actually just get me.

How much has AI been just an accelerant of the product that you're already selling versus something that you can upsell and bolt as like a new product?

I think AI has been a huge game changer where it's like been like the primary focus of the company, right? Like if these foundation models didn't exist or value prop of a product wouldn't be as strong as it is today. So I'd say it's very critical. And I think in fact, one thing that's made it even more critical is what's happening with the recent tariffs, right? Like the volatility, like what tariffs have really created is like this extreme sense of like volatility where like April, container volumes in Long Beach are spiking. Now they're down and the courts reverse the ruling and it gets reversed back in the last hour. So people have no idea, like my volumes keep going up and down and I just can't scale up the human capacity to support it. And now AI really just allows me to kind of come in, like if I'm getting more emails into my inbox, I can deploy these agents and then they can go and handle this excess volume that I would otherwise have to hire contractors really quickly to go do. so it's a huge game changer, especially with what's happening right now.

What was it like selling, maybe call it a month ago, when the trade war chaos was sort of peaking in some ways? And I imagine people at that point feel like they probably need better tools, but at the same time they're like, hey, I can't really handle onboarding, but I'm curious, what, what your experience was actually like.

What I tell them is like, look, you're, you're kind of like right now, the way we price this is on a per success outcome. Your cost of doing this, let's say, is a dollar in house. It's going to be a dollar 30 on pallet. So if we do what we're going to say, you're going to have guaranteed ROI and you're going to have immediate time value. The second thing is that we've built a very, the way our product works is we can ingest the customers as SOP and immediately spin up an agent that replicates their workflow. So we also really emphasize our time to value where we're like, look, you're not changing your tech stack, you're not changing anything about your operation. You're just sharing, you give literally give us a video recording of what you do. We'll capture that and we can then create the agent to go and automate it. And it requires a minimal touch.

You're not changing any of your stuff. I just have to call something out. So you were at retool before pal, we just had David on. and he said that he, it's just so funny because he was like charging on a per outcome basis. BS. That was his take. I don't fully, you know, necessarily agree with it, but it's amazing that you were just there.

I love David. He used to be my former boss, but I think that's one area we probably disagree on. I think outcome-based pricing is a game changer.

Yeah, yeah.

Talk about the round. It's only been seven months since you raised your $21 million Series A. Now there's a $27 million Series B. I'm sure there's a valuation markup. I don't know if you're sharing that, but it's not a huge step up in terms of total capital raised. So what does that tell us about the structure of the business and the burn rate and how you're thinking about capital consumption? You mentioned that AI has kind of infiltrated everything. Is that a cost center now? Are you actually spending significant a significant amount of capital on inferencing AI models, or is this more just we have something that's working, so we're going to hire more, right? More code, more sales reps, more dinners, more steak dinners, more champagne, more hitting the size gong when you get a big client.

So actually, we had, we, most of the capital from the last round, we hadn't even spent. Like, we barely touched it, tapped into that. So this round was entirely opportunistic. And the, the, the part of the reason it came together with the folks general catalyst. I knew them really well. We got to know each other really well, and they helped build Samsara. And Samsara was probably the most iconic logistics software company. So a lot of it was Heyman, Mark and the team there, like, really knew how to build a big business. The second part was I kind of felt like the industry was going for a big change, and I just really wanted to accelerate our momentum on our product and our Enterprise sales motion, where what I saw was I was talking to the CIO and the CEOs of companies like DHL, Kuehne Nagel, Estee Lauder and all these corporations and they were telling me, we're trying to figure out how to use AI. We have no idea which model to pick for which use case. It's like these models keep evolving at a rapid pace. We need someone to be that translation layer to kind of make that happen. So that was very obvious from the conferences that I was going to. And the second thing was when these tariffs kicked in, I was like, There's so much volatility that the value prop of this stuff is a no-brainer and we just really need to accelerate at this time. So that's why it was completely opportunistic where we had the right partner, the market felt like it was just getting ready for the technology and we were like, we know exactly what we want to do. So let's go and accelerate.

Yeah, you mentioned some of those really big companies and them not being able to decide between different models. Have you bumped into any of the large consulting firms, the McKinsey's of the world, because we heard this narrative early in the AI boom that they're making more money than the startups and the tech companies because they're selling pitch decks at extremely high margin, talking about AI transformation and then just saying, hey, if you're a big company, you can go build it. Here's our take on AI, or are they more of a partner that could recommend you Do you have any insight into how the big management consulting firms are confronting the AI issue and plugging into the Fortune 500?

What we've generally seen is that the consulting firms are very much open to partnering with companies. I think the way that you think about it is the executives at these businesses, there's a lot that's happening. There's a lot of noise. I'm not even sure who the right partner is. Do I go with a horizontal solution like Microsoft Copilot, Do I go with one of these newer players? Where do I allocate my capital and who do I take as my partner? And think of the consulting firms as a way to help these companies filter out all that noise on who is the right partner for me to work with. So we very much think of them as critical partners that help us earn the trust of these Fortune 500 corporations.

And.

That'S how we view it. Actually, as the CEO of one of those firms is actually someone who I've gotten no well, and he actually has helped us actually open a couple of doors. Very cool.

Just gotta say you're exceptional at sales. I'm ready to sign up for pallet right now. And I have nothing to do with your interests.

Hey, we're gonna be shipping a lot of hats, a lot of jackets.

You're like, he's like, well, a lot of people think that, you know, our solution might not be right for them, but I'm like, I want to actually try.

Yeah, yeah, yeah, yeah, yeah, yeah, yeah, yeah, yeah, yeah. anti-cell. Cells better than anything else, for sure.

Yeah.

Anything else, Jordy?

No, congratulations on the new round.

Yeah, this is fantastic.

Yeah, I mean, grateful to be here. One last thing, by the way, is that one thing we've really kind of pushed for a palette is this concept called hybrid work.

Sure.

Where what we believe in is actually that like, there's only two places you could work at palette, either in the office or at the customer site.

Ooh, every week.

Every this month, we make our team spend a week at the customer site. So last month, our entire team was out in Medellin at a customer's BPO, learning their operations and learning how they can like, like every single aspect of their processes. And I think this is really important because in a world where software costs are trending to zero, like, if you don't understand the customer's workflows, like in excruciating detail, you might not be like building the right thing. you don't need all good documentation. You can't just go chat GBT, the right answer on how does container track and trace work. You actually have to sit there, observe, learn, and then, that's what- yeah, I love that.

The hiring process, candidates like, so do you guys support a hybrid work? And you're like, of course we do. About a week out of the month, you'll be in South America. and you built out that function at Retool, right? The sort of concept of this deployed engineer.

Is that correct? That's correct.

Yeah.

Yeah.

I was probably the first forward deployed engineer there.

Very cool.

That's cool. So you're pretty bullish on the forward deployed engineering meme kind of just growing and growing in the future broadly for like every company, or is it specific to B2B software or something about AI automation and something that needs to be customized? I imagine that there have to be some organizations that they don't need it because the product is so standardized, right?

Yeah, I think it's not necessary for every type of business. I think in our case, we're dealing with a company that has a lot of internal systems and processes that you have to hook onto. And we're trying to make change management, to your point. What you said earlier was like, Hey, I don't want to change my operations too much. I want to stick with what I do.

So if we want to make change.

Management simple, we need to hook them with your existing infrastructure. So at least for Palette, we think the forward deploy engineering function is critical to make change management easier. But there's obviously tons of companies that.

Could succeed without that function. Yeah, that makes total sense.

Well, thank you so much for stopping by.

Yeah, congrats on all the progress. I'm super bullish. Yeah, I'll talk to you soon. Cheers. I feel all see you. Bye.

How'd you sleep last night, Jordi? I put up historic numbers again. really had kind of a. Did you watch it?

We were on caffeine yesterday, John. I.

Do you. Did you track how much caffeine you were on? I was on a lot of a.

Fair amount of caffeine. Couple years.

I got six and a half hours.

Of sleep, which is almost seven for me. And 82. What'd you put up? What was your final number? Did I beat you?

No, you didn't. Even on my worst night, John, my worst night this month, I still be you.

I got an 84. Anyway, go get yourself 28 sleep, five-year warranty, 30-night risk-free trial, free returns and free shipping.

It's what Charles LeClair sleeps on. That is, when he's crying himself to sleep.

Yeah, there's a timeline post I wanted to highlight here from Andy Nexuist because it ties into our next advertisement. Stripe put up a digital billboard in Grand Central and it just says Stripe billing, usage-based billing. to scale your business faster. And the meme is everyone there having the same thought bubble. What a silly niche ad. Nobody at Grand Central has even heard of Stripe, let alone implemented it in prod like I have. And it's so funny, but it's so true. I have actually implemented Stripe, and I'm sure so many people that go through San Grand Central have. And I think I think it's, I think it's my interesting takeaway from this, sorry, is that there is a desire for, like we talked about out of home obviously, we're gonna read you an ad quick ad, don't worry, it's coming. But I think that there are companies that feel like they need to abstract their message into even broader terms when in fact, I think just being clear about what the product is and just knowing that, yes, implementing stripe is a common thing at this point or whatever. And those people walk through Grand Central.

A lot of people do start yelling about their company without being clear about the product marketing effectively. And then that can just make your life so hard. because people are aware of your brand or your company, but when the moment comes that they would convert, they don't actually think of you in that context.

Yeah, there is a different version of this Stripe ad that is a photo of Patrick Collison talking about increasing the GDP of the internet and stuff, and it's very high fidelity.

I like to see him.

And I'd love that.

Going one of the cloud Classic Arnold.

Oh, yeah. Hitting the Zyz, the ZYZZ guy. Yes, absolutely. But aside from that, it's like, it's like, it's okay to just send the message up front. Just be straight up with it. Like AdQuick, out-of-home advertising made easy and measurable. Say goodbye to the headaches of out-of-home advertising. Only AdQuick combines technology, out-of-home expertise, and data to enable efficiency seamless ad buying across the globe. And yeah, I'm still super long on out-of-home advertising. You can see Stripe is doing it in Grand Central, and it is-- and.

It'S the most fun. It's the most real.

Yep, yep.

Seeing your ad on Meta X, et cetera, is cool.

Yeah.

Seeing it in the real world.

Nothing like it, nothing like it.

It's different.

Did you see Nathan Fielder piloted a full Boeing 737 plane for this?

Yes, I did finish the show.

I finished it. It was kind of a challenge because I kept falling asleep like two-thirds of the way through every episode. So I've seen the entire season, but I actually should probably watch it back again.

It's a little awkward.

But yeah, it was absolutely wild, and especially the context, like the timing of when the show actually premiered and the episode started rolling out. Yeah, it really is insane.

Absolutely.

But he's one of the best to ever do it and he's a real icon. And I would like to be in his next season.

Well, speaking of icons, there's nothing more iconic than a Rolex and you can get one on bezel.com. your bezel concierge is available to source you any watch on the planet. Seriously, any watch. They have 26,000 luxury watches luxury watches available. And so go check it out at getbezel.com and next up we have Rob Taves, a good friend of mine. I grew up with him. I went to middle school and high school with him. Now he's a venture capitalist at Radical Ventures and he's a great columnist and writes about artificial intelligence and has been writing about artificial intelligence since before it was cool, which is fantastic. So we'll bring in Rob and ask him a bunch of questions about artificial intelligence.

How are you doing?

What's going on?

I'm doing great. Thanks for having me, guys.

Welcome to the show. What is top of mind for you right now in AI? What's the biggest thing that you've gotten right over the last few years? I know you have that scorecard, 10 predictions, then you rank yourself as you look back on all of your predictions. What's the big one you got right? What's the big one maybe you missed on?

It's a great question. Yeah, every year I write a column of 10 predictions for the year to come. in the world of AI. And to keep myself intellectually honest, I go back at the end of the year and grade which ones were right, which ones were wrong. Let's see. So far this year.

One of the.

Predictions I made at the end of last year was that President Trump and Elon would have a messy falling out, which would have various implications for the world of AI, which looks like it may be playing out. We'll see how that all comes together.

Yeah, we were reading that today because Elon is no longer a special government employee. But at the same time, messy seems like the key word. There might be a split, but if it's clean, you're getting a yellow, yellow clean split.

We need satellite imagery of whether the red Tesla is parked at the White House.

If there's a Tesla still at the White House by the end of the year, I think you gotta fail that one.

Yeah, but not messy yet, for sure.

Yeah, it's interesting because it is kind of a narrative violation because half of the world was They're gonna be together forever, they're in love, they're gonna be partnered for four years, maybe for 10 years. And then the other half was like, this cannot last, it's gonna blow up and it's gonna be super messy. And it feels like right now it might just be, hey, back to business, sleeping in the factory. Who knows?

Yeah, the book is not yet over.

Yeah, yeah, yeah, anything could happen. Anything could happen. What about things that you feel like have played out as expected? have you been kind of reassured or shocked by the data wall, the pre-training wall, the shift of the focus to reinforcement learning, the importance of tool use going forward, the importance of prioritization versus this narrative around, oh yeah, just scale up the big transformer model, GPT-7 will be ASI. Done.

Yeah, yeah. I think those trends are all very much playing out and it's been interesting to watch. I think it became increasingly clear over the course of last year that the pre-training scaling laws really were plateauing and this narrative emerged towards the end of last year as OpenAI was increasingly teasing its reasoning models and its O series of models that there was this kind of next frontier, an X-AVista for scaling, which was inference time compute and.

Scaling.

Reasoning models and so forth. And the reasoning models 010304, Deep C6R1, et cetera, they have been very powerful and have unlocked a lot of new capabilities and use cases and so forth. I think the jury is still out as to whether they really represent this next massive runway for scaling that will take us many years into the future. I think it's still still may be the case that the fundamental underlying capabilities of the models are not growing as quickly as they did in the GPT-2 to GPT-3 to GPT-4 era. But importantly, that may not matter that much to your point, John, because I think the value and the activity is increasingly moving up the stack. And even if all model capabilities basically were frozen in time today, there were no further advances, there's literally trillions of dollars of economic value to be created by just figuring out how to productize these models, build particular solutions for particular end markets, and even the big frontier labs, OpenAI, Anthropic, et cetera, are increasingly focused further up the stack. So I think that's where more and more the action will be.

Yeah. What is your take on how the shift from pre-training to test time compute affects data center build out, the need for these hyperscale star gate-like massive data centers. That stuff made a ton of sense in the Leopold Aschenbrenner, we're just going to scale it up and get this massive data center going for the biggest pre-training run ever. In a test time inference regime, it feels like maybe it's more on demand, maybe you don't need as many big super clusters, but am I just thinking about that incorrectly because maybe we still need the massive clusters because the rate of token production and is just going completely parabolic.

No, I think that narrative conceptually holds true. And I think a key insight, as you touched on, is inference can be done in a much more decentralized way. You don't need to have hundreds of thousands of GPUs that are all really tightly interconnected, as close together physically as possible. And so in a world where more and more of the compute is inference, either productionization of models or inference time compute, that can be done on GPUs that are more spread out. And you don't need to have these like, map, like five gigawatt clusters. The counter narrative is the like, and I'm sure you guys got sick of.

Like hearing Jevin's Paradox get referenced like a million times over the past few months.

But it's the kind of, we love Jevin's Paradox.

We think it should be taught in middle schools.

We almost got it tattooed right here.

Never forget.

Never forget. Yeah, that guy, that guy has really been a mortal but I think there is a narrative that even as inference becomes more important, as computer gets cheaper and cheaper, there will still be bigger and bigger and bigger pre-training runs, and so that will justify the massive CapEx build out that we're seeing.

Yeah, I've always been interested to see if there's going to be like the big Transformer training runs, like the GPT-4.5 training type training run in image diffusion or in robotics or even I was thinking about, we've kind of solved chess engines, but what happens if you scale that up seven more orders of magnitude? Do you get some weird outlier scenario? The question I always have is, when can I see it on semi-analysis? When can I see it from a satellite image? Then I know that the big training run's happening. I'm wondering, are there any other areas or regimes of training that aren't just predict next word that we could see a huge data center run happen? Or is it really just text is the only option for that scale? Or will we see a VO4 training run and we'll be hearing about, oh, wow, it's at five gigawatt scale because VO4 just needs that much pre-training?

Yeah, yeah. So this was one of my predictions for 2025 is that we we would start to see more and more scaling laws in data modalities other than text, other than language. And I do think that we're starting to see that play out in robotics, for instance, in biology. I mean, there's the whole premise of the whole justification for building such massive compute clusters is this notion of scaling. And as you increase compute and increase data, the model gets reliably better. And we are starting to see like nascent signs of that in some of other data modalities. I think one important challenge or constraint though is there are very few other modalities where there is as much raw data available as there is for text. There is not an internet for robotics training data or an internet for biology even. And so the training data sizes can limit it. It doesn't make sense to have a massively over parameterized model if there's just not enough training data. And so for foreseeable future, at least. I think the amount of training data available will cap how big the biggest robotic foundation model can be, for instance, relative to the biggest general purpose language model.

Do you buy the whole robotics thesis of like, but transfer learning is really effective and we can totally simulate this because we have Unreal Engine. It feels like a little bit of potential cope being like, well, we know that you don't have the trove of the robotics data. And so you're coming up with something that hasn't worked in other modalities, but at the same time, Unreal Engine's pretty real. And you can imagine walking a robot around and learning a bunch of stuff if you train. So what is your take on robotics data and transfer learning, simulated learning, that type of stuff?

Yeah. I think there's no question that robotics foundation models are getting increasingly generalized. And there's more and more signal that that you can in fact build a general purpose robotics foundation model and you can expose it to some previously unseen scenario and it knows how to navigate the real world in a way that generalizes the same way that language models started doing a few years ago. I think this question on training data is a really, really important one and a really key one. And there are very strong opinions on both sides. There are robotics experts who swear you can use simulations in synthetic data to massively scale up the training data set and use that to kind of erupt these scaling laws. And there are other folks who believe that there's really no substitute for real world data. And you can supplement it a little bit with simulation, but the sim-to-real gap is still a very real... There's a meaningful gap there. And so you can't get that much juice out of just simulation. I think today I fall more on the side of the importance of real-world data. I think there's just so much nuance about the real world that isn't adequately fully captured in Unreal Engine or whatever sophisticated simulation engine you can build. But I do think as time goes on, Sim to Real Gap will probably close. And I would imagine it ends up looking not dissimilar from the way the autonomous vehicle industry-- I was about to ask. Where real-world data is essential, right? And everyone I remember seeing Google's cars driving around for over a decade collecting data, but no major autonomous vehicle program today is not deeply based on simulation as well. And so I think some mix ends up being necessary. I think in robotics today, you still have to be heavily weighted toward real-world data, but hopefully just for the sake of leverage and technology advancements, I think simulation will end up getting better and better.

Is there an analogy between the pre-training to test time inference regimes in LLM training and chat models to what's happening in autonomous vehicles and the difference between pre-training on all the data and on policy training that you can do and then also add simulation on top of that? Is there an evolution of the of the kind of mix of training paradigms that you would use in AV. And I guess the bigger question is just like Waymo versus Tesla, is there a meaningful data gap between those two companies? Because Tesla's obviously been tracking tons and tons of data, but Waymo seems to be working pretty well when you get in the back of one. And so it seems like both companies might just have enough data and we might wind up in a situation where no one's talking about a data gap between Gemini, ChatGPT, Anthropic, Llama, they all just have all the data.

Yeah, totally. It's interesting. The way that autonomous vehicle AI stacks work today is because they were kind of crafted and developed in the pre generative AI era. They're not like these massive pre-trained foundation models where they just all of the data in the world. Like they are much more handcrafted. But it is an interesting thought experiment. And there are like more younger next generation autonomous vehicle companies that are taking this approach. Like let's build a foundation model for driving. And, you know, can we do something, you know, similar to what companies like physical intelligence are trying to do for general purpose robotics? Can we just apply a model like that to autonomous vehicles?

How would a startup like that get data? That feels like the hard part. hardest thing because you can't just crawl the web, right?

Exactly. Yeah, yeah, yeah. It's much harder to get training data for. To your question on Google versus Tesla, Waymo versus Tesla, I think this is like a fascinating age-old question. And you're right that Tesla has way more training data in the sense that it has this fleet of personally owned vehicles driving around. The quality of the data is lower than Waymo's though for the specific re reason that they don't have LiDAR as a sensor modality. And so this is like the big debate that before I got into VC, I worked in autonomous vehicles. And like even back then, this was a debate, like can you get to level four autonomy without LiDAR? And Tesla needs to believe that the answer is yes because their business model is selling cars to consumers. And LiDAR is so expensive that like it would completely wreck the unit economics of selling a car to an individual. Waymo can stomach the cost of a LIDAR because their model is a robo taxi model. Honestly, I think the jury is still out. Tesla folks will tell you that we're very close to that and LIDAR was never necessary. But I think it's not completely clear yet. And so in that sense, the data set that Waymo has is more robust just because it's much more multimodal.

Do you have a sense for why LIDAR is so expensive? expensive. Elon Musk was able to make rockets cheap. The iPhone is cheap. How can we not get LiDAR down? Even just a couple thousand dollars, that wouldn't break the Tesla paradigm, right? But I assume that when we're talking about a LiDAR package on a Waymo, we're talking five or six figures and that breaks the model. But historically, humans have been really good at mass manufacturing expensive stuff and make it cheap. so I've always wondered about, you know, Elon for a decade has been LIDAR is doomed, we don't need it, we don't need it. But he also changes his mind. And so I wouldn't be surprised if one day he's just like, yeah, we figured out how to do it.

We have LIDAR in the cars and like, you know, too bad. Yeah, yeah, yeah. And there have been rumors of Tesla experimenting with LIDAR here and obviously under wraps. So like, sure, sure, sure. I wouldn't shock me. I think it's a great question. I think the short answer is It's like, it's a complicated sensor. There's a bunch of lasers. They're moving around and so forth. But to your point, the cost curve has been coming down on LiDAR. And we'll continue to come. So the original bucket-shaped LiDAR that Velodyne made were $64,000 a pop on the really old-school Google self-driving vehicles. Now they're probably a few thousand dollars each. You need several of them on a car, so it doesn't add up. But I think you're totally right. And there are, like research prototypes of LIDAR that are solid state, meaning they don't have pieces that move and that makes them a lot cheaper. And people talk about like $250 per unit LIDARs, which again are not like production ready yet. But I think you're certainly right that like the way this debate could be resolved is like it may just all converge because in a few years later gets cheap enough that like Tesla can use it and everyone can use it.

I had a buddy, friend of the show, Waymo share recently. I'll give you some context. He said Waymo will change the world. Walk down the street. $1 million in metal sitting unused 20 hours a day on every street in America. Garages will be useless turning into storage or ADUs. Parking lots the same thing. Street parking will be more lanes. Driving offense revenue, DMV revenue, parking tickets all go to zero. Gas stations will be worthless. Sounds insane, right? But Uber went from nothing to everywhere in a decade. Waymo might take 15 years, but the disruption will be nuts. How do you think about the downstream? Assuming that you believe some of that is real, and I think Sean makes some great points. How do you think about the investment opportunities that are downstream from ubiquitous autonomous driving? Are there going to be as many venture opportunities or is it... AI car washings?

Startup. Pull the autonomous vehicle in, it washes itself. It's great.

That would be different than a regular.

No, no roll up. We're doing a roll up.

Humanoids, yeah. Yeah, so I just, to me, this seems like a lot of opportunities on the real estate side is like, Hey, can we turn this into more housing?

Yeah.

You know, whatever, but.

Parking lots aren't cheap though.

But yeah, this is, this is, the context here that Waymo monthly rides were sort of ticking up gradually and then just shot up to 708. And I guess they're now doing more rides than Lyft in the Bay Area as well.

It's crazy.

Yeah, it's been amazing to see how quickly Waymo has gone from like a novelty to just a piece of the fabric of life for people in San Francisco. And like most people that I know in the Bay Area in San Francisco use Waymo more often than they use Uber and Lyft. lifts and it's like quickly spreading to beyond just being a Bay Area phenomenon. They're now live in LA, as you guys know, and in Phoenix and in Austin and so forth. And yeah, so I think it is, it's remarkable to see it after all these years finally become like a real business that's scaling quickly. And I really like the excerpt from your friend. I mean, I think I very much agree with that line of thinking and one of the things that initially attracted to the world of autonomous vehicles back like a decade ago. Was this fact that it's really fascinating technology, you know, it's difficult technology being able to get a car to drive itself, but also once you solve it and you start scaling it, it has so many broader implications, second and third order impacts on so much of society and the economy. Like so much of modern life is built around roads and cars and the way cities are designed and so forth. So I do think it will have dramatic implications on civilization, bigger picture. It will play out over a longer period of time because we're talking about the built world and it takes time to adjust. But yeah, I think especially in cities, at least to start, especially in urban areas, it's some crazy stat, like a third of real estate in the average American city is devoted to parking. And so much of that can go away. And it's like such an inefficient use of space. so you can imagine cities being totally redesigned around humans rather than around cars, more pedestrian areas and so forth. You can also imagine there's a lot of people talking about the rise of exurbs, like being able to live further and further outside of an urban setting because when you're commuting, you don't have to be driving. Like you can imagine the entire form factor of a car changes and maybe you have a desk and a couch.

Yeah, I want it to be a desk and a couch. I just want to, yeah, I mean, I've spent a bunch of time thinking about this because I kind of have a gnarly commute right now and it will just become so much better, you know, within when I can get.

Jordi's in Malibu, I'm in Pasadena, you've spent time in both. We'll get you back here eventually.

Yeah, yeah, I'm excited for Waymo to expand the geofence in LA more and more.

Yeah, yeah. Well, this is fantastic. I'm glad to have your back. This is a lot of fun. We can talk about 25 other topics in AI since this is the most fascinating industry right now. We didn't even get a chance to talk about deals and stuff, but I'm.

Sure we'll go into all that in.

The next time you're on. Yeah, that sounds great. Thanks for having me, guys. Thanks so much. We'll talk soon. Bye. Next up, we got to sing. We got to hit gongs. We got lots to do. We're going to say, is he going to sing with us?

It's always hard to sing with a.

Remote guest, but maybe we should sing beforehand.

Find your happy place.

Find your happy place. Book a wander with inspiring views, hotel great amenities, dreamy beds, top tier cleaning, 24/7 concierge service. It's a vacation home by better folks. And we have the founder of Wander in the studio coming in to announce a massive round of funding. Welcome to the show. How are you doing? Get on that wide. Hit that gong.

Hit that gong.

Hit that gong. Welcome to the studio. John. It's great to have you here.

It's great to be here. I was hoping that I'd be able.

To sing with you guys, so I'm a little, I'm a little disappointed that.

I didn't get to sing. It's really hard with the delay. We got to figure this out somehow. Some latency mitigation or something.

We also need to make it a full song.

Yeah.

Because oftentimes I get to place.

There needs to be choruses and verses. Yeah, we need to integrate the whole pitch into one big song. But congratulations, break it down.

Ideally, when somebody walks into a wander for the first time, they're sort of serenaded by us.

Yes, yes.

We can sort of, you know, two, three minutes on the whole home speaker system. So we'll work on that.

We can make that happen for sure.

That'd be great.

But yeah, give us the business update, break down the fundraising round. What are you actually spending it on? 'Cause I know it's an asset light model, but, explain how the round came together, the progress of the business.

Totally. So it's a $50 million Series B led by QED, Fifth Wall alongside Redpoint.

Logan Bartlettson.

Okay, Redpoint, Starwood, a bunch of really incredible folks.

Fantastic.

And yeah, in terms of capital, it's really, I mean, I'd love to get on here and act like we're gonna do some crazy stuff, but it's really Scale. Like we have three core priorities, which is quality stays, quality customer support, and then quality homes. And that's really where we're laser focused.

Very cool. What's the key to onboarding more wanders? I've seen the numbers ticking up every week as we cover you guys. What's the funnel look like?

Yeah, it feels like you guys have a relentless pace and a culture that really celebrates that and yeah, break it down.

Yeah, wander wander definitely has a very high output culture as a, as a startup. I tell the team that like culture is not, you know, like happy hours and, you know, like that kind of stuff. It's about winning. And so, you know, as a company, we obviously very much focus on, on that idea from, from a growth perspective, there's about 300,000 wander worthy locations across North America and Europe. And so that's really our target. From a systems perspective, we actually built out a fleet of AI agents that went and found each one of these homes and then enriched it with owner contact information. So we know exactly who we're going after. And so that's sort of the focus right now is really a sales-driven model onboarding these homes onto the platform and then automating their operations with Wander OS and delivering that great experience to customers.

Talk about kind of looking back a little bit. I mostly want to spend time looking forward, but like navigating through the Zerp era, lessons learned, like that era allowed for a very different type of business model that you guys have evolved, but I would love to hear kind of the backstory.

Yeah, I mean, when Wander started, interest rates were pretty much zero. And so that allowed for us to have a very asset heavy model where we actually went out and bought those first few locations. on balance sheet, really with the idea of solving the Cold Start problem of the marketplace, do things that don't scale. And so as we grew, obviously, that had to transition. You had two crazy events happen at once. You obviously had sort of the massive rise of interest rates. But Wander actually, at the time, had a $100 million credit facility with Credit Suisse as a six-month-old startup, which was incredibly hard to put together. And then to have this systemically important bank explode as a CEO trying to scale the company was pretty wild.

Traumatic.

That was a pretty quick transition.

Talk about, I feel like one of the craziest things you can potentially do as an entrepreneur is go into a category where there is an active startup, even if they're scaled, that's still founder-led. That always seems dangerous because they're still somewhat agile, but obviously you've counter-positioned the company against Airbnb. But what decisions are you making? How are you thinking about maintaining differentiation and really competing as Chesky goes on a run building out different products and different strategies? it seems like there's more opportunity than ever to differentiate. But how do you think about it?

Yeah, I mean, first of all, like, I think Airbnb is a great, a great company, and Brian's like a incredible founder. So I have nothing, nothing negative to say there.

Yeah.

I think, I think for wander, you know, we, we do deliver a little bit of a different experience. So our net promoter score for Q1 is, you know, 85, which is, you know, phenomenally, phenomenally high. But, like, Yeah, like true, true customer love. And that doesn't happen by accident. I mean, literally, if anyone has a negative sentiment in the concierge chat when they're like talking with our support, that literally gets flagged across the entire company. If there's a stay that's below an eight out of 10, then they're going to get a call from our COO. And like, I see that feedback and we're going to be hyper aggressive on fixing it. And that's a across every single stay, every single home, every single customer. And so I think that that relentless customer focus is just a very different model than Airbnb. Airbnb is sort of that unmanaged marketplace versus wander. We truly do care about the quality of our inventory, the quality of your customer experience to the point where literally I will hop on the phone and deal with whatever the issue is to ensure that it gets there. I know that sounds obviously very unscalable, but I think that just purely from a cultural perspective, it forces systems and automations to be built. And in a time where I think that given everything that's happened in AI, you actually do have this opportunity to deliver hospitality and perfection at scale. And so that's really where our focus is.

Can you talk about advertising in this category? I was, we were talking to Keith Ruboy about whether or not Airbnb should have an advertising product because we've seen with Uber and is it Instacart where Fiji Simo was where she spun up advertising. It's not quite a marketplace business, but there's an element of that. But the take rate was low and so the advertising product was very meaningful at those companies. Keith Ruboy's take was that in the housing vacation stays market, it's less relevant because the take rate's a little higher. But do you agree with that? Or do you think that there is a future where just broadly the category is driven by advertising dollars in a meaningful way? Yeah.

When you go on to booking.com as an example, or even VRBO, you will see ads.

Sure. Promoted to get to the... Because if I have a house and I want it rented, I'm willing to sacrifice a little bit of my margin to try and rise to the top of the rankings, right?

You'll actually even see off-platform ads. So like very typical, like, you know, go buy this product, they're actually taking people off platform, which is pretty interesting. Like I'm sure that it's a revenue source. I mean, these platforms spend a ton of money on getting traffic from a performance marketing perspective, from internal marketing, SEO, etc.

Yeah.

And so it certainly makes sense to try and monetize a percentage of that traffic that's never going to end up converting to actually booking a home. But that being said, Keith is obviously correct and very smart that the take rate on vacation rentals is really high.

Sure.

For Wander, our average order value is about $5,400 and you're looking at an average take of about 30%. And so for us, that would have to be a lot of random ads to, you know, like make that up. And of course, the customer experience is not great. We're really trying to market users on that booking. But yeah, I mean, I think for a company like Airbnb, it would totally make sense, especially to the, you know, on the avenue you mentioned where hosts are just paying a little bit more to promote their house to the top of the feed. You know, they have a lot of inventory and sort of pulling yourself out of that is, you know, difficult for your mom pop Airbnb host.

Yeah, talk about disintermediation in the context of marketplaces and platforms. We saw the canonical example of the dog walker, which is basically just a lead gen company, because as soon as you find a good dog walker, you immediately disintermediate. And there's some things that those companies can do to prevent that. With some rentals, it's very much like, I'm going to be in this town for just this week. I need this place. I'm not going to bother disintermediating but if you fall in love with a place and you're going there every year, we've heard about people kind of trying to googgle the place and find a different.

Everynb has an issue where property management companies' list a home and then the person that's booking the home stay there and then just reach out to the property manager and do deal off platform whereas, Wannder, you guys are just full stack, right? So it's like you could even get you could look up the title or whatever and get to the owner and they'd be like, okay, if you want.

To book the house, like, it's still going through Wander. But yeah, yeah. How do you think about that? What does that tech stack look like to prevent that or help that?

Yeah, I mean, so I do think that it is like the core, the core risk. And I think that's even something that like has been talked about on their earnings calls is like direct booking websites. And there's ways for them to mitigate it. And you also have a ton of supply that isn't professionally managed. where the operator isn't going to have their own direct booking website, they're just going to list on Airbnb. And so I think they're actually positioned relatively fine. I think it's like a travel hack that not many people use. For Wander, I am a huge fan of having complete and total control over the business and the platform that I'm building. When I was a kid, my first little company, I was like 13, 14, we were hosting Minecraft servers and whatever else. And when Minecraft Minecraft got purchased by Microsoft. They rolled out a EULA, totally killed my little business, had to fire like four or five people. And so I learned about platform risk at like pretty, you know, pretty young age.

Never again. Wow.

Never again.

That's a great story.

And so, you know, for Wander, I knew I wanted it to be verticalized. I knew I wanted to have like my own booking engine. I knew I wanted to have my own property management software. I felt like that was like the most durable piece. And then you also have to ask yourself, as a space and a brand matures, that brand promise actually matters. And so if people look at Wander and associate it as a brand that says, hey, this is a quality stay, you don't get replaced, quote unquote. And so I think that's also a really important piece, is the underlying brand and that guarantee to the customer they're gonna have a good trip.

How do you think about taste in the context of what you're doing. Wander has always felt like a very, it's felt like a hospitality brand as much as it's felt like a technology company. Where did that come from? From anywhere? I mean, you were building coding tools historically, which, you know, I guess it's, you know, important to have good design in that category, but maybe when you started Coder, it wasn't even the case. So I'm curious where it came from besides people like Kyle crushing it.

Yeah.

My journey as a founder has been pretty fascinating. Obviously, my first venture-backed company I started when I was 17, 18, coder, enterprise developer tools. So radically different space than travel. However, I've always had a deep passion for design, and as a kid, I, you know, did high school online, traveled, you know, 200 plus days a year.

All over the world.

And you were, you were, you were race car. You were driving cars.

Yeah.

I don't really, I don't really talk about it, but, yeah, I used to, I used to race Formula 4.

No way.

And then, yeah, Formula, Formula Mazda.

It was funny. John, John and I got lunch in Malibu, like, a couple years ago at this point, and I was like, oh, do you want I knew he drove cars at a high level. I was like, do you want to go drive my Ferrari or whatever? And John gets behind it and he like, you know, normally when people like are like trying out a car, you know, like everybody's car, they're like taking it to him and he's like, you know, really experiencing the naturally aspirated V12.

That's amazing.

But I was confident. I was okay. I was confident that he was going to take care of it.

So you got the experience for it. That's awesome.

Yeah, it was a great time.

Great meal.

And so, yeah, I think with Wander, I'm candidly speaking, Wander is my soul, but as a company, everything needs to be high quality, the software needs to be on point. I also don't think people realize how much is truly automated with Wander. At the top, you have the booking platform, but underneath is literally this property management software that's running all of the vendor communication, coordination, payouts, preventative maintenance, task tracking, Wander doesn't actually employ any local property managers. That's all just through software, the underlying coordination of vendors, which I don't think that anyone fully realizes because of course we don't market it that way. You want it to feel like a magic trick. And so I think that's probably where you're seeing the design come from, is that if there's anything on the site that bothers us, the entire team is just obsessed over this principle of quality.

Last question for me and we'll let you go. Are experiences or local other services a true complement to vacation bookings and housing? Or is that a round peg in a square hole?

Yeah, the way that I look at it is that I think it's a feature of a platform. I don't think it's a platform.

Of itself.

And I think that you have this rare moment where you can effectively abstract the way that you connect to these service providers. So if you were to go back in time, let's look at like OpenTable as an example, they had to build out integrations with the restaurants. The restaurants had to use OpenTable to manage their reservations or whatever else so that you could provide this online platform. Now with what exists from a technology perspective, you can have an AI agent call a restaurant and make the reservation for you. And so you no longer need to force these types of integrations. And so the way that I look at it from a services perspective is you just end up with this agentic concierge that exists inside of your travel app that goes ahead and calls the local chef or the restaurant or whatever else. And so you don't really end up building necessarily direct integrations. You more build an abstraction layer and a curation layer on the experience Makes.

A lot of sense. I have one more question about SEO. SEO was really big in the early Airbnb story. Are you looking at any of these AI SEO tools? Do you think that it's important to show up in ChatGPT, for example? Are there any services or best practices that you think relate to AI SEO? Isn't it GEO according to Andreessen Horowitz?

I don't know what the acronym is, but it sounds like a good acronym. It's actually something that we have started focusing on pretty intensely. So the real key is sort of where these agents are referencing the materials and the facts that they're getting. And so what you end up with is you basically need a source of truth strategy, which is a really interesting phenomenon. Basically, it's like, how do you sort of become the system of record from a fact perspective or get the data onto a platform that is viewed as having the facts. Like, for example, chat GPT references Wikipedia a lot. Sure. And so, like, that, candidly speaking, it's a little bit harder to, like, quote unquote hack versus, like, traditional SEO. And there's definitely going to be, like, an entire push. And I actually think you're going to see a lot of value creation from platforms like Wikipedia come from the fact that they are viewed as, like, a source of Truth.

Very cool. Anything else? 40.

You said there's 300,000 homes that you guys have sort of soft circled as targets. I'm assuming you're gonna get all of them in the fullness of time. What do you want to do in the next, what do you want to do by 2030? Do you have a target?

Yeah, I mean, hopefully by 2030 we've accomplished that for sure. That's the, that's the pointing to the, yeah, pointing to the, I can't wait.

I can't wait for there to be like five homes left and you're just following around the owners in a helicopter being like, I gotcha, I gotcha, give us the keys.

We'll get it done. And before I jump, one thing I want to note is as a sponsor of the show, how incredible you guys are and how happy we are. And so to anyone who's watching this thinking about where to spend their ad dollars or what podcast to sponsor, Sir, I cannot encourage you more enough to work with these boys. They are incredible and the ROI is through the charts.

Thank you. That really means a lot. It's been really fun.

You guys bet early. You're one of our very first ones and we will never forget it.

Yeah. I think my favorite thing is that people might think that we ran the song by you before doing it live. We did it live. We didn't get any pushback and I think it's all for the Better if there's less oversight.

So we've been having fun. It's funny.

Did we create, did we create?

We created singing. We created jingles. We created the jingle.

We created the jingle from first principles. We created the jingle. No, we literally, they didn't send us any copy. We didn't ask for any copy.

We didn't ask, like, how do you do an ad read for your company?

We just went to your website and just sang the first tagline on there. If it had said anything else, we would have sung that.

It's so drilled into my brain now that I just assume that you guys were singing forever.

No, no, no.

We just went to wander.com and started singing fine your happy place.

Well, we should take you out.

I want to make, I want to make like a rate, we should, we should make like a radio.

Absolutely.

Hey, this is John and Jordy.

Anyway, thank you so much for coming on the show. This is fantastic.

I'm super excited for you and the team. And John and I are like basing our summer plans off of wander vacation, wander vacation.

So for sure.

Thank you. Congratulations.

We'll talk to you bye. Cheers.

Thank you guys so much.

Later, John.

One last news item I want to hit before we get out of here. We were talking about the poly market on Elon Musk out as Tesla CEO in 2025. It is lower than ever. It was around 20% in March, crashed down to 18-15%, was recently sitting around 13%, and now is down at 9%. So the news about Elon leaving the US government has been a bull case for him staying as Tesla CEO, which makes sense because he has a lot of work to do, a lot of opportunity between self-driving and humanoid robots. Who better to run that company than Elon?

And another one, I've been tracking Circle IPO in 2025 is up to 94% chance. It drops to 47% chance. on May 21st, so about a week ago, and it has just rocketed up to $95. And I expect we'll see some news on that front.

Yeah, I mean the other markets, since we're in poly market mode, these are fun. I love doing these. So there's of course our market on how much the iPhone 17 will cost. Over $1,000 is a 13% chance, over $1,500 $2,000, 2% chance. Over $2,000 is only a 2% chance. I think Tim Cook's gonna get it done. Keep iPhones cheap. The other interesting thing is which company has the best AI model at the end of May? Google's running away with it at 96.5%.

Yeah, that's May.

If you go out farther... If you go out farther to the end of the year, Google's at 40%. OpenAI is at 22%, XAI is at 23%, Anthropic's at 7%. And so, a little bit closer of a horse race towards the end of the year. What I want is I want benchmarks and evals for video models now because VO3 seems to be just completely running away with the game. But we haven't seen what the next iteration of Sora looks like. OpenAI clearly cares about that. They've been building a product, an page, via. In fact, the first consumer product from OpenAI was not a chat model. It was DALL-E. DALL-E 2 was the first product they released. And then ChatGPT came out. And so it's obviously in their DNA, they're not just gonna let that-- they're not just gonna let Google run away with it. There's so much more that you can do in video. We see this with Runway, we see this with a bunch of other products in the space. It'll be interesting to track that, but we don't really have a great benchmark Mark or eval for that. So we'll have to get one and then we'll have to put it on PolyMark it. Anyway, we will see you tomorrow. It's gonna be a light show.

Aurora, we launched a new product today, a filtered shower head. Oh, if you go there, let's see.

Big news for Aurora, filtering your shower head, cleaning up the water you're bathing in.

Yeah, so we, this is a product that was in the works for a couple years at at this point, we were pretty strategic about when the right time would be to roll it out and made the best shower filter in the game on a bunch of different metrics, flow rate, filtration, ergonomics, and yeah, go check it out. I made a code or I had Brian, CEO, make a code, TBPN, a little discount, and love it. Yeah, excited to see how this so.

We will be back tomorrow, a little bit of an earlier show. I'm doing some traveling and it'll be no guests, just me and Jordi chopping up the timeline, taking a throwback episode. I think these are some of our best.

It's gonna be fantastic.

I can't believe it. So it'll probably be an hour, hour and a half, around 10 a.m. If you're looking to tune in, we will of course let everyone know and it'll be in your RSS feeds. And if you're listening to the RSS.

Feed, please go leave us five stars on Apple Podcasts or Spotify. Do it. Ben's pointing a jail blaster at us right now.

Thank you for watching.

Take care, guys.

We'll see you tomorrow.