Elon Musk Is Leaving Washington, Meta Partners With Anduril, Kim Jong Un's "Side Launch" Goes Sideways | Peter Rahal, John Andrew Entwistle, Ashlee Vance, Chase Lochmiller, Matan Grinberg, Jonny Dyer, David Hsu, Sushanth Raman, Rob Toews

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Today is Thursday, May 29, 2025. We are live from the TVPN Ultra Dome. That's right, the temple of technology, the fortress of finance, the capital of capital. But now it's also the TBP and Ultra dome.

You heard it here.

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 out of 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 LLMs.

GPT moment for Superdomes.

Yeah, exactly, exactly. The Ultra Dome comes out and you're like, well, now maybe we have to build an ultra dome. Maybe we got to compete. How are we going to do that? So we'll go dome for dome with.

The best of them.

We will.

We will.

Anyway, we got a bunch of news for you. We're going to take you through about 30 minutes of recapping the news, and then we got a stacked lineup. Ashley Vance is coming on. Chase Locke Miller from Crusoe Energy is coming on. We're talking to folks about putting data centers in space. We're talking about. 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.

Space data centers. I'm really excited to talk to Peter.

Rahal from David Bob King. He's making a fortune.

He's back in the bar game. And I think the growth, I would say.

What was the number?

145.

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

That's insane. And now, 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 are. They do cost a lot, but that's still very impress.

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 in revenue that quickly seemingly has product market fit from coast to coast. Right. They have, you know, big presence, you know, in the typical wellnessy cities, but then also in, like, middle of nowhere.

Yeah, yeah. It's crazy. It's crazy. These second acts from These founders, they should work, but sometimes they don't. But he clearly hit, knocked it out of the park with this, so we're gonna be talking to him.

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 dc, 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, there's a lot at stake at SpaceX. We're seeing the, the ninth launch. Interestingly, the, the latest Star 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 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 spaceship right now.

Yeah.

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 that 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 space. 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 because it'd.

Be over the weekend when the site.

Was down recently because it was, you know, it's embarrassing to go down in a big way.

Yeah.

And I'm sure that the culture there just doesn't tolerate no, you know, downtime.

Although held up really nicely for us yesterday with crypto day.

Yes.

Massive day on the Internet.

And the interesting thing is Tesla, the Tesla stock price has been pricing in Elon didn't even get to Tesla Elon leaving Washington for a while. It's up 22% over the past month.

Because 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 poly market on Tesla new CEO? I want to see that and all take you through some of the news out of horrendously probably now that he's not working for the government anymore.

Yeah, a 1% chance.

Yep.

As of today. So.

So when is, 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 offboarding 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.

And so they also cut this off. Yeah, 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, which I think is important. He's not just saying, see ya, he's saying, hey, I actually believe in sort of.

I'm trying to reflect on like 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? Like, seems like they kind of did some work together. They like, worked on a project together. They did a group project.

School project.

School project. And like, they 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. Yeah, Cybertruck or Model S. Okay. You know, Trump got the red Model.

Oh, he did that? 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.

I'm gonna revolutionize this.

I'm gonna revolutionize hoa. There's so many obvious things that we could do to improve the operations of the neighborhood. Realized very quickly that there were some major, you know, I think you weren't chaotic enough.

You should have launched like an HOA coin immediately. Yeah, really, really, really shook things.

Shook things. Nobody's building at the of hoas and crypto.

No, it is white space, long leg. Get on. 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 One, wrote Norm Eisen, a co counsel for the House Judiciary Committee during Trump's first.

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.

So taking a victory lap, normal. It's like saying you hired a contractor.

But also, I don't know, I feel like that, that 130 day thing, like, we're kind of hearing about that for the first time now. Like, that wasn't the way it was messaged beforehand. It was definitely message. Like, Elon's going to be part of this team for four years. Like, like expect Doge to go on a generational run here and do a lot of it was not like, oh, Elon's, hey, just to set you, 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. This is the first I've heard of the 130 day thing. So it feels a little bit of.

Like, heard of that from another guest that we got on the show who is a special government employee and he had messaged it to me earlier, like, oh, it's just a sprint. It's a sprint.

Okay. And 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 US 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 move. It 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.

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?

Breakfast.

You're going to get somewhere in that. Musk promised 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 inauguration. 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. Right. It doesn't crack the budget and so it's not.

Well, the new dramatic bill, you know, increases it dramatically.

So it's not, it's probably like 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.

Stay, keep grinding.

It would completely change entitlements if, 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. Metafired Palmer Luckey. 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 Luckey and Mark Zuckerberg there. Let's hear it for getting the band back Together.

Love it.

Ashlee Vance has an exclusive interview with Palmer Lucky. 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 Ives contract for. For Microsoft, but the contract's going to get recompeted. And at a certain point, why wouldn't Meta compete against Anduril for this?

They.

They have a great team. They have a lot of the hardware. They could actually deliver this. And, you know, the contract is up there, like, go get it. Well, 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. Back to the couch with the red solo cup, drinking a beer. The first Zuck interview.

It's great technology, brother.

It's fantastic. But, yeah, exciting, 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 of 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, like, this individual is layered, and you don't want to just, like, immediately go over the top of, like, 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. It's not like he technically reported to Zuck. And so anyway, they've clearly rebuilt the relationship. Very exciting. And there's been. There's been some progress, even just in public, in public discussions on X between Boz and. 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, Anduril 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 sighting 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, it 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 Andurl's autonomy software.

Soldier on the battlefield. Llama, what do you got for me?

Llama? Yeah, yeah, it really is turning into.

Call of Duty GPT. But it's like, yeah, yeah. Hey Llama, what should I be paying attention to right now?

Really dark. Llama, I'm bleeding out. Send the medevac. How do I tourniquet myself?

Rough.

But I mean, you know, like, like you have to put, you have to put these pieces together. But Llama is a silly, silly name. Well, I love it.

I wouldn't be surprised if they say Eagle or.

Yeah, yeah, yeah, yeah. They might need to, 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 author 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.

Important.

Yep, yep.

Cultural victory.

Yeah, yeah. The, 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, 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 in on pretty much every military base that there's Windows Mach means. And so that, that legacy there was never, it was kind of like even pre, 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, the HoloLens project was, was very cool and IVAS was, 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 warfighter. Even if they were able to put Excel in the hands of the warfighter.

Yeah. What Anduril 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, that's great. 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 procurement 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 US 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 Anduril became the lead vendor in February after Microsoft failed to deliver a functional VR headset. And we'll set the collaboration on the headsets, which the companies have already mostly funded themselves, is going forward. Irrespective of winning the army contract, Anduril is betting other parts of the military will also be buyers. Yeah, that makes a lot of sense. Why would 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. 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.

So good.

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, it was very, very rough. It was just like, that's not. That's literally anti democratic. The whole point of democracy is you can vote for whoever you want. Like 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 is 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, watering fridge groups have come around and are moving forward. So good 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 Chinatalk 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, 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 the 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 like, America has national interests, has different security interests, also has competitive dynamics around brain drain. And 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 this, these policies should go around the top research universities. When you hear, when you talk to the 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, like the next big AI breakthrough probably just going to come from Google. They won't be able to productize it fast enough, and we'll just roll it out into some B2B SaaS. 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, is affecting that. There's 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.

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 US behind India. In the 2023-2024 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 was 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, what is it? 270,000, 270,000. If 270,000 Chinese citizens are coming to American universities, should 270,000Americans 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. Just like 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, Yeah, 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 can't. It had to have been less than 50. 50 total. Yeah, at least that. That I was aware of. It was pretty easy to, you know.

At the same time, I wonder how much of a, how much of a shot across the bow, how painful is this to the Chinese government? Because if you, if you remember the, the whole story of what is it? No, no, no, no, no, no. Russia with the Magnitsky act, it banned adoption from Russia to America. And that was like extremely painful for some reason. I don't exactly know why that was such a hot button issue, but point of leverage against, 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? Like, does this go against their plan in like, a very meaningful way? Is this something that will, will be another, another poker chip on the trade negotiations around tariffs or around the, the flow of fentanyl or something like that? Could this just be an opening gambit that then gets negotiated down and merely just putting this, 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, this is great for us. Please, please send, send all the, all of the students, all the smart people back. Like, 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.

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.

Anyway, guess how many American students studied in China in 2024?

5,000.

Guess again.

10,000.

Guess again.

1,800. 800.

So I was, 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 is nothing. Yeah, I mean, we have like millions of college students in America. Right. You would think that 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 Gu. That's brutal.

Yeah.

After. After that soundboard. You can never go to Pyongyang.

Is not going to be happy to see that. We're not going to 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 fact. 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. 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 just too good. The 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 anticipation. But the big moment of celebration turned into calamity. The 5000 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, like, they didn't send us video of like they didn't broadcast this because they would only broadcast it if it's like successful. So we just have like satellite photos of just. It's just like getting destroyed slowly, slowly. Very, very rough, brutal.

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

And 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, like 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, not you, not, not you go to jail. What has become clear in the aftermath is how an unconventional choice of launch method, Kim's rush timetable, and a top heavy warship overladen with weapons systems was a recipe for disaster. They just keep being like, yeah, just like 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. Said a retired marine colonel that 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 Consian.

Yeah. How bad is this?

I haven't seen one this bad.

This bad. It was a 470 foot long warship. Kim's second destroyer had 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. Nice sweatshirt. Looking good.

Thank you. Hey, it's a sample, too.

Congratulations on your second announcement of the week.

Yep.

This is the first real one. Sorry, sorry that. Sorry that you got leaked. But very excited for you. Excited to have you on the show to break it all down.

Yeah. What we were talking about, 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 Effigy.

And then.

Yeah, our valuations. 7, 7 25.

Wow.

Forecast this year is 140. So I think those. Those numbers and, you know, I think, you know, it's like in. 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 is this?

What other. What other brands have achieved that level of revenue within a year of launch?

There's two Feastables.

Feastables and Prime.

Prime.

Yeah.

Because just massive distribution cannons and really leveraging essentially $100 million worth of free marketing on day one.

Right?

Yeah.

So what's the secret for you here?

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. Like the expectations that are 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 hear people say, like, oh, I'm just not a protein bar person.

Sure, sure, sure, sure. Yeah, that makes sense. Those are people.

If you ask them, like, why not? It's fundamentally taste.

I want to kind of 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 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, is that critical? Or do you think if 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.

That's true.

Buy my product.

You know, I mean, it is very different than Mr. Beast and prime where, you know, you have like major influencers driving this. Like, like it is more product led in that sense.

Yeah.

And I would say, like my credibility or track record is like a lubricant facilitate things.

Yeah.

But the repeat and it's all product driven.

Yeah, 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, you know, 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. It was like, this is like magic. Like technology should feel. Got close with them, became 90% of their volume. So we were basically, you know, 90% of the. Yeah, 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, without us being together. And it 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 like 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, Wagovi transition, even GLP1s, they were able to kind of eat at the edges. Now Eli Lilly is taking share from Novo and it feels like if it can't work in GLP1s, like how can this possibly hold in a protein supply chain? Right. Like you're going to get someone who spins something up that's like one molecule different or something like that. Is that, is that a risk or did you dig into that at that level of depth?

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

Sure.

And you know, it's like, sure, someone could go try it, but we'll just 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, exactly. Roi's not there.

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, you know, Eli Lilly, like, if they spend a bunch of money to figure out how to, you know, alter the GLP1 to get a drug that works like, well, then it's just a matter of doctors prescribing it. Right. And it's like, and it gets, and.

Like in cpg, you kind of have like two years Runway before someone copies you.

Yep.

Now we have like structurally nine years.

Yep.

And I think by that time it's kind of too late.

Yep, yep, yep. I mean, you already see that with the 140 revenue, like, like as that gets bigger, it's just going to be ubiquitous and you own all the shelf space. So even if there is 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.

You know, that would be disappointing.

What was our X bar? Roughly like what's your personal high water mark?

2.

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, I do fantasize about being a public company.

Let's go.

I love it.

This is what my dreams are. We'll have you back after your public company and you're just gonna be like, it's such a headache. It's terrible. I can't say anything. I'm in a quiet period. I can't come on tvpf. And it's the worst.

Yeah.

I might be the irreverent. Yeah.

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 and 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 it doesn't sound like you want to do like a studio.

No.

Only studio analogy would be like we're not gonna do M and A. We're gonna build them. Me and my team, we've demonstrated we can go from scratch. Yeah. So we would just build them. It would be a decentralized model. So like different orgs. So David's the master. David's Mars. And then David Protein is the operating business. Apogee will be its own subsidiary and then we'll create other brands and then they just have to be decentralized organisms like Orgs. Because you, you know, like David in his life cycle is very different than a newborn baby. And so like we need to design the order for agility and speed and so, so that's what we're designing for.

And how much do you view yourself as a 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.

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 restrain from the T word. But yeah, we want to keep making really valuable products. Like that's just our focus. And obviously technology is really the best way to get there.

Have you mapped technology?

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

Yeah, the last deal they did was like Windsurf, Right. Or like the last big outcome for that wildly different company. Have you, 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 and A. But if you, if you think really, really far into like what it takes to create $1001-000000-00000 outcome in consumer packaged goods. Yeah, no one's even come close. Like we all cite like Red Bull is a great outcome, sells it. But these are all like single things and very niche categories that are big ca, 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, to just compound and compound and compound and create this like hundred million, dollar, 100 billion 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. Like, so like David, I use the analogy of like, brands are just human beings. They have fathers, they have, they have DNA, they have behaviors, beliefs, they, you know, 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 our calories coming from protein. So we look at David, you know, it's like the most protein, least amount of calories. That Tam is probably 1.5 billion in revenue in the U.S. so you really need multiple, you need like a house of brands to go after very different parts of the population that's one and then international. 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, 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.

So nutrition science is really, to date, not in science.

Yeah.

And so it's really been. It's a really emotional conversation and not a intellectual conversation. So that's the first place. And it is complicated and our society is really confused around it. And so under the confusion, in 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.

So.

And it's like the interesting thing with 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 up and food, you know.

Yeah.

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 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 no sense.

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. There's a bunch more questions I have, but congratulations on the milestone. Just getting started 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 writing, underwriting that to small chance of $100 billion for sure. That's why they're. 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 interviewed Palmer. Lucky you're hearing about it here first, folks.

You're cooking.

You're cooking. It was good.

Good morning.

It's.

Yeah, Palmer came.

I think he.

Well, he came in yesterday, I think straight from. There's this photo we posted of him and Zuck 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 of it was. How much were you focused on, like the technical side of the deal between Anduril 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 hours and from my memory, you know, 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, the technology and the, The Wall Street Journal story didn't have that much either. And Palmer, he went into some, some detail on our podcast about, about the tech and then, yeah, he got into the backstory. I mean, this is crazy. This. If I've been following Palmer pretty close for the last couple years, I never would have imagined that this would have been possible given the, the intense, the depth of this like nine year war that the. Those he and Meta have had. So, yeah, I did not fully see this coming.

Is it accurate to describe it as a war between Zuck and Palmer or war between Palmer and Meta?

I think it was like more Palmer and Meta. You know, 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 and about Hillary Clinton and became a known Republican in public and was fired from Facebook. 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.

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, like, 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, like, almost definitely. I think Palmer's probably still at Meta.

Making, working on VR, I don't think 100%.

I mean, you know.

Yeah, didn't Jan Kum from WhatsApp stick. Stick around for a long time. And obviously, like, the Instagram guys had kind of a rough go and they're upset about it now, but, like, they. I think they reported directly and, like, built that for a long time. It was just odd that, like, VR was so important in Meta, that Reality Labs, huge investment, and yet Palmer Luckey was not. He should have been on the board. He should have been added, really into the inner circle. It's been a while since I read early Blake's 20s. Who cares? Zuck was 19 when he started the company or whatever. 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. But here they are taking photos as friends again.

Have you gotten a demo yet, any of the Anduril hardware yet?

I haven't gotten on this headset. No. I mean, this has been. And I've been down at Andrew doing some reporting, and Palmer's always like, because this, this is like an extension of this IVAs deal that. That. That Andrew took over from Microsoft.

So I've been down there.

Palmer's like, oh, my secret lab is over to the side.

That's.

That's where these guys are working. I mean, people should know. It's 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, and 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 sort of tech end of this. He just wants to make a better helmet for soldiers, too. And I know he's been spending a lot of time on all the materials and things like that.

Yeah. Have you been tracking any of the other developments at Meta, 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 4 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 for the. 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. On what Meta's been doing in VR AI lately.

I mean, 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 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 Jony I've are doing, you know, we're clearly, we're lurching every. 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 just, 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.

So that is fair. That is fair. I just, I still feel like we're.

Everybody wants a new toy. Give us a new toy.

Somebody will figure this out.

I am confident I'm old enough to remember, like, you know, when I first started reporting. Yeah, it was like exciting. People had different operating systems, they had different takes on computers all the time, you know, and, 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.

We can only refine the bezel so much.

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. I mean.

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

Yeah, I mean, it was half like complete glaze 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. Kind of a nuanced take. But, yeah, they did. They did some people dirty. They put our quotes. They put us in quotes.

They put us in quotes.

But this will be the last time TVPN ever appears in quotes and the last time that Ashley Vance has ever quoted in the information without mentioning Core memory dot com. 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. Haven't watched that. But Smartbox also haven't watched that. Can you cop it to something?

Reinventing the wheel.

We're reinventing the wheel.

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

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. Like, give me the. 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. 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. And we 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 8 to 20 something minute episodes that are, you know, dives into different inventors and scientists and startups. And then so anyway, please go.

You're kind of telling the story of these like various brotopias that are existing all Silicon Valley.

You know, unlike some people that only brotopia. We, we do do many female scientists but you know 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 weeks and so part of that was to your other question. You know, we're working on a movie about brain computer interfaces and, and Neuralink is at the. And so we're following this journey for, for many months, years maybe. And then, and then we filmed a couple of episodes with some Swiss companies.

Yeah. How do you think about what. Oh sorry journey.

What's. What's happening in Switzerland?

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

Switzerland is my second favorite country in the world.

It's like, you know, if you're going to go with the well made museum version of Europe, it's. 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, and just like a incredible education system and they have finance stuff. But we went robotics. You know, I went to a couple university robotics labs. I the.

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 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.

We.

You will see it coming up in a future episode. We had a, a robotic swan. Robots, robot swans dancing at a lake, shooting water and lights and we were up till two in the morning filming that. So they actually have putting a gun.

On them yet they actually have a fantastic robotics would be to put a.

Gun on the robot swan.

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 Philippe Audemars piguet Vacheron Constantin. It's like this machine. It's basically robotics, but just to tell the time and so, so I can imagine an Ashley Vance style deep dive on those companies being really, really good. It's hard tech.

I would, 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, they, the Swiss government really backs EPFL and eth, these two universities kind of on a level that I don't know you, you. 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 slanging checks? Is the. Is are they ready for American industrial venture capital?

Should they go from spending just the entire summer there to spending some time.

During the summer 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.

It's. I mean I try and you know, I don't want to over generalize and crap I an entire country but you know, I do think, I do think there's opportunities there, but then sometimes you walk through the European startups and, and the energy level is, is not the same as you would, you'd find in.

The US they're not sleeping on the floor of the factory over there.

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

Yeah, yeah. We're about to talk to 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 that. You guys have precise. So I mean 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 though wasn't it MGX setting up a data center in France?

Yeah, yeah. I mean the, the overall Stargate project is available to other countries 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.

So from what I like, 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. To pony up at the we would like to participate level.

Interesting.

Is it going to be like luxury AI.

Lvmh, GPT.

Like branded tokens, artisanal tokens.

That is what they do best. Anyway, this has been fantastic. Thanks so much. We'll talk to you soon.

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.

Bye.

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?

In Abilene?

It might be. I don't know, it might be in San Francisco. Oh, we don't have them. Oh, 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 we're 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 Lockmiller 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 he builds. We can hear you now.

Thank you. He does.

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 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.

Let's go. We love to see 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? Like, you know, 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, you know, behind, you know, a long time ago. That was more like kind of the earlier stage stuff. But yeah, so, you know, certainly, certainly different. And I think with Blue Owl, they've been a great partner, you know, one of the leading real estate, you know, 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. So, and then obviously very, very deep, deep pocketed capital providers to really help us, you know, make these projects happen at really significant scale. Now what's different is like this is not an investment in Crusoe, you know, equity.

Right.

This is a, this is a partnership with Blue Owl for this specific project.

Got it.

And just, you know, Crusoe has a business model that is, you know, not asset Light is very capex intensive which requires 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 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 some of sort, 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.

The, there is construction financing that's being provided by JP Morgan. So on the expansion, it's a little over 7 billion that's been 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, with, with our customer, which is a long term lease agreement. You know, being able to partner with a large scale investment grade customer is really what helps unlock a lot of the capital here. You know, when, when people are talking about these very, very large quantums of capital, credit is like the magic unlocked. Right. So, so, so when you have, have big long term offtake 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 money as both a project developer as well as we are a partner with Blue Owl in the ownership of the entity.

Makes sense.

Our customer, you know, it's, it's, it's basically like we're the landlord, right. We have a customer that is paying us a, 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, 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 life cycle of that energy production plan.

Yeah. So so much of the bottleneck of scaling AI has boiled down to just, 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 conferences 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.

The backbone of our industry.

Yeah, 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 5G 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.

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, you know, there was 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. Right. They would frequently get curtailed, which means, like, 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 price. So their issue was actually just not enough demand for power. So it was a good natural fit between AI factories and, you know, low cost, clean, abundant energy. You know, it's a pretty awesome, you know, 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 like crude oil or fuel or like just gasoline? Does that power AWS at all? Like, I'm just curious about that mix.

Yeah, no, there is actually, you know, especially during moments of peak demand, if you have peak demand at night, diesel generators, 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.

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, very inexpensive. And then contrast, contrast 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.

I mean, Abilene is one of the windiest places in the United States. Sort of this corridor that just gets a tremendous amount of wind. And that's why a lot of renewable energy developers built there.

Sure.

You know, I think it's actually important to understand this production tax credit. So the way this works is that, 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'll often see power prices go negative because their actual realized price is 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. Now I have to shut off, which means I 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's 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, you know, we were working with like, you know, the MIT Department of Physics doing, you know, early simulations of the big bang, you know, CCL department at mit. Like, you know, 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. So a lot of people are like, wow, this was a great pivot. And I 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 bottom bottleneck. 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 intelligent systems at scale. And so we did a lot of early investment in terms of making the platform work with Crusoe Cloud 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 Jevons 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 mystery.

It's very pro China media spin like very early on.

I think anybody, everybody was like, wait, 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 the cage.

They powered with a bicycle.

Yeah, yeah, totally. Yeah, there's a couple, 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 bigger, larger scale clusters and, 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 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 are 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, 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 em like two guys in a pickup truck where 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 power, you know, just like 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. I'm gonna just call up Sundar. I got a contract.

No problem.

Yeah, I got, I got some 3090s in here. I got a couple 1080 TI's right.

Over there, a couple propane tanks.

Barbecuing GPUs.

I think the thing is that these projects, they're so big that the capital investment to make them happen is so massive. And you're seeing people speculatively build smaller scale stuff.

Stuff.

But the really big stuff, that's whatever couple hundred megawatts or gigawatt plus, you really need credit to make it happen. 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 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.

Well, yeah, at the $20 million scale, you can get 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, 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. Would 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, you know, the bottlenecks move around. You know, the bottlenecks for AI infrastructure builds kind of move around. You know, you sort of had this moment of, of infinite demand for H1 hundreds when they first launched. And I think Elon famously said that it was way easier to acquire illegal drugs than get an H100. So it's rapidly shifted into energy and data center capacity. And what does it mean to actually build that stuff out? High voltage transformers are definitely a big bottleneck. A lot of that capacity does get built in China. You know, they're. 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. Switchgear can be like a major long lead time item that Crusoe actually started manufacturing in house. So we have factories in Tulsa, Oklahoma, right outside of Denver, Colorado.

When you say switchgear, is that like network switches, like Ethernet routing or something else?

Sorry. It's electrical switch gear. This is basically like your electrical room that has all of the 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, your breaker box in your house.

Got it.

You trip a breaker.

Yep.

You got to go down and you got to go flip the switch. It's like that at, you know, a gigawatt scale data center, something.

Yeah, that makes sense.

But switchgear is definitely a bottleneck. Chillers is another big thing. I think an interesting trend in data centers right now is with the introduction of the GB200, the new Nvidia chip, basically you're seeing this massive transition to liquid cooled computing at significant scale. So. Well, 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, basically move that heat off the chip from a traditional aluminum heatsink or something that's like so big that, you know.

Yeah.

Just.

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 these data centers. And that didn't quite feel correct. So I'm not going to call them out.

Is that a bottleneck?

No, it's not. It depends on how you design it. So we've tried to. I think water can be a very sensitive topic depending on the communities that you're engaged in. And Crusoe's always tried to be a phenomenal partner to 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.

Yeah.

So that means basically you have cold water that flows into the rack and it flows over the chips over. Over this, you know, through this, through 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. From the rack rack. That hot water then goes out to a heat exchanger that's a. 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, like, 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 that. And then you basically have cold water from that that then feeds right back into the system.

System.

So 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.

Yeah, yeah, yeah, yeah.

This, 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.

You know, 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, which is not.

Yeah. At that kind of scale, even a.

Mile architecture is that are open loop.

Where basically you have a fresh water supply and that is, you know, you are consuming a lot 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 you fill it one time, then you're done.

Let's hear for closed loops.

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

Yeah, I mean, we're trying. We have a couple other projects that are underway that hopefully we'll be able to talk about more soon. But similar scale or bigger. It's kind of like what we're seeing. So a lot of demand unfolding within the ecosystem. And I think we try to be thoughtful about our partners. 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 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.

Great to have you.

Take care.

Before our next guest, let me tell you about ramp. Ramp is ramp.com Time is money. Say both easy to use corporate cards.

Almost like tears earlier. Tears of joy.

Yes.

Using Ramp Travel.

It is the most amazing product. I know this is such a shill that.

No, it's not a shill. It was off air.

It's an incredible experience.

It's an incredible experience. It is a beautiful thing that I can get IMO gold medalists to make me my travel business Travel app.

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 your 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 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 expensive side, just the Experience of actually booking is so much easier. It's like, I mean, I wish we.

Had it on camera because it was a really special moment.

Leaked.

Leaked.

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? 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, are full end to end software development lifecycle agents built for the enterprise, big enterprise, not just, 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, it's been, it's been fun.

Talk to me about the evolution of AI agents and coding agents. I remember there was a company a couple years ago that was training their own foundation model. Then the regime seemed to seem 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, some reasoning that we're doing now. It feels like a lot of the coding agent companies are just kind of like we're, we're rappers but we're still printing money and rappers and unnecessary pejorative. It's actually the best way to build this business and it's helping us. So. So where do you fall and what is your take on the different paradigms?

I just got here. I gotta compliment Matan.

I know, I know, I know.

Looking fantastic.

It looks great.

You know. Thank you for when you come to the temple. When you come to the temple you must be dressed appropriately.

Yes, yes, thank you anyways.

But yeah, 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. 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 quite a few who've raised to the tune of like half a billion dollars to train their own models. And I think something that, that a lot of people were saying at the time, or maybe whispering because they didn'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, you know, fine tune their way to having the best models. As you see it in, in general, with code, it's like alternating between OpenAI, Anthropic, Google XAI in terms of the number one spot in code. And so, 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 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 going to get Reddit answers and you're also going to get a pretty good model that can code. And so unless OpenAI says let's not train it on code, it's just you're going to lose to them because they're putting the most, you know, energy, the most cycles into training the big model. And so you just get that as a byproduct.

Yeah, that's, 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 like 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.

Yep.

So exactly right there.

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

Yeah. How have you, how have you guys navigated just partnerships with the labs in general where it's your kind of frenemies? You know, it's like, hey, we can work together.

This is a good question.

At some point somebody's going to try to kill the Other one?

Yeah, no this, this is, 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 0 to 1 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.

Yeah, you remember with pre chatgpt 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 GPT because all that revenue, you know, dried up, went away.

As, 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 a lot of people are talking about these record breaking runs to large arrs and what's going to be coming soon is some record breaking churn for a lot of this 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 0 to 1 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 ChatGPT 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 co pilots 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 O3 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 is just skyrocketing right now in that product. Then there's Kodaks, they also have Windsurf now. And so you can imagine a few different bites of the apple there. Are they indexing the market or are these distinct different markets? Will there be one power law outcome in the coding space in terms of paradigm?

Yeah, great question. I think the first order bifurcation that'll happen is between the non technical audience and technical audience. So like for non technical, being able to spin up apps on the fly is like 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 like going too deep into the code itself. They'll just like, I want a to do list app.

Make it for me.

Okay, great. Y for the technical user, I think that's where it gets a lot more interesting basically. And maybe, maybe this is just a quick like kind of philosophy that we have at factory. Every transformation shift has a very clear behavior change associated with it.

Right?

So like Internet had people getting most of their information from like tv, newspapers, books to then like going on this console on their desk and like, you know, getting all their information there. Mobile had people, you know, walking around like heads up to now, like you know, walking around on TikTok subway servers all the time.

Right.

These are very visceral, obvious behavior. 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 product, the most used AI products right now, there is no new behavior like ChatGPT perplexity. That's just Google with better results. 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, 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, 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 you 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, what, like, 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.

Because money is money and you know, that seems to be the meta right now. But I imagine that you're thinking about this or at least like messing when.

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

And is there, is there like a little bit of a price war here? Because you imagine that you come into an enterprise and you say, hey, this would cost you so much to do with like Accenture. And we're going to do this, this replatforming of your COBOL 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 like 50% margin. But then your competitor comes in and says like, well, we'll do it for 7 million, we'll, we'll do it for 6 million, we'll do it for 5 million. And so there's, there, 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 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 so helping them.

Droids indeed.

Look, I love it, 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, 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. Or we 20% more lines of code. It's just so amorphous and so not tied to reality, 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 wire. Does that ring a bell?

Yes, it does. So this is, this is in like 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 phoned it in.

You want to kind of take the easy path in school.

Yeah, yeah, exactly.

Yeah.

You know, just some fun string theory, which to be fair, it is really fun, fun and beautiful. But decided it wasn't a path for me in particular because, you know, to, 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, Sean McGuire, because he also used to be a string theorist. And he ended up, you know, 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, 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. Not a thumbs up, let's go.

Or you should join.

You should join X. Because Elon just took over and you'd have to be a badass to voluntarily Go there there or you should start a company. And so that was eight days later dropped out of the PhD and started factory.

So.

Well, congratulations.

Very cool.

And yeah, thanks for stopping by. This was fantastic.

And thank you for giving agents at Cooler name. I love droids. We got to get ourselves some droids.

Yeah, we got to get you guys some droids. Thank you guys.

Great jamming.

Have a good one.

Matan.

Speaking of automation, let's tell you about Vanta Automate Compliance. Manage Risk, Prove Trust, Continue continuously. Vanta's trust management platform takes the manual work out of your security and compliance process and replaces it with continuous automation whether you're pursuing your first framework or managing a complex program. And next up we have Johnny from Muonspace. We're talking about data centers with Chase Locke Miller 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 you to let 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 in 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, I, 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 4. 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 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 decade 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 obviously often had to have a lot of deep expertise in everything from, you know, ground stations to, 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 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 about be about, you know, a data company being able to go build a data business without having to deal with all the complexity on the, the space, the ground, the operations, the hardware, the integration side. And that's really what we're trying to solve.

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, you know, 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.

On.

What do you think the key milestones are to get us to a future where we're really doing, you know, mass manufacturing big, you know, mega scale projects in space.

Yeah.

Well, let me, let me start off. I mean, I think you guys are hitting on the right metric, right? 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 icbn.

So I mean, they Were 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 have videos on YouTube, 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.

Wow.

Yeah.

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 going to dramatically change the way you think about feasibility of some of these things. Like, 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 where you, you're 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 sync 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'd think about it.

It's interesting. It feels like SpaceX has commoditized launch and is kind of the power law winner there. Obviously there's other companies, companies that are competing but they've, 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, 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 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 an answer I want to answer. So I'll do both.

Yeah.

On the supply chain side, you know, I think there's a lot of, 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, is solved. I think Endurosat obviously is, is doing very similar things in that way. Some of the places where we really see that, 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, Endurosats, 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 it has a money maker. 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 beam 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, 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, it 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 answer that you didn't ask is I think the other big bottleneck outside of hardware is still software. So like, you know, we we spent, there's a lot of talk right now on hardware, hardware 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 in 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, the hardware integration is still the hardest part. It's really making these large complex systems work 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, 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 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, their blade design for their rack mounts and there's a lot of other, you know, 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 in the SpaceX factories starbase. Are you, 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 get 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, 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, building rockets is really fucking hard. 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 and how easy they make it look. But I mean, Starship is a crazy complex, 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, enough like forward progress is being made or side sideways 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 hope, well, we're all hoping it's going to get us another order magnitude on unit economics. So much of, 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, 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 like, like a really core first order economic driver requiring that, needing that to scale AI training and these type 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 another Another sort of order of magnitude needed. Economics. I don't know if I really answered your question, but that's the way I think about it.

No man makes sense. Well, thank you so much for stopping by. This is great.

Come back on again soon. Yeah, yeah, you bet.

It was great talking to you guys.

We'll talk 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 I've.

Been lucky to use for over a decade now.

Over a decade on Linear.

Must be.

That's crazy. I'm surprised the company's even decade old.

No, no, no, sorry. Half a decade.

Half a decade, okay. Because a decade ago you were in mid.

I was about to say, say the better part of a decade.

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 going to believe this, but it's true. So I just have to say it. And you were the one company that stuck out and I was like, that company's going to be amazing. And I didn't even think of myself as an angel investor. I should have just been like, let me, please, let me invest. 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 tppn.

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 into to all of that, but what has the bread and butter been for the last couple 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 could say you can piece them together and you can build software.

Yeah.

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 tools tools. But surprisingly is 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 Rutil started the idea behind that.

And engineers are not like, oh, I want to work on the internal tool. Typically like, you know, 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, will instantiate themselves in consumer facing products across Metta. But also they have a massive amount of internal tooling that can benefit from, 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 OpenAI 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.

Well, if you look at the homepage page, it's like the logos, it's like, oh, so you guys work with every company?

Every company, yeah.

It's pretty cool. I mean we work from companies ranging from the U.S. army to the U.S. navy, 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 going to start demanding, yeah, we've.

Got to put them on the American dynamism.

Some respect on Retool then. It's 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 Reed Tool 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. It's very cool. Quick. How have you been processing the. The AI boom? When did you first think about implementing LLMs and other AI technology into Retool? And, 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.

Yeah.

You can actually give them to AI 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. And the question is, is it all above? Can we figure out some use case for this LLM beyond just chat?

Yep.

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 of revenue, I want to say something like 80% of it is ChatGPT revenue plus cloud revenue, which is awesome. But Chad is pretty limited. I mean, it's tracking to grow 30x or VR 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. 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, there's the classic Turing test thing of, you know, blue path. Past that way past that.

Yeah.

Yet AIs aren't doing anything yet. So it feels like this 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 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, which is 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. And how does that not destroy every software company? Because I'm seeing MCP servers spun up left and right. And my question keeps being like, 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? Right. 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, like that feels like it's also maybe not.

Even the best example for the regular component. But we also had Stephen on from the co founder and CEO of Lambda Labs. 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 retailers 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.

It's a lot of hours.

And I think the secret is exactly what both of you just pointed out there, which is, is in what cases do you want AI? In what cases do you not want AI? And to give an example, OpenAI has this product called Operator. It's 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 LLM 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, a navy blue color. It will open up the browser, it'll Google find the sock, it'll buy it. I'll use a credit card, it's done. And that's fully non deterministic. It's making it up on the spot. And that's pretty good for a consumer use case. Whereas for a enterprise use case or a federal use case, for example, you actually don't want it at 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? It reads the wikiHow article. It's like, that's not at all what you want. Business has very specific ways of onboarding an employee. And 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 and 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 the time. 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 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 employee easel 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 by express for 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.

So sure, sure, sure. Yeah. And that's something that like a good office manager, good person in HR who's on board 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 Marc Benioff talk about in terms of Salesforce where it's more like resolution based. You want a job done. Our agents are 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 less for him to actually go deliver that value.

As software though, we want 90% margins. Come on, what do you have against high margins? I hear you.

Yeah, no, it creates a. But 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, company 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 a smarter agent. So actually that $3 agent is a deep seek agent. So it's a, you know, say a Chinese agent. For $3 an hour you could go buy O3, which is a quite smart, probably the smartest right now reasoning agent. I think that's something like maybe $120 an hour or something. So it basically depends on what kind of task do you want to do. If you want to do a simple task, actually deep SEQ is quite good at that. At $3 an hour, getting a really good deal compared to hiring human labor. Whereas if you want something, you know, really knowledge worky or something really nuanced done, maybe O3 is better actually. But I think the innovation here is that we are charging on a per runtime hour basis and what we've discovered is an hour of runtime for O3, for example, is actually worth something like 40, 50 hours of human labor.

Wow.

Deep research can do in an hour. I mean, I probably couldn't even do it, honestly. So that I think is really cool. And then what happens is you actually look at how much the customer pays pays per task actually completed. If you compare your 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 it'd 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 evolved? 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 sent 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, of, if not actually 10% of the labor in the US by 2030 is our goal. And the idea is.

Let'S go. I love an ambitious goal.

I love it.

I love it.

Here's the TAM.

Yeah.

U.S. 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.

Yeah.

2030 is a long time away. But we draw the line out it comes to, I think set, actually.

That's incredible.

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

So.

Yeah. 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 get $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 cost seems incredible and yet they've. It seems like they've. 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 federal customer, you might think oh, you know, actually on prem is really important and so they actually prefer to use llama, you know, or something like that.

Sure.

That's not the case actually. You know, OpenAI's was selling a lot of OpenAI it turns out. Actually there's a lot of traction even in sort of big federal agencies for something like OpenAI and they actually have contracts already and so they plug it into retool 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, 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 Mistral for example, people are getting kind of nervous about sending data to other countries LLMs and so it's going to be cool to see how the world plays out. It's surprising. 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 email val's framework, people would just say let's see who does best, who doesn't 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 like 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 like the nature of the contract matter matters more than just benchmark price, etc. Like the quantitative data metrics.

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, like what is under carpathy, call it like spiky intelligence. There's like 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. Yeah.

Very cool.

Cool. But excited to see how the space develops so well.

Thanks for coming on. This is fantastic. Yeah, 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. No, I love the ambition and excited to follow and come back on again soon.

Yeah. Thanks so much for stopping by.

Cheers, 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 on numeral monitors where you're selling, how much you're selling, whether you need, whether you're approaching that threshold, start filing and it does it for you. Automatically cuts it down to 5 minutes per month. 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 a double kill.

Thank you to public.

Anyway, our next guest is from Pallet. We have Shashant in the studio. Let's bring him in and hear the latest update. How you doing?

Doing well. How are both of you?

Fantastic. 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 you're 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's 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. 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? Do you have, 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 user.

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 could 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 get off of paper. But realistically, most companies are on Excel.

You guys have a humanoid robot that goes to a printer to print something out and then faxes, fax machine, still joking.

Of course, humanoid robots will come in soon. But the way it works actually is that you go to one of these. Even the largest logistics providers in the world, 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, 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 100 orders into his system on a Sunday afternoon. And he's like, like, I can't watch the NFL playoffs. I have to type data manually in from my inbox.

That is just my transportation management system.

And this is how I spend my Sunday evenings. And I was like, that's crazy. Like there has to be something better we could do here.

What is the, what is the super bowl of the industries that you sell into? Like, are there specific conferences where everyone gets together in terms of like logistics that are super important for you to sponsor or. 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 PAL, it has come from the industry. They've worked at places like Siva, they've worked places like Uber Freight, they worked in 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 effect 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 ChatGPT. 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 on 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, like April container volumes in Long beach are spiking, now they're down and the courts reverse the ruling and then it gets reversed back in the last hour. So people have no idea. Like my, 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 and 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 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 $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 adjust the customer's estimate 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 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 minimal touch. You're not changing any of your.

I just have to call something out. So you were at Retool before Palette just had David on and he said that he's so funny because he was like charging on a per outcome basis. Bs. That was his take. I don't, I don't fully necessarily agree with it, but. But it's amazing that you were just there.

Yeah, 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. Is a game changer.

Yeah, yeah, yeah.

Talk about the round. It's only been seven months since you raised your $21 million Series A. Now there's $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 amounts of capital on inferencing AI models or is this more just. We have something that's working so we're going to hire more, write 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 most of the capital from the last round we hadn't even spent. We barely touched it, tapped into that. So this round was entirely opportunistic. And part of the reason it came together was the folks that just 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 Hemant 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 like, like I was Talking to the CIO and the CEOs of companies like DHL, Kune Nagle, Estee Lauder and all these corporations. And they were telling me like, 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, 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 like 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 kind of them not being able to decide between different models. Have you bumped into any of the, 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?

So 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 it? Do I go with one of these newer players, like where do I allocate my capital and who do I pick as my partner? And think of the consulting firms as a way to kind of 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 like earn the trust of these Fortune 500 corporations. And that's how we view it. Actually one of the CEO of one of those firms is actually someone who, who I've gotten know 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 industry.

Hey, we're gonna be shipping a lot of hats, a lot of Jacket, you're like.

He's like, well, a lot of people think that, you know, our solution might not be right for them, but yeah.

I'm like, I want to actually try. Yeah, yeah, yeah, yeah, yeah. The ambient anti cell sells better than anything else, for sure. Anything else, Jordy?

No. Congratulations on the new round.

Yeah, this is fantastic progress.

Yeah.

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

Sure.

Where what we believe in is actually that there's only two places you could work at Palette, either in the office or at the customer site. Every month, 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 process. 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. And they don't. You don't need all good documentation. You can't just go chatgpt the right answer on how does container track and trace work. You actually have to sit there, observe, learn, and then that's.

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. You know, about a week out of the month you'll be in South America and you. And you built out that function at retool, Right. This sort of concept of this deployed engineer, is that correct?

That's correct.

Yeah. I was probably the first forward deployed engineer there.

Very cool.

That's cool.

I love that.

So you're pretty bullish on the forward deployed engineering meme. Kind of just growing and growing in the future broadly for every company. Or is it specific to B2B software or something about AI automation and something that needs to be customized? I imagine that. 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 in with your existing infrastructure. So at least for palette, we think the forward deployed engineering function is critical to make change management easier. But there's obviously tons of companies that could succeed without that function.

Yeah. Yeah, that makes sense. Well, thank you so much for stopping by.

Yeah, congrats on all the progress. You're super bullish.

Yeah, I'll talk to you soon.

Cheers.

Bye. How'd you sleep last night, Jordy?

I had kind of a pretty botch it. We were on so much 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. A couple yerba monsters.

I only 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 beat you. I got an 84.

Anyway, go get yourself an aid sleep. 5 year warranty, 30 night risk free trial, free returns and free shipping.

It's what Charles LeClair sleeps on 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 my interesting takeaway from this. Sorry. Is that there is a desire for like we talk about out of home, obviously. And we're going to 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. And those people walk through Grand Central.

Yeah, 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 like aware of your brand or your company. But when the moment comes that they should. That they would convert. They don't actually think of you in that context.

Yeah.

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

I'd like to see him.

And I'd love that.

Going like one of the clubs.

Classic Arnold hitting the zizz. The Z Y. Z guy. Yes, absolutely. But aside from that, it's okay to just send the message up front. Just be straight up with it. Like, Ad Quick out of home advertising made easy and measurable. Say goodbye to the headaches of out of home advertising Only Ad Quick 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. Seeing your ad on Meta X, et cetera is cool. 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?

Yes.

I didn't finish the show.

I finished it. It was kind of a challenge because I kept falling asleep.

Yep.

Like two thirds of the way through every episode. So I feel I've seen the entire season, but, like, I actually should probably watch it back again. But. But yeah, it was. It was absolutely wild. And especially the context, like the timing of when. Of when the show actually premiered and the episode started rolling out. It really is insane.

Absolutely.

But he's one of the best to ever do it, and he's a real icon, and we have to. 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. Go to getbezel.com your Bezel Concierge is available to source you any watch on the planet. Seriously, any watch. They have 26,000 luxury luxury watches available. And so go check it out@getbezel.com and next up, we have Rob Toews, 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 come in the world of AI and to keep myself intellectually honest, go back at the end of the year and grade which ones were right, which ones are 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 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 got to fail that one.

Yeah. Not messy yet, for sure. Yeah.

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

Yeah, well, the book is not yet over, so.

Yeah, yeah, yeah. Anything could happen. Anything could happen. What about things that you feel like have played out as expected? Have you, 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 productization versus this narrative around. Oh, yeah, just scale up. The big transformer model GPT7 will be ASI done.

Yeah, yeah, no, I think, 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 around 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, next vista for scaling, which was inference, time compute and data scaling, reasoning models and so forth. And the reasoning models, 010304, Deepseqs, R1, 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 GPT2 to GPT3 to GPT4 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 and there were no further advances, there's literally trillions of dollars of economic value to be created by just figuring out, 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 stargate 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 like 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 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 even inference time compute that can be done on GPUs that are more spread out and you don't need to have these like mad like 5 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 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 has really been immortal.

Yeah.

But I think there is a narrative that even as inference becomes more important, as compute gets cheaper and cheaper, there will still be bigger and bigger and bigger pre training runs. And so that will justify the massive CapEx buildup that we're seeing.

Yeah, I've always been interested to see if there's going to be the big transformer training runs, like the GPT4.5 type training run in image diffusion or in robotics or even in. I was thinking about like, you know, we've kind of solved chess engines, but like, what happens if you scale that up seven more orders of magnitude? Like just do you get some weird outlier, outlier scenario? The question I always have is like, 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 like a VO4 training run and we'll be hearing about like, oh wow, it's at 5 gigawatt scale because VO4 just needs that much pre training.

Yeah, yeah. So this was one of my predictions for 2025, is that we would, 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 like 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 nascent signs of that in some of these other, other data modalities. I think one, one important challenge or constraint though is there are very few other modalities that, where there's as much raw data available as there is for text. Like there is not an Internet for robotics training data or an Internet for biology even. And so the training data sizes can limit. It doesn't make sense to have a massively over parameterized model if there's just not enough training data. And so for the fort 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? 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 is 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 mean, I think there's no question that Robotics foundation models are getting increasingly generalized and there's more and more signal 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 around training data is a 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 simulation 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 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, like sophisticated simulation engine you can build. But I do think as time goes on that 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 remembers, 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, the kind of like mix of training paradigms that you would use in, in av? And I guess like 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, where no one's talking about a data gap between Gemini, ChatGPT, Anthropic Llama. They all just have all the data.

Yep. Yeah, totally. Yeah. It's interesting. The way that autonomous vehicle AI stacks work today is like 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 fed all of the data in the world. They are much more handcrafted. But it is an interesting thought experiment and there are younger next generation autonomous vehicle companies that are taking this approach like let's build a foundation model for driving and can we do something 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 heart hardest thing? Because you can't just crawl the web, right?

Exactly. Yeah, yeah. It's much harder to get training data for it. To your question on Google versus Tesla or 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 concrete for a reason that they don't have lidar as a sensor modality. And so this is like the big debate that before I got into B.C. i worked in autonomous vehicles and even back then this was a debate like can you get to level 4 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 it would completely wreck the unit economics of selling a car to an individual. Waymo can, can stomach the cost of a lidar because their model is a robotaxi model. Honestly, I think the jury is still out. Like it's, it's Tesla folks will tell you that. Like we're very close to that. And lidar was never necessary. But it's, I think it's not, it's not completely clear yet. And so in that sense, like the data set that Waymo has is more robust just because it's much more multimodal.

Do you have an, do you have a sense for why lidar is so extreme expensive? Like I mean Elon Musk was able to make rockets cheap. Like the iPhone is cheap. Like how can we not get lidar down? Like even just like a couple thousand dollars, like 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 like five or six figures and that breaks the model. But we historically humans have been really good at like mass manufacturing expensive stuff and make it cheap. So. So I've always wondered about 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. And there have been rumors of Tesla like experimenting with lidar here and obviously under wraps. So.

Right.

It wouldn't shock me. I think it's a great question. I think the short answer is just 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. So like the original like kind of like bucket shaped lidar that Velodyne made were like $64,000 a pop on like the really old school Google self driving vehicles. Now they're probably like 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 like 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 event in a few years lidar gets cheap enough that like Tesla can use it and everyone can use it.

I had a buddy friend of the show 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, you know, 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? And like, is it even. Are there going to be as many venture opportunities or is there a car.

AI car, Washington startup pull the autonomous vehicle in, it washes itself. It's great.

That would be different than a regular drive through.

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

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? Or you know, whatever.

But parking lots aren't cheap though.

But yeah, this is, this is in the context here that Wayo 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 is. 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, in the Bay Area, in San Francisco use Waymo more often than they use Uber and Lyft. And it's like quickly spreading to beyond just being a Bay Area phenomenon. Like 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 me 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 it 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, you know, maybe you have a desk.

Yeah, I want it to be a desk and a couch. And 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.

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

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

Yeah. Well, this is fantastic to have you back. This is a lot of fun. We could 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. 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 gotta sing. We gotta hit gongs. We got lots to do. We're gonna say.

Are we.

Is he gonna 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 graded amenities, dreamy beds, top tier cleaning, 247 concierge service. It's a vacation home, but 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 out that wide. Hit that gong. Hit that gong. Hit that gong. Welcome to the studio.

John. 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 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 for us.

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

Yes, yes.

And 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. Pull that off.

But yeah, give us the business update. Break down the fundraising round. What are you actually spending it on? Because 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, red point Logan.

Bartlett's in.

Okay, there we go.

Yeah. Red point Starwood. Bunch of. 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 going to do some like crazy stuff, but it's really scary. 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 like a culture that really celebrates that.

That.

And yeah, break it down.

Yeah.

Wander definitely has a very high output culture. As a startup, I tell the team that culture is not happy hours and that kind of stuff. It's about winning. And so as a company, we Obviously very much focus on that idea. From a growth perspective. There's about 300,000 wander worthy locations across North America, 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 Wanderos 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 a 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 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's an active startup, even if they're scale 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 Cesky 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, I think Airbnb is a great company and Brian's like an incredible founder, so I have nothing negative to say there. I think for Wander we do deliver a little bit of a different experience. So our net promoter score for Q1 is 85, which is phenomenal. You? Yeah, like true, true customer love.

Yeah.

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 8 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 across.

Across every single stay, every single home, every single customer. And so I think that that, like, relentless customer focus is just a very different model than Airbnb. Airbnb is sort of that unmanaged marketplace versus wander. Like, we truly do care about the quality of our inventory, the quality of your customer experience, to the point where literally, like, I will hop on the phone and deal with whatever the issue is to ensure that it gets there. And 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 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? This category. We were talking to Keith Raboy 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 Raboy's take was the. 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, where just broadly the category is driven by advertising dollars in a meaningful way?

Yeah, I mean, when you, when you go on to like booking.com as an example, or even Brbo, like, you will see ads.

Sure, yeah. Promoted to get to the cause. If I have a house and I want it rented, I'm willing to, 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 where they're actually taking people off platform, which is pretty interesting. Like, I'm, I'm sure that it's a revenue source. I mean, these, 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 like try and monetize a percentage of that traffic that's never going to end up converting to actually like booking a home. But that being said, like, Keith is obviously, you know, correct and very smart that the take rate on vacation rentals is really high.

Sure.

For, for Wander, our average order value is about $5,400 and you're looking at like an average take of about 30%. And so like, for us that would have to be a lot of like rent random ads to, you know, like make that up. And of course the customer experience is, is not, not great. We're really trying to market users on, on that, that, that booking. But yeah, I mean, I think for a company like Airbnb 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 you sort of pulling, pulling yourself out of that is, you know, difficult for your mom and 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 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. 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 disintermedia. 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 Google the place and find a different way to go.

Airbnb has an issue where property management companies list a home and then the person that's booking the home just Google that, stay there and then just reach out to the property manager and do a deal off platform. Whereas Wander, 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, 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 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 13, 14, we were hosting Minecraft servers and whatever else. And when 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 a pretty young age.

Never again.

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

Yeah.

How do you think about taste in the context of what you're doing? Wander's always felt like just 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 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 did high school online, traveled 200 plus days a.

Year all over the world.

You were your race car? You were driving race cars?

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

No way.

And then, yeah, Formula Mazda it was funny.

John and I got lunch in Malibu like, a couple years ago at this point, and I was like, oh, do you want to, like. I, you know, 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, like anybody'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. 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. It was a great. It was a great time, great meal. And so, yeah, I think with Wander, I mean, candidly speaking, Wander is like my soul. But, like, as a company, like, 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. Like, 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. Like, 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 kind of 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 and 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 measure, you know, manage their reservations or whatever else so that you could provide this online platform, you know, now with, you know, what exists from a technology perspective, you can have an AI agent, 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 like agenc 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 like an abstraction layer and a curation layer on the experience.

Makes a lot of sense. I mean, I have one more question about. SEO is 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, and are there any services or kind of best practices that you think relate to AI SEO? Or isn't it geo, according to Andreessen Horowitz?

Yeah, I don't know what the acronym is, but it sounds like a good acronym.

They call it that.

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 like, you basically need a source of truth strategy, which is a really interesting phenomenon. Basically it's like, how do you sort of like become the system of record from a fact perspective or get the data onto a platform that is viewed as having the that fact facts. Like for example, ChatGPT references Wikipedia a lot. 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 to Jordy, you said there's 300,000 homes that you guys have sort of soft circled as targets. I'm assuming you're going to get all of them in the fullness of time. What do you, what do you want to do in the next. What do you want to do by 2030? Do you have a, 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 point. Pointing to the.

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

Listen, we, we'll.

We.

We'll get it done. And before I jump, one thing I want to note is as a. A sponsor of. 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, I cannot encourage you more enough to work with these boys. They are incredible. And the ROI is through the charts.

Thank you.

You're the man.

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 youy 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. Did we create.

We created singing. We created jingles.

We created the jingles.

We created the jingle from first principles.

We created the jingle.

No, 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, it.

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

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. We should. We should make like a radio.

Absolutely. Yeah.

Hey, this is John and Jordyn.

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

Super excited for you and the team. And John and I are like, basing our summer plans off of Wander vacation. Wander. So for sure.

Thank you.

Congratulations.

We'll talk to you soon.

Soon.

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%. And so. So the news about Elon leaving the US government has been, you know, 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 market, 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 $1000 is at a 13% chance, over $1500, 2% chance, over $2000 is only a 2% chance. I think Tim Cook's gonna get it done. Keep, keep, keep iPhones cheap. The other interesting thing is which, which company has the best AI model? At the end of May, Google's running away with it at 96. 96.5%. Yeah, that's May if you go out farther. 60 if, yeah, if you go farther to the end of the year, Google's at 40% open A. OpenAI's at 22%, Xai's at 23%, Anthropics 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 you know, we haven't seen what the next iteration of sora looks like. OpenAI clearly cares about that. They've been building a product and image. Image VO. In fact, the first, the first consumer product from OpenAI was not a chat model. It was Dall E. Dolly 2 was the first, 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 gonna, 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 marker eval for that. So we'll have to get one and then we'll have to put it on polymarket.

Got it.

Anyway, we will see you tomorrow. It's going to be a light show.

Rora, we launched a new product today, a filtered shower head. If you go there, let's see Rora.

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 the 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, very cool. Ergonomics. And yeah, go check it out. I made a code or I had Brian CEO make a code TBPN discount. And yeah, excited to see how this goes.

So we will be back tomorrow. Little bit of an earlier show. I'm doing some traveling and it'll be no guess, just me and Jordy chopping up the timeline. Throwback episode. I think these are some of our best.

It's going to be fantastic.

I can't wait. So it'll probably be an hour, hour and a half around 10am 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 gel blaster at us right now.

Thank you for watching.

Take care, guys.

We'll see you tomorrow. Bye.