SpaceX Launch: Deep Dive & Reactions | Josh Reeves, Keller Cliffton, Will Brown, Julia Steinberg, Olivia Moore, Flo Crivello

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Massive news from SpaceX last night.

They did it.

They did it. Flight 10 made it back. Took off from Starbase South Texas.

The.

Booster landed in the ocean in the I think the Gulf of America.

Technically that's absolutely right.

And the actual starship executed a successful flip maneuver. Deployed a mock payload of a bunch of non functional Starlink satellites. Survived re entry just barely, as we'll see. It was a really dramatic video. It was amazing. And then splashdown on target in the Indian Ocean.

It was a full send.

It was a full send. It was. It was a crazy, crazy.

NASA could never watch.

Yeah. Let's watch the recap video that the Wall Street Journal put together. This is pretty interesting. Starbase Texas, this is yesterday. They scrapped two attempts on Monday and Tuesday because of some, some problems with the vehicle. But they got it off the ground. Look at that. They lit the stunning go into space.

So I wish we could get a better sense for just how massive it is.

Those angles and so that. Those are the dummy Starlink satellites. The dummy.

You see that little motor conveyor belt on the left?

Yeah. Just the number of things that have to go right to actually release something from this rocket. It's insane. And then this is the crazy part. There's just a bunch of. Where did the stuff come from?

We clearly didn't need it.

You would think that as soon as I saw, I was like, okay, it's over. The whole thing's gonna blow. For sure. It does. It definitely doesn't make it back because if it's like losing parts, like every part should be important. Right. Like what's going on here. And they're also, the whole time they were like testing the, the flaps, like really pushing them to the limits. Going farther. There it is. Splashing down.

Yeah. You were mentioning earlier, there's a sound bite of them saying they were, they were.

They were going further than they needed to. So they were doing things like, like okay, let's final moment. And then boom.

And then the convenient cut. You would have thought the Journal and the legacy media would have let that.

Yes.

Yeah.

A little bit longer. Massive explosion.

Yeah. I mean the vibes, the vibes going into this were rough. Honestly, lots of people with the Elon's been distracted by politics. Take. Lots of people with the Elon too focused on AI Romantic companions. Take. We covered.

You can imagine the Conversation between Elon and Ani yesterday. Right. For the launch. You got this babe.

I mean, you know that Ani apparently, allegedly the original ANI romantic companion model runs on the non reasoning model. Just Grok 3, I guess.

Just pure love.

Pure love. And if there's any evidence out there in the just market of AI chatting and companions is that you don't need a reasoning model when you are chatting with a romantic companion. So a lot of like the backlash to the GPT5 launch was something like, you know, people were using it not just as a romantic companion, but just as like a life coach, somebody to talk to. It was very conversational and that quick back and forth was what people actually enjoyed. They liked the tone. They didn't care that it wasn't, you know, incredibly good at solving hard math problems or like the IMO or whatever. What you got for me, Tyler?

I think there's also something to be said for like reasoning models kind of mess with the vibes. Yeah, totally. Like it's like the music thing where.

Yeah, yeah.

Sometimes you want a friend that's not gonna think too hard. They're just gonna.

Yeah, yeah, yeah.

In the musical like taste thing.

Yep.

All the reasoning models gave like these weird answers because they would like to prefer, you know, artist names with numbers like that.

Yep. Although I mean I think the reasoning models actually had the best taste of all. But that's a bit of a hot take.

But we got to pull up this post from Red Bull futurist. Very important, he says. Super heavy. The effing goat.

Wow.

And I just needed to highlight this because obviously Red Bull, some of Red Bull futurists work actually has led into this of course.

Amazing.

So absolute legend. A win for Red Bull. Really?

For sure. For sure. Yeah.

It's actually surprising that Red Bull and SpaceX haven't tried to collab yet. You'd think that Red Bull would just be like will give you millions of dollars if you just put Red Bull branding over this. Why not? It'd be good. It'd be good for both parties.

Even the explosions are feel like on brand for Red Bull. Red Bull's down for the crazy risk taking.

I could see Elon going with White Monster.

Really should do that. Entire advertising is special and maybe you don't want to dilute that.

Are you.

Would you go so far to say the White Monster brand isn't special? Would you say? I guess it would be added Red Bull.

It would be added special. Yeah. The reason I was bringing up the reasoning models was because apparently Elon wanted Ani to use the reasoning model like the AI companion has to be able to do the hard math problems, which is funny. So maybe she really was in use making doing rocket science and calculating the last final decisions before this rocket went out. But it was a huge success. But the Wall Street Journal has kind of the play by play here. SpaceX pulled off a smoother test of its Starship rocket, managing a more complete mission after setbacks earlier this year. The starship spacecraft flew through space after launching from the company South Texas complex Tuesday around 7:30pm ET. The vehicle successfully deployed a batch of dummy Starlink satellites and re entered Earth's orbit facing intense heat and forces before splashing down in the Indian Ocean. This is the 10th launch of Starship. I believe this was the. This was ship like 37 or something. They've built a lot of these. Not all of them have launched. Some of them have been scrapped. Some of them blew up in the test stand. Like they really push these things super hard. So it's a 403 foot tall rocket. They started testing this in 2023. There's been a series of explosions, mishaps, previous test flights that have been cut short. Elon Musk has much riding on the rocket, envisioned to one day carry satellites, scientific devices and eventually astronauts.

Just to put this into context, the White House is 70ft tall.

Wow.

So this is.

Yeah, it's like the size of the. Isn't it closer to the Statue of Liberty? I think it's like around that tall. 403ft. I'll have to look that up.

The Statue of Liberty is 305ft.

Oh, absolutely. Mogged an extra 50ft on that. For now, the company is pushing to show it can consistently fly Starship and experiment with its design space SpaceX set up Tuesday's mission to stress test parts of the Starship spacecraft. We certainly saw that on display with the parts flying all over the place. Seeking to give engineers information to continue developing the vehicle. Basically the calculus here is like how cheap can you make this thing? If you use duct tape, will that work? If you use tinfoil, will that work? They really are pushing these things crazy, crazy hard.

I think the other way to put this into context, not everybody is fortunate to be able to build and launch rockets for a living. But anybody that's built software knows that even if you're launching a relatively simple feature, it'll oftentimes break and have issues and bugs and things like that. And it's a little bit, you have a little bit more leeway to ship stuff and make changes on the fly. In this case, they're doing it in this incredibly public setting where the Internet is going to have a very strong reaction one way or another. So the pressure is just insane.

So Musk wants both the Starship booster and spacecraft to be fully and rapidly reusable, more akin to an airplane than a traditional rocket. SpaceX has made major strides with reusability with its workhorse Falcon 9 rockets, which are powered by boosters that can be used many times. SpaceX faces self imposed and external deadlines with the much larger Starship. Musk wants to launch an uncrewed version of of the vehicle to Mars next year, but has said meeting that goal will be tough. Of course, there's a Mars transfer window that only comes up, I think every 18 months or so. So it's really critical to hit it in 2026, or else you gotta wait till 2028. I believe in 2027, a Lander variant of Starship is supposed to be ready to carry astronauts on a NASA moon mission through the agency's Artemis exploration program. That's gonna be really hard because I think they have to refuel in orbit and then also make it safe enough that astronauts can fly on it. Like they have a lot to do there.

This is why we need to get ANI to be able to solve complex physics.

For sure, for sure. And so Elon's obsessed with saving costs, saving time and money. You should go to ramp.com, save time and money. Time is money. Save both easy. Use corporate cards, bill payments, accounting, and a whole lot more all in one place. Go to ramp.com Speaking of ramp, Ramp, of course sponsors the founders podcast, which David Senra had a fantastic episode that just dropped called How Elon Works. And it really contextualized how insane it must be to work on the Starship project. And there's three quotes that I want to run through here that I absolutely loved. So first, when an engineer told Elon the air cooling system for the Falcon 9 would cost $3 million, he shouted over to Gwen Shotwell to ask her what an air conditioning system for a house cost. About $6,000, she said, so the SpaceX team bought some commercial air conditioning units and modified their pumps so they could work atop the rocket. And my take is like, like, yeah, obviously like 3 million is a lot. 6,000 is like nothing. But like if you're spending $3 million on the air cooling system, like it probably has been tested in aerospace environment, it probably comes with a team to help you get it working reliably. There's probably lots of nice to haves that go into that. And yeah, this is, this is.

I mean, you know, you would. A lot of companies that have this much access to capital would not be fixated on things like this. They just say, what's the best solution for our problem? Let's use that.

Yes.

And so to have, again, to have that much access to capital and be that fixated on costs, like most billionaires with a space company are just going to say, well, let's use the best of the best.

Exactly, let's use the best of the best. And let's just do one. Let's do the first rocket and then let's worry about cost control later.

Later.

And that's very different. So you can probably, like spending the $3 million probably speeds up the time to get a single rocket to space, but that's not the goal here. Elon's obsessed with building a system that will get to space over and over and over again. And so there's another quote here that's wild. Elon's just consistently questioning things. This is David Senra talking and trying to find the limit. And then he's quoting Elon. Why do we have to have four bolts there? Who set that specification? Can we do it with two? They would say, no. He said, we'll try it, see if it fails. And then on and on and on, and he just moves down the line. You need to be decisive or you're going to be dead. Elon calculated that he made 100 command decisions a day as he walked the floor. At least 20% are going to be wrong, he said, but we're going to alter them later. But if I don't make decisions, we die. And so, like, it's very clear that looking back at the starship tests, like there are so many gambles going on and so many design decisions that are basically irrational. If you're just trying to get one to space, but you're really building up.

Like playing the game on hard mode.

Minimum, but playing it for the bare minimum, the cheapest possible rocket to get there. And he's probably just adding cost, just dollar by dollar, like, okay, completely blew up. Let's add one more thing that might stop it from blowing up as opposed to the opposite, which is like. Which is like, that can never happen. Everything that stops it from any system or feature or function or part that stops it from blowing up, start there and then maybe we'll pull one of those out if we're really sure that it can not blow up without it. Instead, it's like it's going to blow up. Let's add the minimum amount of parts to make it not blow up. And so everyone in the space community always quotes this Latin phrase, ad astera per aspera to the stars through hardship. I always thought it was just ad astra to the stars, but ad astra per aspera is to the stars through hardship. Through hardship specifically. And I thought that hit really hard. This, this founders podcast is, is fantastic.

There's a bunch of potentially one of the greatest episodes of all.

It really is. Like, there's this great story in here. Well, it says Elon saved money by questioning the requirements when he asked his team why it would cost $2 million to build a pair of cranes. These are cranes. They're supposed to lift rockets. He was shown all the safety regulations imposed by the Air Force. Most were obsolete. So SpaceX then goes to the Air Force and they start questioning them. And it says that SpaceX was able to convince the military to revise them. The cranes ended up costing $300,000. Like that's like 85% savings. It's crazy. He does this over and over and over again. But, but the way he does it is just really, really smart. He's consistently comparing costs for parts, materials to other industries and other cases. Here's an example. Elon consistently pressed his team to, to source components from non aerospace companies. The latches used by NASA cost $1,500 each. A SpaceX engineer was able to modify a latch used in a bathroom stall and create a locking mechanism that only cost $30. And so again, it's like a 98% savings on the latch. And you just do that for every single thing. And it adds up to something that when the economics change, it's not just a cheap rocket. It's like it's the type of rocket that you can launch every single hour, whereas it's just impossible to underwrite that if you're, if you're going to the taxpayer and saying, you know, we need.

And can birth an entirely new industry.

Exactly, exactly.

There was another line in here I'm going to. But, but you guys should go listen to the episode.

Yeah.

David highlights how Elon has this interesting problem where his employees, like, become so wealthy that they lose like, the work ethic that like, made the company what it is. And so this frustration of like, okay, I'm, you know, we're making all this progress, but then eventually, you know, early employees end up with, you know, A nice house, a vacation house. And they don't want to spend quite as much time at the factory grinding. So. Good problem to have.

Well, hopefully you enjoyed the SpaceX stream yesterday. I think they used Restream. If you want to stream, you should use Restream. We were powered by Restream One Livestream, 30 Plus Destinations Multi Stream to reach your audience wherever they are. You can sign up for free. There's one last funny story in here. The day before launch, a final inspection revealed two small cracks in the engine skirt of the rocket's second stage. That's the piece of the bottom. Everyone at NASA assumed we'd be standing down from the launch for a few weeks. The usual plan would be then to replace the entire engine. What if we just cut the skirt? Elon said, like literally cut around it. Why not just trim a tiny bit off the bottom that had the two cracks. Using a big pair of shears, the skirt was trimmed and the rocket launched the next day.

It's wild because another way to. If you had somebody working on your house and they were applying this approach, you'd be like, what are you doing? This is so janky.

Are you insane?

But it works crazy as much when it's part of this.

It took less than an hour to make the decision. Three more principles combined that repeat over and over again. Elon's anti outsourcing, Pro control and Pro D daily iteration. And David has an interesting context here about offshoring. By sending factories abroad, American companies saved labor costs. But they lost the daily feel for ways to improve their products. Elon bucks this trend. He wants to have tight control of the manufacturing process.

He believed that's why he puts tents up in the parking lot.

Yeah, he believed that designing the factory to build the car, the machine that builds the machine, was as important as designing the car itself. It's a fantastic episode. You should go check it out. Do we want to run through the history of SpaceX, the history of these launches? We have Tyler Cosgrove with some beautiful work on the TBPN yet to be sponsored whiteboard. There could easily be a sponsor on there. Maybe figma. Think bigger, build faster. Figma helps design and development teams build great products together. Get started for free for now. Tyler, take us through the history of SpaceX, the history of these various projects which are.

Professor.

Yeah.

Okay, so the intern becomes the professor.

Class is in session.

A lot of people, I think when they hear these about these launches, they aren't even really sure like what rocket is even going on. So I Think you can kind of classify SpaceX rockets into, like, three distinct types. These are, like the active ones that are still going on. So there's Falcon 9. So this was like, the first really, like, you know, commercial, like, not just tests. 2010. This is like, you know, the ninth iteration.

They were doing Falcon 1 before, which is one engine. Right. I think those were like, mostly tests. They weren't really reusable. It wasn't really a business.

Yeah.

At that point.

Yes. That was 2010.

Oh, perfect. All right.

Can you still hear me?

Yeah.

Sound great.

So, okay, so we have. That's Falcon 9. Then Falcon Heavy comes out. 2018. This is essentially just three Falcon 9 boosters just, like, strapped together, but it's kind of a separate thing. Right. These are also always built to be reusable, at least some parts of it.

And that's a big piece of the Falcon 9 has literally just nine engines kind of strapped together. It's all the same engine, so they get the reusability there.

Right.

So they're like, one thing.

Yeah. And then we go down to Starship. I mean, this is what's currently being tested. This is not like doing commercial missions yet, obviously, but this is kind of the next iteration. So this one, they're all kind of two parts.

Right.

But this one has 33 engines on the bottom. That's, like, called super heavy. And then Starship is technically just like the second stage.

Sure. Oh, okay. Yeah, yeah, yeah, yeah.

Okay, so then let's go through. Let's first go through just like, kind of general SpaceX launches. So here, 2006. This is the first Falcon 1 launch. This is what we were talking about earlier.

Okay.

Kind of none of these really do a lot until the two.

And they have, like, three failures. It took them, and they were almost out of business.

They had one of those pictures of Elon in the road.

Yeah. Where he's kind of sitting down.

Yeah, yeah, yeah, yeah. And Kwajalein Atoll out in the Pacific.

Yep, yep. And then we go to 2010. This is Falcon 9, first launch. 2012. This is the grasshopper landing test. Okay. So these are when the first test of, like, propulsion landing. Right. Which we kind of have seen later with the starship, where it catches it.

Right.

Lands down.

Yep.

2012. This is the first ISS cargo mission.

Yep. So this was on the story of the grasshopper legs. That's Doug over at Radiant Nuclear.

Now.

He worked on that project. It was like no one had done that before. Crazy decision. And then Starship is unique in that. Elon's basically factoring out the legs. Because if you take the legs off the rocket, that reduces weight so you can get more payload to space. And then instead of legs, you have, you basically have a pair of chopsticks that catch the rocket. Yeah. And so the legs never leave the Earth. Right, that's the strategy.

Yeah.

So then ISS cargo.

Yeah, ISS cargo. This was the. On the drone ship landing.

Realize I took four years to get the drone ship.

Right.

Yeah.

That crazy video we should pull up after this. That like all the landing failures on the drone ship. I think it's like in the hall of the Mountain King and it's just like crashes after crashes after crashes.

Yeah. Okay, so and then we go to. This is the first 2017, the first reflight of a booster. First time they actually like kind of reused it.

Fully reusable at that point. Yeah, got it.

And then 2018, this is Falcon Heavy, the three Falcon Nines put together essentially. Then this is where they basically just start to get the cadence record of launches per year.

So you see those time lapse videos. If it goes from 1 Falcon 9 launching to 1 launching every second, this is when they.

Yeah, I mean it's pretty incredible. I think the record before this was the USSR.

Oh, really?

I think it was like 1979 or something.

Oh my. Okay.

Yeah, it's pretty insane that they had that record. But then, yeah, we did Starship. So then let's go through Starship launches. Let's go through starship launches. So first one, April 20, 2023.

Yep. So it was fully stacked and it took off. But it blew up after four minutes.

Yeah, basically immediately.

Rapid, unscheduled.

Not all of the engines started. There's 33. They didn't all start. Okay, but that was the first like kind of everything is put together, it goes up.

Got it.

Then the next test, 2023, November, this is all 33 engines started.

Okay.

That was the big, big upgrade. Then we see it reached orbital velocity. Okay, so another big step. June 6th. We see both stages kind of go up and then they both reenter.

Yeah. So they both hit their max altitude.

Yeah.

So they weren't, they weren't trying to go any farther. But coming back is rough because you're going through the atmosphere and then they blow up on the way back.

Yeah.

Okay. But they're making progress.

Yeah.

Cool.

Then we go to October 13th. This is like kind of the famous tower cat.

Yeah, I remember that.

This really blew up the.

The chopsticks.

Yeah, Chopsticks.

Yeah.

Okay. Then we see November 19th. This is the Raptor relates. So Raptor and the Tower Catch.

Did it blow up in the tower? No, they caught it, right? They caught it.

That was the actual crazy.

And then they probably have to like tear it down and like rebuild it because it's not like fully reusable yet. But it proves that they can actually.

That one was wild because it was so sci fi, but it had been almost programmed into people's brains. That. That was like a thing.

Yeah.

Through sci fi, the reaction broadly, like people tech were, you know, pretty blown away. But at the same time, it just, it felt like something that space company.

And the really crazy thing about the Tower catch was that it emphasized how high cadence the actual process of reusability can be. Because I believe that the lower stage, the booster, goes up and is only in the air for like a couple minutes. It's not actually that long. Like, the. The upper stage was in space for like a full hour. Like the mission.

Super heavy.

Super heavy. Just goes up and is back in like 4 minutes or 10 minutes or something like that.

Yeah.

And so you see it go up and then come right back and get. And. And get caught in the tower. And then they can just rotate it over, start refueling it, and it can just bring the next thing up.

Yeah.

So like, the pace of iteration is the system is designed to be like, not launch every day. It's like launch every five minutes. It's like truly like airport level.

Yeah.

Spaceport.

Let's go to first. Block two. Launch. Okay, so block two.

Yeah, it was block two.

That's like. When you look at the starship, like, basically the top section, there's been a couple. It's kind of like this part. There's been a couple iterations of this. So this was kind of the next big, like, upgrade.

Yeah.

And then we see March 6, we see a payload attempt. So this is what you were talking about earlier, where they try to open the doors. Open the doors, put out. They're not real Starlink satellites, but they're like mach ones. Then we see super heavy reflight. So this was super heavy again. Is this booster. That's the first time they actually reused the same one.

Caught it and then put it back up.

Yeah, it didn't actually go back up, but they reignited it basically, and it worked. And then this one just yesterday was payload deployment. And then we talked about this earlier, but both stages had controlled splashdown in the ocean.

It's amazing.

Yep.

What a journey. Well, congrats to everyone.

Small note. It explodes. But next time.

Next time, Next time.

All that matters. It was a controlled touchdown.

Thank you for the breakdown, Tyler.

Feel free to keep the helmet on for the rest of the show and.

Feel free to sign up for Vanta Automate Compliance Manage Risk, Prove Trust Continuously. Vanta's trust management platform takes the million award and security out of your security and compliance process and replace it with continuous automation, whether you're pursuing your first framework or managing a complex program. Philip Johnston was clearly inspired by what's going on, but a little bit frustrated. Wanted to highlight this Nothing pisses me off more than VCs proclaiming they don't invest in deep tech companies outside of LA and sf. Starlink is quietly building one of the biggest cash generators of our time in Redmond, Washington. It's also where Cooper AWS and Azure are 80% plus of of all satellites launched globally in the last year were designed, built and tested. Redmond There's a reason we put Star Cloud Inc. In Redmond and we're on the lookout for more amazing talent. So good luck to Philip Johnston. Hopefully the VCs come around to the good work that folks are doing in Redmond, Washington.

What if we moved Redmond to the Gundo?

We could, we could. I think there's probably for all these companies, there's, there's assets in all the different places. I haven't heard of a company really going deep into South Texas because a lot of the Gundo companies are beneficiaries of the work that SpaceX did in Hawthorne and El Segundo. And in fact I think that there's a space company that's in the. Maybe it's Rivian is currently not a space company, but Rivian currently owns the original SpaceX factory in El Segundo because they've moved out because obviously they scaled up. But a lot of the Gundo companies are beneficiaries of the work that SpaceX did in El Segundo to kind of bring back that industrial capacity. Of course, before SpaceX there was Lockheed and Northrop and a few other primes that were in the area and still are. But the Gundo has been like a great home for defense tech broadly. Maybe Redmond's the next one. Maybe you got to do some. If you're doing satellite R and D, got to get a Redmond an office. If you're doing launch stuff, you want to head out to South Texas because they do seem pretty friendly out there. At the end of the SpaceX stream, the announcer kind of like thanked all the different parties and was like thank you to the county where Starbase is, because Starbase is like this chartered city within the county. And thank you to the people of Texas and the people of this and that.

Well, they got a stock exchange now. They do yesterday. Got nicee Texas.

Nicey Texas.

Something. Something down. Something happening in the. In the Lone Star state.

Yeah, I haven't been to Texas in years. Last time I actually went was for David Center's thing.

Really?

Yeah. Other than that, I don't find a lot of random time to go there. It's been a lot of New York, a lot of sf, Little Miami, but.

I have been a bunch.

When was the last time you went?

Last year, I think I went three or four times for different portfolio companies.

Yeah.

Great place. Great place.

Do we have the video of the SpaceX explosions over time? They have this montage reel. I'd love to play that if you can find that. As I tell you about graphite.dev code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster.

All right, I'm throwing it in timeline. This is the graphite video that I could find.

We will be talking about venture debt and what's going on in that market, but in the meantime, I believe we have a video of SpaceX's launches.

This is SpaceX themselves. How not to land an orbital rocket.

Yes. This is the video I want to watch. Can we go full screen on this? This is great. And just immense, immense confidence to release something like this. That on the face of it, makes the company look bad, but actually demonstrates what makes the company look great, which is not being afraid of failure.

The top comment is this is 100, the most expensive.

It comes down so fast. It comes down so fast. The first one is just like didn't stop at all. Here we go.

Oh.

Oh, no. Wow. There we go.

Beautiful. But this is great. Unfortunately, all this equipment, the smoke's still coming off that.

Yeah. How is that not just gonna blow? That seems dangerous to be around there.

Yeah.

That's a lot of confidence in your product, especially for something that like it.

It actually blows up. It. Yeah. Here it is on the drone ship, I believe, just smashing down constantly. This one trying so hard lands and then it's definitely gonna blow. There we go. You know it's gonna blow up every time.

The music.

Yeah, the music's great. I thought they had a different one with all the mountain king. Wait, what is coming off of that? Why didn't they use the chopsticks? Yeah. Tyler, do you Know why they didn't go for chopsticks on this one instead, like originally. Yeah. Yesterday. Can you look up why they didn't go for. For chopsticks grabbing? Because it seemed like they were able to do that a few flights ago. I'd be curious to know why they didn't do it.

This is brilliant marketing. Yeah, it's the yes and this is so good. The yes and blow up just tilting.

All over the place. Why is it tilting? It's not even going, is it just. Well, it's a ship and it's just about to fall. This is crazy. Oh, it actually made it. It seems like this one's coming down. Oh, that was a tough one.

Solid.

Okay, call it solid. It's going sp. You know it's gonna explode. This is insane. So good. Oh, I could watch these all day.

Not bad.

Anyway, on to venture death.

Yeah, let's get into the Journal. The really?

No. You know what's really burning up the timeline? What is the the audience is clearly celebrating. Gulfstream Aerospace says join us in officially welcoming the world's first the world's longest range aircraft to the skies. The first 8200 nautical mile G800 has.

Officially been delivered longest range business aircraft.

To a customer at our Appleton, Wisconsin completions facility. Look at that plane. So let's give it up for Gulfstream Aerospace.

They don't have the luxury of having quite the number of explosions that they said.

They said to join us in welcoming the world's longest range aircraft to the skies. We are happy to join Gulfstream in welcoming the world's longest range aircraft to the skies. Anyway, let's go to venture debt. There are some changes in the market.

Yeah. The Journal has a story. The asset class has shifted to late stage lending as companies remain private for longer venture debt. Firms are shifting their focus to larger deals with mature private companies as more startups stay private for longer venture debt value hit a record 53 billion in 2024, up from 27 billion the prior year and more than a previous high of 42 billion in 2021. Of course, SVB would have been a big player. So it's actually still, you know, given, given, given how significant SVB was in that market, it's pretty incredible to see the growth.

Yeah.

As the value of deals rose, however, venture debt deal count fell to 1300 transactions in 2024, the lowest level since 2016. The trend continued during the first half of 2025 with a little more than 19 billion of venture debt deal volume. According to a separate Report by Capital Advisors Group. Great, great name. Very, very, very generic. But if you can own it, it's powerful.

Yes.

Debt must react to equity, said Stefan Spazak, director of debt placement at Capital Advisors Group. Venture debt providers have have to target stable companies with solid revenue if there is a lack of equity or sponsors decide to pull back on equity commitments to their portfolio companies.

He added, I didn't fully understand this because it feels like there is very much not a lack of equity right now, but is like what is he.

Well, I mean he's saying. I mean he's saying there's hope. That's the big risk, right? If a company is running in the red and they raise their next round. Sure, sure, sure. Get.

Okay. Yeah, yeah, yeah, yeah, yeah. If this, if the current backers aren't doubling down at series C, D, E, F, which is the vast majority of companies like we focus on the companies that successfully raise every single round anyway.

Startups and growth companies are turning to venture debt as an alternative to raising what is often more expensive equity capital. That stands to dilute existing shareholders in an environment where traditional exit opportunities remain heavily constrained. Venture debt providers say credit also allows venture investors benefits such as retention of company board seats which would have to be given away in an equity financing. The quote. Liquidity constraints on the part of venture equity are still a big driver in the market, said David Sprung, the founder and chief executive of Runway Growth Capital, adding that he expects the venture industries liquidity constraints to continue into next year. Runway typically writes checks of roughly 30 million and it lends to tech, health care and consumer. Earlier this year, for example, data and AI company Databricks announced a 52.5.2 billion. You never know with databricks. They Might be raising 52.

52 billion.

Announced a 5.2 billion credit facility shortly after close.

We want to be 50% debt to equity on this company. On this high growth tech company after Databricks. $150 billion company now or something. It's over 100.

Yeah, they just use the. The greater than symbol.

Yeah, that's right. Yeah.

Which is like who's counting it?

The last, the last deal was a $10 billion Series J. That was the Series K. They did.

The K. They did the K. The company said it plans to use the debt for general corporate purposes. The debt financing was provided by a consortium of investment banks including JP Morgan Chase, Morgan Stanley and Goldman Sachs. Let's give it up.

And Blue Al's in. And Apollo Global Stones in.

Just a couple names really.

They really got the Murder.

Technology companies are looking to diversify their capital sources and debt is increasingly attractive as a non dilutive way to fund growth and lower the overall cost of capital.

Says as companies scale and stay private longer, we see significant opportunities to support high quality businesses with flexible credit solutions. Earlier this month, on the smaller side, Runway committed 20 million to swing education, an online marketplace that connect schools with substitute teachers, which is backed by firms including Apex Partners and Reach Capital. Runway's commitment consisted of a first lien term loan and a revolving credit line. What's interesting is like we hear a lot about the venture debt boom in the context of like the Hadrians of the world or like you know, hard tech industrials. Like makes a lot of sense to have relationships with debt providers because you're buying a lot of land or you're buying a lot of equipment and like you want value.

Yeah, yeah.

Even if you're buying. You know when you, when you read about Crusoe building a massive data center, it's like, well of course there's going to be some credit involved because a piece of that business looks like a traditional mortgage and it looks like a real estate deal almost. And so you want a certain, a certain tranche of capital to be focused on earning real estate like returns as opposed to every paying for everything with venture capital.

So since the 2023 collapse of SVB, one of the most active venture debt providers, more lenders have entered the marketers. Stepped up their existing lending, creating a more competitive landscape. Borrowers not only have more appetite for debt, but they now have more choices as well. One firm that has capitalized on the opportunities created by SVB's collapse is longtime venture debt lender Hercules Capital. Great name which typically invests around 40 million in debt deals. The the firm's deals generally have a 15% loan to value ratio, meaning the borrower's loan volume represents 15% of its total value. Hercules is focused on tech and life sciences. Earlier this year, Hercules entered into an agreement with publicly traded biotech company Moonlake Immunotherapeutics to provide up to 500 million in non dilutive capital. At the close There was a $75 million drawdown, with additional tranches becoming available upon achievement of certain specified milestones. Our biggest competition is the equity market. Again this should be obvious to everyone listening, but founders are kind of going out and saying I need, say I need 100 million. Do I want to, do I want to take the potential risk that comes with equity financing even if I'm going to be. Or sorry Potential risk that comes with leveraging debt, even if I'm benefiting from the lack of dilution. Or do I just want to go and raise a fresh primary round? Anyways, good. Good to see the market recover.

The, the thing that stuck out to me about this was the fact that the deals are getting bigger. So venture debt value hit a record of 53 billion last year. The prior year was garbage. 27 billion in 2023. Obviously high interest rates, a major pullback in the startup and venture community kind of healing from the, from the turmoil of like the SVB crisis. March 10, 2023 was when SVB went bankrupt. So it's like, it's like, yeah, of course 2023 was going to be a bad year. 2021, two years prior was up at 42 billion. So we went from 42 billion down to 27 billion, but are now at a new high watermark of 53 billion. But what's changed is the fact that the deal count fell to 1,341 transactions in 2024, which is the lowest since 20.

More lenders doing less deals.

Exactly. Bigger deals, fewer deals, you know, more embracement, more concentration, more focus on the power law winners. And that makes sense when you see all the capital that's flowing into the really, really big companies. OpenAI Anthropic, the Crusoe's of the world that are able to marshal like a lot more capital. There used to be a time in the SVB era where you could go do a $10 million Series A and get $2 million in venture debt and you would just add that on top to kind of build the relationship, build the credit, stretch the balance sheet a little bit more, extend the Runway. Maybe you pay. It was always like kind of it all goes into one cash bucket and you kind of spend it however you want, but. But it kind of set you up to stretch your financings a little bit further. And a lot of companies just by default got on that, on that, on that train pretty early. And I think that SVB leaving the market obviously really led to consolidation. And so we're seeing venture debt go way, way up the stack to, you know, a $5 billion venture, you know, credit facility for databricks.

And if you remember, even a $20.

Million series like Venture debt round, that's.

Pretty big for swing Education Bench, if you remember, got in a rough spot with venture debt and ended up being acquired by that company, employer.com. i guess they had, they were a decent business, but had tripped some. Yeah, debt covenants and were forced to abruptly shut down.

Yeah.

And then they were ultimately acquired.

Yeah, yeah. And that's the thing is like you say, like, oh, well, I don't, I don't give the venture debt lender a board seat. But you know, they do have debt covenants. They do have the, they're at the top of the cap table, even above the preferred. If there's liquidation, they're going to get their money out first. And so even though they don't have a board seat, they do have incredible leverage over the company and they actually have a sort of control that should be definitely considered.

It's very, one could call it senior.

Senior. It is senior. The other interesting thing is Hercules is, is targeting 15% loan to value ratio. That feels higher than what I've seen in the past. So loan to value means if your company is worth $100 million, they would loan you up to $15 million in venture debt. In the previous era, where I was more familiar with this, it was like you would raise $20 million Series A at $100 million. Post the VC takes 20% of the company in a board seat and then.

On low single digits of 2 million.

In venture debt, 3 million in venture debt, like loan to value of like 3%, 4%. But I think this reflects them being more selective about going into companies that are not just post product market fit and have some like VC hype behind them. Like they have a real.

Well, yeah, you don't, you don't, we don't know what the terms are on these 15% loan to value deals. It could be that you need to keep a multiple of the, of the loan on your balance sheet.

Yep, totally.

Otherwise we're going to, you know, require.

And also they probably have done some sort of like private equity breakup valuation to say that, you know, even if this doesn't, even if the company completely plateaus and all the VC's bail, there's still base case. You know, we can get 15% of the value out here as opposed to the, the, the previous era, which was maybe more risk on in the sense that they were backing earlier companies, but in another way more risk off because they were writing so, so much lower.

Jason. Jason o' Connor says this show is like a Buddha statue I have in the background. Hopefully bring in good luck and fortune.

Thank you, Jason. Jason, exactly what we're going.

We're praying for you and your capitalist endeavors always.

I want to pull up this chart on polymarket of SpaceX Starship fully reusable in 2025. Of course, yesterday was a major market mover. It does not look like anyone had any inside information because the market spiked right as the launch was successful. It jumped from 11% chance that Starship is fully reusable in 2025 to 71% now. The market's hovering at 40%. And the rules here are. On February 28th, Elon Musk posted that it was likely Starship would become fully reusable in 2025. The market will resolve to. Yes, if SpaceX or Elon Musk announces that Starship is fully reusable by December 31, 2025. Otherwise the market will resolve. No. So you are, you are, you know, riding on, you know, SpaceX and Elon's comms, which of course will be hotly debated. And obviously there's not a pure binary in terms of what reusability means. Like, clearly, this rocket came down and exploded. They need to rebuild it. But even when it comes down, they still need to swap out parts and fix things. Like they were saying that during this last SpaceX flight, they deliberately took off a bunch of tiles just to kind of like see if they could do it, what would happen. And so, like, you can tell as the rocket comes down, like a lot of those tiles got roasted and so they might have to swap those out. There are elements that aren't reusable, but.

You'Re definitely going to swap out the.

Stuff that was flying around, all the insulation or something. That was one of the wildest, wildest bits that I've seen anyway.

Well, we have this chart here.

Yeah, we have a chart on. We love to trust the experts on this show. We are specifically trusting the experts on the White House intel deal. If you haven't been paying attention, living under a Data center, the U.S. government is now the proud owner of 10% of intel shares. You, you, the U.S. taxpayer now have a small slice of intel, which also means you have a smaller slice of figure Robotics, because apparently intel capital invested in figure Robotics.

If you were worried that you didn't have exposure, you can.

Yeah, yeah, yeah, you can send the layered SPV emails that you've been getting to the archive and just be riding with Uncle Sam on that one. But we did a little whirlwind tour of who is saying what about the White House intel deal. Semianalysis seems pretty bullish. Gave the latest. It gives the us, the last US chip maker, an actual chance to catch up, spur the domestic sector. The bid here is that the intel story with the government is not going to stop here and that there will be some sort of pressure or incentive applied to other American tech companies to buy from Intel. Jordan Snyder, friend of the show over at Chinatalk is also bullish. He says it's Intel's only chance is government support. The US needs domestic chip fabrication capabilities and this is a good path. Ben Thompson has a slightly positive bias. He pulled out the steel man term and kind of steel manned it. He said national security and the economy concerns are too accurate, too acute to not keep Intel Foundry viable. Although he does cite Scott Lincecombe who's extremely bearish and this says this will lead to widespread inefficient capital allocation in the chip sector. That of course is the fear. The Wall Street Journal is also somewhat bearish. Pitting essential US partners Samsung and TSMC against a government owned competitor is a bad idea. I was talking to a few other folks that both they predicted this but they didn't think it's necessarily the good.

Yeah it has ripple effects if other companies are getting the are getting stronger strongly encouraged to use Intel's services.

Yeah it could make those companies less competitive potentially. The Asianometry was constructive on the deal said could make the deal work by using intel as an Nvidia second source and of course this could potentially hurt Nvidia's margins because the CPUs that Nvidia makes I believe at TSMC are probably high margin. If they have to pay intel their margin will fall. But this is a small piece of Nvidia's overall business and so it shouldn't, shouldn't completely upend the amazing business they've built. Of course Nvidia is reporting earnings today and we are looking forward to tracking.

I have a post here from Buco Capital bloke, the third technology brother yes says the fate of the world is in Jensen's hands. Good thing he's a psycho. And he has an excerpt from an article here. That constant kind of relentless improvement looking down at himself. He never rests on his laurels. One guy told me that after a blowout quarter Jensen came into the room and said this morning I looked into a mirror and I said you suck. He does these mental tricks to make sure he doesn't get over because he's so scared. He's a student of history that the big thing for technology companies to start thinking you're hot stuff and then start becoming complacent. He is so scared of that so he tricks himself to not do that.

It's amazing. Yeah. So closing out our trust the experts infographic. Bill Bishop is slightly bearish he says intel fabs haven't proven they can deliver US government ownership in private companies. That's a slippery slope. So we will be monitoring the slope to see how slippery it is. Hopefully it's the slope of illusion. Mint, what is the Gartner Hype cycle again? The slope of enlightenment.

The slope of enlightenment and then the.

Plateau of productivity, the trough. So let us know where you are on the Gartner Hype cycle.

We are working on some more.

We're going to crunch all the data. Maybe we'll throw it in. Julius, of course. What analysis do you want to run? Chat with your data and get expert level insights. I want to know how people are tracking on the Gartner hype cycle.

Yep. Alex Heath just shared a link. So TikTok's parent company is making more revenue than Meta and is worth less than 20% of its market cap. So there's some reporting here from Reuters. ByteDance, the owner of short video app TikTok, is set to launch a new employee share buyback that will value the Chinese technology giant at more than 330 billion. Driven by continued revenue growth, the company plans to offer current employees $200 per share in the repurchase price program. The people said up 5.5% from $189 it each it offered them about six months ago. The buyback is expected to be launched in autumn. And the latest buyback at a higher valuation will come as ByteDance consolidates its position as the world's largest social media company by revenue. With its second quarter revenue up 25% year on year, the jump resulted in the company's second quarter revenue hitting about 48 billion, most of which is is from the Chinese market as it continues to face political pressure to divest its U.S. arm. And apparently TikTok's U.S. operation remains unprofitable.

So the U.S. operation.

Yes.

How is that possible?

Good question.

They have so many ads and stuff and I thought they were taking a big cut.

I think TikTok. TikTok shop is wildly unprofitable.

That's right. We're subsidizing a bunch of stuff there.

Wow.

Well, maybe it's got to go to Jensen. Maybe it's got to go to Oracle. Keep.

Let's give it to Larry. Yeah, I'm in favor of giving it to Larry.

Anyway, if you're going beyond getting your brand mentioned on TikTok, you're trying to get your brand mentioned on ChatGPT. Head over to Profound Reach. Millions of consumers who are using AI to discover New products and brands. AJ over at Semianalysis says feels like the fact that Zuck poached only a small amount of researchers for Anthropic is really under discussed. They have something that really works with respect to culture, mission and values.

And remember Cursor poached the Claude. Two people on the Claude code team, they went over Cursor for a couple weeks.

Yeah.

And then they were back at Anthropic.

I think it was only one week.

One week, yeah. That is a crazy short stint. Droid says the market implied mandate of heaven. I mean yeah, they like the culture at Anthropic is extremely unique. Like they really do believe that they are on an exponential curve. They believe in straight lines on log linear graphs as they say. I was thinking about that quote the other day because if you look at the data center capacity and how pre training is scaling like it is a straight line on a log linear graph, we're getting orders of magnitude improvements every few years and it does seem extremely predictable. Except the last time I was looking at straight lines on a log linear graph it was Covid and that of course like completely flatlined at a certain point because there are only so many people that can get a disease. And so I'm not, I believe in the straight lines on log linear graphs, but I also believe that straight lines can become flat lines on log linear graphs. And we'll have to keep seeing. What do you think?

So then the question is like where are we on the, on the S curve? Yeah, where are we on the S curve?

I don't know. I think we're pretty early. Pretty early? Yeah, I do think we're early but I think that there's, I don't know, there's a number of small percentage chance things that could result in, in like that S curve hitting. Like everything from like bottlenecks in the supply chain that are somewhat intractable. We run out of a certain like bottleneck product that causes a delay in the next oom of data center build out. We could also see some regulation. We could see the business model's not quite like the, like the, the business community could just panic and it could just become a meme that it's like oh actually like you know, we over invested, we need to pull back for a few years. This is what happened during the dot com boom. Like a lot of those fiber investments made sense over a 10 year, 20 year period but they were overheated in the short term and so that just created like a freeze and all of a sudden we didn't get a continuous build out or we did, but we didn't get continuous capabilities. I don't know. We'll see. What do you think?

I mean, I'm bullish.

Yeah.

What do you think about the fact that it feels like model capability is like very discontinuous? Like it feels like.

How do you mean discontinuous?

It feels like we get like we are on a smooth path of bigger models, chopping wood, training things. But only this is the rune take. As technology rolls out, it rolls out in this smooth curve. But then you experience like a few discontinuities with like new capability comes on, comes online where like the ChatGPT moment, like there wasn't really that much. Like if you were just, if you were to just look at the straight line on a log linear graph, like it would be very hard to say like that's the ChatGPT moment because it was really like in between GPT3 and in between GPT5 and in between like you know, like medium sized models, big models and then even bigger models. And you couldn't see there's no kink in the graph at the ChatGPT moment. There is on the user side. There is on the revenue side, but there's not on the actual scale of data center side. It's not like we went from nothing to something on the actual data center build outside and that caused the. So it's hard to predict where there will be new breakout successes along the curve. Maybe that doesn't matter.

I don't know.

Yeah, I mean I don't think it matters that like you're probably going to see another kink in user usage when school starts again and everyone's like, wow, GPT5 is so good because no one's ever used a reasoning model before.

Yeah. Did you see this post about someone said that GPT5 caused like a draw, a major drop off. This is from Marie Martins. The model giveth and the model taketh away. User registrations coming from AI search. ChatGPT was like this huge boom. You see this journey and then GPT5 launched and this is like way deeper in the slides.

Yeah, I saw. I mean there was another like somewhat similar chart that was like going around a couple weeks ago where it was like basically you could like tie it to when like schools. It was like in May or something. Then usage completely dropped off. Do you remember this chart? But then it was actually like, oh, this is just some like weird. Yeah, this is like for one organization it was only like 100,000 tokens. Like, it was obviously not the actual usage.

Yeah. I would be very surprised if we're. If we're at a phase of ChatGPT adoption where, like, the school usage is still, like, a major factor.

Yeah.

Just because, like, the install base is so big, it can't just be students. Right.

Yeah.

And so, I mean, I'm a little hesitant to, like, pull a lot of stuff from that graph.

Sure.

But it seems.

It seems very weird.

Yeah.

I don't know.

Anyway, this is super interesting chart from. For Mary Martins. She is the founder of Tally Forms. And yeah, basically calling out. They were getting a ton of registrations from people just in chatgpt and then all of a sudden dropped off a cliff. So, yeah, there's some debate in the comments around how Chat GPT5 stopped adding UTM parameters to requests.

Oh, interesting.

There could be an attribution issue there, but they're saying.

Yeah, I mean, we definitely want her to zoom out and look at overall registrations and see if there's a fall off in those. Because was this purely additive or was it just, like an attribution thing? And then. And then I'd love to know, like, is this actually, like, affecting her business? Or is. Or is Tally still growing at the same rate? And it's just like, it feels like it's coming from a different. From a different source, but in fact.

Well, it's not impacting. Pop Mart CEO and founder Wang Ning is now the 79th richest person in the world. According to Morning Brew, his net worth has grown by 20 billion this year. It makes him richer than names like Peter Tim Thiel, David Tepper and Steve Cohen Cohen.

Wow.

Labu billionaire.

Labou billionaire.

We helped. We contributed to this by buying a Labubu for Bishops for Bill Bishop's book. So it's on the way.

Bill Tashi.

Yep. Very excited for that one.

Anyway, back to anthropic. Dario was talking to John Collison on Sneaky Cheeky Piped about how he approaches LLM Economics in an interview with. With John Collison. I thought this was interesting. So Dario says, get kind of burned. There's two ways you could describe what's happening right now in the business model. So let's say in 2023, you train a model that costs $100 million, and then you deploy it in 2024 and it makes $200 million in revenue. Meanwhile, because of scaling laws, in 2024, you also train a model that costs $1 billion, and then in 2025, you get 2 billion of revenue from that $1 billion, and you've spent 10 billion to train the model that year. So if you look at it in a conventional way, the profit and loss of the company, you've lost $100 million the first year, you've lost 800 million the second year, and you've lost 8 billion in the third year. So it looks like you're getting worse and worse exponentially. If you consider each model to be a company. The model that was trained in 2023 was profitable. You paid $100 million and then it made 200 million in revenue. There's some cost to inference the model. But let's just assume in this current tunisch example that even if you add those two up, you're kind of in a good state. So if every model was a company, the model in this example is actually profitable. And I thought about this in the context of GPT4. That was obviously, I think that was like around $100 million training run, something like that. And they've clearly made a ton of money back from that because GPT4 is the backbone of something that generates like billions of dollars in revenue. Of course, they've also trained other models that have been used less and maybe were less additive. But this was framed as like, oh, no, this is like a nightmare. Like, he's exposing the truth that like, these will never make money because they're just going to continually invest endlessly. I didn't see it that way at all. This makes perfect sense.

At some point, you could just stop training. The, the question is, can you just stop training new models and just, well, this is profits of old models.

Yeah, well, it's more just like at a certain point, you run out of. You run out of. You kind of tap the capital markets because maybe you can't raise $10 trillion for, to fund the next model on debt or equity or whatever, but there's no reason that you can't. Like in each of these models, if you wait 10 years, you can afford the next run, right? Because you train the model for 100 million. Let's say you were like, I'm bootstrapping a foundation model company. Crazy. But you could do it. Here's how you do it. You, you, you invest $1 in a model. That makes you a dollar next year, $2 next year. Then you take, you wait 10 years, you save up $10. Then you do the $10 run and you expand until you do the $100 million training run. That makes you $200 million the next year. And $200 million the next year. And you know what you have after five years, you have a billion dollars in profit. What do you do with that billion dollars? You train the next model. Then you wait five years, then you train and then you've saved 10 billion. Then you train the 10 billion dollar market.

This is, assumes that, this assumes of course, that you would have a competitive offering in the market and you wouldn't be getting.

Well.

Yes, yes. But, but that is a broader market dynamic of whether the market is willing to put up like currently the market's 100% cool. Putting up $100 million into a foundation model company. There were like 20 companies that raised $100 million to train foundation models. There's only a few of them left. Then those few, a bunch of them put up, you know, a billion to train the billion dollar model. Now you have, who's, who's going to put up 10 billion to do the really big training run. It's going to be a few labs, it's going to be OpenAI anthropic meta Google. Right. As we get to the hundred billion. Yeah, we might have to wait a little bit. We might have to kind of like accrue savings and pay that down over time. And this is another thing that might cause a kink in like the log linear graph if you can't immediately marshal $10 trillion, $100 trillion. Like right now we are in the phase of like snap your fingers in the Capitol marshals, because we're, we're in this, we're in this era where the.

Gains, remember Tropics round was so oversubscribed they ended up, I think, doubling the allocation.

Yeah. And so this could continue for a while.

Concern, I mean, yeah, the concern is that you can't, can't. It seems difficult for even the big labs to do another 10x on, on these pending training runs.

Yeah, I mean that's what Stargate is. Right. It's a $500 billion project. And so that's probably like $100 billion commitment in the medium term. We're getting into the trillion territory. Maybe it continues forever. Maybe everyone on Earth kind of just says like, yes, we're willing to like everyone sell all your gold and convert that.

But I think if you're on Wall, if you're on Wall Street.

Yes.

Traditional finance guy or girl, and you're looking at this and in biotech you might have something where it's like, hey, we need to spend $5 billion developing this drug, then it's going to be good and we're going to be able to sell it for a really long time. Having massively uncertain future capital requirements is going to just be a concern and an asterisk on the business. I think that's like Finn Hub.

Yeah.

That's why people are saying is really the concern here. You have exponentially increasing costs and just wildly uncertain future capital requirements.

Yeah. And so the way to deal with that uncertainty, those jitters, and like the later stage investors who are, who you have to talk to, to marshal, once you run out of masses who are willing to take wild swings, the way to allay their concerns is show them that, yeah, we spent 10 billion and we're making 2 billion in profit in five years we'll be able to pay that. So you can give us the money now to pull forward what's obviously going to pay off again. And we're confident that the next 10x is going to get us another 10x in profit. And so you can underwrite these at any level. Right now, we're underwriting them every single year. We might stretch out a little bit, we might compress, we might go faster.

We'll see. Well, but Dan Ratliff in the chat says Elizabeth Holmes has hit the timeline. She has been posting ripping posts. She quote tweeted Brian Johnson earlier. Brian said defeating death would be humanity's greatest achievement. Elizabeth says, amen. She gives another quote here. There comes a point where we just need to stop pulling people out of the river. We need to go upstream and find out why they're falling in by Archbishop Desmond Tutu. And yeah, she's ripping some comments. She's getting active on the timeline now. This is mostly my words, not her. Right. This is her mostly my words hosted by others. I wonder if she's getting paper printouts.

Of probably over the phone.

She just said she was responding to Brian and said, first they think you're crazy, then they fight you, then you change the world. And somebody quoted and said she's going to launch cash tag, Theranos, Memecoin, isn't she? And Elizabeth says, never. So anyways, having fun on the timeline?

Yeah. Imagine the thrill of having posts read to you over the prison phone and then replace. Okay, yes, like that one.

She said last time signal said, dreams do come true if you put your mind to it. And Elizabeth Holmes followed him. And VC Bragg said, never deleting this app. And Elizabeth Holmes said, last time I deleted the app, it looked different. Where did the little blue bird go? What happened?

This is funny lore. This is like an Odd. It would be weird to be offline for, for so long.

She's responding to an Elon Musk quote saying, for my part, I will never give up. And I mean never. And Elizabeth says this is one reason Elizabeth. This is one reason Elon Musk wins. He never gives up. That's what it takes. It doesn't sound like, doesn't sound like Elizabeth Holmes is giving up either, but she seems to be a big Elon Musk fan.

I have been shocked by the out of Home campaign. Have you seen this?

Which is not Fight Hurts.

Someone is working on a redemption arc for Elizabeth Holmes and justice for Theranos. I think it's a promotion for the new company of some sort, but it's all over. Yeah, there's a new company I think they're outraising, but the, the, the, the billboards are all over la and they've been up for a long time, like months and months and months. It's been crazy.

Anyway, Ben Gilbert says, if you think your app needs more polish, always remember Google Maps. Shift Maps without Europe.

It's awesome.

That is a crazy screenshot.

It's crazy that they didn't even.

Crazy.

Yeah. They didn't even think to put like the rough outline of Europe, you know, and be like we don't have details on it, but instead it's just like you can zoom out and you only see America, the States and England. And we got Ireland in there, of course. Got to keep island in there. Well, if you're building the next Google Maps, get on Linear Linear App. Linear is a purpose built tool for planning and building products. Meet the system for modern software development, streamline issues, projects and product roadmaps.

Travis Kelsey, right after the announcement launches American Eagle collection. Yes, and Michael Miraflor says nothing is sacred. Monetize everything. Let's see. Let's check in on the American Eagle Eagle stock. It is up another 9% today. So they're just on an absolute tear.

Yes, everyone in tech has been focused on the Taylor Swift wedding, particularly what it means for Nvidia earnings. I have a little thesis here. So obviously Taylor Swift getting engaged, that's going to draw a ton of attention towards the NFL. We've already seen the NFL had a measurable swift effect from 2023 to 2024. They saw 9% gain in female viewership year over year. And game level spikes like a 63% jump among women 18 to 49 for a Chiefs game. So imagine this, NFL and streamers. They lean in broadcasters. If they escalate Moment capture, more shoulder programming, alternate feeds, multi language clips, real time highlight reels. What do you need? You need real time media. It's an AI problem. You need clipping, scene detection, player id, small object tracking. All of this is going to run on Nvidia GPUs Globalization. You need translation at the edge.

Another classic speech billion for Jensen.

Text to speech translation. That's an Nvidia product right there. They have a product Riva that does that. Creators pile in. UGC explodes, reaction videos, podcasts, shorts, consumer AI effects, noise removal, eye contact correction, studio voice, increasingly GPU tensive workloads. People are going to be running RTX PCs with Nvidia broadcast software to get to get this stuff. Ad dollars also follows attention incremental audience, especially for the new female demos. This is going to pull premium dollars to sports ads budgets. This pushes ad tech, recommender systems ranking, creative optimization, frequency control. These are among the most compute hungry inference workloads and an Nvidia sweet spot. They have Merlin for recommendations of ads and Triton for serving ads. Stream quality is going to be an arms race. The women, the Swifties, they're going to demand 4K feeds. Platforms are going to race to improve video. They're going to need to accelerate this with Cuda. This means more GPU accelerated pre and post processing in cloud workflows. Sports production is going to modernize. Autonomous cameras. Analytics are a blueprint for low tier games. These techniques climb the stack for tentpole events. More AI in the truck. More GPUs at the edge in cloud. Transcode farms, hyperscale, Hyperscale. Capex is the real lever here. Aws, Google, Microsoft, Meta, they fund the compute behind all of this. Imagine 2026 CAPEX guides. They're going through the roof over. We're going to be in hundreds of billions of dollars just supporting the Swifty demand for NFL content. Powered by immersive. Exactly. And so all this is going to translate into earnings, of course. Showcases durable broad based inference demand in media and ads. Exactly the vector analysts want to see as the AI cycle tilts from training only to training plus always on inference. So that's what the Taylor Swift engagement means for Nvidia's earnings today.

Groundbreaking. Gabriel says this is the music that Keith or boy listened to in 2019 while doing a thousand burpees. And right before logging on to reply wrong to a political scientist posting about Pete Buttigieg's South Carolina polling results. Play this video.

This video. Video is hilarious. In the meantime, while they're pulling it up, I'LL tell you about numeral sales tax on autopilot. Spend less than 5 minutes, 5 minutes per month on sales tax compliance numeralhq.com and you know who's going to need to use numeral? Travis Kelsey's new American Eagle line. If you buy some American Eagle, they said. Inside Travis Kelce's new American Eagle line. An ad with athletes including SUNY Lee and Keon Anthony. The day after it was revealed that Travis kelce put an 8 carat engagement ring on Taylor Swift's finger. American Eagle had announced it had a limited edition clothing line with its sportswear brand True Colors AE X True Colors by Travis Kelce will launch in two drops today and on September 24th. So get ready and make sure that you're paying your sales tax on True htk. Michael Mayflower says nothing is sacred. Monetize everything. Let's pull up the. The DJ that the video.

The video is going to be bad. Almost impossible to find.

Okay. It's deep in the. Oh, they got it.

They did it.

Let's pull it up. Let's play this.

Get the audio, get the audio.

The audio is key. Let's go full screen on this. This is like so annoyingly, I don't know, I was not a fan of the this. Did you listen to this? You think it's good?

Very Reddit coated.

Yeah.

But this, I can't believe there's.

So many people at this putting up with this Mario song. What. What event is this? It doesn't, it doesn't inspire me. You know what we need like drop.

We need.

We need this. You see the, the. It's like they blow this fog around. Look at this. Yeah, those like CO2 canyon cannons for sure. Like that to blow.

Okay, we got something good out of this. Ben, we need the CO2 cannons.

Whatever. Yeah, whatever those DJ equipment are during the lightning round when we're interviewing.

And Nick, can you look into the health impact studio space with CO2 cannons?

This is very David Solomon coded. Yes. You have to be a Mario fan to understand. Yeah, I get it. I don't know if this would be for me in a big crowd, but who knows? Maybe. Maybe it's fun. It seems like they had fun and.

I'm happy for that these days. Not big into paying to be in a crowd. Yeah, that's pay to avoid one.

Yeah, yeah, yeah, that's rough. Anyway, let's go to Will Menitis. He says hard to think of a piece of writing that's had a greater impact on my life than John Ludig's index mindset in 2021. This Pro Index tendency, writes John Ludig, pervades the private tech markets, startups and even our culture through what I call the index mindset. A focus on preservation over creation, optionality over decisiveness, general over specific. Public companies are an obvious thing to index, but the index mindset manifests in many domains. In wealth, you instead of risk seeking expansion, you focus on steady compounding preservation. Venture capital instead of concentrated bets, you focus on deployment pace and irr. In public markets, instead of active funds like hedge funds, which we'll talk about later in the show, we focus on passive funds and diversification. In employment instead of four plus four to five year 10 years and being focused, you focus on one to two year 10 years portfolio building, lots of logos on your resume. In research and development, instead of being radical and innovative, you focus on being incremental and defensive. And in your personal life, instead of spiky and committed, you focus on being well rounded and committal. Internet software companies are far less risky than they used to be, even at the early stages. There hasn't been a venture vintage since 2002 with negative median returns. Big tech is now huge tech. So the VCs are not taking nearly enough risk because they're, they're not losing money. They should there should. Like it is an indictment of the venture community. If there's not a single fund out there that has a negative or a single voltage that has negative returns because they weren't taking enough risk.

Well, it's median.

Yeah. Yeah, median. But yeah and it's vintage. So it's broadly of course there are funds that don't do bad but it's like as an asset class.

Well we might be turning it around.

Anything's possible. Risk averse people money have flooded in. When people have something to lose, they protect their downside. Think of wealth managers encouraging a safe mix of stocks and bonds. The tech industry has too much to lose and I love Will Menaitis has the most chaotic way to highlight I've ever seen. You can just use boxes in iOS if that's where he's editing this but.

He'S just drawing really draws you in. Drawing all over it.

Drawing all over it and then he switches colors at some point. I have no idea why but Ben Gilbert says he's so good and I agree. Shout out to John Ludig. Citrini says time to bust out the no sequel. Negrini Negronis again.

So I think this was a picture.

From 2021 I think so. There was a Tiger Global meetup.

This is when I think it was roughly 30% of all dollars in the venture industry were going to founder dinners and little events like this.

Essentially. Essentially.

It felt like that at the time. They had the no SQL Negroni.

Yep. The Tiger Tonic. The machine learning margarita. The AI Artificial Inebriation special which is.

A non alcoholic beverage.

Interesting. Interesting.

I say bring it back Tiger.

Yeah. I think you could go further. Further. We had to come up with our.

Own little menu of funny things.

We didn't have a menu at our at our event in New York.

This was an interesting screenshot.

This one from the number one AI agent for customer service. Number one in performance benchmarks, number one in competitive bake offs. Number one ranking on G2FIN AI. I will never apologize for cutting you off.

For an advertiser.

For an advertiser. Continue.

Jordy Hayes event Fewer people can bench 225 than are worth 210 million in the U.S. about 0.4% of the population around 1.3 million people can bench 225 pounds globally. The percentage is likely below 0.1%.

Wow.

With some estimates as low as 0.07%. 2.13 U.S. households have a net worth of 10 million or more constituting approximately 1.6% of all households. If you can bench two plates you're already stronger than 99% of of people on the planet. Just maybe not richer. And Zach Voll says what everyone is thinking only job is to do both.

And we firmly both are grind but well worth it. The grind to 225 was serious for many on the team and I think almost all of us have gotten there and are now beyond it's well worth it. Well worth it.

Buco Capital says your stock trades at $59 but we can make it trade at 62 if we manufacture a crisis by changing the logo and immediately change it back to the original logo. This strategy. I don't think this was their strategy but feels like something out of Nathan for you episode and I would. It's hard to properly manufacture a reaction like that of course.

Oh did you so the Cracker Barrel stories in the Journal today. Logo change spawns Firestorm. It's. Oh, Trump said something about it. Cracker Barrel planned to celebrate a fall menu and logo makeover with a festive country music concert in New York City. I had no idea that's what they were planning. But its new logo stole the show and not in the way the company intended. On Monday the company apologized for how it communicated the changes but didn't pivot from plans to keep updating the brand. The chain replaced its longtime logo featuring a man in overalls leaning against a bar, a barrel with a streamlined version featuring just the chain's name. The move engulfed the restaurant in a culture war firestorm, with some commentators online and some customers accusing Cracker Barrel of eschewing its country charm and heritage for a sanitized image. Critics have lobbied have lobbed personal attacks on social media against Julie Felse Messino, chief executive of the nearly 56 year old chain. She scrapped a beloved American aesthetic and replaced it with sterile, soulless branding, wrote the woke war room on X in a message shared by Donald Trump Jr. She should resign and be replaced with leadership that will restore Cracker Barrels tradition. The fallout has shaved tens of millions of dollars from the company's market cap, spawned calls for boycotts and risk the casual dining chains turnaround plan. Cracker Barrel has defended its changes, saying all the all the more campaign was meant to honor its legacy while bringing new energy to the brand. Our values haven't changed and the heart and soul of Cracker Barrel haven't changed, the company said. The new logo, the fifth iteration in its history, is call back to the original one with its barrel shape in word design. On Monday, Cracker Barrel said the dust up over the past several days had shown how deeply people care about the chain.

Trump said on Truth Social yesterday Cracker Barrel should go back to the old logo, admit a mistake based on customer response, parentheses the ultimate poll and manage the company better than ever before. Make Cracker Barrel a winner again. And they immediately responded reverting it back to the old logo. And if you had invested invested in Cracker Barrel and Nvidia exactly a year ago, you would have outperformed buying Cracker Barrel.

Wait, sorry, what?

52% in the last year and Nvidia is up 41.5% well, if you're looking.

For exposure to Cracker Barrel, either either long or short, go over to public.com investing for those that take it seriously. They got multi asset investing industry leading yields and they're trusted by millions. Folks this weekend says Jeff Morris Jr. Martin Casado dropped a tweet that took over VC Twitter. I wrote about it and what being consensus versus non consensus actually means in today's market. Every weekend there's a new hero, says jmj that takes over Venture Capital group chats. This past weekend was clearly slow on the news front because what I initially read as a fairly standard Take ended up dominating my timeline. This is, we talked about this. Martin Casado said the idea that non consensus investing is where the alpha is is actually quite dangerous. In the early stage. Follow on capital tends to be more and more consensus aligned. For whatever reason, this concept triggered a bunch of investors. We're living in an era where consensus categories like AI, crypto, robotics, bio, defense, autonomous systems, manufacturing are big enough to carry entire generations of startups. You don't need to invent a new category to generate massive outcomes. And that is an interesting, that is an interesting take because like there's these are supposed to be like tech investors, Internet investors and yet like consumer and consensus categories include crypto, bio, defense, manufacturing. It's like everything is now, is now like backable. There was an interesting quote in here that I wanted to highlight something about. You can still, yes, you can still find non consensus companies within consensus consensus categories, but at some point calling ourselves non consensus investors is just glamorizing the job. Take American Dynamism as an example. A venture category branded just a few years ago by a 16Z that now feels like it's industry in itself. Palantir in 2003 was truly contrarian. Nobody else was building forward deployed CIA software. Palantir was a one of one company that probably only Alex Karp, Joe Lonsdale and Peter Thiel could have created. Two decades later, it's more relevant than ever with a $370 billion market cap. Anduril was equally contrarian, but for different reasons. 2025 he says fast forward. American Dynamism is a full blown investment category. Hundreds of startups and dozens of funds are chasing defense, aerospace and manufacturing. I live 15 minutes from El Segundo, which has famously become a dense hub of these companies. There was another one in here about D2C and saying something about like that category being even. Even, even that category.

One note here, I was talking with, was talking with a buddy over the weekend and he was like what's going on with El Segundo? Or is it, is it legit? Are these, are all these companies, are they actually going to build big companies and something. Something Jeff says here. My reaction was some. A small number of them will be massive and most will have middling outcomes or will shut down. But that is what our entire industry is based on. And it's okay, but it's still good that we have this excitement and energy and momentum and a center of gravity in El Segundo.

Yeah, there was something in here. I can't exactly find it, but it was basically saying that like consumer is contrarian right now. It's not very hot. Very few people invest in consumer D2C companies, but that's just in Silicon Valley Venture. There are still plenty of funds, both on the private equity side and on the venture side that are doing deals in consumer all day long. Some brands have kind of expanded and shifted away from it, but there still are lots of funds out there that are doing that. It's just an interesting noodling on what stands for consensus or contrarian right now. Anyway, let me tell you about Adeo Customer Relationship Magic. Adeo is the AI native CRM that builds scales and grows your company to the next level.

You can get started for free with a new 52.

Do you want to do this John Woo post series?

Yeah, this John Woo post is great. We should run through this. So John Woo says do not trust millennials to run your brand. Their vision of the way the Internet works was informed by the Web 2.0, Facebook, 2011, Instagram Vintage filters era and their priors have not been updated since. The Internet is no longer deterministic. It's algorithm driven and not even among your own followers. Your posts are constantly being shown to a panel of users. If they like it, the panel is expanded. If they don't, you don't get reach. That means putting out a high volume of post isn't noise, spam or quote. Low signal volume is necessary so the algorithm can pick up your winners and make them viral. You have to experiment with high volume, learn quickly and double down on your winning formats. The cost of failure is zero. The tree falls in the forest and no one sees it.

But the cost of content creation just yeah, but the cost of no one sees the flopped posts.

Yep, the cost of experimenting. But the cost of not experimenting is astronomical. Sure signs of income competence in the attention age. We don't want to put out noise. We need to protect our brand. We need more followers. That's ignorance. Low quality posts are no longer distributed. Follower count doesn't matter. The news cycle is shorter than ever. People will only remember your winners. Pump up the volume. Totally agree. I think if you look, you know, on X specifically if you look at your favorite poster, if you actually scroll their feed, they'll have a bunch of flops.

Yeah, you'll think of a person as like, oh, every time I see one of their posts, it has to thousands of likes. And then you go to their account and you see so many flops. And the real secret is that they're trying a lot of experiments. When the current thing happens, they're putting up every possible variation of the current thing. It's a good strategy. I like this reply by Holland. She says millennials are still good brand builders, but the execution should be left to the terminally, terminally online. And so there is something about like it's probably not enough just to have like pure slop. It's more like you need a seed of something good, some sort of North Star. But the execution in the modern era does require a lot of aggression. Anyway, we have our first guest of the show joining in just a few minutes in the Restream waiting room. We will get to the numerai story in just a little bit. Should we talk about the app mafia quickly? If you haven't been following this, some folks that we're familiar with, one of them who did PMF or Die had put out a course on how to build an app that makes money, don't raise venture capital. They sort of took over the timeline with a viral video showing them driving Lamborghinis. Kind of all the, all the classic hallmarks of the, of the guru that you previously found on YouTube with here in my garage, that guy and folks on Instagram. Sort of the first time we really saw it on Twitter or on X and it caused a lot of, you know, people, people going back and forth. Harry Gestentner. I don't know how to pronounce his last name, but Harry says apparently I mentioned in the first few minutes of the app mafia course. So here are my thoughts. I went to college with Blake Anderson and no Zach and Hunter too. There are a lot of threads going around about profit margin, et cetera. It's not, it's not that relevant given these kids are clearly netting a minimum six to seven figures probably for the first time in history for anyone that age. This represents a major shift in the education system that platforms like WAP have pioneered. People are talking about audience iq. This course is clearly targeted at kids slash younger founders and certainly something I would have loved 10 years ago. It also represents a shift away from venture backed consumer apps dying from over raising hundreds of apps like Headspace Calm raised eight to nine figures and were stuck with companies that couldn't quite IPO but also couldn't cash flow for the founders. There's entitled socialist mentality of quote why do I have to pay? The reality is if it's free it's not very valuable. I have watched the, I haven't watched the course but these guys are extremely sharp and can provide value to young Founders, they. So they deserve to be compensated for their time. Now there's a wrinkle where the course is now free. Is that right or is now free?

Okay, so, you know, I think they, they. The original video was, was, in their words, designed to elicit a dramatic reaction. Yes. Designed to bring out hate. Right. They're sitting there in a mansion.

Blake loves poking the bear of the algorithm.

Yeah.

Like, he, he's very good at that and very deliberate about that.

But yeah, it is fascinating. I mean, and then immediately people piled on him, were saying, like, oh, the apps must not be making a lot of money, otherwise why would they do this? Which I didn't. It seemed obvious to me why they wanted to do it. They want to build their personal brands. And this is like a business model for building a personal brand. Yeah, it's a.

What's interesting is I don't think I ever paid for a course on specifically on like entrepreneurship or something broad like that, but I have paid for courses on like, very specific technologies. Like I went to a, like a boot Camp for iOS development where they taught us Objective C for two days straight. That had like a real cost and I was able to expense it against the business. I also paid for like a course to learn Houdini, a particular visual effects software. And that kind of had. I thought it wasn't like a get rich quick scam at all. They didn't make any promises. They just said, hey, we're going to teach you the software. We're going to teach you the thing. And so buying books is great. Buying courses on specific topics is great. Lots of what you can learn about entrepreneurship is just available out there for free. You can read Paul Graham's blog, you can listen to Founders podcast. There are plenty of resources. Maybe this is useful. You'd have to try it out now. It's free, so you can make your own decision. Anyway, we have our first guest of the stream in the tvpm.

Welcome to the stream announcement.

Josh, good to meet you. How you doing?

What's happening?

Hello.

Good to see you both.

Hi, John.

Hi, Jordy joining the group.

You sound fantastic today. Whatever microphone you have hooked up is.

Working flawlessly similar to what we have here. Congrats on the news. Break it down for us.

Yeah. So I'm Josh head Augusto. We love serving small business. We've worked with a company called Guideline for a number of years. Close to 10 years at this point. And the news is that guidelines. We are joining forces. Guideline's going to be joining Gusto.

Amazing Amazing.

I think I've actually used Gusto and Guideline together for my entire career.

I've used Gusto at four different companies.

I started in college.

And we have an employee sitting over there that wants a 401. This is.

You have no excuses anymore. Time to set up.

Yeah, talk about the pre history here. The company's been, what was it, YC 2013, 2012 or something? I remember 2012. 2012. Yeah. I remember implementing it at my YC company in 2012, back when it had a different name. And I remember that for a number of different HR functionalities, I would have to kind of go to a different platform and then the data would be fed back. What informed the strategy back then and then. Why are you shifting it? It seemed like it was working for a long time. So why kind of, what is it? Horizontally Integrate, I suppose is the term.

I don't know what all the business is. We just try to make the life of a small business owner easier. But yeah, first off, I mean, thrilled to serve you and your companies and we're always trying to get better. So send me feedback on how we can get better, by the way. But yeah, no, I'd say go way back. We launched Gusto back in 2012 and our first product was Payroll. If you don't pay someone, they quit. So it's the least optional part of the stack. And so we've made progress there. You know, we serve over 400,000 businesses. We love helping tech companies, but I love businesses. There we go.

That's a lot of businesses.

But I also love reminding folks there's more dentist offices in the US than tech startups. So like very focused on that mainstream small business. And yeah, to your point, we listen to customers more than anything and they guide us. And so they told us, hey, there's all these other pain points we want your help with. Our second product was health benefits, but we're not going to build everything ourselves. And so when retirement came up, and generally speaking, what we like to do is take stuff big companies have and bring it to small companies. So from almost a fairness lens, it's like we need to bring great retirement benefits to these small businesses. They deserve it. And that was basically kb, one of the co founders of Guideline. It's kind of a funny story. He was previously the co founder of TaskRabbit. And so back in like 2015, we were in the same building. They were on the second floor, we were on the sixth floor. And there was a slow, slow elevator, like the slowest elevator you've ever seen. And so we would sometimes just be on these long elevator rides and that's how we got to know each other.

I was going to ask, when did the conversation start?

Yeah, people say you meet there, you meet your acquirer, like years before. But in this case, what they don't say is in a very slow elevator.

You'Re gonna hang out for minutes at a time.

But yeah, to answer the heart of your question, we started partnering with them right when they launched in 2016. And yeah, there's an integration. You can kind of connect the two systems. Like, we have tens of thousands of shared customers. Kb, I can say this stat very proudly on his behalf. Like over 10, around $10 billion of retirement savings in the accounts of our shared customers.

Let's hit the size for that.

I mean, Jordy, you hit the gong. We like to hit the gong around here for big numbers. Congratulations.

I like it.

I like hitting the gong for retirement funds.

Yeah, yeah.

I mean, that's, that's again, that's their people's money, that's their retirement peace of mind. But yeah, what we realized is there's a couple things happening. One, we can do even more together. So we're going to continue to partner with third parties on other products, but especially with 401k in retirement, like, we're going to really go deep. And that's what Guideline has done. They're a broker dealer, so there's all these different parts of the stack where if you cut up, you can create better cost savings.

I'm sure you had investors along the way that said, you're sending so many customers to Guideline, why don't you just build this? If you need more capital, we'll provide it. Why did that not make sense? And why, why buy versus build in this situation?

So I think all options are always on the table when you're building a company. Buy, partner, build. And for what we're doing, it's going to be a lot of connected problems. So how do we bring it together as one simple, easy to use product is the key. But I'd say, yeah, the catalyst for shifting from partner to being one company is there's just product stuff we can do that we can't do unless we're combined. I can give you a couple examples if that's helpful.

Yeah, please.

Yeah.

So like the journey of building a company or the employee journey, we think a lot about kind of the person by person, what happens in their life. But let's say someone gets promoted, right? And they get A pay increase. So that's obviously coming through our system because it's going to affect their salary. And in that moment, right, whether it's in the app or in an email, the hey, you now have more money coming into your pocket, your choice. But do you want to set aside a bit more in your 401? Or someone has a kid in our system that's a dependent, but that's a human being, someone just had a kid, right? Maybe you want to go do something there in the context of retirement planning or something related to health benefits. Thinking through the person by person journey piece of it. There's just things we can do that we think will drive more folks offering retirement benefits. There's also a compliance reason too which I can get into.

Let's get into it. We love this.

So like government, right? We're here to like abstract government and sometimes there's carrot stick that government does. So 401k is a good example of a carrot. Like it's pre tax dollars. So literally the government is making it hopefully a no brainer to like put aside money for retirement with meaningful amplification of that money than just, you know, putting it post tax. But they also have compliance requirements. I think over now 20, close to 25 states have rolled out what's basically a mandate that businesses have to provide some type of retirement benefit for their teams. And so that's good intent but it's still stressful because there can be penalties or fines. And so we're also excited that basically we can give peace of mind to more small businesses so they're not stressed out, definitely not getting fined or penalized. And if they want to or need to set up a retirement benefit, we can make it brand dead simple through Gusto plus guideline.

What's the anatomy of a partnership look like in this category? Pre acquisition merger. We were talking a few days ago about the relationship between Apple and OpenAI and we were kind of like wait, like should Apple be paying for the right to have good AI on their phones or should ChatGPT be paying because they did all these extra queries and we were kind of. And I think like the rumor is they netted out to be like there's no money transferred. And I could imagine that sometimes that comes up. Sometimes it's like hey, I'm getting you customers, you got to give me a fee. Like what are the structures? Do you have companies that are in one camp and the other or can you share anything about the relationship beforehand? I'd be interested to know just like, channel sales is something I'm, like, learning about now.

So the first thing to start with is Gusto's entire engine of growth. You know, here's another metric. We can tee it up, but we're going to. We're on track to add about 150,000 customers this year.

Year.

That's a whole. No, Is that businesses? That's small business. Wow. That's a lot of businesses. Yeah. Yeah. Okay.

And so you're talking some guys that absolutely love business. So this is fantastic.

The best news I've heard all day.

We can get into our whole, like, what is AI going to do on the world Tangent if you want to. But yeah, we'll come back to that.

Yeah, yeah.

So basically, like, we are an engine to go bring in more and more small businesses, especially new employers, folks starting out. If you don't pay someone, they quit. So it's right off the bat, like an important key thing for you to do if you're building a team or adding even your first employee. There's a lot of folks, as you can imagine, that would love to distribute through Gusto because of the scale that we're at. What that looks like first is not us starting with the partner, but starting with the small businesses and finding out what are their pain points, who are the products, what are the products they like or want to use. Already they're voting with their actions that come in through our integrations. And then we do a lot of vetting. So think more Apple approach than Android. We want to make sure quality, experience, accuracy, reliability, and then like just this obsession with user experience comes through of whoever we're working with. And then, yeah, we'll do partnership deals across multiple product areas. Time tracking is another example. Sometimes we'll have first party. Like, we'll do our own product and still have best of breed, third party. And then that's a negotiation. There's usually, if we're going to drive a lot of customers to someone, there's some type of rev split because we're creating value for them, there should obviously be value for us.

Yeah, that makes sense.

What is your guidance for? A ton of startups sign up for Gusto today. When they're one or two people, it's just the founders. And what is your kind of framework for the right companies to use Gusto? Because again, companies today, they might start with a couple founders today and be 30 people in six months. Right. These things happen.

We got a vibe code, our own.

But how do you got to rip.

This out and vibe code Our own.

Are you counting the AI agents as people are not, is my question.

Yeah, that's a good question. But yeah, how are you thinking of serving startups as of today? It's obviously from my understanding, a lot of where you guys started, but it's always evolving.

Yeah.

I mean, as a quick backdrop, you're alluding to it, three founders. We all started here in Silicon Valley, we went through yc. I was born and raised here. My parents aren't from tech though they came from. My dad was a teacher, my mom was a teacher.

Same here.

But we are physically here. Oh yeah.

Where did you teach in high school? That I went to high school.

My dad, my dad's had high school.

Very cool. But yeah, it was funny. I don't know if I asked my dad this, I don't think he would have had a great answer, but I do remember asking somebody back in the day, how do I pay myself? I had a company starting to make money. I was like, how do I pay myself? And they're like, oh, you just set up gusto and you just onboard yourself. And I was like, oh, that's cool.

Well, we love serving small business. Obviously tech startups are a part of what we do. We love serving them too. I guess from a target customer Lens, broadly speaking, one to 100 person companies is our sweet spot. That's 98% of the employers in America. But I always love. Also, it kind of blows people's mind usually. There are 6 million employers in America, give or take. Two thirds are less than five employees. Two thirds are less than five Employees. So whenever I meet a small business owner and there are three people and they say I'm small, I'm like, no.

No, you're not small.

You're like the common business owner in America.

You are.

Yeah, the average.

Yeah.

Well, quick thoughts on AI because you alluded to it earlier.

Yeah, I'm interested in, I'm interested specifically in how you think about surfacing AI. Like do you want to put a chat box in front of someone and then that's an interface to all the deterministic workflows you've built? Or do you want to just turn AI loose within your behind the scenes development team and have flows that are working just to improve things, reality check things. Like you're probably using machine learning for fraud detection for years. Is it an evolution of that?

There's a product manager inside of you? I would say yes to both. And more so like we do a lot of complex kind of backend processing of either money Movement, filings, documents. There's a lot of ways to use AI tooling for productivity there, so that's great. And we've always used technology for how we scale, right? Like, we serve over 400,000 customers today. That's only possible through using a lot of software, but from a customer experience lens, actually, again, both. I really think there's this massive understatement here, but paradigm shift around how we use software and how software helps us. When I got into software in high school, what I loved about it is it felt like it gave you superpowers. And then every time I saw books on how to use a tool or I learned someone would brag on LinkedIn, I can use this tool. It really, really annoyed me, because software is not something you should have to learn how to use. It should just work. It should just make sense. It should be intuitive. It should give you superpowers. So conversational interface, I think, is going to be a pretty. Again, understatement, but much more accessible way for a lot of folks to use software, and it'll work in combination with web workflows and stuff like that. So we have a conversational interface for Gusto called Gus. And to your point, it can take actions, right? You get it, you get it. But, like, you can, like, set up a shift schedule. You can go run payroll. Like, you can leverage all of our APIs that we've spent 14 years building. And Gus can do stuff for you, not just give you information.

Funny story. My dog's name is Gus Gustavo. And I have a friend who could never. He was so into B2B software, he works in the B2B software industry that he didn't understand that my dog's name was Gustavo. And for a long time, he would call him Gusto. I was like, I didn't name my dog after the software platform.

Well, I have one.

Speaking of dogs, Bill Bishop is in the substack stream from Cynicism, Cynicism. And he says he's a happy Gusto client. So you have another fan listening right now.

Thrilled to serve you.

I have one question, and I'm curious. When I got onto Gusto back in the day, it was close to a decade ago. At this point, I was. I was confused that I had to hit the button to run payroll.

Oh, yeah.

This is not a payroll platform.

Yes, yes.

Why do I have to. And I remember there was a couple times that I would get an email, and it'd be like. I'd be like, you're like, you need to run payroll. Now. And I was like, why? I think you do. You can't automate it now. But is.

Yeah, yeah.

Is there. Is there kind of a generational divide there in some ways where there's like a generation that understands. Understands. Like payroll is something that you hit a button and you run it versus payroll is just something that is just humming.

At the first startup I ever interned at, the CFO hated me because I would always turn in my timesheets late and he's like, I need to run payroll. And I'm like, just pay me the same every month. I'm fine. You can just put it on autopilot. And they're like, autopilot doesn't exist. This is 2006 or something like that.

So we rolled out autopilot for payroll back in, like 2013.

I remember using it. It was fantastic.

But it was. Yeah. So the key, the difference here between both of your use cases was if you have nothing to input. So if it's like, let's say all salary versus some hourly and. Or like no one took pto. But again, there's inputs that go into payroll. Now, assuming that's all there, it should just work. And that's the way it does work way back when. This is now 2013ish. We have Penny. The pig is kind of our part of our company, kind of brand culture, mascot.

I can see Penny and Gus potentially beefing over who's the most important.

I mean, they're friendly with each other. There's a friendly competition. But we had to have the gif. It was a GIF for running payroll when you clicked run and it went too fast. And we had customers back then go like, it can't be that fast. Something is broken. So we had the GIF just run longer for the sake of it. Just to make people be like, hey, there's actually hard processing happening behind the scenes here. And the world's come a long way since then. So people expect stuff to be fast, simple. We want to automate. I mean, a good example is 401K. So if you want to go change the contribution that's being made, that can now be done easier by us being one company. But yeah, we think eventually payroll becomes something like flowing water. It just works and you don't have to do much direct action yourself.

Fantastic. Well, thank you so much for hopping on chatting.

Acquisition makes a ton of sense and congrats to both teams.

We'll talk to you soon.

Yeah, and make sure you give that teammate a 401k.

We will set it up.

It's happening.

Have a good one.

Thanks.

Good to see you. And we have Keller from Zipline in the restream waiting room. Big news. Zipotle is now live. Chipotle partners with Zipline for aerial delivery.

What more could go? Keller, welcome back. Keller, welcome to the stream.

How you doing?

Even more dramatic background this time.

Every time you deliver. Thank you so much for hopping on.

That's our job, right?

Yeah. That was unintentional. Anyway, how did this come together? It seems like the perfect partner. Walk us through the evolution. Actually, what went into the announcement?

Yeah, I mean, we've been talking to Chipotle for a while. We obviously have announced a few other restaurant partners. I mean, you know, for reference, like, there was a time in my life where I lived on Chipotle. Like, that was my priority.

Every entrepreneur has, like, a Chipotle, Chipotle era.

Raise your hand in the studio if you've lived on Chipotle. I think everyone's.

Yeah, you're getting more. It's just a period of your life where you're getting more calories from Chipotle than anywhere else.

Oh, yes, absolutely.

I can distinctly remember those moments.

It's the base of the pyramid. I also remember. I also remember. I feel like you guys would appreciate this. You know, there was a time when I was living out of my car, actually, and, like, eating Chipotle and, you know, $10, you could get, like, two full meals out of it.

Then you could get, like, the tortillas, too. Those were three. That was a hack.

There's a lot of optimization that you can do. And I remember thinking that, like, one day, I will know.

Like.

Like, how will I know if I'm rich? I will be able to get the guacamole every time without feeling guilty about it.

I have the exact same story. When I went through YC in 2012, my business partner, my co founder, would always get double meat. And I was like, we're trying to save money. We don't. We can't afford double meat.

Get double beans. Double beans are free.

He was tearing us apart. And then I finally just defaulted to, like, look, if you're gonna get it, I'm gonna get it too. And we will both fall on the sword of higher burn. And to this day, if I eat.

We call him moral hazard.

Yeah, moral hazard. But to this day, if I eat out with him and we're at a restaurant, I'll just be like, get whatever he gets. Cause I know he's gonna get something ridiculous. And he's getting the most expensive thing on the menu. And at least then I get stuck with the half of the bill and I'm happy and I'm not like, oh, I got stuck with paying for his expensive thing. Anyway, congratulations. We love Chipotle. What else can you share about the progress of the business? It's felt like classic overnight success, as we love to talk about on the show.

Also, how did you get them to actually name it Chipotle?

That was their idea. That was their idea, not ours.

That's amazing.

I think, you know, look, I think that what we're, you know, obviously there's this, like, big transformation coming in AI and robotics, and there are a lot of, you know, very fancy hyperscalers that get talked about all the time. But the reality is that, like, all the basic businesses and brands that we use and love also want to be able to take advantage of this kind of technology. And so I think a lot of, you know, some. Some of the biggest brands like Chipotle are asking themselves, like, hey, how can we use robotics automation to accelerate or dramatically transform our own brand and the kinds of experiences we can provide to customers? So, yeah, them choosing Zipotle, us starting to deliver for them. I think that we did a delivery in five minutes yesterday from order made to the thing arriving at a customer's house. That's not possible every time. Just to be clear, it does take time to make the food, but I think that something showing up super, super fast like that. In fact, we've found it has been necessary because we've only started really rapidly scaling these food deliveries in the last couple months. It's actually necessary to tell customers to slow down and make sure to blow on the food. We've had people accidentally burn themselves.

Good problem to have.

It's like a weird. Yeah, weird thing, right? People are just used to it being cold or smush. Yeah. Just not that great. So really cool to see that starting to scale, especially for a brand that's, like, very near and dear to my entrepreneurial journey and heart. I mean. Yeah, you know, other things that we're seeing, even since we were last talking, which I think was like, I don't know, 10 weeks ago or something.

Yeah, a couple.

Couple months ago. We have seen, you know, a problem that we were having in July was that the service was growing extremely fast, between 25 and 30% week over week in terms of flight volumes. And in fact. Yeah, like, so, you know, Saturday, new record high flight volume. Sunday, we actually beat Saturday by 20%. This is just two days ago yesterday, you know, Monday was a record day, Tuesday was a record day.

Really cool.

If you keep, if you keep giving us records, I'm going to keep.

Cooler with the record.

No, but even, even cooler is that, you know, right now the service has a net promoter score of 94. So you know, no, not very few services in the United States are close to that today, let alone delivery services. Customers are ordering, a lot of customers are ordering like three to four times per week. In fact, we have many customers who are ordering a couple times a day via this service. I think that, you know, when you realize you can get stuff in five minutes, it actually starts to change the way that you kind of live your lives. It's giving people back like three or four hours a week when they can just be focusing on their kids or on their family rather than like stressing out with traffic and trying to get somewhere. At this rate, in a couple of months our deliveries in the US are going to exceed all of our global flight volume across eight other countries. So yeah, the US is growing super, super fast now. We're launching a new Walmart super center every week at this pace. It's just, yeah, it's, I think, you know, I think the moment for automation and autonomous delivery has arrived.

So is, is Walmart, it's a 10 year overnight success. Should I think about the expansion as driven by go where the Walmarts are and then talk to the city officials to get support and Walmart's kind of like the backbone or is it more like find other cities like Dallas Met whether they're in Texas or not and then partner with companies and businesses that are in those kind of friendly cities that understand the value that this can bring and the demand and then, and then kind of roll out that way. Like is there a particular path that you're taking? Like how should I imagine the map of zipline growing or the coverage map growing over the next few years?

Yeah, that's a really prescient question. I mean Walmart has been a key partner. We're building a lot of charging infrastructure across these metros. With them we're also building independent charging infrastructure that's just designed to serve a lot of different customers at once. So for example, we just opened a big charging site in Rowlett. It's a small city inside a small town inside Dallas where like that one site is going to be able to serve, I think upwards of 40 or 50 restaurants that are all within range. And then from there we can deliver out to customer homes as Long as they're within 10 miles. So like, one key thing to think about here is it's kind of a network optimization problem. But we go a lot farther than normal delivery. You know, where you have a human driving a car wants to go any. From any given restaurant, you can typically reach 10 times as many people via instant delivery as as via traditional deliveries. So. And again, you know, ten times as fast. So we're really focused on going metro by metro right now. A lot of our costs, you know, maintenance kind of happens on a metro basis. So we're going to go tall. Like the goal is to go very tall on each metro. We have a lot of metros now that are like super, super excited and basically on the roadmap for us to launch. And we're trying to build the capacity and launch them as quickly as possible. But building this kind of infrastructure across the U.S. it's a big undertaking. The other cool thing to mention, just really quick is that one thing I'm very, very proud of, more proud of every day. I mean, zipline now has 120 million commercial autonomous miles is the largest commercial autonomous system on earth. Zero safety incidents. That's the main point. Zero safety incidents. Actually, if you just look at the basic safety of cars globally, the system is already provably about 10 times as safe as cars in terms of fatalities or injuries. And you know, from that safety perspective, I mean like Zipline is actually right now about. We have already achieved a level of safety that is 2x the goal that we had set by the end of this year. So like again, safety and reliability is kind of everything. It's like core of what we do. And it's a big part of like why I think cities are starting to understand like this is a incontrovertibly good thing.

Is this a problem for Pizza Hut? Pizza Hut, famously the buildings are huts. You can't land on the roof. How are we going to get pizzas from Pizza Hut?

In important questions.

The important questions. But, but seriously, is there.

I thought you were talking about the size of the pizza.

Oh, no, no, because actually I want to know.

We are working with.

You are working on a pizza compatible.

We just, we just cut it in half.

Okay.

Oh great. Calzones. The company.

Yeah, we already have, we already have the box design for a couple different pizza partners. It works great.

Should, should, should franchisees be thinking about a flat roof? Is that relevant? What does the actual infrastructure look like? As and like, should. Should restaurants and businesses be thinking about zipline compatibility as they roll out the next like version of their, of their retail infrastructure or their, their residential plan or the real estate plan.

Yeah, so it's pretty cool. I mean, first of all, one of the things we announced just in the last couple of months is something we call zipping points. And zipping points are really simple infrastructure. We pay for it, we can drop it in two hours. It does not have to be permitted. There's no construction. As long as we drop a zipping point with a restaurant or a retailer or a hospital or primary care facility, they're instantly enabled with zipline delivery.

Got it.

No power, no permitting, nothing. Do not have to do anything for the building. Interestingly, we are talking to like a lot of hotels, a lot of apartment buildings, and a lot of even these restaurants as they. Because, for example, a lot of these big restaurant brands, they'll only have like two or three or four total designs of buildings that they'll build. And they are in fact now starting to take into account zipline and they're starting to design specifically for autonomous delivery. You don't have to do that, but you can. You know, one big point I would make here is that like the thing that blows my mind, I mean, starting to see this like exponential takeoff from a demand perspective. I would emphasize, by the way, we freaked out enough about demand four weeks ago that we turned off all marketing, all demand generation marketing in the company. We turned off all the in app notifications, we turned off all the field marketing that we were doing. And it basically made no difference to grow 25 or 30%, you know, week over week. I think that the reason this is happening in retrospect is kind of obvious, which is, you know, we're now starting to deliver to a lot of offices, we're delivering to a lot of apartment buildings, we're delivering to universities. Like, I think the product is more viral.

Yeah. When you think about the virality of the product, I mean, sure, this is already happening or will happen, which is if.

How can you not tell me a story about this?

Yeah, my brain goes to some guys at a fraternity, order 30 rack gets dropped into the backyard. And I don't know if you're doing that, you're probably not doing that yet. But that is a very viral moment that people will be taking videos of for a long time.

They'll, you can see, I mean, tons of people are doing TikToks and a lot of those TikToks are getting seen like 7, 8 million times. We were actually initially asking customers to not like, you know, put stuff on social just because like we wanted a chance to do an early access program and kind of like, you know, iron out the kinks. But yeah, even, even people who aren't customers are sometimes like videoing their neighbor or getting a delivery and then putting it on TikTok and having it get seen millions of times.

So it is cool, amazing stuff. Always, always great to chat with you. Shout out to Danielle, your whoever's running your comms program because your remote, your remote call in setup I think is the best of any.

Fantastic.

This is, this is the main, I mean this is the manufacturing line. So this, this line is ultimately capable of producing about 55,000 aircraft a year and that's scaling to that as fast as we possibly can.

That's so many.

We have to learn how to build drones in the U.S. yeah, yeah.

I'm very excited doing it. Thank you. We will talk to you soon.

Have a great day.

Always welcome here anytime.

Talk soon, Kelly. All right, cheers.

Talk soon. Thanks.

Up next we have eight sleep dot com. I get a Pod five Ultra. I put on a clinic last night. Jordi Pillai, my favorite soundboard cue.

I got a 90.

Oh, good for you.

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I'll be right back and I will talk to Will. How you doing?

Hey, how's it going? Great to be back.

Jordy just plays a sound cue and steps away. What's new in your world? Just. Yeah. What's the latest?

Yeah. So about half an hour ago we did a big launch of something we've been building for quite a while at Prime Intellect. So for those who are not met me. Hi, I'm Will Brown. I work at Prime Intellect for a open source research company as well as a compute platform. And we've released something today called an environment hub, which is for RL environments as well as evals. And it's something we've been kind of working towards for quite a while. But I think it's also something that a lot of people are talking about but also wondering, what does this even mean? I saw over the weekend Google trends for RL environments shot up and you guys had made some joke tweets about this recently that I thought were great about Ender.

That's not an RL environment you were in. You place real Amazon orders. It perfectly encapsulates My level of understanding here, so I'd love to go deeper. It feels like a bull case for distributed infrastructure generally because we're maybe like, maybe it's additive, maybe it's replacing, but certainly less of the focus is on like get 100,000 H1 hundreds in one single cluster. There's more to be done in different places. But try and concretize it for me a little bit more. Like, what is an RL environment? How are they being used? What are the trade offs in terms of compute and design of the infrastructure that actually deliver some sort of valuable product at the end of the day?

Sure, yeah. So I think we can get to the distributed aspect of it. But just like first, I think like an environment is essentially it's an eval. Like a lot of the things people make as like popular evals like Sweep Bench or ARC AGI, these are environments, they're a thing where you have some input tasks, you have some harness and then you have a thing at the end that looks at what your model or agent in the harness does and then says a score at the end. This is the exact setup we use for evals, but it's also what you use for RL training. When people are talking about, oh, we're going to make a bunch of RL environments, what they really mean is they're making evals that are designed for agents to do some task interactively.

Yeah. Is the Amazon order like we saw that report that some folks are building like full digital replicas? I mean, I guess it's already digital, but like a, like a, like a simulated environment of Amazon.com or DoorDash?

Yeah.

Are those kind of the power law opportunities that people are really focused on? What are some other examples? Are people building these environments for like, you know, old enterprise software systems that people want agents to interact with. How wide is the scale of RL environments right now?

Yeah, it's pretty huge actually. So I think there is these kind of flagship website sorts of things, but I think there's also a long tail of increasingly niche applications that go down towards these very fine grained, narrow things, all the way up towards broad domains where models really struggle because we don't have a good interface for them. Like it's Excel is one of, it's like everyone uses Excel, but like no one is really like an LLM power user in Excel because it doesn't integrate very well. No, we don't have the cursor for Excel yet as a broadly deployed thing. Yeah, I think it's easier to have an environment for a terminal or for a coding agent because the harness is a little simpler. And so that's one sort of thing you'd want as like an environment. And that's one of the sort of things that like the mechanizes of the world imagine are like building these sorts of things.

Yeah.

I'm sure that like the labs all have their idea of what tasks their customers want models to be better at. They're currently not being used for as well as just what sorts of products are people trying to build. So you can build the greatest agent harness in the world, but if your model hasn't been trained for it, some models might just not be very good because it's not very ergonomic for them. And so you can think of environments as a way of taking a model, having an interface that you really want your model to be great in, like a harness and then just like a feedback loop that lets it get better at being a model or agent in that harness.

Yeah. Help me understand the Excel case more specifically. Copilot exists there. We're hoping that Microsoft rebrands it as Clippy eventually. But there are also like seven different startups that are building, you know, cursor for Excel. Help me understand the context of verifiable rewards and what that would look like in Excel. Because if I, if I'm trying to do an analysis, I'm trying to understand a company's financials, build a dcf, like there are templates, but then to actually get the correct valuation, that's something that like even if I have the perfect DCF and it tells me that Nvidia is worth 5 trillion, like I can't verify that against the market. I could wait a year, but the DCF could still be right and the market could be wrong. So like what does verifiable reward look like? What are people actually building towards in that environment, you think?

Right. Yeah. So the easiest recipe, which like we've done work on as well as I've seen a lot of papers about this and it also just kind of like the obvious. Only real thing you can do is have a correct answer where it's like there is a gold standard, like someone made this easier and we. The agent doesn't see the finished one.

Sure.

And it's like new enough that it's out of the training distribution from pre training, like past six months is perfect. And then you want to train your model to be in the harness where it could make the DCF and then look at what it produces and Then you have all these different things you can check. Did it get all these fields right? Those evaluations are a combination of vibe checks, spot checks. When humans are looking at it for like this is how people have been doing historically. You build a thing, you try it out, you look at it, you try to make a list of what's wrong. And that doesn't really scale. And so to scale it you need to automate this valuation trunk where you want to have a thing that comes out like a dcf, a spreadsheet or a paper or a piece of code and have a way of programmatically checking this. And this checking usually is going to involve LLMs in the loop. Maybe fine tuned LLMs or customize LLMs for grading whether the thing has been done correctly. And then this like you got to iterate on this meta process a bit to have a good grader and see like, does the, does the result of your grader match your human vibe? Check your spot check based on having some kind of experts in the loop. But what you then want to do is take that kind of evaluation process and freeze it as a kind of piece of code. And now you can plug this into your harness. So the harness plus some like input tasks of like, do this for every company and you're like gold standards for every company of like what a report should look like made by some analyst. You're grading against like the golden answer. And now you scale this up.

What was industry standard before you rolled this out? Would the actual AI researchers or AI engineers who were going to do reinforcement learning on a model in a particular domain actually design and implement the environment with the reward all internally and it didn't exist as an external function whatsoever. Was that the status quo in terms.

Of open source infrastructure or the. In terms of like broadly. Very few people have been doing this. The amount of people who have successfully trained a large scale agent model with reinforcement learning is very small.

Yeah.

It is not broadly deployed. Like the companies that are like on the periphery of maybe doing it are like curse red perplexity.

Yeah.

So it's not a thing that like.

Yeah, when I hear a lot of like we're an AI agent startup, what that really means is like maybe you're leveraging another agent or some sort of agentic API in that particular case and.

Then maybe they're using.

Sure. Yeah, you might be, you might train your own and maybe that's the. Is there a significant cost to this? Like, does this affect if I, if I just take the landscape of like everyone who's building Cursor for X right now. That implies that at some point they like if we see this bifurcation and the market for Cursor for X really is you know, highly fragmented and there's not just one foundation model company that just eats everything. Are you going to see small RL reinforcement learning environments with verifiable rewards in every single sub niche of SaaS that these companies are going after and would they have material costs to that? Is it expensive?

I think you have to build the harness anyways. I think one of the hardest things to scale is building good evaluations criteria. If you can do the evaluation bit depending on like how. So one thing is like the infrastructure problem of like doing this for like a frontier scale model.

Yeah.

Is not broadly accessible. It's not the thing that you can just like put in money and it comes out. That's what we're working on building.

Yeah.

But you can do it with like these like tiny models like the non mixed. So kind of technical thing is like to serve models at scale. You really want them to be like large mixture of experts models that are efficient for inference. The current ecosystem for tooling for doing that yourself is not great. Most people are doing like Llama and Quan experiments and these models are like they're good models kind of but they're not really what you want to deploy for a serious application.

Okay. So yeah. Is that. Can you give me a rough order magnitude for the level of cost that if I have a problem, a specific domain where I think I need to train an agent in an RL environment I have the verifiable reward. My AI researcher has defined the harness and the reward and I go to you to actually do the RL on top of maybe an open source model. Am I talking about tens of millions of dollars of GPU costs? Try and ground it for me a little bit more. More.

I would say this is like napkin math.

Yeah.

Like if you want to do like a serious run that would like meaningfully improve a model at like the deep Seq or Kimmy scale. We're talking like hundreds of thousands for like a big boy serious one.

Got it.

You can do a lot for thousands actually.

So it's kind of like. Yeah like those in terms of raw compute. Yeah. Like when people were like for the one day I fine tuned llama on this thing and and now it does this funny thing or I fine tune this image model on my face. Those used to be kind of like prosumer level projects. Now we're getting into the. Okay. This is like a enterprise level effort, but it's probably not going to. You don't need to call up Softbank to get it done.

Right. I mean, there's a whole spectrum of these things.

Yeah, of course.

That's why it's hard to say like, what's the bucket? You can fine tune Llama on your laptop.

Sure.

But you also, you can't fine tune like Kimi or Deep Seq, the big ones on your laptop.

Yep.

And also it's like, how long running is the task? How many samples do you need? How much do you really want to crank it? Like it's one of those things where you can kind of just like get more as you dump in more compute.

Yep.

But currently people are spending a very large fraction of their total compute costs on experimentation and rebuilding the same shit. Like there's not. It's not easy to do this stuff like getting your GPUs to work correctly, getting your libraries to work correctly, deciding what hyperparameters to use people spend. And this is one of the reasons that the labs that needed so much to compute and why the expenses are so high is that they have all these researchers and the researchers are all doing experiments and each of these experiments is like thousands of dollars of compute. And you multiply this over a year and 100 researchers. That's a lot.

Okay, sorry. You can finish. Sorry.

Oh, sure. Yeah. Just that I think there's some of these pieces that once you can get the hard questions answered once you don't need to keep redoing them. For every new environment you can kind of have some very cheap spot checks, like kind of one shot eval. How good is the model at the start is kind of be a bellwether for. Is the running going to work?

Okay. Loosely related to somewhat of the concept of generalizability. I want your reaction to this rune. To this Rune post Rune said, my bar for AGI is an AI that can learn to run a gas station for a year without a team of scientists collecting the gas station data set. What do you think about that as a bar for AGI? We don't need these RL environments for specific. For specific tasks. What are your thoughts?

I mean, one thing you might have that look like is the. Like, I think that could be answered by an agent who realized it's not good at gas station stuff and figures out how to kind of create its own training environment. It's like, okay, I need to. The same way that like, if you want to learn how to code you got to go find stuff to practice on. Maybe that's one way of thinking about what that level of AGI means of, like, truly self learning. Like build your own tasks and curate your own tasks in a way that allows you to check whether you've been doing them correctly or not.

Yeah, yeah. It does feel like we're in this era where there are a few really obvious things that we want to RL on and get really good at. And you see that with the IMO and the math and the deep research reports, and they're very reliable. But then once you come up with some random task, then you need the gas station data set. And so, yeah, maybe the future is go and find those autonomously and set up the reward function, train and then iterate and bake that in.

Yeah, but I think.

Sorry.

Yeah, sorry, go ahead. Oh, yeah, just because I think one way to do this is just like the environment can be the thing you're going to serve. Like cursor is an environment.

Yeah.

Lovable is an environment. All these things. People are already kind of building things that could be environments if they connect the, like the wiring correctly. But, like, I think we're not quite there yet in terms of having this be a thing that people are scaling. And now, like, every company wants to, like, hire, like, environment builders and RL people.

Yeah.

And it's like, you're not. They're not all going to hire people for this. We need to have better ways of, like, scaling this out to more people and like infrastructure as a service, kind of.

Yeah, that makes sense.

Wanted to ask about Dario's comments in his interview with John Collison, talking about. Basically, I'll read the quote. He says there's two different ways you could describe what's happening in the model business right now. So let's say in 2023, you train a model that costs 100 million and then you deploy it in 2024 and it makes 200 million of revenue. Meanwhile, because of the scaling laws in 2024, you also train a model that costs 1 billion, and then in 2025 you get 2 billion of revenue from that 1 billion and you've spent 10 billion to train the model. So if you look in a conventional way at the profit and loss of the company, you've lost 100 million in the first year, 800 in the second, and 8 billion in the third year. So it looks like it's getting worse and worse. If you consider each model to be a company, the model that was trained in 2023 was profitable. You paid 100 million, then it made 200 million of revenue. There's some cost inference with the model, but let's just assume in this cartoonish example. And so Fintwit has just been like freaking out about this, like, being incredibly bearish. It's obviously a bubble and just kind of worried you have exponential increases in cost and then unpredictable kind of like capital needs in the future. Why do you think they should stop freaking out, given that you are just over at Goldman Morgan Stanley?

But yeah, so like, there's an element to the freaking out that's like kind of a good point. Which is like, you can't keep doubling every year.

Yeah.

At some point there's a plateau and you can grow every year. You can still have like exponential growth, but the percentages are not going to. There's only so many people to adopt AI products. And once they adopt it, like if they were going to be spending more and more, it has to be delivering like a very large multiplier of new value per year. And there's some laws of physics of like, how good models are going to get, how, like, fast we can possibly make the chip. Like, the chips are only going to scale so quickly. We can only build so many GPUs year after year with the current, like, rate of growth. And so, like, I do think there will be kind of the space and we end up in where, like stuff broadly works quite well. There are a few big labs who have very good models that are like, you can deploy them. And then there's also this kind of Pareto curve of how much can you spend, how fast does it need to be, how hands on do you want to be for it, how narrow is your thing you want it to do? So if your thing is like, oh, I want to build a great browser agent. This is super broad. There's so many things you can do on a browser. The thing is, I want to build an agent for writing Rust. This is much more narrow. And so if you're making the product for Rust developers, like the Cursor, for example, you can make a model that's just as good as Claude for Opus, that's much smaller and much cheaper, most likely because the focus is more narrow. And so this is how I think about generalizability. You can spend more on compute, you can make the model bigger. These are all different axes to spend. And you can also make it more narrow and go deeper on one thing. And so we're going to have a lot of knobs to turn. I Think, yeah.

Are you broadly long RL environments, short normal pre training data? Do you have any extra color on the relative value or where the low hanging fruit is across those two?

I'm long both, but I think they're going to kind of turn into the same thing. One thing for example, that people have been doing for pre training recently is that people are just using deep seq R1 and generating tons of reasoning samples from it and then mixing those in at the end of pre training and calling it mid training. And it's like in some sense this is RL because it's just taking the juice from doing NRL on deep SEQP3, but it's also pre training. And so I think one thing that we're excited about with environments and scaling these is you can get a lot of good data out of these by you have a like a task set. You have the ability to generate agent data inside of this task set. You have a filter for throwing out the bad stuff and keeping the good stuff. And so can you just like do trillions of tokens this and put it into pre training? Why not?

Do you have insight into what's happening in the video or image world equivalent of RL environments, verifiable rewards, et cetera? Like I was just shocked by the level of quality of text in images in ChatGPT. We're seeing the same thing with Nano Banana from Gemini and it felt like images in ChatGPT particularly was uniquely good at Studio Ghibli and uniquely good at text. And that felt like I was almost putting on my tinfoil hat and saying they're using Photoshop here and they're doing two different layers or something. Or like there's something else going on here that's just like one really good model. Like it feels spiky, it feels particularly good at text and particularly good at cartoons, but it hadn't gotten like way, way better at super photo real imagery or whatever. Sure. So do you have any view on how you translate all the stuff that's happening in the agents and text based LLM world into sort of the diffusion and image or video world?

Sure, yeah. So like I am not a diffusion expert or anything but like I, I imagine it's a mix of essentially these kind of environments where you have some greater as well as like good old fashioned RLHF, like the stuff people were doing for like instruct GPT ChatGPT era where it's like you have like upvote, downvote and then you're training a Reward model to like check these. And I think the image domain is easier to kind of spot errors whether it's a human or an automatic grader. If text is wrong, you can do OCR on the image, get the text back out and see is it the right image from the prompt. And so this is pretty easy to verify versus if a ChatGPT answer is like slop, how do you verify that it's slop? Like what's the algorithm that checks if it's slop or not? That's pretty hard. And so in some sense the image models were just like for a while they were bad at things that we could very easily measure. And it's gotten harder to measure the things LLMs are bad at much faster. And so I think some of this is the old fashioned tricks that made ChatGPT original version as good as it was being applied to the image domain for patching up the obvious fixes.

Give me your hot take. How much do you think Meta is paying Mid Journey with that new deal they announced?

That's a good question.

Do you think it's nine figures a year?

Hopefully. I mean like it feels like it would be more maybe, I don't know, they're spending crazy amounts on everything.

That's what I was saying. And it makes sense for Mid Journey to want to have like a low key announcement about it, but there's like another team that would have been like we just signed a $500 million a year, 10 year deal or something, something obscene that, that looks more like an acquisition. Even though clearly from a dollar value standpoint, even though clearly they're going to continue to operate independently.

Yeah, I would kind of think of it as like Mid Journey's version of doing an API business. So it could just be based on usage to tool. I'm sure there's a big fixed component of it. But think of what you can do the napkin math by saying, okay, what are other image providers charging for API usage like VAL or Replicate. Replicate or like all these other services, like you can kind of map them out the cost of an image or back it out for mid during subscription prices and how much they give you and then say like okay, how many of these are people going to be doing? If they're doing like generative ads for Instagram, that's a lot. If they're doing like every person has the ability to apply it to their Instagram posts or their stories, that's a lot. And so you can, the numbers can get crazy pretty quickly and I think it does Kind of depend on, like if it's just ads or if it's just to certain customers or it's not deeply integrated, then the scale is not as crazy as if it's like. No, you're really getting mid journey stuff everywhere for everyone. Instantly at volume.

Yeah. I was thinking when Studio Ghibli moment happened, that the response from Meta should be to pre render or pre. Pre generate a Studio Ghibli of every single person on Instagram's profile photo as a Ghibli. Because that's basically what people were doing in ChatGPT, like pre generate that. And then just when you, when you open Instagram, it just says, hey, we did this for you. Do you want to share it? And that would probably be like the biggest day of usage on Instagram, but it would also probably bankrupt the company because it'd probably be like $50 billion worth of inference or something like that. I don't know.

It's a lot of.

It's a lot. Those images are expensive.

Got some breaking news. Nvidia beat on revenue and earnings per share, but is down 5%.

Wait, why?

They didn't beat hard enough. They didn't beat hard enough.

Can we bring the gong for the beat?

I mean, let's bring it. Yeah. 4 and 1% respectively.

Nvidia's. Nvidia's like both a competitor and a supplier partner.

Right.

To you? Like.

Yeah, I mean we sell that, we resell the gpu. So like we like, we're big in video fans.

That's great.

Yeah. And I think Nvidia has been very friendly to like the ecosystem of players. Like Nvidia is not trying to be the like, single. You can even like buy GPUs on their website. Like, they don't sell GPUs to people. Yeah, they sell them to like data centers.

Yeah.

And like big companies.

Yeah. And I know that there was that news that they were coming for the Neo Clouds with DJ X Lepton and it felt like, it felt like they were dipping their toe in that area, but it didn't feel like this was existential for anyone else in the, in the ecosystem. It felt somewhat additive. I don't know if you have a take, but.

Oh yeah. So I mean, I think it's also like a different, like they're going to kind of offer that as like a very premium, like white glove sort of thing to certain enterprises.

Sure.

I think we are much more on the end of get all the data centers we can find, like partner with every neocloud and have like really cheap pricing and then like build features on top.

Yeah.

Where part of this is like doing like core research. So like we like have friends Nvidia like we talk to them about like they release a lot of cool like open source like research stuff. And so like that is like very in spirit of like the sorts of things we are like aiming to do. And I think we're like friendly.

Yeah. Are there any RL tasks that you think are like truly intractable? So something that is fundamental to humans, creativity or comedy or something. What's the Mount Everest of developing an RL environment around?

I think the hardest is stuff that a friend of mine was tweeting about this earlier today. Actually one of our collaborators from Evals who's doing some cool open source evals work for computer use. But things that need a human in the loop to have a fine grained, accurate simulation. Like stuff that if a human. If models are not good enough at replicating human behavior yet and that human behavior is key to the environment, then you're not going to have an environment that faithfully captures the task because there's a kind of chicken and egg problem. And so like Twitch Streamer was one example of like having a model that can be good in Twitch chat. Kind of requires like an accurate SIM of Twitch Chat. And it's like, how do you build that? Or like a physical streamer? There's this real time interaction problem you need to solve before you can get started because the scale at which these things move, you can do it if an LLM is simulating the user, you can't do it if you need a real human.

Yeah, I feel like the time horizon feels really, really tricky to simulate when you think about the impact on a life of a certain behavior. I mean we struggle with this with like drug development, understanding, like does something in childhood affect you as a retired person? It's like, okay, now you have to create a simulation of the entire human body to understand that if you did this thing at 18, it's going to cause you to, you know, have your like knee blow out when you're 65 or something like that. Feels much harder to simulate one shot, but maybe we'll get there. Who knows?

Yeah, at some point you just gotta let the error of time run forward and see what happens.

Exactly. Well, thank you for hopping on.

Always great to see you.

Congratulations.

Congrats on the.

Yeah, we'll talk about the Prime Intellect environments hub. We are live now. We're on Twitter X. See you around.

Send it Chat.

See you.

See you guys.

Talk to you later.

Bye.

And yes, we have the Nvidia market chart here. Down 2.75%. Is that what I'm seeing here? Correct. Let's see. Video is doing as well, but high expectations. But, you know, after hours it's down 1.42%. It's bouncing back. Right now the company's trading at $179 a share. Was it $181 a share? Something tells me Jensen's gonna shrug this off. If you look at the six months, the stock has just been smoothly climbing upwards. Anyway, we have our next guest, Julia Steinberg, in the studio.

What's happening?

How you doing?

Welcome back.

I am doing well. I was thinking about wearing like a little hat that said Chinese Communist Party on it to, you know, establish what I was talking about. But unfortunately I came up with this idea 20 minutes ago. And because I am dealing with California infrastructure and not China infrastructure, I could not get it delivered. House in time.

Yeah. Are you driving from LA to SF or vice versa? Where are you going?

Going, yeah. So this may be a bit TMI for the good listeners of tvpn, but I was rear ended a few weeks ago, so my car has since been fixed, but I must drive it up to San Francisco. And I. It's actually sort of thinking about the drive north. It's a lot of what Dan Wayne talks about in Breakneck is sort of like, look, China is able to build these good things. And I was thinking about it, I'm like, why do we not have a functioning highway for Highway 1? Yeah, why? Like PCH, Pacific Coast Highway. It's one of the most iconic American landmarks, one of my favorites. Personally, it's ridiculous that it shouldn't work. And I tweeted, I just sort of had a frustration, like I'm really frustrated that I have to, you know, do this ugly, annoying drive where my car is going to smell like cow shit for six hours rather than see the.

Beauty of the favorite thing. As a kid, my parents, my parents, we'd be on a road trip. My parents would say like, okay, we're going through the cow zone. Big cattle ranch.

Yeah, you have to turn the.

Recirculate. Yeah, recirculate. And I would just be like, I'm hitting the window down. And I was just, if I, if you were my child, you would have.

Been like booted out of the car window at that point.

I was surprised. So PCH between Malibu and LA was shut down after the, the fires for a while and then it was Open to like specific people based on your address. And then it got actually open pretty quickly. And I think that was probably newsome knowing that like, this stretch of PCH is like critical to my popularity in the state. Because there's just a lot, I mean, for no reason other than celebrities drive on that route and if they're. And if he doesn't get it open. So it was open ahead of schedule.

Yeah, yeah, yeah.

He was taking a victory lap of like.

But the one is not really critical to many people's commutes.

It's more of this, especially up by. It's Big Sur that's shut down, right?

Yeah, Big Sur. So I can drive from San Francisco or however far north on the one to Big Sur, but I can't. The sort of Cambria region is cut off that it fell into the ocean. A lot of people on Twitter were sort of. I wasn't expecting the tweet to blow up. And people on Twitter were like, how can this, like, girl expect mother nature to want this freeway here? I was like, this is absurd. Like, we've sent men to the moon. We can't have a bridge. Like, I'm not a structural engineer, but Dan Wang in his book Breakneck, he was like, oh, yeah, the Chinese government has built X amount of like the bridges, like the top 10, some of the biggest bridges in the world in this, like, record short amount of time. And it's frustrating to me that we can't do that. We somehow is admitting that, like as a civilization, we're just going to let the mudslides win.

Yeah. Here's the solution. If you want one, the Highway 1 to open, you got to put a Harris Ranch out there. Because that's the highlight of i5. You stop for the a5 wagyu ribeye. You get a big steak at Harris Ranch. This is the highlight of my trips. Up and down.

Harris Ranch is the really smelly ranch.

That's the really smelly one.

But I didn't realize you could pull over and get a meal.

Oh, yeah, I didn't realize that either.

Oh, you're not doing the five correctly then. Yeah. When you're driving from LA to San Francisco, you run out of gas halfway because you're driving a terrible car. This is my experience in like 2012. And you always stop at Harris Ranch. You get a big steak and it's fantastic.

Yeah. I think most people are flying by.

The other alternative that is actually scenic and nice is the there. Even though we don't have a high speed train, we do have a train that goes.

It takes 24 hours. Like, it just takes an extra skill issue.

Get a book. I thought you were. I thought you were into books.

You're the GM of books.

I do like books.

You're like the general manager of books.

I like being able to read books while I'm not in a moving vehicle.

Oh, it's so nice.

This is one of my more controversial book takes is I like being sitting still.

Okay.

When I'm reading a book, Planes are fine. I can read many books on planes. I've read many books on planes.

Okay, well, speaking of books, take us through your review of Dan Wang's book.

Yeah, so I sort of was introduced to Dan Wang about a year ago. I was actually on the five, listening to one of his articles, put through some voice reader Technology, How Technology Grows, which is how I first got acquainted with the ideas of process knowledge, which is basically that engineering requires a great deal of, like, verbal translation, mission from one person to another, or sort of one. Like elder meant elder. Elder mentor to a mentee. And the United States, we've lost a good deal of that process knowledge in how to make things because we've offshored it to China. And Dan Wang really, in Breakneck, does a really fantastic job of describing how these communities of engineering have maintained this process knowledge, this ability to build things, which in the United States, we've just voluntarily shrugged off and lost. He I say, I would say, like the big idea, if you're going into the Atlantic, this is the excerpt they chose, was that rather than thinking of the United States and China as a capitalist society versus a communist one or a socialist one, we should think of the United States as a lawyerly society and China as an engineering society. So in the United States, a lot of our elites go to top law schools, units for Supreme Court clerkship. One of the most prestigious things you can get, maybe even Supreme Court, is one of those prestigious positions you can get. Whereas in China, the politburo is made out of engineers first and foremost. I think Xi Jinping doesn't have that big of an engineering background, but pretty much most people in the Politburo do. And in the United States, when we focus around rules and regulations, what's getting us from point A and point B is like, well, what is this going to look like? Is this going to violate people's risk rights? Can we do this in China, it's get from point A to point B. It's like, okay, how do we do this? And building something from the ground up.

Yeah, I was listening to Casey Hanmer on Door Cash, and he was talking about how he's trying to install solar panels in the desert and he's to get some, like, environmental report that says that, like, if he puts a solar panel over it, it'll kill this tuft of grass that, like, a bird might come and eat. Meanwhile, like, if he was building, like, a chemical plant, it would be, like, fine because, like. Like the chemical lobbies have lobbied to, like, make it easy. And so it's just, like, nonsense. But my question is the engineering. What's the phrase he uses?

Engineer, Engineering society.

Engineering society and lawyerly society. Right. Engineering empire or something. So I understand that. And it's very alluring. Like, I like engineering more than I like lawyer lawyers, I suppose. But my prior. My prior is that America is number one and America is the best. So should we really try and change horses in the middle of a stream here? Maybe the beauty of America is that we have so many lawyers keeping us great. What do you think?

Well, my dad, who's probably watching right now, is a lawyer. So shout out to the lawyers keeping America great.

But I guess the bigger question is, like, is there a world where we say, okay, let's try and pivot from lawyerly society to more engineering focused? We get halfway there, and we actually are worse off because you want to just like lawyer max or engineer max, and if you're halfway in between, it's just a nightmare.

I don't know.

Well, how I view it is that the United States is very good at engineering maxing in the private market, whereas China is very good at engineering maxing. Just having the state do it, you know, Chinese Communist Party or both.

Both.

But the state capacity for engineering capacity.

Is a lot bigger. But it's also like, this is my biggest issue with Breakneck is that it was just, like, way too Keynesian. It was like, oh, it's so great that the government is, you know, basically getting these people in the middle of nowhere in China to dig holes. And by dig holes, I'm sort of exaggerating a bit, but it's digging these bridges that no one is going to use or these airports in the middle of nowhere that have fewer than half a dozen flights a week. Like, I just don't think that's a good use of market resources there. It's a sort of interesting question that Wang raises, though I don't think he says it straight up. Is like, is capitalism even a useful sort of metric in the 21st century? And I would say absolutely. But we need to prove that in the United States by doubling down on free markets. Free markets could bring us great things, like a beautiful bridge that would make PCH work. I'm a huge believer in market incentives. I think the issue that Wang sort of highlights, though, when he talks about Xi Jinping not wanting like a services economy, is just that in the United States, maybe the culture is a bit broken where our best minds want to do, I don't know, like B2B SAS rather than building bridges or building nuclear power plants or other infrastructure. I do think this sort of culture is changing a bit. We're returning a bit to wanting physical manifestations of American excellence, that it's not just my app is like.02% more productive than your app in delivering an AI girlfriend. But I think that overall, what Wang talks about in China is sort of engineering. Society mixes tooth. It conflates two things. It conflates engineering and it conflates culture. And when the government is in charge of culture and they can say everyone from this district should want to be a guitar manufacturer, which is true in one of the districts in the book that he talks about, which makes guitars, which is pretty random considering that there's not really a historic guitar industry in this city in Guizhou. It's just something that they sort of was like, we're just going to make guitars here. And it happened, and they got very good at it. But with the United States, culture is a lot more organic. It's harder for the United States to say, we're going to make this value really well adopted. And this is something that's sort of bad about China, too. Dan Wang talked a lot about the one child policy in China. He talked a lot about zero Covid in China, where people.

John presented the multiple children policy, have.

Three kids, and Dan rejected that roundly.

I, I like the three kids policy. I think, I think it's a, I think it's a good policy.

There's incentives and, and if you, if you really, really tilt the feel the playing field in the favor of having more kids, like people will have more kids.

I agree. And it's like talking. Of course, you know, I have to bring up Tavis, the engagement that happened yesterday. Oh, yeah, Boyfriend at the end of the day. And I was like, Jake, like, I have to tell you something, but you're not going to be interested in this at all. And he was like, oh, my God, like, what did she do this time? Like, did you get another car accident? And I was like, Travis and Taylor got engaged. He's like, I don't know who those people are. And also like, I'm really not interested in that.

He doesn't read the Wall Street Journal.

Because Taylor, you guys need to Write.

Something about 2014 op ed about Spotify.

Yeah. From that also, I want to know the, I want to know what this engagement means for America. Well, from, from arena, from you guys.

But it's like this, it's one of the weird things. It's like a Taylor Swift baby boom. Like how China is. It's not. Who's a Chinese pop star who's going to get pregnant from a football player and have kids?

I don't know. That's a good question. We'll have to get to the bottom.

I do think there should be a Taylor Swift Orchid collab. You know, she's on the older side. I hope she has many kids. Orchid could be a sponsor, you know, there and having D1 athlete that's also world famous superstar kids.

That's true. I mean, they're, they're certainly, they don't shy away from the economic opportunities associated with their, with their announcements, that's for sure.

No, but I, but I do really think that the Tavis sort of engagement announcement. The what? The royal wedding that will happen in a few years. Like, I unironically do think that this will cause a baby boom because people are very medic. Women are very mimetic. And if number one pop star has.

Kids, I found the answer. Jackie Chan, born in Hong Kong, has two children. That's the answer. We just need to promote Jackie Chan's children in China. That will cause the boom.

Well, maybe the thing with Nepo babies like Nepo, the sort of like weird take on Nepo babies, is that we need to have more Nepo babies and just the shit out of them. So it's like your kids, if you are successful, your kids will be successful, too.

Yeah.

Because the line about kids now is like, oh, if you have kids, especially if you have kids young, they'll draw away from your success.

Yeah.

But if I'm like, oh, my child is heritably going to be like a kung fu superstar. Because I am a kung fu superstar. I totally have kids for some do that.

I mean, that certainly happens in Hollywood. There's a ton of celebrities that have that have kids. I mean, John David Washington is Denzel's son, played football and then was in Ballers, I believe, and a tenant.

I have a sort of funny story about that. I grew up in LA and I was on the debate team at my high school, and there was a lot of sort of overlap between girls who wanted to do the debate team and girls who wanted to do the school play. And this one girl, whose parents were both very, very famous, like, super A list actors, was deciding between doing the debate, doing the debate team, and doing the school play. And our debate coach, he said to me, it's like, well, it's usually pretty easy to convince them that they're not going to have a famous career as an actor and they're a lot more likely to become a successful lawyer. But if both of your parents have stars in the Hollywood Walk of Fame, then that's a lot less likely.

Hmm.

Makes sense. Sorry, I'm prepping a chart. Jordy, you have anything else?

Chart for what?

Our next guest, who's in the restream waiting room.

Sorry, we've been keeping waiting. It's always great to see you. You got to come on more often.

Yes. We should have scheduled more time, but we have someone else in the waiting room, so I'm doing it.

Well, next time, I expect a custom chart to be pulled up.

Next time you're in la, come do the show in person.

I said. I said I'm here.

Okay, fantastic.

Let's do it.

Fix the car. Drive.

You're okay after the accident?

Yes, thank you. Appreciate it.

Always great to catch up.

California to fix the one so we can drive scenically in the future. Thank you so much for hopping on. Our next guest is in the restream waiting room. Olivia Moore from Andreessen Horowitz.

How are you? What's happening?

Good. It's great to see you guys. Thanks for having me.

Great to see you.

I was just sharing with the team the news today, but you break it down for us first. What are you announcing today?

Yeah, so we're announcing what we call the consumer AI top 100, which is where we literally thank you. I appreciate when other people are this excited about data as I am.

Love data.

We live for market maps.

Yes.

Yes.

This one has, I would say it's market map adjacent in that we every single website and every single mobile app around the world in kind of descending order of traffic. And then we pick out the top 50 in each that are AI native companies to just get a look at what consumers are actually using.

I consider myself a bit of a list connoisseur myself, actually. I enjoy making lists. I'm sure you get yourself in hot water with this list, people can say, take me off this list. I want to be under the radar. Put me on this list I want I'm doing better than that other company on here. Talk about the methodology. How confident are you? Is there an element of like Vibe and curation? Is this like the New York Times bestseller list or is this.

No, there's no elements of Vibes. It's all data. For the web list we have a provider called Similar Web and we literally just look at monthly number of visits. We pick the first 50 that are AI and then on the mobile list we do Sensor Tower and we pick the top 50 by monthly active users. But we do get lots of fun texts, emails, inquiries of people either wondering about their rankings or wanting to be on the list. So I'm happy to inform everyone that it is completely unbiased.

There are some things on here that stand out to me as completely unsurprising. ChatGPT number one, Gemini number two, Deepsea Grok up there. That seems obvious to me. Stuff that's standing out are specifically like Janitor tool, like hyper specific tools like Remove background, Remove bg. I've actually used that tool.

Janitor AI is number eight.

Yeah. What else stuck out to you as surprising? What did you learn?

Yeah, every time there's apps that are kind of like literally single purpose. Remove BG is a great example. It was a company that was acquired by Canva but grew to like 32 monthly active users literally by the best product to upload a photo and get the background removed from it. And it's a catchy URL that people remember so it keeps getting usage.

Yep.

The Janitor one is a good call out too because one of the surprises for me, list after list is how many companion products make the list. Like it's always a dozen or so each time. Janitor is one of them and one of the highest ranking ones behind character. So it doesn't seem to be.

It looks very grok Xai.

I would have thought Janitor would be like back office B2B. I thought that would be something to clean up my data warehouse. But you're telling me that it is in fact a companion of some sort?

It is.

I also see Spicy Chat AI. That sounds like something we shouldn't pull up on this stream. Cushion AI has a heart there that seems little suspicious. Juicy Chat. There are a lot of these use cases there. Is this a new thing? Is this the first time you've done the top 100? Like what are the biggest movers that you're noticing or that you expect?

Yeah, this is the fifth list. We do it every six months, so we've done it for about two years now. We started it six months after ChatGPT came out. Interestingly, there's 14 companies that have made every single list. Most of them are in kind of creative tools. So think like Midjourney and 11 Labs. Quite a few of them are general LLM players like ChatGPT Perplexity Po. One of the big I say surprise but probably not a surprise to anyone who's been on Twitter is like vibe coding completely exploded on the list this time. So lovable wasn't even on the last list and now they're like number 23. Replit's also on there is just below the cutoff cursor is on there as well. And it's interesting because like you would think that the developer market is much smaller than the consumer market. So for developer facing products to make an app like this is pretty impressive and it shows that like a significant majority of developers are using them.

Well I think the way that I look at that market is there's so many people in the world that have had an idea for an application without the engineering co founder like the cto. And so that's just like decade plus now of like pent up demand for people that had an idea for an app. And then all these companies, whether it's lovable or replit or things like that have people on TikTok saying like you can make an app now or they're running ads that say like you can make an app. Right. And so that's just like a flood of demand for people. Yeah, non developers becoming developers for the first time.

How are you thinking about Meta's strategy? I noticed Meta AI ranked 46. That feels pretty low compared to the amount of effort Mark Zuckerberg is putting into that project. Although it's early days. Also the Meta AI app, I went to go test it, I realized I had it downloaded because I had bought a pair of Meta ray bands and they kind of, you know, iterated on that product to turn into Meta AI. But you know, LLMs are vended into Instagram and yet Instagram's not on here. Do you think that you'll see more companies that are in the AI bolt on narrative era of their business kind of jump on here? Do you want to keep them separate? What is your thinking about all of that?

Yeah, meta is really interesting. It's funny, the larger tech companies I think have really seen stepped up in the past year or so on the AI front. Like Google is probably the best example of this. Gemini was number two on the list. They also had the AI studio on the list. NotebookLM on the list, Google Labs, which is where you get vo.

Oh, wow. They have four companies on the list.

Yes, four separate entities on the list which were all ranked separately with their own traffic. Grok had a big debut on the list from X, formerly Twitter. Meta, I think, has struggled a little bit, both on web and then on mobile. I don't know if you guys remember the big scandal where they realized that a bunch of the users were accidentally posting their very private posts to the public feed.

Yes.

And so usage fell off a little bit.

Interesting.

They didn't even make the mobile list. But to me, it's like if you guys have tried the Meta AI products, they're a little bit underwhelming. The quality of the images generated. They did the weird celebrity community companion thing. So now that they're working with Mid Journey, I would expect to see them make some improvements here, but it might take a little while.

Yeah, even the Mid Journey thing, it just feels so natural in the other apps. And if you have a billion people opening one app every day, like where Meta has been successful, has been put stories into Instagram, put videos into Instagram. They used to launch sidecar apps like Facebook, had an app called Facebook Camera that was supposed to compete with Instagram. And then they were like, we gotta shell out for Instagram.

Do you think Midjourney's ranking gets hurt because people still use it in discord or is they shift because it feels low at 28?

Sure, sure, sure. Yeah, yeah, yeah. They just recently kind of rolled out the web.

I think that's true for both Midjourney and Suno and a couple other the creative tool apps that also have discords. It's funny because in the first iteration of this list, like no one had a website. Everyone had a discord. And now a lot of those companies are really trying to shift their traffic over.

That's interesting. Yeah. I bet you could do a different list of just like the top discords, because all that's very quantitative and available and relies on even further data. Jordy, do you have anything else you want to take through this? I'm wondering. I can continue.

Go for it.

I'm just interested in understanding your predictions for what the next version might look like. What are you tracking on the earlier stage side that isn't quite ready for breakout adoption as measured by unique monthly visits, but we might see an uptick of in the next year or two on the consumer AI top 100.

Yeah, I'm definitely Expecting to see more in prosumer and productivity. I feel like both the models are just now reliable enough to actually do work for you or getting there. And they're also agentic enough to like Perplexity Comic can draft an email and put it in your Gmail drafts folder, which is amazing. So we saw a couple companies like Manus make the list this time around that thesis, but I'd expect to see things like Fixer Serif and others in that category. Genspark is another big one that I would not be surprised to see on the next list.

The other what's what's been happening to all the companies that actually were GPT rappers, where they were for a while you could build a business to a few million of ARR, probably more. Just basically I remember one just advertising.

Against chat talk to PDF.

Well, yeah, there's those, but I'm saying there was other ones that would be called like Open Chat and it would.

Oh sure, yeah, yeah. When you would search ChatGPT and they.

Would have in app subscriptions.

Literal rappers. Yeah, that's it.

ChatGPT, that was a loophole that was open on mobile. So we. We've only done the mobile list I think four times now and it was complete chaos the first three times because the App Store was not policing what we call fleeceware, which was like all of developers mostly abroad that were just kind of ripping off the free version of ChatGPT, putting it in an app and acting like it was the same thing you got if you paid for ChatGPT Premium and they were called things like chat and ask AI or chatGPT or chat GTP or something. But they finally cracked down on that over the last six months. So now we have a mobile list that's like more representative of true products, but it's all like beauty cam filters now and scan your homework and get answers.

Oh really?

What's your read on how Apple's done from a curation standpoint? There's like a lawsuit happening right now between Xai and OpenAI and Apple.

I mean this is probably going to get printed out and blown up on a big chart in court soon because GROK looks great here. But yeah, I mean, I'd love to know your thoughts on how Apple's curating the App Store.

Apple is a little bit struggling overall with AI. Like we've even seen this with Siri and the fact that they're now potentially going to turn to Gemini and Google Google to fix it for them, which would be kind of unheard of. I think they do an okay but not a fantastic job with curation. It's definitely not like a pay to play situation from what I've, you know, what I've heard. But I also don't think that they're necessarily kind of at the cutting edge of what's truly the best products that are coming out next that people should be spending time on.

Yeah, they also.

They should hire you.

They should, yeah. I mean they also obviously prioritize, they editorialize in what they recommend. And so I would be surprised if they're pushing Companionship anytime soon since the lineage going back to Steve Jobs was this is a very clean productivity, creativity. Well, and I would imagine gets promoted mid journey, I would imagine gets promoted.

Apple computers are going to be every, every day there's an article in the New York Times about how somebody had some. Something tragic happen while getting advice from a model. And so Apple doesn't want to be like, we recommended. You recommended companions and the companions went haywire. Just very.

Anyway, we gotta hop on with our next guest. Thank you so much for.

Thank you for joining.

Thanks for having me. This is so fun.

Thank you for list maxing.

Thank you for list maxing. It doesn't get said.

Thank you for reading it.

Let's hit the gong for the big list for.

We hear. We hear that lung is too loud.

Too loud. Yeah, we're into mic.

Sorry for your ears everyone, but great, great to catch up.

Thanks for hopping on. We'll talk to you soon. Bye. Up next we have Flo from Lindy AI. Big announcement today. We will bring him in from the restream waiting room. While we are waiting for him to join, let me tell you about AdQuick.com out of home advertising made easy and measurable. Say goodbye to the headaches of out of home advertising Only Adquick combines technology, out of home expertise and data to enable efficient seamless ad buying across the globe. Flo, how are you doing? Sorry for keeping you waiting. What's new in your world?

No good. Don't worry, I'm doing great. It's a good day to build B2B SaaS.

Yes.

Let's go. Let's hear B2B SaaS. Finishing out the show with some just amazing news. Tell me more.

Yeah, we just announced a vive coder today. I just saw Olivia's appearance here as you mentioned, lovable and replete and.

And a few of those.

They've been blowing up. What we announced today is a vibe coder that can test its own work.

Okay.

And it's kind of. It's kind of insane to say it because you would assume like, of course you can, but actually none of those products check their work. Like, imagine a software engineer that's just like here, it's like it doesn't work that you haven't tested and like, oh, no, I didn't do that. So basically these Vibe code rely on you to test the work yourself and then like work with them to debug it. And it's like it ends up being a lot of back and forth and painful work.

Are you talking about generating a test suite in code or spinning up a web browser? Interacting with the Vibe coded product?

It's the latter. Thanks for asking. Is it OK if I share my screen? I feel like it'd be better always.

You can share your screen, but we are live, so anything you share will be shared with the Internet. Burns into the training. My test wheel manager, please. Yeah, Vibe code of something right now. Let's see. Live demos, they never go wrong.

I'm not going to do like a.

Live, live, live demo because it does take like three minutes or something, so it'd be a bit boring.

But Singularity Example.

Built a Scrabble checker.

Okay.

And this is when we realized it's actually an emergent behavior that comes out of this agent that we gave a computer to. It was like, all right, I built this Scrabble wheelchair for you. I'm going to open it, I'm going to type a wheel that exists like thunder. It tells me it's valid. Now I'm going to type a wheel that doesn't exist like ZZQXW and oops, it tells me it's valid as well. I noticed there might be an issue. It's showing ZZQXW as valid, even though it should be invalid. Let me fix the API to improve the validation. Fix the API, try again. Doesn't work. So it does have its own computer, its own browser, and its sees the work and can click around and actually test its work.

Yeah. Very cool. What do you think? The landing. The landing not landing page, but like, what do they call it? Like the landing market. The first product market fit moment. Do you have any glimmers of hope? Is this going to be used by restaurants who want to spin up a landing page? That was kind of like the previous boom of. It wasn't Vibe coding, but when you saw folks stand up landing pages with, you know, squarespace or any of those, weebly like there was a whole boom in that. It feels like there's another boom in vibe coding right now. Do you have expectations about where the sweet spot is? Because I would imagine that people aren't going to build like, you know, they're not going to go out and raise $100 million for a company that's built on the back of a Vibe coded solution. It's more of like a prototyping tool right now. But then for small businesses, this could be something that they really rely on for a long time. Like, talk to me at the shape of the early customer.

I think that's actually the perception of trying to fight. I think the reason why Vibe coding so far has been limited to these landing pages. Yeah. Is because the tools have been so limited and landing pages are just like the fastest, dumbest thing you can build. Same for like, this perception that, like, oh, it's like a cute prototyping tool which are not actually going to build your company on this.

You know, we.

The thing that is unlocked by this new paradigm of something as simple as testing your work. If you can't test your work, you can only build very, very simple stuff. If you test your work, we'll see instances of this running for hours and building one of the craziest examples we've built internally. We could eat Lindy bnb. So it's like an Airbnb clone and it's functional. You can select things, you can book them, you can put your place up for rent. It's functional. You can sign in, you can sign up. It's got Google Ads, it's got all of that stuff. So we're actually seeing a lot of. So, yes, we're seeing the landing pages, but now we're also seeing a lot of internal tools. So you're almost getting into retool territory.

Sure.

Because people are like, I'm just going to hook it up to my API and I'm going to build ROI calculators and various internal tools for the team in a couple of minutes.

Yeah. Do you think of this as a separate product or does. Does this sit on top of everything that you've already built? And is there a way to hook in the traditional Lindy's into what you're Vibe coding?

No, it's super integrated with the rest of the product that we built, which is agents, obviously. That's the whole value prop is like, hey, building your website is step one. Once you've done that, you actually have to build the rest of your business. I joke. Building your website is the equivalent of getting your. Your business cards. Like, okay, yeah, you did that. Now you need to build a business. So now that you built your website, Lindy can market it for you, find customers, do the entire customer support for you fully autonomously. I half want to actually launch Lindy BNB and have it fully because I've got enough of one business. I don't want to run like Lindi bnb, but have it fully managed by agents and see how far we can go.

Yeah, it's great. Yeah. Keep sharing demos. I'm excited to check them out. Anything else, Jordi?

Yeah, just. I'm interested, you know, clearly. I think it's almost contrarian at this point to launch another prompt to app builder. Right. And you're insanely, insanely intentional about everything that you do. Do you think that the category actually needs a bunch more people to try to be experimenting here? Right. You see some of these revenue ramps. I think a lot of entrepreneurs would assume that the market is run away. I should focus on something else. But you've clearly made a different decision from the traction.

We're saying there is plenty of room in this market. I think it's like the very, very, very beginnings of this market, as crazy as that sounds also, and we've not told that story yet to anyone, the way this came about was we actually built the V1 of this by accident. So we had this released this release that I went on the show a couple of weeks ago where we were like, hey, we gave a computer to Lindy. And then we realized after we gave it a computer, it was like, oh, fuck, it can build websites and you can QA them. Because that's what happens once you have a computer, you can do everything. So then we've basically packaged it up and released it as an indie build and improved it, obviously. But I think it's basically an emergent capability of the platform. And the reason why we've decided to release it is like, well, one, we were like, fuck, it's all working. And two, we then started to look into the other products and we were like, I can't believe none of them checks their own work. This is actually done. That's like a massive deal. And when we a B tested like, okay, same prompt on lovable red plate. Lindy. This Scrabble example, for example. Every Vibe coder out there, it's a simple example. It's like a very mini app. Every single Vibe coder got it wrong. Every single one, including Lindy, it got it wrong. First shot, as you saw. And then the difference is, like, Lindy hasn't tried its own work, saw that it got it wrong and fixed it. So I think it's day one for this product.

That's very cool. Well, congratulations on the launch.

Keep us last. Very quick question. Where are we on the Gartner hype cycle? Peak of inflated expectations, Trough of disillusionment, slope of enlightenment or plateau of productivity?

I have this conversation every day with a different friend. I forgot the different labels here. But like look, you know, it's basically.

Are we coming down from the peak towards the trough or are we headed up the slope of enlightenment?

I think we're heading up the slope of enlightenment.

Wow.

Bullish.

Bullish. Bull market continues.

Very bullish.

Very bullish.

Well, thank you so much for hopping on. I'll talk to you soon. Have a great rest of your day.

Thanks everyone.

Cheers.

Well, if.

Shout out to Ilhan Vellani.

Yes.

Shout out in the chat.

Yes.

He is at Boston University. At Boston University.

Let's hear it.

Watching with across the coast, five others.

Having a window in Silicon Valley.

Bullish.

Well, let me tell you about Wander. Find your happy place. Book a Wander with inspiring views, hotel graded menus, dreamy beds, top tier cleaning and 247 concierge service. It's a vacation home, but better folks. Not going to find a wanderer on Lindy's vibe coded Airbnb. He's got us all getting good inventory. That's what Wander's done. Jeff Dean is. I don't want to say he was inspired by us, but he posted a beautiful one of one AI generated trading card of him playing soccer. He's the chief scientist at Google, of course. He says our latest Gemini image generation and editing model is quite good. See the examples in the thread below. It lets you indulge in a bit of creative fun. Helps you make new business cards, et cetera. Try it out@gemini.google.com Jeff Dean, of course one of the greatest to ever do it. Very, very cool. We got a. I mean this.

So Logan, Logan one shotted a card generator.

Oh yeah. Can we play with it? Maybe we should play with it after the show and we'll bring it up tomorrow.

It's looking good. He sent me a preview. Yeah, love it.

Also, Packy said I've had. I've mostly had X deleted from my phone for the past month or so, but every now and then I redownload it briefly. It's been funny seeing the slow Nikita fication of the onboarding flow like this new pulsing blue orb on the allow notifications button. I didn't even know Nikita could pull this off.

There's levels.

There are levels to this.

Very, very smart.

That's obviously going to increase the amount of people that turn on notifications because it draws your eye right to it. Also just nicely designed too. That little subtle gradient there to highlight. Allow not too.

Ryan Halligan. This is interesting saying re Sonos. I have two ideas, offers. One, it has a biggish brand, tons of customers, no real competitor, and absolutely horrible products. I'd love to help a PE firm who would want to take it private, fix it, and take it public again for big gain. Two, if you're a very sharp, qualified entrepreneur that wants to disrupt them, I'd like to hear your pitch.

This is the curse of being Sonos. You know, so many capital allocators, private equity guys probably have thousands of dollars of Sonos products that they are dis, you know, unhappy with. And they're all. Every time they go and turn on their TV or their sound system, they're like, I should take this company over. I should go do it.

Keith Raboy in the comments. Let me know if you want to work together.

Yeah, Keith Roy's getting in the the game. Naval is also there. Naval. He's talking about another company that has an amazing product that needs to be distilled to a lower mass market price point.

Kenneth Castle has a fantastic post here. He says, I guess his wife says TS&TK are engaged. He says, question mark. Taylor Swift and Travis Kelsey. He says, oh, I thought you were talking about TK from Uber Cloud Kitchens. What?

What?

Absolute banger.

Well, did you notice what Taylor was.

Wearing.

In her engagement photo?

Absolutely not.

But I did see Cartier Panthere.

Oh, the watch. I did see that 8 carat diamond ring.

But more importantly, she was wearing a Cartier. Where could you get a Cartier Bezel? Get bezel.com, your bezel concierge is available now to source you any watch on the planet. Seriously, any watch gonna be proposing to a pop star.

Nascar. NASCAR has joined Substack. I don't think anybody would have called that four years ago.

We got to do a collab with them. This is the whole thing on Substack. We're gonna do collabs with other people. So we got to get a live video going with them. Get nascar. We've already talked to folks at nascar. This would be the second time we're collabing with nascar.

An absolute terror. Well, folks, thank you for tuning in today.

Thank you for tuning in.

We've had a fantastic time. We hope you have too. We hope you have an amazing afternoon. Follow our substack tbpn.substack.com yes, please. We're growing very hard over there and we will see you tomorrow.

See you tomorrow. Have a good day. Cheers.