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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TVPN. Today is Wednesday, 08/27/2025. We are live from the TVPN UltraDome, the temple of technology, the fortress
Speaker 2:finance, the capital of capital.
Speaker 1:Massive news from SpaceX last night.
Speaker 2:They did it.
Speaker 1:They did it. Flight 10 made it back, took off from Starbase, South Texas. The the booster landed in the ocean in the, I think, the Gulf Of America, technically.
Speaker 2:That's absolutely right.
Speaker 1:And the actual Starship executed a successful flip maneuver, deployed a mock payload of a bunch of nonfunctional Starlink satellites, survived reentry just barely, as we'll see. It was a really dramatic video. It was amazing. And then splashed down on target in the Indian Ocean.
Speaker 2:It was a full send.
Speaker 1:It was a full send. It was it was a crazy, crazy
Speaker 2:thing Yeah. To
Speaker 1: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 the vehicle, but they got it off the ground.
Speaker 1:Look at that. They lit the candle Stunning. Going to space. And so
Speaker 2:I wish we could get a better sense for just how massive it is
Speaker 1:Yeah.
Speaker 2:Those angles.
Speaker 1:And so that those are the dummy Starlink satellites. You can see
Speaker 2:that little motor conveyor belt on the left.
Speaker 1:Yeah. Just the number of things that have to go right to actually release something from this rocket is insane. And then this is the crazy part. There's just a bunch of That's not what we're come from?
Speaker 3:Just take a hit.
Speaker 2:We clearly didn't need it. You would think that
Speaker 1:as soon as I saw it, I was like, okay. It's over. The whole thing's gonna blow. For sure, it doesn't definitely doesn't make it back. Because if it's like losing parts, like, every part should be important.
Speaker 1:Right? Like, what's going on here? And so 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 in
Speaker 2:the Yeah. The were mentioning earlier there's a sound bite of them saying they were they were
Speaker 1:actually They were going further than they needed to. So they were doing things like like, okay, let let's And stretch then boom. And then boom. And then the
Speaker 2:Convenient cut. You would have thought the journal and the legacy media would have let that Yes.
Speaker 1:Have been a little
Speaker 2:bit longer. Yeah. Massive explosion.
Speaker 1: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. Covered the You can imagine
Speaker 2:the conversation between Elon and Ani yesterday, right, before the launch. You got this, babe.
Speaker 1:I mean, you know that you know that Ani, apparently, allegedly, the the original Ani romantic companion model runs on the non reasoning model. Just Grok three, I guess.
Speaker 2:Just pure love.
Speaker 1: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 GPT-five launch was something like, 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.
Speaker 1: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 what you got for me, Tyler?
Speaker 4:I I think there's also something to be said for like, reasoning models kind of mess with the vibes. Yeah. Totally. It's the music thing where
Speaker 1:Yeah.
Speaker 2:Yeah. Sometimes you want a friend that's not gonna think too hard. They're just gonna Yeah.
Speaker 1:Yeah. Yeah.
Speaker 4:A 100 like percent. In in the musical like taste thing Yep. All the reasoning models gave like these weird answers because they would like prefer, you know, artist names with numbers, like that.
Speaker 1:Yep. Although, I mean, I think the reasoning models actually had the best taste of all, but that's a bit of a
Speaker 4:hot take.
Speaker 2:But we gotta pull up this post from Red Bull Futurist. It's very important. Says, super heavy. The effing go, wow. And I just needed to highlight this because obviously, Red Bull some of Red Bull futurists work actually has into this.
Speaker 1:Yeah.
Speaker 2:Of course.
Speaker 1:It's amazing.
Speaker 2:So absolute legend. A win for Red Bull, really.
Speaker 1:For sure. For sure. Yeah. The
Speaker 2:the I'm it's actually surprising that that Red Bull and SpaceX haven't tried to collab yet. You'd think that Red Bull would just be like, we'll give you millions of dollars if you just put Red Bull branding over this.
Speaker 1:That'd be
Speaker 2:why not? It'd be good it'd be good for both parties.
Speaker 1:Even the even the explosions are feel like on brand for Red Bull. Totally. Red Bull's down for the crazy risk taking.
Speaker 2:I could see Elon going with Yes. White Monster Go with that. He really good. Something here.
Speaker 1:Really should do that. I the space advertising is special and maybe you don't wanna delete that. I
Speaker 2:mean, it are you would you go so far to say that White Monster brand isn't special? Would you
Speaker 1:say I guess it would be added Red Bull. Would be added. Special. Yeah. They the reason I was bringing up the reasoning models was because apparently, Elon wanted Ani to use the reasoning model.
Speaker 1:Like, the the the AI the AI companion has to be able to do the hard math problems, which is So so so maybe maybe she really was in use making doing rocket science and and calculating the last final decisions before this this rocket went out. But it was a huge success. The Wall Street Journal has kind of the play by play here. Space Hawks pull 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's South Texas complex Tuesday around 07:30PM ET.
Speaker 1:The vehicle successfully deployed a batch of dummy Starlink satellites and reentered Earth's orbit facing intense heat and forces before splashing down in the Indian Ocean. This is the tenth launch of Starship. I believe this was the this was shipped like 37 or something. They've built a lot of these. Not all of them have launched.
Speaker 1:Some of them have been scrapped. Some of them blew up in the test stand. Like, they really pushed these things super hard. So it's a 403 foot tall rocket. They started testing this in 2023.
Speaker 1:That's 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.
Speaker 2:Just to put this into context, the White House is 70 feet tall. Wow. So this is
Speaker 1:Yeah. It's it's like the size of the isn't it closer to the the Statue Of Liberty? I think it's like around that tall, 403 feet. I'll have look that up.
Speaker 2:The Statue Of Liberty is 305 feet.
Speaker 1:Oh, is Mogged. Absolutely
Speaker 2:mogged. Mogged.
Speaker 1:An extra feet 50 feet on that. For now, the company is pushing to show it can consistently fly Starship and experiment with its design space ups 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 the the the calculus here is like, how cheap can you make this thing?
Speaker 1:If you use, you know, duct tape, will that work? Will you if you use tinfoil, will that work? Like, they really are pushing these things like crazy crazy hard.
Speaker 2:I think the other the other way to put this into context Good. Not everybody is fortunate to be able to launch build and launch rockets for a living. But anybody that's built software knows that even if you're launching a relatively simple feature
Speaker 1:Oh, yeah.
Speaker 2:It'll oftentimes break and have issues and bugs and things like that.
Speaker 1:And Yeah.
Speaker 2:It's a little bit you have a little bit more leeway to ship stuff and and make changes on the fly. Yep. In this case, they're doing it in this incredibly public setting where the Internet is gonna have a a very strong reaction one way or another. So the pressure is just insane.
Speaker 1: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 nine rockets, which are powered by boosters. It can be used many times. SpaceX faces self imposed external deadlines with the much larger Starship. Musk wants to launch an uncrewed version of the vehicle to Mars next year, has said meeting that goal will be tough.
Speaker 1:Of course, there's a Mars transfer window that only comes up, I think, every eighteen 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.
Speaker 2:This is why we need to get ANI to be able to solve complex physics.
Speaker 1:For sure. For sure. And so, you know, Elon's obsessed with saving costs, saving time and money. You should go to ramp.com. Save time and money.
Speaker 1: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. Ramp.
Speaker 1:Speaking of Ramp, Ramp, of course, sponsors the founder's 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 wanna run through here that I absolutely love. So first, when an in when an engineer told Elon the air cooling system for the Falcon nine would cost $3,000,000, he shouted over to Gwen Shotwell, 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.
Speaker 1:And like my take is like like, yeah, obviously, like 3,000,000 is a lot. 6,000 is like nothing. But like if you're spending $3,000,000 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.
Speaker 1:And it'll
Speaker 2:probably is this is I mean, you know, you wouldn't a lot of companies that have this much access to capital Yeah. Would not be fixated on things like this. It's crazy. Just say, what's the best Yes. Solution for our problem?
Speaker 2:Let's use that. Yes. And so to have, again, to have that much access to capital and be that fixated on cost Yep. Like most billionaires with a space company are just gonna say, well, let's use the best of the best.
Speaker 1:Exactly. Let's use the best of the best. And let's And that's fine. Let's just do one. Do the first rocket, and then let's worry about cost control later.
Speaker 1:Later. And that's very different. So you can probably like, spending the $3,000,000 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 like over and over and over again.
Speaker 1:And so there's another quote here that's wild. Elon's just consistently questioning things. This is David Senra talking. Been trying to find the limit. And then he's quoting Elon.
Speaker 1: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.
Speaker 1: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 be dead. Elon calculated that he made a 100 command decisions a day as he walked to the floor.
Speaker 1:At least 20% are going to be wrong, he said, but we're gonna 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
Speaker 2:Playing the game on hard
Speaker 1:minimum But just just bare minimum, the cheapest possible rocket to get there. Yep. 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. Like, as opposed to the opposite, which is like which is like That can never happen.
Speaker 1:Like, do whatever it Everything that stops it from any 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 cannot blow up without it. Instead, it's like, it's gonna blow up. Let's let let 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 Astra 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.
Speaker 1:Through hardship specifically. And I thought that hit really hard. This this founder's podcast is is fantastic. There's a bunch of
Speaker 2:Potentially, one of the greatest episodes of all of it.
Speaker 1: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 $2,000,000 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.
Speaker 1: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. He like, that's, like, 85% savings.
Speaker 1:It's crazy. Crazy. He does this over and over and over again. But but the way he does it is just really, really smart. He is consistently comparing costs for parts, materials to other industries and other cases.
Speaker 1:Here's an example. Elon consistently pressed his team 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 9098% savings on on the latch.
Speaker 1: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. Yeah. Whereas, it's just impossible to underwrite that if you're if you're going to the taxpayer and saying, you know, we need
Speaker 2:can be new industry.
Speaker 1:Exactly. Exactly.
Speaker 2:There was another line in here. I'm gonna but but you guys should go listen to the episode. Yeah. It David highlights how Elon has this interesting problem where his employees like become so wealthy Yeah. They lose like the work ethic
Speaker 1:Yeah.
Speaker 2:And like made the company what it is. And so this frustration of like, okay, I'm, you know, we're 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 wanna spend Yep. Quite as much time
Speaker 5:Totally.
Speaker 2:At the factory grinding. So good problem to have.
Speaker 1:Well, hopefully, you enjoyed the SpaceX stream yesterday. I think they used Restream. If you wanna stream, you should use Restream. We were powered by Restream. One livestream, 30 plus destinations, multi stream to reach your audience wherever they are.
Speaker 1:You can sign up for free. There's there's one last funny story in here. The day before a launch, a final inspection revealed two small cracks in the engine skirt of the rocket's second stage. That's that's the piece of the bottom. Everyone at NASA assumed we'd be standing down from the launch for a few weeks.
Speaker 1: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.
Speaker 2:It's wild because another way to just if you had somebody working on your house Yeah. And they were applying this approach, you'd be like, what are you doing? This is so janky.
Speaker 1:Are you insane? But it works. Crazy to me.
Speaker 2:It took
Speaker 1: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 daily iteration. And David has an interesting context here about offshoring. By sending factories abroad, American companies save labor costs, but they lost the daily feel for ways to improve their products.
Speaker 1:Elon bucks this trend. He wants to have tight control of the manufacturing process. He believes That's why
Speaker 2:he puts designs tense up in the parking lot.
Speaker 1:Yeah. He does 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 wanna run through the history of SpaceX, the history of these launches?
Speaker 1:We have Tyler Cosgrove with some some beautiful work on the 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.
Speaker 1:What
Speaker 2:you Professor.
Speaker 4:Yeah. Okay. So I think
Speaker 2:The should intern becomes the professor.
Speaker 1:Class is in session.
Speaker 4:A lot of people, I I think when when they hear these about these launches, they're like aren't even really sure like what rocket is even going on. Mhmm. So so I think you can kind of classify SpaceX rockets into like three distinct types. These are like the active ones that are still Yeah. Going on.
Speaker 4:So there's Falcon nine. So this was like the first really like, you know, commercial like not just tests. 2010, this is like, you know, the ninth iteration.
Speaker 1:Falcon One before which is one engine. Right? I think But those were like mostly tests. They weren't reusable. It wasn't really a business.
Speaker 4:Yeah. That point. Yes. That was 2010.
Speaker 1:Perfect. Alright.
Speaker 3:Can you
Speaker 4:still hear me?
Speaker 2:Yeah. We sound great. So, okay. So we have
Speaker 4:that that's Falcon Nine. Then Falcon Heavy comes out 2018. This is essentially just three Falcon nine boosters just like strapped together. Yep. But it's kind of a separate thing.
Speaker 4:Right? You can These are also always built to be like reusable at least some parts of
Speaker 2:it.
Speaker 1:And that's a big piece of like the Falcon nine has literally just nine engines kinda strapped together. It's all the same engines so that they they get the reusability there. Right? So they're doing like one thing.
Speaker 4:Yeah. Yep. And then we go down to Starship. I mean, is what's currently being tested. Mhmm.
Speaker 4:This is not like doing commercial missions yet obviously. Mhmm. But this is kind of the the next iteration. So this one, they're all kind of two parts. Right?
Speaker 4:But this one has 33 engines on the That's like called super heavy. And then Starship is technically just like the the second stage. Sure. Oh, okay. Yeah.
Speaker 1:Yeah. Yeah.
Speaker 4:Yeah. Yeah. Okay. So then There's two let's go through Let's first go through just like kind of general SpaceX launches. Yep.
Speaker 4:So here 02/2006, this is the first Falcon one launch. This what we're talking about earlier.
Speaker 1:Okay.
Speaker 4:Kind of none of these like really do a lot until
Speaker 1:three failures. It took them And they were almost out of business. They
Speaker 2:Yeah. Yeah.
Speaker 4:In the Yeah. Where he's kind of sitting down.
Speaker 1:Yeah. Yeah. Yeah.
Speaker 4:Yeah.
Speaker 1:In Kwajalein Atoll Pacific.
Speaker 4:Yep. Yep. And then we go to 2010. This is Falcon Nine launch. 2012, this is the Grasshopper Landing Test.
Speaker 4:Okay. These are when the first test of like propulsion landing Yeah. Right? Which we kind of have seen later with the Starship where it catches it. Right?
Speaker 4:Down. Yep. 2012, this is the first ISS cargo mission. Yep. So this was
Speaker 1:And and and the 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.
Speaker 1: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? Yeah.
Speaker 1:That's the strategy?
Speaker 4:Yeah. Then ISS cargo. Yeah. ISS cargo. This was the on the drone ship
Speaker 1:I realized that took four years to get the drone ship right. Yeah. We have that crazy video we should pull up after this that like all the landing failures on the drone ship with think it's like in the hall of the mountain king and it's just like Yeah. Crashes after crashes after crashes. Yeah.
Speaker 1:Okay. So And then
Speaker 4:we go to, this is the first 2017, the first, reflight of a booster.
Speaker 1:Okay. Is first
Speaker 4:time I actually like kind of reused it.
Speaker 1:Fully reusable at that point. Yep. Got
Speaker 4:it. And then 2018, this is Falcon Heavy.
Speaker 1:This is
Speaker 4:the three Falcon Nine's Yep. Together essentially.
Speaker 1:Yep.
Speaker 4:Then this is where they they basically just start to get the cadence record of launches per year. Yep. So this was
Speaker 1:You see there's like there's like time lapse videos. If it goes from like one Falcon Nine launching to like one launching like every
Speaker 4:I think the record before this was The USSR in Oh, really? I think it was like 1979
Speaker 1:or Okay.
Speaker 4:Yeah. It's pretty insane that they had that record. Yep. But then, yeah, we got Starship. So then let's go through
Speaker 1:Starship launches?
Speaker 4:Let's go through Starship launches.
Speaker 2:Okay.
Speaker 4:So first one, 04/20/2023. Yep. So
Speaker 1:it's fully stacked and it took off but it blew up after four minutes. Yeah. Basically, it made Yeah. Update unscheduled
Speaker 4:there's 33. Okay. They didn't all start.
Speaker 3:Okay.
Speaker 4:But that was the first like kind of everything is put together Mhmm. It it goes up. Got it. Then the next test, twenty twenty three November. Yep.
Speaker 4:This is all all 33 engines started.
Speaker 6:Okay.
Speaker 4:That was a big big upgrade. Yep. Then we see it reached orbital velocity.
Speaker 1:Okay.
Speaker 4:So another big step. Yep. June 6, we see both stages kind of go up and then they both reenter.
Speaker 1:Yeah. So they both hit their max altitude.
Speaker 4:Yep.
Speaker 1: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.
Speaker 4:Yeah. Okay.
Speaker 1:But they're making progress.
Speaker 4:Yeah. Cool. Then we go to October 13. This is like kind of famous tower cat.
Speaker 1:Yeah. I remember that chopsticks.
Speaker 4:Blew up the The chopsticks. Yeah. Chopsticks? Yeah. Okay.
Speaker 4:Then, we see November 19. This is the Raptor relates. So, the Raptor
Speaker 1:And the tower catch, did it blow up in the tower? No. They caught it. Right?
Speaker 4:They caught it.
Speaker 2:Oh yeah.
Speaker 1:Yeah. That was actually crazy. Yeah. But 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
Speaker 2:That one was wild because it was so sci fi. Yeah. But it had been almost programmed into people's brains that that was like a thing Yeah. Through sci fi.
Speaker 1:Yeah. Yeah.
Speaker 2:The reaction broadly like people
Speaker 1:Yeah.
Speaker 2:Attack were, you know, pretty blown away but at the same time it just it felt like something that Yeah. A space company
Speaker 1:And could do. The really crazy thing about the tower catch was that it it emphasized how high cadence the actual process of reusability can be because I believe that the the the 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 is fixed.
Speaker 1:Super heavy just goes up and is back in like four minutes or ten minutes or something like that. Yeah. And so, you see it go up and then come right back and get and 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.
Speaker 4:Yeah.
Speaker 1:So like the pace of iteration is is the 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.
Speaker 4:Yeah. Space port. Let's go to first block two launch. Okay. So block two Yeah.
Speaker 1:It's block two.
Speaker 4:That's like when you look at the starship like basically the top section Mhmm. There's been a couple It's kind of like this part. There's been a couple iterations of this. Mhmm. So this was kind of the next big like upgrade.
Speaker 1:Yeah.
Speaker 4:And then we see March 6, we see a payload attempt. So so this is what you're talking about earlier where they try to
Speaker 1:Open the doors.
Speaker 4:Open the doors, put out they're they're not real Starlink Yeah. Satellites but they're like, you know, Mach ones. Yep. Then we see Super Heavy Reflight. So so this was Super Heavy again is the this booster.
Speaker 4:That's the first time they like actually reuse the Caught same it
Speaker 1:and then put it back up.
Speaker 4:Wow. Yeah. Like it it didn't actually go back up but they like re ignited it basically and it worked. Wow. And then this one just yesterday was payload deployment and then we talked about this earlier.
Speaker 4:They both had controlled splashdown in the ocean.
Speaker 1:It's amazing.
Speaker 4:Yep.
Speaker 1:What a journey. Well, congrats to everyone.
Speaker 2:Small note that that that it explodes. It explodes. But next time.
Speaker 1:Next time. Next time.
Speaker 2:That matters there was a controlled touchdown.
Speaker 1:Thank you for the breakdown, Tyler.
Speaker 2:Thank you. Feel free to keep the helmet on for the rest of
Speaker 1:the And feel free to sign up for Vanta, automate compliance, manage risk, prove trust continuously. Vanta's trust management platform takes the manual work and security out of your security and compliance process and replaces 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.
Speaker 1:Starlink is quietly building one of the biggest cash generators of our time in Redmond, Washington. It's also where Coopier, AWS, and Azure are. 80% plus of of all satellites launched globally in last year were designed, built, and tested in Redmond. There's a reason we put Star Cloud Inc. In Redmond, and we're on the lookout for more amazing talent.
Speaker 1:So good luck to Philip Johnston. Hopefully, the VCs come around to the good work that folks are doing in Redmond, Washington.
Speaker 2:What if we moved Redmond to the Gunda?
Speaker 1:We could. We could. I think there's probably a for all these companies, there's there's assets in all in in all the different places. I I haven't heard of a company really going deep into South Texas and like because a lot of the Gundot companies are beneficiaries of the work that SpaceX did in Hawthorne and El 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 is currently owns the original SpaceX factory in El Segundo because they've moved out because they obviously, they scaled up. But a lot of the Gundot companies are beneficiaries of the work that SpaceX did in El Segundo to kind of bring back that industrial capacity.
Speaker 1:Of course, before SpaceX, there was Lockheed and Northrop and a few other primes that were in the area and still are. But the Gundos been like a great home for defense tech broadly. Maybe Redmond's the next one. Maybe maybe you gotta do some if you're doing satellite R and D, gotta get a Redmond off an office. If you're doing launch stuff, you wanna head out to South Texas because they do seem pretty friendly out there.
Speaker 1:At the end of the the SpaceX stream, the 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.
Speaker 2:Well, they got a stock exchange now.
Speaker 1:They do.
Speaker 2:That's right. Got Nicey Texas.
Speaker 1:Nicey Texas.
Speaker 2:Something something down something happening in the in the Lone Star State.
Speaker 1:Yeah. I haven't been to Texas in years. Last time I actually went was for David Center's thing.
Speaker 2:Really?
Speaker 1:Yeah. Other than that, I don't find a lot of random time to go there. It's been a lot of New York, lot of SF, a little Miami.
Speaker 2:But I have been a bunch.
Speaker 1:When was the last time you went?
Speaker 2:Last year, I think I went three or four times for different portfolio companies.
Speaker 1:Yeah.
Speaker 2:Great place. Great place.
Speaker 1:Do we have the video of the the the SpaceX explosions over time? They have this montage reel. I'd love to play that. You can find that as Give us a sec. I tell you about graphite dot dev code review for the age of AI.
Speaker 1:Graphite helps teams on GitHub ship higher quality software faster.
Speaker 2:Alright. I'm throwing it in the timeline. This is Go the to graphite dev best that I could find.
Speaker 1:We will be talking about venture debt and what's going on in But that in the meantime, I believe we have a video of SpaceX's launches
Speaker 2:SpaceX themselves, how not to land an orbital rocket
Speaker 1:Yes. This is the video I wanna 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.
Speaker 1:List one.
Speaker 2:The top comment is this is 100% the most expensive GT
Speaker 1:down video ever made. Down so fast. The first one is just like you didn't stop at all. Here we go. Uh-oh.
Speaker 1:Uh-oh. Uh-oh. Uh-oh. Uh-oh. Oh, no.
Speaker 1:Wow. There we
Speaker 2:go. Beautiful.
Speaker 3:But
Speaker 2:This is great. Unfortunately, all this equipment The smoke's still coming off.
Speaker 1:That yeah. How is that not just gonna blow? That seems dangerous to be around there.
Speaker 2:Yeah. That's a lot of confidence in your product for you
Speaker 1:Especially for something that, like, it blow it actually blows up. Yeah. Here it is on the drone ship, believe, smashing down constantly. This one, trying so hard, lands, and then it's definitely gonna blow. There we go.
Speaker 1:You know it's gonna blow up. Oh. Every time.
Speaker 2:The music?
Speaker 1:Yeah. The music's great. I thought they had a different one with the Hollow Mountain King. Wait. What is coming off of that?
Speaker 1:Why didn't they use the chopsticks? Yeah. Tyler, do you know why they didn't go for chopsticks on this one? Instead did
Speaker 4:this Originally?
Speaker 1: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.
Speaker 2:This is brilliant marketing. Yeah. It's the yes and.
Speaker 1:This is so good.
Speaker 2:The yes just
Speaker 1:tilting all over the place. Why is it tilting? It's not even going. It's just
Speaker 2:Well, it's a ship on the sea.
Speaker 1:On the ship and it's just about to fall? This is crazy. Oh, it actually made it. It seems like. This one's coming down.
Speaker 1:Oh. That was a tough one.
Speaker 2:Solid? Okay.
Speaker 1:Solid. It's gonna explode. You know it's gonna explode. This is insane. So good.
Speaker 1:Oh, I could watch these all day.
Speaker 2:Not bad. Anyway,
Speaker 1:onto venture debt Yeah.
Speaker 2:Let's get into the journal The really some no. The beat of the
Speaker 1:really burning up the timeline what is the the audience is clearly celebrating? Gulfstream Aerospace has joined us in officially welcoming the world's first the world's longest range aircraft to the skies. The first 8,200 nautical mile g 800 has officially
Speaker 2:been world's delivered longest range business aircraft.
Speaker 1:To a customer at our Appleton, Wisconsin completions facility. Look at that plane. So let's give it up for Gulfstream Aerospace.
Speaker 2:They don't have the luxury of having the They quite the number of explosions that
Speaker 1: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.
Speaker 2: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 start ups stay private for longer. Venture debt value hit a record 53,000,000,000 in 2024, up from 27,000,000,000 in the prior year and more than a previous high of 42,000,000,000 in 2021.
Speaker 2: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 it's pretty incredible to see the growth.
Speaker 1:Yeah.
Speaker 2:As the value of deals rose, however, venture debt deal count fell to 1,300 transactions in 2024, the lowest level since 2016. The trend continued during the 2025 with a little more than 19,000,000,000 of venture debt deal volume according to a separate report by Capital Advisors Group. Mhmm. Great great name. Very very very generic.
Speaker 2:But if you can own it, it's powerful. Yes. Debt must react to equity, said Stefan Spazek, director of debt placement at Capital Advisors Group. Venture debt providers have have to target stable companies with solid revenue if if there is a lack of equity or sponsors decide to pull back on equity commitments to their portfolio companies. He added.
Speaker 1:I didn't fully understand this because it feels like there is very much not a lack of equity right now. But is it it it like, what is he
Speaker 2:Well, I mean, he's saying I mean, he's saying that there's hope. That's the big risk. Right? If a company Sure. Running in the red and
Speaker 1:they Oh, raise their next
Speaker 2:round. Sure. Sure. Get into
Speaker 1:Yeah. Yeah. Yeah. Yeah. If this if the current backers aren't doubling down at series c Yeah.
Speaker 1:D, e, f, which is the vast majority of companies. Like, they're we we focus on the companies that successfully raise every single round. Anyway
Speaker 2:Start ups 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 industry's liquidity constraints to continue into next year. Runway typically writes checks of roughly 30,000,000 and it lends to tech, health care, and consumer. Earlier this year, for example, data and AI company Databricks announced a $52.5.2.
Speaker 2:5,200,000,000.0. You never know what Databricks. They might be raising $52.52. 52,000,000,000. Announced a 5,200,000,000.0 credit facility shortly after close.
Speaker 1:Wanna be 50% debt to equity on this company. This high growth tech company.
Speaker 2:I think it's like After David.
Speaker 1:$150,000,000,000 company now or something. It's over a 100. It's it's like Yeah.
Speaker 2:They they just use the the the greater than
Speaker 1:Yeah. That's right.
Speaker 2:That's right. Yeah. Which is like, who's counting it?
Speaker 1:The last the last deal was a $10,000,000,000 series j. Oh, that wasn't in
Speaker 2:the last series k.
Speaker 1:They did the k?
Speaker 2: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 JPMorgan Chase, Morgan Stanley, and Goldman Sachs. Let's give it up.
Speaker 1:And Blue Owl's in and Apollo Global's in and Blackstone's in.
Speaker 2:Just a couple names.
Speaker 1:They really they really
Speaker 2: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.
Speaker 1:Yeah. Says As companies scale and stay private longer, we see a significant opportunities to support high quality businesses with flexible credit solutions. Earlier this month on the smaller side, Runway committed 20,000,000 to Swing Education, an online marketplace that connects 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 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.
Speaker 1: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 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 gonna 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.
Speaker 2:Yeah. So since the 2023 collapse of SVB, one of the most active venture debt providers, more lenders have entered the market or 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 is capitalized on the opportunities created by SVB's collapse is long time venture debt lender, Hercules Capital, great name, Which typically invest around 40,000,000 in debt deals. The firm's deals generally have a 15% loan to value ratio, meaning the borrower's loan volume represents 15% of its total value.
Speaker 2:Hercules is focused on tech and life sciences. Earlier this year, Hercules entered into an agreement with publicly traded biotech company Moon Lake
Speaker 1:Mhmm.
Speaker 2:Immunotherapeutics to provide up to 500,000,000 in non dilutive capital. At the close, there was a $75,000,000 drawdown with additional tranches becoming available upon achievement of certain specified milestones. Our biggest competition is the equity market. Mhmm. Again, this should be obvious to everyone listening but founders are kind of going out and saying, need say, I need a 100,000,000.
Speaker 2:Do I wanna do I wanna take the potential risk that comes with equity financing even if I'm gonna be or sorry. Potential risk that comes with leveraging debt even if I'm benefiting from the lack of dilution? Or do I just wanna go and raise a fresh primary round? Anyways, good to good to see the market recover.
Speaker 1: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 53,000,000,000 last year. The prior year was garbage. 27,000,000,000 in 2023, obviously, high interest rates, major pullback in the startup and venture community, kind of healing from the from the turmoil of, like, the SVB crisis.
Speaker 2:Was March 10.
Speaker 1:March 2023. Was when SVB went bankrupt. So Yeah. It's like it's like, yeah, of course, 2023 was gonna be a bad year. 2021, two years prior, was up at 42,000,000,000.
Speaker 1:So we went from 42,000,000,000 down to 27,000,000,000, but are now at a new high watermark of 53,000,000,000. But what's changed is the fact that the deal count fell to 1,341 transactions in 2024, which is the lowest since 2016.
Speaker 2:Doing less deals.
Speaker 1: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 Cruseaus 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 $10,000,000 series a and get $2,000,000 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 it was always like kind of it all goes into one cash bucket and you kind of spend it however you want.
Speaker 1:But in but it 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 to, you know, a $5,000,000,000 venture, you know, credit facility for Databricks.
Speaker 2:Yeah. If you remember
Speaker 1:Even a $20,000,000 series like like, venture debt round, like, that's pretty big for Swing Education.
Speaker 2:Bench, if you remember, got in a rough spot with venture debt and ended up being acquired by that that company employer.com. Mhmm. I guess they had they were a decent business, but it tripped some Yeah. Debt covenants and were forced to abruptly shut down. Yeah.
Speaker 2:And then they were ultimately acquired after
Speaker 1:Yeah. And 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 gonna get their money out first. And so even though they don't have board seat, they do have incredible leverage over the company and they actually have a sort of control that should be definitely considered.
Speaker 2:It's very The one could call it senior.
Speaker 1: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 a $100,000,000, they would loan you up to $15,000,000 in venture debt.
Speaker 1:In the previous era where I was more familiar with this, it was like you would raise $20,000,000 series a at a $100,000,000 post. The VC takes 20% of the company in a board seat. And then
Speaker 2:on low single digits of
Speaker 1:million in venture debt. 3,000,000 in venture debt. Like, loan to value of, like, 3%, 4%. But I think this 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 revenue
Speaker 3:Well, yeah.
Speaker 2:And the real we 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 Yep. On your balance sheet.
Speaker 1:Yep. Totally.
Speaker 2:Otherwise, we're going to Yeah. You know, require
Speaker 1:And 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 VCs 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 in another way more risk off by because they were writing so so much lower.
Speaker 2:Jason Jason O'Connor says, this show is like a Buddhist statue I have in the background to hopefully bring in good luck and fortune.
Speaker 1:Thank you, Jason.
Speaker 2:Jason. Exactly what we're going. We're praying for you and your capitalist endeavors Okay. Always.
Speaker 1:I wanna 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 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%.
Speaker 1:And the rules here are on February 28, Elon Musk posted that it was likely Starship would become fully reusable in 2025. The market will will revolve resolve to yes if SpaceX or Elon Musk announces that Starship is fully reusable by 12/31/2025. 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.
Speaker 1: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 they were saying that during this last SpaceX flight, they deliberately took off a bunch of tiles just to kinda like see if they could do it.
Speaker 1:What would happen? And so, like, you can tell when as the rocket comes down, like, a lot of those tiles got roasted. And so they might have to, you know, swap those out. There are elements that aren't reusable. But
Speaker 2:definitely you'll gonna swap out the stuff that was flying around.
Speaker 1:All the insulation or something. That was one
Speaker 2:of the
Speaker 1:wildest wildest bits that I've seen.
Speaker 2:Anyway Well, we have this chart here.
Speaker 1:Yeah. We have a chart on we we 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 US government is now the proud owner of 10% of Intel's shares. You.
Speaker 1:You, The US 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. So If
Speaker 2:you were worried that you didn't have exposure, you can
Speaker 1:Yeah. Yeah. Yeah. You can you can you can you can send the the layered SPV emails that you've been getting to the archive and 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.
Speaker 1:Semi analysis seems pretty bullish. Gave the latest the last it gives The US the the last US chipmaker an actual chance to catch up, spur the domestic sector. The the the bid here is that the the Intel story with the government is not gonna 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 China Talk, is also bullish. He says it's Intel's only chance is government support.
Speaker 1:The US needs domestic chip fabrication capabilities, and this is is a good path. Ben Thompson has a slight positive bias. He he he pulled out the steel man term and kinda steel manned it. He said national security and the economy concerns are too accurate or too acute to not keep Intel Foundry viable. Although there he does cite Scott Linscomb who's extremely bearish and this says this will lead to widespread inefficient capital allocation in the chip sector.
Speaker 1:That, of course, is the fear. The Wall Street Journal is also somewhat bearish, Pitting essential US partner Samsung and TSMC against a government owned competitor is a bad idea. I was talking to a few other folks that both they they predicted this, but they didn't think it's necessarily the good outcome.
Speaker 2:It has ripple effects if if other companies are getting the or getting strongly encouraged to use Intel's Yep. Services.
Speaker 1:Yeah. It could make those companies less competitive potentially.
Speaker 2:Yeah.
Speaker 1:The the Asianometry was constructive on the on the deal, said could make the deal work by using Intel and as an NVIDIA second source. And, of course, this could potentially hurt NVIDIA's margins because the CPUs that NVIDIA makes, I believe, 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 the amazing business they built. Of course, NVIDIA is reporting earnings today, and we are looking forward to tracking
Speaker 2:that I have a post here from Buco Capital Bloke, the third technology brother. Yes. It 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.
Speaker 2: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.
Speaker 1: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.
Speaker 1:That's a slippery slope. So we will be monitoring the slope to see how slippery it is. Hopefully, it's the slope of illusionment. What is the Gartner hype cycle again? This Slope of enlightenment?
Speaker 2:The slope of productivity. The trough.
Speaker 1:Know where you are on the Gartner hype cycle.
Speaker 2:Are We're working on some
Speaker 1:more We're gonna crunch all the data. We'll throw it in Julius.
Speaker 2:Of course.
Speaker 1:What analysis do you wanna run, chat with your data, get expert level insights? I want to know how people are tracking on the Gartner hype cycle.
Speaker 2:Yep. Alex Heath just shared a link. He said TikTok's parent company is making more revenue than Meta and is worth less than 20% of its market cap.
Speaker 5:Mhmm.
Speaker 2: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 330,000,000,000, driven by continued revenue growth. The company plans to offer offer current employees $200 per share in the repurchase program. The people said up 5.5% from a $189.
Speaker 2:It 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
Speaker 1:Mhmm.
Speaker 2:With its second quarter revenue up 25% year on year. The jump resulted in the company's second quarter revenue hitting about 48,000,000,000, most of which is is from the Chinese market as it continues to face political pressure to divest its US arm. And apparently, TikTok's US operation remains unprofitable. So
Speaker 1:US operation? Yes. How is that possible?
Speaker 2:Good question.
Speaker 1:They have so many ads and stuff. And I thought they were taking a big cut of
Speaker 2:I think TikTok TikTok shop
Speaker 3:Yep.
Speaker 2:Is wildly unprofitable. That's
Speaker 1:right. We're subsidizing a bunch of stuff there. Yep. Wow. Well, maybe it's gotta go to Jensen.
Speaker 1:Maybe it's gotta go to Oracle. We'll keep monitoring.
Speaker 2:Let's give it to Larry. Yeah. I'm in favor of giving it to Larry.
Speaker 1:Anyway, if you're going beyond getting your brand mentioned on TikTok, you're trying to get your brand mentioned on ChatuchikiT, head over to ProFound, reach millions of consumers who are using AI to discover new products and brands. AJ over at Semi Analysis 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.
Speaker 2:And remember, Cursor poached the Claude two people on the Claude code team
Speaker 1:They went over to
Speaker 2:Cursor for a couple weeks Yeah. Were back. In Anthropic.
Speaker 4:I think it was only one week.
Speaker 1:One week? Yeah. That is a crazy short stint. Droid says the market implied mandate of heaven. I mean, yeah, they they like the the the culture at Anthropic is extremely unique.
Speaker 1: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 I was thinking about that quote the other day because if you look at the data center capacity and the and the how pre training is scaling, like, is a straight line on a log linear graph. We're 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.
Speaker 1: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 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?
Speaker 4:So then the question is like where are we on the
Speaker 1:On the s curve?
Speaker 4:Yeah. Where are we on the s curve?
Speaker 1:I don't know. I think I mean, we're pretty early. Pretty early? Yeah. I I I do think we're early, but I I think that there's I don't know.
Speaker 1:There's just a there's, like, 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 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, they're actually, like, you know, we overinvested.
Speaker 1:We need to pull back for a few years. This is what happened during the the .com boom. Like like a lot of those fiber investments made sense over a ten year, twenty year period, but they were overheated in the short term. And so that just created like a freeze and all of a sudden, didn't get a continuous build out. Or we did, but we didn't get continuous capabilities.
Speaker 1:I don't know. We'll see. What do you think?
Speaker 4:I mean, I'm bullish. Yeah.
Speaker 1:What do you think about the fact that it feels like model capability is is like very discontinuous? Like, it feels like
Speaker 4:Well, how do you mean discontinuous?
Speaker 1:It feels like it feels like we get we like like, we are on a we are on a smooth path of like bigger models, chopping wood, training things, but, like, only this is the room take. Like like, as technology rolls out, it rolls out in this, smooth curve, but then you experience, like, a few discontinuities when, like, new capability comes on comes online. Or like the ChatGPT moment, like there wasn't really that much like like if you were to if you were to just look at the 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 GPT three and in between GPT five and in between like, you know, like medium sized models, big models and then even bigger models. And and like you couldn't you couldn't see, there's no kink in the graph at at at the ChatGPT moment. There is on the user side.
Speaker 1:There is on the revenue side, but there's not on the actual, like, scale of data center side. It's not like we went from, like, nothing to something on the actual data center build out side, and that caused the like, 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.
Speaker 4:Yeah. Mean, I don't think it matters that like you're probably gonna see another kink in user
Speaker 1:Yeah.
Speaker 4:Usage when school starts again. And everyone's like, wow, GPT five is so good because no one's ever used to reasoning model before.
Speaker 1:Yeah. Did you see this did you see this post about someone said that GPT five caused like a a major drop off? This is from Marie Martins. The model giveth and the model taketh away. User registrations coming from AI search.
Speaker 1:ChatGPT was like this huge boom.
Speaker 3:Mhmm.
Speaker 1:You see this, Jeremy? And then GPT five launched. And this is like way deeper in the slides.
Speaker 4:Yeah. I I saw I mean, there was another like somewhat similar chart Yeah. That was like going around a couple weeks ago where it was like, 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.
Speaker 4:This is like for one organization. It was only like a 100,000. Like it was obviously not actual usage.
Speaker 1:Yeah. I would be very surprised if 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, the the install base is so big, it can't just be students. Right?
Speaker 1:Like
Speaker 4:Yeah. And then so mean, I'm a little hesitant to like Yeah.
Speaker 3:Pull a
Speaker 4:lot of stuff from from that graph. Sure. But Makes sense. It seems it seems very weird.
Speaker 1:Yep. I don't know.
Speaker 2:Anyway This is super What? Interesting chart from from Mary
Speaker 1:Yep.
Speaker 2:Martin. She is the founder of Tally Forms.
Speaker 1:Yeah.
Speaker 2:And, yeah, basically calling out they were getting a ton of registrations from people just in chat GPT.
Speaker 6:Mhmm.
Speaker 2:And then all of a sudden dropped off a a cliff. So
Speaker 1:Yeah. Let's see. Figure out
Speaker 2:what There's some debate in the comments around how GPT five start stopped adding UTM parameters to request.
Speaker 1:Oh, interesting.
Speaker 3:So there
Speaker 2:could be an attribution
Speaker 1:Yeah.
Speaker 2:Issue there. But they're saying
Speaker 1:Yeah. I mean, we we definitely want her to zoom out and look at overall registrations and see if there's a a fall off in those because Yeah. Was this 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?
Speaker 1:And and it's just like it feels like it's coming from a different from a different source, but
Speaker 5:in fact Well,
Speaker 2:it's impacting Pop Mart CEO and founder Wang. It's not. Ning. He's now the seventy ninth richest person in the world. According to Morning Brew, his net worth has grown by 20,000,000,000 this year.
Speaker 2:It makes him richer than names like Peter Thiel, David Tepper and Steve Cohen.
Speaker 1:Steve Cohen.
Speaker 2:Wow. Laboo billionaire.
Speaker 1:Laboo billionaire.
Speaker 2:That is great. We helped we contributed to this by buying a Labooboo for
Speaker 1:Oh, we did. Bishops. For Bill Bishops, So
Speaker 2:it's on the way, Bill. Toshy. Yep. Very excited for that one.
Speaker 1: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.
Speaker 1:So let's say in 2023, you train a model that costs a $100,000,000, and then you deploy it in 2024, and it makes $200,000,000 in revenue. Meanwhile, because of scaling laws in 2024, you also train a model that costs $1,000,000,000. And then in 2025, you get 2,000,000,000 of revenue from that $1,000,000,000, and you've spent 10,000,000,000 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 a $100,000,000 the first year. You've lost 800,000,000 the second year, and you've lost 8,000,000,000 in the third year.
Speaker 1:So it looks like you're getting worse and
Speaker 2:worse. Exponentially.
Speaker 1:If you consider each model to be a company, the model that was trained in 2023 was profitable. You paid a $100,000,000 and then it made 200,000,000 in revenue. There's some cost to inference the model, but let's just assume in this current Tunisia 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 GPT-four.
Speaker 1:That was obviously I think that was like around a $100,000,000 training run, something like that. And they've clearly made a ton of money back from that because GPT-four 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.
Speaker 1:Like he's exposing the truth that like, these will never make money because they're just gonna continually invest endlessly. I didn't see it that way at all. This makes perfect sense
Speaker 2:to At some point, you could just stop training. The the question is, can you just stop training new models and just
Speaker 1:Well, profits this is
Speaker 2:of old models.
Speaker 1:Yeah. Well, it it's more just like at at a certain point, run out of you run out of you you kind of tap the capital markets because maybe you can't raise $10,000,000,000,000 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 ten years, you can afford the next run. Right? Because you train the model for a 100,000,000.
Speaker 1: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 invest, you know, dollars 1 in a model that makes you $1 next year, dollars 2 next year.
Speaker 1:Then you take then you wait ten years. You save up $10 then you do the $10 run. And you expand until you do the $100,000,000 training run that makes you $200,000,000 the next year and $200,000,000 the next year. And you know what you have after five years? You have a billion dollars in profit.
Speaker 1:What do you do with that billion dollars? You train the next model. Then you wait five years. And then you train and then you save 10,000,000,000. Then you train the $10,000,000,000 market.
Speaker 2:Assumes that this assumes, of course, that you would have a competitive offering in the market and you wouldn't be getting
Speaker 1: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 a $100,000,000 into a foundation model company. There were, like, 20 companies that raised a $100,000,000 to train foundation 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.
Speaker 1:Now you have who's who's gonna put up 10,000,000,000 to do the the the really big training run? It's gonna be a few labs. It's gonna be OpenAI, Anthropic, Meta, Google. Right? As we get to the 100,000,000,000, yeah, we might have to wait a little bit.
Speaker 1: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 have to if you can't immediately marshal $10,000,000,000,000, a $100,000,000,000,000. Yep. Like, right now, we are in the phase of like snap your fingers in the capital marshals because we're we're in this we're in this era where the Yeah. Games So remember,
Speaker 2:Dropbox round was so oversubscribed, they ended up, I think, doubling the allocation.
Speaker 1:Yeah. And so this could continue for a while. Concern I mean,
Speaker 2:the yeah. The concern is that you can't can't seems difficult for even the big labs to do another 10 x on on these pending training runs.
Speaker 1:Yeah. I mean, that's what Stargate is. Right? It's a $500,000,000,000 project. And so that's probably like a $100,000,000,000 commitment in the medium term or getting into the trillion territory.
Speaker 1:Maybe it continues forever. May maybe everyone on Earth kind of just says, like, yes, we're willing to,
Speaker 2:like Yeah.
Speaker 1:Everyone sell all your gold and convert that.
Speaker 2:But I think if you're I
Speaker 1:think if you're
Speaker 2:on Wall Street
Speaker 1:Yes.
Speaker 2:Traditional finance Yes.
Speaker 4:Guy Yeah.
Speaker 2:Or girl, and you're looking at this. And and in in biotech, you might have something where it's like, hey, we need to spend $5,000,000,000 developing this drug Yeah. But then it's gonna be good and we're gonna be able to sell it for a
Speaker 1:really long time. This is everybody's Having
Speaker 2:Yeah. Massively uncertain future capital requirements Yep. Is gonna just be a concern and an asterisk on the business. Yep. So I think that's like Finhub Yeah.
Speaker 1:That's why people are saying
Speaker 2:is is really the concern here. You have exponentially increasing costs and just wildly uncertain future capital requirements.
Speaker 1:Yeah. And so the it it like the way to deal with that like uncertainty, those jitters and like the later stage investors who are who are you have to talk to to marshal. Yeah. 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 $10,000,000,000 and we're making $2,000,000,000 in profit. In five years, we'll be able to pay that.
Speaker 1:So you can, you know, give us the money now to pull forward what's obviously gonna pay off again. And we're confident that the next 10 x is gonna get us another 10 x in 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.
Speaker 1:We might compress. We might go faster. We'll we'll see.
Speaker 2:Well Dan Ratliff in the chat says, Elizabeth Holmes has hit the timeline. She has been That's posting true. Ripping posts. She quoted quote quoted Brian quote tweeted Brian Johnson earlier. Yeah.
Speaker 2: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.
Speaker 2:And, yeah. She's ripping some comments. She's getting active on the timeline.
Speaker 1:Now, this is Mostly my not words. Her. Right? This is her Mostly my
Speaker 2:words. Yeah. Hosted by others. Yeah. I wonder if she's getting paper printouts of
Speaker 1:Probably over the phone.
Speaker 2: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 gonna launch cash tag Theranos meme coin, isn't she? And Elizabeth says, never. So anyways, having having fun on the timeline.
Speaker 1:Yeah. Imagine thrill of having posts read to you over the prison phone and then replying, okay. Yes. Like that one.
Speaker 2:She said last The post time that one. 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.
Speaker 2:Where did the little blue bird go? What happened?
Speaker 1:This is funny lore. This is like an odd it would be weird to be offline for so long.
Speaker 2:She's she's responding to an Elon Musk saying, for my part, I never I will never give up and I mean never. And Elizabeth says, this is one reason Elizabeth oh, sorry. This is one reason Elon Musk wins. He never gives up. That's what it takes.
Speaker 1:Really?
Speaker 2:It doesn't sound like it doesn't sound like Elizabeth Holmes is giving up either. But she seems to be a big Elon Musk fan.
Speaker 1:I have been shocked by the out of home campaign. Have you seen this?
Speaker 2:The Which is Love by Blood?
Speaker 1:Hurts. I 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 Is there all over new company? Yeah. There's a new company.
Speaker 1:I think they're out raising. 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
Speaker 2: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.
Speaker 1:It's crazy that
Speaker 2:they didn't think
Speaker 1:Yeah. They didn't even think to put like the rough outline of Europe, you know, and be like, yeah, 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 and England. And we got Ireland in there, of course. Gotta keep Ireland in there.
Speaker 1:Well, if you're building the next Google Maps, get on linearlinear.app. Linear is a purpose built tool for planning and building products. Meet the system for modern software development streamline issues, projects, and product road maps. And so building.
Speaker 2:Travis Kelce, right after the announcement Yes. Launches American Eagle Collection. Yes. And Michael Mirafloor says nothing is sacred. Monetize everything.
Speaker 2:Let's see. Let's check-in on the American Eagle stock. It is up another 9% today. So they're just on an absolute tear.
Speaker 1:Yes. Everyone in tech has been focused on the the Taylor Swift wedding, particularly what it means for NVIDIA earnings. I have a little thesis here. So
Speaker 2:Yep.
Speaker 1:Obviously, Taylor Swift getting engaged, that's gonna draw a ton of attention towards the NFL. We've already seen the NFL had a measurable swift effect from twenty twenty three to twenty twenty four. They saw 9% gain in female viewership Solid. Year over year in 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.
Speaker 1: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. Yep. You need clipping, scene detection, player ID, small object tracking.
Speaker 1:All of this is gonna run on NVIDIA GPUs. Globalization, you need translation at the edge. Another Classic speech AI. 100,000,000,000
Speaker 2:for Jensen.
Speaker 1:Teach 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, podcast shorts, consumer AI effects, noise removal, eye contact correction, studio voice, increasingly GPU intensive workloads.
Speaker 1:People are gonna be running RTX PCs with NVIDIA broadcast software to get to get this stuff. Ad dollars also follows attention. Incremental audience, especially for for the new female demos. This is gonna pull premium, premium dollars to sports ads budgets. This pushes ad tech recommender systems, ranking, creative optimization, frequency control.
Speaker 1:These are among the most compute hungry inference workloads and an NVIDIA sweet spot. They have Merlin, for for, for recommendations, of ads and Triton for serving ads. Stream quality is gonna be an arms race. The women, the the the Swifties, they're gonna they're gonna demand four k feeds. Platforms are gonna race to improve video.
Speaker 1:They're gonna need to accelerate this with CUDA. This means more GPU accelerated pre and post processing in cloud workflows. Sports production is gonna modernize autonomous cameras, analytics, our blueprint for low tier games. These techniques climb the stack for tentpole events. More AI in the truck, more GPUs at the edge in in in in cloud transcode farms.
Speaker 1:Hyperscale Hyperscale CapEx is the real lever here. AWS, Google, Microsoft, Meta, they fund the compute behind all of this. Imagine twenty twenty six CapEx guys are going through the roof over 10. We're gonna be in hundreds of billions of dollars just supporting the Swifty demand for NFL content Yep. Powered by
Speaker 2:media. Exactly.
Speaker 1:And so all of this is gonna translate into earnings, of course. Showcases durable broad based inference demand in media and ads exactly the vector analysts wanna 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.
Speaker 2:Groundbreaking. Gabriel says, this is the music that Keith or Boyd 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.
Speaker 1:Replay this video? This video is hilarious. In the meantime, while they're pulling it up, I'll tell you about Numeral. Sales tax and autopilot spend less than five minutes five minutes per month on sales tax compliance, numeralhq.com. And you know who's gonna need to use numeral, Travis Kelce's new American Eagle line.
Speaker 1:If you buy some American Eagle, they said inside Travis Kelce's new American Eagle line, an ad with athletes including Sunni Lee and Keon Anthony. The day after it was revealed that Travis Kelce put an eight 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, a e x True Colors by Travis Kelce will launch in two drops today and on September 24. So get ready and make sure that you're paying your sales tax on True. H color u t Michael Mira Flor says nothing is sacred. Monetize everything.
Speaker 1:Let's pull up the the DJ that
Speaker 2:The video the video is gonna be Bad? Almost impossible to find.
Speaker 1:Okay. It's deep in the Oh, they got it. They did it. Team got it.
Speaker 2:Let's pull
Speaker 1:it up. Let's play this.
Speaker 2:Get the audio.
Speaker 1: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 this.
Speaker 1:Did you listen to this? You think it's good?
Speaker 2:Very Reddit coded.
Speaker 1:Yeah. But this I can't believe there's so many people in this putting up with this Mario song. What what event is this? It doesn't it does inspire me. You know what we need?
Speaker 2:Like, great reddit drop.
Speaker 1:We need we need this you see the the it's like they blow this fog around. Look at this.
Speaker 2:Me, Mario. Yeah.
Speaker 1:The the the there's, like, c o two can cannons for sure. Like that to blow
Speaker 2:the smoke. Got something good out of this. Ben, we need the c o two cannons.
Speaker 5:C o two
Speaker 1:Whatever those yeah. Whatever those DJ equipment are. Oh, yeah. During the lightning round, when we're interviewing a a
Speaker 2:And Nick, can you look into the health impact of being in a studio space with CO2
Speaker 1:cannons? Regardless, this is very David Solomon coded. Yes. You have to be a Mario fan to understand. Yeah.
Speaker 1:I I I I get it. I don't know if this would be for me and a big crowd, but who knows? Maybe maybe it's It seems like they had fun and I'm happy for them.
Speaker 2:These days not not big into paying to be in a crowd.
Speaker 1:Yeah. That's The
Speaker 2:pay to avoid one.
Speaker 1:Yeah. Yeah. Yeah. That's that's rough. Anyway, let's go to Will Menidas.
Speaker 1:He says, hard to think of a piece of writing that's had a greater impact on my life than John Ludwig's index mindset in 2021. This pro index tendency, writes John Ludwig, pervades the private tech market 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 risk seeking expansion, you focus on steady compounding preservation in venture capital. Instead of concentrated bets, you focus on deployment pace and IRR.
Speaker 1: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 tenures and being focused, you focus on one to two year tenures portfolio building, lots of logos on your resume. In re in research and development, instead of being radically 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.
Speaker 1: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 they should like, it is it is an indictment of the venture community if there's not a single fund out there that has a negative or a single vintage that has negative returns because they weren't taking enough risk.
Speaker 3:Oh, it's median.
Speaker 1:Yeah. Yeah. Median. But yeah. Yeah.
Speaker 1:And it's vintage, so it's broadly. Of course, there are funds that don't do more bad. But it's like as an asset class.
Speaker 2:Well, we might be turning it around.
Speaker 1:Anything's possible. Of risk people heading back. 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.
Speaker 1:The tech industry has too much to lose. And I love Will Menidas 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
Speaker 2:drawing all over it.
Speaker 1: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
Speaker 2:to John
Speaker 1:Ludig. Sutrini says, time to bust out the no sequel Negroni's again.
Speaker 2:So I think this was a picture from 2021.
Speaker 1:I think so. There was a Tiger Global
Speaker 2:meet up. This is when I think it was roughly thirty percent of all dollars in the venture industry were going to founder dinners and little and little events like this.
Speaker 1:Essentially. Essentially.
Speaker 2:It felt like that at the time.
Speaker 6:It was close.
Speaker 2:They had the no SQL Negroni.
Speaker 1:Yep. And The Tiger Tonic, the machine learning margarita, the AI artificial inebriation special.
Speaker 2:Which is a non alcoholic beverage.
Speaker 1:Interesting. Interesting.
Speaker 2:I say bring it back, Tiger.
Speaker 1:Yeah. I think you could go further further. We we we gotta come up with our own little menu of funny things. So We didn't have a menu at our at our event in New York.
Speaker 2:This was an interesting Yep. Screenshot.
Speaker 1:This one from Fewer Not Ai, the number one AI agent for customer service.
Speaker 2:That's right.
Speaker 1:Number one in performance benchmarks. Number one in competitive bake offs. Number one ranking on g two, fin.ai. I will never apologize for cutting you off
Speaker 2:For an advertiser.
Speaker 1:For an advertiser. Continue, Jordy Hayes.
Speaker 2:Event. Fewer people can bench two twenty five than are worth 10,000,000. In The US, about point 4% of the population, around 1,300,000 people can bench 225 pounds. Globally, the percentage is likely below point 1% Wow. With some estimates as low as point o 7%.
Speaker 2:2.13 US households have a net worth of 10,000,000 or more constituting approximately 1.6% of all households. If you can bench two plates, you're already stronger than 99% of people on the planet, just maybe not richer. And Zach Voell says what everyone is thinking. Only job is to do both. And we firmly
Speaker 1:Both are a grind, but well worth it. It's the grind to $2.25 was was serious for for many on the team and I think almost all of us have gotten there and are now beyond. It's it's well well worth it well worth it.
Speaker 2:Buco Capital Good luck out there. 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 It does. For you episode. And I would it's hard to it's hard to properly manufacture a reaction like that.
Speaker 2:Of course,
Speaker 1:this is not Cracker Oh, did you? So the the Cracker Barrel story is in the journal today. Logo change spawns firestorm. It's oh, is And
Speaker 2:that Trump said something about it?
Speaker 1: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 this this 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.
Speaker 1: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 Fels Massino, chief executive of the nearly fifty six 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 junior. She should resign and be replaced with leadership that will restore Cracker Barrel's tradition. The fallout has shaved tens of millions of dollars from the company's market cap, spawned calls for boycotts and risked the casual dining chains turnaround plan.
Speaker 1: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 a callback to the original one with its barrel shape and word design. On Monday, Cracker Barrel said the dust up over the past several days had shown how deeply people care about the chain.
Speaker 2:Trump said on truth social yesterday, Cracker Barrel should go back to the old logo, admit a mistake based on customer response, parenthesis, the ultimate poll and manage the company better than ever before. Mhmm. Make Cracker Barrel a winner again. And they immediately responded reverting it back to the old logo. Wow.
Speaker 2:And if you had invested invested in Cracker Barrel and Nvidia
Speaker 3:You thought
Speaker 1:they did.
Speaker 2:Exactly a year ago, you would have outperformed buying Cracker Barrel.
Speaker 1:Wait. Wait. Sorry.
Speaker 2:What? What was that? 52%
Speaker 1:the in last the last year. And
Speaker 2:Nvidia is up 41 and a half percent.
Speaker 1:Well, if you're looking for exposure to Cracker Barrel, either either long or short, go over to public.com and invest for those that take it seriously. They got multi asset investing, industry leading yields, they're trusted by millions, folks. This weekend, says Jeff Morris junior, Martin Casado dropped a tweet that took over VC Twitter. I wrote about it and what being consensus versus non consensus actually means into today's market. Every weekend, there's a new hero, says JMJ, that takes over venture capital group chats.
Speaker 1:This past weekend was clearly slow on the news front because what I initially read is a fairly standard take ended up dominating my timeline. This is we talked about this. Martin Casado said the idea that nonconsensus investing is where the alpha is is actually quite dangerous in the early stage. Following capital tends to be more and more consensus aligned. For whatever reason, this concept triggered a bunch of investors.
Speaker 1: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 take because like we're there's VCs are supposed be, like, tech investors, Internet investors, and yet, like, cons
Speaker 2:Consumer and
Speaker 1:Consensus categories include crypto, bio, defense, manufacturing, AI. It's like everything is now in 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 nonconsensus companies within consensus categories, but at some point, calling ourselves nonconsensus investors is just glamorizing the job. Take American Dynamism as an example, a venture category branded just a few years ago by a sixteen z that now feels like its industry in its in itself. Palantir in 2003 was truly contrarian.
Speaker 1: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 $370,000,000,000 market cap. Andrew Earl was equally contrarian but for different reasons. 2025, he says, fast forward, American dynamism is a full blown investment category.
Speaker 1:Hundreds of startups and dozens of funds are chasing defense, aerospace, and manufacturing. I live fifteen minutes from El Segundo, which has famously become a dense hub of these companies. There was another one in here about, about DSC and saying something about like that category being even even even that category One
Speaker 2:note here. I I was talking with I was talking with a Yeah. Buddy over the weekend and he was like, what's going on with El Segundo? Or or or is it is it legit? Mhmm.
Speaker 2:Are these or or all these companies are they actually gonna build big companies? And something something Jeff says here oh, my my reaction was some a a small number of them will be massive and most will have meddling outcomes or or will shut down. But that is 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 and a center of gravity in El Segundo.
Speaker 1:Yep. There was something in here. I I I can't exactly find it. But it was basically saying that like like consumer is is contrarian right now. It's not very hot.
Speaker 1:Very few people invest in consumer d to c companies. But that's just in, like, 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. So it's a it's just a it's just an interesting noodling on what what what stands for consensus or contrarian right now.
Speaker 1:Anyway, let me tell you about Adio. Customer relationship magic. Adio is the AI native CRM that builds, scales, and grows your company to the next level. You can get started
Speaker 2:for With the new 52
Speaker 1:Do wanna do this John Woo post?
Speaker 2:Series The Yeah. This John Woo post is great. We should run through this. So Okay. John Woo says, do not trust millennials to run your brand.
Speaker 2:Their vision of the way the Internet works was informed by the web two point o 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.
Speaker 2: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.
Speaker 2:The tree falls in the forest and no one sees it.
Speaker 1:This is huge content creation.
Speaker 2:Just Yeah. But the cost
Speaker 1:of No one sees no one sees the flopped posts.
Speaker 2:Yep. Hurt. The cost of experimenting but the cost of not experimenting is astronomical. Yep. Sure signs of incompetence in the attention age.
Speaker 2:We don't wanna put out noise. We need to protect our brand. We need more followers. That's ignorance. Low quality posts are no longer distributed.
Speaker 2:Follower count doesn't matter. The news cycle is shorter than ever. People will only remember your winners
Speaker 1:Yep.
Speaker 2: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 It's they'll have a bunch Crazy. Just like flops.
Speaker 1:Yeah. You'll think of a person as like, oh, every time I see one of their posts, it has thousands of likes. Then you go to their account and you see so many flops and and 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.
Speaker 1: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 and then and then the 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.
Speaker 1: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. It's 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.
Speaker 1:Harry, Gestenter. I don't know how to pronounce his last name. But Harry says, apparently, mentioned in the first few minutes of the AppMafia course, so here are my thoughts. I went to college with Blake Anderson and know Zach and Hunter too. There are a lot of threads going around about profit margin, etcetera.
Speaker 1:It's not it's not that relevant given these kids are clearly netting a minimum 6 to 7 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 are have pioneered. People are talking about AudienceIQ. This course is clearly targeted at kids slash younger founders and certainly something I would have loved ten years ago. It also represents a shift away from venture backed consumer apps dying from over raising.
Speaker 1:Hundreds of apps like Headspace Calm raised 8 to 9 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.
Speaker 1:Now, there's a wrinkle where the course is now free. Is that right?
Speaker 2:Course is now free.
Speaker 1:Okay.
Speaker 2:So, you know, I think they they the the original video was was in their words designed to elicit a dramatic reaction.
Speaker 4:Yes.
Speaker 2:It's designed to bring out hate. Right? Sitting there in a mansion.
Speaker 1:Blake loves poking the bear of the algorithm. Yeah. Like, he he's very good at that and very deliberate about that.
Speaker 2:But, yeah. I it it is fascinating. I mean and and then immediately, piled on and were saying like, oh, the apps must not be making a lot of money otherwise Yeah. Why would they do this? Which I didn't it seemed obvious to me why they wanted to do it.
Speaker 2:They wanna build their personal brands and this is like a business model for building a personal brand. Yeah. This it's a it's a
Speaker 1: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. And 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, the particular visual effects software.
Speaker 1:And that kind of had I I 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 gonna teach you software. We're gonna teach you this thing. And so buying books is great.
Speaker 1:Buying courses on specific topics is great. Lots 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 podcast. There there are plenty of resources.
Speaker 1:Maybe this is useful. You'd have to try it out. Now, it's free, so you can make your own decision.
Speaker 2:Anyway Yep.
Speaker 1:We have our first guest of the stream in the TDPM. Welcome to stream.
Speaker 2:Announcement. Josh, good to meet you. How you doing? What's happening?
Speaker 6:Hello. Good to see you both. Hi, John. Hi, Jordy. Hi, Jay.
Speaker 6:Joining the group.
Speaker 1:You sound fantastic today. Whatever microphone you have hooked up is working flawlessly.
Speaker 2:Similar to what we have here. Congrats on the news. Break break it down for us.
Speaker 6:Yeah. So I'm Josh at Augusto. We love serving small business. We've worked with a company called Guideline for a number of years, close to ten years at this point. And the news is that we are joining forces.
Speaker 6:Guideline's gonna be joining Gusto.
Speaker 2:Amazing. Amazing. I think I've I've actually used Gusto and Guideline together for my entire career.
Speaker 1:I've used Gusto at four different companies.
Speaker 2:I started in college.
Speaker 1:And we have an employee sitting over there that wants a four zero one k. We're This is it up. Have no excuses anymore.
Speaker 2:Time is set up.
Speaker 1:Yeah. Talk about the the the the prehistory here. The company's been what what was it YC twenty thirteen, 2012 or something? I remember 2012. 2012.
Speaker 1:Yeah. I remember implementing it at my YC company in 2012 Okay. Back when it had a different name. And and I remember that 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, would be Yeah. Fed back.
Speaker 1:What informed the strategy back then? And then why are you shifting it? It, like it seemed like it was working for a long time. Yeah. So why Yeah.
Speaker 1:Why kind of what is it? Horizontally integrate, I suppose, is the term?
Speaker 6:I don't know what other business owner jargon is.
Speaker 1:We just
Speaker 6:we just try to make the life of a small business owner easier. But, yeah. First off, I mean, to serve you and your companies and and we're always trying to get better. So send me feedback on how we can get better, by
Speaker 1:the way.
Speaker 6:But yeah, no, I'd say we're 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.
Speaker 6:You know, we serve over 400,000 businesses. We love helping tech companies, but I love
Speaker 1:That's a
Speaker 6:lot of businesses. Too.
Speaker 1:That's a lot of business.
Speaker 6:Reminding folks there's more dentist offices in The US than tech startups. So Wow. Like very focused on that mainstream small business yeah, to your point, you know, we we listen to customers more than anything and 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 you know, we're not gonna build everything ourselves.
Speaker 6:And so when retirement came up and like generally speaking what we like to do is take stuff big companies have and bring it to small companies. Mhmm. Right? So from almost a fairness lens, it's like we need to bring great retirement benefits to these small businesses. They deserve it.
Speaker 6:And that was basically KB, the the one of the cofounders of Guideline. It's kind of a funny story. He was previously the cofounder of TaskRabbit. No way. So back in, 2015, we were in the same building.
Speaker 1:Yeah.
Speaker 6:They were on the Second Floor. We were on the Sixth Floor, and we 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
Speaker 1:how we got to know each other.
Speaker 2:Yeah. Was gonna I was gonna ask when did the conversation Yeah.
Speaker 1:Say you meet your you meet your acquirer like years before, but in this But case they don't say it's in a very slow elevator.
Speaker 2:You're gonna hang out Yeah. For minutes at a time. Yeah.
Speaker 6:But, yeah, to answer your the heart of your question, we started partnering with them Mhmm. Right when they launched in 2016. And, yeah, there's an integration. You can kinda connect the two systems. Like, we have tens of thousands of shared customers.
Speaker 6:You know, KB, I can say this stat very proudly on his behalf, like over 10 around $10,000,000,000 of retirement savings Wow. In the accounts of our shared customers.
Speaker 2:Let's hit the size for that. I
Speaker 6:mean Yeah.
Speaker 1:Jordy, you you hit the gong. We we like to hit the gong around here for big numbers. Congratulations.
Speaker 6:I like it. I like hitting the
Speaker 2:I like hitting the gong for retirement funds.
Speaker 1:Yeah. Yeah.
Speaker 6:That's that's again, that's their people's money. That's their retirement Yeah. Peace of minds.
Speaker 1:Yeah.
Speaker 6:Yeah. What we what we realized is there's a couple things happening. One, we can do even more together. Mhmm. So we're gonna continue to partner with third parties on other products, but especially with four zero one k and retirement, like we're gonna really go deep, and and that's what Guideline has done.
Speaker 6:There are broker dealers. There's all these different parts of the stack Which cut
Speaker 2:out the Yeah. Why you
Speaker 6:can create better cost savings.
Speaker 2:I'm sure you had investors along the way that said you're sending so many customers to Guideline. Why don't why don't you just build this Mhmm. You know, if you need if you need more capital, we'll provide it. What what what why did that not make sense and and why why why why buy versus build in this situation?
Speaker 1:So
Speaker 6:I think all options are always on the table when you're building a company, buy, partner, build. And, like, for what we're doing, it's gonna be a lot of connected problems. So, you know, 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 like, there's just products that we can do that we can't do unless we're combined. I can give you a couple examples if that's helpful.
Speaker 1:Yeah. Please. Yeah.
Speaker 6:Yeah. So like the journey of 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 gonna affect their salary.
Speaker 6:And in that moment, right, whether it's in the app or in an email, the, hey, like, you now have more money coming into your pocket, you know, your choice, but do you wanna set aside a bit more in your four zero one k? Or someone has a kid, you know, in our system that's a dependent, but that's a human being. Someone just had a kid. Right? Like, maybe you wanna go do something there in the context of retirement planning or something related to health benefits.
Speaker 6:So kinda 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
Speaker 2:Let's get into it. Yeah. We love this.
Speaker 7:Yeah. Pretty much.
Speaker 6:So so like government, right, we're here to abstract government and sometimes there's carrot stick that government does. So four zero one k is a good example of of a carrot. Like, it's pretax 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.
Speaker 6: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
Speaker 3:Mhmm.
Speaker 6: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, can make it brand dead simple through Gusto plus guideline.
Speaker 1: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? They had all these extra key queries.
Speaker 1:We were kinda and I think, like, the rumors, 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 gotta give me a a fee. Like, what what are the structures?
Speaker 1:Do you have companies that are in one camp and the other? Or do you can you share anything about the relationship beforehand? I'd be interested to know just Yeah. Like channel sales is something I'm like learning about now.
Speaker 6:So the first thing to start with is Gusto's entire engine of of growth. You know, here's another metric.
Speaker 1:We can
Speaker 6:tee it up. We're gonna we're on track to add about a 150,000 customers this year.
Speaker 1:But that's a lot. No. Wow. That's a lot of businesses.
Speaker 2:Yeah. Yeah. Okay. And so
Speaker 6:You're talking We really
Speaker 2:guys that absolutely love business. This is Yeah. Fantastic.
Speaker 1:All day.
Speaker 6:We can get into our whole like what is AI gonna do in the world
Speaker 1:Oh, yeah.
Speaker 6:Tangent if you want to.
Speaker 2:That's interesting too.
Speaker 6:But yeah, we'll come back to that. Yeah. So But it's an adamant
Speaker 1:of deals.
Speaker 6:So basically, like we are an engine to go bring in more and more small businesses especially new employers, folks starting out. Right? If you don't pay someone, they quit. Mhmm. 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.
Speaker 1:Yep.
Speaker 6:And so there's a lot of folks, as you can imagine, that would love to distribute through Gusto because of the the scale that we're at. And so what that looks like first is not us starting with the partner but starting with the the small businesses and finding out like what are their pain points, who are the products, what are the products they like or wanna 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 wanna make sure quality experience, accuracy, reliability Mhmm.
Speaker 6: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. Sure.
Speaker 6:And then that's a negotiation. There's usually if we're gonna drive a lot of customers to someone, there's some type of rev split.
Speaker 1:Yep.
Speaker 6:Because we're creating value for them. There should obviously be value for us.
Speaker 1:Yeah. That makes sense. What is
Speaker 2:your what is your guidance for ton of start ups sign up for Gusto today when they're one or two people, it's just the founders. And and what is what is your kind of framework for, you know, the right companies to use Gusto and and because, know, again, companies today, they might start with a couple founders today and be thirty thirty people in six months. Right? These things happen. We're like,
Speaker 1:we got a
Speaker 2:vibe coder on. But how do how do you
Speaker 1:You gotta work this out and vibe coder on
Speaker 2:what did
Speaker 6:you go wrong? Are you counting the are you counting the AI agents as people are not is my question.
Speaker 2:Yeah. Yeah. That's a good question. Yeah. But yeah.
Speaker 2:How are you how are you thinking of serving startups as of today? It's obviously from my understanding Yeah. A lot of where you guys started but it's it's always evolving.
Speaker 6: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. You know, I was born and raised here.
Speaker 6:My my parents aren't from tech though. They came from like my dad was a teacher, my mom was a teacher. And so
Speaker 2:Same here.
Speaker 6:We are Oh, yeah? Where did you teach?
Speaker 2:High school that I went to.
Speaker 6:High school. My dad my dad's at high school.
Speaker 1:Very cool.
Speaker 2:But yeah, was funny. Great. I think I I don't know if I asked my dad this. Don't think he would have had a great answer. But I do remember asking somebody back in the day, how do I pay my I was had a company who was starting to make money.
Speaker 2:I was like, how do I pay myself? And they're like, oh, you just set up like Gusto and you just onboard yourself. And I was like,
Speaker 6:oh, 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 like target customer lens, you know, broadly speaking, like one to 100 person companies
Speaker 1:Mhmm.
Speaker 6:Is our sweet spot. That's 98% of the employers in America. But I always love, like, also, it kinda blows people's mind usually, there's there's 6,000,000 employers in America, give or take. Wow. Two thirds are less than five employees.
Speaker 1:Wow.
Speaker 6:Right? 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. The average.
Speaker 6:Are Yeah. The average. Yeah.
Speaker 2:Well, quick thoughts on AI because you alluded to it earlier.
Speaker 1:I'm interested in I'm interested specifically in how you think about surfacing AI. Like, do you wanna put a chat box in some in in front of someone and then that's an interface to all the the deterministic workflows you've built? Or do you wanna just turn AI loose within your, you know, 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?
Speaker 6:There's a product manager inside of you. I would say yes to both and more. Yeah. So like we do a lot of complex kind of back end processing of either money movement, filings, There's a lot of ways to use AI tooling for productivity there. So that's great.
Speaker 6:And we've always used technology for how we scale. Right? Like, serve over 400,000 customers today. That's only possible through through using a lot of software. But from a customer experience lens, actually, again, both.
Speaker 6:I really think there's this massive, I mean, understatement here, but paradigm shift around how we use software and how software helps us. You know, when I got into software in high school, like, what I loved about it is it felt like it gave you superpowers. Mhmm. And then every time I saw, like, books on how to use a tool or I learned like someone would brag on LinkedIn, I can use this tool, it like really really annoyed me because software is not something you should have to learn how to use. It should just work.
Speaker 6:It should just make sense. It should be intuitive. Should give you superpowers. So conversational interface I think is gonna be a pretty, I mean, again, understatement, but like 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. And so we have a conversational interface for Gusto called GUS.
Speaker 6:Sure. And to your point,
Speaker 3:like, it
Speaker 6:can take actions. Right?
Speaker 3:That's okay. You get it.
Speaker 6:You get it. But like you can like shut up a shift shift schedule. You can go run payroll. Like you can leverage all of our APIs that we spent fourteen years building and Gus can do stuff for you, not just give you information.
Speaker 1:Funny story. My dog's name is Gus, Gustavo. And I have a friend who could never he was so into b to b software. He works in the b to b software industry that he didn't understand that my dog's name was Gustavo. And for a long time, he would call him Gusto.
Speaker 1:And I was like, I didn't name my dog after the software platform.
Speaker 2:Well, I I have one
Speaker 1:Speaking of dogs, Bill Bishop is in the 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.
Speaker 6:Thrilled thrilled to serve
Speaker 2:you, Chad. I have one I have one question. And and I'm curious. When when I got on to Gusto Yes. Back in the day, it was it was close to a decade ago at this point.
Speaker 6:Oh, do I
Speaker 2:was I was confused that I had to hit the button to run payroll. Was like, this is not a payroll platform.
Speaker 1:Yes. Yes.
Speaker 2:Why why do I have to And I remember there was a couple times that I have to 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 I I think you do you can automate it now. But is Autopilot. There Yeah.
Speaker 2:Yeah. Is there is there kind of a generational divide there in some ways where there's like a generation that understands like payroll is something that you hit a button and you run it versus payroll is just something that is just humming.
Speaker 1:At the first startup I ever interned at, the CFO hated me because I would always turn in my time sheets 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.
Speaker 1:And they're like autopilot doesn't exist. This is 2006 or something like that.
Speaker 6:So we we've rolled out autopilot for payroll back in like 2013
Speaker 1:I remember using it. Was fantastic.
Speaker 6: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 there's inputs that go into payroll. Yeah. Now assuming that's all there, like it should just work and that's the way it does work. We way back when, this is now twenty thirteen ish, like we have Penny the pig is kind of our like kind of a part of our company, kind of brand culture mascot.
Speaker 2:Yeah. Can see Penny and Gus potentially beefing over who's the most important
Speaker 6:I mean, they're they're they're friendly with each other. There's a friendly competition. But but we had to have the the GIF. It was a GIF for like running payroll when you clicked run, and it went too fast, and we had customers back then go, like, can't be that fast. Something is broken.
Speaker 6:So, we had the GIF just run longer Right. The sake of to make people be like, hey, there's actually hard processing happening behind the scenes here. Amazing. And and the world's come a long way since then. So, people expect stuff to be fast, simple.
Speaker 6:We want to automate. Mean, a good example is four zero one k. So, if you want to go change the contribution that's being made, that can now be done easier by us being one company. Yeah. But yeah, I I we think eventually payroll becomes something like flowing water.
Speaker 6:It just works. And and you don't have to do much direct action yourself.
Speaker 1:Fantastic. Thank you so much for hopping on.
Speaker 2:Chatting. Congratulations. The acquisition makes a ton sense, and congrats to both teams.
Speaker 1:We'll talk to you soon. Yeah.
Speaker 6:And make sure you give that teammate a four one k.
Speaker 1:We will. Will set it up. It's happening. Have a good one.
Speaker 2:Awesome job.
Speaker 1:You soon. Good to see you.
Speaker 2:Bye. Bye.
Speaker 1:And we have Keller from Zipline in the restream waiting room. Big news. Chipotle is now live. Chipotle partners with Zipline for aerial delivery. Let's go.
Speaker 1:Keller.
Speaker 2:Welcome back Keller. Welcome back to
Speaker 1:the stream. How you doing?
Speaker 2:Even more dramatic background this time.
Speaker 1:Every time you deliver. Thank you so much for hopping on.
Speaker 7:That's our job. Right?
Speaker 1:Yeah. That was unintentional. Anyway, how did this come together? It seems it it it seems like the perfect partner. Walk us through the the evolution that actually what went into the announcement.
Speaker 7:Yeah. I mean, we we we've been talking to Chipotle for a while. We obviously have announced a few other restaurant partners. Yeah. I mean, you know, for reference, like there was a time in my life where I lived on Chipotle.
Speaker 7:Like that was my
Speaker 2:Every entrepreneur every entrepreneur has like a Chipotle era.
Speaker 1:Raise your hand in the if you've lived on Chipotle. I think everyone's
Speaker 2:You you're getting more it's just a period of your life where you're getting more calories from Chipotle than anywhere else.
Speaker 1:Oh, yes. Absolutely.
Speaker 2:I can distinctly those moments.
Speaker 7:It's the base of the pyramid.
Speaker 2:Yeah. I
Speaker 7: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 action like eating Chipotle and you know, $10 you could get like two full meals out of it.
Speaker 2:Like the tortillas too, the Yeah. A
Speaker 7:lot of optimization that you can do and I I remember thinking that like one day I will know like it like, how will I know if I'm rich? I will Yes. Be able to get the guacamole every time Yes. Without feeling guilty about that.
Speaker 1:I have the exact same When I went through YC in 2012, my business partner, my cofounder
Speaker 3:wealth.
Speaker 1: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.
Speaker 2:It was
Speaker 1:tearing us apart. And then I finally just defaulted to, like, look. If you if you're gonna get it, I'm gonna get it too. And we will both fall on the sword of higher burn. And and to to this day, if I moral hazard.
Speaker 1: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. Because I know he's gonna get something ridiculous, and he's gonna be the most expensive thing on the menu. And at least then I get stuck with the half of the bill, and I'm happy.
Speaker 1:And I'm not like, oh, I got stuck. We're paying for his expensive thing. Anyway, congratulations. We love we love Chipotle. What what else Excited.
Speaker 1:What else can you share about the progress of the business? It felt like, you know, classic overnight success as we love to talk about on the show. But
Speaker 2:Also, how did you get them to actually name it Chipotle?
Speaker 1:It was amazing. That
Speaker 7:was their idea. That was their idea, not ours.
Speaker 4:That's amazing.
Speaker 7:I think, you know Look, I I think that what we're 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 wanna 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 like accelerate or, you know, dramatically transform our own brand and the kinds of experiences we can provide to customers. So, yeah, them choosing Zapote, us starting to deliver for them. I mean I think that we did a delivery in five minutes yesterday from like order made to the thing arriving at a customer's house.
Speaker 7:That's not possible every time just to be clear. It does take time to make the food. But like, you know, I think that if something's showing up super super fast like that In fact, we've we've found it has been necessary because we 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.
Speaker 7:Wow.
Speaker 2:Good problem to have.
Speaker 3:It's like
Speaker 7:a weird yeah. Weird weird thing. People are just used to
Speaker 1:Yeah.
Speaker 7:Getting cold. Getting cold or smush yeah. It's just not not that great. So you know, 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. Yep.
Speaker 7: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
Speaker 1:A couple months ago.
Speaker 7:Ten 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 2530% week over week in terms of flight volumes. And in fact yeah.
Speaker 7:Like so, you know, Saturday new record high flight volume. Sunday, we actually beat Saturday by 20%. This is just two days ago. Yes. You know, Monday was a record day.
Speaker 7:Tuesday was a record day. It's amazing.
Speaker 6:Really cool.
Speaker 2:If you keep giving us records, I'm gonna keep do the hornet.
Speaker 1:Yeah. It's so so Cooler with
Speaker 3:the record.
Speaker 7:No. But even even cooler is that, you know, right now the service has a net promoter score of 94.
Speaker 5:Wow. So, you know, no
Speaker 7: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.
Speaker 7:At this rate, in a couple months, our deliveries in The US are gonna exceed all of our global flight volume across eight other countries. So, yeah, US is growing super super fast now. Launching a new Walmart supercenter 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.
Speaker 1:So is is Walmart
Speaker 2:It's a ten year overnight success.
Speaker 1: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, 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 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?
Speaker 7: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.
Speaker 7: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 gonna 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. Mhmm.
Speaker 7: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
Speaker 1:Wow.
Speaker 7:As as via, you know, traditional deliveries. That's again, you know, 10 times as fast. So we're really focused on going metro by metro right now. A lot of our costs, you know, maintenance kinda happens on a metro basis. So we're we're gonna go tall.
Speaker 7: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. Yep. And we're and we're we're we're we're trying to build the capacity and launch them as quickly as possible. But, you know, building this kind of infrastructure across The US, it's like it's a big undertaking.
Speaker 7:And, you know,
Speaker 1:the other
Speaker 7:the other cool thing to mention, just really quick, is that like, you know, one thing I'm very, very proud of, more proud of every day I mean, Zipline now has a 120,000,000 commercial autonomous miles. It's the largest commercial autonomous system on earth. Zero safety incidents.
Speaker 2:That's crazy.
Speaker 7:That's the main point. Yeah. Zero safety incidents.
Speaker 2:It's amazing.
Speaker 7:If you just look at the basic safety of cars globally, the the system is already 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, you know, ZipLine is actually right now about we have we have already achieved a level of safety that is two x our 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, the 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.
Speaker 1:Is this a problem for Pizza Hut? Pizza Hut, famously, the buildings are huts. You can't land on the roof. How are we gonna get pizzas from Pizza Hut in Important questions. The important questions.
Speaker 1:But but seriously, like, there any
Speaker 6:I thought you
Speaker 7:were asking about the size of the pizza. Oh, no. No. No. Because actually
Speaker 1:I wanna
Speaker 7:know because actually, we are working with it.
Speaker 1:Are working on a pizza compatible.
Speaker 7:We just we just cut it in half.
Speaker 1:Okay. Oh, great. Calzones. Layers. The the company already have calzones.
Speaker 1:Yeah.
Speaker 7:We already have we already have the box designed for a couple different pizza partners. It works great.
Speaker 1: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?
Speaker 7:Yeah. So it's pretty cool. I mean, first of all, one of the things we announced just in the last couple 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.
Speaker 7:It does not have to be permitted. There's no construction.
Speaker 1:Wow.
Speaker 7: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.
Speaker 1:Got it.
Speaker 7:No power, no permitting, nothing.
Speaker 5:Yep.
Speaker 7: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. Yep. 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.
Speaker 7: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. It to grow 25 or 30%, you know, week over week.
Speaker 7: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, think the product Yeah. Viral.
Speaker 2:Yeah. When you think about the virality of the product, I mean
Speaker 1:Oh, yeah.
Speaker 2:Sure this is already happening or will happen, which is a
Speaker 1:How can you not I'm my story brain about this.
Speaker 2:Yeah. My brain goes to some guys at a fraternity order a 30 rack. Yeah. It's 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.
Speaker 7:They'll I mean, tons of people are doing TikToks and a lot of those TikToks are getting seen like seven, eight million times. Yeah. 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 kinda like, you know, iron out the kinks. But yeah, even even people who aren't customers are sometimes like videoing their neighbor getting a delivery and then putting it on TikTok and having it get seen millions of times. So it is cool.
Speaker 1:Some incredible
Speaker 2:stuff. Always always great to chat with you. Shout out to Danielle, your your whoever's running your your comms program because your remote She's got us. Your your remote call in setup I think is the best of any Fantastic.
Speaker 1:Guess that
Speaker 7:everybody This is the I mean, this is the manufacturing line. So this this line is ultimately capable of producing about 55,000 aircraft a year. And and that's
Speaker 2:that's yeah. We're scaling to
Speaker 7:that as fast as we possibly can.
Speaker 1:That's so many We
Speaker 2:have to
Speaker 7:we have to learn how to build drones in The US.
Speaker 1:Yeah. Yeah. I'm very excited about Thank you. We will talk to soon. Have
Speaker 2:a great of day. Talk soon, Kelly.
Speaker 1:Talk soon, Alright.
Speaker 2:Cheers. Talk soon. Thanks.
Speaker 1:Up next, we have Eight Sleep dot com. I get a pod five ultra. I put on a clinic last night. Jordy Pele, my favorite soundboard queue. I got a 90.
Speaker 2:Oh, good for you.
Speaker 1:Got a 90. Eighty four seven. Roasted. 100% quality. 88% consistency.
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Speaker 2:TBPM. I'll be right back.
Speaker 1:And I will talk to Will. How are doing?
Speaker 5:Hey. And how's it going? Great to be back.
Speaker 1:Jordy just plays a sound cue and steps away. What's new in your world? Just, yeah. Wait. What's what's the latest?
Speaker 5: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, I'm Will Brown. I work at Prime Intellect. We're a open source research company as well as a compute platform.
Speaker 5: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, like, a lot of people are talking about, but also, like, wondering, like, what does this even mean?
Speaker 4:Yep.
Speaker 5:Like, I I saw, like, over the weekend, like, Google Trends for RL environments, like, shut up. Yeah. And you guys had made some joke tweets about this recently that I thought were great about, like
Speaker 1:Ender. That's not an RL environment we were in. That's you place real Amazon orders. It it perfectly encapsulates my level of understanding here. So I'd love to go deeper.
Speaker 1:It feels like a bull case for distributed infrastructure generally because we're maybe, like, it's maybe it's additive. Maybe it's re maybe it's, replacing. But, certainly, of the focus is on, like, get a 100,000 h one hundreds in one single cluster. There's more to be done in different places. But what try and concretize it for me a little bit more.
Speaker 1:Like like, what is an RL environment? How are they being used? What are the what are the what are the trade offs in terms of compute and design of the infrastructure, that that actually delivers some sort of valuable product at the end of the day?
Speaker 5:Sure. Yeah. So I think we can get to the distributed aspect of it. Just, like, first, I think, like, an environment is essentially, it's an eval. Like Mhmm.
Speaker 5:A lot of the things people make as, like, popular evals, like SweetBench or like ArcGI, like, are environments.
Speaker 1:Yep.
Speaker 3:They're
Speaker 5:a thing where you have some input tasks. Mhmm. You have some kind of 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. And so this is, like, the exact setup we use for evals, but it's also what you use for RL training. And so when people are talking about, oh, we're, like, gonna make a bunch of RL environments, what they really mean is they're making evals that are designed for, like, agents to, do some task interactively.
Speaker 1: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. Totally.
Speaker 1:Are are 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 old enterprise software systems that people want agents to interact with? Like, how wide is this is the scale of RL environments right now?
Speaker 5:Yeah. It's pretty huge, actually. So I think I think there is, these kind of, like, flagship website sort of things, but I think there's also, a long tail of, like, niche applications that go down towards, like, these very fine grained narrow things all the way up towards, like, broad domains where models really struggle because we don't have a good, like, interface for them. Like, I think Excel is one of it's like, everyone use Excel, but, like, no one is really, like, an LM power user in Excel because it doesn't integrate very well. Yeah.
Speaker 5:No. We don't have the cursor for Excel yet as a broadly deployed thing.
Speaker 1:Yep.
Speaker 5: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, an environment, and that's one of the sort of things that, like, the mechanizes of the world and imagine are, like, building these sorts of things. Yeah. I'm sure that, like, the labs all have their idea of, like, what tasks their customers want models to be better at
Speaker 1:Yeah.
Speaker 5:They're currently not being used for, as well as just, like, what sorts of products are people trying to build. So, like, you can build the greatest agent harness in the world, but, like, if your model hasn't been trained for it Sure. Like, some models might just, like, 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 like, having an interface that you really want your model to be great in, like a a harness, and then just, like, a feedback loop that lets it get better at being a model or agent in that harness.
Speaker 1: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, know, a cursor for Excel.
Speaker 1: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's worth 5,000,000,000,000, 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.
Speaker 1:So, like, what does verifiable reward look like? What are people actually building towards in that environment, you think?
Speaker 5:Right. Yeah. So the easiest recipe, which, like, we've done work on as well as I've seen papers about this, and it also just kind of like the obvious only real thing you can do is have a correct answer.
Speaker 1:Yeah.
Speaker 5:Where it's like, there is a gold standard, like someone made this ECF.
Speaker 1:Yep.
Speaker 5: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.
Speaker 1:Yep.
Speaker 5:Like, past six months is perfect. And then you wanna train your model to, like, be in the harness where it could make the DCF Mhmm. And then look at what it produces, and then you have all these different things you can check of, like, did it get all these fields right?
Speaker 1:Yep.
Speaker 5:And this those evaluations are a combination of, like like, vibe checks, spot checks when humans are looking at it for, like this is how kind of people have been doing historically. You just, like, 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, you need to automate this evaluation chunk Yeah. 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.
Speaker 5:And this checking usually is gonna 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 gotta 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 wanna do is take that kind of evaluation process and freeze it as a kind piece of code. Mhmm.
Speaker 5:And now you can plug this into your harness. So the harness plus some, like, input task of, like, do this for every company, and your, like, gold standards for every company of, like, whatever work should look like made by some analysts. You're grading against, like, the golden answer, and now you scale this up.
Speaker 1:What was the industry standard before you rolled this out? Would would, like, the actual AI researchers or or AI engineers who were going to, do reinforcement learning on a model in 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?
Speaker 5:In terms of, like, open source infrastructure or, like, the in terms of, like, just methods. Broadly. Yeah. 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.
Speaker 4:Yeah.
Speaker 5:I imagine. It is not broadly deployed. Like, the companies that are, like, on the periphery of maybe doing it are, like, cursor at perplexity. Yeah. So It's not a thing that's, like, the small pile
Speaker 1:of 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. Then maybe They're using Azure. Yeah.
Speaker 1: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 Cursor4x right now, that implies that at some point, they like, if we see this bifurcation in the in the market for Cursor for X really is, you know, highly fragmented and there's not just one Yeah. Foundation model company that just eats everything Mhmm.
Speaker 1:Are you gonna 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, like, material costs to that? Is it expensive?
Speaker 5:So like, I think you have to build the harness anyways. I think one of the hardest things to scale is building good evaluations and appropriate criteria.
Speaker 1:Yep.
Speaker 5: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.
Speaker 5: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
Speaker 1:Sure.
Speaker 2:That are
Speaker 5:efficient for inference. The current ecosystem for tooling for doing that yourself Mhmm. Is not great. Most people are doing, like, LAMA and QUAN experiments. So these models are, like, they're good models, kind of, but like they're not really what you want to deploy for a Okay.
Speaker 5:Serious
Speaker 1:So yeah. Is that wait. Can can you give me a, like, a rough order of magnitude for the for the level of cost that it would it would 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, you know, defined the harness and the reward, and I go to you to actually do the the RL on top of maybe an open source model, am I Yeah. Am I talking about tens of millions of dollars of of GPU cost? Like like, try and ground it for me a little bit more.
Speaker 5:Like, I would say this is, like, napkin math.
Speaker 1:Yeah.
Speaker 5:Like, if you want to do, like, a serious run that would, like, meaningfully improve a model of, the DeepSeek or Yeah. Kimi 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.
Speaker 1:So it's kind of like yeah. Like, those old ones
Speaker 5:raw compute.
Speaker 1:Yeah. Like, when when people were like For the one day call. I fine tuned Lama on this thing and now it now now it does this funny thing or I fine tuned this image model on my face. Like, those used to be like kind of like prosumer level projects. Now we're getting into the, okay.
Speaker 1:This is like a enterprise level effort, but it's probably not gonna you you don't need to call up SoftBank to get it done.
Speaker 5:Right. I mean, there's like a there's a whole spectrum of these things.
Speaker 1:Yeah. Of
Speaker 5:course. That's why it's hard to, like, say, like, what's the bucket? Because you can, like, you can fine tune Lama on your laptop.
Speaker 1:Sure.
Speaker 5:But you also you can't fine tune, like, Kimi or DeepSeek, the big ones on your laptop.
Speaker 4:Yep.
Speaker 5:And also it's like how long running is the task.
Speaker 1:Yep.
Speaker 5:How many samples do you need? How much do you really wanna crank it? Like, it's one of those things where you can kinda 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.
Speaker 2:Sure.
Speaker 5:Like, there's not it's not easy to do this stuff. Like, getting your GPUs to work correctly, getting your, like, libraries to work correctly, deciding what hyperparameters to use. Like, people spend and this is one of the reasons that, like, the labs that needed so much to compute and why the expenses are so high is that, like, have all these researchers, and researchers are all doing experiments. And each of these experiments is, like, thousands of dollars of compute. Mhmm.
Speaker 5:And you multiply this over a year and a 100 researchers, that's a lot.
Speaker 1:Okay. And so yeah. Sorry. You you you can finish. Sorry.
Speaker 5:Oh, sure. Yeah. I just like, I think there's some of these pieces that, like, once you can get the the hard questions answered once
Speaker 1:Yeah.
Speaker 5:You don't need to keep redoing them for every new environment. Yep. You can kind of have some very cheap spot checks. Like, he like, a a kind of one shot eval, like, how good is the model at the start is kind of be a bellwether for, like, is the running gonna work?
Speaker 1:Okay. Loosely related to somewhat of the concept of generalizability. I want your reaction to this Rune to this Rune post. Roon 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 dataset. What do you think about that as a bar for AGI?
Speaker 1:We don't need these RL environments for specific, for specific tasks. What are your thoughts?
Speaker 5: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.
Speaker 4:Yep. And
Speaker 5:figures out how to kind of create its own training environment. It's like, okay. Need
Speaker 6:to practice.
Speaker 5:The same way that, like, if you wanna learn how to code, you gotta 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?
Speaker 1:Yeah. Yeah. It does feel like we're in this era where there are a few really obvious things that we wanna 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 dataset. And so, yeah, maybe the future is is, go and find those autonomously and and set up the reward function train and then iterate and bake that in.
Speaker 2:Yeah. But but I think Sorry.
Speaker 5:Yeah. Sorry. Go ahead. Oh, yeah. Just because I I think one way to do this is just, like, the environment can be the thing you're gonna serve.
Speaker 5:Sure. Like, cursor is an environment. Yep. 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, think we're not quite there yet in terms of having this be a thing that people are scaling.
Speaker 5:And now, like, every company wants to, like, hire, like, environment builders and RL people.
Speaker 1:Yeah.
Speaker 5:And it's like, you're not they're not all gonna hire people for this. Yep. We need to have better ways of, like, scaling this out to more people and, like, infrastructure as a service kind of.
Speaker 1:Yeah. That makes a ton of sense.
Speaker 2:Wanted to ask about, Dario's comments in his interview with John Collison
Speaker 1:Oh, sure.
Speaker 2:Talking about, basically, I'll 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 a 100,000,000, and then you deploy it in 2024 and it makes 200,000,000 of revenue. Meanwhile, because of the scaling laws in 2024, you also train a model that costs 1,000,000,000. And then in 2025, you get 2,000,000,000 of revenue from that 1,000,000,000 and you've spent 10,000,000,000 to train the model.
Speaker 2:So if you look in a conventional way at the profit and loss of the company, you've lost a 100,000,000 in the first year, 800 in the second, and 8,000,000,000 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. Paid a 100,000,000, then it made 200,000,000 of revenue. There's some cost inference with the model, but let's just assume in this cartoonish example.
Speaker 2:And so FinTwit has just been like freaking out about this, like being incredibly bearish about this. It's obviously a a bubble, you know, and and just kinda 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 were just over at Goldman. Morgan Stanley.
Speaker 5:But Right. Yeah. So, like, there's an element to the freaking out that's, kind of a good point, which is, like, you can't keep doubling every year.
Speaker 3:Yeah.
Speaker 5: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 gonna there's only so many people to adopt AI products. And once they adopt it, like, if they were gonna 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 gonna get, how, like, fast we can possibly make the chip.
Speaker 5:Like, the chips are only gonna 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, like, the spacing we end up in where, like, stuff broadly works quite well. There are, like, a few big labs who have very good models that are, like, can deploy them. And then there's also, like, this kind of fredo curve of, like, how much can you spend, how fast does it need to be, how hands on do you wanna be for it, like, how, like, narrow is your like, thing you wanted to do.
Speaker 5:So if your thing is, like, oh, I wanna build a great browser agent, this is super broad. There's so many things you can do on a browser. The thing is I wanna build an agent for writing Rust. This is much more narrow. So, like, if you only if you're making, like, the product for Rust developers, like the cursor, for example, you can make a model that's just as good as Quad four Opus that's much smaller and much cheaper, most likely, because the the focus is, like, more narrow.
Speaker 5:And so this is kind of how I think about generalizability is, like, 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, like, more narrow and go deeper on one thing. And so we're gonna have a lot of knobs to turn, I think.
Speaker 1:Yep. Are you broadly long RL environments, short, normal pre training data? Do you have a do you have any, like, extra color on the relative value or, like, where the low hanging fruit is across those two?
Speaker 5:I'm long both, but I I think they're gonna kind of turn into the same thing. Like like, one thing, for example, that people have been doing for, like, pre training recently is that people are just using, like, DeepSeek r one and generating tons of, like, reasoning samples from it and then mixing those in at the end of pre training and calling it mid training. And it's like is in some sense, this is RL because it's just taking the juice from doing RL on, like, DeepSeek v three, but it's also pretraining. And so I think one thing that we're excited about with environments and scaling these is, like, 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.
Speaker 5: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 of this and put it into pretraining? Why not? Yeah.
Speaker 1:Do you have insight into what's happening in the video or image world equivalent of RL environments, verifiable rewards, etcetera? Like, I I was just shocked by the level of quality of text in images and ChatGPT.
Speaker 2:Yeah.
Speaker 1:We're seeing the same thing with Nano Banana from Gemini. And it felt like it felt like Images and ChatGPT particularly was like uniquely good at Studio Ghibli and uniquely good at text. And that felt like I was I was almost like putting on my tinfoil hat and saying like, 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 a real one really good model. Like, it feels spiky.
Speaker 1:It feels particularly good at text and particularly good at cartoons. But it hadn't gotten, like, way, way better at, you know, super photo real imagery or whatever. Sure. Sure. Do do you have a do have any view on how you translate all of the stuff that's happening in the in the agents and and text based LLM world into sort of the diffusion and and image or video world?
Speaker 5: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 Yep. As well as, like, good old fashioned RLHF, like, the stuff people were doing for, like, instruct GPT, JACK GPT era where it's, like, you have, like, upvote, downvote.
Speaker 1:Yep.
Speaker 5:And then you're training a reward model to, like, check these. I think the image domain is easier to kinda spot errors
Speaker 1:Yep.
Speaker 5:Whether it's a human or an automatic grader. Like, if text is wrong, you can, like, do OCR on the image, get the text back out, and see is it the right image from the prompt. And so you it's this is, like, pretty easy to verify versus, like, 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? Like, that's pretty hard.
Speaker 5:Yeah. And so in some sense, like, the image models were just, like for a while, they were bad at things that we could very easily measure, and it's getting it's gotten harder to measure the things LMs are bad at much faster. And so I think some of this is the, like, the old fashioned tricks that made ChatGPT original version as good as it was being applied to the image domain for kind of matching up the the obvious fixes.
Speaker 2:Give me your hot take. How much, how much do you think Meta is paying mid journey with that new deal they they announced?
Speaker 5:It's a good question. Do think it's 9?
Speaker 2:I do you think it's 9 figures a year?
Speaker 5:Hopefully. I mean, like
Speaker 2:It feels like feels like it would
Speaker 5:be More maybe. I don't know. Yeah. Yeah. They're spending crazy amounts on everything.
Speaker 2:Like Well, that that's what I was saying and and it it makes sense for mid journey to wanna have like a low key announcement about it. But there's like another team that would have been like, we just signed a $500,000,000 a year's ten year deal or something something obscene obscene that that looks more like an acquisition even though clearly from a from a dollar value standpoint, even though clearly they're gonna continue to operate independently.
Speaker 5:Yeah. I would kinda think of it as, like, mid journey's version of doing an API business. So, like, it could just be based on usage to to I'm sure there's a big picture component of it. But, like, think of, like, what you can kind of do the napkin math by saying, like, okay. What are other image providers, like, charging for API usage, like, Val or, like, replicate or, like, all these other services.
Speaker 5:Like, you can kind of map and map the cost or of an image or back it out from the during subscription prices and how much they give you. And then say, like, okay. How many of these are people gonna 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.
Speaker 5:And so you can the numbers can get crazy pretty quickly, and I think it does kinda depend on, like like, if it's just ads or if it's just to, like, certain customers or it's not, like, deeply integrated, then it like, the scale is not as crazy as if it's like, no. You're really getting, like, mid journey stuff everywhere for everyone instantly at volume.
Speaker 1:Yeah. I was I was thinking when Studio Ghibli moment happened that the response from Meta should be to pre render or 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 wanna share it?
Speaker 1:Yeah. 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 $50,000,000,000 worth of inference or something like that. I don't know.
Speaker 5:It's a lot of inference.
Speaker 1:It's a lot. And and that's how those images are expensive. Yeah.
Speaker 2:Got some Yeah. Breaking news. Breaking news. NVIDIA beat on revenue and earnings per share. But is down 5%.
Speaker 1:Wait. Why?
Speaker 3:That's not
Speaker 2:what beat hard enough. They didn't beat hard enough.
Speaker 1:Can we ring the Gong for the beat?
Speaker 2:I mean, let's ring it.
Speaker 1:It's yeah.
Speaker 2:41% respectively.
Speaker 1:NVIDIA's NVIDIA's, like, both a competitor and a supplier partner, right, to you? Like Yeah.
Speaker 5:I mean, we we sell the we resell the GPU. So, like, we, like, we're a big NVIDIA fan.
Speaker 1:So you're root rooting
Speaker 2:for them.
Speaker 6:That's great.
Speaker 5: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.
Speaker 5:They sell them to, like, data centers
Speaker 1:Yeah.
Speaker 5:And, like, Totally. Big companies.
Speaker 1:Yeah. And I I know that there was that news that they were coming for the Neo Clouds with DJX 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 in the ecosystem. It felt somewhat additive. I don't know if you have a take. But
Speaker 5:Oh, yeah. So, I mean, I think it's also, a different like, they're gonna kind of offer that as, like, a very premium, like, white glove sort of thing to certain enterprises.
Speaker 1:Sure.
Speaker 5:I think we are much more on the end of, like, get all the data centers we can find, like, partner with every Neo Cloud Yep. 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, like, have friends at NVIDIA.
Speaker 5:Like, we talk to them about, like, their they've released 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.
Speaker 1:Yeah. Are there any RL tasks that you think are, like, truly intractable, something that, like, is is fundamental to humans' creativity or comedy or something? Like, what what what's the Mount Everest of of developing an RL environment around?
Speaker 5:I think the hardest is stuff that and a friend of mine was tweeting about this earlier today, actually. One of our collaborators who, from Evals is doing some cool open source Evals work, for computer use. But things that need a human in the loop to have a, like, 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 gonna 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 like, having a model that can, like, be good in Twitch chat kind of requires, like, an accurate sim of Twitch chat. Yeah.
Speaker 5:And it's like, how do you build that? Or, like, a physical streamer. Like, there's a this real time interaction problem that you need to kinda solve before you can get started because the the scale at which these things move, you can do it if an LLM is simulating the user.
Speaker 1:Yep. You
Speaker 5:can't do it if you need a real human.
Speaker 1:Yeah. I feel like the the the time horizon is really it feels really, really tricky to simulate when you think about, like Yeah. The the the impact on a life of a certain behavior. I mean, we'd struggle with this with, drug development, understanding, like, does something in childhood affect you as a retired person? It's like, you okay.
Speaker 1:Now you have to create a simulation of the entire human body to understand that if you did this thing at 18, it's gonna 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 maybe we'll get there. Who knows?
Speaker 5:Yeah. At some point, you just gotta let the error of time run forward and see what happens.
Speaker 1:Exactly. Well, thank you for hopping on. Always great to see you.
Speaker 2:Congratulations on the whole Yeah.
Speaker 1:We'll talk
Speaker 5:to the Prime Elect Environment Hub. We are live now. On Twitter. X. See you around.
Speaker 2:Send it, chat. See you. See you guys.
Speaker 1:Talk to you later. Bye. And yes. We have the NVIDIA market chart here down 2.75%. Is that what I'm seeing here?
Speaker 1:Correct? Let's see
Speaker 2:how What's trading?
Speaker 1: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 a $179 a share.
Speaker 1:Was it a $181 a share? Something tells me Jensen's gonna shrug this off. If you look at the six months, the the stock has just been smoothly climbing upwards. Anyway, we have our next guest, Julie Steinberg, in the studio. Welcome
Speaker 2:What's happening?
Speaker 1:Julie, how are doing?
Speaker 2:Welcome back. I
Speaker 8:am doing well. I was thinking about wearing, like, a little hat that said Chinese Communist Party on it to, know, establish what I was talking about.
Speaker 1:Yes.
Speaker 8:But, unfortunately, I came up with this idea twenty minutes ago. And because I am dealing with California infrastructure and not China infrastructure, I could not get it to the house in time.
Speaker 1:Yeah. You are you driving from LA to SF or vice versa? Where are you going?
Speaker 8:Yeah. So this this may be a bit TMI for the good listeners of TBPN, but I was rear ended
Speaker 2:Yeah.
Speaker 8:A few weeks ago. So my car has since been fixed, but I must drive it up to San Francisco.
Speaker 1:And
Speaker 8:I was 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's 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?
Speaker 1:Yep.
Speaker 8:Why like, PCH, Pacific Coast Highway, it's one of the most iconic American landmarks.
Speaker 1:Yeah.
Speaker 8:One of my favorites, personally. It's ridiculous that it shouldn't work. And I tweeted it. 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 gonna smell like cow shit for six hours rather than see the beauty of
Speaker 2:the situation. Favorite thing as a kid, my my parents, we'd be on a road trip. My parents would say like, okay, we're going through the the the cow zone. You were Yep. Big cattle ranch.
Speaker 1:Yeah. You have to turn Yeah.
Speaker 2:Recirculate. Recirculate. I just be like, I'm hitting the window down and I
Speaker 8:I if I if you were my child, he would've been like booted out of the car window at that point.
Speaker 2:I was surprised. So PCH between Malibu and LA was shut down after the fires for a while and then it was open to like specific people based on your address and then it got actually opened pretty quickly. And I think that was probably Newsom 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 and if he doesn't get it open. So it was open ahead of schedule. Yeah.
Speaker 2:Yeah. He was taking a victory lap of like But
Speaker 1:the one is not really critical to many people's commutes. It's more of
Speaker 2:this Well, especially up by it's Big Sur that's shut down. Right?
Speaker 8:Yeah. Big Sur. So I can drive from San Francisco or however far north on the one to Big Sur, I the can't sort of Cambria region is cut off that Okay.
Speaker 2:Sort of
Speaker 8:fell into the ocean. A lot of people on Twitter were sort of I I wasn't expecting the tweet to blow up, but 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.
Speaker 8:Like, I'm not a structural engineer.
Speaker 1:Mhmm.
Speaker 8:But Dan Wang in his book Breakneck, he was like, oh, yeah. The Chinese government has built x amount of, like, the bridges, like, top 10 bay some of the biggest bridges in the world
Speaker 1:Yeah.
Speaker 8:In this, like, record short amount of time. And it's it's frustrating to me that we can't do that. We somehow is admitting that like as a civilization we're just gonna let the mudslides win.
Speaker 1:Yeah. Here's the solution. If you want one, the Highway 1 to open, you gotta put a Harris Ranch out there because that's the highlight of I 5. You stop
Speaker 2:It is.
Speaker 1:For the a five Wagyu rib eye. You get a big steak at Harris Ranch. This is the highlight of my trips, up and down.
Speaker 2:Harris Ranch is a really smelly ranch.
Speaker 1:That's a really smelly one. It's I didn't realize you could
Speaker 2:pull over and get a meal.
Speaker 1:Oh, yeah.
Speaker 8:No. I didn't realize that either.
Speaker 1:Oh, you're not doing the five correctly then. Yeah. When you're driving from LA to San Francisco, you ran out of gas halfway because you're driving a terrible car. This was my experience in like 2012. And you always stop at Harris Ranch, you get a big steak, and it's fantastic.
Speaker 2:Yeah. I think most people are are flying by.
Speaker 1:The other alternative that is actually scenic and nice is there even though we don't have a high speed train, we do have a train that goes
Speaker 2:from It
Speaker 8:takes twenty four hours. Like, just takes an
Speaker 1:get a book. I thought you were I thought you were into books.
Speaker 2:You're the GM of books.
Speaker 8:I do like books.
Speaker 2:You're the general manager to of
Speaker 8:read books while I'm not in a moving vehicle.
Speaker 1:Oh, it's so nice.
Speaker 6:It is one
Speaker 8:of my more controversial book takes Okay. Is I like being sitting Stable. Still.
Speaker 1:Okay.
Speaker 8:When I'm reading a book, planes are fine. I can read many books on planes. I've read many books on planes.
Speaker 1:Okay. Well, speaking of books, take us through your review of Dan Wang's book.
Speaker 8: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 transmission Mhmm. From one person to another or sort of one, like, elder ment elder elder mentor to a mentee. The United States, we've, like, lost a good deal of that process knowledge in how to make things because we've offshored it to China.
Speaker 8:Yep. And Dan Wang really and and and 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 exert 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, you know, 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.
Speaker 8:Whereas in China, the Politburo is made out of engineers, first and foremost. I 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, well, what is this gonna look like? Is this gonna violate people's rights? Can we do this?
Speaker 8: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.
Speaker 1:Yeah. I was listening to Casey Hanmer on DoorDash, and he was talking about how, like, he's trying to install solar panels in the desert. He needs 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, like, lobbied to, like, get it make it easy. And so it's just, nonsense.
Speaker 1:But my my question is the the the the engineering what what what what's the phrase he uses? Engineer?
Speaker 8:Engineering society.
Speaker 1:Engineering society and lawyerly society. Right? Engineering empire or something. So I I understand that. And and it's very it's very alluring.
Speaker 1:Like, I like engineering more than I like lawyer lawyers, I suppose. But my prior 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?
Speaker 8:Well, my my dad, who's probably watching right now, is a lawyer. So shout out to the Legend. Lawyers keeping America great. But I
Speaker 1:guess the big question is like, is there a world where where we say, okay, let's let's try and pivot from lawyerly society to more engineering focused. We get halfway there, and and we actually are worse off because you wanna just, like, lawyer max or engineer max. And if you're if you're halfway in between, it's just a nightmare. I don't
Speaker 9:know. Well,
Speaker 8: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.
Speaker 2:Well, both.
Speaker 8:Is there
Speaker 2:Both. Capacity for
Speaker 8:engineering bigger, but it's also like this is my biggest issue with Breakneck is that it 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 it's a sort of interesting question that Wayne raises, though I don't think he says it straight up.
Speaker 8:It's like, is capitalism even a useful sort of metric in the twenty first century? And I would say absolutely, but we need to prove that in The United States by doubling down on free markets. Mhmm. Free markets could bring us great things like a beautiful bridge that would make PCH work. I've I'm a huge believer in market incentives.
Speaker 8: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, b to b SaaS 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's not just my app is, like, point o 2% 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. It it mixes two it conflates two things.
Speaker 8: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 it like, we're just gonna make guitars here, and it happened, and they got very good at it.
Speaker 1:Mhmm.
Speaker 8: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. Jen Wang talked a lot about the one child policy in China. Right.
Speaker 8:He talked a lot about zero COVID in China where people
Speaker 2:John presented the multiple children policy.
Speaker 1:The three
Speaker 2:Have three kids,
Speaker 1:please. Policy. And Dan rejected that roundly. It got destroyed.
Speaker 8:I I like the three kids policy. Think I think it's a I think it's a good policy.
Speaker 1:I think they have the money. There's incentives. And and if you if you really, really tilt the feel the the playing field in the favor of having kids, like, people will have more kids.
Speaker 8:I agree. And it's like talking of course, you know, I have to bring up Tavis, the engagement that happened yesterday. Oh, yes. I was talking to my boyfriend at the end of the day and I was like, Jake, like, I I have to tell you something, but you're not gonna be interested in this at all. Okay.
Speaker 8:And he was like, oh my god. Like, what did she do this time? Like, did she get into 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.
Speaker 1:He doesn't read the Wall Street Journal because Taylor
Speaker 2:Mon, you guys need to write something
Speaker 1:about Spotify about
Speaker 2:Oh, yeah.
Speaker 1:From that.
Speaker 2:Also, I wanna know the I wanna know what this engagement means for America. It's
Speaker 1:a good
Speaker 8:Well, I think from that Arena. From than you we have kids. But it's like this it's one of the weird things. It's like a Taylor Swift baby boom. Mhmm.
Speaker 8:Like, how China is it's not who's a Chinese pop star who's gonna get pregnant from a football player and have kids?
Speaker 1:I don't know. That's a good question.
Speaker 8:We'll have
Speaker 1:to get to the
Speaker 8:bottom of
Speaker 9:I do think
Speaker 8: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 d one athlete that's also world famous superstar kids.
Speaker 2:That's true. I mean, they're they're certain they don't shy away from the economic opportunities associated with their with their announcements. That's for sure.
Speaker 8:No. But I but I do really think that the the Tavis sort of engagement announcement, the what the royal wedding that will happen in a few years. Like, I unironically do think this will cause a baby boom. Because people are very mimetic, women are very mimetic. And if number one pop star has kids
Speaker 1: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.
Speaker 8: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 Yeah. And just 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.
Speaker 6:Yeah.
Speaker 8: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 would totally have kids
Speaker 1:for I someone to do mean, that certainly happens in Hollywood. There's a ton of celebrities that have that have kids. I mean, John David Washington is Danzel's son
Speaker 2:Mhmm.
Speaker 1:Played football and then was in Ballers, I believe, in a Nice. Tenant.
Speaker 8:I I have a sort of funny story about that. Please. I I grew up in LA and I was on the debate team at my high school. And there is 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, a plus list actors was deciding between doing the debate doing the debate team and doing the school play.
Speaker 8:And our debate coach, he said to me, he's like, well, it's usually pretty easy to convince them that they're not gonna have a famous career as an actor and they're 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.
Speaker 1:Makes sense. Sorry. I'm prepping a chart. Jordy, do have anything else?
Speaker 2:Chart for what?
Speaker 1:Our next guest. Oh. Who's in the restroom waiting room.
Speaker 2:Julia. It's always great to see you. You gotta come on more often.
Speaker 1:Yes. We should have scheduled more time. But we have Yeah. We have someone else in the waiting room.
Speaker 8:I'm Well, time, I expect a custom chart to be pulled up.
Speaker 1:Next time you're in LA, come do the show in person.
Speaker 8:I that I said I said I'm here.
Speaker 1:Okay. Fantastic.
Speaker 2:Let's do it.
Speaker 1:Fix the car, drive
Speaker 2:it to your team,
Speaker 6:and also
Speaker 2:the accident.
Speaker 8:Yes. Thank you. Appreciate it.
Speaker 1:And we will love catch up. California to fix the one so we can drive scenically in the future. Thank you so much for humming on. Our next guest is in the restream waiting room. Olivia Moore.
Speaker 1:From Andrews and Horowitz. How are
Speaker 2:you What's happening?
Speaker 9:Buddy, it's great to see you guys. Thanks for
Speaker 2:to see you.
Speaker 1:I was just sharing with the team the news today, but you break it down for us first. What are you announcing today?
Speaker 9:Yeah. So we're announcing what we call the Consumer AI Top 100 Mhmm. Which is where we literally thank you. I appreciate when other people are this excited about data as I am. We love data.
Speaker 2:We live for market maps.
Speaker 1:Yes.
Speaker 9:Yes. This one has I would say it's market map adjacent
Speaker 1:Yeah.
Speaker 9:In that we every single website and every single mobile app around the world Mhmm. In 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.
Speaker 1:I consider myself a bit of a list connoisseur myself, Yes. I enjoy making lists from time I'm sure Be like get yourself in hot water with this list. Be like I say, take me off this list. I wanna be under the radar. Put me on this list.
Speaker 1: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?
Speaker 8:Or is this No.
Speaker 9:There's no element of vibes. It's all data. So we literally, for the web list, we go we have a provider called SimilarWeb, and we literally just look at monthly number of visits.
Speaker 4:Yep.
Speaker 9:We pick the first 50
Speaker 1:Mhmm.
Speaker 9: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.
Speaker 1: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.
Speaker 1:Stuff that's standing out are specifically like
Speaker 2:Nerd AI?
Speaker 1:Tool, like, hyper specific tools like remove background, remove BG. I've actually used
Speaker 2:that tool. Janitor AI is number eight.
Speaker 1:Yeah. What else stuck out to you as surprising? What did you learn?
Speaker 9:Yeah. Every time there's, apps that are kind of, like, literally single purpose, remove dot b g is a great example. Yep. It was a company that was acquired by Canva, but grew to, like, 32 monthly active users literally by being 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.
Speaker 4:Yep.
Speaker 9: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 Yeah. It's always a dozen or so each time. Janitor is one of them and one of the highest ranking ones behind characters. So it doesn't seem to This be looks
Speaker 1:because you don't
Speaker 2:know love. It looks very grok, x AI
Speaker 1:Yeah. Would have thought janitor would be, like, back office, b to b, like I I 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. Interesting. Also saw the spicychat.ai.
Speaker 1:That sounds like something we shouldn't push up pull up on this stream. Cushion.ai has a has a heart there that seems a little suspicious, juicy chat. These 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?
Speaker 1:Like, what what are the biggest movers that you're noticing or or that you expect?
Speaker 9:Yeah. This is a 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.
Speaker 9: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 Eleven Labs.
Speaker 1:Sure.
Speaker 9:Quite a few of them are general LLM players like PatchyBT, Perplexity, Poe.
Speaker 4:Yep.
Speaker 9: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 Sure. Wasn't even on the last list, and now they're, like, number 23. Replit's also on there.
Speaker 4:Both
Speaker 9: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 a significant majority of developers are using them.
Speaker 2: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, a CTO. And so that's just like decade 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 Replet 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. Yeah.
Speaker 2:Right? And so that's just like a flood of demand for peep yeah. Nondevelopers becoming developers for the first time.
Speaker 1: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 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 it into Meta AI.
Speaker 1:But, you know, LLMs are vended into Instagram, and yet Instagram is 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 wanna keep them separate? Is it what is your thinking about all of that?
Speaker 9:Yeah. Meta is really interesting. It's funny. The the larger tech companies, I think, have really, stepped up in the past year or so on the AI front. Like, Google is probably the best example of this.
Speaker 9:Yeah. Gemini was number two on the list. Huge. They also had the AI studio on the list, NotebookLM on the list, Google Labs, which is where you get VO.
Speaker 1:Oh, wow. They four Grock?
Speaker 9:Four companies on here. Four four separate entities on the list, which were all ranked separately with their own traffic.
Speaker 1:Yeah.
Speaker 9:Grok had a big debut on the list from from X, formerly Twitter. Yeah. 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.
Speaker 1:Yes.
Speaker 9:And so usage fell off a little bit.
Speaker 1:It did come out. Okay. Yeah. Yeah.
Speaker 9:So 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 overwhelming. Like, quality of the images generated, the they did the weird celebrity companion thing. So now that they're working with Midjourney, I would expect to see them make some improvements here, but it might take a little while.
Speaker 1:Yeah. Even the Midjourney 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's 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
Speaker 2:for Instagram. Mid do you think midjourney's ranking gets hurt because people still use it in Discord? Or is or is I think shift? Because it feels low at 28. Sure.
Speaker 1:Sure. Sure. Yeah. Yeah. Yeah.
Speaker 1:Just recently kinda rolled out the web.
Speaker 9:I think that's true for both Midjourney and Suno and a couple of other 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. Yeah. And now a lot of those companies are really trying to shift their traffic over.
Speaker 1:That's interesting. Yeah. Bet you could do a different list of just like the top Discords because all of that's very quantitative and available and even it rely relies on even further data. Jordy, do you have anything else you wanna take through this? I'm wondering if I can continue.
Speaker 2:Go for it.
Speaker 1:I I 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 in 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?
Speaker 9:Yeah. I'm definitely expecting to see more in prosumer and productivity. Mhmm. We're feel like both the models are just now reliable enough to actually do work for you Yep. Or getting there.
Speaker 9:And they're also agentic enough to like, Perplexity Comic can draft an email and put it in your Gmail
Speaker 1:Yeah.
Speaker 9:Drafts there, which is amazing. Yeah. So we saw a couple companies like Manus make the list this time Sure. Around that thesis, but I'd expect to see things like Fixer or Seraph
Speaker 1:Mhmm.
Speaker 9:And others in that category. Genspark is another big one that I would not be surprised to see on the next list.
Speaker 2:The other big surprise what's been happening 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 advertising against ChatGPT.
Speaker 1:To PDF.
Speaker 2:And Well, yeah. There's those. But I'm saying there was other ones that would be called, like, Open Chat. And it would
Speaker 1:be Oh, like sure. Yeah. Yeah. When you would search ChatGBTs.
Speaker 2:And they would have
Speaker 1:in app subscriptions Literally, literally, wrappers. Yeah.
Speaker 2:That's it. Yeah. ChatGBT.
Speaker 9: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 developers, mostly abroad
Speaker 1:Yeah.
Speaker 9:That were just kind of ripping off the free version of ChatGBT, putting it in an app, and acting like it was the same thing you got if you paid for ChatGBT premium.
Speaker 1:Yep.
Speaker 9:And they were called things like Chat and Ask AI or ChatGBT or ChatGBT or something. But they finally cracked down on that over the last six months. So now we have a mobile list that's like
Speaker 1:Yeah.
Speaker 9:More representative of true products. But it's all like beauty cam filters now and Sure. Scan your homework and get answers.
Speaker 2:Oh, really? What's your read on how Apple's done from a curation standpoint? There's like a lawsuit happening right now between x AI
Speaker 1:Yeah.
Speaker 2:And OpenAI and Apple.
Speaker 1:I mean, this is probably gonna get printed out and blown up on a big chart in in court soon because Yeah. Grock looks great here. But, yeah, mean, I I I I I'd love to know your thoughts on on on how Apple's curating the the App Store.
Speaker 9: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 gonna 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 with curation. It's definitely not like a pay to play situation Yeah. From what I've, you know, what I've heard.
Speaker 9:But I also don't think that they're necessarily kind of at the cutting edge of of what's truly the best products that are coming out next that people people should be spending time on.
Speaker 1:Yeah. They also They should hire you. They should. They they I mean, they also obviously prioritize they editorialize in what they recommend. And Yeah.
Speaker 1: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.
Speaker 2:Well, and Apple
Speaker 1:would imagine gets promoted. Midjourney, I would imagine gets promoted.
Speaker 2:Apple comes It's true. Gonna be every every day. There's an article in the New York Times Yep. About how somebody had some something tragic happened to them while getting advice from a model. Yep.
Speaker 2:And so Apple coms doesn't wanna be like, we recommended you recommended companions and the companions went haywire. Yep. It's just very
Speaker 1:Anyway, we gotta hop on with our next guest. Thank you so much for joining the show.
Speaker 9:Thanks for having me. This was so fun.
Speaker 2:Thank you for list maxing.
Speaker 1:Thank you for list maxing. It doesn't get so And keep
Speaker 9:reading it. I'm not Let's
Speaker 1:hit the gong for the big list.
Speaker 2:We hear we hear that gong is is too loud.
Speaker 1:Too loud.
Speaker 2:Sorry for your ears everyone. But great great to catch up.
Speaker 1:Thanks for hopping on. We'll talk to soon. Talk soon. Bye. Up next, we have Flo from lindy dot ai.
Speaker 1: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 ad quick combines technology, out of home expertise, and data to enable efficient seamless ad buying across the globe.
Speaker 1:Flo, how are doing? Sorry for keeping you waiting. What's new in your world?
Speaker 3:Yeah. All good. Don't worry. I'm doing great. You know, it's a it's a good day to build b two p SaaS.
Speaker 2:Yes. Yeah. Let's go. Let's hear it for b
Speaker 1:two p SaaS. Finishing out the show with some just amazing news. Tell me more.
Speaker 3:Yeah. We we just announced a a vibe coder today. I I just saw Olivia's appearance here. She mentioned Lovable and and Markleet and and a few of those. They've been blowing up.
Speaker 3:What we announced today is is is a vibe coder that can test its own Okay. And it it's kind of it's kind of insane to say it because, like, you would assume, like, of course, can, but, actually, none of those products check their work. Like, imagine the software engineer that's just like, here. And it's like, it doesn't work. Did you even test it?
Speaker 3:And they're like, oh, no. I didn't do that. So, basically, these Vibe coders rely on you to 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 and painful work. We just built
Speaker 1:about are you talking about generating a test suite in code or spinning up a web browser interacting with the with the Vibe coded product?
Speaker 3:It's it's the latter. Okay. Thanks for asking. Is it okay if
Speaker 7:I share my screen?
Speaker 3:I feel like it'd be better.
Speaker 4:Oh, you
Speaker 1:can share your screen, but we are live, so anything you share will be shared with the Internet.
Speaker 3:I'll just make sure my of g b 12 manager. Please. Yeah.
Speaker 1:Vibe code or something right now. Let's see. Live demos. They never go around.
Speaker 3:I'm not I'm not gonna do, a live live live demo, because it does take, like, three minutes or something, so it'd be a bit boring. Wow.
Speaker 2:Like, you
Speaker 1:know Singular is
Speaker 3:the way. Example. Built a 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.
Speaker 3:It's like, alright. I built this Scrabble wheel checker for you. I'm gonna open it. Okay? I'm gonna type a wheel that exists like thunder, and, yeah, it tells me it's valid.
Speaker 3:Now I'm gonna type a wheel that doesn't exist like z z q x w and oops. It tells me it's it's valid as well. Mhmm. I noticed there might be an issue. It's showing z z q x w as valid even though it should be invalid.
Speaker 3:Let me fix the API to improve the validation. Fix the API. Try again. Doesn't work.
Speaker 1:Okay.
Speaker 3:So that's it does have its own computer, its own browser, and it sees the work and can click around and and actually test its work.
Speaker 1:Yeah. Very cool. What what do you think the landing the landing not landing page, but, like what do they call it? Like, the like, the the the landing market. The first the first, like, product market fit moment.
Speaker 1:Do you have any glimmers of hope? Like, is this gonna 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, Squarespace or or any of those Weebly, like there was a whole boom in that. It feels like there's another boom in in vibe coding right now. Do you have expectations about where the sweet spot is?
Speaker 1:Because I I would imagine that people aren't going to build like, you know, they're they're not gonna go out and raise a $100,000,000 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 about the shape of that early customer.
Speaker 3:I think that's actually the perception of trying to fight. I think Mhmm. The reason why fight coding so far has been limited to these landing pages Yeah. Is because the the tools have been so limited. And landing pages also is like the the the the fastest, dumbest thing you can build.
Speaker 3:Same for, like, this perception. They're like, oh, it's like a cute prototyping tool, but you're not actually going to build your company on this. Mhmm. You know, we we it's a thing that is unlocked by this new paradigm of something as simple as, like, testing your work. If you can't test your work, you can only build very, very simple stuff.
Speaker 3:If you could if you test your work, we'll see instances of, like, this running for hours and building. Like, one of the craziest examples we've built internally. We could need, like, Linde BNB. So it's like an Airbnb clone, and it's functional. Like, you can you can select things.
Speaker 3:You can book them. You can put your place up for for for rent. It's functional. You can you can sign in. You can sign up.
Speaker 3:It's got Google Ads. It's got all of that stuff. So, you know, we're actually seeing a lot of so, yes, we're seeing the landing pages, but now we're also seeing a lot of, like, internal tools. So you're almost getting into, like, retool territory. Sure.
Speaker 3:Because people are like, I'm just gonna hook it up to my API, and I'm gonna build, like, oh, like, calculators and, like, various internal tools for the for the team in, a couple of minutes.
Speaker 1:Yeah. Do you think of this as, like, a separate product? Or does does this, like, kind of sit on top of everything that you've already built? And can you is there a way to, like, hook in the traditional, like, Linde's into what you're vibe coding?
Speaker 3:No. It's it's super integrated with the rest of the product that we build, which is, like, agents, obviously. And so that's the whole value prop. It's like, hey. Building your website is step one.
Speaker 3:Like, once you've done that, you actually have to build the rest of your business. Like, I I joke, like, building your website is sort of the equivalent of getting your your your business cards. Like, okay.
Speaker 1:You Yeah.
Speaker 3:That you did that. Now you need to, like, build a business. So, like, now that you built your website, Lindy can, like, market it for you, find customers, do the entire customer support for you fully autonomously. I I have want to actually launch LindyBnB and have it fully because I I've got enough of one business.
Speaker 5:I don't wanna run like Linde BNB, but have
Speaker 3:it fully managed by agents, you know, and see Yeah. See how far we can
Speaker 1:No. It's great. Yeah. Keep sharing demos. I'm I'm excited to check them out.
Speaker 1:Anything else, Jordy?
Speaker 2:Yeah. Just I I I'm interested, you know, clearly, I think it's almost contrarian at this point to launch another prompt to app builder. Right? And 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?
Speaker 2:Right? You see some of these revenue ramps. I think a lot of entrepreneurs would assume that the market is is run away. I should focus on something else, but you've clearly made a different decision.
Speaker 3:From the traction we're seeing, there is plenty of room in this market. I think it's it's like the very, very, very beginnings of this market, as crazy as that sounds. Yeah. Also and, you know, we've not told that story yet to anyone. The way this came about was, like, we actually built the v one of these by accident.
Speaker 3:So, you know, we had this released this released that, like, 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 to a computer, was like, oh, fuck. It can build websites, and you can QA them. Because that's what happens once you have a computer.
Speaker 3:You can do everything. So then we we basically packaged it up and released it as as an Lindy build and and improved it, obviously. But I think it it's basically an emergent capability of the platform. And the reason why we've decided to release it is, well, one, we were like, fuck. It's it's all been working.
Speaker 3: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. Like, this is actually, turns out it's like a massive deal. And and when we AB tested, like, okay, same prompt on, like, lovable, Replied, Lindy, this Scrabble example, for example, every vibe code out there, it's a simple example. It's like a very mini app. Every single vibe code got it wrong.
Speaker 3:Every single one, including Lindy. Like, it got it wrong first shot as you saw. And then the difference is, like, Lindy has then tried it on work, saw that it got it wrong and fixed it. So I I I think it's it's day one for this product.
Speaker 1:That's very cool. Well, congratulations on the launch. Keep us Last
Speaker 2: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?
Speaker 3:I have this conversation every day with with a different friend. I I forgot the different labels here, but like, look, you know.
Speaker 2:Are it's basically are we are we coming down from the peak towards the trough or are we headed up the slope of enlightenment? I
Speaker 3:think we're heading up the slope of enlightenment.
Speaker 2:Wow. Bullish. Bullish. Bull market continues.
Speaker 3:Very bullish. Very bullish.
Speaker 1:Well, thank you so much for hopping on. I'll talk to soon. Have a great rest of your day.
Speaker 6:Thanks, everyone.
Speaker 2:Bye. Cheers.
Speaker 1:Well, if you
Speaker 2:Shout out to Ilhan Vilani
Speaker 1:Yes. Shout out.
Speaker 2:In the chat. Yes. He is in university. At Boston University.
Speaker 1:Let's hear it. For b
Speaker 2:Watching with
Speaker 1:Cross the coasts. Five others. A window in Silicon Valley. Bullish. Well, let me tell you about Wander.
Speaker 1:Find your happy place. Book a Wander with inspiring views. Hotel grade amenities, dreamy beds, top tier cleaning and twenty four seven concierge service. It's vacation home but better, folks. Not gonna find a Wander on Lindy's vibe coated Airbnb.
Speaker 1:He's gotta solve getting good inventory. That's what Wander's done. Jeff Dean is I I don't wanna 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.
Speaker 1:See the examples in the thread below. It lets you indulge in a bit of creative fun, helps you make new business cards, etcetera. Try it out at gemini.google.com. Jeff Dean, of course, one of the greatest to ever do it. Very, very cool.
Speaker 1:We got a I mean, this
Speaker 2:So Logan Looks great. One shotted a a card generator.
Speaker 1:Oh, yeah. Yeah. We play with it? Maybe we should play with it after the show and we'll bring it up tomorrow.
Speaker 2:It's looking good. He's he sent me a preview. Yeah. Love it.
Speaker 1: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.
Speaker 2:I didn't know levels
Speaker 1:to the game. There is 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.
Speaker 1:That little subtle gradient there to highlight allow. Not not too
Speaker 2:Brian Halligan
Speaker 1:This is interesting.
Speaker 2:Saying, re Sonos, I have two ideas offers. One, it has a biggest 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 a big gain. Two, if you're a very sharp qualified entrepreneur that wants to disrupt them, I'd like to hear your pitch.
Speaker 1:This is the 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.
Speaker 2:Keith Rabois in the comments.
Speaker 1:Keith Rabois.
Speaker 2:Let me know if you wanna work together.
Speaker 1:Yeah. Keith Rabois is getting in the game. Naval is also there. Is He's also he's talking about another company that has an amazing product that needs to be distilled to a lower mass market price point.
Speaker 2:Kenneth Castle has a fantastic post here. Yes. He says I guess his wife says TS and TK are engaged. He says, question mark. Travis Taylor Swift and Travis Kelce.
Speaker 2:He says, oh, I thought you were talking about TK from Uber slash Cloud Kitchens. What? Is amazing. Absolute banger.
Speaker 1:Well And Did you notice what Taylor was wearing in her in her engagement photo?
Speaker 2:Absolutely not. But I did see
Speaker 1:Cartier Pantheir.
Speaker 2:Oh, the the watch. Yeah. Did see that that that
Speaker 1:Eight carat diamond ring. But more importantly, she was wearing a Cartier. Where could you get a Cartier? Bezel. Get bezel.com.
Speaker 1:UBezel Concierge is available now. Source you any watch on the planet. Seriously, any watch. If you're gonna be proposing to a pop
Speaker 2:Yeah. Star NASCAR. Yes. NASCAR has joined Substack. Don't think anybody would have called that NASCAR.
Speaker 2:Four years ago.
Speaker 1:We gotta do a collab with them. This is the whole thing on Substack. We're we're we're gonna do collabs with other people. So we gotta get a live video going with them. Get NASCAR.
Speaker 1:NASCAR. We've already talked to folks folks at NASCAR. This will be the second time we're collabing with NASCAR.
Speaker 2:An absolute terror. Well, grand officer. Thank you for tuning in today.
Speaker 1:Thank you for tuning in.
Speaker 2:We've had a fantastic time. We hope you have too. We hope you have an amazing afternoon. Follow our Substack, tbpn.substack.com.
Speaker 1:Yes, please.
Speaker 2:We're growing very hard over there. And we will see you tomorrow.
Speaker 1:See you tomorrow. Have a good day. Cheers.