TML Inkling, California Forever?, TSMC Capex | David Baszucki, Everett Randle, Eric Glyman, Jordan Black

(01:38) - TML Inkling (11:31) - 𝕏 Timeline Reactions (15:15) - California Forever? (17:27) - TSMC Capex (18:32) - Everett Randle is a general partner at Benchmark, where he invests in AI, enterprise software, and frontier technology companies. Before joining Benchmark, he was a partner at Kleiner Perkins and previously invested at Founders Fund, BOND, and Vista Equity Partners, backing companies including Anthropic, Rippling, Flock Safety, SpaceX, and Chainguard. (48:32) - Eric Glyman is the co-founder and Co-CEO of Ramp, the AI-powered finance automation platform helping businesses manage spending, accounting, procurement, and corporate cards. Previously, he co-founded Paribus, which was acquired by Capital One, and is known for building software that helps companies save both time and money through automation. (01:07:19) - 𝕏 Timeline Reactions (01:16:36) - Jordan Black is the co-founder and CEO of Senra Systems, a company applying AI and advanced software to modernize precision manufacturing for aerospace and defense. He focuses on building automated, software-defined factories that dramatically accelerate the production of complex, high-performance components for the next generation of industrial and defense technologies. (01:28:29) - David Baszucki is the co-founder and CEO of Roblox, the online platform where users create, share, and play millions of interactive 3D experiences. An engineer and longtime software entrepreneur, he previously co-founded Knowledge Revolution and has led Roblox’s growth into one of the world’s largest gaming and creator platforms. TBPN is made possible by: Ramp - https://ramp.com Public - https://public.com Cisco - https://www.cisco.com Console - https://www.console.com CrowdStrike - https://www.crowdstrike.com Figma - https://www.figma.com MongoDB - https://www.mongodb.com NYSE - https://www.nyse.com Railway - https://railway.com Shopify - https://www.shopify.com Codex - http://openAI.com/codex Follow TBPN: https://TBPN.com https://x.com/tbpn https://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231 https://podcasts.apple.com/us/podcast/tbpn/id1772360235 https://www.youtube.com/@TBPNLive

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00John Coogan?

  You're watching TVP and today is Thursday, July 16th, and we are live from the TVP Ultra Dome, the temple of technology, the fortress of finance, the capital of capital. Let me tell you about ramp.com. Time is money. Save both easy use corporate cards, bill pay, accounting, and a whole lot more all in one place. We have a very special show for you today because we have Tyler Cosgrove guest hosting. He's here in Great to be here. Chair. And I know I'm gonna make mistakes today because I always throw it over to Jordy. I gotta remember this Tyler, it reminds me of this video from Warren Buffett. We gotta play it to show what I'm going through emotionally today without Jordy in the TVP and Ultra Dome. Let's pull up this video of Warren Buffett throughout the years at the Berkshire Hathaway

• 0:44John Coogan?

  shareholder meetings to give you all. Charlie, how do you feel? Was that Charlie, me? How you? Charlie. Charlie. I'm so used to that. Oh, you gotta play it from the beginning. I checked myself a couple times already. Years and years, Warren Buffett always goes to Charlie after he gives his comment. He, he, he, he, he gives his speech and then he kicks it over to Charlie through the years. Charlie, Charlie, Charlie. Tear jerker. Yeah, makes me wanna cry. It's emotional. Charlie, how do you feel? Was that Charlie, me? How you? Charlie. Charlie. I'm so used to that. Oh, you gotta play it from the beginning. I actually checked myself a couple times already.

• 1:27John Coogan?

  Years and years, Warren Buffett always goes to Charlie after he gives his comment. He, he, he, he, he gives his speech and then he kicks it over to Charlie through the years. Charlie, Charlie, Charlie. Tear jerker. Yeah, makes me wanna cry. It's emotional. Charlie, how do you feel? Was that Charlie, me? How you? Charlie. Charlie. I'm so used to that. That's Greg Abel. So if that happens today, I apologize. But there is a ton of news we're gonna be going through today. We have a packed lineup as well. We have Ev Randall, Eric Klein, and Jordan Black, Dave Bazooki from Roblox coming on. We have a great show, and there's a lot of news. The first big story is of course, Thinking Machine's new

• 2:10John Coogan?

  model has released. Miramarati's AI startup released its first model in bid to loosen AI giants' grip. We're gonna be talking about open source, closed source, where the frontier is, national geopolitical model moves. And some people had an idea this was gonna happen, some inkling. Oh, they had an inkling. That, yeah, that they're gonna read some. Did they? I didn't have an inkling that they were going to jump into the open source grade. I think it's actually, I think it makes a lot of sense, given the Tinker API, right? The whole business is, is, you know, you're doing fine tuning on open source models. Yeah. It makes a lot of sense that they're gonna have their own. Yeah. That, you know, you can easily. It's sort of like, they are set up as a business to launch an open source model without it degrading any other piece of their business because the Tinker API, that fine

• 2:53John Coogan?

  tuning that they do, that integration with the customers that they have, actually benefits from open source. Yeah. And then they can go to their clients and say, look, you know, it's the red hat model at any time you can leave because we are giving you the weights of the model, open source. You can do whatever you want with them, but keep working with us because we're helping you a bunch and we're making money in the process. So Thinking Machine's lab, the first model is an open weights model designed to chip away at the lead of OpenAI and Anthropic, says the Wall Street Journal. Former OpenAI Technology Chief Miramarati is betting on more customizable artificial intelligence models to chip away at the lead that the frontier labs, such as her former employer, hold over the technology. TML, a company led by Maroti, released its first AI model Wednesday and did it with open weights,

• 3:37John Coogan?

  meaning that others can modify it with their data. Called Inkling, the model has 975 billion total parameters, making it far smaller than estimates of the most advanced closed source models. Yeah, but remember, so it's mixture of Yeah, mixture of experts. So only, I think the number is 41 billion of those are actually like active. At any moment. Yeah, so this is definitely on the, on the bigger side of open source models. Sure. But like that number, it's not, these aren't like dense models like what you traditionally think of. Sure. Of the models like, you know, four years ago. Yeah, yeah. Miramarati told the Journal, "We trained it to be a broad, balanced foundational foundation model, strong across many domains, flexible enough to adapt. Inkling is not

• 4:20John Coogan?

  the strongest overall model available today, open or closed," which is a different frame of reference for many of these model launches. There's, it's been, everyone's been jockeying for the frontier, even if they're not world-class at everything. Usually when they launch, they say, oh, well, we're best at something or we're best at this, but a different tone, different communication strategy. And I think it's being well received. I think people are having fun with the reaction. Yeah, I mean, I think the main picture is that this model is like uniquely set up for the Tinker API. Yes. It's built to be fine tuned. Sure, sure. That's the whole point. Got it. Didi Das says, "Thinking Machines just dropped the best open weight AI model outside of China," and obviously that is a big topic of conversation as business leaders

• 5:03John Coogan?

  in the United States have some policies and some reticence about using Chinese open source models, even if they're not worried about the dystopian, you know, Manchurian candidate hidden inside the weights. Maybe they just want to be aligned with a US-based company for a variety of reasons. Inkling beats Nematron 3 Ultra, and benchmarks put it between Kimi K 2.5 and 2.6. Of course, there's also news today that Kimi K 3 will be launching and is another jump forward, but there's back and forth between some AI researchers around what's going on there, how long that strategy will continue. So Dee Dee says, "Many were

• 5:44John Coogan?

  contending to this throne, but Thinky has come out on top. Really solid release and will pair well with Tinker." So there are some benchmarks that you can go and dig into if that's your thing. There's a, there's another very bullish take from Jack Morris of Ingram Labs. He says, "People are underestimating what a big deal this is. This is the only open weight model that, that's trained without distilling for OpenAI, from OpenAI or Anthropic. Kimi distills, GLM distills, Quen distills, Nematron distills, Kimi and DeepSeek, which count. Basically, a fully different tech stack, the first pure open frontier coding

• 6:26John Coogan?

  model. Very exciting." And there's a community note on this. Can you break down exactly like, where are they standing on the shoulders of giants? Where are they not? Yeah. So, yeah, so I think this tweet is not exactly true. In the blog post, they say, "To bootstrap post-training, we ran an initial supervised fine tuning on synthetic data generated by open weight models, including Kimi K 2.5." Okay. So I think that's like generally how people think of like distillation, that they mean something related to this. Sure. So I think that actually is not that different than what people like, you know, at Nvidia with Nematron did. Sure. So this is not like very new, I think. But it's sort of like the lightest touch of distillation that could happen because it's just one piece of the pipeline. Sure. One small amount of data. Yeah.

• 7:10John Coogan?

  It's not one of these scenarios where we're like, why is it identifying as Claude? Or why is it, why is it just saying that it's ChatGPT? But it is funny because you can kind of say like, oh, well, if this is like kind of distilled on, on Kimi, and Kimi's kind of distilled on closed source. Yep. Well, then maybe you get some kind of two-layer distillation. This sort of round trip loop. Yeah, yeah. At the same time, there's probably something to be said for the more layers of abstraction, the, the, the more, you know, ingredients you pour in, like the distillation becomes weaker and weaker. Yeah. And I think there's also an important question of like, well, okay, they're doing some level of distillation, like why? Because you can either be like, well, they're just doing it to save time, whatever. Like, obviously, they have these capabilities. Yep. But there's no point in, in, you know, doing everything over again. You might as

• 7:52John Coogan?

  well just, just use what's out there already. Or is it because actually like these capabilities that they get from this, this, you know, distillation light, whatever it is. Yeah. Are those actually super imperative to the model like being good? There was a reaction from Ingram, the company founded by Jack Morris. First, let me tell you about Consol. Consol builds AI agents that automate 70% of IT, HR, and finance support, giving employees instant resolution for access requests and password resets. So Ingram says, "Our founder, Jack Morris, recently issued some unfounded claims that got community noted. We deeply apologize for the confusion caused by his original post, the follow-up post, and the follow-up to the follow-up post. Nevertheless, we stand by his conviction in his own takes and in strong open source models like Inkling." And

• 8:35John Coogan?

  there is a question of like, distillation is a vague term where it's not a binary thing. Yeah. And if it's not in the pre-training data, does it count? I don't. I think it's also very much this, this mean people love to talk about on X. Yeah. They like to kind of, you know, scapegoat, oh, you know, it's all distillation. That's the only reason Chinese models are good. Yep. Is that actually true? Well, I mean, Anthropic's head of national security policy, Taran Chabra, accused Zepu, Z.ai, of distilling both Claude and OpenAI models for GLM 5.2 at the Aspen Security Forum earlier this week. This is from Vincent Chow, senior AI reporter at SCMP. He said, "It's the first time that they've named Zepu specifically after previously calling out DeepSeek, Alibaba,

• 9:17John Coogan?

  Moonshot, and Minimax. Join the, join the club at this point."

• 9:17John Coogan?

  We've even heard about whole companies that just like resell Claude tokens or GPT's

• 9:21John Coogan?

  Yeah. Also accused, they also accused DeepSeek of continuing its adversarial campaign of

• 9:23John Coogan?

  5.6 tokens and that looks like a reasonable business because it's just a wrapper company.

• 9:26John Coogan?

  distillation. Anthropic is now shutting down distillation accounts on the order of millions

• 9:29John Coogan?

  Of course, you want to work with them, but then you don't realize that on the other

• 9:32John Coogan?

  accounts of per week. That is crazy scale. You have to, I mean, you always think about

• 9:33John Coogan?

  side, who are their customers? Why do they, why did they get to 100 million run rate so quickly? Well, maybe it's a lab that's trying to distill through this pass through

• 9:37John Coogan?

  it as like, oh, there's like, shut down that one company or shut down that one block of entity. And of course, it's hard to like watermark the tokens. Once they go out the

• 9:41John Coogan?

  IP addresses. But when there's a really, really distributed attack. API and they get passed through some other system and they can go through other countries, all sorts of things. So millions per week, that is crazy. That's got to be really difficult to, uh, it's a game of whack a mole. Uh, they say GLM is quote, probably the most advanced Chinese model on the market now, which poses significant cybersecurity challenges. Um, they hinted that Anthropic will expand access to Mythos to ensure fair fight for cyber defenders. Um, and they said that distillation challenges real in shrinking US a lead in AI suggesting that the US government could do more to clamp down on Chinese model adoption globally by working with allies similar to trusted telecom efforts like Huawei and ZTE. So obviously

• 10:26John Coogan?

  a hot topic and people will be debating how, how, how exactly how heavy of a hand the government should be putting.

• 10:33Speaker 01

  Yeah, I think this, this release is also makes a lot of sense. And I think it was a week ago, there was that article about like Beijing is looking at curbing overseas access to Chinese top AI models. Right? So if, if you're not going to be able to access the Chinese open source, right? It makes a lot of sense to, to start doing American open source, Western open source.

• 10:51John Coogan?

  Yeah, it really does feel like there's a pretty

• 10:53Speaker 01

  It feels very well timed.

• 10:54John Coogan?

  Yeah, there's, it seems like there's a pretty wide gap with between at least what's reported, uh, preferences from Beijing, from the actual government and the companies. The companies are like, send us all the Nvidia chips. Let's distill everything. Let's, and then let's open source these models and compete internationally. And Beijing's like, hey, maybe we need like, you know, an indigenous supply chain here. Maybe we need to, you know, lock down these models, keep our lead over here, go work internally. Uh, I don't know. But if you're worried about security, head over to CrowdStrike. Your business is AI, their business is securing it. CrowdStrike secures AI and stops breaches. Uh, this was an interesting, uh, post from Grace Lee. Uh, she, she asked the question, how did OpenAI Soul finally

• 11:37John Coogan?

  learn design taste? Uh, she projected a thousand websites by GPT 5.6 soul into a design manifold and discovered big holes. These holes were where GPT 5.5 previously generated outputs, outputs with quote, bad AI smell. So there were, you know, there's these tells in any AI model, but it's not this, it's that, the M dash. Uh, once people start identifying those as, ah, we don't like that. It's too AI, it's too generic. Um, one way it appears to actually sort of beat that out of the model is to actively avoid those specific things. And then she calls out three particular areas that have been, uh, avoided as anti-patterns.

• 12:19John Coogan?

  One, the bento box layout in dashboards. Uh, two, large typefaces and hero images. I did realize that, that sometimes you would ask for a website and you would just get a massive block of huge text. And that's just not the way you, when you land on a beautiful website. It's usually there's more wordsmithing, there's more terse language.

• 12:39Speaker 01

  Well, you know, you, you make your first website with, with five, six hole or whatever, and it looks really good. And then you make 10 and they're like, oh, okay, there, there's actually a lot of patterns I'm, I'm seeing.

• 12:46John Coogan?

  Totally, totally.

• 12:47Speaker 01

  And you can start clocking them like everywhere you see, you see a lot of like Claudeisms, whatever on general design. You see them everywhere.

• 12:53John Coogan?

  Yeah, especially if you don't come with any opinion.

• 12:56Speaker 01

  The, you know, high border radius on the edges. There's a little color on the side.

• 13:00John Coogan?

  Yeah, yeah. Uh, especially if you don't come with like an opinion. If you come like, uh, we made a whole vibe coded website in Codex for just the latest episode of Nick Bostrom on Joe Rogan. And I wanted it to look like a UFC fight card and a fight promotional website. Uh, and it doesn't look like any like normal AI slop. I mean, there's still like AI generated images. It looks like AI, but it doesn't look like, oh yes, that's the bento box layout, or that's the offset layout, or that's the purple, or it's stealing from linear. It's a completely different style. So if you at least inject like one reference point, you'll usually land somewhere.

• 13:38Speaker 01

  Yeah. I mean, it is interesting though. This makes it seem like, you know, the new model is not necessarily, it doesn't have like higher variance with outputs it gives, but it, we basically just found like, oh, there, there's certain examples that people really don't like. Let's just remove those. But you're not necessarily like making the model more creative by, by removing these like patterns it always comes to.

• 13:58John Coogan?

  Yeah. Well, you're giving like the, the flavor of creativity and maybe that's

• 14:04Speaker 01

  Yeah, but you can imagine if we kind of keep the same model for six months, we'll just notice new patterns.

• 14:09John Coogan?

  Totally.

• 14:10Speaker 01

  And you'll have this kind of

• 14:11John Coogan?

  But at the same time, like mid journey had like a very distinct look and people liked that look, at least some people. And so if you can, if you can quickly personalize and customize and land in a place where someone whose job is designing dashboards is happy every time with the layout, like there is somewhat of a platonic ideal for some of these design patterns. And at the same time, uh, if you're, yeah, working on, uh, certain, like there, there are certain designs that are just like solved, like, you know, make the call to action green or blue, not red, right? Uh, and so some of those like do need to be consistent. Uh, and then also I imagine that, um, many folks who are using these

• 14:55John Coogan?

  tools like in enterprises are doing, even if it's not a fine tune, they're uploading a reference for everything that they're designing. So it's consistent with the brand that they've designed.

• 15:04Speaker 01

  Yeah.

• 15:05John Coogan?

  Anyway, let me tell you about the New York Stock Exchange. Want to change the world? Raise capital at the New York Stock Exchange. Just do it. Just do it. Stop making excuses. Um, California Forever lost a $3.2 billion shipyard project from defense startup Sironic after the company chose the port of Brownsville, Texas over Solano County. I was, oh, no, you're not supposed to clap for that. We got a Texan in the studio who's happy about that. This is bad news for California. We want California to have a whole bunch of amazing stuff. Uh, Brandon Gral, who wrote the newsletter, tppn.com today, uh, was very disappointed about this. Uh, the automated shipyard known as Point Alpha, Port Alpha

• 15:49John Coogan?

  is expected to create roughly 10,000 permanent jobs along with thousands of union construction jobs. Supporters say California's lengthy approval process ultimately cost the state one of the first marquee tenants that California Forever had appointed to as evidence its planned city could anchor a new era of American shipbuilding. Uh, Joshua, uh, executive director for the California Alliance for Jobs said California failed to move with the urgency the product required, quote, while Texas moved quickly and aggressively. Thank you, Jackson. Um, California could not provide clear expedited approval process needed. Uh, he said, calling the decision an enormous loss for Solano County, California workers and our state's manufacturing economy. Earlier this year, California Forever signed a 40

• 16:31John Coogan?

  year construction labor agreement covering 70,000 acres and labor groups later backed legislation to fast track environmental review and permitting for the proposed shipyard the legislation has yet to advance. Instead, Texas approved a $211 million tax abatement package in June to secure Sironic's investment at Brownsville, roughly 20 miles from Starbase. Labor leaders said they warned that without expedited approvals, the project would leave the state. And that is exactly what happened. A project insider told the San Francisco Chronicle that California Forever itself remains on track, but acknowledged that losing a major defense contractor sends a powerful signal about the state's ability to compete for large industrial investments. Very disappointing, but, uh, I like Yan, I like the California

• 17:15John Coogan?

  Forever project and I'm excited for where he takes it next. I'm sure he's on the hunt for the next major tenant. Um, but we have our next guest soon in the waiting room. We'll bring in Everett Randall from Benchmark in just a minute.

• 17:29Speaker 01

  Got to talk about TSMC.

• 17:31John Coogan?

  Yes, TSMC. Um, where is this in the stack? TSMC both, uh, beat earnings, um, and raised their capex guide. They're spending a lot more money. Um, and

• 17:42Speaker 01

  Fledged to invest an additional 100 billion in the US, plans to spend a record amount cementing a position atop the global semiconductor supply chain.

• 17:50John Coogan?

  Yes. Um, but, uh, and, and yeah, and they're, they're investing another 100 billion in, in Arizona fabs. But, uh, people are worried about overspending. The news is the, the NASDAQ dropped 1% on TSMC's spending plans, offset by strong results. Um, very, very, uh, very, very odd story that in a time when even TSMC, which was not a particularly AGI pilled company for a long time, since they've been through the, the smartphone boom, the so many booms and busts, so many cyclical build out cycles, um, that when they are finally like, yes, now is the time, people are, I don't know. They're skeptical. But we have Ev Randall in the waiting room. Let's bring him in to the TBB and Ultra Dom. Ev, how are you doing?

• 18:35John Coogan?

  Hey gentlemen, how we doing? Welcome to the show. Jordy's traveling. Johnny, not Jordy. We have Tyler Cosgrove.

• 18:41Speaker 01

  Jordy's traveling.

• 18:42John Coogan?

  On our team, a guest host today. Very excited to have you. Um, how are you doing? How is, uh, how's the year going? I'm interested in just like your general state of the markets. You recently said, I've, you said, it's an incredibly disorienting time to be investing. What's disorienting? You just put money in every company and they all go up.

• 19:03Everett Randle?

  That's certainly what it feels like feels like for the last 18 months, which is which is scary in and of its own. Yeah, I did. I was on, you know, my partner, Jack Altman's podcast, I'm Capped with Trey and Delian over at Favers Fund. And I was saying that one of the scariest things of today, and then we can go to the disorienting part, but one is just the scariest parts. Is this feeling of inevitability. Like, it kind of feels like sometimes, oftentimes, it does feel like as in venture investors, we are monkeys throwing darts at a dartboard. And, you know, you never really know when, like, what number you're going to hit.

• 19:42Everett Randle?

  But imagine you're that monkey and you just keep hitting like the triple 20, like every time you throw it and you're like, this is weird. And, you know, your response to that usually is just like throwing a lot more darts. So the last 18 months, the last 24 months, everyone, I think, is feeling, feeling, you know, very, very confident in in the market or just like how how other companies are going. And all these companies are growing extremely fast. And so everyone is investing a ton of money. It's all getting marked up very, very quickly. We obviously had the SpaceX IPO, which was huge for several firms. We're probably going to have the OpenAI and Anthropic IPOs that are going to be huge for a bunch of firms. Like, there's just this sense that, like, we all know that AI is going to change the world in so many ways.

• 20:24Everett Randle?

  We all know that, you know, all these, you know, space is big, defense is big, nuclear energy is big. All these things are big and therefore, you know, more and more money into these things and they just keep getting marked up. And the last time I felt like investors had this much of a sense of inevitability, like, yes, it's expensive, but like it's going to get marked up in six months, so therefore we should do it, was the summer and fall of 2021. And we all kind of know how that that ended up.

• 20:50John Coogan?

  Yeah, I want to talk about what's similar to 2021, what's different. But first, there was something, I don't remember exactly who said it on that podcast that you did with Jack, Dylan and Trey. But there was this concept of when a firm has one of these huge power law wins, like a SpaceX and an Anduril and Anthropic and OpenAI, then the liquidity is coming and they're, the phrase that was used on the podcast was playing with house money. Does that mean like literally recycling or just your LPs are more excited to back you, write bigger checks? Like the purse strings are looser? Like, what does playing with house money mean? How does it feel? What are the risks?

• 21:32Everett Randle?

  Yeah, a useful analogy here is maybe like in sports. So like, let's say you are, you know, up to bat in baseball in the World Series and you hit a grand slam. And then the next, the next at bat, you hit like another grand slam. And so you're like, okay, I've hit two grand slams in a row. Basically, whatever else I do for this game, like I did my job, like I'm good, like I'm great. And counterintuitively, honestly, that might make you better because you're just swinging free. You're swinging away. You're taking a lot of risk. You're like, screw it. I've already done my job. I've already, you know, you know, contributed to my team and scored a bunch of, a bunch of runs for my team.

• 22:16Everett Randle?

  So like, I'm just going to swing away. I think that very much is the case around the industry where if you have a lot of exposure, especially in Anthropic, but also in OpenAI and a few other companies, a lot of these firms have sprinkled their exposure across several different funds. So it's not like you invested in Anthropic in one fund. Like, I know funds that have Anthropic in like eight of their funds because they're like, this is, like, this is the, this is the golden goose, the masa golden goose, you know, thank all the golden eggs. So we're going to put it in every fund. And so then now they're like, look, all of our funds look great. They're going to look even better when Anthropic IPOs. So like, let's take some risk. Let's like, you know, let's swing away.

• 22:59Everett Randle?

  And honestly, it might, it might do them well, but that's, that's the whole concept of playing with house money is like, Anthropic is going to buoy so many fund returns across their portfolio of funds that you might, you know, you're like, look, look, we don't need to play super conservatively from here on out.

• 23:11John Coogan?

  And, and that feels like something that is uniquely different than 2021. 2021 felt like much more of a broad-based bubble in the sense that there were power law winners at the time, but you didn't have the same effect of if you've spread this one company across all of your, maybe I'm just not remembering, but I don't remember it that way. I remember it much more like there are, there are so many SaaS companies that are going to go from 100 million ARR to 2 billion, 1 billion, that we can underwrite them all, even though they are competing. And then there's this AI wave that's coming. But what do you remember about 2020, 2021 that was similar or different?

• 23:52John Coogan?

  It feels like it was a little bit more driven by spreadsheets and actual growth math as opposed to a major technological shift. But what was that era like for you?

• 24:03Everett Randle?

  It's funny, you still had like, obviously you didn't, you didn't have the extent of IPOs of like a SpaceX and OpenAI or Anthropic. But, you know, you had like DoorDash, you had, you know, Airbnb, you had Palantir. So you had like, you did have some liquidity, you know, New Bank, a few others. So you had like, there was a lot of money that was made, but it wasn't, you're right that it wasn't to the extent of Anthropic where you're like, oh, we had New Bank, so therefore like we can like go to the beach and just like take a bunch of risk.

• 24:32John Coogan?

  And Palantir in particular was, I mean, what, 10 billion IPO and not really sprinkled across many funds, very concentrated and sort of a black sheep of venture for a long time. I don't know if that's the right term, but.

• 24:47Everett Randle?

  You're totally right. Like the actual IPO, like, you know, one, it didn't do well. I think the share price was like stuck at like $8 for like a year or two or three years. It took a while for it to take off. So you didn't, you didn't have nearly as much money. It's funny, I actually went back, I remember in, I think in like 2024, 20, yeah, 24, so a couple of years ago, I was like, I want to go back and like read, like, what were we doing? Were we all high? Like, what, like, what was going on? Like, were we, like, were we just drunk?

• 25:16John Coogan?

  Yeah, there was this guy who wrote this whole piece about like aggressive crossover funds coming in. That was a crazy moment.

• 25:22Everett Randle?

  That was a crazy moment. But I was like, okay, like, this is, like, what, like, what was, like, if I was to go back and read investment memos, like, and put myself in my mind then, and not me, but just like the industry's mind, like, was this all rational? And I think that the really tough part about 2020 and 2021 was that from like the last two decades before then, all of these trends that we were investing behind were very secular. So if you like, look up the e-commerce penetration rate as a percentage of total commerce in the US, it's like the most straight linear line you've ever seen. But then 2020 happens, we all get locked up and there's like this insane acceleration. And so tech investors were always, you know, taught and trained on the fact that like,

• 26:06Everett Randle?

  growth kind of goes one way. Like, there's, it's not cyclical. It's not like up and down. And so you look back at a lot of these investment memos and a lot of what people were thinking and the companies were doing unbelievably well. Like, all these SaaS companies were growing like, you know, 200, 300%. They had really good fundamentals. The cohorts looked good, like customers were expanding, they were staying. Like, the, all the fundamentals were really, really good. And then, of course, you had an overlay on top of that, which was like the public markets were pricing SaaS companies at like 40 to 50 times sales. That's the craziest thing to me. It's like, you look back at, at like, you know, the Snowflake IPO

• 26:45Everett Randle?

  and you're like, I was, I was reading the S1 and I was like, the thing was that like, less than 500 of revenue went out at like $80 billion. And I was like, okay, there's some crazy stuff that's happening right now, but we're like, we have not seen anything, anything like the tops of the SaaS 2021 bubble when like Snowflake was going out at like 120 times revenue on the public markets.

• 27:07John Coogan?

  How much, how much of the multiple compression that's happened is venture capitalists actually learning their lesson? The market learning their lesson or just purely interest rate effects?

• 27:16Everett Randle?

  I think it's actually just the, the compression and multiples that we see now is people are just more scared of the business models. Like, obviously, you know, everyone's saying like, oh, SaaS is basically dead, like terminal value concerns, all those things. But when you think about all the most popular business models and the most popular businesses that are getting funded right now, like, there's no, there's no precedence on public markets of like an AI app company. Like, we don't know what like an AI app company will trade at. We don't know if it'll trade much better than SaaS, moderately better than SaaS or the same as SaaS. We, we don't really know how like a space company, besides, you know, with the exception of SpaceX, which is like an exception, not the rule, we don't know how like a space company we will trade. We don't know how.

• 28:01John Coogan?

  With that one, what about like ASTS, Rocket Lab? Like, there's a couple of public comps in like the pure play space area, no?

• 28:07Everett Randle?

  That's true. I, unless on launch, I more mean like, you know, satellite companies.

• 28:11John Coogan?

  Sure, sure.

• 28:12Everett Randle?

  Or like, and yes, you could say the same thing about like, yeah, with Anduril, there's obviously a lot of, a lot of primes. But like, God, I hope it doesn't trade like that.

• 28:21John Coogan?

  Yeah, yeah, yeah. Much more like.

• 28:23Everett Randle?

  That's the thing where it's like, a lot of the things that people have been investing in either don't have precedence.

• 28:28John Coogan?

  Sure.

• 28:28Everett Randle?

  They have something about them, like lower gross margins or capital intensity that's scary. Or the incumbents trade really poorly. And so you're like, well, like, you know, this is kind of like when a firm went out. I think in 2020, no one knew if it would trade like a bank or like a payments company. And like sort of traded as a hybrid of the two, but no one really knew how to like, how to, how to think about the company for a few quarters until it's public. So I think lower multiples, mostly because people are just discounting because they don't really know how these things are going to trade.

• 28:59John Coogan?

  Sure. I want to talk about closed source, open source, just token maxing and the economics of AI right now. But I want to go back to your January 31st, 2024 post. You said, making a real effort to not take for granted the quote, $3 Uber, Uber across town era of AI. And I hope you are too. That feels remarkably prescient, extremely true. I didn't realize, I think the last time we talked about it was around just the models getting expensive, around reasoning and the gross margins changing. But now it feels like this is like directly targeted at CFOs of like large companies

• 29:44John Coogan?

  who are showing up with, I mean, we have Eric Lyman coming on the show. They had one, their AI spend, spend hit 1.5 million in a single week. And so we are out of that era, but as you, as you reflect on that, was that what you were predicting? How are you, how are you seeing opportunities across new companies in the era of like cost control and ROI maxing? How are you processing that idea of like the end of the Uber era? Because in many ways, there's still a knockout, drag out fight between Codex and Claude Code and they're resetting limits every 12 hours, six hours, they're fighting it out. Like, we're still sort of in the capital fight, but at the same time, we're also in the, some, some enterprises are really controlling costs now.

• 30:28Everett Randle?

  Yeah, there's, oh god, there's so much to this topic and there's so many different things we could talk about. So I'll try to hit the best portions of it. Yeah, the tweet, the tweet, I think there was like a consumer part of the tweet and then an enterprise part of the tweet. And like the consumer part of the tweet was like, there's no ads. You know, the L L M's don't want anything of us. They're still super raw. It's just this like silly little service that like clearly is going to need to mature into an adult, you know, cash flowing product one day, but right now it's not. Like you could also compare it to like the old days of Instagram. Like when Instagram didn't want anything from you, it was amazing. It was like the best app ever. And now it wants money from you in the form of like you, you know, being an ad unit.

• 31:11Everett Randle?

  And so all you see is short form video and it's like, you know, rod, you know, and like brain rot. And T V P and videos. So those are, those are the ones that say, and then on the enterprise side, there was all this, um, you know, that there was reports that sometimes it was like, man, cursors, it's really hard to compete against something like Claude Code because they would compare the basically amount of Claude usage you could get through a subscription plan with, with, with Anthropic versus A P I via cursor. And you'd get like 20x the usage with Anthropic. Like this insane subsidization on Anthropic. And I think both just the incremental adoption of A I by enterprises and that's starting to like move down a bit.

• 31:52Everett Randle?

  I still think there's like a fair amount of subsidization, but it's like starting to go away a little by little as, as these, as just like the token hungriness of the models gets much higher. Like now that we've done like, you know, we've moved from like, again, just chat G P T to long running agents that are like way token hungrier because they're reasoning models, um, and like you that use sub agents and all these things. Yeah, the costs have just like absolutely ballooned. Um, and, and so I like, on one hand, it's, it's like very clear that we've like exited the three dollar Uber stage. On the other hand, you know, there's folks like Dylan Patel, um, at semi analysis and there's some of these like really forward leaning

• 32:31Everett Randle?

  companies that are like, not only are token costs reaching our human labor costs, but like we hope they go over. You know, and like, we hope all of our competitors use open source models and like, we hope all of our competitors use, you know, um, like dumb models because our employees will be using the frontier intelligence models. And like, that's our competitive advantage. And so I don't believe there's like, there's, there's a lack of clarity around all of this that I think is again, part of the disorienting thing about even investing in A I. I will say we're seeing an immense amount of app companies. I think if an app company, like app companies are either already at 80% plus, um, open source usage

• 33:13Everett Randle?

  for like their own apps that they're, that they're serving to, to their customers. Or like 90% of them are trying to get to that ratio plus. Um, so a lot across our portfolio and beyond, a lot of people are working with folks like fireworks to, you know, custom train and fine tune, um, these increasingly good open source models. Um, because and like Jesse at Decagon actually had a really good post on this where he talked about just the fact that like for mature use cases that can be, that are well known and can be fine tuned on, you just don't need frontier intelligence anymore. And oftentimes it's best for these app companies to fine tune open source, um, models around those specific use cases.

• 33:51John Coogan?

  Yeah, are, are you finding with the application layer companies internally, they're adopting the semi analysis approach? They're using the frontier to build their tools, but then if they're vending out tokens, they want those to be very efficient because that, that scales with their user base, not with their employee count?

• 34:10Everett Randle?

  Yes, I think that, that is probably completely correct. I think it's like an extremely good take. Where it's like, yeah, like for, and, and, but the only reason I think of that is because what are they using it internally for? You know, like, like they're using it for coding and like they're using it for, and like these are, these are high velocity startups where like the number one thing that matters is high quality shipping velocity of software. And so, um, if they can get a competitive different, uh, if they can be differentiated competitively by shipping faster, by using Fable and just like spamming, you know, Fable the whole time, they're going to do that. Um, but then the thing that they're selling their customers is, is a very different use case. So if it's like a support, you know, agent, um, you can use open source for that, but like the frontier intelligence on coding is still, you're seeing a lot of incremental gains for that.

• 34:55John Coogan?

  Yeah, yeah, the frontier labs are the spikiest on coding. Um, like that, that thinking machines example from Bridgewater felt like a unique spike in, in research and news analysis that might not show up at a frontier lab because it's maybe a smaller market. Uh, but, uh, but thinking machines like bring that to bear, fine tune something that outperforms everything at a lower cost. Um, what, what else are you sort of retreating to in the age of the application layer? Are you more likely to look at two sided market places, network effects, uh, something with like the other sources of power from zero to one?

• 35:34John Coogan?

  Um, if, if just like big pile of code is not defensible in the long term, like it was maybe a decade ago? Um, yeah, what are you, what are you actually looking for? And then are you actually seeing entrepreneurs acknowledge that and then go and build that?

• 35:52Everett Randle?

  Yeah, yeah, I mean, I, I will say like seeing a nice at scale marketplace with clear network effects. It's like a, it's like a drink of water in the desert. It's like, oh my God, you know, like I don't have to worry about A I labs or, you know, business model quality or any of these things. And so it is a breath of fresh air because, um, I feel like those, you know, those are always in style, you know? Um, these like super seven powers Modi businesses that somehow avoid A I exposure because maybe they're, they're consumer marketplaces or something. Um, so, so I absolutely think that's the case. I'm also, I, I, I've always been relatively less, um, or like not really in the bearish camp around lab risk for a lot of these, um, app companies.

• 36:36Everett Randle?

  Um, you know, one, like, one, one, like silly example could be like, you know, some people like, oh, like, you know, Claude for legal is coming out, like Anthropic's going to legal, like, uh-oh, legal A I space. And my response has always been like, look, like Anthropic in like three months of 2026 probably added the amount of like near, like even medium or long term TAM that exists in A I legal, which is still like a ton of revenue, like it's still an immense amount of revenue. But like, you're telling me that they're going to put like their eight, like their SWAT team to like grind out what is a top down sale market over like seven years to maybe add some portion of the A R R that they added like in Q one?

• 37:21Everett Randle?

  Like what, like it just doesn't, like, it just doesn't make any sense at all in terms of like the highest and best use of like the labs time. And so I think all of these markets, like again, like, um, people need to think about like, well, what, like, what are the theoretical competitive risks and what are like the practical competitive risks? And like throughout SaaS, I'm sure like if, you know, um, you know, Microsoft at one point was like, we're going to win this extremely niche market for X at any given point. And it became like the number one project for the business, um, then they could go do that. But they didn't do that because they had like Microsoft Office, you know, doing tens of billions of A R R and like their security business doing tens of billions of A R R. And so it's all these things around, um, prioritization that I think are, that I, that I think, um, people don't think about.

• 38:06Everett Randle?

  And so I'm not that bearish on, on the app layer stuff. And then the last thing I'll say is that the, the other really interesting thing that I'm seeing is that there are all these like short term things that I totally get why companies are doing them. Um, and I think they, they like kind of have to do them that in the long term, we're going to look back and be like, this clearly made no sense to do long term. The biggest one, um, that, that I see is like every app or not every app company, but like a lot of these app companies now feel like they need to have like a labs team where it's like every single app company, um, you know, they'll hire like, you know, a few researchers from Meta or something. And then all of a sudden it's like, well, we're, you know, we can defend ourselves from the labs because like we also have a research team. And like, we're doing like, we're doing like A I research.

• 38:49Everett Randle?

  And it's something that I think we'll look back at in like, in some cases, it will have been valuable. But in many cases, I think it's just like a way for founders to be like, oh no, look, like we also have researchers, like we don't have risk from the labs, like we're doing our own research. And I just think that like, there's not, there's not that many opportunities for like an in-house research team to be doing that much groundbreaking work, um, you know, relative to like what, what the actual best researchers are doing, um, within all the places that have the most G P U's, which is the frontier labs.

• 39:17John Coogan?

  Yeah, it's interesting because labs can mean a few things. It could mean A I research or it could mean experiments. And if you're an eBay.

• 39:26Everett Randle?

  This isn't Ramp Labs, by the way, because Ramp Labs is, is doing like also experimentation.

• 39:30John Coogan?

  Very different case, but, um, but, uh, there's, there's a world where you're eBay and you realize that like the labs aren't really going to steamroll you because you have this like liquidity in this market and this network effect. Um, but you know, just figuring out the right way to integrate A I. And maybe it's not just stuffing a chatbot in the corner. Maybe it's something a little bit more polished and having a team that can go out and look at the full product surface area without needing to be like the top down A I mandate of like every feature needs to be A I enabled is probably the wrong pattern. But letting a team go around and say, well, yeah, actually we don't need to add A I to the checkout flow

• 40:13John Coogan?

  because we want addresses to be deterministically verified. But in terms of descriptions, if somebody's asking about this product, throwing an A I summary there might make sense. And we're going to use an open source model for that because it's going to run on, you know, millions and millions of, of product descriptions or something like that. Uh, Tyler, I want to give you a chance to ask a question if you have anything.

• 40:34Speaker 01

  Yeah, yeah, I was, I was curious, um, how worried are you about like the massive dependence that open source has on, on China? There was this article, I think a week ago, and it was something to the extent of like Beijing is looking at uh, curbing overseas access to Chinese top A I models. Um, almost all of the, the Western open source models seem to be like quite reliant on the Chinese models, which in some sense seem to be reliant on, on American open source. Maybe it's just a circle, but it seems like that's like. If a lot of these app layers are just training their own models, they're doing fine tunings on open source models.

• 41:10John Coogan?

  From China.

• 41:11Speaker 01

  Yeah.

• 41:12John Coogan?

  Those go away.

• 41:13Speaker 01

  Or they stop accelerating.

• 41:14John Coogan?

  Because China says no.

• 41:15Speaker 01

  Yeah.

• 41:16Everett Randle?

  Yeah. Yeah, 100%. It's funny, I, on a podcast recently, I just, for some reason, can't prevent myself from saying spicy takes that get people mad at me. And we were talking about open source models, I think it was on Harry Sevins' pod, and I was like, where are the good Western models? Like, why, like, we're like, all, like, and some, and I'm like, we don't have any good open source models. And everyone was like, we have so many good open source models.

• 41:47John Coogan?

  Jensen is dunking on you.

• 41:48Everett Randle?

  This company, and this company, and this company is like, good. And then I didn't, because I restrained myself, I just wanted to tweet back the open router token rankings.

• 41:56John Coogan?

  Yeah.

• 41:57Everett Randle?

  Then where are they? If they're so good, why don't people use them?

• 41:59John Coogan?

  Yeah.

• 42:00Everett Randle?

  Why do you, like, look at the top 10 on open router? Like, all of them are Chinese, all of them. And so I think that, I think that, like, a good pushback to what I said on that podcast was like, well, they're coming. And I've always been like, well, where are they? But now we actually are starting to see some American teams, like, actually really go hardcore at the opportunity. And so, like, one, Nvidia obviously cares deeply about there being a strong open source ecosystem. They've done more than any single company across the entire stack to fund and support and, like, bring into existence an awesome open source ecosystem. And so I think we all owe Nvidia and Jensen a debt of gratitude for pushing so hard for a healthy open source ecosystem.

• 42:44Everett Randle?

  So they have NemoTron now. NemoTron, by all appearances, is like a great start. And I know a lot of people in our portfolio, they're actually quite bullish on, like, the future of NemoTron. Thinky, just Thinking Machines Labs just came out with Inkling, which, again, a lot of people are very excited about. They don't claim that it's, you know, at the frontier even of Chinese open source yet. But again, it's extremely customizable, which people love, enterprises and app companies love. And again, it's a commitment, you know, seemingly a bit of a commitment to continue to develop open source models. Reflection AI has always been, you know, they now have, their strategy is, I don't think they've released one yet, but like, their strategy is clearly to, you know, have the American open source model.

• 43:26Everett Randle?

  And so I think relative to even three or four months ago, there's more that you can point to around, like, okay, like, the West is actually trying to do these things. In terms of, like, the nested contingencies of, like, who's distilling who, and like, where are all the model capabilities coming from? I think, like, I think the whole distilling thing is, like, I think it's oversimplified. Like, I think it's, like, a little too simplistic. I think it's also, like, a little, like, maybe there's some, like, xenophobia in there where it's like, in the public, where it's like, well, the only way that the Chinese models are good is if they're just, like, distilling.

• 43:56John Coogan?

  Sure.

• 43:57Everett Randle?

  And they're doing nothing else.

• 43:58Speaker 01

  Yeah, it's like.

• 43:59Everett Randle?

  Like, they clearly cook some stuff up. Like, they clearly are doing some really good creative things. And, like, the DeepSeek paper was, like, truly groundbreaking. Like, it was awesome.

• 44:07John Coogan?

  And you can see it, because, like, open source architectures get ported back into foundation models and closed source labs all the time. And also, you just see that there's a ton of successful AI researchers who come from China and stuff. But yeah, I think that's all a good point.

• 44:20Everett Randle?

  Yeah.

• 44:21John Coogan?

  I have another question related to the application layer. I'm interested, like, venture's been through these, like, sort of experiments, whether it was, like, biotech for a little bit, D to C e-commerce was sort of enabled by Facebook, and then eventually, D to C didn't die, it just sort of returned to the, the, the better fit was, like, CPG private equity firms know how to do it, they still do it. There's still some amazing outcomes, usually in, like, the 500 million to 1 billion category. You're not seeing trillion dollar CPG companies anytime soon. But is there, are there any areas in the application layer that you're seeing, oh,

• 45:05John Coogan?

  this category is now potentially investable as a venture opportunity because of AI? I'm thinking, like, game studios or something else? Or is there a, or is there a pocket of previously venture backable companies that maybe should be moved more over into, hey, just bootstrap that, get it to scale, do some private equity, secondary, run it cash flow positive, more of like a lifestyle business?

• 45:29Everett Randle?

  Yeah. I think there's a lot of both. I mean, even, like, if you think about it, even, even in some of the more obvious verticals where we've seen early AI winners, like, even in legal, right? Like, legal before AI was not seen as, like, a venture category.

• 45:43John Coogan?

  Yeah, yeah. Atrium and Clearspire, two, like, really solid runs at that, the tech-enabled law firm. And, you know, Ruff goes on both, on both accounts. And now it's like, oh, the money's flowing, the business looks like a normal tech company. Yeah, there's still, like, margins and whatnot, they gotta pay for tokens. But like, in general, it looked a lot more like a tech company than a law firm.

• 46:04Everett Randle?

  For sure. And even the SaaS companies that sold into law, it was always just like, oh, super constrained TAM, it's a slog, you can't get law firms to pay a lot. And now, you know, Legora and Harvey have just, like, absolutely eye-watering numbers that, like, you know, for the last three years now, and clearly are among, like, the very.

• 46:22John Coogan?

  And Harvey just acquired Benchmark, right?

• 46:23Everett Randle?

  That was a jump scare. I was like, we did what?

• 46:27John Coogan?

  We did what? Yeah. Probably a good strategic move, but also just a hilarious troll in the timeline.

• 46:35Everett Randle?

  But then, on the PE, like, on the, on the, on the, on the other side, there's, like, obviously, we're in Recore, and they've become this, like, huge, awesome platform for the task economy and kind of, like, you know, finding the data that actually now moves these models forward.

• 46:54John Coogan?

  Yeah.

• 46:55Everett Randle?

  There's so many, if you think about, like, at the limit, if the limit to, like, getting AI agents to be able to do everything is to, like, find all the data in the world and, like, feed it to them in a really high-quality way, there's so many people I know that are finding, like, going out in the world and finding, like, extremely niche or just, like, data that no one would think of, and then, like, you know, making it, you know, like, high-quality servable to labs or anyone that wants to buy that data. So like, there's one, for example, that's, like, basically instrumenting a medical clinic. So like, every conversation is recorded, every, you know, thing that they're doing is video recorded, they're like, you know, almost doing, like, a, yeah, like, like, you know, putting telemetry throughout every portion of a medical clinic, and then, like,

• 47:40Everett Randle?

  making that a data set. And so I feel like, like, again, like, is that venture scalable trillion dollar? Probably not doing it if you're, like, just like the medical clinic data company.

• 47:49John Coogan?

  Yeah.

• 47:50Everett Randle?

  But I think there's gonna be a lot of, like, entrepreneurial people that make a lot of money just bootstrapping these things and building them to, you know, 50 to 100 million dollar revenue businesses for, like, eight to 10 years.

• 48:00John Coogan?

  Yeah.

• 48:01Everett Randle?

  And like, that's, that's sort of all you need to do.

• 48:02John Coogan?

  Yeah, it's exciting for, like, entrepreneurship broadly. Like, it's just, it's just an exciting time to be building. Well, thank you so much for taking the time to come chat with us. Have a great rest of your day, have a great weekend, and we'll talk to you soon.

• 48:13Everett Randle?

  Thanks, guys.

• 48:14John Coogan?

  Goodbye. Let me tell you about public.com, investing for those that take it seriously. They got stocks, options, bonds, crypto, treasuries, and more with great customer service. Our next guest is TBN Royalty. We got Eric Lyman from Ramp, he's the co-founder and now the co-CEO. He's in the waiting room, and we'll bring him in to the TBN Ultra Dome. First time we've talked to him since he's become co-CEO. How is it? How does it feel?

• 48:40Eric Glyman?

  I feel so good to be back. I missed you guys.

• 48:43John Coogan?

  I missed you too. First time chatting with Tyler directly. I think he's popped in a few times. You've chatted with us in every different permutation, the yellow suits, in person, in the New York Stock Exchange, all over the place. But how are you settling in into the new title, co-CEO?

• 49:01Eric Glyman?

  It feels good. It's, what's been so fun, Kareem and I have worked basically this way together for 15 years.

• 49:09John Coogan?

  Yeah, I was about to say, everyone's, like, trying to do, like, hot takes around it. I'm like, have you actually met these guys? They've been co-CEO the entire journey, even going back before Ramp.

• 49:19Eric Glyman?

  It's, it's been fun. Like, I, like, for me, like, part of what makes this fun is, like, for, we've known for years, like, Kareem is the secret weapon of the company. Like, he's driving so much of what's going on now, it's, like, more obvious to people of, like, we got at least two of us, there's, there's actually way more interested people at the company. But no, we're, it's, we're moving fast, growing faster this year, and it's just fun. You know, now it's, he can swap and take some, some events off my hands too, which is great.

• 49:51John Coogan?

  Yeah, I love it. Well, businesses on Ramp are moving tokens fast through their systems, it's showing up in their books. You built a website, token-spend.fm. I love the dot FM. I think that's a very fun TLD. But what inspired this? I imagine it was from, like, direct conversations with your customers? Did this come internal? What were the findings? What were the goals of the project?

• 50:17Eric Glyman?

  You nailed it. Like, over the last year, the last four months alone, Ramp customer spend on tokens has grown by 21x.

• 50:28John Coogan?

  Wow.

• 50:29Eric Glyman?

  21x.

• 50:30John Coogan?

  Is that a gong, or is that a wah wah? It's a little bit of both.

• 50:35Eric Glyman?

  It's some of every, it depends who's making the money or spending the money. And look, by the way, like, the crazy part is, it's not like people are like, turn it off. It's like, no, I actually want to spend more on the right things. And so, like, you know, so we saw this from our customers, we saw this from ourselves. You know, a few years ago, AI spend was a routing error, like, error to, I think in May, it hit almost 10% of our payroll spend. The equivalent was on tokens on payroll. And, look, there's great things you can say about it. We're launching products faster than ever. We're more efficient than ever. We're growing faster and yet, you know, you, I hate to say it, there are people at the company who like use Fable to like look up the weather.

• 51:20John Coogan?

  That happened years ago. We heard about that at other companies.

• 51:24Eric Glyman?

  No, I'm teasing, I'm teasing. But, no, it's a, there's this whole thing where people know and get in the abstract of models even from a year ago were amazing, are great at doing tasks, and we can be more efficient. Two accounting teams need to be able to monitor this. Like, it's, you know, I think of our CFO who would get a bill for hundreds of thousands of dollars, and then the work began of like, you need to allocate some to engineering, some to sales and marketing, some to, you name it. And so there's just so many products that weren't built by the labs. And so today's launch around token spend management is a place where

• 52:06Eric Glyman?

  any company, whether or not you tried Ramp, can, can, can link up your, your API keys, and then you're, you're good to go. And, you know, we're helping people, really within minutes, start cutting their spend by several percentage points. And so it's been a very fun launch.

• 52:22John Coogan?

  Yeah. What was the, what was the first sort of generative AI application at Ramp? Was that the GPT API for understanding receipt data?

• 52:34Eric Glyman?

  So this was actually, so that was our first ML model, for sure. But the generative use case, this, I think it was six months before ChatGPT came out, we hopped on GPT-3, and we started using this for, for Go Team.

• 52:51John Coogan?

  Yeah, classifying different receipts, putting things in the right expense category. Things that could be done deterministically, fuzzy logic could apply, but LLMs were uniquely suited. But at the time, that was a rounding error. Then you go forward to May, and you get a bill for $1.5 million in a single week. What's the actual process for, for untangling what's happening? Are you looking at prompts? Are you just going to Slack and saying, hey, you know, you were one of the top 10 drivers of token spend? Can you flesh out a little bit of what, what you got done this week, that type of thing? Like, what is the correct way for an organization to interrogate their spend,

• 53:34John Coogan?

  maybe qualitatively, after they're done with the quantitative side?

• 53:39Eric Glyman?

  So great. Most organizations that are even at a place to be thinking about this, they're using lots of tools, right? They're spending on OpenAI models, they're spending on Anthropic, they're using Gemini, they might be dabbling in open source, they're using Cursor. And so the first step is actually just seeing it. It's being able to link up your keys so you can understand and start to break up basic questions of like, what's happening today, not in a month, when you go get your bills. Connecting and tagging that, and that's something you can do out of the box through the product. We come back within minutes to help you understand it, and so you can start to go and see, okay, not just, this person normally spends $1,000 a month,

• 54:23Eric Glyman?

  but they've already ran through $800 in an hour. And so you can set up notifications, we show you unusual spikes. And so, again, think back to the early days of Ramp and corporate cards. A lot of this was alerting and visibility. It's these types of insights, and you also see things like, you know, we know how the, the most efficient companies are running. And so if you aren't caching, you are overspending. Some people will leave fast mode on, which can be multiple times more expensive. And so we'll just highlight that for you.

• 54:54John Coogan?

  Sure.

• 54:55Eric Glyman?

  And then finally, at the end, you get to controlling it, you know, acting on it. And, you know, I think for today, there's so much to do on the analytics itself. But I do think there's more sophisticated opportunities to be had, whether that's in, in small model training, in routing, and much more. And, and we're excited at the whole space. I, I think there's so much to do to help companies save.

• 55:18John Coogan?

  Okay. Sure.

• 55:20Speaker 01

  Yeah, so I see the average company, 59% of their token spend is on frontier models. How do you, how should companies be thinking about allocating between frontier models and open source? Is it almost a thing where like, you're in an explore phase, using the frontier models, you're, you're doing these kind of net new coding tasks, whatever? And then once you find this repetitive thing, you're, you're running the same process every day, every week? Is that when you, when you allocate it towards open source? Maybe you're even doing a fine tune. How should people be thinking about that kind of stuff?

• 55:49Eric Glyman?

  It's a perfect question, and I, I think for companies out there, if you're listening and like, haven't used these models, like, I, I, I would say using frontier models just to get a feel is good. It is surprising the capabilities that models have. And, you know, if you, if you don't have a multi-thousand-dollar-a-month build, like, to start there, I think is, is reasonable. But then you start getting into optimization, and there's two, there are a few sets of interesting questions. One, there are cases when using frontier models can in fact be cheaper. Like, for example, in our own benchmarks, on our software engineering benchmark, people think of Sonnet as an older model in, let's say, the Anthropic world. And it is cheaper per call, but it needs to think a lot harder

• 56:34Eric Glyman?

  and call more agents working in collaboration. And, and actually, the smarter models, like, it's kind of like you met someone smart, like, they don't need to go and do like, long division, they can just like do division in their head. There are cases where using frontier models, Scott Woo, calling Scott Woo is much faster. His hourly rate is much higher, but there might be certain things. You know, Scott Woo per second might be cheaper than, you know, hiring a team of third graders.

• 57:04John Coogan?

  I'm like, I want one Scott Woo instead of a thousand midwits.

• 57:07Eric Glyman?

  This is right. So, so, so that's part one. But then, the, the really interesting part is, when you get down into benchmarking of what is the nature of work that you're doing, you know, you can use these, you know, trillion parameter models to answer really tough questions. But when you start seeing very high production use cases, you'll see, you know, if you know all of the input tokens you're getting are around customer service, you know, you'll see companies like Sierra having their own small models around what makes great efficient. And so they've lobotomied, you know, just the part of the brain that is really useful for those types of services.

• 57:50Eric Glyman?

  Two, if you can dynamically start to route based on the complexity of the task, you can say, a small model just for accounting, it maybe is all we need. We don't need to go ask, you know, a model that can allow us to cure cancer and, and do quantum physics and that kind of a thing. And so, in some sense, it's on both, and you start to get really interesting answers the more that you can benchmark your own business, and the more that you have high fidelity about the nature of the inputs you're getting, the outputs you're seeing, and then the efficacy per cent on getting to that. And there's so much to build around this area.

• 58:31John Coogan?

  Talk a little bit about the shape of AI product development, the AI work you're doing, Ramp Labs, sort of the surface area, the spikes there. Because there's, there's, you know, just using AI to improve the product that is deterministic, write better software, then there's also AI integrations, like, I mean, it's such an anodyne feature, but I love the fact that you can open up the Ramp app and just ask a model, like, how much did we spend on camera equipment last month? And it'll just tell me, and that's amazing. And I'm sure I could like wire it up to some other system, but like, I love just having it there. And then there's also like AI research and harness development, all sorts of work that's happening there.

• 59:12John Coogan?

  And that's, can be expensive, but how are you thinking about all the different trade-offs and all the different work within the AI slash Labs umbrella?

• 59:24Eric Glyman?

  So on using this, I mean, this is just an incredible technology, as you know. Like, I think about like, part of what, like, let's talk about like B2B SaaS for a second. You know, if we must.

• 59:35John Coogan?

  Yes, please.

• 59:37Eric Glyman?

  You know, come on.

• 59:38John Coogan?

  I was waiting. I was waiting to.

• 59:40Eric Glyman?

  Yeah, we're finally doing it, you know, boys. All right, so the problem with most B2B SaaS is awful is companies are complicated and people want different things. And so the accounts payables clerk wants a view, your accountant wants a view, the CFO wants a different view, one person wants a button, you want to make it simpler for these people, more advanced for another, and how do you deal with this? Well, turns out generative interfaces, where based off of who you are, how you're using your product, it can show you the interfaces you need with the views, the graphs that you like to do your work, can be intuitive. And so it's very interesting in making products

• 1:00:20Eric Glyman?

  that are very powerful, but feel simple and relevant for the products. And so on one side of it, like, forget Ramp, I just think organizations in spending time around dynamic and generative interfaces, there's, I think you can just make better computers, you can make better tools for people. Why do we care as a provider of services?

• 1:00:46Eric Glyman?

  What is so different structurally about spend on models and on tokens and on software is you could just hammer Salesforce all day, you're not going to get like a bigger bill from Salesforce. Sorry, go on, Cream's calling, I'll call back.

• 1:01:05John Coogan?

  Confident man.

• 1:01:06Eric Glyman?

  Yeah, you're on, I'll save it for a minute. But to go a bit deeper on it, if you start going and using, as folks know, in the token maxing era, lots of tokens, like, your bill can go from a thousand to 10,000, 100,000, to a million dollars, like, very quickly if you start going. And it's not like payroll spend that companies are able to manage in some way. It's not like normal vendor spend. In some sense, it's like an untapped corporate card that you can spend as you go. And by the way, the meter's not running. And you don't see it. And this starts to feel a lot like what we've obsessed over for years of

• 1:01:50Eric Glyman?

  can you help people manage every incremental dollar far better? And so it's pulled us deep into answering the question of if you want to know return on investment, we should be thinking about like, what is return? What did you buy? Can you understand just the semantics of it? So what was the output to the efficiency as, there's more types. So it is, we're obsessing over this from every floor of the building.

• 1:02:14John Coogan?

  One of the, one of the interesting things about Ramp is, you know, everyone who has Ramp card in an organization has, you know, they can open up and see all their transactions, they can see their budgets, their limits, the policy that applies to them. And they, you know, they can implicitly understand that, you know, if they spent $10,000 on their card or $1,000, like, did they deliver that much value to the organization? And I'm wondering if you see either Ramp or just generally, businesses need to push more of that data to the end user, the token consumer, and how will that instantiate?

• 1:02:52Eric Glyman?

  I'll give you an example from like, the just card world. And we're seeing this already in AI spend measurement. So in the card world, there's this concept of just like out of policy spending. Like, let's say that you, let's say you never got a notice, and you spend on Uber Eats because you forgot to switch over the card on the weekend. You might keep running it up and never really realize it. And it turns out if you just tell people once, hey, that was out of policy, you see spend, an out of policy spend just drop. You tell people, like, you weren't supposed to do that. They don't do that. And, you know, people actually want to be good and do the right thing.

• 1:03:29John Coogan?

  And this is the checking the weather with Fable 5.

• 1:03:33Eric Glyman?

  Yeah, it's like, I didn't realize I spent $100 to check weather. And, you know, sometimes some subtle UI like this and feedback goes a long way. And so in the product we've already seen, actually just exposing people, here's your AI spend, like John Tyler, I don't know if you guys know what you spent on token spends yesterday, but on Ramp, you can know. And it turns out when you see it, you start getting more efficient. And so even just the act of exposing it to you is driving down these savings for people. See, you nailed it. There's so much there.

• 1:04:11John Coogan?

  Yeah. We probably spent a lot on tokens yesterday. We were vibe coded a bunch of really, really jokey sites that provided a lot of laughs and a belly laugh. We had Sagar and Jetty on the show, who does not like prediction markets, and we built him an entire prediction market for his entire life. And the belly laugh that he got from that was priceless. It was all play money. But I think it was worth it, but I actually haven't seen the token bill, so I don't know. It might have been, it might have been rough.

• 1:04:43John Coogan?

  I want to talk, do you have another couple of minutes?

• 1:04:45Eric Glyman?

  Of course.

• 1:04:46John Coogan?

  Okay, I guess the last question for me. The Ramp Econ Lab, that is a separate lab. I'm very interested in the knock on benefits of Arakarazian's excellent work studying the economic impacts all over. I mean, the research has gone to the front page of the Financial Times, the Wall Street Journal, so many other places. What has that unlocked for you as CEO in conversations with customers? What have been like the knock on effects of that that project?

• 1:05:16Eric Glyman?

  At first, it's just, you can kind of just understand the world better. It's very obvious in AI, it's been this, I guess to paraphrase Elon, like a supersonic tsunami, where it's gone from didn't really exist years ago to perhaps 1% of the United States' GDP in the next 12 months. Like, it looks quite likely at this point. And this data's going so fast, like, you look at most economic indicators, and you get things a quarter later, it's not measured precisely, whereas Ramp data, you know, we're tracking about 1% of all corporate spend in the United States, and you can just see it, and you can understand it. And you can adjust your strategies faster. So I think it actually helps people better

• 1:05:59Eric Glyman?

  run their business and not get left behind. So I just find it useful for finance teams and technologists, people building businesses. Beyond it, it's just grown awareness. You know, we're competing against some of the best known brands ever created. And, you know, if we're going and trying to win you over and say, you know, try our tools, you should trust us to move money, store money, help you get more from every dollar an hour, and you've never heard of us, it's just a much harder sell to, oh yeah, I saw Ramp in the Journal on TVPN, you know, on the Founder's Podcast, or, you know, more and

• 1:06:41Eric Glyman?

  more, it starts unlocking it. And when it shows up in a way where it's actually already providing value to you before we have a conversation, it's, you can get deeper much faster. And, you know, I think over the long run, that that leads to more growth.

• 1:06:56John Coogan?

  That makes a lot of sense. Well, thank you for taking the time to come chat with us. Congrats on the launch of the website.

• 1:07:01Eric Glyman?

  Thanks, Sean.

• 1:07:02John Coogan?

  Token-spend.fm. Go check it out. Optimize your token spend today with Ramp's latest project. Have a great rest of your Thursday. Have a great weekend. We'll talk to you soon. Goodbye. Let me tell you about Figma. Agents, meet the canvas. Your AI agents can now create and modify your Figma files with Design System Context. We have a couple interesting op-eds I want to take a cruise through in the Wall Street Journal. The bear case for Malibu. This is interesting. For decades, this 21-mile stretch of coastline served as one of America's most durable expressions of wealth, offering residents ocean views, private beach access,

• 1:07:43John Coogan?

  and the opportunity to spend large portions of the day on Pacific Coast Highway. That proposition is beginning to face scrutiny. Rising insurance costs, wildfire exposure, limited restaurant options, and the difficulty of completing basic errands have weakened the case for full-time residents, according to property advisors who are familiar with the West Side. Quote, "You are paying $18 million to live somewhere that makes buying toothpaste feel like regional travel," said Graham Pelt, a partner at Royal Property Research. "Several homeowners have recently shifted their primary residences to Brentwood, Montecito, and Pasadena, retaining Malibu properties for occasional use. The beach remains attractive, but the emerging bear case is that visiting it may be sufficient."

• 1:08:27Eric Glyman?

  Interesting.

• 1:08:28John Coogan?

  Interesting. This is, this is the wrong, I feel like this is the wrong day for Jordy to step away from the show, because this is a, this is not good news. I feel like he would, if he were here, he would be defending Malibu, but fortunately, he's not. I have another.

• 1:08:41Eric Glyman?

  I guess we just can't really.

• 1:08:43John Coogan?

  We'll never know.

• 1:08:43Eric Glyman?

  I think I mostly agree with what I'm reading.

• 1:08:45John Coogan?

  Yeah, yeah, it's made some good points. There's another, there's another interesting op-ed. This one's in the Financial Times. They're calling it the end of Bottega Veneta. Bottega Veneta's position is the preferred label of consumers seeking to display wealth without displaying a logo showing signs of strain. The Italian fashion house's woven leather bags, oversized footwear and muted branding help define the quiet luxury era, but their growing visibility has made the products less useful as signals of discretion. Quote, "The customer bought Bottega because only certain people recognize it," said Isabel Marchand, an analyst at Mode Capital. "The problem is that now everybody recognizes it." That's not good. Stylists say some younger shoppers are moving towards vintage accessories, smaller Japanese labels and tapout T-shirts. Familiar with those.

• 1:09:30John Coogan?

  "Whose providence cannot be immediately identified from across a restaurant. Bottega remains a significant luxury business, but its cultural difficulty is that the absence of a logo has effectively become one." Interesting. I feel like Jordy would push back on that, too, but there's one more we should go through. Apparently, the G-Wagon is losing its grip. The Mercedes-Benz G-Class, long the default vehicle of musicians, professional athletes and men who describe routine commercial activity as motion, is losing ground among a small influential group of tastemakers. In recent polling, future Jacob Elordi and Gunna each identified the 2014 Jeep Grand Cherokee as the emerging vehicle of choice.

• 1:10:11Speaker 01

  Yeah, I've been hearing this.

• 1:10:12John Coogan?

  Yeah, yeah, it is on the come up, citing its restrained styling, limited social media exposure and availability with a factory-installed CD player. That's a nice feature. Quote, "The G-Wagon communicates the owner has money," said one person briefed on the survey. The Grand Cherokee communicates that the owner has somewhere to be. That's a good point. Dealers have reported increased interest in low-mileage examples with dark paint, tinted windows and minimal modifications. Mercedes remains dominant on conventional luxury buyers, but among chads with motion, according to the study, the status hierarchy is shifting. Authenticity now requires cloth seats, a loose headliner and at least one dashboard warning light.

• 1:10:52Speaker 01

  Yeah, and I think we found this this graph of different tastes in cars, how they've moved.

• 1:10:56John Coogan?

  Yes. Can we pull this up? How overall taste in cars has shifted from 2025 to 2026? Looks a little bit like polling numbers, and we'll see. The Mercedes G-Wagon has dropped from 95% approval to just 45%. Meanwhile, the Jeep, the 2014 Jeep Grand Cherokee here has jumped from 33% to 97%.

• 1:11:19Speaker 01

  Yeah, I mean, certainly among my friends, I think the 2014 Jeep Grand Cherokee has almost become kind of like the aspirational car.

• 1:11:24John Coogan?

  Sure.

• 1:11:25Speaker 01

  This is like, you really know you've kind of made it once you're running with in one of these.

• 1:11:28John Coogan?

  Yes, yes. Other, other big movers, the Nissan Murano Cabrio, of course, went from 65% to 83%. The Dodge Challenger Hellcat Scat Pack is moved from 45% to 74%, eclipsing the G-Wagon as the must-have vehicle. And the 2016 Honda Accord, a strong showing, going from 22% to 54%.

• 1:11:50Speaker 01

  Yeah, I mean, over the course of a single year, that's, that's a pretty big jump.

• 1:11:52John Coogan?

  Yeah, it seems like if you, if you, if you got a G-Wagon, you could get a 2014 Jeep Grand Cherokee and a Honda Accord from 2016, potentially. That might be the move. Well, we'll keep following the story and we'll see what Jordy has to say about all of this in the future, when he's back in the TV Pin Ultra Down. We had to take a shot at him. We had to have fun. No, of course, we're, we're joking around with Jordy. Let's go back to the timeline because there are some.

• 1:12:19Speaker 01

  We're going to talk about the DoorDash CLI.

• 1:12:22John Coogan?

  Yes, DoorDash launched a CLI, which.

• 1:12:25Speaker 01

  People have been asking for this.

• 1:12:26John Coogan?

  Have they? Have they been? DoorDash, I mean, it, there's that funny meme of like, robot, push the order food button. This makes it like one step easier. Are they imagining that people are locked in terminals, vibe coding, and that they will want the DoorDash CLI to order them food? Or are they expecting developers to build whole applications on top of DoorDash?

• 1:12:50Speaker 01

  So, yeah, I mean, I think the idea is mostly that you'll have coding agents use the CLI to then order. So presumably, you're super locked in. You know, you've had your Codex School running for six hours. It's going to, it's going to ping something.

• 1:13:03John Coogan?

  Is this bad news for MCP? Like, because they have an API. They have just a web front end that a computer use agent can go and use.

• 1:13:13Speaker 01

  Sure.

• 1:13:14John Coogan?

  I wonder why the move to CLI, maybe it's faster, maybe more token efficient. People are trying to be efficient. A CLI means you can drop DoorDash into whatever you already run, wired into your internal tools and Office Catering orders itself. I could imagine Office Catering, if you're starting to build or vibe code sort of like a, an ERP for your office organizing, you could potentially do that. But, I mean, DoorDash shared orders in an office is pretty seamless. Usually, someone who's like quarterbacking the order would just drop a link in Slack. Everyone picks what they want in the DoorDash app. It's all linked together and paid.

• 1:13:52Speaker 01

  I mean, I think it's just one of those like last mile problems where you've automated so much, but you still have to manually do the DoorDash order. Might as well just.

• 1:13:58John Coogan?

  People are having fun with it. Lawrence Jang says, "My biggest fantasy is becoming a reality." Jarvis, order $57 worth of Shake Shack on DoorDash, no tip. That's a lot of, that's a lot of Shake Shack. That's potentially too much.

• 1:14:13Speaker 01

  It's actually not that much. Shake Shack is actually pretty expensive.

• 1:14:15John Coogan?

  Yeah. $54, $57.

• 1:14:18Speaker 01

  Sure, maybe for.

• 1:14:19John Coogan?

  That's got to be like two huge burgers and something like that.

• 1:14:22Speaker 01

  That's true, that's true.

• 1:14:23John Coogan?

  Well, Mod Retro CEO Torin was interviewed by Take Him, and Dylan Abriscado and her team shared his favorite moment from the interview. Tay's Take says, "I'm extremely bullish on Mod Retro. They have Steve Jobs-like product taste that will serve them well beyond retro video game consoles." That's interesting. What would they do outside of retro video game consoles? Something new, something to compete with the Xbox. "Jobs' original DNA was combining beautifully designed, high-quality products with a simplified, friendly customer experience. After using the chromatic, I believe, Mod Retro can deliver that type of premium user experience with less frustration and fewer data privacy issues.

• 1:15:05John Coogan?

  I wouldn't be surprised to see them expand into televisions, headphones and other high-volume consumer electronics. Maybe a dumb TV, which Palmer was talking about when he came on the show. He's sick of smart TVs and their advertisements and signups and all QR codes and all that."

• 1:15:20Speaker 01

  A mod-like device, music.

• 1:15:23John Coogan?

  I'm very interested in, do you think the M64 will be somewhat hackable in the sense that you could get a sort of a dummy cartridge and then you could potentially vibe code a ROM that loads onto the Mod Retro, gives you the full experience of the controllers? Because we've been building a lot of web-based games and WebGL.

• 1:15:44Speaker 01

  Yeah.

• 1:15:45John Coogan?

  And those are fun, but it just doesn't feel the same when you're on, you know, a MacBook keyboard that's not really, you know, mechanical keyboard. You don't have a mouse, you don't have a controller. I bet, I mean, I imagine with, it's also pretty easy to wire up an Xbox controller as an input to a web-based game.

• 1:16:01Speaker 01

  Yeah, yeah, I mean, you can just connect Bluetooth. It's like.

• 1:16:03John Coogan?

  Yeah, but there's something, there's something magical about the original sticks of the N64.

• 1:16:09Speaker 01

  Yeah.

• 1:16:10John Coogan?

  And actually seeing it, like the constraints actually breed the innovation. You can create some mashup between Mario Kart and GoldenEye or whatever you want pretty easily with vibe coding. It'll be interesting to see where the hackers take it, how moddable the Mod Retro is. Anyway, we have our next guest in the waiting room. Let me tell you about Cisco first. Critical infrastructure for the AI era. Unlock seamless real-time experiences and new value with Cisco. And we have Jordan Black from Senra Systems. He's the co-founder and CEO with a huge funding announcement. How are you doing? Welcome to the show.

• 1:16:46Speaker 04

  Doing great. Thanks for having me.

• 1:16:47John Coogan?

  Long overdue. I mean, I heard about this company because you've been working with Founders Fund for a while, right? But take me through a little bit of the history, introduce yourself and the company.

• 1:16:57Speaker 04

  Absolutely. Jordan Black, CEO, co-founder, started this company over three years ago, right on my apartment, building wire harnesses on my carpet floor.

• 1:17:05John Coogan?

  Yeah.

• 1:17:07Speaker 04

  Founders Fund, been a great investor in us since the pre-seed, all the way to Series B, which you just did.

• 1:17:14John Coogan?

  How much was the Series B? Tyler's going to hit the gong.

• 1:17:17Speaker 04

  Let's go.

• 1:17:18John Coogan?

  How much did you raise?

• 1:17:19Speaker 04

  $65 million.

• 1:17:27John Coogan?

  Okay, so, uh, explain like I'm five, the, the, the, the product, the customer base, what's fueled the growth, what's, uh, what's in the supply chain, what do you, what, what, what's your key value add?

• 1:17:41Speaker 04

  Perfect. I brought some props on the show, but

• 1:17:44John Coogan?

  Fantastic.

• 1:17:45Speaker 04

  Senra is solving the wire harness problem, uh, in the US for aerospace defense. And you probably wonder where the wire harness is or anyone watching this. And this is what it is. It's just like a bundle of wires, connectors, cables, think of it like your iPhone charger, but a lot more complex. And this whole thing I'm holding in my hands is designed in Excel spreadsheets and PowerPoint slides, and it's all done by hand today as well, by a really skilled workforce putting this together. And think of it like a cheesecake factory, but trying to scale it. It's really complex and there's no culinary schools that exist and no recipes and you're just gotta figure it out and make it happen too.

• 1:18:25John Coogan?

  How on earth are people designing these in PowerPoint?

• 1:18:30John Coogan?

  That seems like a crime. Like, is it, they're drawing out little diagrams on, on PowerPoint slides with like the, the, the draw line tool?

• 1:18:40Speaker 04

  They use that. They use Microsoft Paint Visio is a big one people design things on. This is anything from the large aerospace defense companies to startups too, but it's, it's the, the input into wire harnessing is not sanitized. The output of who builds this, how you build it, what's the right way to build it, it's not sanitized. And like Senra is solving this hundred sixty-five billion dollar market, uh, by being the ones that says like, the bullshit's over and we're just going to take over and sanitize the entire thing.

• 1:19:09John Coogan?

  So why not a pure software solution, like just wire harnessing, SaaS? There are big companies that have been grappling with vertical integration, the Anduril, SpaceX. Like, I imagine that you could sell this as a SaaS product, but why, why work on the actual production?

• 1:19:29Speaker 04

  That's where the problem is. I, we started the company even with the design tool and we got some traction with that too.

• 1:19:35John Coogan?

  Okay.

• 1:19:36Speaker 04

  And in the day, every company just wants the wire harness and they want to come faster than normally is. They want to plug in and work. Uh, and it's the quality, it's the speed, it's the cost, but they care about the physical product. And I think if you want to make a generational company where it's like, where were we before Google Maps, you know, came out, it's like, we're, how are we building harnesses in the US today? It's like, we're with Senra ten years ago and that's kind of what the goal we want to have. Um, but it takes the problem, we have to vertically integrate the entire thing.

• 1:20:04John Coogan?

  And what, what's driving the customers to Senra? Is it, uh, speed because you're local? Is it forward deployed, uh, engineers that you've sent into organizations to sort of co-design wire harnesses before you make them? Is it the made in America or price or speed? Like, what, what, what are the key factors that jump out?

• 1:20:25Speaker 04

  Yeah, I think just being better is not, is not how we're gonna win and how we're gonna win every time. But it's like, quality is our number one thing. Like, it's really hard to get a high quality harness because it's all done by hand. So you don't know it works until you plug it in, turn on the rocket, and the wires fit in the right spot or the wires aren't crossed and the whole thing blows up. Like, they just recall like a million cheap vehicles because like the wire harness is bad. But this is a really big problem just in any industry. So quality is our number one thing. Uh, and we're over ninety-nine percent first pass yield with all our customers. And like, you just, we'll never go out of style and this is why you keep coming back to us. Uh, the second is gonna be speed. It usually takes months to quote something, takes, you know, even over six months to even get a wire harness from a customer to our company today, where it's

• 1:21:10Speaker 04

  gonna be faster, uh, for the customers we're growing with. And the last one's like that forward deployed engineering portion of it. So we do everything prototype to production. So we will partner with the Neo Primes, the Primes, just any of these companies, say, let's be your engineering partner, let's be your expert and tell you how you should design this thing, how you should be thinking about it, and let's go build you the prototypes and let's go scale in the production sense of it. Like, we're not just your contract manufacturer. Like, here's the PowerPoint slide, go build it. It's like, here's the PowerPoint slide, let's go design this perfectly, build the prototypes perfectly, and then make this at least your problems in the long term too.

• 1:21:44John Coogan?

  What, what subcategories of electronics or, or, or products are actually growing their wire harness footprint? I'm thinking of like the smart fridge boom where there was a move to put a screen and a wifi router in every device in your kitchen. And it feels like that sort of peaked and maybe that's declining. Um, what are you seeing outside of the obvious automotive, space, defense categories that are sort of like sneakily interesting markets or maybe on a growth trajectory that you might not have expected unless you were on the ground in the industry?

• 1:22:21Speaker 04

  Yeah, that's a great question. Uh, I think it's, it's, it's maybe obvious, but like the data center, uh,

• 1:22:28John Coogan?

  Oh, sure.

• 1:22:29Speaker 04

  But what's really interesting, it's not just the wiring that goes in the data centers, but the surrounding, uh, infrastructure around it. It's like, we need more generators, we need more chargers, we need more HVAC equipment. So you're seeing a really big, uh, inflection point in that sector too. Uh, aerospace on just the actual commercial aerospace, like more satellites, you have obviously defense with everything growing into. Um, but anything that requires electricity. So now you're seeing all these new energy companies. So I think the one that's going to start taking off is gonna be like microreactors or nuclear reactors. Like, those are really difficult wire harnesses to build. And there's not a lot of people who know how to build that stuff as well. So as people, the new incumbents and the Westinghouses of the world start like, uh, scaling up, it's like,

• 1:23:14Speaker 04

  we're ready to be kind of part, a part of that journey as well too.

• 1:23:18John Coogan?

  What does your path to automation look like? Uh, how, how, like, uh, how did you make the first wire harness? How are you making one today? What does it look like in a decade?

• 1:23:32Speaker 04

  It's scaled from me building it in my apartment three years ago and just going to investors saying, look, I have revenue, I can build wire harnesses.

• 1:23:42John Coogan?

  So you like literally like ordered the parts on Amazon and like put it together, basically?

• 1:23:46Speaker 04

  I just put together carpet floor, I got, you know, this, this PO, let's, uh, revenue generating, uh, within the first few weeks. Um, I think the first year was, uh, got a really great team of like, because my background is from SpaceX, of like really skilled technicians who've been doing this for ten, twenty years and they were building harnesses. Now, probably over ninety percent of our workforce is people who we've trained to go build a harness in four weeks versus the number of years it takes to go build that. Uh, so I think that's like the inflection point now of like, how do you scale the unscalable? It's like, build a training program, build an operating system for them to go build these harnesses on, and then build as much, integrate as much semi-automation to the factory too. And then what's gonna happen the next like one to five year range is like,

• 1:24:31Speaker 04

  we have a dedicated team working on AI and robotics of like, talking to all the new companies, talking to the existing incumbents of like, we are ready to go bring in as much robotics and much automation into this factory. We're tracking all the data from the design input into telling technicians exactly how to do with work instructions to the physical automation data points of like, how are they doing things with their hands? Um, and the really goal, I think everyone from the technicians building it to the executive level suite is how do we automate this as much as possible? And I think that's the really exciting part, but we have a really good foundation of like, we're building this, we're collecting the data, we're working with our customers, we're seeing what their cost points are and trying to grow as much as possible.

• 1:25:11John Coogan?

  Uh, a couple of years ago, Daniel Gross wrote a blog post called AGI Bets, and I think the very first one was, uh, is copper underpriced, which I think was a very funny one. He was a hundred percent right. Copper has, uh, has risen in cost a lot. Do you think about raw material input costs as, uh, an important lever on your business? Do you hedge? Is this material? Or, uh, or are you able to pass it through to customers and not have it affect the core business?

• 1:25:42Speaker 04

  Uh, I think it's a little bit of both, but overall, it's like, we're buying this and we're, we're, we're not making the copper wire, we're not making the connectors, we assemble it. And that's kind of our, our point of, um,

• 1:25:53John Coogan?

  Yeah.

• 1:25:53Speaker 04

  value add. But I think the difference is because we're this engineering partner, we want to be a cost-effective supplier for these customers too. So we can go, we had actually our own software, um, that we built out in an AI tool that ended up like looking at the bomb or the bill of material costs and says, this is how much it should be. And then suggesting to the customer, you should go with X, Y, Z other component because it's cheaper, readily available, it'll work for your application. But nobody's telling them, this is how you should do it. And that's why I say it's so much like a cheesecake factory of like, why are we using this really exquisite beef when we can go maybe this over here, which like has the same flavor, or you can't even taste it once you put a thousand calories of cheese on it or something like that too. So, um, that's really, I think, the value add too. It's like, the price of copper is going up,

• 1:26:38Speaker 04

  nothing we can necessarily change in our control to do that besides having better suppliers and distributors we work with and working with our end customers of choosing the right products for them to.

• 1:26:47John Coogan?

  Where are you based and who are you hiring?

• 1:26:51Speaker 04

  We have two factories, one in Redondo Beach and then one in Cypress, California. And that's eight, we just opened that up. It's 82,000 square feet of manufacturing space. And we're hiring all across the board. We're hiring in operations, so technicians, engineers, industrial engineers as well, too. Manufacturing people just be on the ground floor, building the factory from the ground up. And really exciting is like, there's not a lot of greenfield factories that you say, this is how things should be built, this is how they should be done. This is, we're building the ship as we're driving it to. We're hiring people on the engineering side from the software perspective and automation of like, how do

• 1:27:31Speaker 04

  we go have a lever of making this more efficient and more automated in the future? And then we're also hiring us like business development and sales of like partnering with these customers and the program management side of like, you get to go fly these customers, see what the wire harness needs are, see what your product goes into and like really get integrated with their end, their end goals too.

• 1:27:52John Coogan?

  Very cool. Well, congratulations on the new round. Thank you for everything you're doing and thank you for coming on the show. Have a great Thursday.

• 1:27:59Speaker 04

  Thank you so much.

• 1:28:01John Coogan?

  Let me tell you about Railway. Railway is the all-in-one intelligent cloud provider. Use your favorite agent to deploy web, app service, databases and more. Well, Railway automatically takes care of scaling, monitoring and security. I'm very glad that the, that the dog bark or the, yeah, the bark made it through. Let me also tell you about Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds, online, in-store, on mobile, on social, on marketplaces, and now with AI agents. And without further ado, we have David Bazooka from Roblox. He's the founder and CEO. He's been on the show before. Welcome back, David. How are you doing?

• 1:28:37Speaker 05

  Hey, it is great to be here. Thank you.

• 1:28:40John Coogan?

  Thank you so much for taking the time to come chat with us. I'm very excited about Build. I'm very excited about a lot of other things going on in the Roblox world. But take us through the announcement today. It makes so much sense. I think a lot of people could have predicted this happening, but I'm very interested in the shape of the project and how you actually see it changing what Roblox is.

• 1:29:02Speaker 05

  Yeah, the shape is ambitious and at the same time, it goes all the way back to our roots. You know, 20 years ago, when we launched, we had this mission and vision of removing limits of gaming and having everyone be a creator. The notion of a UGC platform was new. It's interesting that 20 years ago, our first slogan was you make the game. And so, you know, time has an interesting way of going full circle. Fast forward to where we are right now. Roblox Studio has a bunch of models working to accelerate creation. We have the Studio Assistant. People are using it with MCP. And so we're gathering

• 1:29:45Speaker 05

  all of those models and bringing the Studio Assistant right to a tab in our mobile app, both for one-shot game creation and iterative gaming creation. It's really an elegant unification of what has traditionally been Roblox Studio, all the way to the, the mobile app tab as well.

• 1:30:03John Coogan?

  So right now, I've seen tons of models that are capable of designing incredible games when prompted appropriately in a variety of, of, of systems, but they're all sort of expensive right now. Some of them are subsidized on plans. But I think everyone's optimistic about the cost coming down by orders of magnitude very quickly. But how are you thinking about doing that dance right now of giving creators the most powerful AI and not putting too many limits on it, but setting yourself up for a really solid financial footprint over time as the product gets more popular?

• 1:30:44Speaker 05

  The, the, the hope is, you know, our well over 130 million DAUs, more and more of them can be creators. And I'll highlight that the economics aren't changing. You know, we expect more and more money to flow to our creator ecosystem as even part of this announcement. There's a, there's a neat thing underneath what people see on the user-facing side of Roblox, that we're a huge infrastructure company. We have data centers all around the world. We have bandwidth. We have CPU. We have inference. And we started this fortunately well over 10 years ago to keep costs down and performance high. A lot of the inference we run today, we run all on our own data centers. We optimize that in a way. The philosophy

• 1:31:29Speaker 05

  and the optimism of costs coming down goes straight to build in that, just as Roblox Studio was the way people made games 20 years ago, that's still going to be live. But we think as games get more complex, as they get multiplayer, as they have interesting economies, as we want to save the infrastructure, all of that running behind it, that promise comes back with people being able to prompt and create games. Our, our vision is that everyone will have access to this for a certain amount. We will initially have the ability to buy more token usage if you want. But the, the beautiful thing is this is eventually consistent. And as inference gets cheaper and cheaper and cheaper, just as some other things were

• 1:32:12Speaker 05

  expensive 20 years ago, we think more and more people are going to be able to use this more and more.

• 1:32:16John Coogan?

  How, as you reflect on the decision to build your own infrastructure, how bad would it be if you hadn't done that right now? Would, do you, do you, would you be feeling like a memory crunch? Would you be, are you feeling any of that? Like, what about what's going on in public cloud or the AI build out is well positioning you or, or maybe even affecting you?

• 1:32:42Speaker 05

  Yeah, I think we've said publicly before, the cost benefits of our infrastructure may be roughly 3X. Now, I don't, I don't want to quote that on inference and other things, but there's an enormous advantage to that and an enormous advantage of taking all that money, pushing it to creators rather than cloud providers. We, we are great partners with some of the cloud providers, especially in burst mode. There's a mathematical optimization where if we can run on our own infra most of the time and burst to cloud when we need to, that's kind of like the optimal cost structure. But, but, but I do think the vision is we want all 130 million of those creators and users to participate in making games.

• 1:33:26John Coogan?

  Take me through some of the other AI initiatives that are rolling out across Roblox right now. I was fascinated by the AI up-resing technology. I'd been very optimistic about that all over gaming. We've seen it, early signs of it with DLSS, but clearly this is next generation technology. What's the, what's the feedback been? What's the process like? How?

• 1:33:53Speaker 05

  I think there's a little bit of a fun boiled toad thing going on here. We're all used to what a game looks like. We've been all playing games for 10 or 20 years. We know what they look like and, and we have an expectation of what we look like. I don't think any of us have the expectation that a game should be photorealistic at 4K 60 hertz like a movie. Like, like that is something that's the province of movies right now, offline video models that create super high-res. And in our minds, we haven't disconnected, like, what could that be like? Our, our vision and our dream and our hope is multiplayer

• 1:34:36Speaker 05

  gaming at photorealism, 4K 60 hertz. And we believe the best strategy for this is not pure 3D, traditional gaming, not pure video world model, you know, action systems and all of that, but a hybrid system that is, is both optimizing the coordination of the thousand people in the multiplayer world with local super up-resing for each user. And so that's, you know, that's what we published a blog post on. It's why we're working on this super up-resing video model that we're going to incorporate. We showed some early demos, more demos to come, but, but we do believe it's almost going to be like going

• 1:35:17Speaker 05

  from black and white movies to color movies. No one has, we just aren't used to a purely photorealistic feeling game.

• 1:35:24John Coogan?

  So if the successful, that like the, the keys to success as a UGC game creator, sometimes it can be asset-driven. They can create something really high fidelity. Sometimes it can be, they are able to actually instantiate the game quickly. All of that's becoming easier with the two products you mentioned. What remains the secret sauce to a breakout UGC creator on Roblox?

• 1:35:54Speaker 05

  Yeah, I think it's, there's a couple of interesting factors here. The overarching thing, if we take a step back, that gaming provides us in society is really our belief, like, we think the world needs to be playing a little bit more, like, hanging out together, using their imagination, you know, it's how we've evolved as humans, and play is just a good thing. We think that as far as the creation of these experiences, we're going to see more and more interesting ways for people to play together. I feel it's a little bit like we've moved from oil painting to Photoshop. We're all going to get better at making digital assets and things like that, but there's

• 1:36:38Speaker 05

  going to be enormous room for creativity around what type of environments we play in. We're all going to feel more powerful creating those environments. We're going to have the same opportunities, I think, for many of the large teams on Roblox that are big studios now, but we will also have opportunities for first-time creators, just as sometimes first-time video producers get a breakout hit. I do think we're going to make that possible as well.

• 1:37:07Speaker 01

  Yeah, I'm curious how you're thinking about, you know, using AI not just to build the games, but also like within the games. So like, you know, I think everyone who's used these models has had this idea of like, oh, this would be an incredible NPC, right, in a game, you can talk to it, it has this incredible, you know, ability to respond to what you're doing. I'm curious how Roblox is thinking about, you know, using models within the game.

• 1:37:28Speaker 05

  I would say yes, yes, yes, yes, both NPC creation as well as dynamic world creation as well. You know, one can imagine a gaming world where like in the movie Inception, there is a dream master who can modify the whole world for other people in real time. That's a very complicated computational challenge, you know, folding the road over in that dream sequence in Inception. But dynamic world generation, I think we're going to see in real time, also NPCs, you know, both, not just doppelgangers and digital twins and every single sci-fi movie we've ever seen.

• 1:38:10Speaker 05

  There's another really interesting aspect for NPCs, and that is very hard, I think it's much harder in the gaming industry to figure out, is that thing going to work, or is it going to be interesting? We've seen so much success in code acceleration, because we can define it, we can write a test plan, we can do iterative loops, we can let it go all night and get better and better. A game is a lot more difficult to define what is good. I think we're going to see more and more NPCs used as testing agents. And the interesting thing about NPCs is rather than trying to write a test plan, like, let's put 100 random NPCs in a game, give them the same mission as a human, and see how they perform. The fun thing about really extrapolating to the future with a lot of compute and a

• 1:38:55Speaker 05

  lot of inference is those NPCs could conceivably run 100 times faster than humans. So it's feasible to imagine a 100-player test for 100 hours with NPCs being compressed down to an hour. That starts to introduce the notion of Wiggens loop programming for game creators initially with NPCs.

• 1:39:16John Coogan?

  You mentioned Inception, the whole team's nodding because they all just saw it in 70mm in theaters because it was re-released. They love that. What about Roblox the movie, or IP that is developed in Roblox going to the big screen? We saw Backrooms, a Blender project, very successful summer blockbuster. What's the future of that pipeline?

• 1:39:42Speaker 05

  We are looking into it. We've been really conservative because what we've always imagined, Roblox as a IP factory, where new IPs that are not coming from the movie angle are coming from the, you know, dress to impress and grow a garden angle. I just went and bought some dress to impress physical toys. So I think we're looking at how maybe in the future we would accelerate less of Roblox and more of those creators. It's fun to imagine a future where the brands of those creators supports properties. So I would say a lot of opportunity there.

• 1:40:18John Coogan?

  How is advertising developing in Roblox? It feels like AI unlocks, it just lowers the cost of actually doing a branded integration. Someone who's a non-technical marketer can potentially come to you and say, I want a physical instantiation of my store, I want to do some sort of stunt, and you can say, yeah, like, this will just be a couple tokens, it's going to be a couple hundred bucks.

• 1:40:43Speaker 05

  I think you're exactly right. What we're experimenting as well, even the descriptions of experiences, the thumbnails that creators make, all of that is starting to become AI and dynamically generated. I would also say as our discovery tool moments more and more starts to become front and center in the product, that's a much more advertising format a lot of young people are used to. Also, our on-platform advertising business, which is creators, in addition to using our recommendation algorithm boosting by buying advertising on our homepage, is going very well. And then, as you mentioned, we're seeing continued growth in both brand integration

• 1:41:28Speaker 05

  as well as video advertising as well.

• 1:41:31John Coogan?

  Sorry. It's very funny. How are you thinking about new platforms, new consoles, just the general strategy of the Roblox footprint? Are we past peak new platform, or is there, are there more surfaces that you want to expand on to?

• 1:42:00Speaker 05

  I know three surfaces right now. We're doing early experiments with Android TV, which is exactly the same Roblox client. Many experiences on Roblox that are not, you know, super high Twitch related are super interesting there. I think there's a huge opportunity to be on all TV platforms. Of course, we really respect Nintendo and Switch, continuing to talk with them. We do think Roblox should be on that device. And then, as we start to see all this collection of AR glasses and VR headsets starting to pop out, you know, we're going to see more and more maturation of what is kind of the

• 1:42:44Speaker 05

  standardized AR form factor, which is heads-up display overlaid on glasses, ultimately projection. That's a real interesting platform for 3D communication as well, so we're tracking that. And of course, we're big fans of Meta Quest and Roblox is live there, and a lot of people play in VR right now.

• 1:43:06John Coogan?

  Yeah, in general, the glasses format, I mean, there's been some exciting launches, Snap Spectacles and the Meta Ray-Ban displays, but it feels like we're in a little bit of like a AR/VR winter, in the sense of like, it's just wait for the next major iteration, we're just sort of in-between cycles. Is that what you feel?

• 1:43:27Speaker 05

  I think there's a huge AR glasses opportunity. Once we get speaker, microphone, camera, projection, lightweight, all working together, everyone's dancing around the edge of it. Arguably, the Google Glass from 10 years ago, I feel, was on the right track. What's the lightest wearable, everyday option? So I feel we may be in an AR winter, I'm not sure, but I'm very optimistic about that form factor.

• 1:43:58John Coogan?

  Yeah, yeah. It's, yeah, it's interesting. I'm such a VR bull, but at the same time, when I see just rumors about, oh, this next great display was canceled, or something like that, I'm not.

• 1:44:12Speaker 05

  Yeah, I mean, VR and AR are super different. I had the privilege of trying on a VPL data glove, literally, when Jaron Lanier ran the first, you know, VR system on SGIs, so I saw it super early. So I'm super optimistic about AR.

• 1:44:32John Coogan?

  What about, like, screenless experiences? I mean, there's a lot of, like, smart speakers and the Meta Ray-Bans that don't have the displays, have an AI that you can talk to, and I'm wondering, like, is there, is there any opportunity for a Roblox creator to create a game that, I mean, there are games on Amazon Alexa, and I'm wondering if there's any Roblox creator that could potentially create a game that doesn't require a screen, at least for part of the experience?

• 1:45:03Speaker 05

  I think the more Roblox is not thought of just as a game or a platform, but incredibly high-performance, low-cost infrastructure that's available to everyone. That infrastructure is both single-player and multiplayer, it's 2D and it's 3D, it can be on low-end devices and high-end, and as that infrastructure more and more incorporates NPCs and audio and those types of things, you can imagine crossover-type games that involve NPC interaction, jumping from those with a visual display to pure NPC interaction. So I would say we're, you know, very focused on providing high-quality, low-cost infrastructure

• 1:45:47Speaker 05

  throughout the platform, and I think also focused on where it makes sense from performance and privacy, whether it's our voice safety models, our text filter models, our super up sampler model that we've announced, NPC model, game creation coding model, scene gen model, single-part creation model. There's many of these where we feel we have the data to build world-class and kind of put it all together in our build harness.

• 1:46:18John Coogan?

  What is your, like, overarching philosophy on where certain pieces of the safety and KYC infrastructure should live? Because, I mean, I have kids, they're not playing games yet, but I imagine they will at some point. I'm probably going to have an opinion about the amount of screen time, I'm probably going to do some research on what the right amount is. Some of that can live at the device level, some of it can live at the application level, some of it can live just at the parenting paying attention level. How do you think about the different pieces of the puzzle, where identification lives, where screen time lives, where different filters live? Is this an important trade-off?

• 1:46:58Speaker 05

  This is a top, big discussion in DC, right? What responsibility do device manufacturers have? Do they have to tag the age of every device? I would roll back all the way to Roblox values. One of the four is we are responsible, and that value has led us to, in a way...

• 1:47:20Speaker 05

  Shutting off a phone call on my Apple Macintosh. Sorry about that. I hope you don't hear that. So that has led me to, um, sorry about that.

• 1:47:34Speaker 05

  Problem having integrated phone on your PC. That has led us to, um, taking responsibility and doing a few big moves. No, no sharing image or video, um, age checking now everyone on the platform. So both AI and biometric signals and really being unique in, in leading that charge. We ultimately will take every age signal we can get, whether DC mandates it from a device, whether we collect it and we, we just get higher and higher resolution. But we're not waiting for a law or for device manufacturers to do that. Like we're, we're, we're already done. Like we're already age checking everyone and using

• 1:48:19Speaker 05

  that to ban communication and, and monitor content. The other thing I, I would highlight is there's no silver bullet there in that even with device age check, so many parents are so busy that so many devices get handed around the, the household, just go take my phone, go take my tablet, that it, that we will have young people, we will have nine year olds on devices that are age checked for 18, that I, there is some reliable, um, reliability and constantly doing continuous age checking like we do.

• 1:48:54John Coogan?

  Yeah. I mean, the funniest example I can remember is, uh, there's this old Twitter exchange where, uh, presumably a young woman got, uh, banned from using Twitter by her parents. And so she logged into her Samsung SmartFridge and sent a tweet. It was like, I'm back online. And it just shows you like, kids are so ingenious, like they will get around things. So you have to have layers of protections at every level. And there's no, there's no one size fits all approach, which I think is your.

• 1:49:24Speaker 05

  That's exactly right.

• 1:49:25Speaker 01

  Yeah. I'm curious how you're thinking about safety, especially in regards to AI. I mean, every time a new frontier model comes out, you'll see someone within like an hour who's jailbroken. They have this crazy prompt and you can get the model to say all these like crazy stuff. Um, so I'm wondering how you're thinking about that, especially in terms of these, these like large language models.

• 1:49:41John Coogan?

  Like red teaming?

• 1:49:42Speaker 01

  Yeah.

• 1:49:43Speaker 05

  Yeah. I would say we're going further than that in that now for, um, everyone on our platform under 16 right now, they're, they have a huge corpus of content. It's called Kids and Select content. It's well over 20,000 games, but these are going through a fairly excruciating both user funnel as well as moderation funnel. And in a way it's working really wonderfully. That's an enormous amount of content. At the same time, it's not the full UGC catalog of millions and millions of things. Um, and because we have age check, we can push it there. The vision with build is we have the ability in build, um, that we don't fully have in studio where everything's being created by a prompt where

• 1:50:27Speaker 05

  we can see a history of all the prompts that have been used to create a game as well as, um, ultimately the images that have been uploaded, the models, all of those kinds of things to really make a similar determination on the quality of that content. Whereas when you use a wide open IDE, whether it's Roblox Studio or VS Code or whatever, you probably can make anything. And so we, we are optimistic. We will keep the same safety gauntlet for experiences created by build. We're, we're also really optimistic that because our discovery system is so unique to gaming, it's, it's very much based on estimated long-term retention,

• 1:51:10Speaker 05

  based on direct measurement, that our discovery team's pretty optimistic, even if there's 20 times more games being created, one could have the fear, oh my gosh, we're going to get a lot of AI slop. But you know, we already have millions of people making games. Some of them are amazing. They're not all amazing. They need to make it through, um, a high retention gauntlet before they start really being surfaced. So the, the beauty of this is we think our current discovery systems are already perfectly poised for the expansion of creation from build.

• 1:51:45John Coogan?

  Yeah. This is the aggregator thesis, the, you're already filtering everything and you're set up for it. Um, how are you thinking about, uh, intellectual property on Roblox in this where it gets even easier to make games and, and experiences? Um, there have been some artists and IP owners that have been more lean forward on, yeah, remix my songs or use my likeness. Uh, Sora had this weird cameo feature that I thought was pretty elegantly implemented where, uh, someone could go in and say, anyone like Jake Paul was like, anyone can make, can remix my image. I want to be all over the internet. Other people said, don't put me in any videos that you generate. Uh, and I'm wondering if there's,

• 1:52:26John Coogan?

  uh, like what the long-term relationship with different pieces of IP. Some filmmakers might want a bunch of free UGC games that promote their movie, uh, and some might not want any of their IP to leak into Roblox. How are you treating that?

• 1:52:41Speaker 05

  Yeah. So we, um, you know, that relationship between IP holders and current creators and game developers is really complicated. There's, there's multiple countries, there's Hollywood contracts, like, like, uh, how they, imagining a small one or two person shop, going and getting a license to some big IP is somewhat unfathomable. We, we do believe the future of this is just like Roblox solving it in a systems oriented way. We, we have a platform right now that is somewhat new called IP manager where we want, and we are running the gamut all the way from some pieces of IP, which, hey, we're open for licensing.

• 1:53:24Speaker 05

  We want multiple creators to come and use our IP. Um, the IP from the movie Saw is in our IP manager. And, and so a creator who's interested in using that IP can directly contact, you know, do an online contract and start producing something from that. But that, that IP manager can also act as an IP controller as well. And IP can go up there more. And the more that AI gets good at auto scanning and auto detecting can also be some companies that just say, no one anywhere should be using our IP. So I think we, we're

• 1:54:05Speaker 05

  viewing this as a systems opportunity. And just like the democratization of gaming, we want more creators making interesting games, democratization of the licensing process.

• 1:54:17John Coogan?

  Yeah. I mean, I've been really optimistic about AI solving this because I've watched firsthand how YouTube has dealt with it where, yeah, you put a song in, immediately the royalties just go over there. You don't make money, but that artist does. And most artists are fine with that. And then they always have the option to click that button and say, actually, I don't want that at all. And it's not perfect. Everyone has approvals at the right time, but it's like this stable equilibrium where I think everyone gets what's economically viable.

• 1:54:45Speaker 05

  I'm very optimistic. Like this will ultimately be a solved problem.

• 1:54:48John Coogan?

  Yeah. It's exciting. Well, congratulations on build. Congratulations on all the progress. Thank you so much for taking the time to come chat with us.

• 1:54:55Speaker 05

  July 28th, build goes into alpha. July 28th. Thank you.

• 1:55:01John Coogan?

  Thank you so much for coming on the show. Have a great Thursday. Have a great rest of your week. We'll talk to you soon.

• 1:55:05Speaker 01

  Good to see you.

• 1:55:06John Coogan?

  Goodbye. Let me tell you about MongoDB. What's the only thing faster than the AI market? Your business on MongoDB. Don't just build AI. Own the data platform that powers it. Um, uh, in creator world, there's some news from Colin Samir. Lexus is now the official car of Colin and Samir. What does that actually mean? They made four ads for them that roll across, the rollout across YouTube. They're sponsoring four videos on their channel. It's the first of its kind deal, uh, that represents broader shift taking place in media. The aperture of what it means for a brand to work with the creators changing quickly. It's very cool to see because obviously they've been on YouTube for a long time.

• 1:55:47John Coogan?

  They've done a lot of like host read ads, mid roll ads, but this is a much deeper integration and something that I think will be, uh, hopefully replicated all over YouTube and be a new source of revenue for, um, for creators of all kinds. So I was excited to see this. In other entertainment news, uh, Jake, uh, from Econ CM Pick, uh, Econom Pick, uh, says this is almost hard to believe. Disney spent $129 billion acquiring Marvel, Star Wars, Pixar, ESPN, and Fox, which is 182 billion in today's dollars. Throw in all their legacy

• 1:56:30John Coogan?

  assets and the entire company's market cap today is $169 billion.

• 1:56:34Speaker 01

  Wow.

• 1:56:36John Coogan?

  Do you know what this picture is missing?

• 1:56:39Speaker 01

  Uh, which, what do you mean?

• 1:56:41John Coogan?

  So, so they're saying they acquired all these assets and the company is only worth $169 billion. What's missing from this analysis?

• 1:56:50John Coogan?

  The cash that's been returned to shareholders. Disney across, uh, dividends and buybacks has returned like 70 billion, maybe more to shareholders, which is, I don't know. I just saw this and it is, it is, it is an interesting angle because they have spent a lot acquiring and the company is not worth more than what they acquired. So there's this question of like, were those, were those acquisitions accretive or destructive or dilutive? But, uh, there is a whole separate picture, which is that, uh, a lot of cash has been returned to shareholders throughout this journey.

• 1:57:22Speaker 01

  Yeah. Also, I mean, that's the mechanism with, with, with which those acquisitions were funded also.

• 1:57:27John Coogan?

  Yeah. Yeah. Matters a lot. I don't know. It was sort of interesting. Uh, Sean Frank has a pitch. He says you should move to New York City. Bro, you gotta move to NYC. The weather horrible, 100 degrees, easy. AC, F that. Taxes so high. Rent highest in the country. Air quality, some of the worst in America. Tech, bro, we banned. Do they really ban Waymo in New York?

• 1:57:49Speaker 01

  Uh, I believe so. Yeah. There's no Waymos.

• 1:57:52John Coogan?

  Wow. That's very wild. Uh, yeah. If you can make it here, you can make it anywhere. So I don't know. Do you ever have aspirations to move to New York City?

• 1:58:00Speaker 01

  Uh, at some point it seems.

• 1:58:02John Coogan?

  You've been to New York City?

• 1:58:03Speaker 01

  Yeah.

• 1:58:03John Coogan?

  It's a nice city. That's the thing is that all of this is true and it's still a great city to hang out in. It's so fun. It's so dense. You can see so many people walk around. It's beautiful. It's just like, I don't know. It's unlike anything else. Still great, but, uh, yeah.

• 1:58:16Speaker 01

  You've never lived in New York City?

• 1:58:17John Coogan?

  I've never lived in New York City, but I've spent like a lot of time there. So I've had a good time. Anyway, let me tell you about Codex. Codex is a powerful workspace for getting work done with AI agents, whether writing code, analyzing data, creating content or automating business workflows. Codex helps you move projects forward from start to finish. Um, and there's some, there, there's some other news in the timeline, but we can go over it more next, next week. Uh, Eli Lilly is buying psychedelics firm Atai Beckley for an initial $2.8 billion. Atai was founded by Christian Angermeyer. I've actually interviewed him years ago. Uh, fascinating deal, working on psychedelics and a bunch of other things. Therapeutics for mental health conditions, a huge deal going on there. And, uh, there's

• 1:59:00John Coogan?

  a few other stories, but we can get to them tomorrow. We're off tomorrow. There's some travel going on, but we'll be back Monday at 11 AM Pacific sharp. Thank you to everyone who tuned in in the chat. Thank you for, uh, positive reviews of Tyler. Let us know what you think of Tyler. Leave us a review on Apple Podcasts and Spotify. Write us an email. Uh, tell us how he did. I think he did fantastic.

• 1:59:22Speaker 01

  Have the best Thursday of your life.

• 1:59:24John Coogan?

  Yes. There you go. That's a good impression. That's a good impression. Um, but, uh, but thank you. Sign up for newsletter at tbpn.com and we will see you on Monday.

• 1:59:33Speaker 01

  See you.

• 1:59:34John Coogan?

  Goodbye.

• 1:59:36John Coogan?

  Oh, we got the flashbang. There we go.