TBPN - Tim Cook Retires, Mark Gurman Joins, Images 2.0 | Howie Liu, Scott Stevenson, Alex Wiltschko, Spiros Xanthos, Carolina Aguilar, Jake Jurewicz

Episode Date: April 21, 2026

(00:15) - Tim Cook Retires (19:43) - Howie Liu, co-founder and CEO of Airtable, discusses his journey from learning programming in high school to founding Etacts, which was acquired by Salesforce, and eventually establishing Airtable to democratize software creation. He emphasizes the importance of building a product that is significantly better than existing options, highlighting Airtable's evolution into a low-code platform that empowers users to create custom applications without coding. Liu also reflects on the company's growth, noting its valuation milestones and the strategic patience involved in developing Airtable over several years before its public launch. (47:50) - Mark Gurman, a prominent technology journalist known for his in-depth coverage of Apple, discusses the recent leadership transition at Apple, highlighting John Ternus's appointment as CEO following Tim Cook's decision to step down. He emphasizes Ternus's decisive leadership style, likened to Steve Jobs, and his focus on product innovation, including the development of new AI-powered devices and a significant revamp of the iPhone lineup. Gurman also notes that Ternus's promotion is expected to bring a sharper focus to Apple's product development, aiming to reinvigorate the company's innovation pipeline. (01:08:28) - Image 2 Reactions (01:17:50) - Scott Stevenson, co-founder and CEO of Spellbook, discusses the company's significant growth, highlighting that they have onboarded over 4,400 customers across 80 countries, making Spellbook the most widely used AI contract review tool globally. He attributes this rapid international adoption to strong inbound interest and emphasizes the product's multilingual capabilities, facilitated by AI models adept at handling various languages and supplemented with jurisdiction-specific legislation and norms. Stevenson also critiques the use of Contracted Annual Recurring Revenue (CARR) as a metric, pointing out how some companies inflate their ARR figures by reporting future, non-guaranteed revenues, and advocates for more transparent and grounded revenue reporting practices. (01:33:42) - Alex Wiltschko, founder and CEO of Osmo, is pioneering the integration of artificial intelligence with olfactory science to endow computers with a sense of smell. In the conversation, he discusses the complexities of digitizing scent, the development of Osmo's proprietary Olfactory Intelligence technology, and its applications in creating fragrances for brands. He also highlights the company's recent $70 million Series B funding aimed at scaling their AI-powered olfaction technology across various sectors. (01:47:04) - Spiros Xanthos, co-founder and CEO of Resolve AI, discusses how their AI agents assist in debugging and managing production systems, complementing coding agents that generate code. He highlights the importance of reliability for businesses like Coinbase, Salesforce, and MongoDB, emphasizing that Resolve AI serves as the first line of defense by detecting and resolving production issues to minimize customer impact. Xanthos also notes the company's rapid growth, attributing it to the significant demand for automating production operations and their focus on building a successful product. (01:54:11) - Carolina Aguilar, CEO and co-founder of Inbrain Neuroelectronics, discusses her company's development of graphene-based brain-computer interfaces aimed at restoring health by creating intelligent connections between the neural system and AI. She explains their focus on implantable systems to achieve precise neural interaction, highlighting three product verticals: a semi-chronic platform for tumor and epilepsy resection nearing commercialization, an implantable platform targeting Parkinson's disease, and a vagus nerve sensor for therapeutic applications across various organs. Aguilar also emphasizes the importance of integrating their technology into existing surgical workflows to facilitate adoption without the immediate need for advanced robotics. (01:59:22) - Jake Jurewicz, co-founder and CEO of Blue Energy, has over a decade of experience in the energy and construction sectors, holding degrees in Nuclear Science & Engineering and Physics from MIT. He discusses Blue Energy's recent $380 million funding aimed at building the world's first project-financeable nuclear power plant by prefabricating components in existing shipyards, thereby reducing construction costs and timelines. This approach leverages mature light water reactor technology and centralized manufacturing techniques from offshore industries to make nuclear power more economically competitive. Follow TBPN: https://TBPN.comhttps://x.com/tbpnhttps://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231https://podcasts.apple.com/us/podcast/technology-brothers/id1772360235https://www.youtube.com/@TBPNLive

Year watch TVPN. Oh, no. It's Tuesday. April 21st, 2026. We are live from the TBPN Ultral, the Temple of Technology, the Fortress of Finance, the Capital of Capital.

Massive, massive news. Tim Cook to step down at Apple. This broke yesterday. Germinator had the scoop, of course. He's coming on on the show later today, but it's on the cover of the Wall Street Journal today. Heavily predicted, often debated.

It's a time to reflect on Tim Cook's legacy and what's up next for John Turnus, the longtime insider. We just say incredibly well executed, incredibly smooth. They sort of telegraphed it. It wasn't a surprise. Yes. It was already fully priced in. Yes. I personally was hoping that the market would give Tim Cook a 21% salute.

Yes. Where when the news went out, it just immediately nukes 21%. Massive red candle. Let everyone know this is, we don't like this. We love him. It's a sign of respect. We'll miss him dearly. Of course, rebound immediately.

Yes. But I think that's something that the market collectively should try to do for. Yes. More symbolism in the candles, for sure. Chartology is really the key thing. A 21% so long. But of course, what is Apple at right now? Are they moving at all?

Down 3% today, 2.5% but up 3% over the last five days. Still nearly a $4 trillion company. They're doing buying and they're cooking. So let's go through a little bit of, the review of the news and some of the previous discussions that we've had around Tim Cook and John Ternis because we're going to be learning a lot more about John Ternus and he's probably going to do a lot more content, a lot more media, a lot more interviews, and we will be hearing from him at keynote events for probably over a decade, maybe two decades. We will see. So in January,

Bloomberg reporter Mark German, who's coming on the show later today, predicted that John Ternis would succeed Tim Cook as Apple's next CEO. Let's just pull up this, clip. Let's give some credit to the Germanator. He didn't predict it on our show first. I think he scooped it and posted it. I know, I know, but this was back in January. I dropped the clip. The crux of the argument was twofold. Ternus's relative youth among a pool of potential successors. He's 50. Everyone else in the Apple executive team, late 50s through their mid-60s, turning 66 this year in the case of Tim Cook. Your Apple's board, you like continuity, you like an insider, you like people who know what they're doing have been there for a while, they know where the bodies are buried.

Okay? These guys all have hundreds of millions of dollars, if not more. Pause. I love Mark German so much. He's the best. He's truly the best. And he's coming on in 40. 45 minutes.

But continue. Yeah, at 50 he's the only one who is, if let's say Tim Cook hangs out another three to five years, you're not going to point another CEO. who's 65, 70 years old, he's the only guy. Apple, they get vast majority of the revenue from hardware. He's the hardware guy. Have they screwed up any hardware since he's been in charge? No.

He's a steady hand. He knows what he's doing. He's really the only choice. There was this New York Times report a few weeks ago, basically saying that it could be Greg Joswiak, could be Eddie Q, could be Geregrin, could be Greg Federegi. It's for sure not going to be Craig. it's not going to be Deirdreau.

It's not going to be Eddie. It's not going to be Jaws. The only category that makes sense is an operations person because you look at the current CEO, Tim, obviously, comes out of the ops world. You look at the guy who would have been CEO if Tim Cook didn't stay so long. I'm not saying he shouldn't have stayed so long. He's done, obviously, a fantastic job for shareholders and the employees and what have you. Would have been Jeff Williams.

He was the COO. So Sabi Khan, he was named CEO a few months ago, but he's really been in that job for the last half a decade, I would say. So anyways, it'll be Ternus or Sabi or someone completely out of left field. I don't think this is imminent. So we'll see what ultimately happens, but all signs are turning towards Ternus. Everyone has an opinion that Ternus is going to be the next CEO fine. I've been shouting this from rooftops the last two years.

But no one has given evidence, like, what is this based on, right? Has there ever been a baton handoff? Is he getting more responsibility? Well, they have a big baton. You know what? You have white smoke coming out of the... Sure. Do they have a smoke? Very environment.

Do they have a big scoop? Maybe. Is that the end of the club? That's scary. You know, maybe out of the farce. Do they have a comically large baton? Like we have our scoop? Yeah.

Oh, Mark German, the scoopinator. He's a scoop dogged dog. Doggy dog, Scoop athlete, the scoop, the scoop is on fire. We're very excited to have Mark German joining in just 40 minutes. What a great run he's been on reporting this story. It's absolutely fascinating. So yesterday evening, Mark was the one with the scoop. Tim Cook will assume the role of Apple's executive chairman,

and John Turnus will take the reins of the company. Mark followed up with a scoop with internal memos from both Cook and Ternus announcing the transition. I don't. I mean, I understand, I don't know, maybe I don't understand what it's like to be 65, but I was always optimistic that the Warren Buffett, 65 to 95 would be the new trend and that people would just say, you know what, Tim Cook's healthy. He's going, he's going. Everything to date was a warm up. Yeah. It's time to go on the actual run. That's, I would, I mean, I totally understand. He's like, I got another, I got another tennis to me. I'm going to, I'm taking us to 40 trillion.

Yeah, I don't know. I mean, maybe Warren Buffett's in a different world because he's more of an investor, maybe doesn't need to travel as much, doesn't need to be in the arena, shaking hands, kissing babies, doing product launches, you know, being in D.C., getting wrangled into things. Like, Buffett can be more like hands off and just sort of read the news, review the financials and delegate. Step in with some liquidity. Yeah, yeah.

needed. Yeah, it's more, it's a, it's a more hands-off role. I don't know how, I mean, I imagine that the role of CEO of Apple is incredibly demanding, but I, I liked the idea of just, just locking in and being like, oh yeah, I'm 65. Everyone expects me to, everyone expects me to step down, but I got another 30 years in me. But, you know, he, he chose a different path and he is retiring or stepping into the executive chairman role. Ben Thompson published Tim Cook's impeccable timing, which eulogizes Cook's impressive accomplishments as the head of Apple. Ben Thompson kicks it off with an interesting thing.

He says, it's the nature of business that the eulogy for a chief executive doesn't happen when they die, but when they retire, or in the case of Apple CEO, Tim Cook, announced that they will step up to the role of executive chairman on September 1st. One morbid exception is when the CEO does die on the job

or quits because they're dying, but the truth of the matter is that they were, is that where any honest recounting of Cook's incredibly successful tenure as Apple's CEO, particularly from a financial perspective, has to begin with the numbers. And he says that the numbers are extraordinary. Cook became CEO of Apple on August 24th, 2011. And in the intervening 15 years, revenue has increased 303%. Profits surged 354%.

And the value of Apple has gone from a mere two years. 297 billion to over 4 trillion, a staggering 1,251% increase. And there was some chatter back and forth on the timeline over whether Tim Cook had simply put Apple on cruise control and lucked out as many big names in tech also saw 10 to 40x increases in their market caps. This is from Brandon Gorell's newsletter at tbPN.com. You can sign up today for free. But this interpretation ignores the fact that many of the biggest public tech companies in 1980 when Apple IPOed are no longer even close to the top of the pack anymore. And Brandon cites Xerox, Motorola, Texas Instruments, IBM, and HP, which all fell by the wayside over the past 30 years. Well, Apple built the biggest consumer hardware company on the planet and thrived in the public market. And I was doing some digging on this as well. I pulled up, you know, it's easy to look at like, well, zoom back to. the MAG 7, all of the MAG 7 have done fantastically well over the past 15 years during Tim Cook's tenure. Did he do anything special? Is he in a different category in some way? And maybe not

when you look at, when you look backwards from the current MAG 7, but if you go back to 2011 when Tim Cook took the reins and you look at what were the biggest tech companies there, then and how have they performed. It does look like outperformance because Apple was at 377 billion. That was, you know, big, huge, the biggest company at the time. Then Microsoft at 218. What their peers were at the time where he took the helm. And to be clear, Apple, Microsoft, Google, and Amazon were clearly there. Fang was the term at the time. Facebook, Amazon, Apple, Netflix, Google, for some reason, Microsoft. Microsoft didn't make the cut in that acronym.

That has since changed, of course. But there were a lot of companies that didn't go on as significant of runs. You have IBM, Oracle, Intel, Cisco, Qualcomm, and HP, all that were in the top 10. They were sort of the Mag 10 of 2011. And now they are not in the Mag 7, although many of them have done very well. So it seems, this was our take from a long time. you know, we like to harp on the failure of Apple intelligence and how Siri is ineffective sometimes and the FaceTime interface is odd and the new iPhones app is hard to use. But where it

matters, we give them credit on Gen Moji. No, where it matters is, did they navigate tariffs? Did they navigate supply chain? Did they navigate the transition to Apple Silicon, delivering a great product, consistently that doesn't break. Like, we have ordered so many Apple devices throughout building TBPN, and there was a time when you would get a new consumer product, and it would just be, oh, it's a bad one. I got a bad one. And I got to take it back.

And that's never happened. The quality control is flawless. And navigating a very, very difficult chip export act from Biden in 2022, all the way to the Trump tariffs, to different political swings back. and forth and back and forth. And Tim Cook has just done a great job of, like, keeping the wheels on the train going down the track. And I think that should be celebrated,

even though the sexy new AI features are... He's bound to be under underappreciated because he wasn't, he wasn't the bit visionary that Steve was. But he also never, I don't think he ever wanted to be seen in that way. But the consistent operational excellence over almost two decades is almost unprecedented at this scale. It is, yeah, just the way you put it, right? The same experience that I had getting a new Apple computer as like a teenager I have today. It is actually almost remarkable how similar the experience is.

You open this wonderful box. You get a great device. It works for a long time. And you still get that today. So the consistency. And yeah, I think he will just get more, when people kind of process the run over time, he will just get more and more respect. Yeah.

And a lot of the other computer manufacturers have had to go into bloatware and pre-installed software and Apple's been very good at holding the line there. They've, of course, ramped up. services business, integrated advertising in places that were somewhat unexpected, since that was always how they were counter positioned against Google. But they've done it in a way that hasn't been that annoying. I feel like I don't see that many people complaining about ads in the app store. People see the ads and they're like, wow, this company is bidding on the keyword for their direct competitor. That is, you know, extremely competitive behavior.

The same thing happens on Google. Didn't expect to see it in the Apple ecosystem. Of course, it's going to happen. The... Regov in the chat says, not a single product recall under Tim Cook. Is that possible? Wow.

I think that is incorrect. What did the recall? Says they recalled a 15-inch MacBook Pro in 2019. Did BenGate? The AC wall plug adapter in 2016 and 2019. Battery gate service program. They've had some back and forth. But, you know, a very, very successful run.

The other two things that the chat was mentioning was the Apple car and the failure of that program, maybe a little bit, they bit off too much more than they could chew. I think, you know, looking at what's happened in China with every phone manufacturer launching a car that's extremely impressive, I would have loved to see Apple execute there. And I think that would have been very good for the American technology industry, the electric vehicle industry, a variety of different, American industrial efforts, but it was not to be, unfortunately. And then there's the Applevision Pro, which I think a lot of people, you know, look at the churn rates,

look at the retention rates, and they just see it as an underwhelming product. I still like it, but I'm in the minority, and I acknowledge that fully. I do think that they made the right decision to turn it into a home cinema, a home theater. Like they understood that there was not. enough of a video game library, a VR game library to plug into in any meaningful way. And so they made the decision. I think one of the lead staff members on the Applevision Pro project was from the Dolby Cinema team, which had done Dolby Vision and some of the actual theater buildouts.

And so they were able to bring that experience and understand what actually makes for a great movie watching experience in a premiere cinema. and how can we recreate as much of that as possible in VR? Still, you know, obviously didn't hit the mark fully because the product has not taken off by any stretch of the imagination. But overall, it was a fun project, and I'm hoping that they continue that. It might wind up pivoting into just camera glasses

and they'll go up against the meta-ray bands, which might be the more prudent, you know, business strategy. But I still like, you know, these incredible investments in VR. What are you laughing at? Josh over at Semaphore says, nobody tell the new Apple CEO that he has a streaming service. We've got a good thing going here, lighting iPhone and AirPods money on fire to make great movies and shows. And we don't need that getting any extra attention right now. Yeah.

5,000 likes. Yeah, it is interesting. Yeah, Ternis is about as far as you can be from the Apple TV services organization. But I don't know. I talked to a filmmaker in Hollywood. successful filmmaker like years and years ago before the before Apple TV was really ramping up and he was saying that Apple's brand is so prestigious that it's sort of antithetical to the Hollywood mindset which is much more VC risk on you're going to have flops like every every movie studio understands that it is impossible

to predict the perfect success and have the level of polish that comes from these slight iterations I think you could, though. Yeah, built different for sure. But, and so it's a different culture because if you have, you know, Apple's, Apple hasn't, I mean, they've had like flops, but even the flops, like, they still feel like very on brand. They don't have like a silly movie that is just like bad. And running that risk was always a problem. But I feel like Apple navigated it really, really well, especially with the F1 project and has done,

has done really well with the content side. And they have held a brand standard that feels like almost at the level of HBO pretty quickly. Whereas some of the other streaming services have kind of gone more scattershot, more reality TV, more, you know, sort of silly projects that might put, you know, might entertain viewers, but don't fully, they don't create a cohesive brand idea of like what, what am I getting when I open that particular app on the Apple TV? Anyway, continuing, Mark German said on TVPN in January that Ternus really viewed, really is viewed as the ultimate hardware guy at Apple, Ralph Winkler at the Wall Street Journal, published an article yesterday detailing Ternus's pedigree with physical products, quote, if Jobs is a product visionary and cook a supply chain guru, Ternus is a hardware savant who exists somewhere in the middle.

Turnus, who has a background in mechanical engineering, has been working at Apple for 25 years. And most recently led hardware engineering of all of Apple's products. He played a crucial role in the development of Apple AirPods, obviously a massive success. And he redesigned Apple's computers to use company design chips instead of Intel's, a massive move that extended battery life and improved performance. And set them up very well for AI. AI. Yeah. Turnus is taking over Apple at a time when the company has largely sat on the sidelines of the AI race,

going so far as to outsource the technology-powering Siri to Google's Gemini. Turnus will have to somehow manage this dynamic. Ben Thompson wrote about it in November of 2025. Apple's plans are a bit like the alcoholic who admits they have a drinking problem, but promises to limit their intake to social occasions, namely how exactly does Apple plan on replacing Gemini with its. own models when, one, Google has more talent. Two, Google spends far more on infrastructure. And three, Gemini will continue, will be continually increasing from the current level.

A number of people have talked about, you know, what are the challenges that Ternus is inheriting on supply chain, right? Kind of like, you know, stuck in China in a big way. That presents a pretty meaningful, you know, risk to the business. And then sort of like overall dependency on on Google, especially on some of these key products. But without further ado, let's bring in, let's bring in Howie Lou from Airtable. Howie, how are you doing?

Welcome to the show. Thank you so much for coming on down to the TBPN Ultradome. For those who might be living under a supercomputer, not a data center, introduce yourself. Tell us who you are. All right, Howie Lou, co-founder and CEO of Airtable, now also maker of hyperagent part of Airtable.

Cool. I've been doing this for 12, 13 years now. 13 years. Over night, success. Give us the back story. Take us from college through early career to the first, the founding moment. Yeah, yeah. So in high school, I kind of got into programming.

My dad had this C++ book. Left it in this, you know, a quarter of the house one summer, and I was super bored. C++ is a rough place. I mean, this was like 2003. Yeah. Yeah, it was like pre-Python for the first part. Yeah, like, I mean, Python was around, but people didn't really use it. That wasn't the jumping off point.

Java and C++ plus. early days for even web apps, like, Rails didn't exist, like all that stuff. So learn C++, I thought it was kind of cool. And then started thinking about like, how do I turn this into like a real career? Because it was a lot more fun than like classes and like I went to Duke, took some like mechanical engineering classes.

But on the side, basically learned how to do web app programming, like first with PHP, then like Rails and stuff. And I stumbled on Y Combinator actually like pretty early on. It was like, maybe 06. That's like the first class. Literally the first class. Like, oh five. because I remember, like, I saw Looped, St. Walton's first company, and I was doing research.

Like, I wanted to do a similar type of company or product. And I was like, no, you know, I was a nobody. And college didn't know anything. And through that, like, found out about Looped. I was like, damn it, somebody's already got this, this idea and then learned about YC and, like, Sequoia. And so that kind of became my first inroad into, like, just learning about that whole world of, like, startups and tech. Eventually, after college, applied to YC with my first company, which was basically, it was called ETAC's, like, contact. with an E. Okay. And it was like a personal CRM product. Oh yeah. Yeah, exactly. Oh yeah. Yeah, they were like, oh, this is a big problem. Everybody has this problem. Yeah, we'll fund it right away. Am I correct? And my take has always been that the people that clamor for a personal CRM really just don't realize that

they're friends or people that they do business with and they should either just use a real CRM or just don't and just be friends. I mean it's yeah. I think I think it's like a very unique. target audience for whom it's a very high pain point so sure I think there's like a market there but like it's a very like power user pro-sumer audience and the punchline of it though was that like after a year of work we like working this thing raise some money you know hired like a couple people and then we kind of realized like I sort of realized like I think it's a more niche market than we set out to to go after and we had some like different acquires come knocking like

salesports was one of them but like also big like consumer internet companies who want to just buy us for talent sure And to me it was like, And what, this is 2000. Like, we were winter 2010, that batch, and the acquisition talks were like 2011, basically, late 2011. And, you know, we kind of got this point where I realized, like, I want to work on a really big problem, like a meta problem. Not like, here's one small niche for, like, some people. But instead, like, what's like the underlying problem, which is, you know, you could actually build this whole CRM with, like, an app platform, right?

Like, you really want something that's a lot more just configurable and customizable. And so we took an acquisition by Salesforce, worked there. And like, for me, the big light bulb moment was, you know, Salesforce is one big data. What's Benny off like on all hands? I mean, I would say, he's an electric on the table.

Well, there weren't that many, like, all hands were quite infrequent at Salesforce at the time. But, like, I went to, like, their big sales kickoff that year. I mean, Mark is, like, a very smart guy and also a very, like, commanding presence. Like, he's a physically, like, if you met him, like, on the street, you didn't know who he was.

Like, you'd probably think he was, like, linebacker in the NFL. Like, he's massive. And he just, like, he exudes charisma. Like, even in, like, a quiet, small room, like, he'd take meetings in his house. Like, I'd go over with, like, you know, some of the other, like, he's the salesman. He's the final boss. I mean, but, like, not only so, like, he's like, he's like going head to head with him. It's over. I'd be like, I give up. I give up. But he's just, like, he's just got such a presence, even when he's not, like, booming, you know, out loud, like, on a stage. Like, when he's in a quiet room. The dolphin sound.

I don't know about that one, but I didn't get to see that part, but that's the whole genesis of Salesforce. Apparently he came up with the idea while he was swimming with dolphins. I guess that's what all the Hawaii motifs are for. It was a fun time. I mean, honestly, it was a really fun company. Sure. You know, it was like for being in enterprise software, it was like one of the more fun experiences. Like, you know, people were kind of super laid back.

It was like all aloha. And like, or what? But learned a lot. You know, and I think like for me, the big aha was like. like, wow, like all of enterprise software is basically just like a database with like some app logic and like interfaces on top, right? And like that's basically all that Oracle is used for. That's basically what SAP is.

That's what Salesforce is. And if you could create like a way simpler version of that, like that's super intuitive, like that might be a big market. And that was basically the genesis of our table was like, I want to go and like basically PLGFI before that even was a term like this category. Sure, sure. So yeah, what was the initial like? like hunting for team, raising money, building an MVP.

Like, what was the first step? I mean, the second time around, like, so this was my second company then at Airtable. You know, I wanted to do things a little bit differently than the first time. Like the first time was kind of like just go and like apply to YC, get in, do whatever it takes to get some traction. Like it literally felt like this roller coaster. Yeah, yeah. Every week it was like launch, get some, you know, signups, go and like raise money. And Airtable was a lot more premeditated.

Like we spent two and a half years building the product before even launching. Wow. It was actually weirdly a very parallel timeline to Figma. So like both like two and a half years around the same time. Yeah. Launched around the same time. Yeah. Very like PLG in both cases.

And we both kind of exploited like, you know, the advent of like rich browser experiences like for the first time. So like you couldn't build like a rich real time like single page app experience before maybe like 2011. And really it became like, you know, kind of really legit in like 2014-15 with like V8 becoming like. mainstream and dominant, like, you know, just like the performance of the browser became there. Yeah, yeah. So we built this product, like, you know, the premise was, let's make it really, really simple for, like, anyone, like a small business owner, like, you know, podcasters

or even like people within a larger, larger company to build their own app or database. Yep. And they're like, you know, FileMaker, Microsoft Access, like some of these products existed back in the day, but never made the transition to the web. Yeah. We kind of built it. Yeah, my career started shortly after. you guys kind of like came onto the scene and my first ever business,

we signed up for Airtable like probably day one and still use it, uh, how many like eight years later, something like that. So like just running like it's been core infrastructure every single day. That's awesome. Yeah. And like evolved and,

um, but it turns out like databases are pretty sticky, right? Like think about all the Oracle installs and like just random like large enterprises that are just still chugging away, like, you've got your system of record in there and, like, built a lot of, like, customization. Oracle database as a revenue line within Oracle is growing. Revenue. I'm not surprised.

Top line is growing for the Oracle database. Not their AI stuff is a separate thing. GPUs, yeah. Very different valuations, but it is growing, which is, I think, a narrative violation that I think a lot of people wouldn't take. Talk about, like, the early go-to-market. I mean, you said PLG, but, like, are you sending this to, like, startup friends? Are you trying to sell this into Salesforce on day one?

Like how are you thinking about like enterprise versus mid-market versus startups versus like pro-sumer? There's like so many different routes you can go. Yeah. So this was like 2013-ish, right? And like at the time there weren't that many. I mean, there wasn't like really a PLG like thing. Yeah, yeah, yeah. I mean, Slack had I think just come out when we launched in 2015.

So they had launched a little bit before Dropbox and maybe Evernote were kind of the best like PLG pioneers. Yeah. And they were both very like consumer prosumer first. So like solo, like individual user first. Drew Houston has the funniest riff on, I don't think he calls it PLG, but he calls it like the web growth, the web 2.0 growth playbook, which is like going viral. But he takes it a lot further.

And he's like, so you want to sneeze on as many people as possible? And he refers to that as like, if you send them in a file, you've sneezed on them. And then they might create an account. It's just like a much more like visceral way of viral marketing. I can't even get this thing off. Well, yeah, no. I mean, think a thing about, so my first company is an ad network. Yeah.

So we would, you know, a company would come and say, like, I want to advertise, you use a $100,000 budget. And then the company would put together a dashboard. Yeah. Of, like, potential buys. And then the person would go through. And so it was inherently viral every customer that would work with us. Had to log into Airtable and, like, use a product.

So that was just happening at, like, massive scale. Yeah. And I think that, like, that type of, like, you have some, like, data set, like, you know, maybe it's for your adventory or whatever, maybe it's for like your CRM or whatever. You need to collaborate with it. Like, it's a very fundamental construct in just like how knowledge work is done. Right. So I think like the lesson learned from here like that the principle applied was like can you go after something that's so foundational that like it's always going to be around, right? Like I think with the personal CRM thing, I kind of felt the

like turbulence of like, is this in vogue right now? Is it not? And I really wanted to go after something that felt like it's going to be around for decades, right? And, like, what's more eternal than, like, people need, like, databases? A database that you can do stuff with. The past 40 years of computing, it's probably going to be around for the next 40. And, like, even now with agents, it's, like, the database layer actually becomes more important, right?

You don't want just, like, a bunch of ephemeral context windows, like, for agents. Like, they need to, like, store and collaborate on data along with humans. So, you know, we kind of picked that as the vantage point. And a lot of the early customers were, like, startup founders, like, small business owners. But, like, interestingly, we had, like, we had written this fake business plan. It was basically like a vision deck more than an actual business plan.

But like we had said, you know, conjectured, like, we're going to have to go after like a long tail of like the kind of pro-suber, SMB audience, basically like Dropbox. Yeah, yeah. And I think what was really surprising is it turned out to be a little bit more like Slack where we got the most virality within larger companies. So like there'd be a big like media company or like even like a scaled startup, like a Wii work or something that would run all of their operations very quickly early

on on Airtable and then just grow with the company. Right? And so like I mean we work was one of our early customers had like like probably 10,000 people like you know when they were at their peak like it basically was like used by every almost employee there And like a lot of their operations building operations, etc were just built on air table by default and I kind of learned the the value of like having this like data gravity like once you get enough data into a product like air table like it just kind of retains really well within the company and gains more and more usage Yeah, how do you Until the company. Well, you index against the industry that you're in. So I want to get to all the good part right now and all that stuff. But walk us through, since this is your first time on the show,

like, you know, you went from being one of the hottest companies in tech during the whole no-code boom, the like PLG boom, ZERP. like it must have just been, you know, I mean, an insane experience. And then like there's kind of this reset in late 2022, 2023. How has it been kind of like building out of that, you know, trough? And then like have you, I'm assuming it sounds like you've been like very re-energized by this new, this new opportunity. Yeah. I mean, one of the maybe benefits of like not being an overnight success because we took like two and a half years to build the product. Sure. Even like from 2015 to 2017-18, I would say like, we were getting like a steady compounding of growth, but it wasn't

like Slack or like Dropbox where it just overnight became super easy, right? Like it felt like we had to really grind. We had to think about like how do we need to like improve the product and increase the kind of like shareability and the scalability of it. So it's kind of a grind for like at least the first five years. And 2018 when we got our first unicorn round is kind of the first year where it felt like it was starting to get easy, right? So 2018 to 2021, like very fun, easy years, but also like everything is so. Everything is so. Like money just was being printed in the world, unlimited money. And like, you know, we got to raise, like, a big, you know, set of rounds.

How would you like 100 X revenue multiple? Or, yeah. I mean, yeah. And just, like, the absolute scale of funding was, like, huge compared to prior art. Right. Like, now, I mean, you can raise, like, $100 billion, you know, like, if you're opening eye. But, like, at the time, like, you know, we raised, you know, our first unicorn round was, like, $100 million dollar round. And we raised, like, another, like, a couple hundred. and then like a few hundred more.

And then like our big round was our series F, which was like kind of at the peak of like the markets. Yeah. Raised 700 plus million in that round. Wow. And an 11 billion valuation. And you know, we still have like all of that money on the balance sheet

and we're now like cash flow positive. So I think like, you know, it's kind of a fun, fun time to like, you know, kind of get to like ride that wave. And then, you know, but like I always, I think for myself knew like, you know, you have to build like a durable business.

And so like valuations are going to like rise and fall. It's just going to be like macro. But like, you know, ultimately either we build a great enduring business or we don't. And if we don't, then like, you know, you could be like a flash in the pan. Right. So I think we were always like trying to focus. And I tried to focus on like what do we actually need to do to like compound growth. Like go after the enterprise. Obviously at the time, especially like it was clear that was like the move. Right. You get PLG. But eventually you have to go into the enterprise and win like these big multimillion dollar contracts like become. a really sticky system within these larger companies. And we did that. And like, we're still doing that. We have, like, a bunch of the Fortune 500, like, running really critical operations on airtable. Whether it's, like, content production at a big media company or, like, you know, like fund operations at a company, like, you know, like financial services company. So these are like the, like, almost like modern ERP equivalents. Did you hire a different set of individuals to work on that that we already connected and knew that flow? Or was it something where like your best sales reps just sort of got bigger and bigger and leveled up? It was a little of both.

I mean, I think it's a different muscle. Like I think rooduct selling is even at that time, like, you know, not that effective. Like I think like just knowing somebody at a big company like doesn't, even if you're like, you know, very senior and they're very senior, like doesn't actually help that much. Like we've had some reps come in. Like they've had like a decade long relationship with like, you know, the CMO of X, Z company. And I think that gets you like a phone call. It gets you like a meeting. Yeah.

But ultimately, like, buyers are wising up, right? They have been for quite some time where it's not just like, oh, I know this guy, I'm going to like, or, you know, gal like I'm going to buy this, like product from them. Like, you actually have to like show them why this is going to help their, you know, help them in their job, right? And help the company. And so I think it became much more about, like, transitioning from like, oh, people can just use it on their own and they'll figure it out on their own to like starting to do more of a consultative sale, like come in and say like, okay, how can we solve like a really big problem for you? Yeah. And maybe like for one company, it's like, how do I consolidate like my end? end-to-end operations for like how we do all of our brand planning, launching new products,

all that. And that's kind of like, it's like one part consulting, one part like just thinking about like a big enterprise scale solution. And then one part like being able to leverage the flexibility of our product, almost like in a Palantir like way to show the customer like, we can actually solve this really deep problem for you quickly. Is there any sort of like PLG motion or land and expand that happens in the Fortune 100? Like, because there's some small team inside of Coca-Cola or something that's using Airtable,

and then you're able to use that as a demo or jumping off point. That does happen. Yeah, I mean, it's like, there are some companies where you just can't even get your foot in the door without the top-down. Sure, sure. Like, we were firewalled out until we got some

Oh, interesting. So they can't even... They literally block you, right? Okay. Your IP is, like, blocked. Okay. It might be like hard wall, like request access. So, you know, there are some companies where you have to come in top down.

But like they're, you know, I would say 70 plus percent of our current enterprise accounts, including the ones that are like now like five plus million in revenue, like originated from teams within the company organically adopting air table. Right. Sometimes it was kind of like shadow IT. They just figured it out on their own. And they just like they showed real value from using the tool, right? They would build some real operation on it and say like, well, I've been waiting for like IT to, deliver me this old bespoke solution or some like crappy other vendor for like two years now,

I got impatient and just built the thing myself. And that's like a big, I think, you know, I think of like the enterprise landscape now is like, you know, there's plenty of dollars in enterprise, right? Even now, like, you know, it's just shifting from like traditional software to now AI. But like there's plenty of dollars, right? The budget's there. But like the question is, you're not the only one going after it. And so like, what's your kind of asymmetric wedge to get in there and take those dollars, right? And if you're a big company like a Salesforce, maybe it's like, we already have the distribution,

we have like the customer data in there. We're going to go and attack adjacencies. If you're an Airtable, we don't have like the scale of like a service now or like an SAP or Salesforce. What we did have is like the usability of the product. So like the PLP was like kind of the entry point. And then also like even when we pitched to other people in the company that hadn't used air table,

they had probably heard about it from a friend, like maybe the CMOs, like, you know, partner like uses their table. in their company or we can go in and just show them like a really compelling demo quickly. Talk about AI. What are customers demanding? What have you rolled out? Where does AI fit in well? Where does AI take a back seat? Yeah, I mean, I think it's crazy because it's like we've, we've seen like so many layers of disruption happening almost in parallel. Yeah, like you know, you think about like desktop to mobile. It was like a single form factor change kind of kind of easy almost like execute on.

That was the one that I experienced at sales force. The big thing at the time was like Mark would tell every team, like, show me the mobile UI first before you show me like the desktop UI. Yep, I remember that. Right. And, you know, it was like the right move and also kind of a simple move. Now it's like you've got at one level, like obviously every product should have like AI in it. So, you know, we have the obvious stuff.

Like you can now talk to AirTables assistant like co-pilot style and have it do stuff on your behalf in the product. We have what we call field agents, which are kind of like the amazing. ability to map reduce AI calls against all of your data. So you have like 20,000 customer records and run like, you know, AI, agentic, like, you know, kind of tool calls, like search and like research about the company, like synthesize, like, hydrate a bio for every single contact, that kind of stuff. One run time. Yeah.

And like, you know, we do all that stuff. But to me, like, the more interesting, you know, kind of disruptions underneath that are like, one, like, you know, are people, do people even want to come into your interface anymore? Yeah, that's what I was going to ask. Like, why? you care about, like, storing the data in a sort of safe, secure way. Yeah, sales sales force. They just went, like, headless recently.

Like, is there a plan for that? Or how are you going to be in the future? I think it's like, I think the right move is like hybrid headless, right? Like, I think the whole, look, like, if you want to just like a backend database, you could use like Postgres, like Superbase, right? Like, you know, it's, and, you know, there's like PhP, my admin equivalent, like, modern day ones, right? Like, Prisma has its own version of it.

Like, that are okay or they're good, right? But I think what most people actually want, especially in a business context, is like you want the database, but you want to have like proper permissioning, you want to have proper collaboration. And most importantly, like you don't want to exclusively interface with the data through like an agent, right? Like you want to do that a lot of the time. But like it's really helpful to actually go in and see the actual data. Like I think of it as the equivalent of, you know, even though agentically you can like generate all your code and you should as a frontier developer, like does that mean you never want to inspect any lines of code? ever, like, no, like, you still want to see, like, a diff of, like, all the actual, like, code files change, whether that's in your IDE or in GitHub or whatever.

And so I think the equivalent here is, like, you want to be able to drop down into a really nice interface. And we've done some work around, like, kind of figuring out what's the best blend of the two, right? So, like, with chat chbtee, for instance, we have a kind of a first class integration where you can go in through chat chbtee and, like, interact with your data and air table, say, like, hey, pull me, like, all the customers that are, like, waiting for an outreach for me, and pre-draft, like, outreach messages.

But then it can basically compose like a fragment of a view within the Chachapit interface. So like you can actually see like air table. Sure. But like, you know, kind of a part of the interface. So it's not completely headless. It's almost like you get to pull out like pieces of its face at the right time on demand. And I think that's a really important kind of like UX form factor. Yeah.

How are you thinking about speed in the context of AI? I feel like the models keep getting smarter. but they also keep getting slower, basically. And while I'm extremely confident that I could point a deep research agent at a massive air table with 20,000 rows and get very good results, like a lot of times I'm just in my email and I want to find one thing very quickly. And that feels like it has yet to be, you know, AI-a-fied or at least like L-LM-A-Fied. It's very much like, okay, well, I should probably just.

just fall back to like a SQL query or just some Boolean logic or just like vanilla search because I want this now. Yeah. I think both are going to be really important experiences. And obviously we have like, you know, kind of great like smaller and faster models. Sure. Like the mini, you know, that are great for like more synchronous interactions and like within air table.

Like if you go to air table or you use chat to PT with like one of the smaller models, you get that like faster kind of almost like more like real time experience. But I do think like a really important class of work. that will come to dominate, like, every frontier or company trying to reinvent themselves to be frontier, is like figuring out how to operate in this new modality of like, you know, it's like the best developers today,

don't go and, like, sit there in front of their IDE and, like, synchronously, like, talk to the agent. You have, like, 30, you know, separate branches that are each being worked on by a different agent. And, like, you can have the agents continue to, like, update, you know, the branch based on human and other agent feedback, right? So you can have, like, comments back or, like, you know,

run, like, tests, et cetera. And I think this whole idea of like, look, it's going to take like hours for that entire loop to complete, right? Like agent pushes some changes. The changes get feedback from other agents or humans. Agent responds to that. Like that whole loop could be hours, not just like minutes. So you're not going to sit there and like watch it one at a time. But the powerful thing about this is like each one is still actually operating faster than like a human engineer could have like back in the day.

Right. Like when I think about like the speed with which like our early team at Airtable could build features and we got a very good team. like one agent on one branch can, you know, do the work of like maybe three humans back in the day operating probably in like three times the time, right? So it's literally like a 10x, you know, kind of leverage factor just for one agent. But the best engineers are now able to multitask and kind of basically say, look, I'm going to oversee my own little team of like 20 to 30 agents working concurrently. And so I think it requires like, it's almost like everybody needs to graduate from being an IC to like an IC manager of agents, meaning like,

in every function, like if you're like a VC analyst, your job should no longer be to go and synchronously research one company. It's like you're going to go and research like 30 companies and do them all faster, better, and higher quality, right, like than what you could before. And so I think that's the greatest leap that is going to be challenging for a lot of people and a lot of roles to make the leap on because it's a totally different mentality to like how you operate and what your role is than before. What are you pushing the team to achieve So a lot. I think like there's basically like three different levels of self-disruption we're trying to do at air table, right?

One is like the core product itself, like how do we reimagine that for an increasingly agent-led future? So all the like headless hybrid type stuff we talked about and like, you know, like the best testament to that is like do we see like massively growing, you know, basically tool call volume from, you know, chat, petite, Claude, any other agent products? like are people using Airtable more and more agentically? And is it working smoothly for them? So that's like priority one. The second though is like I think we have to like really transform how we operate internally. Right. Like you know, clearly like the companies, the best companies in the future are not just

going to hire like massive armies of people to do everything. Right. Like they're going to hire like people who can really effectively leverage agents. Right. It's so obvious that's happening in engineering where like, you know, if you could hire one engineer who could be fully agentically leveraged, you get more out. output than like 30 kind of traditional engineers doing traditional engineering. So that's kind of one internal thing. But then the third is like I'm a strong believer that like you have to go and

skate to where the puck is going, like index against like the big title wave coming. Right. Like Amazon did this like back in the day against like the growth of the internet. Right. Like they, you know, Bezos picked books and like, you know, e-commerce because like he thought that would be the best way to index against the growth of the internet. And so for us like we get that through air table and like kind of hybrid headless air table. But we're also placing a big bet on hyperagent because hyperagent is basically like taking all of the like excitement of frontier agents, like i.e. OpenClaw and like YOLO agents that can just like have access to your data and tools and do stuff, like really, really like long running stuff, not like 10 second tasks, but like 10 hour

tasks. But for non coders. And we want to do it in like a business friendly way. Right. So like you can go and like do this, deploy it into your company, run like agents across, you know, your entire company. And so that's kind of like a bet on if we believed Airtable, you know, 10 years ago was like the most meta problem, like the largest problem we could work on, which is like software arguably is like was the biggest and fastest growing industry at the time, right? And like how do we go after that entire category and index against that? How do we now go against agents and say like we want to build like the best agents platform that any business and any person can come in and use and just start building agents with, right, and deploying them into their company, right? And so if we do that really well, then like we get to doubly win both as the data layer, but also kind of have a bet on the agent wave. Yeah.

Last question. Should children learn C++? Definitely not. No, I think. And is that because of C++ or because of the AI era? I think, well, I mean, I think both. Like, I think the fundamentals of good technical architecture are going to be the most important thing. But that has let, like, I think the abstraction that really matters now for creating value,

is raising up, right? Like, it used to be at one point, like, you know, Bill Gates wrote, like, some of his first programs in, like, literally, like, machine code, right? And, like, would punch it into his, like, PDP 10. And, like, clearly, you could be a great startup founder or be a great software engineer and make lots of money, like, without having to go down to that level. And so I think now with agents, like, the bar has raised yet again

where, like, what you really need is, like, good product business and, like, tech architecture sensibilities. Like, how should this system work? Like, where should the different, like, levels of, you know, kind of responsibility belong. And like if you can get really good at that, then you have super leverage. If you are just kind of like learning the literal kind of like lines of code and how to write them that, you know, a lot of engineers were poor, I think that's going to be

increasingly below the frontier line of like agents can just do it, like equally or better to humans. Yeah. That makes a lot of sense. Well, thank you so much for coming on the show. Thanks for having. Have a fantastic rest of your day. Great hanging.

Talk soon. We have our next guest. Mark German, the Germanerminator himself in the waiting room. Let's bring him in to the TVP on Ultram. Mark German, how are you doing? Tired, how are you doing? Tired, I can imagine. This has been months in the works.

You predicted this many times, but also on our show. How did this come together? Did this match your timeline? Were you surprised by this particular Monday that it was announced? Walk us through the scoop. Yeah. And get the scoop. Get the scoop ready.

This is the scoop. That's funny. You got the golden scoop for you. The golden scoop. Oh, I've never, I've never seen that. Yes. It's a new prop in the studio. You'll have to take it for a spin the next time here in person.

The opening I deal is already doing work for you guys. There you go. So here's the deal. There's a reason I published my profile of John Ternis just a few weeks ago, right? This was all coming together. things really ramped up internally at Apple on this at the end of last year. Things have been in motion. The plan was to announce it after the 50-year anniversary celebrations.

And it almost felt like the 50-year celebrations were not just about Apple's 50 years, but sort of a goodbye celebration to Tim Cook and his legacy at the company. So it all came together over several months. this really started about two years ago when Tim Cook identified John Turnus as the next one. Ternis had been being prepared for this role probably for over five years at this point since they put him on the executive team

and he became SVP of hardware engineering. But this started in early 2024. And at the time I wrote that that was the first time I wrote that he would be the next one. Yeah. How do you, have you been able to press? I know you've published a few memos. Have you been able to ascertain anything about the internal response? Are Apple employees excited about this? It feels like it's been managed from a communications

perspective very carefully. And so it shouldn't have been a surprise to anyone. But our Apple employees generally excited about this? It seems like there's a lot of cause for optimism. But I'm always interesting to hear. Yeah, there was that one article a couple months ago where clearly they were getting quotes from former employees that were like kind of taking pot shots at him. Yeah. He's never made a hard decision. Yeah, that was the quote that went into the journal. But I don't know.

It seems like it didn't matter because he got the job. Well, got the job two years ago. And I think he's going to do a hell of a job in this new role. I am quite optimistic for Apple in the long term with Ternus at the helm. He has product sensibilities that Tim Cook simply doesn't have. He has product decision-making ability that Tim Cook certainly had, but wouldn't utilize because he himself knows that product-based decisions is not where he could have the most impact. Just like Tim Cook really oversaw the operations part of Apple as the CEO and led product development to other members of the executive team,

my expectation is that John Turnus will be intimately involved with the product side of the organization as he was in his prior role to CEO, and will leave the operational side to people like Saabi Khan and Priya, the people who run the operations division at Apple, supply chain manufacturing, procurement, AppleCare, you name it. So he's going to pick his spots and his spots is hardware and product development. There's a reason that when he chose his successor for the hardware engineering organization, he chose Tom Marriab, not an innovator, but an incredible execution guy when it comes to hardware engineering. airing product quality. He did that because his belief is that he will still be intimately involved and sort of be that product visionary for Apple in this new chief executive position. Yeah. Does, uh, when I remember Steve Jobs, I think of jobs as an innovator, as a visionary, as someone who both did Pixar in the iPhone, you know, so many different

projects, a lot of them wildly successful. Um, Tim Cook felt like a focusing of that a little bit, but you still had the car, Vision Pro. There's a few different projects going on. Is this more, is this the most focused Apple has ever been and will ever be? Or do you think that there's, do you think Ternus has like some aces up his sleeve where he might want to take a wild swing at something? The thing with John Ternis is going to have to do is stay the course. Annual iPhone, iPad, Mac, Apple Watch, AirPods upgrades. But at the same time, is going to need to do a better job bringing out new product categories that Tim Cook has done. If you look at Tim Cook's legacy in terms of major new products, it really was on the services side.

The AirPods and Apple Watch, those were both really developed by management teams, engineers, and people who came from the Steve Jobs era. That's not a slight, but my point being is that we really haven't seen anything wholly new that is also successful since 2016 with the AirPods and the Apple Watch at the end of 2014. The Vision Pro has obviously been a Tim Cook product, a Tim Cook priority, and it's been sort of a flop, at least for now. I know Apple has a very long, decade-long spatial computing roadmap. They eventually want to get to AR glasses. They'll have display list, glasses to compete with meta several months from now in 2027. But he needs to get cracking.

There are six major Apple products in development right now, six major new product categories. AI Airpods, smart glasses, pendant, smart display. Is that the lamp or the kitchen thing? No, no. Lamp is number five. Smart display is different. The tabletop robot, so that's the lamp, the moving lamp. And then number six is a, I'm only going to say very little about this, but a security camera.

Okay. interesting. Well, at least the Applevision Pro has one key fan. Do you think the lamp, do you think the lamp is a predecessor for a humanoid? Do you think Apple would ever do a humanoid? I do. But I think it's going to be a decade if they do. And they're going to wait and see. Yeah, I feel like it says a lot that they're not talking about it. That you don't know about an internal humanoid project yet.

Oh, I do. Oh. But, but. Yeah. They're exploring humanoid and the idea of a humanoid. They're not working on it full throttle, but they have a large robotics initiative. They're working on AI robotics technology, and they're also working on robotics hardware. John Ternis actually took control over the robotics hardware team about a year ago.

He took it from the AI chief that Apple got rid of a couple weeks ago, John Jan Andreo. But they're also looking at – they're actually building – it's really cool, a gigantic manufacturing arm. or a gigantic robotic arm that they want to use in manufacturing, but also used in Apple retail stores to grab products off the shelf in the back room and whatnot and bring it into the store. That's probably five years away. But they're looking at robotics from a manufacturing standpoint, from a retail standpoint,

and also, most importantly, from a consumer standpoint, they've also been exploring a mobile robot, something like an Amazon Astro, but I don't think that's probably going to see the light of day. That's fun. I feel like Apple has the perfect brand. Talk about robotics. Talk about Ternis' challenge with supply chain broadly what you think he's going to be focused on over the next five years.

I don't think he will be. I don't think he will be. I think just like Tim Cook. But is that not you're saying like just basically like broadly ignore that it's kind of a key risk to the business to have, you know. I mean. No. His team. With the hands on, in all hands meeting with Apple employees this morning, he was pretty clear that Tim Cook didn't do everything.

Tim Cook chose his spots. and Ternis said that he's going to pick his spots as well. As we know, Tim's spots was operations, finance, and sales, and he delegated everything else. My sense is that Ternus is going to – Ternus is mandate. Ternis was hired because they believe that he's going to be able to bring Apple back to the forefront of product, device, innovation. They already have the best-in-class operations, finance, salespeople. don't need turn us to do that. They need turn us to keep his eye on the prize, which is products. Yeah. And what do people point to when they say that there's a risk to Apple staying on the

frontier of product development? I saw the Android phone that has the privacy screen that you toggle on and off. That looked like kind of a cool feature. There's folding phones that they're working on. But are any of these features that exist in other phones? It feels like they haven't actually got into ground swell and started pulling iPhone users away from the ecosystem. But are there key features that people are worried about? It's not here yet. Yeah. It's not here yet.

Nothing you've seen is the risk. Okay. The risk is whatever the hell meta and OpenAI and Hark and all these companies eventually come out with. The risk is one of those companies doing something really cool and jettisoning Apple from that perspective. But we all know that nobody has done quote unquote cool stuff. stuff yet to steal away iPhone

users. Nobody's ditching their iPhone for Android. In fact, the switching is going in the other direction despite the fact that Apple is supposedly the most innovative company in the world and has the least innovative AI technology. Yeah, but consumers care about value and things like the MacBook Neo

really deliver that value. Brand, colors, value. Turnus was only senior VP of hardware engineering at Apple for five years. It's a short tenure to be an SVP of a division at Apple. in the re-use him because he's... Oh, there you go.

No, he's been at Apple 25 years. No, I'm kidding. We use that ironically. No, I know. But the point I'm trying to make is that he still has a legacy. And Ternus' legacy is making Apple hardware more performant in terms of speed and battery life and higher quality. He's really focused on the durability and the reliability and the reliability of Apple products. And it's meaningful, I think, that the person that they chose to be Ternis's replacement in hardware engineering, Tom Mareeb from Intel, is a product quality and reliability expert rather than a product design person.

Yeah. What was the thinking? I mean, I remember we talked about this how I got the new iPhone and it has immediately been dinged. What was the thinking I'm making it disposable? But it's better for heat or better for wireless connectivity, even though you can't get the color to adhere. to the to the material as much so it scratches off is that the is that the current tradeoff like yeah yeah there's tradeoffs with every material like titanium was light it looked cool you could beat blasted it did so you know interesting i mean it looked interesting and it gave them a good marketing point

like oh come by a titanium phone like anyone cares about the material of their phone um but it had really bad uh properties related to heat aluminum which we've known for 20 years is an excellent material to build consumer electronics out of. So they went back to the basics. You know, they were really talking about at the end of last year, splitting the line between ultra-thin with the iPhone Air and pushing the iPhone Pro to the right as much as possible by making it more performant. My expectation is they're really doubling down on this. Their goal is really to just squeeze as much performance and power in these iPhone pros as possible. And for everyone who needs less power, you can get the thinner and lighter iPhone Air. And I think you're going to

continue to see Ternis pushing that direction, making the MacBook Pro is amazing and most performant as it can be in pushing everyone else to the MacBook Neo and the MacBook area. I think his legacy on performance and product quality is really important thing to remember. Has Ternis ever talked publicly about AI in any capacity? He talked about AI in his all-hands meeting with employees this morning. he said that... I'm going to check it out. No, just hold on.

I'm kidding. Hold on. I don't want to give you inaccurate. Yeah, fake news. Okay. Yeah, just hold on. Bear with me. Internal memos.

No, no, no, no. Okay. He said that he's especially excited to be stepping into this role at this moment because I am telling you, we are about to change the world once again. He said Apple has an incredible roadmap ahead, and that I'm not exaggerating when I say this is the most exciting time

to be building products and services at Apple in my entire career. AI is going to create almost unlimited potential. We're going to be able to keep unlocking possibilities that are going to create entirely new opportunities for our products and services, and I'm so excited about what that's going to mean for our users. Earlier this month, he reorganized Apple's

hardware engineering division around in a new AI platform that they're going to be using to improve product development processes and overall quality. Interesting. Okay. I saw a post here from Bubble Boy. I want your reaction. Apple is about to become the mecca of hardware engineers around the world with John Ternis taking over at Apple.

Is Apple not already the mecca? Is there actually somewhere to go, but that is up in terms of hardware? engineer recruiting, do you see this as changing the culture in some meaningful way? I mean, they don't pay like these, you know, Open AIs, Harks and Metas of the world. Apple has been pillaged by Open AI and meta and all these companies. As of late, they are stripping apart Apple's hardware engineering division, hiring people from every team they can get their hands on throwing very big offers at them. And so this has been a really big issue that Termis has been dealing with over the last year.

and change. So, but Apple is, you know, the hardware mecca. They're the company that everyone wants to poach from. Yeah. And they're the company that people go to to learn how to build consumer devices. So this is definitely, yeah, I agree to a large extent with you, actually. All right, with bubble boy. Yeah.

Bubble boy. What, I did, this might be somewhat separate, but just get me up to speed on the folding iPhone. What is the latest there? announced in September Turnus' first big new product super exciting super pumped we've talked about this

I'm sick of the candy bar phones been the same junk for 15 excuse me 20 years now I want a foldable I want a bigger screen I really hope John Neat wants a newspaper-sized phone well they have those

I've seen those in China the trifle right but this is a bifold don't get me start on the trifles okay explain the trifle wait why are they awful it seems amazing John wants pages of screens that he can turn. Limsy and they break. You need a trifold and Apple-like quality.

In 20 years, because Apple, like, to take a good old time. When Apple does a trifold, it'll be good. Okay, okay. You know, I open up a foldable phone right now. You open it up and you can hear the screen sort of creaking, right? And then you have that big line in the middle. And then it's, like, impossible to get your thumb in to open the thing. Yep.

I hope Apple fix that. I don't want to hear a creek. For $2,000, I don't want to hear a creek. I don't want it to sound like I'm stepping on, you know, a wooden floor. Yeah. I want it to just open and I want it to open quickly and nicely and it not be like I'm trying to lift the weight. Yeah. It's still going to be weird for video consumption, though, because I feel like we've done vertical video, nine by 16 and then 16 by 9 widescreen.

But if you open up a foldable phone, you eventually get a square. And that doesn't really make like a movie watching experience. No, Apple's is different. Apples is like the new Huawei phone where it is iPad screen ratio. iPad screen ratio. When you open it. Okay. When you open it.

Yeah, okay. So still black bars. Any Intel on. No, no, no. Black bars. Yeah, sure. There will be black bars. When you rotated black bars on the top of it.

If you're watching like a cinema film or even if you're scrolling Instagram, like you won't necessarily get more view because for so long, all the content production has been ultra-wide screen if you're making a Tarantino film and it's super cinematic. Or if you're on TikTok and you're doing vertical video, then you're going to have black bars on the side for the most part. But for so many other applications, you know, for Word documents and notes and TVPN will look great on it. Yeah. Yeah. Something to look forward to. What do you think Ternis's new comp package looks like?

You know, we were, we, we almost marched on Cupertino, uh, mobile times because of Tim Cooke's, to get Tim Cook. To get him a raise. You're going to get cuff yourself to the, uh, to the spaceship. Yeah, exactly, exactly. I would, I'm just guessing. I'm just guessing. Um, I think a million shares. Hmm.

Over 10 years. That's pretty big. Ellen, can I just tell you why I think that? Yeah, why? Because that's what they, because that's what they gave Tim Cook when he was named CEO. a million over 10 years. I would assume it's the same. But again, I don't know.

Entry level researcher salary, but it's a good start. Pretty much. Tim Cook is getting Tim Cook, you know, Tim Cook was getting 100 million a year and then everyone flipped out

except you guys. And so he had to cut his pay to like 40 million and then when things died down, he's like, all right, I'll take my 70, 80 million. I slept peacefully. for those years. And then you should see my sleeve score once.

We were really, we were really the strongest supporters of the Tim Cook pay package. I guess a million. I was just like, okay, the free market values a baseball player at the same amount as a guy leading, you know,

a $4 trillion company. Make it make sense. Yeah. Maybe it'll be 500,000 shares. Maybe it'll be 500,000 shares. I don't know. But I know that they gave Tim Cook a million. You got to get those numbers up.

You got to get those numbers up. It's time to March. Really? You're all in on harness already? We should preemptively March. We're bullish on both. We love both here. Well, now you get both now.

I know, we do. Yeah. Why is 65 a retirement age for the CEO of Apple? Like, we were talking about Warren Buffett. He was able to manage a, you know, a trillion-dollar organization well into his 90s. Is it a more physically demanding? job? Is he traveling more? Is it his hand

ringing from shaking hands in DC? Like, why not have another 10 years if you're in that seat? I don't think the hand situation has much to do with shaking other people's hands. Okay. Why is he not there another 10 years? Well, he needs to give the new guy runway. Okay. I'm sure there are some in, I'll just tell you what Tim Cook I'm not going to get into it.

What I'm going to do is tell you why Tim Cook said he's stepping down. He said he's stepping down because it's the right time. And there's an intersection of John Turner's being ready. Apple's finances being in a very strong place. And Apple's future road about being in a very strong place. In terms of the real reason why he's stepping down now, you can read some of my prior articles, taking a deeper look at the situation. Okay.

Yeah, makes sense. Cool. I love seeing you. I love talking to you. Thank you for coming on. Congratulations. I love you guys, too. Get some sleep.

Great to see you, Mark. Keep up the amazing work. We'll see you soon. We'll see you in 15 years for Termis Jr. Can't wait. We'll see you. Goodbye. Let's pull up the Open AI launch.

What's going on? Image Gen 2. I've been playing with this for a while. It is. Wild, wild examples. They are live streaming. Sam should have saved the Death Star meme for this. Yeah.

For this launch. Let's see. What are they said? Organized Image. And we think we made a lot of progress in both of this visual understanding and visual generation, both of these aspects, as a result, being able to handle this kind of tasks very well. And we now have an output for this where you can see eight different real cool office for me. The level of detail in these models is getting so extreme. It's post-slop.

It is post-slop. That's a good point. but I've seen some where people are like generate the entire periodic table with details about each element and a visualization of each element. And it's just like so much information so dense that you have to wind up zooming in so much just to get all the information. It's like the idea of generating like a single photo of a person in an outfit was, uh, was remarkable just a year ago, I guess, when the studio Ghibli thing happened. and now you can generate layers and layers of detail here. Good teaser. They said this is not a screenshot and posted the image.

Something that prompt, tell everyone about the prompt you've been running with Wiki. Oh, yeah. I've been doing this thing where I take a Wikipedia article and I ask ImageGen 2 to turn it into an infographic. Or you can actually do an Instagram carousel, like 10 images. that tell the story of something. I did this with John Turnus. And it's remarkable. I mean, the text is perfectly photoreal.

The other thing that's interesting is the brand comes through an interesting way. It's not like it has like one style for infographic. Like I had it make an infographic about John Turner's and his career and his path and everything that he's done at Apple. And it put in images of the projects that he's worked on, but then also had like an Apple. like brand aesthetic, like a white background, the correct fonts. But then I did the same thing for like the Eldon Ring movie that we were talking about yesterday. So I went got the Wikipedia for the Eldon Ring movie that has some details and some leaks of who might be in the

playing different roles. And it was able to go get images, go get headshots of those people, put those in because it has tool calls now. So you can actually like if you say like generate an infographic of John Turnus's career, it will do like a pretty good job generating someone who looks sort of like John Turnus. But then you can actually just take his canonical headshot and say, no, use this exact photo of John Turnus. And it will just drop it right in. And so it looks perfect because it is just like a copy paste basically on top of the layers. Let's get some audio again.

Let's see what else is going on here. Output. This is particularly useful for very complex prompts for things that require like web searches, but require you to output multiple images that have to. maintain coherence with each other, or even for it to check its work before saying, hey, here's your final output. But let's just look over some examples of this first.

Gabe actually kicked off a few of these examples at the start of the live stream. So let's go to the one on the phone, which is the one of him and Sam, the selfie of them, and they created a manga of it. And if we look at the very first image, we can see, yeah, it does look like Gabe and Sam, right? Yeah. But I think what's even cooler about it is that if you look at the follow-up images, they still look like Dave and Sam, and they still look like in the style that was originally maintained.

Yeah, children's stories, coloring books. It's like really insane. Yeah. Yeah. Among pages one, two, and three. I did that this weekend. It was very successful. Rave reviews in the Kugan household for AI-generated coloring bucks for mythical creatures that my...

To give a little back way of this, combining different creatures. We beta tested the instant version of this model on Elam Arena under the codename duct tape. A few of you on the internet were like really good detectives and deduced that it was us. But we're going to announce that it was us. And so in this pump, we basically asked that basically GBT images too to go and find social media reactions to this duct tape model and basically quote people. And so we see quotes from threads, LinkedIn, Reddit, etc. But I think an even crazier part is that we've also asked the model to put a QR code to chatGPD.com so that you can try out this model right now for yourselves.

And can we just make sure that it works? Yeah, I try. Oh, nice, nice, nice. So image generation with thinking allows you to do really complex things. So in this case, web search, synthesize answers, and put a QR code all in. one image. But we have still more, and Alex will talk to you about these new details. It's so interesting. The tool use is getting really advanced. We also made a codex that actually was able to generate a vector diagram to make sure

that everything was correct and then regenerate the image on top of that. Of course, we should go to the timeline because there's some people that are having fun with the image generation. Someone made presidents in Eldon Ring. There's Joe Biden, which is a, you know, a Dark Soul-style boss that you can fight.

And FDR, Lord of the New Deal. And these images just looks remarkable if you ever played any of the Eldon Ring or Dark Souls games. Because, of course, like the text is flawless, and then you can fight Richard Nixon in front of the Watergate.

And this looks like a mod that I think people would play if it actually existed. Blake Robin said the world is now ready for the rumored open AI image model. People are creating Google Street View images that just look perfect and Grand Theft Auto 5 loading screens. And there's a big trend of people creating things that look like screenshots of live streams. And then they put themselves in the live streams and have all fun with that. And there's one of Satsinadella presenting. a slide and like even the minor text at the bottom of the slide in the picture.

It's sort of remarkable to think that all of this is generated, basically one-shotted. Justine Moore was posting about this long time ago, April 6th. This ad was one-shotted by Open AI's image model. Prompt was literally make an advertisement for the M4 Pro Mac Mini. And I mean, you can see how quickly this will speed things up. The question is just like, what is your source content? what do you want to visualize or deliver via this format? The whole meme of like, turn this essay into bullet points, turn this bullet points into paragraphs.

Now you can turn this infographic into text and turn the text back into an infographic. I feel like a lot of slides. Someone made Palantir for tracking your Uber Eats and FedEx deliveries and it looks pretty believable. Yeah. We can pull up the screenshot here. Yeah. people um there's something there's something interesting about this where uh i've seen a number of of uh slide decks that could be infographics and i'm wondering if there's going to be a new level of

like compression where people are saying like just send me a screenshot like a one page or screenshot uh over text instead of like a slide deck that i have to click through that is a lot of information that but if you zoom in but if you zoom in there's like pretty impressive fidelity It's just that's wild But yeah I mean if you're trying to If you're trying to deliver a whole bunch of information That could go into slide deck

Condensing it down into an infographic feels like Potentially a new trend and I wouldn't be surprised if you see a lot of these Flowing out into Instagram carousels and other sorts of content If you're trying to summarize some sort of content A history quotes you know any sort of information like that Anyway Tyler Cowan back to the timeline, Tyler Cowan made an incredible call back in July of 2020 in the depths of COVID in Bloomberg.

He said, this year is likely to be remembered for the COVID-19 pandemic and for a significant presidential election, but there is a new contender for the most spectacularly newsworthy happening of 2020, the unveiling of GPT3. As a very rough description, think of GPT3 giving computers a facility with words, a faculty, no, a facility. with words that they have had with numbers for a long time and with images since about 2012. What a remarkable post. This was two months after Guern's scaling hypothesis post and two and a half years before Chatsypte was released.

That is remarkable. There's a lot of folks that are chiming in with. I called it too. Anyway, I believe we have our next guest in the waiting room. Scott Stevenson from Spell Buck. Scott, how are you doing? Scott, how are you doing?

How are you guys? We're good. Welcome to the show. How are you doing? Cool. Yeah. Thanks for having me. Can you, I mean, I want to go into the contracted IRA debate, but let's get the update on

Spellbook. How are things going? Where's the company at? How are you feeling? Going very well. We had a killer Q1. Crushed our stretch targets last year. Yeah, we're over 4,400 customers on board in 80 countries now.

80 countries? Yeah, we're the most used AI Contract Review tool in the world. Why so international so early? It's been inbound, yeah. We've had a ton of interest inbound. So, yeah, it really, you know, the choice is accept the customers or turn them away. You know, we chose to accept them, yeah. Is the product sort of multilingual by default?

I would say yes. A lot of it is driven by AI models. AI models have some ability to deal with different, actually pretty good ability to deal with different languages. and then we're able to supplement the models with legislation and norms from many different jurisdictions since we're a legal product. Yeah. So, yeah, where else are the key integration points? Like, what's the hard work to, like, bring a country on board or even bring a new flow on board or expand the capabilities of the product as models are just sort of getting better every month by default in the background? Yeah, I mean, I think for us that the bit, you know, we try to be.

two years ahead of the market and build things that are two years ahead of what anyone else is building in legal AI or elsewhere, and we've consistently done that. We built the very first Gen. AI product for lawyers back in the summer of 2022. This is like before chat, GPT. So a lot of like Claude for Word just came out. That was kind of what we launched like four years ago. So we're pretty, pretty far ahead from that now. What we really focus on is building unique workflows that are not just chat. I think if you're building something chat shaped, it's very difficult. to make that defensible because there's going to be some really good general AI products for just generic chat-based work.

What we focus on as spellbook is really rails for high volumes of contracts and contract workflows. So we sell to like Fortune 10, Fortune 100 companies and really companies of all sizes who are processing, you know, hundreds of thousands of contracts, not just with the legal team, but with the sales team, the procurement team. You know, we're in manufacturing, shipping, you know, all of these different verticals. And we kind of build these end-end rails that allow these contracts to move quickly and safely through organizations. And, like, there's a lot that can slip through the cracks when you're dealing with these high volumes of contracts. And a lot of mistakes are made.

So, you know, we give, like, every legal team a second set of eyes on, like, these massive flows of contracts going through the organization. Yeah. What drew you to Cargate? Why are other, is it legal AI companies that you, that you, that you, that you, feel like are getting a little bit dicey on this front or, you know, how do we get here? Yeah, so I've got some interesting examples to cite, but, you know, I think it's an enterprise AI problem. And I'll say, I'll say first, like, my goal here with this tweet and what I'm doing is to

destroy as much equity value as possible by discrediting this obscene metric of C-A-R, or at least the way it's being used today. So we can all get back to, like, building real companies. So that's what I'm trying to get out there. Sure. I mean, where this came from is I think I just noticed more and more founders and investors telling me things about ARR reporting, you know, mainly the public reporting, but also some of the internal reporting, that was just getting more and more skewed.

And, yeah, there's all these headlines being published about, you know, ARR records being broken. Sure. And, you know, when the laws of physics are being broken, you have to ask, is it AI? breaking the laws of physics or, you know, might there be some other kind of illusion going on as well? And I think it's a bit of both. We have really high growth, awesome companies being built. But when you have really high growth, you know, issues can kind of fester and hide underneath. So, yeah, I'd heard a lot of more and more stories of people using this metric of C error,

often using this metric when they're talking to press about, you know, their revenue. and then gaming it in some pretty obscene ways. So maybe I just tweeted about it. Yeah, the tweet. So you say the setup. Company signs three-year enterprise deals. Year one is discounted. Say one million.

Year two steps up. Two million. Year three is full price. They report three million as they are, even though they're only collecting one million dollars this year. That's a big deal. The worst part, the customer has an opt-out option at 12 months. It's not actually a three-year contract.

So they're basically like taking the three-year number, pulling it into the present, even though it's not a, it's a contract that the customer can get out of. Interesting. And they're not actually on the hook. So it's not really. That's rough. Yeah, yeah, yeah. Just react to that, I guess. Yeah.

So I think, you know, that's a specific real example that I heard of in the wild from an insider of how these error metrics were being gamed. to create some amazing revenue charts. But I would say there's, you know, a broad category of issues that I can talk about, like, a few of them that, you know, after the tweet went viral, I got a huge response of other founders and investors saying that they were saying the same thing and, like, some other examples of the types of gaming that's going on. Yeah, because if you get one person in a category that starts doing this, then other people like suddenly have to start reporting the same way. and it creates a vicious cycle. And it starts pretty innocent. For folks that don't know, C.R. For folks that don't know, C.R.

is contracted error. So it allows you to count revenue that's not live yet. So maybe you're doing like a nine-month implementation or you have a one-year pilot. Yeah, it was meant for short term stuff. Like, hey, this contract is going, you know, this customer is actually going to be going live next quarter, but we've signed it and we're just going through the implementation process. Yeah, yeah. But there's nothing that there's no, like, law that says you can't say, like, we're going to extend the sort of, like, timeline dramatically.

It just is not a very grounded way to run your business. Exactly, exactly. Yeah. And, like, I think it's innocent, like three months extra credit, you know, arguably useful. But it's a very easy metric to game, especially if you miss those obligations. So I think because we kind of normalized, you know, the forward deployed engineer, which, you know, we used to call a perfection. services. And so now you have these really complex implementations where you might be promising a customer like, hey, we'll build this feature. And once we build this feature, then we'll start billing you. What happens if you don't build that feature? So one of the issues you see is companies stacking all these commitments of they'll switch on billing once they deliver X with their forward deployed engineers. And then what happens if they miss that or what happens if that gets delayed? And then they're reporting it up front as ARR publicly, but they're not actually at the

the point where the error is live. So, yeah, that's another category of issue. And then there's, you know, people reporting pilots, you know, just three-month pilots as error and they're free, free pilots. You know, I was talking to an investor yesterday. It just sees that all the time from early-stage companies, like coming out of accelerators saying they have like a million error and they look under the hood and it's just all pilots that haven't converted yet.

So there's a host of different, you know, issues with the metric. And then the other one is the step-up contract where, yeah, you're, stepping up, you know, year one is, you know, 25% of the cost. Year two is a little higher. Year three is higher. And then people are either amortizing that back over the period to get a higher average or even taking like that year three amount, like you said at the beginning. So, yeah, there's a bunch of patterns that are happening. The other thing is like there's early opt-outs. So like, you know, you can have early opt-outs in these long-term contracts. And but there's all, I mean, we're a contract company.

So there's a million ways that a contract can be termed. I've seen a few contracts. Yeah. Yeah. So. Yeah. Yeah. I think it's a really ungrounded metric and people should stop using it to report their enterprise

AI company should stop using it to report their error publicly. I think no one should take it seriously, except maybe internally for some projections. You know, it's not a good, good metric. What is the gold star example of using ARR correctly? Because it's very easy, once the company's public, to just say, okay, let's just go off of, you know, gap revenue for the year. And like, what did you actually book this quarter? There's a whole revenue recognition policy. It feels like there's some benefit to tracking ARR month by month if you're a high growth startup.

But what is the best? Overrated. Companies should just report their daily annualized run rate. Maybe. Or hourly. Yeah. And that goes in the debate of annualized versus annual role, right? So how have you processed sort of the better cases?

Like, what is the responsible way to report a revenue metric in 2026? Yeah, I mean, I think it depends on the company and the shape of the company and whether it's usage-based billing or seat-based billing, which you still have lots of both. Definitely don't do like hourly, you know, annualized run rate based on the hour. That's not good. I think the main thing I would say is it should be. It's like what revenue is actually live right now for like what customers are you actually billing and are actually paying you? So calculating run rate based on, you know, the month of revenue that you have coming from customers that are actually paying you that you're actually billing. I think that's okay.

I think, you know, annual recurring revenue based on live customers that you're actually billing that are actually using your service. I think that's pretty good. I think once you start stretching into people who will pay you or, you know, might pay you, that's where things start to. I mean, it can just be so easily gamed and anything that can be gameed will be gamed. Are you optimistic that anything will change or do we need to see a massive correction

and a dark, in the dark ages like post-2022? I mean, I would like to see a steep correction and then back to building. You know, we'll see if we can make that happen. You know, my reach is only so far. but, you know, I've spoken to a lot of reporters in the past, like, 48 hours who are like,

I'm always going to ask now, like, when the company tells me their ARR, are they talking live error? Are they talking, you know, this, like, long-term committed error that might come? So I hope, you know, at least the journalists are going to be a little bit more savvy and ask, ask more questions before they report on these numbers. Yeah. The, I want to ask about who suffers. But in terms of ARR, like, yeah, there's almost something where you should just report your last month's revenue instead of doing the times 12 thing. And then if people want to multiply it by 12, they can.

But at least you're just reporting, hey, last month, this is what the Stripe account did. You can also just say by Q3, we will be at XARR. Exactly. That's a different way of saying that's better than saying we are at 10 million CAR. C-A-R. Yeah, yeah. Exactly. Much better.

Who suffers here? Is it purely investors because I feel like a good venture capitalist, their job is to dig into the contracts during due diligence to set prices? And if they want to pay a thousand times ARR because they think it's 100 times CARR, like that's their risk profile. Like I would maybe be careful, but that's their job. Or is there a risk that employees see a headline number and, think that the business is more stable than it is and they join and then they're they're rugged like

uh how do you think this affects the who needs to watch out for this basically yeah i mean i think um i think investors are generally good investors are generally very aware of the difference between c a error and error and aware of the the widening gap between these metrics and like in most board decks you see two metrics on the press you only you know you usually see c r but it's called error yep in in a board deck you see both metrics so so you know investors are quite aware but but i i i'd I don't think it's victimless at all. I think, yeah, employees are signing up for companies. And as you know, in like a high-growth startup,

people are committing a ton of blood and sweat to be successful. Part of it is based on the growth of their equity. And if it turned, and they might think they're multiple, you know, they might read the headline number. They may not know the number that's actually in the board deck. They might read the headline, you know, ARR in the press release. And they might base their decision to join a company based on these headline revenue numbers, which are really not grounded in reality whatsoever.

And by that, I mean, I have literal examples, confirmed examples of, you know, the press number being three to five times higher than the actual live error number. So, like, that's a huge difference. If you think about a multiple. Yeah, yeah, yeah, yeah. And so between a public company

that's trading at 10x, revenue multiple or something. And then you get your offer from a company and it seems like they're at 10x, but they're actually at 50x, Like that is very material for how you should think about valuing that, that stock that you're working for. There's the customers. Like customers are trying to figure out which company is most mature or least mature.

And then there's the, you know, like the whole competitive landscape. It's like if one person, if one company starts doing this, all companies have to start doing it. And it just creates. Yeah, I mean, we can start doing contracted viewership. So we can sign three-year deals with people in the audience that requires them to tune in to show every year. They have an opt-out after a month if they don't like it after a month. It's still advertising based on contract and viewership. Exactly.

The contract for the rest of the year. I watch every day, every hour. I mean, I guess that sort of does happen for YouTube channels that, I mean, no one really does this, but there was a time when YouTube channels were sort of valued on like the subscriber number as opposed to the average view number. And of course, there are some channels where every video gets a million views and they only have 100,000 subscribers for whatever reason. And then there's vice versa where someone's been doing, you see this on like old legacy

media accounts on X where they'll have like 30 million followers. And then the post will get like three likes. And it's like those are two wildly different metrics. Like that happens all the time. But this is the name of the game in Silicon Valley, the metrics game. Everyone's finding an edge somewhere. Well, thanks for keeping everyone honest. And good reporting, good luck, fighting the good fight out there and spreading the good word.

Don't get too sucked into all this. You're a business to build, you know. You can take, we promise you can come back on in three years with your, with your honest ARR and take a good victory lap. No, become an investigative journalist. Pivot to investigative journalism. Blow those doors wide open on this. Wow, this goes deeper than I thought.

Good to, good to see you. Have a good one. Thanks, guys. We'll talk to you soon. Up next, we have Alex from Osmo, building olfactory intelligence. We've talked about this before. Can AI smell? That's our current benchmark for AGI.

We say if, you know, we talk about white-collar work, we see Somaliers as white-collar workers. Unless you can smell, it's not AGI, and artificial intelligence is falling short. But it's your first time on the show. I would love an introduction on yourself. in the company because I'm fascinated by this topic. Let's talk about it. Your Somalia comment and also what you talked about with Max Hodak, spit on my mind. My name's Alex Gulchko.

I'm founder and CEO of Osmo. We're giving computers a sense of smell. I've been working on this problem for 20, exactly, 20 years or so. 20 years. First has an academic. I did my PhD inel factory neuroscience at Harvard and trained under Bob Dada who trained with Richard Axel, got the Nobel Prize for discovering the reception.

of smell. And my AI mentor trained with Jeff Hinton who got the Nobel Prize for Deep Learning. Yeah. And I'm the one weirdo that's like that's like that's incredible. That's amazing. We've been waiting for you to join for the entire history of the show. There's been great prophecies of your arrival for hundreds of years. I'm so excited. Okay. I'm so pumped to be here. So, so should we start with maybe like a olfactory science 101? Can you set the ground on like how does smell even work? What are the important sort of like? building blocks that we should know, and then we can build up to the next generation and how AI is being applied?

100%. So the chemical slice of reality, all the stuff that's data in the air, we can detect that. Our sense of smell is literally our brain leaving our skull. So when you smell a molecule, whether it's a tree or it's a meal or a drink, like the physical pieces of that thing, enter into your nose and touch a piece of tissue about the size of a postage stamp. And that's your brain, right? So like you were in physical communion with that thing. That information gets turned into neural data, which actually skips all of the normal way stations for the other senses

and goes right to your centers of memory, the hippocampus, and emotion, the amygdala. So our sense of smell is very primal in that regard. So it's like, the reason why when you smell something, you get dragged into a memory and you cannot stop it, you're just like back in high school or you're back as a kid, is because we're physically wired for that. So that's real.

I've always heard that, I've always heard that phrase, smell is the sense that's most tied to memory, but I didn't know if it was just something you saw on like a t-shirt or something. No, literally neuroanatomically true. Target wall art. Yeah, yeah, it feels like target wall art. I don't know.

It's just one of those things that you repeat. They say a smell of pop science. A thousand words. Okay, so that sounds like something that's extremely hard to reverse engineer. Do we have sensors? Because, you know, LLMs, it was so obvious that we had text

that was already encoded into data, into ones and zeros. And so transforming that and encoding it, I mean, it was an incredible breakthrough, but it felt like the text was, the data was already in the computer. And I feel like that's not true for olfactory data, for smell data,

but how are we, do we need to digitize this before we do anything with it? How does digitization of smell work? Yeah, great question. So I was very fortunate to have those guys as my colleagues, I actually spun Osmo out of Google

brain. And so I was there when all that stuff got invented and I brand a digital of action team at Google Brain for about six years before we decided to make it a company through Lux and through GV. And you have it exactly right. Like the internet had been been accumulating for a while. So we had all this text data. So we could basically slurp that down and start building models. We have chemical sensors. They're called mass spectrometers. There's other kinds of chemical sensors, There's mock sensors. There's like a dozen. The history of sensors that can burn chemistry into data is about 100 years old, maybe more.

I mean, a lot of it was pushed forward in the Manhattan Project, actually. Wow. But what we've been missing is a map, right? So for sound, low to high frequency is a map, which lets us build MP3 and speakers and microphones and Spotify, et cetera. And for color, RGB is a three-dimensional map of color. And that lets us build CMOS, CCD, you know, cameras, et cetera. we haven't had the map for smell.

And that's not crazy because there's three channels of color information in our eye, but we know there's over 300 channels of information in our nose. So in a way, we actually did need to wait for artificial intelligence to mature in order to have the ability to extract a 300-dimensional map from data. And that's exactly what we did, starting with our first work at Google Brain. So you've got to go get a crap ton of information, right? A bunch of molecules, what they smell like. We've since collected the largest AI dataset for scent in the world.

That's what drives olfactory intelligence. We have five million sniffs digitized. Over a quarter million physical samples created. We've digitized about six billion fragrance molecules. So all this is like inside of the company because there's literally nothing on the internet. The fragrance industry has done a phenomenal job keeping everything secret. So we built it all ourselves. Remarkable, Jordy.

How are you going to make money on that? It's a good question. So if you go, actually, how can we make money on this? So does TBPN have a scent? Yes, and it's terrible. There's rubber smell in the studio because we have wires here. In the studio, there's like thousands of cords and cables. And the cables smell.

We do a good job hiding them. But we have so much gear going everywhere. It's a lot of rubber, a lot of plastics. And so we had to get these racetracks. Racetracks. They're called to cover all the cables. And it turns out these things smell terrible. A lot.

It was off gas as well. Yeah, they off gas. So we wanted to get these. our viewers, the full CEPA and experience. I think we absolutely do that. It would be like a can that sits on their desk, aerosol, and it would just spray

a rubber smell into the room. So they could experience what we experienced. We could capture it, but I think we should fix it. So really concretely, we raised our series B. We put an additional 70 million in the bank with 2 Sigma leading Lux. The Gong. That was to underwrite building a fragrance factory.

Okay. So we have a robot that's the size of a school bus that makes a new fragrance every 100 seconds. And what we do is we design and manufacture fragrances for brands. Oh, yeah, that makes sense. And so we use olfactory intelligence to design it. So super fast, data-driven, basically, you know, perfect fit for the brand and for the consumer of that brand. And then we actually physically make it. And what leaves our factory is a steel drum of that fragrance while we bill them for it.

Yeah. We also will do end-to-end. So, like, if you want to actually make a physical bottle, we'll actually put the fragrance in the bottle for you. So the full product comes out. So if you guys want to launch a TVPN column or something like that, we could design it for you. I mean, like if you tell me the prompt right now. It should smell like burnt rubber. No, no, no.

We're not doing burnt rubber. Burr rubber. There's some, it smells like disagreement. No, it needs to smell like, like old $20 bills. Okay. From the 1980s and mahogany, the official wood of business. We need it to smell like mahogany mixed with old $20 bills, the smell of money. That's okay, cool.

We've done to smell a money one, which we demoed actually on the New York Stock Exchange for, which is pretty cool. That's amazing. That's amazing. But no, I'll send you. We'll make something. I'll send it to you. Talk about sensor miniaturization. My phone has three cameras and no smelling sensor. Can we swap one of these out?

When you say mass spec, I imagine like a device the size of a living room. I imagine that they are getting smaller. Dishwashers. The dishwasher. Is there a dishwasher? Is there a path to actually shrinking that down to something that's more portable? So, yeah, in the same, there's like many kinds of cameras, right? So the one in the Hubble telescope, not getting smaller.

So if you need resolution, it's going to be big. But you can make tradeoffs. And like when the thing that's reading the data instead of it being a person, it's an algorithm, you can actually make really intelligent tradeoffs, which is what we've done. So we actually have a sensor right now in the size of two shoe boxes. Okay. And I kind of use that metric aptly because we've actually used it to smell fake shoes. So if you're buying a pair of like $500 Air Jordans,

the real smell different from the fakes, we can actually pick that up. That's crazy. It turns out we can. Yeah. Yep. The counterfeiters use cheaper glues, turns out. Interesting.

And the other thing that's interesting is we can actually tell the factory of origin of the shoe 93% of the time. So the smell is a fingerprint. So we're already miniaturizing these devices. Look, the path to get from two shoe boxes to one shoebox is pretty clear. Yeah. We're working on that. To go to something that's like the size of the AirPods case,

there's going to be some like barcourt engineering required. To have it be a component that fits in your phone, there's some breakthroughs like, I can't quite see you through the fog yet. But there's nothing like, look, our noses do it. So there's nothing that Mother Nature is saying of the impossible, but we just got a lot of work to do. Yeah, that makes a lot of sense. What about taste?

How closely is taste link? Talk me through the Somali example. Yeah, so labor is everything that happens in your mouth, you know, that's a sensory experience of food. Taste is not as like 10% of that. It's like what happens on your tongue. Like you ever eat a jelly bean that like plug your nose? Yep.

And you just actually can detect very little of what's going on there. It's because 90% of what you experience is actually called retronasal faction where when you're biting, we're biting on something there's a chimney effect in the kind of almost the steam of what you're eating goes back through your nose and you smell it. Excuse me. And then there's also the texture and everything in your mouth. So we've done tests.

And our OI models, this is from a while ago, we haven't revisited it, we're really focused on fragrance right now, but our OI models actually work on flavor surprisingly well. And so the whole world of flavor is there for us with Moretti, but we're really focused on this particular business. I've seen a couple of these sort of, I don't want to call them niche,

but like vertical AI projects that are not fully generalizable. There's a DNA model also from Google or DeepMind. And it feels like they're starting to get on scaling curves, on scaling laws. Are you at a point where you feel like, oh, if I 10x the computer, 100x the compute that goes into some of the world? I believe Alex is ready for a one gigawatt data center. He can be trusted with that. I would trust you. But how universal do you think scaling laws are?

Is there a scaling law here? Is it database? Is it compute-based? Both? How are you thinking about it? The bitter lesson's real. The better lesson's super real. I always think about technology as S-curves, right?

And like, what's driving you up that S-curve? And then how can you hop on the next one? Our current S-curve is data, which is why we're maniacally focused on, like, generating a ton of data. Like, we have a giant fragrance robot that spits out a ton of fragrances. We have mass specs running 24-7. We have sensory panels, both domestically, have a building of people that just smell all day abroad.

And we ship them great some stuff to smell. And that's how we get that. of five million sniffs, right? So data, data, data. The size of the models is not a limiting factor right now. And it will be at some point and then switch to the other S curve. Yeah, yeah, because you don't just have like the open internet to scrape because there's not an existing data set. Totally double-edged sword, right? So we had to make it all, right, which is really hard. But also nobody else has it because we had to make it all and had to learn a ton of stuff in order to do that at scale and efficiently and all that stuff. Yeah. Where is the, where is the business today?

I mean, you've raised money. It seems like there's, you know, monetization opportunities for sure. Are you fully in commercialization? Are you still in research? Is it half and half? Like, how do you think about raising more money over time and just growing the business?

Yeah, so we're always going, like we started with like this curiosity-driven drive to figure out how to digitize snow, which is like a pretty wacky thing to do. So we're always going to be trying to push the edge here. But look, we have a factory. we manufacture fragrance for brands. We did this commercial, kind of R&D to commercial transition last summer, and we're kind of almost at the end of that,

and we built a manufacturing organization, we built a sales organization. We have some really amazing partnerships with some big brands, and we're making fragrances for brands. You can go into Target and buy a product that has our fragrance in it today. And so we're scaling this part of our business.

We're still placing bets on the future, though. Right. So I think we've got really the tiger by the tail in this, it's a whole other conversation. Sometimes you should come to the factory in New Jersey and see how it operates. But like the fragrance industry is wild. We've got a lot of work to do there,

a lot of opportunities, so we're focused on that. Amazing. Well, congratulations and thank you for the work that you do. We think it's so important. One of the most interesting companies we've ever learned about on the show. Yeah, true science fiction. Awesome.

I love it. We're trying to make science fiction into science fact, but like open invitation to come see how it all gets made. It's pretty crazy in person. So come to the Willy Wonka chocolate factory where all this stuff happens. I would love to. We'd love to.

Thanks so much. So great to meet you. Come back on soon. Yeah, we'll talk to you soon. We'll be good rest of your day. We're running a little bit behind, but up next we have Spiros from Resolve AI, raising a massive round to build AI that runs production systems.

Let's bring in Spiros. How are you doing? Hello, guys. We'll be here. Welcome to the show. Sorry, we're running a little bit late. Kick us off with an introduction on yourself and the company. I'm one of the founders and the CEO of Resolve AI were building agents that can help you

debug and run production. Think of it as the counterpart to coding agents that produce all this code and our agents are there to support you. Okay. Are you always, is your customer always like deeply in the throes of vibe coding, has rolled out agentic coding across many organizations? Who is the target customer? Do they have to already be deep in the agentic coding wave

to really get the value here? They don't have to, but the two are correlated. Like anybody who runs a large software system has this problem. The only solution we have so far is humans manually solving it, right? Using the tools, being on call. Of course, now AI allows us to automate all of this. But I would say this is true, it was true before. Now with all the AI generated code, it becomes a necessity, right?

So we see strong correlation between the two often. Yeah, and what are customers coming to you asking? Is it, I want the code that's, you know, written, we're writing way more lines of code. We want to be more readable, or we want it to be more secure, or we want it to be more performant, or all of the above. The way to think about it is like, for anybody who's delivering their business through software, look at some other customers, Coinbase, Salesforce, MongoDB, right? To them, reliability is of paramount importance. If anything goes wrong and affects customers, it's a big problem. So resolve becomes essentially the first level of defense that captures any problem that happens in production that can affect end users.

Yep. Gives you a resolution and a fix, let's say, so you can accelerate that loop, right? And it doesn't take too much human effort, but more importantly, it doesn't cause impact to customers. What is, like, I mean, the company is now over $1.5 billion in valuation. what has been like the key to growth? Is it just product-led growth? Do you have a big sales team? How are you actually scaling the business

as you scale the valuation? Yeah. So this is a very big problem, right? Anybody who has, as I said, delivered business or software, is facing this issue. Yeah. And whether you're a CTO, you know, who pays for, let's say,

developers to focus on reliability, or whether you're an individual that has to solve this problem, you'd rather have AI do it for it. So we've seen like huge amount of demand from day one since we launched the company a bit more than a year ago. And we've seen it coming from both big and small companies. We primarily focused on larger enterprises because we think there is a lot more complexity. You know, given the complexity of their software.

And, you know, most of the growth, I guess most of the, let's say, the demand comes inbound to us because it's a well-understood problem. And of course we have like both product-led approach, let's say, but also sells-led approach as we work with large customers. as we work with lots of customers. Yeah. In some ways, like, the naive approach would be, okay, just appoint a typical AI agent at the code base and just tell me, you know, where the fault lines are. But I imagine there's some special sauce

in the engineering to understand knock-on effects that can happen across a large code base. Are you actively working around context windows or creating like a special harness to understand these problems that can come up before they do? Yes, so think of it, like, we have a production ID, basically, right? The same thing you have for your code, we have it for all your production systems.

Production involves code, it involves, let's say, telemetry logs, metrics, tools like data dogs, Planck. It involves AWS, right? So you have to deal with all of these, not just code. And then we also are training our own models now to improve, let's say, at the state of the art, let's say, right? You can go far enough, let's say, with, you know, a good harness, you know, and a lot of work, let's say, on the genetic front.

But now, and we just announced together we're funding that we're building a lab to focus on actually, you know, training our own models for this domain. Sure, sure. How, what is, what goes into getting like relevant data or actually nailing a specific model for this? Because I imagine that you have some great clients, they probably don't want you training on their data.

Right. if you just grab some open source code, it might not be as complex as like the Coinbase mono repo or whatever they have going on over there. So how do you actually create enough training data to justify a special model? What is important here to understand is like, the training doesn't happen like on code per se.

What happens on is actually the action a human takes to perform a task for the most part. Yeah, yeah. And we're talking about very long kind of, let's say, planning tasks here, right? it might take like many, many iterations, looking at code, looking at data dog, looking at infrastructure. And this, generally speaking, this is not in the training set of models. So, in software, let's say, generally, is both deep and wide domain, right?

So I think if you actually focus on building a model for the types of problems we're trying to automate in how you run in debug production, I think you have a lot of gains, both in performance, cost, but even like quality of outcomes, right, and that's our goal. And I would say, you know, the big labs make it sound, make it look like it's, impossible for anyone else to build a model, but I don't think that's the case. And, you know, that's what we're seeing ourselves with our investments. Yeah. How do you put together such a low dilution round?

Yeah, tell us about the round. I want to hit the go. The 40 on one and a half billion. So it is an extension with just didn't necessarily be a T. We just did the A at a billion dollars like two months ago, right? And I would say, resolve. There we go. Sorry, continue.

There's always, essentially, in many ways, created this market, right? Like AI for production. Sure. And I think it's well understood by investors. It's also proven, given the customers we have. Yeah. So, and we're also a very ambitious company, right? Like, we are obviously trying to build the agents and the models for this domain.

And we have a lot of traction. So, I mean, as simple as that, right? Like, there's nothing you can do to create a load dilution out other than be very successful, in my opinion, these days. That's a great answer. That's a great answer. Step one, be successful. I love it. Step one, focus on building a business, right?

This is my first startup as a founder. I made this mistake many times before, right? Thinking that raising money is success. It's not. It follows real success on the product. Yep. Yeah, no, that's 100% right. I love it.

Well, thank you so much. Congratulations on the new round. Yeah, great having you on. And great having you on the chat. I'm excited to watch you guys. Thank you. We'll talk to you soon. Have a good day.

Goodbye. Up next. We have Carolina Aguilar from InBrain Neuroelectronics, building the first inhuman study of graphene brain interfaces. What's going on? Welcome to the show. How are you? Thank you. Very good.

Thank you for having me. Please, since this is the first time on the show, introduce yourself in the company a little bit. Yes. My name is Catalina Aguilar. A lot of people call me Carolla. I am the CEO and the co-founder of In Brain Your Electronics. And we are a graphene-based brain-computer interface, the robotics company that actually is developing the most intelligent interface

between the neural system and AI to restore health for billions. Okay. So walk me through brain computer interfaces and the decision tree that got you to graphene specifically. I'm familiar with like the first decision is probably invasive versus non-invasive. We've talked to a number of founders that have taken either approach. How did you confront that first question? Yes. Well, I call them implantable and non-implantable systems.

Yeah. And in our case, we're an implantable company. We believe that the real signal processing that is going within the neural system is actually deeper in the brain and to listen carefully to what it says, the neural system says, being able to decode it, but also modulate it, we need to be close to those neurons and interact with those neurons firsthand. Okay. So when I hear modulate, it sounds like not only processing information that's coming out of the brain, but also potentially writing information back into the brain?

Is that the long-term vision? Yes. And this is the magic of graphene is actually about reading and writing, very effective. at micrometric precision within the brain. I think that's why we took, let's say, higher risk to get an advanced material into this funnel because we see that the benefit is incredibly impactful. Okay. What are the most near-term commercial applications?

Yeah. So the Morgan Stanley report stated the market in $400 billion, and we thought that we needed to bring a platform with three product verticals to actually penetrate such a big market. So we are creating three products. One is, let's say, not implantable, actually. So it's a semi-chronic platform, kind of like the modern Eutra. It's like 100 contacts of graphene that can read and write. We went into two more an epilepsy resection at the beginning, and that one is.

pretty close to commercialization. We're almost there. The second product is the implantable platform for the brain. So this is a implant on the brain for Parkinson's disease. So we didn't do, sorry, assistive BCI because we saw a 1.8 billion market that is sub-optimal that we could actually displace very easily with this technology. So we decided to go therapeutics into Parkinson. And the third one is the same platform, but instead of a, let's say, brain sensor, we connect a

baggage nerve sensor that is actually able to decode all the fibers that go into the different organs. So we have a therapeutic target for each of the organs just by targeting that nerve in the neck. What about the actual implantation process? We've followed from NeuroLink. They had to build a whole robot just to drill into the same. skull, it's incredibly high precision. Are surgeons capable of implanting this at this stage, or will there need to be other robotic devices that are developed to actually deploy this technology safely? It's an excellent question. I'm coming from Metronic. I spent 10 years in

neuromodulation and another three in diabetes. And I think in the future, when micro-robotics are ready, we will have a very close relationship between our interfaces and micro-robots that probably can deliver this implantation in 30 minutes. But today, when there is not micro-robots and we are not Elon Musk, we decided to actually have our platform ready for the current surgical workflows that today exist. So we are not changing much from the neural migration workflows. And it's an easy procedure. Two hours, one or two hours, you know, it's enough. In the case of the neck is 45 minutes. Wow.

Wow, that's very impressive. Well, congratulations on all the progress and thank you for the work that you do. And thank you for stopping by the show. Yeah, great to meet you. Have a great rest of your day. Cheers. We'll talk to you soon. Up next, we have Jake from Blue Energy.

He's the co-founder and CEO with a massive raise. It's a gong breaker. Jake, how you doing? Welcome to the show. You guys, I'm doing well. I got a feeling you have the biggest number for us. I think you have the biggest number. Kick us off.

How much have you raised and then we'll get into what you're going to do with it? But tell us about the financial situation for the company. We have announced a $380 million raise. Okay, go ahead. And what will you be doing with all that money? Yeah, so our focus, we're really unique amongst the field of nuclear players right now. Our focus is on building the world's first project financeable nuclear power plant. So we're using this funding to actually put deposits down on long lead equipment, as well as

finishing out the engineering and development licensing on some of our first sites. Does that mean like less R&D risk or more in like the GE or Westinghouse territory, more like, you know, going with products that have been de-risk, but it's very expensive and maybe the underwriting is different. time around or are you working on an entirely new reactor design somewhere in the supply chain? No, you had it exactly right. We are not a reactor designer. We're a developer, but our technology is the proprietary approach by which we go about building the plant. So what bugged me and why I started the company was I had a lot of friends in nuclear space designing really exciting new reactors, and then you have a lot of incumbents in the space who are working on, you know,

kind of the same old technology that we've been operating safely for 70 years. But nobody was focused on the core issue of how do we build nuclear on time and on budget. So I grew up in a construction family. I used to be a draftsman from my father's architecture firm. So I just grew up around a lot of construction, did my nuclear engineering physics degrees in the space and just felt like there isn't, there hasn't been anyone really focused on the root cause issue. So what we're doing is we're borrowing best practices from LNG and offshore oil and gas and offshore wind to pre-fouther. fabricate everything at existing oil and gas, fab yards, and shipyards. And then we barge it all as a prefabricated system on the order of 1,000 or 2,000 tons to the operating site.

And then basically they're just installing it like giant Lego pieces. But what that allows us to do is bring a lot more debt financing to bear. So we're not taking a lot of reactor technology risk to start in the beginning. We're using mature light water reactor technology to start. But we'll happily work with the Gen 4 reactors as, they as they mature. Cool. Take me through. I feel like you've been wanting a company like this. Yeah, I've been wanting this for a long time. I've been John's, John's point has been copy paste. Yeah, it's like, hey, we know how to do this.

It works. So this is, we don't need to like reinvent. I mean, it's great if we want to reinvent the wheel. Yeah, we need the next gen tech. New reactors, but also more of the current done. Let's just build some. Yeah. So my, yeah, my question is about Vodal, uh, lessons from the Vodal project. Uh, what, what do you think did well that you want to copy, that you want to learn from. What, if anything, do you want to do differently? Yeah. So to put some stats on Vogel, it, like so many other nuclear projects in the West,

ended up being about two to three times over budget and behind schedule. But when you double click on where that cost was, you realize it wasn't actually in the reactor technology or the equipment. It was over 40% of it was just the construction overhead. So it was the cost of training and relocating 10,000. thousand skilled workers to book to the site Fed Vogel. You know, think about the cost of training, relocating their families, retaining them once they're trained because data center projects are trying to steal that talent.

You have to set up a nuclear quality assurance program in the field. So there's all this overhead. It's basically like building a small town. And then the hope is that you'd be able to move that, you know, traveling circus around from site to site. And then a third of the project cost was just capitalized interest on debt because it took over 10 years to build before it started generating revenue. So these are the two big problems we're trying to address is we are moving most of that work offsite.

We're keeping the workforce centralized at the Fabyard and the shipyard where they already are. So we can start to put nuclear into a learning curve and drive the cost down over time akin to what we've seen in wind, solar batteries and gas turbines. What they did well was it was a mature light water reactor technology. It's a passively safe reactor technology. they really pushed the world forward a little bit in the licensing space and steel composite structures, which we're looking into as well. They actually had, this is not well known, they originally wanted to barge it in up the Savannah River, but they had to then dredge the Savannah.

They would have had to dredge the Savannah River for miles, and that would have become part of their environmental impact statement. So they ended up, it became such a regulatory and permitting nightmare that they gave up. And they said, all right, let's just truck it in. and then they had to truck it in and build a module assembly building on site. So they ended up doing all the welding on site. Yeah. Just a nightmare.

Nightmare remodel. Very interesting. I'm fascinated. Where's the company base? Where are you guys based? We're in Chevy Chase, Maryland, pretty close to NRC headquarters. And then we've also got a big presence in Edinburgh, Scotland, where there's a lot of offshore engineering talent, particularly from like kind of the history of shipbuilding and off for oil and gas.

Yeah. And then we've also got an office in Houston also kind of offshore oil and gas capital the world. Okay. I read a blog post about one of the potential problems or stumbling blocks that nuclear projects run into. And I want to reality check it with you. The thesis was basically that we have a reactor design.

We have a, you know, there's infrastructure around that. Cement needs to get laid. Pipes need to go here. and there, but oftentimes the regulation will change while the project is underway. And so in order to stay ahead of the changing regulation, you might have to jackhammer a bunch of concrete and move a pipe to a different route because the regulation has changed. Is that real? And is there anything that we have done or can do to get to a regime where the regulation is more locked and deterministic so that I imagine you're not going to build this overnight, but if it takes you a

couple of years, you know that the contracts that you put in place, the plans that you put in place today will hold and you won't face a massive delay. Yeah, so that was another one of the big learnings from Vogel. Vogel was the first and still today, I think the only project that did a combined operating and construction license, which means once they locked the blueprint, they really were not allowed to make changes to it during construction. So every time they encountered something and said, oh, we need, you know, the craft labor wound the rebar clockwise instead of counterclockwise. You know, they had to jackhammer it up or they had to go and re-approve it all.

And there's just a, there's a long list of things like that that they encountered. So one of the things we're doing is we're following a slight of different licensing process, the original licensing process of part 50, whereby we're going to incrementalize it so that we don't have to encounter that rework, that kind of regulatory triggered rework situation. But also, because we're following this prefab approach and we're moving 80% of the CAPEX into a fixed price contracting environment with these fab yards and shipyards, it forces us to go to something like 60% detailed design up front and locking those designs because that is what is going to be coming in prefabbed from the fab yard. So it's sort of baked into the strategy. But really this is

about taking a lot of those lessons learned and making sure we don't make the mistakes of the past. But I'll also say we've never had a more supportive regulatory environment than we have for right now. This is a critical juncture in the history of nuclear power that we can take advantage of with where the NRC is presently at. What is the power output for the first reactor that you're targeting to bring online? So we are focused right now for the first project using light water small mazer reactors, which the power range of the units we're looking at, between 50 and roughly 300 megawatts per unit. Yeah.

Each site we're targeting doing is going to have multiple units. So it's going to be a gigawatt to a gigawatt and a half per site because multi-unit operations. That makes a lot of sense. It is important. Yeah. And it helps drive down costs. And then are you already sharing a timeline? Do you have an optimistic scenario, a base case, a bear case?

I'm sure you get asked this all the time is the worst question. but we talk to a lot of nuclear founders and we hear a lot of 2030s and there's a whole bunch of projects with hyperscalers and big tech companies that are looking at 2032, 2035. It's exciting. Better, you know, 2032 than never. But do you have anything to share on like the timeline of rolling out new nuclear capacity in America? Yeah, we'll be announcing things very soon. But what I can share on the dates, and this is actually another unique thing we're doing, part of our strategy is we're pursuing this thing we call gas to nuclear conversion.

So we're actually going to be building half the nuclear plant right away. So the whole nuclear steam turbine system set up for nuclear steam conditions and quality. And we're going to fire it early with two combustion turbines. It's a two-on-one combined cycle. So it's kind of a Frankenstein combined cycle. We've actually gotten the NRC to buy off on this methodology through a Topka report recently. So that allows us to actually project finance half the cap. for a first SMR, and then we will spill the reactor and splicing the steam and switch it over

from gas steam to nuclear steam. So that actually accelerates our commercial operation date with confidence. So we're looking at generating first power in 2030, 2031, mostly driven by gas turbine delivery dates today. And then our first nuclear commercial operation, we're looking at 2032. Okay. So is that switchout possible at any legacy natural gas infrastructure site in America? currently? Because that seems like an environmentalist dream. I'm not ready to say yes or no. Yes.

I think this opens up a whole new world of fossil to nuclear convergence, which we think is an important precedent to set. Yeah, it seems huge, if possible. But I imagine that, you know, it's not exactly USBC on both sides. But hopefully one day we can build the adapter. That's right. What we're really focused on is, you know, there's a lot of announcements out there.

a lot of sometimes noise of what, there's a lot of exciting things that happen in the nuclear sector. We think we've got the first project, financeable nuclear project, and the first one that's going to power, it'll be a new build that powers a new AI data center. So we're excited about that, and we think

our timeline is credible, is aggressive, but credible and defendable. And we've got the right set of partners around it to make it happen. That's amazing. Don't use the word data center. We're using the word super computer. They're super computers. They're super computers now.

No one likes the data center. Everyone likes a supercomputer. Yeah. Anyway, thank you so much for taking the time to come chat with us. Great to meet you, Jake. I'm sure you'll be back on soon. Good luck with everything. We really appreciate your approach.

It feels like you're making plays. And I like how pragmatic and but innovative the approach is at the same time. It's great stuff. Thank you. We'll talk to you soon. Goodbye. And we will close out on this. I need your reaction.

John, Ferrari's first electric car is priced at The low price of $650,000. An absolute steel. They're giving them away at that price. It's electric, right? So you don't have to deal with gasoline? You don't have to deal. Yeah, you save a lot on gas.

You don't have to deal with all the noise that comes out of a V12. Yeah, no noise, and you save on gas. Yeah. Oh, well, yeah, I mean, if you're saving on gas and you're driving, I mean, if oil keeps spiking and gasoline goes to $1,000 a gallon and you're filling up, up every week. You could easily be spending millions of dollars a year on gasoline in a normal car. So there's potential cost savings here. So it's sort of a more you buy, the more you save situation. I think that Ferrari Luce. There's really going to be a like what kind of Ferrari

client are you moment. No, I think it'll be a status symbol. The depreciation, if you see someone with this, you know they can eat 300 grand of depreciation. That and you know that they are that they are high on the list for the F-90. They are working their way up, buying in now. And when the F-90 comes out in a decade, they're getting a call. Yeah. They're getting a call for sure. Yeah, very interested to see how this does in the market.

And the good thing is if you are excited about the Luchet, but you're not excited about paying $650,000, you will have an opportunity to buy them for far less than that very, very quickly. Probably. Probably. But thank you for hanging out with us today. It's been an honor and a privilege. to be here with you. We hope you have a wonderful afternoon. Leave us five stars on Apple

podcast and Spotify. Throw that flashbang. Sign up for our newsletter. TBBN.com. Goodbye.