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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
You're watching TBPN. Oh, no. It's Tuesday, 04/21/2026. We are live from the TBPN Ultra, the temple of technology, the fortress of finance, the capital of capital. Massive, massive news.
Speaker 1:Tim Cook to step down at Apple. This broke yesterday. Gurmanager had the scoop, of course. He's coming on the show later today, but it's on the cover of The Wall Street Journal today. Heavily predicted, often debated.
Speaker 1:It's a time to reflect on Tim Cook's legacy and what's up next for John Turnis, the long time
Speaker 2:We just say incredibly well executed. Incredibly smooth. They sort of telegraphed it. It wasn't a surprise. Yes.
Speaker 2:They was already fully priced in. Yes. I personally was hoping that the market would give Tim Cook a 21% salute.
Speaker 1:Yes.
Speaker 2:Where when the news went out, it just immediately nukes 21%.
Speaker 1:Massive red candle. Let everyone know this is we love him.
Speaker 2:It's a sign of respect.
Speaker 1:We will miss him.
Speaker 2:Of course, rebound immediately. Yes. But I think that's something that
Speaker 3:Yes.
Speaker 2:The market collectively Yes. Should try to do for
Speaker 1:Yes. More symbolism in the candles for sure. Chartology is really the key thing.
Speaker 2:That's 21% silver.
Speaker 1:But of course, what is Apple at right now? Is that is are they moving at all? Down 3% today, two and a half percent, but up 3% over the last five days. Still nearly a $4,000,000,000,000 company. They're doing fine and they're cooking.
Speaker 1:So let's go through a little bit of the review of the news and some the previous discussions that we've had around Tim Cook and John Turnis because we're gonna be learning a lot more about John Turnis. He's probably gonna do a lot more content, 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 Gurman, who's coming on the show later today, predicted that John Ternis would succeed Tim Cook as Apple's next CEO.
Speaker 2:Let's let's just pull up this clip. We have some credit
Speaker 1:He the didn't predict it on our show first. I think he scooped it and posted it. I But this
Speaker 2:this was back in January. I dropped the clip. The
Speaker 4:crux of
Speaker 1:the argument was twofold. Ternus' relative youth among a pool of potential successors.
Speaker 5:He's 50. Play it. Mhmm.
Speaker 6:Everyone else in the Apple executive team, late fifties through their mid sixties
Speaker 1:Yeah.
Speaker 6:Turning 66 this year in the case of Tim
Speaker 7:Cook. Mhmm.
Speaker 6:You're Apple's bored. You like continuity. You like an insider. You like people who know what they're doing and have been there for a while. They know where the bodies are buried.
Speaker 6:Okay? These guys are all have hundreds of millions of dollars, if not more.
Speaker 2:Pause. I love Mark Gurman
Speaker 8:so much.
Speaker 1:He's the best.
Speaker 2:He's truly the best. He's
Speaker 1:coming It on is.
Speaker 2:He's coming on in in forty Forty five minutes. Continue.
Speaker 6:Yeah. At 50, he's the only one Mhmm. Who is if let's say Tim Cook hangs out another three to five years
Speaker 2:Yeah.
Speaker 6:You're not gonna appoint another CEO who's 65 Yeah. 70 years old
Speaker 4:Yeah.
Speaker 6:He's the only guy. Mhmm. Apple, they get vast majority of the revenue from hardware. He's the hardware guy.
Speaker 4:Yep.
Speaker 6:Have they screwed up any hardware since he's been in charge? No. No. He's a steady hand. Knows what he's doing.
Speaker 6:He's really the only choice. Mhmm. You know, there was this New York Times report a few weeks ago basically saying that it could be Greg Jurewicz, it could be Eddie Q, it could be Dierdre O'Brien, it could be Craig Federighi. It's for sure not gonna be Craig. It's not gonna be Dierdre.
Speaker 6:It's not gonna be Eddie. It's not gonna be Jaws. The only category that makes sense is an operations person because you look at the current c e 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.
Speaker 6:He's done obviously a fantastic job for shareholders and employees and and what have you, would have been Jeff Williams. He was the COO. So Sabi Khan, he was named COO 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 Ternis or or Sabi or or someone completely out of left field. Mhmm.
Speaker 6:I don't think this is imminent. Mhmm. So we'll see what ultimately happens, but all signs are turning towards Ternis.
Speaker 1:Mhmm. Mhmm.
Speaker 6:Everyone has an opinion that Ternus is gonna be the next CEO fine. From you. I've been shouting this from rooftops the last two years, but no one has given evidence. What is this based on? Right?
Speaker 6:Has there ever been a baton handoff? Is he getting more responsibility?
Speaker 2:Well They have a bit like a big baton?
Speaker 1:You got one of these and then You know what?
Speaker 6:You have you have white smoke coming out of Sure.
Speaker 1:Well, Texas. It's smoke. Very environment. Maybe. So Is that the end of the club?
Speaker 1:That was scary.
Speaker 6:You know,
Speaker 2:maybe one of the large baton. Like like we have our scoop. Yeah.
Speaker 1:Oh, Mike Gurman, the scoop inator. He's a scoop dog, scoop athlete, the scoop, the scoop. The scoop is on fire. We're very excited to have Mark Gurman joining in just forty minutes. What what what a great a great run he's been on reporting this story.
Speaker 1: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 Turnis will take the reins of the company. Mark followed up with a scoop with internal memos from both Cook and Turnis announcing the transition. I I don't I mean, I I understand I I don't I don't know.
Speaker 1: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? I'm I'm Tim Cook's healthy. He he's he's going
Speaker 2:Everything to date was a warm up.
Speaker 1:Yeah. It's time
Speaker 2:to go on the actual run.
Speaker 1:That's I I would I mean, I totally understand. I
Speaker 2:got another 10
Speaker 7:x. I
Speaker 2:mean, NeoLab. I'm going to I'm I'm I'm taking us to 40,000,000,000,000.
Speaker 1:Yeah. I don't know. I 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 be in the arena shaking hands, kissing babies, doing product launches, you know, being in DC, getting wrangled into things. Like, Buffett can be more like hands off and just sort of read the news, review the financials and and delegate. With
Speaker 2:some liquidity Yeah. If needed.
Speaker 1: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 like the idea of of just just locking in and being like, oh, yeah. I'm 65.
Speaker 1:Everyone expects me to everyone expects me to step down. But I got another thirty 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.
Speaker 1: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 1. 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 financials perspective, has to begin with the numbers. And he says that the numbers are extraordinary. Cook became CEO of Apple on 08/24/2011.
Speaker 1:And in the intervening 15, revenue has increased 303%, profit surged 354%, and the value of Apple has gone from a mere $297,000,000,000 to over 4,000,000,000,000, a staggering 1251% 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 40 x increases in their market caps. This is from Brandon Gurrell's newsletter at tvpn.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 IPO ed are no longer even close to the top of the pack anymore.
Speaker 1:And Brandon cites Xerox, Motorola, Texas Instruments, IBM, and HP, which all fell by the way iconic names. Over the past thirty years while Apple built, the biggest consumer hardware company on the planet and thrived in the public market. And I was 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 the the the Mag seven. All all of the Mag seven have done fantastically well over the past fifteen years during Tim Cook's, tenure.
Speaker 1:Did he do anything special? Is he is he in a different category in some way? And maybe not when you look at when you look backwards from the current Mag-seven. 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 377,000,000,000. That was, you know, big, huge, the biggest company at
Speaker 3:the time.
Speaker 1:Then Microsoft Yeah.
Speaker 2:You got the 02/18 what what Yeah. Their peers were Yeah. At the time where he took the Yeah.
Speaker 4:And to
Speaker 1: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 didn't make the cut in that in that acronym. That has since changed, of course.
Speaker 1: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-ten of 2011, and now they are not in the Mag-seven, 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 iPhotos app is hard to use.
Speaker 1:But where it matters But
Speaker 2:we give them credit on Genmoji. No.
Speaker 1: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.
Speaker 1:I got a bad one. Yeah. And I got to take it back. And that's never happened. The quality control is flawless.
Speaker 1: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. Yeah. And I think that should be celebrated even though the new
Speaker 7:features are He's bound
Speaker 2:to be under appreciated Yeah. Because he wasn't he wasn't the visionary that that that Steve was. Sure. But he also never I don't think he ever wanted to be Yeah. Seen in that way.
Speaker 4:Yeah.
Speaker 2:But the consistent operational excellence over almost two decades Yeah. Is almost unprecedented Totally. At this scale. Totally. It is Yeah.
Speaker 2:Just just the way you put it. Right? I The the same the same experience that I had getting a new Apple computer Yeah. As like a teenager Yeah. I have today.
Speaker 2:Yeah. It is actually almost remarkable how similar the experience is. You open this wonderful box, you get a great device Yep. That works for a long time. Yeah.
Speaker 2:And and you still get that today. So the the consistency and, yeah, I think I think he will just get more when people kind of process the run, over time, he will just get more and more respect.
Speaker 1:Yeah. And a lot of the 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 a line there. They've, of course, ramped up their 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.
Speaker 1: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.
Speaker 1:Of course, it it's going to happen. The
Speaker 2:in the chat says, not a single product recall under Tim Cook. Is that possible?
Speaker 4:Wow. I
Speaker 2:think that is incorrect.
Speaker 1:What did the recall?
Speaker 2:Says they recalled a 15 inch MacBook Pro in 2019.
Speaker 1:Did Bengate? Did Apple
Speaker 2:AC wall plug adapter in 2016, 2019. Yeah. Battery gate service pro.
Speaker 1:They've had some they've had some back and forth. But but but 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.
Speaker 1:And then there's the Apple Vision 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.
Speaker 1:I think one of the lead staff members on the Apple Vision Pro project was from the Dolby Cinema team, which had done Dolby Vision and and some of the the actual theater build outs. And so they were able to bring that experience and understand what actually makes for a great movie watching experience in a premier, cinema and how can we recreate as much of that as possible in VR. Still, 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 Bans, which might be the more prudent business strategy.
Speaker 1:But I still like these incredible investments in VR. What are laughing at?
Speaker 2:Josh over at semaphore Yeah. 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 any of that getting any extra attention right now. Yeah. 5,000 likes.
Speaker 1:Yeah. It is interesting. Yeah. Ternus is about as far as you can be from the Apple TV services organization. But I don't know.
Speaker 1:I talked to a I talked to a filmmaker in Hollywood, a very successful filmmaker, like, 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 movie studio understands that it is impossible to predict the perfect success and have the level of polish that comes from these slight iterations
Speaker 2:to I think you could, though. Apples.
Speaker 1:Yeah. Yeah. Bill 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.
Speaker 1:And, running that risk was always a was always a problem. But I feel like Apple navigated it really, really well, especially with the f one 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 scatter shot, more reality TV, more, you know, sort of silly projects that might put, you know, might entertain viewers, but don't fully they 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. Yeah.
Speaker 1:Anyway, continuing, Mark Gurman said on TBPN 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' 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. Ternis, who has a background in mechanical engineering, has been working at Apple for twenty five years Overnight success. And most recently led hardware engineering of all of Apple's products.
Speaker 1:He played a crucial role in the development of Apple AirPods, obviously a massive success, And he redesigned Apple's computers to use company designed chips instead of Intel's, a massive move that extended battery life and improved performance.
Speaker 2:So Ternus is And set them up very well for AI. AI.
Speaker 1:Yeah. Turnis 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. Turnis will have to will have to somehow manage this dynamic. Ben Thompson wrote about it in November 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 will be continually increasing from the current level where Yeah.
Speaker 2:Mean, number a number of people have have talked about, you know, what are the challenges that that Ternus is inheriting. One, supply chain. Right? Kind of like, you know, stuck in in China Yeah. In a big way.
Speaker 2:Yeah. Presents a pretty meaningful, know, risk to the business. Yeah. And then sort of like overall dependency on on on Google on some of these key products. But Yeah.
Speaker 2:Without further ado Sure. Let's bring in Let's
Speaker 1:bring in Howie Luthers to table. 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.
Speaker 1:Tell us who you are.
Speaker 8:Alright. Howie Liu, co founder and CEO of Airtable. Yeah. Now also maker of HyperAgent, part of Airtable. Cool.
Speaker 8:I've been doing this for twelve, thirteen years now.
Speaker 1:Thirteen years. Overnight success. Give us the backstory. Take us from college Yeah. Through early career to the first the founding moment.
Speaker 1:Yeah.
Speaker 8:Yeah. So in high school, kinda got into programming. Like, my dad had this c plus plus book. Mhmm. Left it in this, you know, corner of the house one summer and
Speaker 1:I was
Speaker 9:super bored.
Speaker 1:C plus plus. Learned it. I mean,
Speaker 8:this is, like, 2003 Okay.
Speaker 1:Okay. Yeah. Was a pre Python for the
Speaker 8:mean, Python was was around, but really use it.
Speaker 1:That wasn't the jumping off point.
Speaker 8:Java and stuff. Early days for even, like, web apps.
Speaker 1:Right?
Speaker 8:Like, Rails didn't exist, like, that stuff. So learned c plus plus. Sure. Thought it was kinda cool. Yeah.
Speaker 8:And then started thinking about, like, how do I turn this into, like, a real career? Because it 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 o six.
Speaker 8:That's like the first class. Literally the first class. Like, guess o five. No. Because I I remember like I saw Hooped Yeah.
Speaker 8:Someone's first company and I was doing research like I wanted to do a similar type of company Yeah. Or product and I was like nope, you know, I was a nobody. College, didn't know anything. And through that, like found out about Luke and I was like, damn it. Somebody's already got this this this idea and then learned about YC and like Sequoia.
Speaker 8: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 eTacz, like contacts with an e. Okay. It was like a personal CRM product. Oh, yeah.
Speaker 8:Yeah.
Speaker 1:They were like, oh,
Speaker 8:this is a big problem. Everybody has problem. Yeah. I'll fund it right away. Am
Speaker 1:I correct in in my my take has always been Yeah. The people that clamor for a personal CRM really just don't realize that their friends are people that they do business with. They should either just use a real CRM
Speaker 4:Yeah.
Speaker 1:Or just don't and just be friends.
Speaker 8:I mean, it's yeah. I think I think it's like a very unique target audience for whom it's a very high pinpoint. So Sure. Think there's, a market there, but, like, it's a very, like, power user, prosumer audience. And the punchline of it, though, was that, like, after a year of work, we, worked on this thing, raised some money, you know, hired, a couple people.
Speaker 1:Yeah.
Speaker 8:Yeah. And then we kind of realized, like, I sort sort of realized, like, I think it's a more niche market than we set out to to go after. Mhmm. And we had some, like, different acquirers come knocking, like Salesforce was one of them, like, also big, like, consumer Internet companies who wanted to just buy us for talent. Sure.
Speaker 8:And, you know, to me, it was like
Speaker 2:And what this is 2,000
Speaker 8:We and were winner 2010, that batch. Oh. And then the acquisition talks were like 2011, basically. Okay. Late late twenty eleven.
Speaker 8:And, you know, we kinda got to this point where I realized like, I wanna work on a really big problem, like a meta problem. Not like, here's one small niche for, like, some people.
Speaker 1:Yeah.
Speaker 8:But instead, like, what's, like, the underlying problem, which is, you know, you could actually build this whole CRM
Speaker 1:Yeah.
Speaker 8:With, an app platform. Right? Sure. Like, you really want something that's a lot more just configurable and customizable. And so we took an acquisition by Salesforce Okay.
Speaker 8:Worked there. And like for me, the big light bulb moment was, you know, Salesforce is one big data
Speaker 2:What's Benioff like on all hands?
Speaker 8:I mean because he's
Speaker 1:he's he's like he's
Speaker 2:an electric on this many
Speaker 8:all like, all hands were quite infrequent at Salesforce at the time. But like, went to like their their big sales kick off that year. Yeah. I mean, Mark is like a very smart guy Yeah. And also a very like commanding presence.
Speaker 8:Like he's a physically like you would if you met him like on the street and didn't didn't know who he was, like you'd probably think he was like a line backer in the Like he's massive. Yeah. He just like he exudes charisma. Like Yeah. Even in like a quiet small room like he'd take meetings in his house.
Speaker 8:Like I'd go over with like you know some of the other like He's
Speaker 1:the sales guy's final boss.
Speaker 8:I mean, but like, not like,
Speaker 2:he's like, going he's head to head with him.
Speaker 8:It's over. I get it. Forfeit. Best salesman ever. But he's like, he's just got such a presence even when he's not like like booming, you know, out loud like on a stage
Speaker 4:like Yep. When
Speaker 8:he's making the
Speaker 2:the dolphin sound when he
Speaker 8:goes Oh. I don't know about that one but I didn't get to see that part but
Speaker 1:That's the whole genesis in Salesforce. Apparently, he came up with the idea while he was swimming with dolphins With a pod. Dolphin.
Speaker 8:I guess that's what what all the Good little Hawaii motifs are for.
Speaker 1:Yep. Yep. He loves
Speaker 8:It was a fun time. I mean, honestly, 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 kinda super laid back.
Speaker 8:Yeah. It's like all aloha and like Aloha. Or what? But learned a lot, you know. And I think like for me the big was like, wow, like all of enterprise software is basically just like a database with like some app logic and Sure.
Speaker 8: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.
Speaker 8:And if you could create like a way simpler version of that, like that's super intuitive, like that's that might be a big market.
Speaker 2:And Yeah.
Speaker 8:That was basically the the genesis of Airtable is, like, I wanna go and, like, basically PLGFI before that even was a term, like Yeah. This category. Sure.
Speaker 1:Sure. So, yeah, what was the what was the initial, like, hunting for a team, raising money Yeah. Building an MVP? Like, what was the Yeah. Step?
Speaker 8:I mean, the second time around, like, so this was my second company that Yeah. Airtable. You know, I wanted to do things a little bit differently than the first time. Like, the first time was kinda 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.
Speaker 8:Right?
Speaker 1:Yeah.
Speaker 8:Yeah. Every week, it was like, launch, get some, you know, sign ups, go and, like, raise money. And Airtable was a lot more premeditated. Like, spent we two and a half years building the product before even launching.
Speaker 1:Wow.
Speaker 8:Yeah. It was actually weirdly a a very parallel timeline to Figma. So, like, both Sure. Two and a half years the same time
Speaker 1:Yeah.
Speaker 8:Launched around the same time Yeah. Very, like, PLG in both cases. Yeah. And maybe both kind of exploited, you know, the advent of like rich browser experiences Yep. Like for the first time.
Speaker 8:So like you And multiplayer. Yeah. You couldn't build like a rich real time like single page app experience before maybe like 2000 like 11/12 Yeah. Like, and really became like, you know, kind of really legit in like 2014 Yeah. '15 with like v eight becoming like Yeah.
Speaker 8:Really mainstream and dominant. Like, you know, just like the performance of the browser became there. Yeah.
Speaker 1:Yeah.
Speaker 8:So we built this product like, you know, and the premise was let's make it really, really simple for, like, anyone, like a small business owner, like, you know, podcasters Yeah. 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. So Yeah.
Speaker 8:We kinda built it.
Speaker 2:Yeah. Career started shortly after you guys kind of like came onto the scene Yeah. And my first ever business, we signed up for Airtable like day Yeah. One and still use it how many like eight years later something So like like just running like it's been core Yeah. Infrastructure every single day.
Speaker 2:That's awesome. Yeah. I appreciate it. And, like, evolved and Yeah. And, but It turns out,
Speaker 8:like, databases are pretty sticky.
Speaker 2:Right?
Speaker 9:Like, think
Speaker 8: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 Yeah. Built a lot of, like, customization.
Speaker 1:Oracle database as a revenue line within Oracle is growing. Revenue. I'm I'm not sure. Is growing for the Oracle database. Not their their AI stuff is a separate thing.
Speaker 8:GPUs. Yeah.
Speaker 1:Very different valuations, but it is growing, which is I think a narrative violation that I think a lot of people would take. Talk about, like, the early go to market. I mean, you said PLG, but, like, who are you sending this to, like, start up friends? Are you trying to sell this into Salesforce on day one? Like Yeah.
Speaker 1:How how are you thinking about, like, enterprise versus mid market versus start ups versus, like, prosumer? There's, so many different routes you can go.
Speaker 8:Yeah. So this is, like, twenty thirteen ish. Right? And, like, at the time, there weren't that many I mean, there wasn't, like, really a PLG, like, thing.
Speaker 1:Right? Yeah.
Speaker 8: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 best, like, PLG pioneers. Yeah. And they were both very, like, consumer prosumer first.
Speaker 8:So, like, solo, like, individual user first.
Speaker 1:Yeah. Then Drew Houston has the funniest riff on I I don't think he calls it PLG, but he calls it, like, the web growth the web two point o growth playbook, which is, like going viral. But he takes it a lot further and he's like, so you wanna sneeze on as many people as And he refers to that as like, if you send them Yeah. A file that you've sneezed on them. Oh, yeah.
Speaker 1:Then they might create an account. It's just like a much more like visceral way Yeah.
Speaker 8:A viral market. I can't even get this thing off.
Speaker 7:No. I mean,
Speaker 2:the thing about so so my first company is an ad network. Yeah. So we would you know, a company would come and say, I wanna advertise Yeah. Use a $100,000 budget. And then the company would put together a dashboard Yeah.
Speaker 2:Of, like, potential buys and then the person would go through. So it was inherently viral. Every customer that Right. Would have to use had to log in to Airtable and, like, use a product. That So was just happening at, like, massive scale.
Speaker 8:Yeah. Yeah. And I I think that, like, that type of, like, you have some, like, data set, like, you know, maybe it's for your ad inventory or whatever. Maybe it's for, your CRM or whatever. You need to collaborate with it.
Speaker 8:Yeah. Like, it's a very fundamental construct in in just like how knowledge work is done.
Speaker 1:Right? Yeah.
Speaker 8:So I think, like, the lesson learned from here, like, the principle applied was, like, can you go after something that's so foundational that, like, it's always gonna be around. Right? Like Mhmm. I think with, the personal CRM thing, I'd kind of felt the, like, turbulence of, is this in vogue right now? Is it not?
Speaker 8:Like Yep. And I really wanted to go after something that felt like it's gonna be around for decades. Yep. And, like, what's more eternal than, like, people need, like Database. A database That
Speaker 2:you can do stuff
Speaker 8:past forty years of computing, it's probably gonna be around for the next forty. And, like, even now with agents, it's like the database layer actually becomes more important. Right?
Speaker 2:Yeah.
Speaker 8:You don't want just, a bunch of ephemeral context windows, like, for for agents. Like, they need to, like, store and collaborate on data along with humans.
Speaker 2:So, you know, we kinda pick that
Speaker 8: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, like, fake business plan. It was, like, basically, like Yeah. A vision deck more than an actual business plan.
Speaker 8:But, like, we had said, you know, conjectured, like, we're gonna have to go after, like, a long tail of, like, the kind of prosumer SMB audience, basically like Dropbox. Right? 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 So, like, there'd be a big, like, media company or, like, even like a scaled startup like a WeWork or something that would run all of their operations very quickly early on
Speaker 1:Mhmm.
Speaker 8:On Airtable and then just grow with the company. Right? Mhmm. And so Yeah. Like, I mean, WeWork was one of our early customers, had, like like probably 10,000 people, like Interesting.
Speaker 8:You know, when they were at their peak. Like, basically was like used by every almost employee there. Yeah. Right. And like a lot of their operations, building operations, etcetera, were just built on Airtable by default.
Speaker 8:And I kinda learned the the value of like having this, like, data gravity. Like, once you get enough data into a product like Airtable, like, it just kind of retains really well within the company and gains more and more usage.
Speaker 1:Yeah. How did you
Speaker 2:think Until until the company.
Speaker 8:Well, you against the industry What that you're
Speaker 2:so so I wanna get I wanna get to all the goods the the good part, like, right now and all that stuff. Yeah. 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 Yeah. 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. Then, like, there's kind of this reset in late twenty twenty two, How 2020 how has it been kind of, like, building out of that, you trough?
Speaker 2:And then, like, have you I'm assuming it sounds like you've been, like, very reenergized by this new this new opportunity
Speaker 1:Yeah. For
Speaker 8:him. 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 twenty seventeen, eighteen, 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?
Speaker 8: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, you know, 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, it's kind of the first year where it felt like it was starting to get easy. Right?
Speaker 9:Mhmm.
Speaker 8:And yeah. So 2018 to 2021, like very fun, easy years, but also, like, you know Everything is so good. In the world, unlimited money, and like, you know, we got to raise like a big, you know, set of rounds like
Speaker 2:we How would you like a 100 x revenue model?
Speaker 8:Or I
Speaker 1:mean, yeah.
Speaker 8:And and just like the absolute scale of funding was like huge compared to prior art. Right? Like, now, I mean, you can raise, like, a 100,000,000,000, you know, like, if if you're opening eye. But, like, at the time, like, you know, we raised, you know, our first our first unicorn round was, like, a $100,000,000 round. We raised, like, another, like, couple 100 and then like a few 100 more.
Speaker 8:And then like our big round was our series f which was like kind of at the peak of like the markets. Yep. Raised 700 plus million in in that round.
Speaker 4:Wow.
Speaker 8:And an 11,000,000,000 billion valuation. And, you we know, still have like all of that money on the balance sheet and we're now like cash flow positive. That's amazing. I think like, you know, it's kind of a fun fun fun time to like, you know, kinda get to like ride that wave. Yep.
Speaker 8:And then, you know, but like I I always, I think for myself, knew like, you know, you have to build like a durable business. Right? And so like valuations are gonna like rise and fall. It's just gonna be like macro. But like, you know, ultimately either we build a great enduring business or we don't.
Speaker 8:And if we don't, then like, you know, you could be like a flash in the pan. Right? So Yeah. 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, you know, compound growth, like go after the enterprise. Obviously, at the time, especially like, it was clear that was like the move.
Speaker 8: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 Yeah.
Speaker 8:Whether it's, content production at a big media company or, like, you know, like, fund operations at a company, like, you know, like, financial services company. Sure. So these are, like, the, like, almost,
Speaker 1:like, modern ERP explosions. Hire a different set of individuals to work on that that were already connected and knew
Speaker 3:that flow?
Speaker 1:Or was it something where, like, your best sales reps just sort of got bigger and bigger and leveled up?
Speaker 7:Or both?
Speaker 8:It was a a little
Speaker 5:of both.
Speaker 8:I mean, I think it's a different muscle. Like, I think Rolodex 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 XYZ company. Sure.
Speaker 8:And I think that gets you like a phone call. It gets you like a meeting.
Speaker 1:Yeah.
Speaker 8:But ultimately, like, buyers are wising up. Right? Yeah. And they have been for quite some time where it's not just like, oh, know this guy. I'm gonna like or, you know, gal, like, I'm gonna buy this, like, product from them.
Speaker 8:Like, you actually have to, like, show them why this is gonna help their, you know, help them in their job. Right? And help the Yeah. 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 Yeah. 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?
Speaker 8:Yeah. And maybe like for one company it's like, how do I consolidate like my 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, be able to leverage the flexibility of our product, almost like in a Palantir like way
Speaker 1:Yeah.
Speaker 8:Yeah. To show the customer, like, we can actually solve this really deep problem for you quickly.
Speaker 1:Is there any sort of, like, PLG motion or land and expand that happens in the Fortune 100? Like Yeah. 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 or jump off point that does happen.
Speaker 8: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. Like a lot of big banks, like, we just we were firewalled out until we got some
Speaker 1:Oh, interesting. Top down intro. So they can't even
Speaker 8:They literally block you. Right? Okay. Yeah. Your IP is, like, blocked.
Speaker 1:So it's like,
Speaker 8:might be, like, hard wall,
Speaker 1:like Yeah.
Speaker 8:You know, request access. Okay. So, you know, there are some companies where you have to come in top down. But like there you know, I would say 70 plus percent of our current enterprise accounts, including the ones that are like now like 5 plus million in in revenue, like, originated from teams within the company organically adopting Airtable. Right?
Speaker 8:Sometimes it was kind of shadow IT. They just figured it out on their own. Yep. And they just like they showed real value from using the tool. Right?
Speaker 8:Yeah. Like they would build some real operation on it and say like, well, I've been waiting for like IT to deliver me this like old bespoke solution or some like crappy other vendor Yep. For like two years now. I got impatient and just built the thing myself.
Speaker 1:Yep.
Speaker 8:And that's like a big I think, you know, I think of like the enterprise landscape now as 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. Mhmm. But like, there's plenty of dollars.
Speaker 8: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, like, take those dollars? Right?
Speaker 8: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 gonna go and attack adjacencies. If you're Airtable, we don't have, like, the scale of, like, a, you know, ServiceNow or, like, an SAP or Salesforce. Sure.
Speaker 8: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 Airtable, they had, you know, probably heard about it from a friend, like, maybe the CMO's, like, you know, partner, like, uses Airtable in their company or we can go in and just show them, like, a really compelling demo quickly.
Speaker 1:Talk about AI. What are customers demanding? What have you rolled out? What where does AI fit in well? Where does AI take a backseat?
Speaker 8:Yeah. I mean, I think it's crazy because it's like we've we've seen like so many layers of disruption happening Mhmm. Almost in parallel. Right?
Speaker 6:Yeah.
Speaker 8:Like, you know, you think about like desktop to mobile, it was like a single form factor change. Kind of kind of easy almost Yeah. To like execute on. That was the one that I experienced at Salesforce. Like, 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.
Speaker 1:Right?
Speaker 8:Yep. Like, go mobile first.
Speaker 1:Right? Yep.
Speaker 8:And, you know, it was, like, the right move and also kind of a simple move. Yeah. Now it's like, you've got at one level, like, obviously, every product should have, like, AI in it. Yeah. So, you know, we have the obvious stuff.
Speaker 8:Like, you can now talk to Airtable's assistant, like, copilot 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 ability to map reduce AI calls against, like, all all of your data. So you can 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 Hydrating bio for every single product. That kind stuff. Run at a time.
Speaker 8: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? And this
Speaker 6:is Yeah. That's what I
Speaker 2:was gonna ask, like, why you care about, like, storing Yeah. The data in in a in a sort of safe, secure Salesforce,
Speaker 1:they just went like headless recently. Yeah.
Speaker 2:Like Yeah.
Speaker 1:Is there a plan for that or how are
Speaker 8:you Yeah. Gonna I think it's like think the right move is like hybrid headless. Mhmm. Right? Like, I think I think the whole look.
Speaker 8:Like, if you wanted just like a back end database, you could use like Postgres, like Subbase. Right?
Speaker 1:Like Yep.
Speaker 8:You know,
Speaker 5:it's and, you
Speaker 8:know, there's like PHP, my admin equivalents, like modern day ones. Right? Like Prisma has its own version of it. Yep. Like, that are okay or they're good.
Speaker 8:Right? Yep. Like, but like I think what most people actually want, especially in a business context, is like you want like the database Mhmm. But you want to have like proper permissioning, you want to have proper collaboration.
Speaker 1:Sure.
Speaker 8: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. Yeah. But like it's really helpful to actually go in and see the code like see the actual data.
Speaker 8: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 wanna 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 wanna be able to drop down into a really nice interface. And we've done some work around like kind of figuring out what what's the best blend of the two.
Speaker 8:Right? So like with ChatuchPN, for instance, we have a kind of a first class integration where you can go in through ChatuchPN and like interact with your data in Airtable and say like, pull me like all the customers that are like waiting for an Outreach for me and predraft like Outreach messages. Yeah. But then it can basically compose like a fragment of a view within the ChatGPT interface. So like you can actually see like Airtable Sure.
Speaker 8:But like, you know, kind of a part of Yeah. The
Speaker 2:So it's
Speaker 8:not completely headless. It's almost like you get to pull out like pieces of its face Yeah. At the right time on demand. And I think that's a really important kind of like UX form factor.
Speaker 1: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. Yeah. 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.
Speaker 1:Like, a lot of times, I'm just in my email, and I wanna find one thing very quickly. And that feels like it has yet to be, you know, AI ified or at least, like, LLM ified. Yeah. It's very much it's very much like, okay, well, I should probably just fall back to SQL query or just some Boolean logic or
Speaker 2:just like
Speaker 1:vanilla search because I want this now.
Speaker 8:Yeah. I think both are gonna be really important experiences. And obviously, we have, like, you know, kind of great smaller and faster models like the mini, you know, Yeah.
Speaker 1:Mini and stuff.
Speaker 8:You know, that that are great for, like, more synchronous interactions Mhmm. And, like, within Airtable, like, you go do to Airtable or you use ChatuchPati with, like, one of the the smaller models, you get that, like, faster kind of almost, like, more, like, real time experience. Mhmm. But I do think, like, a really important class of work that will come to dominate, like, every frontier company or company trying to reinvent themselves to be frontier Mhmm. Is, like, figuring out how to operate in this new modality of, like you know, it's, the best developers today don't go and, like, sit there in front of their IDE and, like, synchronously, like, talk to the agent.
Speaker 8:You have, like, 30, you know, separate branches that are each being worked on by a different agent.
Speaker 1:Yep.
Speaker 8: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, etcetera. And I think this whole idea of, like, look. It's gonna take, like, hours for that entire loop to complete.
Speaker 8: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,
Speaker 1:like, minutes.
Speaker 8:So you're not gonna sit there and, like, watch it one at a time. Yeah. But the powerful thing about this is, like, each one is still actually operating faster than, like, a human engineer could have Mhmm. Like, back in
Speaker 4:the day.
Speaker 8:Right? Like when I think about like the speed with which like our early team at Airtable could build features and we had 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 Mhmm. Operating probably in like three times the time. Right?
Speaker 8:So it's like literally like a 10 x kind of leverage factor
Speaker 2:Speed up.
Speaker 8:Just for one agent. But the best engineers are now able to multitask and kind of basically say, look, I'm gonna 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, a VC analyst, your job should no longer be to go and synchronously research one company. It's like you're gonna go and research, like, 30 companies and do them all faster, better, and higher quality, right, like than than what you could before.
Speaker 8:And so it I think that's the greatest leap that is gonna be challenging for a lot of people in a lot of roles to make the leap on because it's it's a totally different mentality to like how you operate and what your role is Yeah. Than before.
Speaker 2:What are you pushing the the team to achieve? So
Speaker 8:a lot. You know, I think like there's 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, 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, Chatchpati, Claude, any other agent products?
Speaker 1:Like Mhmm.
Speaker 8:Are people using Airtable more and more agentically? Yeah. And is it working smoothly for them? So that's, like, priority one. The second, though, is, I think we have to, like, really transform how we operate internally.
Speaker 8:Right? Like, clearly, like, the companies the best companies in the future are not just gonna hire, like, massive armies of people to do everything. Right? Like, they're gonna hire, like, people who can really effectively leverage agents. Right?
Speaker 8: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 output than, like Yeah. 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 way of coming. Right?
Speaker 8: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 Airtable and, like, kind of hybrid headless Airtable, 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 Yeah. Agents that can just, like, have access to your data and tools and do stuff, like, really, like, long running stuff, not, like, ten second tasks, but, like, ten hour tasks.
Speaker 8:Yeah. But for non coders. Mhmm. And we wanna do it in like a business friendly way. Right?
Speaker 8: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, ten years ago was, like, the most meta problem, like, 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, we wanna 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.
Speaker 8:Right? And so if we do that really well, then, we get to doubly win both as the data layer
Speaker 1:Yeah.
Speaker 8:But also kind of have a a bet on the the agent wave.
Speaker 1:Yeah. Last question. Should children learn c plus plus
Speaker 8:Definitely not.
Speaker 1:No. I think And is that because of c plus plus or because of the AI era?
Speaker 8:I think well, I mean, think both. Like, I think I think the fundamentals of good technical architecture are gonna 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 Yeah. And, like, would punch it into his, like, p p 10.
Speaker 8:Yeah. 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 Mhmm. How should this system work?
Speaker 8:Like, where should the different like levels of, you know, kind of responsibility belong? And like Yeah. If you can get really good at that, then you have super leverage. If you are just kind of like like learning the literal kind of like lines of code and how to write them that, you know, a lot of engineers were before, I think that's gonna be increasingly below the frontier line of like agents can just do it equally or better to humans. Yeah.
Speaker 1:That makes a lot of sense. Well, thank you Well, so
Speaker 7:much for
Speaker 1:coming on the show. Thanks for
Speaker 2:having you.
Speaker 1:Have a fantastic rest
Speaker 2:of Great your hanging. Talk soon.
Speaker 1:We have our next guest, Mark Gurman, the Gurmanator himself in the waiting room. Let's bring him in to the TBPN Ultra Dome. Mark Gurman, how are you doing?
Speaker 6:Tired. How are you doing?
Speaker 1: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?
Speaker 1:Did this match your timeline? Were you surprised by this particular Monday that it was announced? Or
Speaker 2:Walk us through the scoop.
Speaker 1:Yeah. And get
Speaker 2:the get the scoop.
Speaker 1:Get the scoop ready. This is the scoop. I've the golden scoop for you.
Speaker 2:The golden scoop.
Speaker 6:Oh, I've never I've never seen that.
Speaker 1:Yeah. That's awesome. It's a new prop in the studio. You'll have to The new
Speaker 6:prop I like to
Speaker 1:see. Next time here in person.
Speaker 6:The OpenAI deal is already doing work for you guys.
Speaker 7:There you go. New props.
Speaker 6:So here's the deal. A reason I published my profile of John Turnis 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.
Speaker 6:Things have been in motion. The plan was to announce it after the fifty year anniversary celebrations. And it almost felt like the fifty year celebrations were not just, you know, about Apple's fifty years, but sort of a goodbye celebration to Tim Cook and his legacy at the company. So it all came together over over over several months. This really started about two years ago when Tim Cook identified John Turnis as the next one.
Speaker 6:Turnis had been prepared for this role probably for over five years at this point, they put him on the executive team when he became SVP of hardware engineering. But this started in in early twenty twenty four, and at the time, I I wrote that that was the first time I wrote that he would be the next one.
Speaker 1:Yeah. How do you have you been able to process 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.
Speaker 1:But are Apple employees generally excited about this? It seems like, there's a lot of cause for optimism, but I'm always interested
Speaker 8:Yeah. To hear
Speaker 2:There was that one article a couple months ago where clearly they were getting quotes from former employees that were like kinda taking potshots at him. Yeah. Basically saying like He hadn't He's never made a hard decision.
Speaker 1:Yeah. That was the quote that went to the journal, but I don't know. It seems like it didn't matter because he got the job.
Speaker 6:Well, got the job two years ago, and I think he's going to do 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 left product development to other members of the executive team, my expectation is that John Ternis 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 Sabi Khan and Priya, the people who run the operations division at Apple Supply Chain Manufacturing Procurement, AppleCare, you name it.
Speaker 6: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 Mariab. Not an innovator, but an incredible execution guy when it comes to hardware engineering 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.
Speaker 1:Yeah. Does when when I remember Steve Jobs, I think of Jobs as an innovator, as a visionary, as someone who both did Pixar and the iPhone, you know, so many different projects, a lot of them wildly successful. 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?
Speaker 1:Or do you think that there's do you think Ternus has, like, some aces up his sleeve where he might wanna take a wild swing at something?
Speaker 6:The thing with Tim or what John Ternus is gonna have to do is stay the course. Mhmm. Annual iPhone, iPad, Mac, Apple Watch, AirPods upgrades. Yeah. But at the same time, is going to need to do a better job of bringing out new product categories that Tim Cook has done.
Speaker 6: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, you know, those were both really developed by management teams and 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 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.
Speaker 6:They eventually want to get to AR glasses, they'll have display list glasses to compete with Meta several months from now into 2027. Mhmm. But he needs to get cracking. There are six major Apple products in development right now. Six major new product categories.
Speaker 6:Mhmm. AI AirPods, smart glasses
Speaker 4:Yep.
Speaker 6:Pendant Pendant. Smart display
Speaker 1:Is that the lamp or the the kitchen thing?
Speaker 6:No. No. Lamp is number five. Smart display is is is is different.
Speaker 1:Okay.
Speaker 6:The tabletop robot, so that's the lamp, the moving lamp. And then number six is a I'm only gonna say very little about this, but a security camera.
Speaker 1:Okay. Interesting. Well, at least the Apple Vision Pro has one key fan.
Speaker 6:Do you think the
Speaker 2:lamp do you think the lamp is a is a predecessor for a humanoid? Do you think Apple would ever do a humanoid? I
Speaker 6:do. I do. But I think it's gonna be a decade if they do and they're gonna wait and It says
Speaker 2:it says a lot that they're not
Speaker 1:Talking about it?
Speaker 2:That you don't know about an internal humanoid project yet.
Speaker 6:Yeah. Oh, I do.
Speaker 1:Oh. But but Yeah.
Speaker 6:They're exploring humanoids and the idea of being humanoid.
Speaker 2:Yeah. But they're They're
Speaker 6: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, you know, got rid of a couple weeks ago, John Jurewicz. Yeah.
Speaker 6:But they're also looking at actually they're building 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, a consumer standpoint. They've also been exploring a mobile robot, something like an Amazon Astro, but I don't think that's probably gonna see the light of day.
Speaker 1:That's fun. I feel like Apple has a perfect brand
Speaker 2:Talk about robotics. Talk about Ternus' challenge with supply chain broadly, what you think he's gonna be focused on over the next five years.
Speaker 6:Oh, I don't think he will be. I I don't think he will be. I think just like But is that not
Speaker 2:but is that not you're saying, like, just basically
Speaker 1:He's delegating it.
Speaker 2:Broadly ignored that it's a kind of a key risk to the business to have, you know,
Speaker 1:some I know. His team.
Speaker 6:Yeah. With the hands in 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 gonna pick his spots as well. As we know, turn Tim's spots was operations, finance, and sales, and he delegated everything else.
Speaker 6:My sense is that Ternis is going to Ternis' mandate. Ternis was hired because they believe that he is going to be able to bring Apple back to the forefront of product device innovation.
Speaker 1:Mhmm.
Speaker 6:Okay? They already have the best in class operations, finance Yeah. Salespeople. They don't need Ternus to do that. They need Ternus to keep his eye on the prize, which is products.
Speaker 1: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 I saw the Android phone that has the the 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.
Speaker 1:But are are any of these features that exist in other phones? It feels like they haven't actually gotten a groundswell and started pulling iPhone users away from the ecosystem. But are there key features that people are worried about or what It's not yet. Yeah. Okay.
Speaker 1:It's not
Speaker 6:here yet. Nothing you've seen is the risk.
Speaker 3:Okay.
Speaker 6: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 Yeah. And jettisoning Apple from that perspective. But we all know that nobody has done quote unquote cool stuff yet to steal away iPhone users. Nobody is ditching their iPhone for Android.
Speaker 6: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.
Speaker 1:Yeah. But consumers care about value and things like the MacBook Neo really deliver that value. Brand, colors, value. System, privacy. Yeah.
Speaker 6:Ternus was only senior VP of hardware engineering at Apple for five years. Mhmm. It's a short tenure to be an SVP of a division at Apple. And the reason is because he's oh, there you go. No.
Speaker 6:He's been at
Speaker 2:Apple twenty five years. Yeah. I'm kidding. We use that ironically.
Speaker 6:No. I know. But the the point I'm I'm 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
Speaker 3:Mhmm.
Speaker 6:And higher quality. Mhmm. He's really focused on the durability and longevity and the reliability of Apple products. Mhmm. And it's meaningful, I think, that the person that they chose to be Chernis' replacement in hardware engineering, Tom Harieb from Intel, is a product quality and reliability expert rather than a product design person.
Speaker 1:Yeah. What was the thinking? I mean, I remember we we talked about this, how I I got the new iPhone and it has immediately been dinged.
Speaker 2:What was the thinking on making
Speaker 1:it And, but but but it's 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 trade off? Yeah.
Speaker 6:Yeah. There's trade offs with every material. Like, titanium was light. It looked cool. You could beat blast it.
Speaker 6:It's a so, know, interesting. I mean, it looked interesting, and it gave them a good marketing point. Like, come buy a titanium phone, like anyone cares about the material or their phone. But it had really bad properties related to heat. Aluminum, which we've known for twenty years, is an excellent material to build consumer electronics out of, so they went back to the basics.
Speaker 6: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. Yeah. 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.
Speaker 6:And Sure. I think you're going to continue to see Ternus push in that direction, making the MacBook Pro as amazing and most performant as it can be in pushing everyone else to the MacBook Neo and the MacBook Air. And I think his legacy on performance and product quality is really important thing to remember.
Speaker 2:Yeah. Has Ternis ever talked publicly about AI in any capacity?
Speaker 6:He talked about AI in his all hands meeting with employees this morning. He said that
Speaker 2:I'm gonna check it out.
Speaker 6:No. Just hold on.
Speaker 2:I'm kidding.
Speaker 6:Hold on. I don't want to give you inaccurate Yeah. Fake news.
Speaker 1:Just a good sign.
Speaker 6:Okay. Yeah. Just hold on. Bear with me.
Speaker 1:I think I Internal memos.
Speaker 6:No. No. No. No. Okay.
Speaker 1:He said
Speaker 6: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
Speaker 1:There you go.
Speaker 6:Is going to create almost unlimited potential. We're going to be able to keep unlocking possibilities that that are going to create entirely new opportunities for our products and services, and I'm so excited about what that's gonna mean for our users.
Speaker 8:Yeah.
Speaker 6: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.
Speaker 1: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 Turnis taking over at Apple.
Speaker 1:Is Apple not already the mecca? Is is there actually somewhere to go, but that that is up in terms of hardware engineer recruiting? Do you see this as changing the culture in some meaningful way?
Speaker 6:I mean, they don't pay, like, these, you know, OpenAI's, HARCs, and Metas of the world. They're Apple has been pillaged by OpenAI 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 TURMIS has been dealing with over the last year and change. So but Apple is, know, the hardware mecca.
Speaker 6:They're the company that everyone wants to poach from, and they're the company that people go to to learn how to build consumer devices. So this is definitely yeah. I I agree to a large extent with you actually. Yeah. Alright.
Speaker 6:With Bubble Boy.
Speaker 1:Yeah. Alright, 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?
Speaker 6:Announced in September, Turnus' first big new product. Yeah. Super exciting. Super pumped. Yeah.
Speaker 6:We've talked about this. I'm sick of the candy bar phones. It's been the same junk for fifteen excuse me, twenty years now. Yeah. I want a foldable.
Speaker 6:I want a bigger screen.
Speaker 1:Yeah. I really hope It's exciting.
Speaker 2:John Neat wants a newspaper sized phone.
Speaker 1:I well, they have those. I've seen those in China. He's through the the trifold. Right? But this is a bifold.
Speaker 6:Don't get me started on the trifold. Explain the trifold.
Speaker 1:Wait. Why are they awful? It seems amazing.
Speaker 2:John wants pages of screens that he can turn.
Speaker 6:Blimsy and they break.
Speaker 1:Okay.
Speaker 6:They need a trifold and Apple like quality in twenty years because, you know, like, takes good old time when they do a when they when when Apple does a trifold, it'll be good.
Speaker 1:Okay. Okay.
Speaker 6:You know, I open up a foldable phone right now, you open it up and you can hear the screen sort of creaking. Okay. Right? And then you have that big Yeah. Line in the middle, and then it's like impossible to get your thumb in to open the thing.
Speaker 6:Yep. I hope Apple fixed that. I don't wanna hear a creak. Yep. For $2,000, I don't wanna hear a creak.
Speaker 6:I don't want it to stand stand sound like I'm stepping on, you know, a wooden floor.
Speaker 1:Yeah.
Speaker 6:Right? 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.
Speaker 1:Yeah. It's still gonna be weird for video consumption, though, because I feel like we've done vertical videos, nine nine by 16 and then 16 by nine widescreen. But if you open up a foldable phone, you eventually get a square, and that doesn't really make like a movie watching
Speaker 6:experience better. Apple's is different. Apple's is like the new Huawei phone where it is iPad screen ratio.
Speaker 1:IPad screen ratio. When you open it. Okay.
Speaker 6:When you open it.
Speaker 1:Yeah. Okay. So still black bars
Speaker 6:yeah. Sure. There'll be black bars.
Speaker 1:When you rotate it black bars. On the top of box.
Speaker 6:If you're
Speaker 1:watching like a cinema film or Right. Even if you're scrolling Instagram, like, you you won't necessarily get more view because for so long, all the content production has been ultra widescreen. 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 then you're you're gonna have black bars on the side for for the most part. But for so many other applications,
Speaker 7:you know,
Speaker 1:for Word documents and notes and
Speaker 6:TBPN will look great on it.
Speaker 1:Yeah. Something to look forward to.
Speaker 2:What do you think Ternus' new comp package looks like? You know, we were we we almost marched on Cupertino because of Tim Cook. To to get raise.
Speaker 6:Tuck yourself to the the spaceship. I
Speaker 2:know. Yeah. Exact
Speaker 6:I would I'm just guessing. I'm just guessing. I think a million shares. Over ten years.
Speaker 1:That's pretty big.
Speaker 6:And can I just tell you why I think that?
Speaker 1:Yeah.
Speaker 6:Why? Because that's what they that's what they gave Tim Cook when he was named CEO, 1,000,000
Speaker 1:over Sure.
Speaker 9:Ten years.
Speaker 6:So I would assume it's the same. Yeah. But again, I I I don't know.
Speaker 2:Yeah. Entry level researcher salary, but it's a good start. You can
Speaker 7:Pretty much. If you
Speaker 1:can Tim
Speaker 6:Cook is getting Tim Cook, you know, Tim Cook was getting a 100,000,000 a year, and then everyone flipped out except you guys, and so he had to cut his pay to like 40,000,000, and then when things died out, he's like, alright, I'll I'll I'll take I'll take my $7,080,000,000.
Speaker 2:I slept peacefully for for those years, And then you should see my sleep score once.
Speaker 1:We were really we were really the the strongest supporters of the of the Tim Cook pay package.
Speaker 6:I guess I guess a million.
Speaker 1:I wish you I mean, it's just like look at the value
Speaker 2:that he's created the same amount as a guy leading, you know
Speaker 1:A $4,000,000,000,000 company.
Speaker 2:Make it make sense.
Speaker 6:Yeah. Maybe it'll be 500,000 shares. Maybe it'll be 500,000 shares. I I don't know. But I know that they gave Tim Cook a million.
Speaker 6:You gotta get those
Speaker 1:numbers up. You gotta get those numbers up. It's time to march.
Speaker 6:Really? You're all in on furnace already?
Speaker 4:We should free up the leap art.
Speaker 1:We're we're bullish on both. We love both here.
Speaker 6:Well, now you get you get both now.
Speaker 1:I know. We do. The yeah. What why why is 65 a retirement age for the CEO of Apple? Like we were talking about Warren Buffett.
Speaker 1:He was able to manage a trillion dollar organization well into his nineties. Is it a more physically demanding job? Is he traveling more? Is it is his hand ringing from shaking hands in DC? Like, why not have another ten years if you're in that seat?
Speaker 6:I don't think the hand situation has much to do with shaking other people's hands.
Speaker 1:Okay.
Speaker 6:Why is he not there another ten years? Well, he needs to give the new guy runway.
Speaker 1:Okay.
Speaker 6:I'm sure there are some I'll just tell you what Tim Cook not going to get into it. What I'm going 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 Turnis being ready, Apple's finances being in a very strong place, and Apple's future roadmap being in a strong place. In terms of the real reason why he's stepping down now, you can read some of my prior articles
Speaker 1:Sure.
Speaker 6:Taking a deeper look at the at the situation.
Speaker 1:Okay. Yeah. Makes sense.
Speaker 2:Cool. I love seeing you. I love talking to you. Thank you for Congratulations. Coming Get some
Speaker 6:see you guys
Speaker 1:coverage. Get some sleep.
Speaker 2:Great to see you, Mark.
Speaker 1:And keep up the amazing work. We'll see you soon.
Speaker 2:Same, Sam.
Speaker 6:We'll see you in fifteen years for Terminus Junior.
Speaker 1:Can't wait. We'll see you. Goodbye.
Speaker 2:Let's pull up The OpenAI launch. OpenAI launch.
Speaker 1:What's going on
Speaker 2:with Image Gen two.
Speaker 1:I've been playing with this for a while.
Speaker 7:There are
Speaker 1:wild wild examples. Are livestreaming
Speaker 2:Sam should have saved the Death Star meme Livestream. For this. Yeah. For this launch.
Speaker 10:Plenty layout into coherent and 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 these kind of tasks very well. And we now have an output for this where you can see eight different real cool outfits for me. Kwan, what do like?
Speaker 1:The level of detail in these models is getting It's so
Speaker 2:post slop.
Speaker 1:It is post slop. That's a big that's a But big I've seen 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 like the idea of generating like a single photo of a person in an outfit was was remarkable just a year ago, I guess, when the Studio Ghibli thing happened. And now you can generate layers and layers of of detail here. Good teaser.
Speaker 1:They said this is not a screenshot and posted the image.
Speaker 10:And detail. Something
Speaker 2:that prompt tell tell everyone about the prompt you've been running with with Wiki.
Speaker 1:Oh, yeah. Media. I've been doing this thing where I take a Wikipedia article and I ask ImageGen two to turn it into an infographic or you can actually do an Instagram carousel, like 10 images that tell the story of something. Did this with John Turnis and it's it's remarkable. I mean, the text is is perfectly photo real.
Speaker 1:The other thing that's interesting is the the brand comes through in an interesting way. It doesn't it's not like it has, like, one style for infographic. Like, I had it make a infographic about John Turnis 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 Elden Ring movie that we were talking about yesterday.
Speaker 1:So I went and got the the Wikipedia for the Elden Ring movie that has some details and some leaks of who might be in the, in in 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 Turnis' career, it will do, like, a pretty good job generating someone who looks sort of like John Turnis. But then you can actually just take his canonical headshot and say, no, use this exact photo of John Ternis, and it will just drop it right in. And so it looks looks perfect because it is just like a copy paste basically on top of the layers.
Speaker 2:Let's get some audio again.
Speaker 1:Let's see what else is going on here.
Speaker 5:Output. This is particularly useful for very complex prompts, for things that require like web searches, for require you to output multiple images that have to maintain coherence with each other. Yeah. Or even for it to check its work before saying, hey, here's your final output. But let's just like look over some examples of this first.
Speaker 5:Gabe actually kicked off a few of these examples at the start of the livestream. 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 Mhmm.
Speaker 5:They still look like Dave and Sam, and they still look like children's
Speaker 2:stories Yeah. Coloring books.
Speaker 1:Yeah.
Speaker 2:It's like really should
Speaker 5:be very among pages one, two, and three.
Speaker 1:This weekend.
Speaker 3:It was very successful.
Speaker 1:Rave reviews in the Kugen household for AI generated coloring books for mythical creatures that my son came up with, combining different creatures.
Speaker 5:We beta tested the instant version of this model on Ella Marina under the code name duct tape. A few like a few of you on the internet were like really good detectives and deduced that it was us. But we're gonna announce that it was us. And so in this prompt, we basically asked that
Speaker 8:You got us.
Speaker 5:Basically GBT images too to go and find social media reactions to this duct tape model and basically quote people. So we see quotes from threads, LinkedIn, Reddit, etcetera. But I think an even crazier part is that we've also asked the model to put a QR code to chatgbt.com so that you can try out this model right now for yourselves. And can we do that? Just make sure that it works?
Speaker 10:Yeah. I tried.
Speaker 5:Oh, nice. Nice. Nice. So image generation with thinking allows you to do really complex things such as 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.
Speaker 1:It's so interesting. The tool use is getting really advanced. We've got some version of CodeXware. Actually was able to generate a And diagram to make sure that everything was correct and then regenerate the image on top of that. Of course, the we we should go to the timeline because there's some people that are having fun with the image generation.
Speaker 1:Someone made presidents in Elden Ring. There's Joe Biden, which is a, you know, a Dark Souls style boss that you can fight and FDR, Lord of the New Deal. And these images, it just looks remarkable if you ever played any of the Elden Ring or or Dark Souls games because, of course, like, the text is 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 if it actually existed. Blake Robbins said the world is now ready for the rumored OpenAI image model.
Speaker 1:People are creating Google Street View images that just look perfect and Grand Theft Auto five loading screens. And there's a big trend of people creating things that look like screenshots of livestreams, and then they put themselves in the livestreams and have all fun with that. And there's one of Sachin Adela presenting a slide and, like, even the minor text at the bottom of the slide in the picture, it's sort of remarkable to to think that all of this is generated basically one shotted. Justine Moore was posting about this long time ago, April 6. This ad was one shotted by OpenAI's Image Model.
Speaker 1:Prompt was literally make an advertisement for the m four 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 or deliver via this format? The whole meme of like turn this essay into bullet points, turn this bullet points into paragraphs.
Speaker 1:Now you can turn this infographic into text and turn the text back into an infographic. I I feel like a lot of slides
Speaker 2:talent here for tracking your Uber Eats and FedEx deliveries, and it looks pretty believable. Yeah. We can pull up the pull up the screenshot here.
Speaker 1:Yeah. People there's something there's something interesting about this where I I've seen a number of of slide decks that could be infographics, and I'm wondering if there's gonna be a new level of, like, compression where people are saying, like, just send me a screenshot, like, a one pager screenshot over text instead of like a slide deck that I have to click through. That is a lot of information. That
Speaker 2:would But if you zoom in, there's like pretty
Speaker 1:Oh, it's like pretty
Speaker 2:aggressive fidelity.
Speaker 1: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 that could go in a 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 Cowen, back to the timeline.
Speaker 1:Tyler Cowen made an incredible call back in July 2020 in the depths of COVID in Bloomberg. He said, this year is likely to be remembered for the COVID nineteen pandemic and for a significant presidential election, but there is a new contender for the most spectacularly newsworthy happening of 2020, the unveiling of GPT three. As a very rough description, think of GPT-three giving computers a facility with words, a faculty, oh 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 Gurman's scaling hypothesis post and two and a half years before CHECH PT was released.
Speaker 1: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 Spellbook. He's a co founder and CEO. Scott, how are you doing?
Speaker 9:Doing great. Doing great. How are you guys?
Speaker 1:We're good. Welcome to the show. How are you doing?
Speaker 9:Good. Good. Yeah. Thanks for having me.
Speaker 1:Can you I I mean, I wanna go into the contracted IRR debate, but let's get the update on Spellbook. How are things going? Where's the company at? How are you feeling?
Speaker 9:Going very well. We had a killer q one. Crushed our our stretch targets last year. Yeah. We're over 4,400 customers on board in 80 countries now.
Speaker 1:80 countries?
Speaker 9:Yeah. We're the the the most used AI contract review tool in the world.
Speaker 1:So Why so international so early?
Speaker 9:It's been inbound. Yeah. We we've had a ton of interest inbound. So, yeah, it it really you know, the choice is accept the customers or turn them away. Yeah.
Speaker 9:You know, we chose to accept them. Yeah.
Speaker 1:Is the product sort of multilingual by default?
Speaker 9:I would say yes. Like, a lot of it is driven by AI models. AI models have some ability to deal with diff actually, good ability to deal with different languages. Yeah. And then we're able to supplement the models with legislation and norms from many different jurisdictions since we're a legal product.
Speaker 1:Yeah. So, yeah, where 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?
Speaker 9:Yeah. I mean, I think for us, the the bit you know, we try to be two years ahead of the market and and 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've built the very first Gen AI product for lawyers back in the 2022. This is like before ChatGPT. Wow.
Speaker 9:So a lot of, like, clod for word just came out. Yeah. 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.
Speaker 9: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 based work. What we focus on at 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 their sales team, their procurement team. Sure. We're in manufacturing, shipping, all of these different verticals.
Speaker 9:We kind of build these end to end rails that allow these contracts to
Speaker 1:move
Speaker 9:quickly and safely through organizations. Like, there's a lot that can slip through the cracks when you're dealing with these high volumes of contracts. 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.
Speaker 2:Yeah. What drew you to Cargate? Why other is it is it legal AI companies that you that you feel like are are getting a little bit dicey on this front or or, you know
Speaker 8:Yeah. I mean
Speaker 2:How how how do we get here?
Speaker 9:Yeah. So I've I've got some interesting examples to cite, but, you know, I think I think it's an enterprise AI problem. I'll say I'll say first, like, my goal here with this tweet and and what I'm doing is is to destroy as much equity value as possible by did by Sounds like discrediting this obscene metric of CARR Yeah. Or at least the way it's being used today. So we can all get back to, like, building real companies.
Speaker 9:So that's that's that's what I'm trying to get out there. Sure. Mean, where this came from is I think I just noticed more and more founders and investors telling me things about ARR reporting, mainly the public reporting, but also some of the internal reporting Mhmm. That was just getting more and more skewed. Mhmm.
Speaker 9:And, yeah, there's all these headlines being published about, you know, ARR records being broken.
Speaker 1:Sure.
Speaker 9:And, you know, when the laws of physics are being broken, you have to ask, is it 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 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 CERR, often using this metric when they're talking to press about, you know, revenue and then gaming it in some pretty pretty obscene ways.
Speaker 9:So And maybe I
Speaker 1:just tweeted about it.
Speaker 2:Yeah. The the tweet. So Yeah. You say the setup. Company signs three year enterprise deals.
Speaker 2:Year one is discounted, say 1,000,000. Year two steps up 2,000,000. Year three is full price. They report 3,000,000 as ARR even though they're only collecting $1,000,000
Speaker 1:a big deal.
Speaker 2:Yeah. The worst part, the customer has an opt out option at twelve 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 not Yeah. It's a contract that that the customer can can get out of.
Speaker 2:Interesting. And they're not actually on on the hook. So it's not really
Speaker 1:It's rough. We so so Yeah. Yeah. Yeah. You just react to that, I guess.
Speaker 9:Yeah. So I think I think, you know, that's a specific real example that I I heard of in the wild from an from an insider of how this this these error metrics were being gamed to create, you know, some 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.
Speaker 2:Yeah. Because because focus of the donuts. You get one person in a category that starts doing this, then then the other people
Speaker 9:We have to report
Speaker 1:the have same
Speaker 2:to start reporting the same way and it creates a vicious cycle.
Speaker 9:Yeah. And it start and it starts pretty innocent, you know. C ARR for folks that don't know, C ARR is contracted ARR. 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.
Speaker 2:For short short term stuff. Like, hey, this this this contract is going you know, this this customer is actually gonna be going live next quarter
Speaker 1:Mhmm.
Speaker 2:But we've signed it and we're just going Got through the implementation process. Yeah. Yeah. And but but yeah. There's nothing that there's no, like, law that says you can't say, like, we're gonna extend the the sort of, like, timeline dramatically.
Speaker 2:Mhmm. It just is not a very grounded way to run your business.
Speaker 9:Mhmm. Exactly. Exactly. Yeah. And, like, I think it's innocent.
Speaker 9:Like, three months extra credit, you know, arguably useful, but it's a very easy metric to gain, especially if you miss those obligations. So I think because we we kind of normalize, you know, the forward deployed engineer, which,
Speaker 1:you know, we used
Speaker 9:to call professional 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.
Speaker 9:Then what happens if they miss that or what happens if that gets delayed? They that and then they're reporting it upfront as ARR publicly, but they're not actually at the point where they're the ARR is 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 ARR and they're free free pilots. That you know, I I was talking to an investor yesterday who just sees that all the time from early stage companies, like, coming out of accelerators saying they have, a million ARR, and they look under the hood, and it's just all pilots that haven't converted yet.
Speaker 9:So there's a host of different, you know, issues with the metric. And then 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.
Speaker 9: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
Speaker 2:terminated for a Seen a few contracts.
Speaker 9:Yeah. Yeah. Yeah. So Yeah. What yeah.
Speaker 1:I think
Speaker 9:I think it's it's a really ungrounded metric, and people should stop using it to report their enterprise AI companies should stop using it to report their ARR publicly. I think no one should take it seriously except maybe internally for some projections. You know, it's it's not a not a good good metric.
Speaker 1:What is the gold star example of using ARR correctly? Because it's very easy once the company is public to just say, okay. Let's just go off of, you know, GAAP 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.
Speaker 1:But what is
Speaker 2:Overrated best companies should just report their daily annualized run rate
Speaker 1:or Yeah. And then and that goes to the debate of annualized versus annual. Right? So how have you processed sort of the better cases? Like, what is the responsible way to report a revenue metric in 2026?
Speaker 9: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 lots of both. Definitely don't do, like, hourly, you know, annualized run rate based on the on the hour. Yeah. That's not good.
Speaker 9:I think the the main thing I would say is it should be live. 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, 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. 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 gamed will be gamed.
Speaker 2:Yeah. Yeah. Mean Are you optimistic that anything will change or do we need to see a massive correction and and a dark and a dark the dark ages, like I mean post 2022?
Speaker 9:I I mean, I would like to see a a steep correction and then back back to 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 I I've had I've spoken to a lot of reporters in the past, like, forty eight hours who are like, I'm always going to ask now.
Speaker 9:Like, when the company tells me their ARR, are they talking live error? Are they talking, you know, this, like, long term committed ARR that might come? So I hope, you know, at least the journalists are gonna be a little little bit more a little bit more savvy and ask ask more questions before they report on these numbers.
Speaker 1:Yeah. The I wanna 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 wanna multiply it by 12, they can, but at least you're just reporting, hey, last month, this is what the Stripe account did.
Speaker 2:You can also just say by q three, we will be at x ARR. Mhmm. Or Exactly. Because that's different way of saying that's that's better than saying we are we are at 10,000,000 Yeah. C a r.
Speaker 2:Yeah. Yeah. So
Speaker 9:Exactly. Much better.
Speaker 1:Who who suffers here? Is it 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, you know, a thousand times ARR because they think it's a 100 times CARR, like, that's their risk profile. Like, I would maybe be careful, but, you know, that's their job.
Speaker 1: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 rugged? Like, how do you think this affects the who needs to watch out for this, basically?
Speaker 9:Yeah. I mean, I think I think investors are generally good investors are generally very aware of the difference between CER and ARR 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 CRR, but it's called ARR.
Speaker 1:Yep.
Speaker 9:In in a board deck, you see both metrics. So Yep. So, you know, investors are quite aware, but but I I I don't think it's victimless at all. I think, yeah, employees are signing up for companies. As you know, in in, like, a a high growth startup, people are committing a ton of blood and sweat to be successful Yeah.
Speaker 9:Based on you know, part of it is based on the growth of their equity. And if it turn and they might think they're they're they're multiple you know, they might read the headline number. May they may not know the number that's actually in the board deck. They might read the head the headline, you know, ARR in in the in the press release, and they might base base their decision to join a company Totally. Based on these headline revenue numbers, which are really not grounded in reality whatsoever.
Speaker 9:Like and by that, I mean, I have literal examples, confirmed examples of, you know, the the press number being three to five times higher than the actual live ARR number. So, like, that's a huge difference if you think about a multiple Yeah. Yeah. Yeah.
Speaker 1:Between a public company that's trading at 10 x revenue multiple or something, and then you get your you get your offer from a company and it seems like they're at 10 x, but they're actually at 50 x. Like, that is very material how you should think about valuing that that stock that you're waiting for. Makes a ton of sense.
Speaker 9:Then 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 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.
Speaker 2:Mean, we can start doing contracted viewership. So we've signed three year deals I
Speaker 9:love it.
Speaker 2:People in the audience that requires them to tune in to Do
Speaker 1:the the show every show. Every year.
Speaker 2:They have an opt out after a month
Speaker 1:Yeah. Yep.
Speaker 2:If they don't like it after a month.
Speaker 9:Still advertising based on contracted viewership contract
Speaker 4:for the rest of year.
Speaker 9:Watch every day, every hour.
Speaker 1:I mean I mean, I 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 a million views and they only have a 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, 30,000,000 followers. And then the post will get, like, three likes. And it's like, those are two wildly different metrics.
Speaker 1:Like, that happens all the time. But this is the name 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 spreading the good word.
Speaker 2:Don't don't don't get too sucked into all this. You're
Speaker 1:You got a business to build, you know?
Speaker 2:Can take
Speaker 8:I'm building
Speaker 2:back on. Promise you can come back on in three years Yep. With your with your honest ARR and take a good victory lap.
Speaker 1:No. No. Become an investigative journalist. Pivot to investigative journalism. Blow those doors wide open on this.
Speaker 2:Wow. This goes deeper than I thought. Yeah. Good to good to see you.
Speaker 1: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.
Speaker 1:Can AI smell? That's our current benchmark for AGI. We say if if, you know, we talk about white collar work, we see sommeliers as white collar workers. Unless you can smell, it's not AGI and artificial intelligence falling short. But it's your first time on the show.
Speaker 1:I would love an introduction on yourself and the company because I'm fascinated by this topic.
Speaker 7:Let's talk about it. Your Somalia comment and also what you talked about with Max Koenig has been on my mind.
Speaker 1:Amazing. My name
Speaker 7:is Alex Wiltschko. I'm founder and CEO of Osmo. We're giving computers a sense of smell. I've been Hi, Mike. Working on this problem for twenty exactly twenty years or so.
Speaker 2:Twenty years.
Speaker 7:First as an academic. Tonight's success. I did my PhD in olfactory neuroscience at Harvard and trained under Bob Datto who trained with Richard Axel, who got the Nobel Prize for discovering the receptors of smell. Wow. And my AI mentor trained with Jeff Hinton who got the Nobel Prize for deep learning.
Speaker 7:Yeah. And I'm the one weirdo that's like
Speaker 1:waiting for you to join for the entire history of the show.
Speaker 2:There's been great prophecies of your arrival
Speaker 1:for hundreds of years. I'm so excited.
Speaker 7:Okay. I'm so pumped to be here.
Speaker 1:So so should we start with maybe like a olfactory science one zero one? 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?
Speaker 7:It it a 100%. So the chemical slice of reality, all the stuff that's data in the air
Speaker 2:Mhmm.
Speaker 7: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 the physical pieces of that thing enter into your nose and touch a piece of tissue about the size of a postage stamp. Mhmm. And that's your brain.
Speaker 7:Right? So like you're in physical communion with that thing. Yeah. That information gets turned into neural data which actually skips all of the normal way stations for the other senses Yeah. And goes right to your centers of memory, the hippocampus, and emotion, the amygdala.
Speaker 7:So our sense of smell is very primal in that regard. So it's it's like it's the reason why when you smell something, you get dragged into a memory and you cannot stop it. Yeah. You're just like back in high school or you're back as a kid. It's because it's we're physically wired for that.
Speaker 1: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 in like a t shirt or something.
Speaker 7:No. Literally neuroanatomically tricky.
Speaker 1:Target wall art. Yeah. Yeah. It feels like Target wall art. I don't know.
Speaker 1:It's just one of those things that you repeat
Speaker 2:They say
Speaker 1:a spell
Speaker 2:pop sires. A thousand words.
Speaker 1:Okay. So that sounds like something that's extremely hard to reverse engineer. Do we have 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 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?
Speaker 7:Yeah. Great question. So I was very fortunate to have those guys as my colleagues. I actually spun Osmo out of Google Brain. Oh.
Speaker 7:And so I was there when all that stuff got invented and I ran the 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. Yeah. So we could basically slurp that down Yeah.
Speaker 7:And start building models. Got it. We have chemical sensors. They're called mass spectrometers. There's other kinds of chemical sensors, mock sensors.
Speaker 7:There's like a dozen. The history of sensors that can turn chemistry into data is about a 100 years old. Sure. Maybe more. I mean, a lot of it was pushed forward in the Manhattan Project actually.
Speaker 7:Wow. But what we've been missing is a map. Okay. Right? So for sound, low to high frequency is a map, which lets us build m p three and speakers and microphones and Spotify, etcetera.
Speaker 7:And for color, RGB is a three-dimensional map of color. Yeah. And that lets us build CMOS, CCD, you know, cameras, etcetera. We haven't had the map for snow. 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.
Speaker 7:Wow. 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. Yeah. So you gotta go get a crap ton of information, right?
Speaker 7: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 5,000,000 sniffs digitized, over a quarter million physical samples created. We've digitized about 6,000,000,000 fragrance molecules.
Speaker 7: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.
Speaker 2:Remarkable. Jurewicz? How are you gonna make money
Speaker 4:on this?
Speaker 1:It's a good question.
Speaker 7:So if if if you go actually, let's talk. How can we make money on this?
Speaker 1:Yeah.
Speaker 7:So does TBPN have this scent?
Speaker 1:Yes. It's terrible. Terrible. There's rubber smell in the studio. There's in the studio
Speaker 2:there's like thousands of cords Cables. And cables. The cables And we we do a good job hiding them. But we have so much gear going everywhere.
Speaker 1:It's lot of rubber, a lot of to
Speaker 2:get these Racetracks. Racetracks, they're called to cover all the cables. And it turns out these things smell terrible.
Speaker 7:A lot. Those off gas. Yeah.
Speaker 1:They're off gas.
Speaker 2:So we wanted to give our viewers
Speaker 1:Yes.
Speaker 2:The the full
Speaker 1:experience. I think we actually do not. It would
Speaker 2:be like a can that sits on Yeah. Their desk Yeah. Yeah. Aerosol and it would spray a rubber smell into the room Yeah. So they could experience what we experienced.
Speaker 7:We capture it but I think we should fix it.
Speaker 1:So Yes.
Speaker 7:Really concretely, we raised our series b. We put an additional 70,000,000 in the bank Kinda. With two sigma leading luxe. Love that it got the gong. Congratulations.
Speaker 7:That 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 hundred seconds. And what we do is we design and manufacture fragrances for brands.
Speaker 1:Oh, yeah. That makes sense.
Speaker 7:And so we we use olfactory intelligence to So design super fast, data driven, basically, you know, perfect fit for the brand and for and for the consumer of that brand. And then we actually physically make it and what leaves our factory is a steel drum that fragrance oil and we build 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 Mhmm.
Speaker 7:So the full product comes out. So if you guys want to launch a TBPN Cologne or something like that, we could design it for you. I mean, like, if you tell me
Speaker 2:the prompt right now smell like burnt rubber.
Speaker 7:No. No. No.
Speaker 1:We're not doing burnt rubber.
Speaker 7:Burnt rubber. There's some it smells like disagreement.
Speaker 1:No. It needs to smell like like like old $20 bills. Okay. From the 19 That is insane. Mahogany.
Speaker 1:The official wood of business. Need to smell like mahogany That's with alright. With old $20 bills, the smell of money.
Speaker 7:That's Okay. Cool. We've done this we've done the smell of money one which we demoed actually on the New York Stock Exchange floor which
Speaker 1:is That's pretty amazing. That's amazing. But
Speaker 7:no, I'll I'll send you I'll we'll make something. I'll send it Talk to
Speaker 1:about sensor miniaturization. Phone has three cameras and no smelling sensor. Can we swap one of these out? Like I when you say mass spec, imagine like a device the size of a living room. I imagine that they are getting dishwasher.
Speaker 7:The size of the dishwasher?
Speaker 1:Is there a path to actually shrinking that down to something that's more Sure. Portable?
Speaker 7:So, yeah. In the same there's like many kinds of cameras, right?
Speaker 1:So the
Speaker 7:one in the Hubble telescope not getting smaller. So if you need resolution, it's got it's gonna be big. But you can make trade offs. 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 trade offs, which is what we've done. So we actually have a sensor right now.
Speaker 7:It's 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. Oh. So if you're buying a pair of, like, $500 Air Jordans, the reels smell different from the fakes.
Speaker 7:We can actually pick that up. That's crazy. Real from the we can
Speaker 1:Yeah.
Speaker 7:Yep. The the the counterfeiters use cheaper glues, turns out. Interesting. And the the other thing that's interesting is we can actually tell the factory of origin of the shoe 93% of the time. Mhmm.
Speaker 7:So there it smells a fingerprint. So we're already miniaturizing these devices. Look, the path to get from two shoe boxes to one shoe box is pretty clear. Yeah. We're working on that.
Speaker 7:To go to something that's like the size of the AirPods case, there's gonna be some like, part four engineering required. To have it be a component that fits in your phone, there's some breakthroughs like, can't quite see through the fog yet, but there's nothing like, look, our our noses do it. So there's nothing that mother nature is saying is like impossible. Yeah. But we just got a lot of work to do.
Speaker 1:Yeah. That makes a lot of sense. What about taste? How closely is taste linked? Talk me through the sommelier example.
Speaker 7:Yeah. So flavor is everything that happens in your mouth, you know, that's that's a sensory experience of food. Taste is not as like 10% of that. It's like what happens on your tongue.
Speaker 3:Like Yeah.
Speaker 7:You ever eat a jelly bean and like plug your nose?
Speaker 1:Yep.
Speaker 7:And you you just actually can detect very little of what's going on there? Yeah. It's because 90% of what you experience is actually called retro nasal olfaction, where when you're biting or biting on something, there's a chimney effect in the kind of the almost the steam of what you're eating goes back through your nose and you
Speaker 1:smell it. Oh. Excuse me.
Speaker 7: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 Meredi, but we're we're really focused on on this particular business.
Speaker 7:Yeah.
Speaker 1:I've seen a couple of these sort of I don't wanna call them niche, but, like, vertical AI projects that are not fully generalizable. There's a DNA model also from Google or D Mind. 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 10 x the computer, 100 x the compute that goes into some I believe
Speaker 2:Alex is ready for a one gigawatt data center.
Speaker 1:He can be trusted with
Speaker 7:that.
Speaker 2:I I I
Speaker 1:would trust you. But but Appreciate it. How universal do you think scaling laws are? Is there a scaling law here? Is it data based?
Speaker 1:Is it compute based? Both? How are you thinking about it?
Speaker 7:The better 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?
Speaker 7:Our current s curve is data, which is why we're maniacally focused on like generating a ton of data. Like, have a giant fragrance robot that spits out a ton of fragrances. We have mass specs running twenty four seven. We have sensory panels, both domestically. Have a building of people that just smell all day abroad.
Speaker 7:Wow. And we ship them crates of stuff to smell. How we get to 5,000,000 sniffs. Right?
Speaker 1:Sure.
Speaker 7:So data, data, data. The the the size of the models is not the limiting factor right now.
Speaker 1:Yeah.
Speaker 7:And it will be at some point, and then switch to the other s curve.
Speaker 1:Yeah. Yeah. Because you don't just have, like, the open Internet to scrape because there's not an existing data set. Makes sense.
Speaker 7:Totally. Double edged sword. Right? So we've had to make it all. Right?
Speaker 7: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.
Speaker 1:Yeah. Yep. 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.
Speaker 1:Yep. 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 and just growing the business?
Speaker 7:Yeah. So we're we're always going like, we we started with like this curiosity driven drive to figure out how to digitize Snell, which is like a pretty wacky thing to do. So that we're always going to be trying to push the edge here.
Speaker 9:Yeah.
Speaker 7:But look, we have a factory. We manufacture fragrance for brands. We did this commercial kind of r and d to commercial transition last summer. Sure.
Speaker 4:And we're
Speaker 7: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. We're making fragrances for brands. You can go into Target and buy a product that has our fragrance in it today.
Speaker 1:No
Speaker 7:way. 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.
Speaker 7:Sometimes you should come to the factory in in New Jersey and see how it operates. But like the fragrance industry is wild. Yeah. We've got a lot of work to do there, lot of opportunities, so we're focused on that.
Speaker 1:Amazing. Well, and thank you for the work that you do. We think it's so important.
Speaker 2:And One of the most interesting companies we've ever learned about on the show. Yeah.
Speaker 1:True science fiction. Awesome. I love it.
Speaker 7:And And we're trying to make science fiction into science fact but like open invitation to come see how it all gets made. It's crazy in person. So come to the Willy Wonka chocolate factory where all this stuff happens.
Speaker 1:I would love to. Thanks so much. It's so great
Speaker 2:to meet you. Come back come back on soon.
Speaker 1:Yeah. We'll talk to you soon. Have a 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.
Speaker 1:How are doing? Hello, guys.
Speaker 4:Good to
Speaker 6:be here.
Speaker 1:Welcome to the show. Sorry we're running a little bit late. Kick us off with an introduction on yourself and the company.
Speaker 4:I'm one of the founders and the CEO of Resolve AI. We're building agents that can help you debug and run production. Think of it
Speaker 1:Yeah.
Speaker 4:As the counterpart to coding agents that produce all this code Yeah. And our agents are there to support you.
Speaker 1:Okay. Are you always or is your customer always, like, deeply in the throes of vibe coding, has rolled out agentic coding across many organizations? Like, who is the target customer? Do they have to already be deep in the agentic coding wave to really get the value here?
Speaker 4:They they don't have to. But the two are correlated. Like, anybody who runs a lot of their system has this problem. The only solution we had so far is humans manually solving it. Right?
Speaker 4:Using the tools, being on call. Of course, now AI allows us to to automate all of this. Yeah. But I would say, this is true. It was true before.
Speaker 4:Now with all the AI generated code, it becomes a necessity. Right? So we see strong correlation between the two often.
Speaker 1:Yeah. And and what are what are customers coming to you asking? Is it is it I want the code that's that's, you know, written? We're writing way more lines of code. We want it be more readable, or we want it to be more secure, or we want it be more performant, or all of the above.
Speaker 4:The way to think about it is like, for anybody who's delivering their business through software
Speaker 1:Yeah.
Speaker 4:Look at some of our customers. Coinbase Sure. Salesforce, MongoDB. Right? Yeah.
Speaker 4:To them, reliability is of paramount importance. Sure. If anything goes wrong and affects customers, it's a big problem. Yeah. So resolve becomes necessarily the first level of defense Yep.
Speaker 4:That captures any problem that happens in production, but it 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.
Speaker 1:What is and, like, I mean, the the the company is now over $1,500,000,000 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 the the business as you scale evaluation?
Speaker 4:Yeah. So this is a very big problem. Right? Anybody who has, like I said, delivered three business software is facing this issue. Yeah.
Speaker 4:And whether you're a CTO, you know, who pays for, let's say, developers to focus on liability, or whether you're an individual that has solved this problem, you'd rather have AI do it for you.
Speaker 2:Yeah.
Speaker 4:So we've seen like huge amount of demand from day one since we launched the company a bit more than a year ago. Yeah. 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. Yeah.
Speaker 4:You know, given the complexity of the software. And, you know, most of the growth I guess most of the the the, let's say, the demand comes inbound to us Mhmm. Because it's a well understood problem. And, course, we have, like, both product led approach, let's say, but also sell side approach as we work with large customers.
Speaker 1:Yeah. In in in some ways, like, the naive approach would be, okay. Just point 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 or or creating, like, a special harness to understand the the these problems that can come up before they do?
Speaker 4: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. Yeah.
Speaker 4:Production involves code. It involves, let's say, telemetry logs, metrics like tools like Datadogs, Splunk. Involves AWS, right? So you have to deal with all of these, not just code. Yeah.
Speaker 4:And then, we also are training our own models now to improve, let's say, the state of the art, let's say, right? How far 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 on the agentic 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.
Speaker 1: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.
Speaker 1:At the same time, 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 how do you actually create enough training data to to justify a special model?
Speaker 4:What is important here to understand is like the training doesn't happen like on code per se. Right? What what happens on is actually the action a human takes to perform a task for the most part.
Speaker 1:Yeah. Yeah.
Speaker 4:And we're talking about very long kind of, let's say, planning tasks here. Right? It might take like many many iterations. Yeah. Looking at code, looking at Datadog, looking at infrastructure.
Speaker 4:Yep. So and this, generally speaking, this this is not in a training set of models. Mhmm. So and software, let's say, generally is a both deep and wide domain. Right?
Speaker 4:So I think if you actually focus on building a model for the types of problems we're trying to automate and how you run and 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 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
Speaker 1:I don't think that's the case.
Speaker 4:Yeah. And you know, that's what we're seeing ourselves with our investments.
Speaker 2:Yeah. That makes sense. How do you put together such a low dilution round? What what Yeah.
Speaker 1:Yeah. Tell us about the round. I wanna hit the gong.
Speaker 2:40 on 1 and a half billion.
Speaker 4:So it it is an extension. We we just did essentially the a.
Speaker 1:We just we just did the a at
Speaker 4:a billion dollars like two months ago. Right? And I would say, resolve.
Speaker 1:There we go.
Speaker 2:Sorry. Continue.
Speaker 4:Resolve is essentially in many ways created this market. Right? Like AI for production. Sure. And I think it's well understood by investors.
Speaker 4: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.
Speaker 4:Mhmm. And we have a lot of traction. Mhmm. So, I mean, as simple as that. Right?
Speaker 4:Like, there there's nothing you can do to create a low dilution route other than be very successful in my opinion these days.
Speaker 2:That's a great answer.
Speaker 1:That's a great answer. Step one, be successful. I love it.
Speaker 4:Step one, focus focus a on business. My first startup as a founder. Yeah. Yeah. I made this mistake many times before, right, of thinking that raising money is success.
Speaker 4:It's not. It follows real success on a product.
Speaker 1:Yep. No. No. That's a 100% right. I love it.
Speaker 1:Well, thank you so much. Congratulations on the new round.
Speaker 2:Yeah. Great having you on. Congrats on team. Excited to watch you guys come.
Speaker 4:Thank you.
Speaker 1:We'll talk to you soon. Cheers. Have a good day. Goodbye. Up next, we have Carolina Aguilar from InBrain Neuro Electronics building the first inhuman study of graphene brain interfaces.
Speaker 1:What's going on? Welcome to the show. How are you?
Speaker 11:Thank you. Very good. Thank you for having me.
Speaker 1:Please, since it's the first time on the show, introduce yourself and the company a little bit.
Speaker 11:Yes. My name is Carolina Aguilar. A lot of people call me Carolla. I am the CEO and the cofounder of InBrain New Electronics. Yeah.
Speaker 11:And we are a graphene based brain computer interface therapeutics company that actually is developing the most intelligent interface between the neural system and AI to restore health for billions.
Speaker 1:Okay. Alright. 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 noninvasive. We've talked to a number of founders that have taken either approach.
Speaker 1:How did you how did you confront that first question?
Speaker 11:Yes. Well, I call them implantable and non implantable systems. Yeah. Yeah? And in our case, we're an implantable company.
Speaker 11:Yeah. We believe that the real signal processing that is going within the neural system is actually deeper in the brain and and to listen carefully to what it says, what the neural system says, being able to decode it but also modulate it. Mhmm. We need to be close to those neurons and interact with those neurons firsthand.
Speaker 1: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?
Speaker 11:And this is, the the magic of graphene is actually about reading and writing very effectively at micrometric, precision within I the think that's why we took, let's say, higher risk to get an advanced material into this funnel Yeah. Because we see that the benefit is is incredibly impactful.
Speaker 2:Okay. What what are what are the most near term commercial applications?
Speaker 11:Yeah. So the the Morgan Stanley report stated the market in 400,000,000,000, and we thought that we needed to bring a platform with three product verticals to actually penetrate such a such a big market. Mhmm. So we are creating three products. One is, let's say, not implantable, actually.
Speaker 11:So it's a semi chronic it's a semi chronic platform, kind of like the modern Utah array. It's like a 100 contacts of graphene that can read and write. We we went into tumor and 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.
Speaker 11:So, this is an implant on the brain for Parkinson's disease. So, we didn't do, sorry, assistive BCI because we saw a 1,800,000,000 market that is suboptimal that we could actually displace very easily with this technology. So we decided to go therapeutics into Parkinson's. And the third one is the same platform, but instead of a, let's say, brain sensor, we connect a vagus 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.
Speaker 1:Mhmm. What about, the actual implantation process? We followed from, Neuralink. They had to build a whole robot just to drill into the skull. It's incredibly high precision.
Speaker 1: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?
Speaker 11:It's it's an excellent question. I'm coming from Medtronic. I spent ten years in neuromodulation and another three in diabetes. And I think in the future, when micro robotics are ready, we will have a a very close relationship between our interfaces and micro robots that probably can deliver this implantation in thirty 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.
Speaker 11:So we are not changing much from the neuromodulation workflows.
Speaker 1:Okay.
Speaker 11:And it's an easy procedure. Two hours one or two hours, you know, is enough. In the case of the neck, it's forty five minutes.
Speaker 1: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.
Speaker 2:Yeah. Great to meet you.
Speaker 1:Have a great rest of your day.
Speaker 2:Cheers.
Speaker 1: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?
Speaker 1:Welcome to the show.
Speaker 3:Yes. I'm doing
Speaker 2:I got a feeling you have the biggest number first.
Speaker 1:I think you have the biggest number as 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.
Speaker 3:We we have announced a $380,000,000 raise.
Speaker 1:And what will you be doing with all that money?
Speaker 3:Yeah. So our focus we're 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.
Speaker 1:Does that mean, like, less r and d risk or more in, like, the GE or Westinghouse territory, more like, you know, going with, products that have been derisked, but it's very expensive and maybe the underwriting is is is different this time around? Or or are you working on, an entirely new reactor design somewhere in the supply chain?
Speaker 3:No. You 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. Sure.
Speaker 3:So what bugged me and why I started the company
Speaker 1:Yeah.
Speaker 3: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 Yeah. Who are working on, you know, kind of the same old technology that we've been operating safely for seventy years. Yeah. But nobody was focused on the core issue of how do we build nuclear on time and on budget. Yeah.
Speaker 3: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 and physics degrees in the space and just felt like there isn't there hasn't been anyone really focused on the root cause issue. Yeah.
Speaker 3:So what we're doing is we're borrowing best practices from LNG and offshore oil and gas and offshore wind to prefabricate everything at existing oil and gas fab yards and shipyards, and then we barge it all as a prefabricated system on the order of a thousand or 2,000 tons to the operating site.
Speaker 1:Okay.
Speaker 3:And then really, you know, basically are 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 Yep. But we'll happily work with the gen four reactors as they as they mature.
Speaker 1:Cool. Take me through
Speaker 2:I feel like you've been wanting a copy
Speaker 1:this for a
Speaker 4:long time.
Speaker 2:I've been John John's John's point has been
Speaker 1:Copy paste.
Speaker 2:Copy paste. Hey. We know how to do this.
Speaker 1:It works. Like, is it. We don't need copy paste.
Speaker 2:Reinvent I mean, it's great if we wanna reinvent the wheel.
Speaker 1:Yeah. We need the next gen tech.
Speaker 2:New reactors. But
Speaker 1:But also more of
Speaker 6:this current gen.
Speaker 2:Let's just build some.
Speaker 1:Yeah. So my yeah. My question is about Vogtle. Lessons from the Vogtle project. What what do you think they did well that you wanna copy, that you wanna learn from?
Speaker 1:What do you what, if anything, do you wanna do differently?
Speaker 3:Yeah. So to kinda put some stats on Vogtle, it it, like so many other nuclear projects in the West, was 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. Yeah. It was over 40% of it was just the construction overhead.
Speaker 1:Mhmm.
Speaker 3:So it was the cost of training and relocating 10,000 skilled workers to book to the site at Vogtle, you know. Yeah. 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. Yeah. You have to set up a nuclear quality assurance program in the field.
Speaker 3:So there's all this overhead. It's basically like building a small town. Yeah. And then the hope is that you'd be able to move that, traveling circus around from site to site.
Speaker 1:Yep.
Speaker 3:And then a third of the project cost was just capitalized interest on debt because it took over ten 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 off-site. We're keeping the workforce centralized at the Fabyard and the shipyard where they already are so we can start to put Nuclean to a learning curve
Speaker 1:Yep.
Speaker 3:And drive the cost down over time, akin to what we've seen in wind, solar, batteries, and gas turbines. You know, what they did well was it was a mature light water reactor technology. It's a passively safe reactor technology. They they really pushed the the world forward a little bit in licensing space and steel composite structures, which we're looking into as well. They actually had this is not well known.
Speaker 3: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. Yeah. And they said, alright.
Speaker 3:Let's just truck it in. And then they had to truck it in and build a module assembly building on-site.
Speaker 2:Remind me
Speaker 6:So they ended
Speaker 3:up doing all the welding on-site.
Speaker 1:Yeah. Think way the remodel from night nightmare remodel. Very interesting. I yeah. I'm I'm I'm I'm I'm fascinated
Speaker 2:by company Where is based? Where are you guys based?
Speaker 3:We're in Chevy Chase, Maryland, pretty close to NRC headquarters. And then we've also got a big presence in Edinburgh, Scotland Yeah. Where there's a lot of offshore engineering talent, particularly from, like, kind of the history of shipbuilding and offshore oil and gas. Yeah. And then we've also got an office in Houston Yeah.
Speaker 3:Also in kind of offshore oil and gas capital world.
Speaker 1:Okay. I I read a blog post about one of the potential problems or stumbling blocks that nuclear projects run into, and I want a 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.
Speaker 1: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, you know, 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 the regulation is more locked and deterministic so that I imagine you're not gonna build this overnight.
Speaker 1:But Yeah. If it takes you a couple years, you know that the the the contracts that you put in place, the plans that you put in place today will hold and you won't face a massive Yeah.
Speaker 3:So that was another one of the big learnings from Vogtle. Vogtle was the first and still today, I think, 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
Speaker 6:it Mhmm.
Speaker 3:During construction. Mhmm. So every time they encountered something and said, oh, we need, you know, load the craft labor, wound the rebar clockwise instead of counterclockwise, you know, they had to jackhammer it up.
Speaker 1:Yep.
Speaker 3:Or they had to go and reapprove 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 slightly different licensing process, the original licensing process of part 50, whereby we're gonna 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 contract environment with these fab yards and shipyards, it forces us to go to something like 60% detailed design upfront and locking those designs because that is what is gonna be coming in prefab from the fab yard.
Speaker 1:Yeah.
Speaker 3:So it's 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.
Speaker 1:Sure.
Speaker 3:Like, this is a critical juncture in the history of nuclear power that we can take advantage of, with where the NRC is presently at.
Speaker 1:What is the power output for the first reactor that you're targeting to bring online?
Speaker 3:So we are focused right now for the first project using light water small modular reactors, which the the power range of the units we're looking at range between 50 and roughly 300 megawatts Yeah. Per Yeah. Each site we're targeting doing is gonna have multiple units. So we're it's gonna be a gigawatt to a gigawatt and a half per site because multiunit operations That
Speaker 1:makes a lot of sense.
Speaker 3:Is is important. Yeah. And it helps drive down costs.
Speaker 1: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. It's the worst question. But we talked to a lot of nuclear founders, and we hear a lot of twenty thirties, and there's a whole bunch of projects with hyperscalers and big tech companies that are looking at 2032, 2035.
Speaker 1:It's exciting. Better, you know, 2032 than never. But do you have, anything to share on, like, the the timeline of rolling out new nuclear capacity in America?
Speaker 3: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 gonna be building half the nuclear plant right away.
Speaker 7:Okay.
Speaker 1:So the
Speaker 3:whole nuclear steam turbine system set up for nuclear steam conditions and quality. And we're gonna fire it early with two combustion turbines as a two on one combined cycle. Oh. So it's kind of a Frankenstein combined cycle. We've actually gotten the NRC to buy off on this methodology, through a top report recently.
Speaker 3:So that allows us to actually project finance half the CapEx for a first SMR, and then we will build the reactor and splice in the steam and switch it over from gas steam to nuclear steam. So that actually accelerates our commercial operation date with confidence. Interesting. So we're looking at generating first power in 2030, 2031, mostly driven by gas turbine delivery dates today.
Speaker 1:Yeah.
Speaker 3:And then our first nuclear commercial operation, we're looking at 2032.
Speaker 1:Okay. So is that is that switch out possible at any legacy natural gas infrastructure site in America currently? Because that seems like an environmentalist dream. Right? To say yes or no.
Speaker 3:Yes. So I think this opens up a whole new world of fossil to nuclear convergence, which we think is an important precedent to set.
Speaker 1:Yeah. It seems huge if possible. But, yeah, I imagine that, you know, it's not exactly USB C on both sides, but hopefully one day we can build the adapter.
Speaker 3:That's right. Yeah. The what we're really focused on is, you know, there there's a lot of announcements out there, a lot of sometimes, you know, noise of what you know,
Speaker 7:there's a lot
Speaker 3:of exciting things happen in the nuclear sector. Yeah. We think we've got the first project, financeable nuclear project, And the first one that's gonna power it'll be a new build that powers a new AI data center. Yeah. So we're excited about that.
Speaker 3:And we think our timeline is is credible is aggressive, but credible and defendable. Yeah. And we've got the right set of partners around it to make it happen.
Speaker 1:That's amazing. Don't use the word data center. We're using the word supercomputer. Supercomputer. They're supercomputers.
Speaker 1:They're supercomputers data center. Everyone likes a supercomputer. Yeah. Anyway, thank you so much for taking the time to come chat with
Speaker 2:us. To meet you, Jacob. I'm sure you'll be back on soon. Good luck with I really we really appreciate your approach. Yeah.
Speaker 2:Feels like you're you're making plays and Yeah. I like how pragmatic and It's
Speaker 1:very pragmatic.
Speaker 2:Innovative the approach is at the same time.
Speaker 1:It's great stuff.
Speaker 3:Thank you. Appreciate your
Speaker 1:you soon. Cheers. Goodbye.
Speaker 2: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.
Speaker 1:An absolute steal. They're giving them away at that price. It's electric. Right? So you don't have to deal with gasoline?
Speaker 1:You don't
Speaker 2:have to do Yeah. You save a lot on gas.
Speaker 1:You don't you don't have to deal with all the noise that comes out of a v 12.
Speaker 2:Yeah. You save on gas. Yeah.
Speaker 1:Oh, well, yeah. I mean, if you're saving on gas and you're driving I mean, if if if oil keeps spiking and gasoline goes to a thousand dollars a gallon and you're filling 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.
Speaker 2:Think Yeah.
Speaker 7:Ferrari Luche.
Speaker 2:There's really gonna be a, like, what kind of Ferrari client are you moment?
Speaker 1:No. I think it'll be a statue because you see someone with this, you will
Speaker 2:know they can eat $300 of depreciation.
Speaker 1:And you know that they are that they are high on the list for the f 90. Like, 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
Speaker 8:for sure.
Speaker 2:Very interested to see how this does in the market. And the good thing is if you are excited about the Luche, 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.
Speaker 1:Probably. Probably.
Speaker 2: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.
Speaker 1:Leave us five stars and have a podcast in Spotify. Throw that flash bang. Sign up for our newsletter, tbpn.com. Goodbye.