TBPN - 🔴 CODE RED 🔴, AWS CEO Joins, Tae Kim Tells All | Matt Garman, Tae Kim, Tarek Mansour, Matt Mullenweg, Jason Fried

Episode Date: December 2, 2025

(00:19) - Papperger Pushes Rheinmetall to Top (13:35) - 𝕏 Timeline Reactions (16:11) - Anduril Says Failures are Part of Development (20:21) - 🔴 CODE RED 🔴 (38:35) - 𝕏 Timelin...e Reactions (56:20) - Stratechery: Gemini Spurs New AI Infra Race (01:30:37) - 𝕏 Timeline Reactions (01:42:23) - Matt Garman, CEO of Amazon Web Services (AWS), discussed several key announcements at AWS re:Invent 2025, including the introduction of frontier agents designed to enhance software development, operations, and security through autonomous capabilities. He also highlighted the launch of Nova 2, AWS's latest Frontier AI models, and Nova Forge, a tool enabling customers to integrate their own data into pre-training checkpoints to create customized models. Additionally, Garman announced the general availability of Trainium 3, AWS's new chip aimed at accelerating training and inference processes for customers. (01:55:08) - Tae Kim, a senior writer for Barron's and author of "The Nvidia Way," discusses Nvidia's unique corporate culture under CEO Jensen Huang, emphasizing its blunt communication style, agility in decision-making, and meritocratic approach to talent recruitment. He highlights how these factors have contributed to Nvidia's sustained success and ability to outmaneuver competitors. Kim also addresses the company's strategies in navigating challenges such as competition from Google's TPUs and geopolitical issues affecting sales in China. (02:23:05) - Tarek Mansour, co-founder and CEO of Kalshi, a leading prediction market platform, discusses the company's recent $1 billion Series E funding round, which elevated its valuation to $11 billion. He highlights the mainstream adoption of prediction markets, attributing this shift to factors such as declining trust in traditional media, the legalization of such markets, and their integration into daily activities like sports viewing. Mansour also addresses Kalshi's strategic partnerships with platforms like Robinhood and Coinbase, emphasizing their role in driving user engagement and expanding the platform's reach. (02:42:16) - Matt Mullenweg, co-founder of WordPress and CEO of Automattic, discusses the recent live release of WordPress 6.9, highlighting its development by over 900 contributors worldwide. He emphasizes the importance of freedom in technology, advocating for open-source licenses as a "bill of rights for software." Mullenweg also introduces Beeper, a service that consolidates various messaging platforms into a single interface, aiming to enhance user experience across different networks. (02:53:06) - Jason Fried, co-founder and CEO of 37signals, is renowned for developing web-based productivity tools like Basecamp and HEY. In the conversation, he discusses the launch of Fizzy, a new Kanban-style project management tool designed to be simple, colorful, and open-source, aiming to bring vibrancy and ease of use to the software industry. Fried emphasizes that Fizzy is built for their own needs, reflecting their philosophy of creating products they personally find useful, and offers it at a straightforward price of $20 per month with unlimited users and usage. TBPN.com is made possible by: Ramp - https://ramp.comFigma - https://figma.comVanta - https://vanta.comLinear - https://linear.appEight Sleep - https://eightsleep.com/tbpnWander - https://wander.com/tbpnPublic - https://public.comAdQuick - https://adquick.comBezel - https://getbezel.com Numeral - https://www.numeralhq.comAttio - https://attio.com/tbpnFin - https://fin.ai/tbpnGraphite - https://graphite.devRestream - https://restream.ioProfound - https://tryprofound.comJulius AI - https://julius.aiturbopuffer - https://turbopuffer.comPolymarket - https://polymarket.com/fal - https://fal.aiPrivy - https://www.privy.ioCognition - https://cognition.aiGemini - https://gemini.google.comFollow TBPN: https://TBPN.comhttps://x.com/tbpnhttps://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231https://podcasts.apple.com/us/podcast/technology-brothers/id1772360235https://www.youtube.com/@TBPNLive

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Starting point is 00:00:00 You're watching TVPN. Today is Tuesday, December 2nd, 2025. We are live from the TBPN Ultradome, the Temple of Technology, the Forteous of Finance, the capital of capital ramp.com, baby. Time is money. Save both. These to use corporate cards, bill pet, accounting, a whole lot more, all in one place. That's right.
Starting point is 00:00:19 Why is no one talking about Armin Pappager? He's the CEO of Reinmetall, and they've been on an absolute tear. of course going to get to Code Red. We're going to talk about Open AI, but we talk about Open AI every day, basically. And I thought it'd be interesting to meet the CEO behind the world's fastest growing defense company. It's on the cover of the business section of the Wall Street Journal. When I think high growth defense companies, I usually think Anderl or, you know, Seronic, or there's so many other companies that are growing very fast in defense tech. Ryan Mattal's been on an absolute tear. They're now basically the same size as Lockheed Martin and
Starting point is 00:01:00 General Dynamics. And it was a small company just a few years ago. So Ryan Battal, they make, you can see the gun that they make in that picture. They make a massive cannons. They make artillery shells. They've been very important to the Ukraine war. So in the last three years, they've been on an absolute tear. They've gone from roughly $5 billion in market cap three years ago to $80 billion in market cap.
Starting point is 00:01:25 We've got to ring the gong. We've got to warm up the gong. Ring the gong. 80 billion market. cap. They've been on a tear, but they had, and there's been like three, they've been basically three key drivers to the growth, to the story. We'll tell the story in three acts, as briefly as we can. And while we, while we do, we will say thank you to Gemini 3 Pro. Three-act story about Rayne Matal, three-act Gemini, Google's most intelligent model yet, state-of-the-art reasoning,
Starting point is 00:01:55 next-level vibe coding, and deep multimodal understanding. So, first, they had a head start. This company, they actually started it over a century ago. 1889, can you believe that? Very, very old. So they spend their first 25 years basically just stacking up ammo for the German Empire. This obviously comes to a head in 1914 when World War I breaks out. And at the time, the company was one of the largest arms manufacturers. Like they were pretty big after 25 years of just stockpiling ammo, growing, growing, growing as a defense company.
Starting point is 00:02:32 World War I breaks out. But then after the war, they got to pivot. They got a pivot because the treaty of Versailles forces them to switch to non-military products. They say, hey, you got to build. Make some trains. They get fixated on trains. And also typewriters. Not the first group to get fixed.
Starting point is 00:02:50 Fixated on trains. Happens to the best of them. But they have a good run. They stay in business. They keep making trains. Locomotives, particularly. You know, they're making big stuff. And then 20 years later, it's the mid-30s, 20, it's 1935 around there.
Starting point is 00:03:07 They are, they're starting to get back into weapons and ammo production. They can't stay away. Who are they rearming? The Wehrmocked. And World War II, obviously, it's massive for production. They're printing. They're making lots of weapons. But by the end of the war, their facilities have basically been destroyed by areas.
Starting point is 00:03:27 They need to rebuild the company from scratch. So after the second war, they get banned from making weapons again until 1950. Keeps happening. And so they have to go back to making typewriters. They keep getting relegated to typewere, like, you guys, no more guns. That's enough. You have to make some typewriters. And so they get back into defense tech in the 50s, 60s.
Starting point is 00:03:48 The German Armed Forces gets reestablished in 1956. And by 1979, Ryan Matal is making 120 millimeter guns that go on leopard tanks that you've probably seen in that image roughly. And so there's lots of M&A, lots of diversification over the next few decades. They expand into automotive and electronics, and that kind of brings us to the second act of the story, which is the Ukraine War.
Starting point is 00:04:10 So Russia invaded Ukraine on February 24th, 2022, about three years ago. Ryan Mottal was around $5.5 billion, market cap then. And three days later, Olaf Scholes, the Chancellor of Germany, gives what's known as, the Zaytonwold,
Starting point is 00:04:29 Zytenwenda speech, which is literally translates to turning point. So he says, this is a turning point. Europe has been invaded. We now have a foreign army on European soil.
Starting point is 00:04:40 Even though Ukraine's not part of NATO, it feels like, you know, Russia is expanding. If they just keep going in the same direction, they're eventually going to be in our hometown. So we got to do something about it. And what does he propose?
Starting point is 00:04:51 He doesn't just say, hey, this is a big deal. He says, no, we're actually going to invest $100 billion, like off balance sheet from some fund into defense tech, we're going to spend more money. And then, of course, there's a whole bunch of other initiatives that happen. There's the Trump negotiations around how much Europe should pay as a portion of GDP on defense. But basically, it's this major turning point where Europe goes
Starting point is 00:05:13 from spending, you know, sustainment levels. Okay, we're going to spend this much every year. We are going to double or triple or, you know, exponentially grow our spending. And it's all going to be net new. So you can go and fight for it. And that's what Ryan Matal does. And so. So revenue has grown. Helsing is sort of born out of that era. Helsing is like the newer version of Ryan Mattel. Ryan Mattel is like the old, you know, roll up. It's been around for over 100 years.
Starting point is 00:05:37 Helsing, I think it started. Helsing was 2021. Was most recently in the news because they raised, I think, $600 million from. Daniel Eck, right? Yeah. sparked controversy, of course. A lot of people in the Spotify world, the world of music. Just think that defense tech is defied back.
Starting point is 00:05:55 Oh, I didn't realize that. There was actually backlash. Totally. I didn't see that. You know, if you're an artist and you, you know, believe in peace at all cost, you're going to probably be against that. It depends. Maybe if you're, you know, POD or you're some other, you know, musician that was played
Starting point is 00:06:18 during the war on tear, you could be very pro, the Helsing investment. It's possible. But yes, I understand. Overall. So, revenues grown 50%. since 2022, and they are now guiding for sales. I think they do maybe around like 10 billion euros. I was kind of going back and forth on euros, USD, but they're guiding for sales of $58 billion in an operating margin of more than 20% by 2030. So they have like almost AI growth level numbers
Starting point is 00:06:47 of everything. It feels very similar where there's a structural change in the way their business is going to work. Same thing as Eli Lilly, same story. There's a couple of these stocks, where there is now sort of a mega trend and they are in position to capture a ton of value as long as they can execute. The big question is, you know, what winds up happening? But the third leg of the stool,
Starting point is 00:07:09 the third important piece in this story is the current CEO, the man no one is talking about, until today, Armin Papyrger. He's been called a white-haired Goliath. I love that. CNN, just randomly through that.
Starting point is 00:07:23 Can we pull up a picture? Just randomly threw that in. There he is. There's some other photos. And last year, he was targeted in an assassination plot by the Russians. What? So the CNN reported that Russia had made a series of plans to assassinate several defense industry executives all across Europe who were supporting Ukraine's war effort. And they also were planning to set up fires in different, there was an IKEA that got lit on fire.
Starting point is 00:07:51 There were a number of different attacks. But fortunately, American intelligence discovered the plan. plot and informed Germany in time to stop the attack. And now the white-haired Goliath is... Ryan in the chat says, this feels like a paid ad. For who? I can assure you it's not. John woke up this morning.
Starting point is 00:08:08 We're at the gym, and he's like, why is no one talking about Rhymetol? Yeah. And decided to write about it in the newsletter today. That's funny. No, he's on the cover of the Wall Street Journal. And so... So they stopped the attack.
Starting point is 00:08:25 And so Russia clearly sees Armand Papinger, Popperger, as a critical to the European defense ecosystem. But separately, there is a debate over how, like, where the business goes over the next few years. Because on the one hand, like the NATO inventory requirements are growing a lot. That's going to drive a lot of net new demand for military equipment purchases. And the market's been historically undersupplied. But on the flip side, Ryan Matal may or may not be able to absorb as much of the demand as They're planning too. They have lots of integration to do between all their different acquisitions.
Starting point is 00:09:00 And also with a potential end of the Ukraine war. Yeah, it feels like the stock would just immediately trade down on news of a peace deal. And it has, even on rumors of a peace deal. Yeah. Exactly. Yeah, it's down 15% of the last month. Yeah. But they're scaling up in the Wall Street Journalists.
Starting point is 00:09:18 Earlier this year, Armin Papurger opened a new factory that will allow his company to produce more of an essential caliber of artillery. shell than the entire U.S. defense industry combined, surrounded that day by dignitaries, including the head of the North Atlantic Treaty Organization, NATO. The Ryan Mottal CEO is riding a wave of post-Cold War military spending that is reshaping the global arms trade. Ryan Mottal is now the world's fastest growing large defense company and a key player in Europe's quest to rearm its home country. Germany is shedding its post-war reticence on military spending to lead the charge. To capitalize, Pappager has,
Starting point is 00:09:55 pushed the once obscure gun barrel maker into almost every part of the battlefield from satellites to warships. And that's what people are kind of saying about, there's a lot of acquisitions, there's a lot of new projects, there's a lot of new deals. Like, you know, the gun barrels, they've been doing that for 136 years. Satellites, they're kind of newer to it. Do they have the lineage? Do they have the experience? Can they stick the landing on those contracts? The money's certainly there.
Starting point is 00:10:22 But is the expertise there? That's the big question. So his goal is to create a go-to defense company with the heft and breadth to rival the American giants that have dominated the industry since World War II. And if he's writing any software, he's got to get on graphite.com. Code review for the age of AI. Graphite helps teams on GitHub ship higher quality software, bastard. Ryan Mital's stock is up 15x since Russia's full-scale invasion of Ukraine in 2022, giving a market cap of 80 billion, roughly on par with U.S. rival. and when he took over the job, he started this job in 2013.
Starting point is 00:10:59 So he's been CEO of Ryan Mattel for 12 years. The company was $1.6 billion. Overnight success is right. Sort of like what happened, Lisa Sue. You know, she's 10x that stock. I mean, the funny thing is that Jensen's also 10X to NVIDIA in that time. But the Lisa Sue story is a little bit more impressive because AMD was really like down in the dumps and she has turned that company around fantastically.
Starting point is 00:11:26 But back to Ryan Mittal. This month, Ryan Mattel set out ambitions to quintuple sales by the end of the decade to the equivalent of roughly $58 billion. Papberger reflecting on his long tenure at the company told investors that seeing such figures was like a wonder world. It's a wonder world. I love when an executive is speaking a different language and it just doesn't quite translate. Like, is that what we say?
Starting point is 00:11:52 Kind of get the gist. I get the gist. He's happy. I'm happy for him. You know, good job. We had a, we had a buddy of ours who, actually, I'm just going to, I'm going to name, I'm going to name, I'm going to name him. I was going to keep him anonymous, but it's just too funny. Somebody's proposed, 2.6 is proposing the TBPNX standard oil X, Ryan Mattall collab.
Starting point is 00:12:13 So we were talking about, we were texting with Sean Frank and Connor McDonald at the Ridge yesterday about how they're black, Cyber Monday went and they shared a bit on it and Sean ends it and says bro the future is beautiful and I am so happy to be alive with this like an incredible reaction to a successful Black Friday. I'm so glad it went well for them. I mean the Wall Street Journal did report that on a busy Cyber Monday outage at Shopify Haltz transactions. Shopify experienced an outage on Cyber Monday that interrupted transactions for some merchants but it sounded like it was not affected. Well, so it was the real issue was the admin panel went down. Okay. It freaked a lot of people out because you're not able to log in and see what's happening.
Starting point is 00:12:57 Yeah, of course. And also, like, even if everything's working as standard as expected, like, that's the day you're just refreshing the admin panel all day. Like, because you're just like, how much money am I making? Like, this is really critical, right? Yeah. So, yeah, there were some reports that a handful of merchants had actually had features on their site go down. Yeah. I didn't see any.
Starting point is 00:13:17 I didn't see a ton of people saying, like, I lost my Cyber Monday, but obviously, the good folks at Shopify will obviously be working extra hard to resolve any of this and provide a proper postmortem. Overall, it does seem like Cyber Monday and Black Friday, Black Friday, Cyber Monday broadly just went very well. Like, it just seems like consumer confidence was up, revenue was up, spending was up. Harley had a post, he said, total global Black Friday, Cyber Monday sales by Shopify, merchants over the last five years. 2021 was 6.3 billion. 2020 was 7.5 billion. 20203 was 9.3 billion.
Starting point is 00:13:54 2024, 11.5 billion. And then 2025, 14.6 billion. So combination of execution at the company level and execution at the Shopify level. And then obviously the market plays a big role as well. Yeah. It really did seem like things are just broadly going well or at least okay. I think everyone's sort of like nervous with with crypto up and down and
Starting point is 00:14:24 is there an AI bubble and how big of a bubble? What will happen? Somewhat of a coat red going on. It has been a code red. Before we jump into that story. Profound. Get your brand mentioned in chat GPT. You reach millions of consumers who use AI to discover new products and brands. I was going to say kind of the andoril was covered in the Wall Street Journal. The Wall Street Journal's been doing quite a lot of defense tech coverage. Anderl, they had been talking about their approach of not using government funding for testing purposes, which historically company would get a contract and then they would work to actually make it. And so the government was effectively funding R&D. Anderil has a more traditional like venture style model where they raise VC dollars. They
Starting point is 00:15:08 spend that money to test and develop products. And so they gave a quote that was like, we do fail a lot, but the extra context that was necessary was that that's not happening on the on the taxpayer's dime. Yeah. And it's part of their, you know, approach of doing rapid iteration and sort of like going according to plan. Of course, that was taken out of context and turned into a headline that was, we do fail a lot. And not so dissimilar from what has happened to Open AI in the last 24 hours where sounds like an internal, internal meeting was leaked. We were wondering, like, what is it? Well, we can, yeah, let's actually,
Starting point is 00:15:53 let's actually reel a little bit more on the, on the Wall Street Journal, Anderall thing. Because I think it's interesting. And I want to go into some of the response, like how they responded to this. First, let me tell you about cognition, the team behind the AI software engineer, Devin, crush your backlog with your personal AI engineering team.
Starting point is 00:16:11 So, Wall Street Journal came out with this story. we do fail dot dot dot dot a lot it's a very funny quote i actually think it's an awesome quote we'll get into it i think they should put on t-shirts and hats like i think it's actually a very their next campaign i think it's a very key cultural i think it's like a don't work at anderol type moment it makes a ton of sense in terms of like the the culture of like fail fast this is this is not new in silicon valley and yet it's still being reframed as new it's i'm surprised that there's like alpha here still but uh let's see palmer luck you says the valley reasons for slowness are bureaucratic BS and cowardly executives who cater to snide analysts
Starting point is 00:16:50 and public market outlets like WSJ that have nothing to say about years late programs and everything to say about a fire that covered 0.0002% of our test site. I'm not even exaggerating. That's the real number. It is exactly what anyone would expect from testing a system that violently blasts lithium-powered drones out of the sky. This is what weapons development should look like. Camp Pendleton has over 200 fires per year on their training range and that is with fully mature weapon systems Going on and on about this for paragraphs is so pathetic Oh no getting close to a fire every single weekday Yeah, they obtained satellite imagery that reveals the damage to the grass on the weapons test
Starting point is 00:17:33 range The other the other examples of the story are similarly absurd John you're telling me that the grass was damaged at the explosives testing ground? Yeah. You're telling me something... You're telling me there was an explosion at the weapons testing facility. Yeah, it was wild. The other examples in this story are similarly absurd.
Starting point is 00:17:57 Oh, no, an engine sucked in a piece of fad. Stop the presses. Autonomous boat behaves exactly as designed and stops moving when it receives a faulty command, and are all hit by pattern of setbacks. It's just so pathetic. The type of thing that can only be written and taken seriously by people who have no idea how hardware development actually works. And of course, a few other folks in the ecosystem chimed in.
Starting point is 00:18:20 Mainly, there's a good post here from Blake Scholl, founder of Boom Supersonic, he says. If you plan to pass every development test, you'll move slowly and expensively. It's optimal to fail many dev tests. Selective, quote, outtake into headlines suggest a hatchet job, not an honest report on an attempt to do things differently and better. Yeah, I still just think the, uh, the, uh, the, we do fail a lot is just, it's so ripe for a billboard campaign, a t-shirt, a hat or something, because, uh, it, if you, like, the whole thing with Silicon Valley is that you should fail 99 times and get up again.
Starting point is 00:18:58 And succeed once, because if you succeed once and fail 99 times, it's a million times better. It's infinitely better than zero, zero failures, zero successes. Like, like, like, you will take a. ton of failure for one success. And that's the whole, that's the whole ethos. That's the American ethos. That's the, yeah, it's the American ethos. It's the technology ethos.
Starting point is 00:19:19 There's a lot there. Anyway, back to, oh, actually, right, we can wrap up with, you can go read the Wall Street Journal report on Armin Papager, if you, Papager, if you want. We've got to figure out how to pronounce this name. He did have one, one fun line in here, which was, what did he say? He said something like, he said, referring to, so now he's, you know, basically the same value as Lockheed Martin in general, the dynamics. And he said, on the U.S. companies, he said, they come to me 10 years ago. It was a different story.
Starting point is 00:19:56 And so he's just flexing the fact that, like, he's now big enough that he, he, he requires, like, you can go visit him because he's like, made it. Always a good sign. Yeah, he's taking a little victory lap. And there's some other funny things in here. But you can go read that. Let me tell you about linear. Meet the system for modern software development. Linear streamlines work across the entire development cycle from roadmap to release.
Starting point is 00:20:23 So let's head over to Red Alert Territory. Gavin Baker responding to the reporting says October, 1.4 trillion in spending commitments. November, rough vibes. In December, code red. Life comes at you fast. It certainly has felt, it certainly has felt fast ever since that fateful podcast. Yes, that was a crazy turning point. Although there was plenty of conversation, you know, prior to that around,
Starting point is 00:20:54 yeah, around what the trajectory of open AI would actually look like. Yeah, it's hard to actually understand the full nuance here. Like somebody in the replies, a rational analysis. insane, at insane analyst. What a crazy handle. So as debt obligations come at you fast, and it's like, that's not really what's happening here. Like, like the,
Starting point is 00:21:17 the code red, like, leak from this, the information reported. It was clearly like some sort of all hands that Sam Altman was, you know, holding a town hall with the rest of the Open AI team. And he's kind of just saying,
Starting point is 00:21:30 like, lock in. That's what he should have said. You never say code red. You got to say, lock in, brothers, lock in. Don't say, Rough vibes.
Starting point is 00:21:38 Don't say rough vibes. Code red. Say lock in. Say, we're taking that hill. We're storming their fortress. We will grind Google Gemini team into paste with, and we will crush our enemies. We will see them driven before us. Hospitals learned this lesson.
Starting point is 00:21:53 Yes, they used to say code red. That meant there was a fire in the hospital. And that you would probably want to figure out a way to get out. Yes, yes. They started, is it code blue? Yeah. Now they will say code blue. So if you hear code blue in a hospital,
Starting point is 00:22:08 yell code red and run. You need to be worried. You need to worry. But maybe, maybe, okay, steel man, steel man here, maybe Sam Altman was using code red in the hospital sense. He didn't say code blue. If he had said code blue, we should be really worried. But he said code red.
Starting point is 00:22:26 So he's saying it's not that bad. But don't you think they just retired? I think they just retired. Yeah. So he's saying, I'm using retired phrase. I'm not, I'm not saying code. If I was saying code blue, you could have used code brown, which is a hazardous spill. Okay.
Starting point is 00:22:41 Which Gemini 3 spilled on the timeline. It's very hazardous. We got a code brown. Yeah, we got a code brown. That's a crazy. Is that real or is that some like meme joke? No, this is, no, no, I'm reading the hospital emergency code. Okay, okay.
Starting point is 00:22:56 Well, anyway, let me tell you about Restream. One live stream, 30 plus destinations. If you want a multi-stream, go to Restream.com. Chiching. No, I think if you're, if you're a CEO who's under incredible scrutiny, like you're Sam Alpin, and you have beat reporters at this point who are texting your employees every single day, hey, what's going on, what's on the ground? Give me a quote.
Starting point is 00:23:21 What happened? Yeah, so to give people, to give people context, the beat reporter, a beat reporter might reach out to, they will actually adopt the strategy of just trying to wear someone down where they will send hundreds of messages to individual people on the team, just over and over and over, relentless, like, email, cell phone, Instagram, DM, LinkedIn, just like constantly, constantly, constantly, constantly flooding, hoping that at some point this person just says, like, fine, like, I'll chat with you. The name, Beat Reporter, comes from them trying to beat you down.
Starting point is 00:23:54 That's the whole point. Is that true? That's where it comes from. No way. Yeah. Are you missing with me? Yeah. I got messing with you.
Starting point is 00:24:02 Okay, okay, okay. I have no idea. But I like the idea of it. It's like, they just try and beat down your employees. They're trying to beat you down. I got a beat reporter on my team. I was like, on my tail. Yeah.
Starting point is 00:24:13 Yeah, no. I mean, it's certainly what it's, what it's become. There is a little bit of it. No, no, I think there's B reporting. There's gumshoe reporting. Gum shoe reporting is where you report and you're actually walking around the town so much that you get gum on your shoes. That's the idea.
Starting point is 00:24:31 It's like you're on the ground reporting, you're walking around the city, you're talking to people. And then I think like a beat cop and beat reporting is like you're on a beat, like it's a drum beat. Like every day you report on the same thing. And so it's about consistency. It's not, it's not, what are you laughing at now? Ryan in the chat, if you work in an AIS startup and you aren't drinking Mountain Dew code red every day, you aren't going to make it. What if Sam was talking? What if he was just saying we got to lock in?
Starting point is 00:24:58 We got to lock in. I bought us a bunch of code red every day. I want you all drinking it every day. Yes. It's time to really focus. Yes. And of course that snippet got pulled out. I just want to know what person on the OpenAI team thinks it's in their best interest to be in a meeting like that and then just go share inflammatory quotes on said meeting.
Starting point is 00:25:23 Just leave. Just go make 10 times as much money in a different lab. You know, if you don't like your employer, just bounce and make more money. Like, why are you, why are you sitting there leaking and just dragging your company down? Don't you have stock options? Yeah, that's what you there? I'm so, I'm so confused. It's a mole.
Starting point is 00:25:41 There's a mole. There's someone inside the organization who's working against them or something. I don't know. Seems rough. Anyway, there is some praise for Open AI on the timeline, which we should get to you from none other than Blake Robbins. Blake says, Open AI is operating on a different level. Play a sound cue, Jordi.
Starting point is 00:26:00 the amount they have shipped in the past few weeks and months is incredible feels like we are witnessing a generational run this was on october 6th okay this was on october 6th sora was i think number one in the charts at that point yes it's now 21 yes uh pulse was got some excitement early on but uh i think people are a little bit not feeling like as excited Yep. Atlas launched. Yep. And then it's hard to really gauge what adoption has been like. I know some people that love it.
Starting point is 00:26:39 So, Eric Sufert on October 6th, quote tweeted Blake Robbins and kind of summed it up. I think he said, indeed, impressive. But the scattershot nature raises questions about the company's discipline and ability to support these disparate initiatives. is OpenAI a frontier research lab, a social network operator, a commerce engine, a hardware company, because it's hard to do all of that well.
Starting point is 00:27:06 And then Eric goes back and finds his old... And they're still like very much care about competing in code gen, right? Yeah, that seems like really important. And so if you go back, if you go back to the BG2 interview or just the BG interview, Sam's answer to the question, the question of how are you going to support the 1.4 trillion of commitments was we're automating
Starting point is 00:27:32 science and we're making and we're making like consumer electronics and the reason that that that didn't to me that that was kind of like a concerning answer because yeah google has been doing those things for years yeah but they've earned the right because they have 25 years funding it with massive cash flow Yeah, hundreds of billions of dollars of revenue and so much cash just to go around. And it's always been this like academic lab and this sort of like environment where they do side projects. But they've just, they, I think before they started any of that, they had firmly established themselves as like the go-to search engine. And they were funding that with cash. So they were funding these initiatives with cash flow.
Starting point is 00:28:18 I believe so. And even though they've been doing it for this long, it's not like Sundar's going out there and saying, guys, we're actually going to do it. We're going to do an extra $100 billion next year because we're automating science and we're doing this new consumer electronic device. Yeah, no, no. It is crazy.
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Starting point is 00:28:46 And this comes from the chat, of course. If Sam Altman really wants to set the record straight, Everyone's saying Code Red, oh, Code Red, it's so bad. He needs to come out with a statement, we're going to Baja Blast Gemini out of the App Store. If he says our plan is to Baja Blast Gemini and Anthropic into the minor leagues of AI research, I think he just wins completely.
Starting point is 00:29:14 What do you think, too? I think people are underestimating the possibility that Code Red, it was actually red was past tense of read. Oh, okay. So they're talking about the code that was read by the model. Oh, yes, yes, yes. Oh, what was the code read in this scenario? It might have been RE80.
Starting point is 00:29:28 They were talking about the next agent model that was doing the code again. I have read the code and we're ready for the next pre-training run. I listened to Mark Chen on Ashley Vance's core memory podcast. It's very good. You should go listen. Also, Ashley has a new YouTube channel for Core Memory Podcasts. So if you want to find it, head over there. And it was interesting.
Starting point is 00:29:51 Mark Chen, I really like the way he runs that organization. I liked a lot of things he had to say. He had some funny, funny takes, some funny anecdotes, basically just saying, you know, he's extremely competitive, he doesn't want to lose, he's, he's, you know, going all out right now. And that one of the ways he's dealt with the talent wars is to just go to everyone on his team and say, hey, I'm not going to match dollar for dollar with meta. like if you want to make 10 times as much money, yeah, you're free to leave.
Starting point is 00:30:23 Like, you can just go. But we are on a mission here. We're a team. And we think what we're building is so big that in the long term, we will be better. We will be bigger. And he also clarified, interestingly, that although there was a big raid,
Starting point is 00:30:39 and a lot of people from open AI did go to meta, he was saying, like, there's been, he was basically like there's a lot of poaching that's happened from Open AI generally. Like whenever someone starts a new, They always go to Open AI. They're like, we need at least one Open AI guy to know how they do it, right?
Starting point is 00:30:53 It makes a lot of sense. He also said he didn't lose a single direct report. I don't know exactly how many direct reports he has, but he was saying that he didn't lose a single direct report. So maybe that's like, maybe he's trying to say, okay, there were people that were two lawyers down. Yeah, yeah, his, his lieutenant stuck around. It was sort of interesting.
Starting point is 00:31:10 But he did say that he also, he sort of echoed Shalto and said that he believes that pre-training, there's still low-hanging fruit there, that Open AI will be doing new pre-training runs, that they have seen, that scaling is holding, that there's no plateau. He also said they have models internally that outperform Gemini on benchmarks.
Starting point is 00:31:35 Yes. And obviously he capped you out of that by saying benchmarks aren't the only thing that matter. So I do think, I mean, it's worth sharing some more from... Let's actually play this clip from Ashley Vance here. says OpenAI has seen Gemini 3 and is both moved and not. We sat down with Open AI's research chief Mark Chen 90. Yeah, yeah.
Starting point is 00:31:58 So to speak to Gemini 3 specifically, you know, it's a pretty good model. And I think one thing we do is try to build consensus. You know, the benchmarks only tell you so much. And just looking purely at the benchmarks, you know, we actually felt quite confident. we have models internally that perform at the level of Gemini 3, and we're pretty confident that we will release them soon, and we can release successor models that are even better. But, yeah, again, kind of the benchmarks only tell you so much.
Starting point is 00:32:31 And I think everyone probes the models in their own way. There is this math problem I like to give the models. This is funny. I think so far none of them has quite cracked it, even thinking models. Can you just tell us? So, yeah, I'll wait for that. Is this, like, a secret math problem? Oh, no, no, no.
Starting point is 00:32:50 Well, if I'm not to hear, maybe it gets trained on. It's going to get so saturated. To speak to Gemini theory specifically, you know, it's a pretty good model. And I think... I think this is looping. One thing we... Yeah, I loop. Having a secret math problem that you give every model to assess it is pretty elite.
Starting point is 00:33:13 I keep reflecting on like, so let's read what Prins is saying here. So new interview with Mark Chen from Open AI. Ashley Vance, the interviewer, has apparently been spending a lot of time at Open AI, including sitting in on meetings. He seems to be writing a book. And he seems to think that Open AI has made some huge advance in pre-training. Pre-training seems like this area where it seems like you've figured something out. You're excited about it.
Starting point is 00:33:36 You think this is going to be a major advance. Mark doesn't spill the beans, though. He says, we think there's a lot of room in pre-training. A lot of people say scaling dead. is dead. We don't think so at all. Big question about what that means. Is that scaling RL? Is that scaling dollars in? Is it, oh yeah, if you invest
Starting point is 00:33:52 $100 trillion, you can give it one more IQ point. It's like, yeah, that would be an example of like scaling, holding, but like no one's going to make that trade off. No one, no one is going to be like, yeah, I'm down. Totally. Spend the $100 trillion. Okay, so what Sam said in the internal Slack memo. Oh, it was a Slack memo. Yeah.
Starting point is 00:34:13 Because he was directing more employees to focus on improving features of chat chbt, such as personalizing the chat bot for more than 800 million people. And again, we've seen them launch more functionality around this. I think the theory is that this could be a very, like, make the product really, really sticky. Whether or not that's true generally is still unclear. It's certainly people have been very loyal to 4-0. Altman also said this is in the information piece.
Starting point is 00:34:43 Did he mention Baja Blast? He hasn't specifically said Baja Blast, but I think he's kind of alluding to it. He's warming up to talking about Baja Blast. Other key priorities covered by the code red include image gen, the image generating AI that allows users to create variety of photos.
Starting point is 00:35:03 You had included in your newsletter last week that you've been going over to Gemini specifically for Nanobanana. Yes. So I wonder if this is a broader trend. Does this actually matter? I think it does. I think that the image generation functionality, like fundamentally what LLMs are doing,
Starting point is 00:35:26 what these chatbots are doing is they're basically instantiating full web pages. They should be able to instantiate anything that you could possibly land on, whether it's a video, an image, a blog post with images embedded, an audio format. It should be able to not just understand everything and give you the answer, but it should be able to contextualize that answer in any format. And so I do think being able to generate images at the top shelf, top tier way. The big question we were talking to Tyler was, should they say, hey, we're just going to use nanobanana. Which is like a crazy thing, but, you know, there is a world where they say like, hey, yeah, like, we're not going to focus on that.
Starting point is 00:36:04 We're actually going to just bend in nanobanana, but we are going to be the, the, the front door, the aggregator, and we're just going to be the the, the actual runway in the the background, right? Yeah, yeah, yeah, handed off to a different team potentially. I don't know. It seems like that's probably a little bit too close to home, but Ben Thompson has had this, this claim for a while that potentially Open AI has a strong hold on the consumer market to the point where if they swapped out the underlying model, they would still accrue
Starting point is 00:36:38 tons of the value because people don't really know what model is which. Like, I think the average user doesn't do it. But first, Tyler has a... Yeah, I mean, I think that especially makes sense in the context of images and video because they're just so expensive. Yeah. Like, um, I think a nano, banana pro image is like, I think it's like 10 cents. No way. It's really, or, okay, that might be per like a thousand or something, but it's still, it's still, they're really expensive. Yeah, yeah, yeah. Videos are even more expensive. Videos are like really, really expensive. Oh. So, I think it makes more sense in that scenario because, You would imagine that it's just so expensive to vend it yourself.
Starting point is 00:37:13 It's like you're spending so much resources on that. Yeah. We have to look at this. I believe this is nanobanana. Let me see if I can find this. This nanobanana pro image that, let me see if we can pull this up. It's from John Gregorchuk. It says, architects are cooked.
Starting point is 00:37:32 AI is coming for you. Prepare accordingly. Have you seen this, Jordi? I did see that. You did see this one? Yeah. Did you look at the image closely? No.
Starting point is 00:37:42 Okay. So is it, is it? It's one of the funniest images I've ever seen. So basically this image, it's like a, it has a walkway with like a 40 foot drop to the ground. I mean, it's not quite that bad, but it's close. Yeah, I just, I just, I didn't, I don't buy the, the, the theory that architects are cooked just because you can generate like a floor plan or, uh, or designs for a home, just because the actual process is you're dealing with a city, basically, right?
Starting point is 00:38:18 And you're trying to get things permitted. Yeah. It's not like the problem that's just making pretty designs, right? It's the classic, let me see, I'm trying to put this in the chat. It's the classic, like, you know, is the radiologist's job just to look at images and detect cancer? No, it's way more than that. Okay, so this is the image, and I was actually crying, laughing, because the tagline is,
Starting point is 00:38:46 architects are cooked, AI is coming for you, prepare accordingly. And you see this, and it's like this AI-generated image, and it looks like remarkable. It looks like a floor plan. It looks like a floor plan. It looks amazing. Like, it looks like, okay, yeah, that's like, all the lines are straight.
Starting point is 00:39:00 We used to be in the era of like any text would be typoed, and there would just be crazy lines everywhere. But you zoom in and it's like one of the funniest layouts ever because you realize that it's just, it's just one massive room with like three or four. Okay, so first off, okay, so you come in through the two car garage. Then there's a powder room. So, so first of, there's this mud room, lawn, mudroom and laundry with two bathtubs in it. Scroll up to the right. Okay, just go.
Starting point is 00:39:31 Yeah, right there. So why do you have two bathtubs next to your coat closet? In the mudroom. In the mud room. And also, like, you can't go. Normally, you come out of garage, you go straight to the mud room. But here, you have to go into the main area, which is the gallery hall. And then you go from there, into there.
Starting point is 00:39:47 And so scroll to the left a little bit so we can see the full. What is the coat? What is the coat bath? There's a powder room. And then there's the mask. With the coat bath and two toilets. And why are two toilets next to each other? Remember we were touring that facility and we had two, it had two bathrooms right
Starting point is 00:40:03 to each other with no line next to it? Yeah, yeah, yeah. We were in the in the office, in the crazy office that had the machine, one of the bathrooms just had, it was like, it was like meant to be a private bathroom. And it just had two toilets there. We were like, why the two toilets? Yeah, so it's like, so you come in through your main foray, then there's a master bathroom, then there's a coat bathroom with two more toilets. And then there's a huge walk-in closet, which isn't even directly attached to anything else. So you have to like go through this corridor to get to the rest.
Starting point is 00:40:39 And so this master suite has three toilets. But then it gets better, dude. So go over to the top right hand side. So look at bedroom number two. It's just like off the center. Then bedroom number three is there. Then there's a Jack and Jill bath. Then scroll down.
Starting point is 00:40:57 Wait, three sink? Three sinks, no toilets. And then there's another bedroom. And then there's a third. The third bathroom. This is... With you have five sinks. This is...
Starting point is 00:41:14 You might not like it, John, but this is... This is architecture at its best. You have five... You have five sinks next to your two bedrooms, which... And then also, bedroom two doesn't have a bed. Anything. It just connects it. It opens into the gourmet kitchen.
Starting point is 00:41:33 Gourmet kitchen. But then... If you scroll down, if you scroll down, you can see that there's like this huge walk guest suite. What is the huge walk guest suite? And then you have this like massive dining room that just makes no sense. And then down at the bottom to kick it off, there's, of course, like the great room that's directly tied into the kitchen with just the most open floor plan you can possibly imagine. And then if you scroll down, you'll see that there's like just these windows that like all of a sudden go to. Trevor in the chat says bathroom scaling loss.
Starting point is 00:42:03 Why are all of a sudden the doors like vertical instead of this is supposed to be a top down image and now I'm looking at these doors and they're like present. What did the comments say? Do the comments say like, hey, buddy, why did you put, you know, three sinks in that one bathroom? Well, everyone, everyone gets that it's a joke. Oh, it was meant to be, it was meant to be a joke. Yeah, yeah, yeah. Okay, yeah. Yeah, yeah. This John guy like totally thinks it's so funny and he's just like joking around.
Starting point is 00:42:32 And so everyone's just like nightmare fuel. Like this is crazy. And John's making the same jokes. It's super convenient off the open floor plan. No kitchen toilet? And then people just joking about all the different stuff. And I don't know. I mean, you know, is AI going to help with, you know, architectural design?
Starting point is 00:42:52 Of course. Is it is nanobanana going to randomly one shot like the perfect floor plan? No. Also no. But, you know, of course there's there's stuff that's, That's the funniest image. It's so funny. So funny.
Starting point is 00:43:07 Anyway, I was actually dying, laughing at this thing. Okay. Back to the Code Red. Vanta. Automate compliance and security. AI that powers everything from evidence collection and continuous monitoring to security reviews and vendor risk. D.D.D. Das is adding fuel to the fire.
Starting point is 00:43:26 He says, this is why OpenAI is in Code Red in the two weeks since the Gemini launched. JPT unique, daily active users, a seven-day average are down 6%. He is sharing, to be clear, web traffic data. Ah, these traffic sources are so rough. I just feel like people use apps. Like the web traffic is probably a good proxy. It's probably a decent proxy.
Starting point is 00:43:52 But even then, I just, I don't know how high intent those users are. Because it's like, do you think you're being tracked by similar web that effectively? Like, I would hope that I don't have that much spyware on my Chrome browser that knows exactly where I am. Maybe it does, but I would think that, you know, Open AI and Gemini and Google would be like, yeah, we're not, we're not letting you put a pixel on our site. Do you know, do, do we should have someone from similar web on the show, explain it to us. Tell us your sources. Yeah. Tell us everything.
Starting point is 00:44:26 How do you actually calculate all this stuff? Because, I mean, you could just poll people. you could just ask a million people. Hey, what are you using? Right? I don't think that's how this works. But the app store... I wonder if any of the Chrome extensions sell your data.
Starting point is 00:44:40 I'm sure a number of them. Yeah, yeah, I have this Chrome extension installed right now. TBPN timeline viewer. It was vibe-coded by someone sitting over there. He doesn't even know what programming language was written in. This is not true. Latelynus. Did I ever tell the story on the show?
Starting point is 00:45:01 I don't know. Tyler doesn't want to tell it. So Tyler gives us this, we use a Chrome plugin to, like, track the show when we're sharing posts between us. And this Chrome plugin, he, like, vibe coded it. And he sends it over, and I unpack it to install it. And I'm like, why are there, like, node modules here? Like, that's usually for, like, Node.js JavaScript on the back end. And he's just like, what are you talking about?
Starting point is 00:45:27 I was like, you don't know that you're using Node. It's a good extension, sir. Because I think it was just so... I trust Claude. I trust Claude to make the right decision. I don't even specify what programming language it uses, which is like pretty sick. It's actually extremely bullish for Claude and Cloud Code. It's really good.
Starting point is 00:45:45 Anyway, the part of the Code Red, of course, is that OpenAI's SORA app has fallen out of the top 20 most downloaded apps in the United States on both the App Store and Google Play. And so things are falling. I actually opened up SORA today. I looked at it, and there was some cool stuff happening. This is a little bit of a hot take. Like, it was not, there was still a lot of slop, which I would define as like, you know, it's a POV video of a bus driver with a bunch of cats on the bus, and it's like cute and funny. Or like, you know, it's a chipmunk, water skiing, like that type of stuff.
Starting point is 00:46:22 Is that why you were late for the gym today? No. But I was sneaking a peek at Sora while I was driving. And if I die and crash because I'm looking at slop, this would be extremely depressing. But... At a stop sign? Yeah. I was stopped.
Starting point is 00:46:38 But there was one cool one, which was more like pixel art, actually. And it was interesting because you remember the Open AI Super Bowl ad? Like, if you prompt SORA to make that type of content, it actually is really cool. And you can remix it in a very interesting way. And so, like, Sam had taken, somebody else had done, like, a bunch of geometric shapes pulsing to, like, electronic music. And then Sam was able to take it and say, make it orchestral music and make them pastel colors. And he was able to, like, remix off of that. And that felt like, okay, maybe we're getting into Suno territory.
Starting point is 00:47:18 Very odd that Suno and Sora are so close in names. I don't know how that happened. Maybe they should team up or something. Wouldn't be the first time OpenAI has named something. thing. Well, who, who, oh, yeah, I. Oh, yeah. I know. I don't know. But, uh, I don't know. I, I was, I was, I was seeing like, I, I don't think it's fully
Starting point is 00:47:36 over, you know, I think it's like, it's in a, uh, it might be in just a trough of disillusionment. You know, no. This could be, this could be a trough. The trough is in a trough of disillusionment. The trough is in the trough. It's entirely possible. But clearly, uh, the vibes are rough and people are, uh, taking shots, terminally online engineer says just put the ads in the chat little bro in the chat bot because sam olman says open ai is making it a very aggressive infrastructure bet with new partnerships but to be fair this clip was from a long time ago that was like at least a couple months ago yes yes yes and also uh you can
Starting point is 00:48:15 do both what is interesting is that it's it's it's maybe it sounds like they're delaying it sounds like they're delaying ads which is which feels odd because uh i personally was i'm maybe the only person It's really excited about ads in Chachachaputee. I think it's a good thing for the business. I think it makes a ton of sense. And I was excited to see where that rolls out. I hope that they don't delay it. I think that that's where they should be running.
Starting point is 00:48:37 But if they really are losing ground to Google and Gemini and like the Gemini app so quickly, I'm shocked because it feels like the Gemini 3 News, like the launch went well. People were excited about the model. The model card looked good. The benchmarks look good. But you still have to be pretty tuned in to understand.
Starting point is 00:48:56 understand the nuances of the model one way or another. Like, it's just not like the big model smell and the vibes. Like your average AI user doesn't care if the model responds with, it's not just this. It's that. Like most people, clearly, that's why it wound up getting RLed into the model. Most people are like, wow, contrastive parallelism. This is epic. I love it.
Starting point is 00:49:24 Thank you. Like, this is really contrast. parallelism. Yeah, antithetical parallelism. Like, I've never, this is like a big, big, big phrase, big word. Like, this is amazing. And so I'm, I'm shocked that there would be such a, I'm not, I'm not shocked by like a vibe shift in, on X and in teapot with regard to how people have been skeptical of the Open
Starting point is 00:49:47 AI financing. And so they've been looking for a crack to show. And Gemini coming out and, and leap, frogging a little bit, even if it's just on some obscure benchmark that the end user might not even care about. I was really interested in, I understand that, like, X would jump on that narrative, but I'm surprised to see, if it's true, this idea that, like, there's actually some sort of consumer shift. And, I mean, it seems like with the red alert comments, like, maybe, maybe it is, maybe it is. So you think they have to explain the funding gap at this point?
Starting point is 00:50:26 or can we all just agree that maybe everyone got a little too excited? Yeah, I don't know. I don't know. I feel like everyone's sort of repriced everything already with the Oracle round-tripping and just this idea that some of the equity investments, like they are circular, but it's basically just like a discount on their purchases. And, you know, these things probably aren't as binding as we think. And so I feel like the,
Starting point is 00:50:56 The Open AI is going to blow up the economy narrative. I feel like that was really oversold and is much... It should be fading, in my opinion, but I don't know. Bucco Capital bloke has been digging into the funding hole. Apparently, Chad GPT is also down right now. I just tested it. It's not down for me, but the chat says it's down. And X is saying it's down.
Starting point is 00:51:23 Oh, really? Oh, wow. time to Baja blast those surfers back online, brother. It's time to rock. We need a pump-up speech that doesn't include any negative phrases that can be taken out of context. We need to be Baja blasting. We have to Baja blast our way to the top of the app store. Sora team, I need you to Baja blast.
Starting point is 00:51:48 Bill, it's time to Baja blast to the top of the app store. You have to Baja blast at the top of the app store. You have to, and we're going to have to baha blast some funding into this company because apparently there's a $270 billion funding hole. Here, this is from a podcast between Ranjan, who writes at Reed Margins and Alex Cantorwitz at Big Technology. They did a podcast together. And here's the quote from Bucco Capital Bloch.
Starting point is 00:52:21 It says, squaring the total, it leaves Open AI in a lot. a $270 billion funding hole. The math doesn't work. Maybe Open AI should release to the world. Here's how the math can work, because I haven't seen anyone state how this can actually work. And so even if you get there, Open AI does fall $207 billion short of the money. It needs to continue funding its commitments, right?
Starting point is 00:52:41 So it has, in 2030, Open AI, free cash flow will be about $287 billion. That's, like, insane. That's, if, this is, this feature. feels like silly to me because if you're in a situation where you have $287 billion of free cash flow, like you can't raise more debt on that. Like I feel like math tends to work out when you go from a nonprofit to a $300 billion cash flow a year in 10 years. Like it's just, everything just forms in front of you.
Starting point is 00:53:19 Like yes, you are building the bridge as you're driving, but like that tends to happen when you're on that much of a tear. The bigger question is, like, can they actually free cash with $287 billion in 2030? So Amazon's free cash flow for 2024 was $38 billion. And let's see what Google's... Yeah, this is like a... 72.
Starting point is 00:53:43 So saying that they're going to do three times more than Google and Amazon... So this is the HSBC report is modeling $386 billion in annual enterprise AI revenue by 2030. Enterprise AI revenue. Huh. These are just huge numbers. It's almost not worth analyzing. I still think the biggest thing is just understanding how significant, how tied up are these contracts.
Starting point is 00:54:17 Well, let me tell you about fall, the genera of media platform for developers. develop and fine-tune models with serverless GPUs and on-demand clusters. So what else is going on? We should read through Ben Thompson's latest piece because he's provided a lot more context on Google, NVIDIA and Open AI with a post called Google, Nvidia, and Open AI. And we thank Ben Thompson for always having an even keel. Highly recommend subscribing to Strateree.
Starting point is 00:54:49 It's a fantastic publication if you're not subscribed already. And he's a former guest of the show. So let's read through his latest Monday piece. He says, A common explanation as to why Star Wars was such a hit and continues to resonate nearly half a century on from its release with everyone except Jordy Hayes, who hasn't seen it?
Starting point is 00:55:11 He hasn't seen any movies. I've seen Star Wars, John. How many Star Wars have you seen? I have to have seen all of them except some of the more, it's been some recent... All of them except some of them. Well, no, the more recent ones. Like, it hasn't there been, like, a new Star Wars in the last?
Starting point is 00:55:26 How many Star Wars are there, Trudy? Is there, there was, is there six? Six. There's six Star Wars. That's how many movies they've made? Six, like, real Star Wars. They're six. There's six.
Starting point is 00:55:39 Yeah, I'm gonna, I'm gonna, hasn't there been like, six? Everyone calls it, the septilogy. Yeah, there's six. Wait, there are six. There's nine. There's three trilogies. There's the original trilogy, the prequel trilogy, and then the sequel trilogy, and then there's also two spin-offs. Okay, so I didn't watch any of like the new ones.
Starting point is 00:56:00 But you watched the prequel trilogy. The rise of Skywalker. Do you're talking about George Lucas directed? Yeah. Okay, okay. So he's a Lucashead. Yeah, exactly. Okay.
Starting point is 00:56:09 So you've seen a new hope. I look at those as like real Star Wars. You've seen Return of the Jedi, and then you've seen Phantom Menace and Revenge of the Sith and Return of the Something. I can't actually. I actually don't know that much with the Star Wars. But anyway, you should know enough
Starting point is 00:56:25 to follow along with this analogy from Ben Thompson. He says, you have Luke, bored on Tatouine, called to adventure by a mysterious message born by R2D2,
Starting point is 00:56:35 that he initially refuses, refusing, refusal of the call. This is the classic, this is the classic hero's journey. So he refuses the call. A mentor in Obi-Wan Kenobi
Starting point is 00:56:48 leads him to the threshold. of leaving Tatouine and faces tests while finding new enemies and allies. He enters the cave, the Death Star, escapes after the ordeal of Obi-Wan's death. Spoiler alert, Ben, what are you doing, brother? What if somebody hasn't seen it? And they don't know that Obi-Wan dies. It's crazy. Oh.
Starting point is 00:57:07 And carries the battle station plans to the rebels while preparing for the road back to the Death Star. He trusts the force in his final test and returns transformed. And when you zoom out to the original trilogy, it's simply an expanded version of the story. This time, however, the ordeal is in the entire second movie, The Empire Strikes Back. The heroes of the AI story over the last three years have been two companies, Open AI and Invidia. The first startup is called, the first is a startup called with the release of Chachypti to be the next great consumer tech company. The other was best known as a gaming chip company characterized by boom and bus cycles, driven by their visionary. an endlessly optimistic founder
Starting point is 00:57:51 transformed into the most essential infrastructure provider for the AI revolution over the last few weeks. However, both have entered the cave. They're in the cave. There's the cave of disillusionment and are facing their greatest ordeal. The Google Empire is very much striking back.
Starting point is 00:58:10 And I believe, didn't Anjene over at A16Z coined that? The Empire Strikes Back? Formerly. 16 Z. He went independent. Oh, he's independent. Yeah.
Starting point is 00:58:21 Oh, I had no idea. So is this what Sam meant when he tweeted the picture of the Death Star? I feel like we never really figured out what he meant by that. That was before GBT5, I think. Yes. I think he wanted the 2025 vague post of the year award. It's so vague that even after the release, he still on no one. No, no.
Starting point is 00:58:39 I think this is it. I think this is it. It's Google's the empire, and he's launching the thing that will take a to Google directly. time because, like, Open AI was, like, clearly in the lead of the models. Like, 2.5, I think, I think 2.5 was the best gem around. Not in cash flow. You know, who has more soldiers, who has more researchers, who has more TPUs, right?
Starting point is 00:59:01 Like, you know, it would be fair to characterize, it'd be fair to characterize Google as the empire the whole time. Yeah. I mean, I guess the founding of Open AI, then Google is definitely the Death Star. Interesting. Isn't that their kind of? origin story of opening I? Yeah, yeah, yeah, it was.
Starting point is 00:59:21 They were worried about that. Anyway, I enjoy the Star Wars-based analogies. Almost as much as I enjoy Numeral.com. Compliance handled. Numeral worries about sales tax and VAT compliance, so you can focus on growth. So Google strikes back. The first Google blow was Gemini 3,
Starting point is 00:59:39 which scored better than OpenAI's state-of-the-art model on a host of benchmarks, even if actual real-world usage was a bit more uneven. Gemini 3's biggest advantage is its sheer size and the vast amount of compute that went into creating it. This is notable because OpenAI has had difficulty creating the next generation of models beyond the GPT4 level of size and complexity. What has carried the company is a genuine breakthrough in reasoning that produces better results in many cases, but at the cost of time and money.
Starting point is 01:00:11 Oh, time and money. Throw in a ramp.com ad right in the middle of the trajectory article. I love it. Gemini III's success seemed like good news for NVIDIA, who I listed, Ben, listed, as a winner from the release. Quote, this is maybe the most interesting one. InVidia who reports earnings later today is on one hand a loser because the best model in the world was not trained on their chips for proving once and for all that it is possible to be competitive without paying NVIDIA's premiums.
Starting point is 01:00:39 On the other hand, there are two reasons for Vydea's optimism. The first is that everyone needs to respond to Gemini, and they need to respond now. not at some future date when their chips are good enough. Did you know that Sundar was, like people were claiming that he had used the phrase code read and he back in 2022 at the chat GPT launch when Bard was popping? Yes, yes, yes. And so, yes. I'm remembering that now, but I missed it.
Starting point is 01:01:07 Sundar came out and said he didn't use that exact term, but there was reporting that he did. And I heard a rumor that he also said that he wanted to Baja blast Sam Altman out of the atmosphere with a Death Star laser. I want to try to find more historical examples of Baja blasting, folks. We got a Baja blast. You got a Baja blast sometimes. So Google started its work on TPUs a decade ago. everyone else is better off sticking with invidia, at least if they want to catch up. Secondly and repeatedly, Gemini reaffirms that the most important factor in catching up or
Starting point is 01:01:53 moving ahead is more compute. This analysis, however, missed one important point. What if Google sold its TPUs as an alternative to Nvidia? We're going to talk to Tay Kim, author of the Nvidia way about that. He's going to tell all. He's going to tell all. He's breaking his silence. So that's exactly what the search giant is doing. First, with a deal with Anthropic, then a rumor deal with meta, and third with the second wave of neoclouds, many of which started as crypto miners and are leveraging their access to power, to move into AI. So a lot of those neoclouds, they found a bunch of power, and they don't really have the right chips yet, or maybe they're upgrading their chips. They might be in a new cycle, and so TPU could be
Starting point is 01:02:33 at the top of the menu for them. Suddenly, it is Nvidia that is in the crosshairs with fresh questions about their long-term growth, particularly at their sky-high margins. If there were in fact, a legitimate competitor to their chips. This does, needless to say, raise the pressure on OpenAI's next pre-training, run on NVIDIA's Blackwell chips. The base model still matters, and Open AI needs a better one, and NVIDIA needs evidence that it can be created on their chips. What is interesting to consider is which company is more at risk from Google and why.
Starting point is 01:03:04 On one hand, NVIDIA is making tons of money, and if Blackwell is good, Vera Rubin promises to be even better. Moreover, while meta might be a natural. Google partner, the other hyperscalers are not. They're not going to be selling. We're going to have the CEO of Amazon Web Services, Matt Garman on the show
Starting point is 01:03:23 in just 30 years. And AWS announced a new chip today. And I don't think AWS is going to be buying TPU anytime soon, but we will be asking him that question exactly. And I want to get to the bottom of it. So, Open AI, meanwhile, is losing more money than ever and is spread thinner than ever, even
Starting point is 01:03:39 as the startup agrees to buy ever more compute with revenue that doesn't exist yet. That's a wild sentence. Not mincing words. And yet, despite all that and while still being quite bullish on Nvidia, I still like Open AI chances more. Whoa. Oh, Ben Thompson likes Open AI's chances. Indeed, if anything, my biggest concern is that I seem to like Open AI's chances better
Starting point is 01:04:05 than Open AI itself. Whoa. NVIDIA's moats. Wait, he wrote this before. He wrote this before the Red Alert. Interesting. He's really got a crystal ball over there. So, Nvidia's moats.
Starting point is 01:04:18 If you go back a year or two, you might make the case that Nvidia had three moats relative to TPUs. Senior superior performance, significant more flexibility due to GPUs being more general purpose than TPUs, and Kuda and the associated developer ecosystem surrounding it. Open AI, meanwhile, had the best model extensive usage of their API and the massive number of consumers using chat GPT. The questions then is what has...
Starting point is 01:04:40 happens if the first differentiator for each company goes away. That, in a nutshell, is the question that's been raised over the last two weeks. Does Nvidia preserve its advantages if TPUs are as good as GPUs and is OpenAI viable in the long run if they don't have the unquestioned best model? So, Nvidia's flexibility advantage is a real thing. It's not an accident that the fungibility of GPUs across workloads was focused on as a justification for increased capital expenditures by both Microsoft and meta. TPUs are more specialized at the hardware level and more difficult to program for at the software level.
Starting point is 01:05:15 To that end, to the extent that customers care about flexibility, then Nvidia remains an obvious choice. The interesting thing about the flexibility is that isn't SSI a big TPU buyer? I feel like SSI was maybe going big on TPU. And I think of SSI is very much like, we're going to experiment. we need maximum flexibility. By default, I would assume that they're a heavy consumer of GPU
Starting point is 01:05:43 because they want as much flexibility as possible. But maybe the nature of Ilya's research is flexibility within, that is still afforded within the TPU ecosystem. They're using TPUs through Google Cloud. Yeah. But there's been no... Oh, yeah, they're not buying them. But still, it just means...
Starting point is 01:06:00 That implies more flexibility because you can just turn it on or off. Yeah, I'm talking about the actual, like, the TPUs is an ASIC. it has, it has like literally like less features than the GPU, like a gaming GPU and like the TPU doesn't, I think it doesn't support like FP4, right, or something like that. There's some, there's some type of math that is harder to do on a TPU because it's making tradeoffs, right? And and so even though I don't understand it fully, I understand that, that, you know, TPUs are more specialized at the hardware level. And so if you were to be in like the era, the era of research, maybe you would want something that's less specialized because you'd be like,
Starting point is 01:06:39 I'm going back to exploring all sorts of different types of math that are necessarily optimized. Yeah, but again, if you're buying TPUs through the cloud, you're effectively just buying cloud services. Yeah. You do have more flexibility because you can say, hey, we want to use more of this or we want to use less. You're not like buying a bunch of servers and chips.
Starting point is 01:06:56 Yeah, yeah, yeah, yeah. On the scale thing, that makes perfect sense. Yeah, I think also, like, historically, TPUs have definitely been more restrictive just because of, like, the software was just not as good. or it was closed source or whatever. And then yesterday, Don't Patel was talking about how Google is slowly trying to open source more and more stuff from the TPU.
Starting point is 01:07:14 So you would imagine that in the future, it should be much easier to use TPUs generally. Sean in the chat says, flexibility in terms of, hey, I have this new architecture, do I need to write kernel code from scratch or is there a nice Kuda module I can use just time, right? Flexibility is engineering work from NVIDIA. Yeah, yeah, no, that's a really good point.
Starting point is 01:07:33 So Kuda, meanwhile, has been a critical source of Nvidia lock-in, both because of the low-level access it gives developers, but also because there is a developer network effect. Dylan Patel was talking about this. You're just more likely to be able to hire low-level engineers if your stack is on Nvidia. The challenge for Nvidia, however, is that the big company effect could play out with Kuda in the opposite way to the flexibility argument. While big companies like the hyperscalers have the diversity of workloads to benefit from the flexibility of GPUs, they also have the wherewithal to build an alternative software stack. that they did not do so for such a long time is a function of it's simply not being worth the time and trouble
Starting point is 01:08:14 when capital expenditure plans reach the hundreds of billions of dollars. However, what is worth the time and trouble changes. A useful analogy here is the rise of AMD in the data center. That rise has not occurred in on-premises installations or the government, which is still dominated by Intel. Rather, large hyperscalers found it worth their time and effort to rewrite a extremely low-level software to be truly agnostic between AMD and Intel, allowing the former's lead in performance to win the battle. And so AMD, better performance, better efficiency per dollar, but didn't have the best software.
Starting point is 01:08:53 And now, but now because there's so much on the line, so many, the spending amount is so high, companies will go and work around all the bugs, develop new software that allows them to take advantage of AMD's better performance. In this case, the challenge Nvidia faces is that its market is a relatively small number of highly concentrated customers with the resources, mostly as yet unutilized to break down the Kuda Wall as they
Starting point is 01:09:19 already did in terms of Intel's differentiation. It's clear that Nvidia has been concerned about this for a long time. This is from Nvidia waves and moats, which he written at the absolute top of the Nvidia hype cycle after the 2024 introduction of Blackwell. This article takes this article full circle. This takes this article full circle. This is from the previous Ben Thompson article in Stratory. It says in the before times, i.e. before the release of chat GBT, NVIDIA was building quite the free software moat around its GPUs. The challenge is that it wasn't entirely clear who was going to use all of that software. Today, meanwhile, the use
Starting point is 01:09:57 cases for those GPUs is very clear and those use cases are happening at much higher level, at a much higher level than Kuda frameworks, i.e. on top of models. That, combined with the massive incentives towards finding cheaper alternatives to NVIDIA, means both the pressure to and the possibility of escaping Kuda is higher than it ever has been, even if it is still distant for low-level work, particularly when it comes to training. Invidia has already started responding. I think that one way to understand DGX cloud is that is NVIDIA's attempt to capture the same market that is still buying Intel server chips in a world where AMD chips are better because they have already standardized on them. NIMs are another attempt to build lock-in.
Starting point is 01:10:41 In the meantime, though, it remains noteworthy that NVIDIA appears not to be taking as much margin with Blackwell as many have expected. The question as to whether they will have to give back more in future generations will depend on not just their chip's performance, but also on redigging a software mode increasingly threatened by the very wave that made GTC such a spectacle. So Blackwell margins are doing just fine, I should note, he's back to the original article, the modern article, as they should in a world where everyone is starved for compute. Indeed, that may make this entire debate somewhat pointless. Implicit in the assumption that GPUs might take share from GPUs might take share from GPUs, is that for one to win, the other must lose, the re-react-exempts.
Starting point is 01:11:25 decision maker maybe TSM, which makes both chips and is positioned to be the real break on the AI bubble. Interesting. So chat ChitpT and Motes resiliency. I can read through this one. Chat ChitpT, in contrast to NVIDIA, sells into two much larger markets. The first is developers using their API and according to Open AI. Anyways, this market is much stickier and reticent to change, which makes sense. Developers using a particular model's API are seeking to make a good product. And while everyone talks about the importance of avoiding lock-in, most companies are going to see more gains from building on. Never avoid locking. Always locking. From what they already always Baja blast. And for a lot of companies that is opening eye, one, I would caveat here, we were
Starting point is 01:12:09 talking to a founder yesterday who, um, off the show, who was saying he, um, immediately, uh, as soon as as Gemini three launched, spent like 12 hours, uh, 12 hours, like, uh, just moving, moving, over to Gemini from opening eyes. So depending on the product, I don't know that API is always going to be super sticky. I say winning business one app by one by one will be a lot harder for Google than simply making a spreadsheet presentation
Starting point is 01:12:41 to the top of a company about upfront costs and total cost of ownership. Still API costs will matter. And here Google almost certainly has a structural advantage. The biggest market of all, however, is consumer. Google's bread and butter. What makes Google so dominant in search, impervious to both competition and regulation is that billions of consumers choose to use Google
Starting point is 01:12:58 every day, multiple times a day, in fact. Yes, Google helps this process along with its payments to its friends, but that's downstream from its control of demand, not the driver. What is paradoxical to many about this reality is that the seeming fragility of Google's position, competition really is a click away. It is, in fact, its source of strength. And then there's an excerpt from the United States. We can skip this one and continue at the bottom. The CEO of a hyperscaler can issue a decreesure to work around Kuda. An app developer can decide that Google's cost structure is worth the pain
Starting point is 01:13:29 of changing the model undergirding their app. Changing the habits of 800 million people who use Chachapit every week, however, is a battle that can only be fought by individual by individual. This is Chachapit's true difference from NVIDIA in their fight against Google. And so this, I think, is the most important takeaway
Starting point is 01:13:50 is just Ben Thompson creates aggregation theory, this idea of like, it's so important to aggregate demand in the modern internet world. It's potentially the only thing you can do, you can't really monopolize supply.
Starting point is 01:14:06 It's very hard to monopolize supply, but monopolizing demand is something that happens. And the strength of habits is significant. Like we're watching this stuff every single day so we can take the time to, okay, yeah, we should test out this other, you know, model. We should daily drive this app.
Starting point is 01:14:26 But for a lot of people, if they have a map that's installed and they've been using it for a year, they're never changing. Even if the model's slightly better over there. They're just not even going to hear about it because they're just like, this is the thing that I use to plan my vacations. And the thing that I've heard come up multiple times is people that when Gemini 3 launched, they switched to Gemini 3 on desktop, but they stayed using chat GPT on mobile. Yep.
Starting point is 01:14:47 And, I mean, to be completely transparent, like the Gemini mobile app is really, really struggling to stay connected. There's something in the, when you fire off a prompt, it doesn't like save it locally and then cache that and then send it off, inference it and then come back. Like, unless you keep the app open, like it will, it will just give you like a server disconnected error. Like, I've gotten like dozens of these. and that's going to be a real, I think it should be something they should be, they should be able to fix
Starting point is 01:15:20 in like a weekend. But, you know, hopefully it's soon. But for a lot of people. Logan. Yeah. Well, they'll get it. I'll get it. But back to the moat and the map,
Starting point is 01:15:32 the moat map and advertising. This is, I think, a broader point. The naive approach to moats focuses on the cost of switching. In fact, however, the more important correlation to the strength of a moat is the number of unique purchasers to users. The strength of the moat is increased by the number of buyers.
Starting point is 01:15:55 Okay. So you can see where this is going with like, Nvidia has five buyers. Yeah. And ChattGBT has a billion buyers. And once it has advertised. Or 20 million. How many?
Starting point is 01:16:06 Yeah, advertisers might be even more, right? Yeah. So this is certainly one of the simpler charts I've ever made because it's literally just one line. But it's not the first in the moat genre. So he talks about the moat map. I argue that you could map large tech companies across two spectrums. The degree of supplier differentiation from Facebook where the suppliers completely commoditized, just your friend on Facebook, to Microsoft and Apple where the suppliers are somewhat more controlled. Yeah, there's the... What a chart. The more unique buyers of your product you have, the stronger your moat, because it's
Starting point is 01:16:42 hard to convince each one of them. And then second, the extent to which a company's network effects were externalized, internalized network effects are Facebook again, and then externalizes Microsoft. And so putting this together gave the moat map. So who has the network effect versus the suppliers map? If we scroll down there, you can see them. What you see in the upper right are platforms, the lower left are aggregators. Platforms like the App Store enable differentiated suppliers, which allows them to
Starting point is 01:17:12 profitably take a cut of purchase, purchases driven by those differentiated suppliers. Aggregators, meanwhile, have totally commoditized their suppliers, but have done so in the service of maximizing attention, which they can monetize through advertising. It's the bottom left that I'm describing with the simplistic graph above. The way to commoditize suppliers and internalized network effects is by having a huge number of unique users and by extension, the best way to monetize that user base and to achieve a massive user base in the first place is through advertising. It's so obvious the bottom left is where Chachibit sits. I wonder what he thinks then about them potentially kind of delaying ads?
Starting point is 01:17:48 Probably punching the air. Him and Eric Suford would probably, oh, no. And I'm right there with them. I completely agree. Boom. Launch the ads product. Launch the ads product. Get it out.
Starting point is 01:18:04 Come on. Don't delay that. That's the most important thing. So at one point, it didn't seem possible to commoditize content more than Google or Facebook did, but that's exactly what LLMs do. The answers are a statistical synthesis of all the knowledge the model makers can get their hands on and are completely unique to every individual. At the same time, every individual's user usage should, at least in theory, make the model
Starting point is 01:18:32 better over time. It follows then that Chachapitis should obviously have an advertising model. This isn't just a function of needing to make money. Advertising would make chat GPT a better product. It would have more users using it more, providing more feedback, capturing purchase signals, not from affiliate links, but from personalized ads, would create a richer understanding of individual users, enabling better responses. And as an added bonus, and one that is very pertinent to this article, it would dramatically
Starting point is 01:18:57 deepen Open AI's moat. Yeah, I keep going back to this idea that OpenAI needs personalized ads, like Instagram. Like that's what Sam said when he was interviewed multiple times on his ad strategy. He was like, you know, like ads could be bad, but these Instagram ads are pretty good,
Starting point is 01:19:15 you know? He's, and people are always like, he's backtracking. It's like, no, that's fine. Get,
Starting point is 01:19:21 like, do the proper business model. Like, please implement the correct business model. I'm happy about that. But the interesting thing is that Instagram does not service ads when you, necessarily when you search for something. Like, if you're on a video for, like, a Ferrari, like, you don't just immediately get an ad as your next thing for, like, Ferrari of Hollywood.
Starting point is 01:19:46 Like, or Ferrari of Beverly Hills. Like, no, you get an ad for the toaster that you were about to check out on. I actually do. Like, half, half the ads I get on meta are local dealerships in L.A. Yes, but importantly, not when you're, like, search. It's not tied to search. And so chat chattiepD can do the same thing where they can clearly show you,
Starting point is 01:20:11 where they can clearly show you something that you are about to check out, you're shopping for Christmas for this thing, you're searching for the Roman Empire, let's show you the ad for the thing that you're shopping for right next to it. It's fine. And so I think that can work very well.
Starting point is 01:20:26 Anyway, let's go to Google's advantages. It's not only question that Google can win the fight for consumer attention. The company has a clear lead in image and video generation, which is one of the reasons why I wrote about the YouTube tip of the Google Spear. I mean, Google's advantage in data is insane. Like, YouTube.
Starting point is 01:20:42 So massive, and that's got to be just compounding compound. I mean, we're uploading another three hours of video to YouTube today. You're welcome. This one's for you, son. This one's for you, Dennis. But the flip side is like they also see the entire internet because of the way the Google bot scrapes. Like, the Google searching in Gemini is such a killer feature. It's such a killer feature if they can keep that on and they can actually surface that.
Starting point is 01:21:08 And the AI search results are obviously going to get good. They're going to figure out how to surface it. I think I'm still pretty optimistic. But let's see what Ben Thompson has to say. And let's also tell you about Adio, the AI Native CRM. Adio builds scales and grows your company to the next level. So Google is obviously capable of monetizing users. Even if they hadn't turned on ads in Gemini yet, it's also pointing out as Eric Sufer did in a recent Stratory interview,
Starting point is 01:21:32 two of the best, collabing. We'd love to see it. That Google started monetizing search less than two years after its public launch. It is search revenue, far more than venture capital money, that has undergirded all of Google's innovation over the years,
Starting point is 01:21:45 and it is what makes them such a behemoth today. In that light, OpenAI's refusal to launch and iterate on an ads product for ChatGPT, now three years old, is a dereliction of business duty. He's calling him out. Whoa. Particularly as the company signs deals
Starting point is 01:21:59 for over a trillion dollars of compute. What are you doing? Sam, get the ads out. Put the ads in the chat bot. We love it. Just put the ads in the chat bot. You got to Baja blast some ads into that app. You got to.
Starting point is 01:22:12 I want ads in Chad GPT, please. On the flip side, it means Google has the resources to take on chat GPT's consumer lead with a World War I style war of attrition. Ryan Mattal callback. Open AI's lead should be unassailable, but the company's insistence on monetizing solely via subscriptions with a downgraded, degraded user experience for most users and price elasticity challenges in terms of revenue maximization is very much opening the door to a company that
Starting point is 01:22:41 actually cares about making money. To put it another way, the long-term threat to NVIDIA from TPU's margin, from TPUs is margin dilution. The challenge of physical products is that you do actually have to charge people who buy them, which invites potentially unfavorable I always, so, yeah, who both Gemini and ChatGPT will have ads eventually, right? Yes. You can bet on that. Who will ramp ad revenue faster? It's hard not to bet on Gemini, even with a smaller user base, because they have the ad network. They have all the, they have all the customer relationships already.
Starting point is 01:23:18 They can just say, like, hey, here's a pop-up. Do you want it? Yes. Here's $10,000 of free ad credits. Try it out, right? native, it will already be in AdWords. The example that I use is like how, you know, Zuck was able to take Instagram, which had a lot of users,
Starting point is 01:23:33 plug it into the meta ads platform and just scale revenue like crazy. And then do it again with reels. And so, yeah, very, very clear that they both will have ads. And again, if Gemini can really ramp that quickly, they could, again, like I do feel like we're moving towards a world where every consumer will be able to get the best LLM for free, right? I don't necessarily believe that every American will be paying for an LLM in five years. And so if Google can get there first and then keep Gemini on the frontier and deliver the best,
Starting point is 01:24:16 free, fastest text and image model, that's going to be very, very difficult to compete with. And so again, like getting, getting to ads faster, it feels like it makes more sense. I like that point. I have a rebuttal. First, I'm going to tell you about Figma. Think bigger, build faster. Figma helps design and development teams build great products together. So getting to ads first is an advantage.
Starting point is 01:24:41 That's your take. I like it. But there is a little bit of a risk with launching ads first because you could forever be branded with. You're the ads one. And we saw this when Arvin from Perplexity came on the show, and he mentioned this idea of ads in LLM queries. And we all agreed on the discussion. We all agreed that ads were going to come to AI tools because that is the way to get the most people using them and make intelligence free. And you got in a debate with Mark Cuban over this, for example.
Starting point is 01:25:18 And it seemed very logical. But there is the fact that the first major chat app to put ads in their app is going to be a massive news cycle. It's just going to be like national news. Sam Adman. Exactly. It'll be OpenAI has ads now or it'll be Gemini has ads now. And so you don't necessarily, like it's much easier to be the second mover there because it's going to be less of a news cycle. And so you kind of do want to, there is a little bit.
Starting point is 01:25:51 bit of advantage to being the second mover there, right? Because you're, you're going to get sort of branded as like, oh, that's the ad supported one. And the other one can add ads. And people will be like, oh, yeah, like, I guess, but that's like standard. Yeah, there's going to be like a backlash. And people will be like, oh, no, I don't like this company, blah, blah, blah, blah. Like, the harder, the harder thing is just how do you do it, right? Certainly, like, I do feel like it's different. You're going to an LLM. People are going to an LLM for advice and recommendations that's different than going to Google and searching and seeing ads at the top.
Starting point is 01:26:23 I mean, there's plenty of surface area. No, no, I'm not saying there's no surface area, but I'm just saying like the right way to do ads in LLM is not clear yet. Yeah, yeah, I mean, we'll need to do some experimentation. But, I mean, just starting with, you know, like Google already has retargeting information. I actually went to Gemini with a question
Starting point is 01:26:44 and it clearly knew everything about me. And it said, you're the host of TVPN? and you've founded these companies. And it already knew that, probably just because I authenticated with something else. I don't know. But it should know, okay,
Starting point is 01:26:57 hey, we could retarget you with this. Let's put this in. And the same thing with Open AI. Like with ChatGPD, there's plenty of spaces where it's like you're waiting for it to give you the answer. Okay, hey, we're generating you the image. Why don't you show me other images of ads right there?
Starting point is 01:27:14 There's tons of surface area. I agree that there will be a whole bunch of iterations on like what the ideal ad looks like. But yeah, you can clearly get out. So let's go back to Ben Thompson, close this out. It says the reason to be more optimistic about Open AI is that an advertising model flips this on its head because users don't pay.
Starting point is 01:27:34 There is no ceiling on how much you can make from them, which by extension means that the bigger you get, the better your margins have the potential to be and thus the total size of your investments. Again, however, the problem is that the advertising model doesn't exist yet. So he started this article recounting the hero's journey in part to make the easy leap to the empire strikes back. However, there is a personal angle as well.
Starting point is 01:27:56 The hero of this site has been aggregation theory and the belief that controlling demand trumps everything else. There's their Google was my ultimate protagonist. Moreover, I do believe in the innovation and velocity that comes from a founder-led company like Nvidia. And I do still worry about Google's bureaucracy and disruption potential making the company less nimble. and aggressive than Open AI, more than anything, though I believe in the market power and defensibility of 800 million users, which is why I think ChatGPT still has a meaningful moat. At the same time, I understand why the market is freaking out about Google. Their structural advantage, their structural advantages in everything from monetization to data
Starting point is 01:28:37 to infrastructure, to R&D is so substantial that you understand why Open AI's founding was motivated by the fear of Google winning AI. easy to imagine an outcome where Google's inputs simply matter more than anything else, which is to say one of my most important theories is being put to the ultimate test, which perhaps is why I'm so frustrated at Open AI's avoidance of advertising. Google is now my antagonist. Google has already done this once. Search was the ultimate example of a company winning an open market with nothing more than a better product.
Starting point is 01:29:10 Aggregators win new markets by being better. The open question now is whether one that has already reached, Gail can be dethroned by the overwhelming application of resources, especially when its inherent advantages are diminished by refusing to adopt an aggregator's optimal business model. I'm nervous and excited to see how far aggregation theory really goes. Fascinating. That's his baby. Yeah.
Starting point is 01:29:33 It's a, it is, I agree. It is the correct, it is the correct framing. It'll just be very interesting to see. I really wonder, who's going to, who's going to take the leap first? who is going to jump and put ads in the app first. It feels like Google should do it. It feels like Google will be able to do it. Yeah, nobody's going to be like,
Starting point is 01:29:59 what? Google is putting ads in a product? Yeah. It won't be that surprising. So they should probably move faster. We have some breaking news. What's the breaking news? Jason Freed is joining the show at 2 p.m.
Starting point is 01:30:10 I can't wait. Surprise guest. He's launching Fizzy today. Yes. Canban, as it should be, not as it is. has been. I will wait, we'll wait to talk about this
Starting point is 01:30:21 until he joins in an hour and 20 minutes. So a little surprise guest appearance from a legend. He's calling out his competitors directly. I love when the founders do that. Founder mode. Founder mode. Should we talk about John G. Andrea
Starting point is 01:30:37 leaving the company? He's out. He's out. I quit. I quit. You like that one. I think that's probably been used before. Some headline, but.
Starting point is 01:30:46 Amar Subram. So, of course, Mark German has the scoop, I believe. The Germanator. Germanators added again. He says Apple AI chief, John G. Andrea, is leaving the company. Amar Subramanya from Microsoft is joined a lead AI under Craig Federigi. And so we should dig in a little bit to this history. So Swix has a little bit of a deep dive here.
Starting point is 01:31:17 He says, Amman brings a wealth of experience to Apple. He's quoting here. Having most recently served as CVP of AI and Microsoft and previously spent 16 years at Google where he was head of engineering for Google Gemini. Wait, oh, I guess at the end of that because Gemini is not 16 years old. This is bearing the lead.
Starting point is 01:31:36 He joined Microsoft AI four months ago. Wow, what a crazy turn of that. LinkedIn says six months ago, but who's counting? That's pretty fast. But this makes sense, considering Apple is partnering with Gemini, and not a lot of people are going to be in a better position to help integrate that into Syria than Amar.
Starting point is 01:31:56 Yeah, I mean, I don't know. Maybe there's something to just having a taste of all the different big tech companies. Oh, yeah, I've been at Microsoft. I know how they work. I've been at Google. I know how that works. I'm ready to rock over here. German does need to come back on ASAP.
Starting point is 01:32:14 I agree, Ragov. He was fantastic. We'll get him in person. Hopefully before the end of the year. So, German continues. He says, Strange hire for a number of reasons, but it's hard to argue that the Apple job is a bad one.
Starting point is 01:32:25 Anything is an important improvement at this point. So the bar is as low as it comes. Easy to lay up on the resume. So that'll be fun to see. I'm personally just excited to actually test drive, what Gemini, how it works in Siri, how seamless that is.
Starting point is 01:32:41 Because if it really is just raise, press the button, get Gemini, and it's linked up properly and it doesn't have timeouts and it gets back to you pretty quickly, like that's going to be a pretty powerful experience. That's definitely going to cut down on chat GPT app usage for iPhone users, I would imagine. Underrated threat. I would think so. Like the, there are so many moments where people are counting out Apple. It's not, yeah, I don't even know that, I don't even know that Apple will benefit massively from this. It's not like they're going to sell twice as many iPhones. They're already so big.
Starting point is 01:33:20 It's not like they're going to charge for it. I don't think it's necessarily, like, especially bullish for Apple. Yeah. It's an underrated threat for Open AI. I would think so. There's a lot of queries that all hit Open chat, GBT on mobile that are not even like super economic, but just a lot of my usage around. Yeah. Like, hey, just trying to learn about something.
Starting point is 01:33:39 or research or product, et cetera. Yeah. And if that's just like, again, one tap and you're in there. Yeah. I mean, yeah, the original promise of Siri was, you know, not just, hey, what's the weather today? But really asking anything. And Gemini clearly solves that for 99% of knowledge retrieval queries.
Starting point is 01:34:00 I would be, I think I'm going to be using that a lot unless they really botch it. And I don't know how they're going to botch it. But, yeah, what do you mean? Yeah, I mean, I think the, Anything's possible, yeah. Apple's like, hold my beer. They can be like, for privacy reasons, every time you press the button, you have to e-sign. And it's like, why are we doing that?
Starting point is 01:34:19 Yeah. Like, the original, like, Siri kind of vision was like this very conversational AI, right? Yeah, yeah. But I don't think Gemini has a real-time voice model yet. Like, I'm pretty sure Open AI is the only one that has that. Really? Huh. I don't think that matters at all.
Starting point is 01:34:34 Really? Yeah, I really think that... Because that form factor feels like that would be the best thing to be. You press the button on your iPhone. And then it's just on. And then it's just on. Yeah. Yeah.
Starting point is 01:34:43 I mean, I wouldn't be surprised if they can, if they can, like, get that model, that version of the model out. Because it's really just, like, distilled a little bit faster. It's not some, like, uncanny breakthrough that the Gemini team will not never be able to crack, right? So they just have to build that. But honestly, like, I don't know that that's certainly not how I would use it for most things. Most things I would say, okay, like, I have one question, get me an answer within a
Starting point is 01:35:12 reasonable amount of time and maybe read it off to me or produce like an article that's, you know, a pretty readable article summarizing the answer to my question. And then, yeah, maybe there is like a back and forth, but I don't know. Oh, you're getting, you're getting truth zoned in the chat. Gemini does have a real-time voice feature. Gemini Live. Yeah, I think it's on the app. I've used to try that. I don't have the map. So. Yeah.
Starting point is 01:35:37 Journalistic force Head of door to you. Stand by. Tyler. Anthropic is acquiring Bun. What do you have to say? Yeah.
Starting point is 01:35:47 I mean, this is definitely in line with their like, you know, focus on dev stuff. Okay. What is Bun? Bun is a, it's like a,
Starting point is 01:35:59 I don't know, it's like a bundler for JavaScript. It's like a very dev. It has dramatically improved the JavaScript and TypeScript developer experience, they're going to make Claude code even better.
Starting point is 01:36:09 I like the Gabriel from OpenAI here is OMG in the chat, which is like a pretty crazy thing to say. But I appreciate it. So Claude is one of the world's smartest and most capable AI models for developers. Startups and Enterprise's Cloud Code represents a new era of agentic coding, fundamentally changing how teams build software.
Starting point is 01:36:31 In November, Claude Code achieved a significant milestone. just six months after becoming available to the public. That's crazy. It's only been six months. Wow. It reached a $1 billion revenue run rate. We were always struggling to understand what that meant, right? Yeah, well, so there are two ways to pay for a cloud code.
Starting point is 01:36:48 There's either with your cloud subscription where you get like Cloud Pro or Cloud Max, and there's a certain amount of tokens you can use. Then there's also, you can just directly wire up APIs calls essentially to Cloud Code. And then you're being charged directly based on usage. So that's probably what that revenue is from. Yeah. And then, yeah, I also have thought about this thing where like, oh, you can break down the number of tokens from the subscription. So it's like your $20 subscription, three-fourths of your tokens are on Claude Code.
Starting point is 01:37:16 I mean, three-fourths of your $20 is counts as Claude Code revenue. Okay. Yeah, yeah, that makes sense. I'm not sure that they can account for it. So it was founded by Jared Sumner in 2021. Bunn is dramatically faster than leading competition. I say it's a breakthrough JavaScript runtime. Does it compete with V8?
Starting point is 01:37:33 I'm very interested in like it's Node.js. It competes with Node. The thing that Tyler needs to learn. What was that company that Open AI acquired earlier this year for like a billion? I know the one you're talking about. It's not analytics or something. Yeah, but again, I remember at the time people were like, oh, like, Open AI's competitors are not going to be happy about this acquisition.
Starting point is 01:37:58 and so that comment from Gabriel. Well, congratulations to the Bun team. Congratulations to Anthropic and everyone on the Claude Code team. Very excited that you're getting to work together for your massive deal. Speaking of other massive deals, Alfred Lynn. Alfred Lynn. Hit the, get that gong ready, John. What did he do?
Starting point is 01:38:20 Alfred Lynn comes in on the board of DoorDash buys $100 million. of DoorDash. Colin in Linton sanity. He's not done stewarding. DoorDash. He's continuing to steward the company with a $100 million buy. And, of course, sends the stock up almost 6% on that. Pretty remarkable.
Starting point is 01:38:45 Are excited about it. You ripped. He ripped. What is this another $4.6 million to donate it to shrimp welfare? Okay. So they, yeah. Basically, the story is anthropic, they were doing some, like, research
Starting point is 01:39:03 and about smart contracts. And so they had Claude Code try to figure out, like, you know, issues in smart contracts. And then I'm not sure exactly where the, like, money came from. Maybe it was for, like, bounties. But there was some way in which CloudCode
Starting point is 01:39:20 basically generated, like, $4.6 million in, like, cash from, finding these exploits. So then they just... Did it actually generate real money? Or is this like the hypothetical? This is simulated testing. Okay.
Starting point is 01:39:35 Huh. Simulating. So yeah. So it probably means that they could have like basically stolen $4 million dollars from people, but they don't want to do that. Maybe they should have if they really want to get up the... In other anthropic news,
Starting point is 01:39:48 David Sachs says he's still waiting on Dario's support after the New York Times piece was published. Sam Altman, of course, came in and said, David Sacks really understands AI and cares about the U.S. leading in innovation. I'm grateful we have him. Of course, Dario and Sacks, not the biggest fans of each other. So I don't expect that one coming through anytime soon. While we wait for our first guest, Matt Garman,
Starting point is 01:40:19 let's pull up this clip from Huberman Lab, if we can play this. Rob Moore is highlighting Dr. Jeffrey tells Huberman that LED lighting in buildings is a public health crisis that could be on par with the use of asbestos. Many building contractors
Starting point is 01:40:37 slash designers are coming to him worried they're going to be sued in asking how to start fixing the issues. So let's pull this up when we have a second. Because I am very concerned about the amount of short wavelength light that people are exposed to nowadays, especially kids. The group of us
Starting point is 01:40:53 are shuffling around, some of them are saying this is an issue on the same level as asbestos. This is a public health issue and it's big. LEDs came in and people won the Nobel Prize for this very rightly at the time because they save a lot of energy. The LED has got a big blue spike in it, although we tend not to see that. And that is even true of warm LEDs and there is no red. The light found in LEDs, when we use them, certainly would be using them on the retinney looking at mice, we can watch the mitochondria gently go downhill. They're far less responsive. They, their membrane potentials are coming down.
Starting point is 01:41:37 The mitochondria are not breathing very well. Can watch that in real time. Under LED lighting. And LED lighting at the same energy levels that we would find in a domestic or a commercial environment. This is why I want to read. rig the studio with incandescent light. Incandescent. We're going back to candles. Candlelight. Let's do candlelight. How about a hearth? If we put a hearth, so we have lights above our heads, I'm sure, or LEDs, killing us slowly and softly. If we put a somewhat a bonfire
Starting point is 01:42:09 right above us. That'd be the way. And then we just, when the wood kind of burns out, the show's over. We just go until the... That would be good. I like that. Let me tell you about turbopuffer, serverless vector in full-text search, built from first principles and object storage, fast 10x cheaper and extremely scalable. And our guest, Matt Garman. And, yeah, Matt Garman. Well, we are joined by the CEO of Amazon Web Services. Matt Garman, thank you so much for taking the time to come and chat with us. How are you doing?
Starting point is 01:42:39 Hi. Thanks, thanks guys for having me. Please, take us through some of the high-level announcements. Obviously, it's Reinvent. Very exciting. Congratulations all the progress. I would love to know what's at the top of your mind, what's on the top of your presentations over the course of the event.
Starting point is 01:42:58 Yeah. We had a couple of really exciting announcements today. A couple I'd highlight. First, we introduced these idea of frontier agents. Yeah. These are agents both in Kiro for software development as well as in operations and security. And these frontier agents are meant to accomplish much, much more than customers were ever able to do in the past, where we have these autonomous agents that can help customers really turbocharged their software
Starting point is 01:43:23 environment. So super excited about that. We had some announcements around Nova, which is our frontier AI models that we announced. We announced Nova 2 and our new sets of models. And one of the things I'm in particular really excited about is Nova Forge, which allows customers to actually bring their own data to pre-training checkpoints, mix in their data with Amazon data, finish training the model, and at the end of it, have a custom model that deeply understand. their own enterprise data and is just for them. So that's another thing that I'm excited about. And then the third thing is we announced a new chip around Traneum 3
Starting point is 01:43:58 to really turbocharge the next generation of training and inference for our customers. And so quite excited to get that, and that went GA today as well. That's very exciting. Let's go back and start with the first one. Let's talk about coding agents and your own proprietary models. How are you thinking about positioning those to potential buyers? Are you, do you like the benchmarks these days? Do you think that we're sort of like post all the benchmarks?
Starting point is 01:44:29 Or do you think those are still useful tools for a buyer who's making a decision? Is it about integration? Is it about cost? How are you positioning them? Yeah. When you think about software development, it's not about pure benchmarks. It's really about what is going to allow you to get the most amount of work done. And when we think about our offering, which is called Kiro,
Starting point is 01:44:47 It's really focused on in an enterprise or environment where somebody is doing high-velocity development, they actually need more structure. People love vibe coding and it's exciting, but you can actually get down a path where you get stuck. And you'll often find actually that you spend just as much time trying to get back to where you were before as if you had just coded it from the beginning. We have this idea of specs that gives you structure to what you're trying to build. And so you can have agents go and start to build around those specs together with you and your, team. And it gives you the structure that allows you to go really fast and undo if you need to, can make sure that you're hitting your design requirements. And it really allows you and the agents to operate in conjunction with each other and move really, really fast. And we're starting to build
Starting point is 01:45:32 these much more capable agents that can go and actually do long running tasks for you on your behalf. But all of it is kind of ties into this structure. And we view that as a way to deliver kind of real development that's going to be meaningful on a large code base with large teams and enterprises where they have existing things, not just kind of single individual people sitting there kind of doing vibe coding, which, you know, you can do vibe coding on Kiro as well, by the way. We think that that's just not sufficient for what real development's going to need. Yeah. Talk to me about what it actually looks like to set an agent off and say, hey, I got a task for you, come back to me in a few days, which it sounds like that's where we're going.
Starting point is 01:46:10 We've been tracking the meter benchmark, and it seems like we've been seeing doublings there, But again, a lot of those have been, the benchmark has been, how long would it take a human to do this task? The actual agent might have done it faster. And so it's not necessarily that you're actually letting something cook over the weekend. What's the experience been like and what have people been reporting about these long-running agents? Yeah. I think the first and actually most important thing is thinking about how you actually kind of have a mind change on how you think about software development, where you think about not about do this task, get it back, look at it, do this task,
Starting point is 01:46:47 but how are you thinking about directing a lot of agents to go out there and do lots of different things and let those run for long periods of time where they can kind of have amorphous tasks. Like instead of go write me this function, like try to go solve this problem for me. And then it'll come back and then you can, but if you send out two or three or 10 or 20 or 50 of those things, then your job as a software developer and as a product leader is actually much more around coordinating those when they come back. troubleshooting, make sure that, you know, directing them, course correcting, et cetera. And so I'm excited about that. We've already seen these processes go off and work for multiple hours at a time
Starting point is 01:47:23 on particularly like really hard, tricky amorphous tasks. And we think those things are going to continue and be more the norm of how software developer teams change what they accomplish. We think Kiro is going to be the engine that's going to drive a lot of that. Yeah. Yesterday we were talking to Vincent from Prime Intellect and they do some of this like fine-tuning on smaller models. And he has this thesis, I think, that you share,
Starting point is 01:47:47 that a lot of businesses will need to take a pre-trained and then bring their own data, fine-tune it, not just because it's important from performance and output, but also from cost. But I'm interested in understanding how you think the market will shape out. Do you see implementation partners and, like, consulting firms coming in and doing that? I was asking him like, you know, there's a lot of tech startups that are going to be able to do that. They're going to understand I need to build an RL environment around my app. But for larger legacy companies, they might not understand.
Starting point is 01:48:22 So how are they going to wind up using that tool in particular? I think they will. And I actually just want to highlight one piece there where some of what we announced today is a little bit different. We announced this idea. It's an open training model with Nova. And so the difference of what you just said is people take a pre-trained model and they'll do RL after the first. fact and they'll try to do some fine tuning, which is great, but there is actually limits to where that does. In fact, if you do too much post-training, oftentimes those models or forget what they've
Starting point is 01:48:50 done at the beginning, they'll start to lose some of their reasoning and their core intelligence. Yeah. I mean, this is an unsolved problem, except when you go and insert your data in the pre-training phase. And so what we do with NOVA is we expose checkpoints. You can take a 60-point percent trained or an 80-per-trained model, pre-trained model. Insert your data into that pre-training phase, mix it in, we then expose actually Amazon training data to you via an API that you can then mix it together. And so it's like you said, here's my all my corpus of corporate data, here's everything that I need to know about my industry. We then mix that in and then finish
Starting point is 01:49:25 pre-training the model. So you get a pre-trained model that totally understands your company and your data. And then you can go do fine-tuning. You can go do reinforcement learning gyms. After that, you can shrink them down and distill them. You can do all those things, but on a pre-trained model that deeply understands what your company does. And is that called mid-training now? Is that the right buzzword for that? It's not like we're, and mid-training is a different thing. This is the first time that anyone's ever exposed this idea.
Starting point is 01:49:49 Okay, thank you. To deliver pre-training checkpoints where we can mix in your data. No one's ever done this before today. Very cool. It's first time. Great. Well, then yeah, on market structure, do you think it's self-serve enough that, you know, large corporations will do it?
Starting point is 01:50:06 Or do you need an AI lab? Do you need AI scientist? Do you need someone who can write TensorFlow or Pi Torch or something to implement this? Or is it something where just a normal software engineer at a large company could go and pull this off the shelf and implement it? Yeah. We'll see. I think we're going to keep working on the tools today. I do think that for some enterprises, they'll want to have some consulting folks that help them with this.
Starting point is 01:50:28 I think we'll have some people where you have some experts that should come and teach how to do this. And I think we'll quickly get the tools to a point where, you know, it's not somewhere where, you know, a non-touching. technical person is going to go do this for sure. But it may be a software developer that tends to be a little bit more on the AI or ML side that we hope is going to be able to go do this without having to have a whole bunch of expertise about how to go free train a frontier model. Yeah. On the cost side, obviously you're working, you announced a new chip.
Starting point is 01:50:57 I imagine that there's, you know, the emergence of some synergies across the models that you're developing, the software you're deploying the cloud and then also the chip. How are you positioning the, like the Traynium ecosystem? Is this something that you're planning on really doubling down on across the entire stack? Or do you want to be more chip agnostic? Are we going to see you buying TPUs in the future? No, we definitely, well, a couple of things that there all to unpack. The first is we're very excited about Traneum and think it has enormous potential.
Starting point is 01:51:32 And we absolutely think there's a benefit to optimizing every single layer of that stack where we have the best cost performance that we can deliver at Traynium. We have optimized models for you to use and applications and agents at the top of that that we talked about. So we think that whole optimization of that stack is going to be critically important. And, of course, we're going to support choice for our customers as well. And so we'll continue to offer GPUs from Nvidia as an example. And we have a very tight partnership there.
Starting point is 01:52:02 But we do think and we're quite excited about what Traneum 3 is going to offer for customers. And I do think that we're going to see an explosion of that ecosystem as more and more people get access to those chips and are able to take advantage of the pretty significant cost performance benefits that you can get from running on training. How are you thinking about open source, the open source ecosystem that you need to build around Traneum? That's the big discussion with the DPU right now, the question of, you know, Google has some amazing folks. They have some amazing software folks, it seems like. they don't necessarily need to open source everything. And so a lot of people are waiting to see how much the industry, you know, builds open source alternatives independently versus how much does Google just give away. What's your thought process on building an open source ecosystem or even just giving developers access to close source software to run efficiently on Traneum?
Starting point is 01:53:00 Yeah. No, we're all in favor of having an open set of software to run on Traneum. In fact, we have our neuron SDK, which is open source today and allows everyone to contribute to that. We think that the more that we can collaborate on that software ecosystem to make it easier for people to use chips. And we, of course, support the broad set of whether it's PITORCH or other kind of open frameworks as well. So we collaborate across the industry on that and are big advocates of contributing to and supporting that open ecosystem. Jordy? Love to get your insight on just like general constraints for for AWS as a business,
Starting point is 01:53:41 what you guys are doing on the power side. Is that a real constraint? Anything that you can share there? Yeah. You know, like, as we're scaling incredibly rapidly, we've recently announced that we've added 3.8 gigawatts of data center capacity in the last year alone, which is just an insane amount of data center capacity. Thank you.
Starting point is 01:54:03 Oh, you're welcome. And so it's ramping incredibly fast. And it is a constraint. You know, we have more demand than we have supply today for AI. Sure. And as we ramp up the supply chain, we think about all of the constraints. We think about chip constraints. We think about networking constraints.
Starting point is 01:54:21 We think about power constraints. We think about networking constraints, data centers, et cetera. And so we're working really hard to try to remove every single one of those. And with an industry that's growing as rapidly as the AI one is, there's always going to be some constraints. And we work really hard to keep removing blockers every time so we can keep growing fast. Makes sense. Well, we have a hard stop. So thank you so much for taking the time on such a busy day to come chat with us.
Starting point is 01:54:48 We'd love to have you back on the show and go way deeper. But thanks so much. And congratulations in all the massive releases. We're excited to dig in deeper and keep chatting about them. But have a great rest of your day. We'll talk to you soon. Thanks, drop me on. Goodbye.
Starting point is 01:55:00 Cheers. Let me tell you about public.com. Investing for those that take it seriously. They got multi-ass investing, and they're trusted by millions. We have Take Him, author of the Invidia Way, and a Barron's senior writer, joining the show. Take Him, the author of the Invideo Way. Take him on the beat. For joining the show.
Starting point is 01:55:22 And I'm sorry it took us so long. We've exchanged posts on X many times, and we wanted to have you on the show earlier. but I'm so glad we got to ask right away. Because it's the perfect time to talk to you. Do you have roommates? Not. No roommates. No roommates.
Starting point is 01:55:40 Long time listener, first time caller. I'm so excited to be on this. I'm so excited to have you here. Reminder, everyone, go buy the book. Seriously, Christmas is coming. I can't imagine a better gift for everyone. For a 10-year-old? For a 4-year-old.
Starting point is 01:55:54 I know what my son's getting. He's getting the InVidio way. Jensen Wong. Multiple copies. Multiple copies. No, seriously. Get 10 copies. Give them that. A lot of teenagers have read it. It's amazing and they reach out and it's an inspirational, entrepreneurial book that a lot of parents are giving to the kids. I love your headset, by the way. Because we're actually developing our own TBPN over here headset because this is just like this is the ideal set of. I was telling my friend, I don't care if I look like a dork. My hearing is going.
Starting point is 01:56:30 So, like, I get locked in when I have the head so I can hear everything. Oh, and it's wired. The worst is AirPods. Air pods have a tiny lag. If you're doing Zoom calls, it just, it ruins it. But we feel like you're right here at the table with us. It's not Code Red over there. He's Baja blasting.
Starting point is 01:56:46 Yeah. You know he's Baja blasting. Anyway, let's, let's, I mean, we have some time. Let's run through, I want to, know a little bit more about your perception of Jensen, your perception of NVIDIA, and just set the table for us, we know how, what is his management style, how does he, he has all the direct reports, he reads everyone's like to-do lists every day, they have tons of employees, they never fire people? Like, what makes NVIDIA's culture unique,
Starting point is 01:57:16 set the table for us so then we can go into the opportunities and challenges with that framework in mind? So the first thing I found out about their culture is it's very bluby. Like, I think in most companies, and you guys have done startups, but I don't know if you work for large corporations, bureaucracy builds a process that gets ossified. Vida is the complete opposite. Like, if things are not going well, he'll chew you out in front of the whole company. And that kind of blunt mentality, I think, you know, sparks better performance because you don't want to be embarrassed in front of Jensen in front of the whole company. But also, it just sparks agility. Like when I talk to people at Intel or Google, like the biggest problem they have is meeting paralysis and you need to get findoffs from like five different executives.
Starting point is 01:58:07 And in Vida, like you have a meeting. Jensen makes the call. He seeks out the right information and he moves. So there's agility at Vidia. The other thing is just a meritocracy. Even from the beginning like 30 years ago, Jensen's always asking who's the smartest person that you work with? who should I try to recruit? And from the beginning, like Dwight Dirk's, who's one of the top people right now, he recruited him because he talked to this other guy and he said, oh, Dwight's really smart.
Starting point is 01:58:36 Like, I really enjoyed working with him. And he just almost ruthless in the sense. He just goes after him and recruits them and bring people aboard. So this meritocracy, agility, speed, and just getting rid of the internal politics, I think, really separates him to the idea. How has most of the team becoming millionaires affected the culture, if at all? I think they have that thing in the first 10, 15 years,
Starting point is 01:59:05 like people started getting sports cars and putting them in the parking lot. But a lot of people... Let's go. That's the best news of you. That's fantastic. Sounds like it's had an incredible impact on the culture. Jobs finished. You don't need to respond.
Starting point is 01:59:18 You don't need to say anything more. I think winning culture breeds winning, and people want to stay with winners. Yeah. Right? Yeah. You want to win on the track then. A lot of the people I meet in terms of colleagues, they work for a chip company for five years and the chip doesn't work out. Yeah.
Starting point is 01:59:33 And you just waste it five, seven years in life. So you want to stay with a winning company. And Vividia has been winning for 30 years. So it's kind of like winning if it gets winning, you get the talent. And then the talent stays. Like there's so many top executives that Envidia that have stayed there for 25, 30 years. And there's also, there's, there's some benefit of people when, if somebody doesn't have a scarcity mindset, right? And they're just playing to win.
Starting point is 01:59:58 Like, they're just like, they're, they're no longer thinking like, oh, if we can just get to that next milestone and get this secondary sale. And if I, if I can participate and if I can vest my two years and sell into the next tender offer, then I'll, you know, they're just like, we're good. All that matters is just being as elite as we possibly can be and just, and doing it, uh, and doing it, uh, for the love of the game, basically. And a lot of these people that, like, they made it, they could retire. They could have retired 10, 20 years ago, but they stay and still work 80 hours,
Starting point is 02:00:29 100 hours a week because that's what's expected. Like even the marketing people, NVIDI are working 80, 85 hours a week. And that kind of mentality, I think, is different at the companies. Okay, let's shift into the competitive dynamic. I mean, NVIDI has been, I was revisiting the performance of the MagS7
Starting point is 02:00:48 since the dawn of ChachypT, it's been three years exactly. Nvidia, by far the winner, top 10x on market cap, the next closest company, I think, maybe four-xed by comparison. And so the clear AI winner in the public markets, the most obvious AI trade that just completely ripped. Now, you know, there's this whole narrative of like, how strong is their moat? What is the TPU mean?
Starting point is 02:01:17 Is the TPU going to be significant? competitive? Is there going to be margin compression? How have you been processing this new narrative that Nvidia might face serious competitive threats because they're so on top of the world? Everyone owes them so much money that people are saying, I got to get a discount from somewhere. And I'll go to Google maybe. I want to talk about this 10x move. It hasn't been like straight up to the right. There's always been every three, six months, there's always a reason to sell in video.
Starting point is 02:01:49 The H-100 problem, the transition to Blackwell, China, AIC, Brockcom competition. So this stuff has been happening, this entire 10x move up, and the media loves to latch on to the latest thing to worry about, right?
Starting point is 02:02:04 We had EAPSEC earlier this year the entire media establishment was, it's over for the AI tree. AI models have become so efficient when it was actually the opposite, because the reasoning models, and there was an exponential demand for compete. So I find it amusing, like, the whole world kind of discovered that Google had a really good
Starting point is 02:02:24 chip in the TPU, which they've been working on for a decade, too. They've had it for 10 years, right? They've offered it to clients in 2018. This is nothing new. So ironwood specs, you know, which I always take with a grain of salt with specs. Even in Vividia, they talk about 25x improvement with Blackwell ones, more like... I'm really just focused on the name Ironwood. goes pretty hard. It's pretty good.
Starting point is 02:02:48 They got some good names over there and Google. Ironwood came out, all the specs came out in April. All this stuff isn't new. And another thing I want to say is TPUs, their chips, we're going to see in TPUs estimates in
Starting point is 02:03:06 2025. And Google, at Google Cloud, Nvidia GPUs took more share than TPUs this year. Like, no one talks about this, right? And now everyone's going, Ironwood is going to take over the world. And the videos are trouble. Is that just because we're still early of a Gemini. No, it was a Gemini three thing. People are like, Gemini three is the best model in the world.
Starting point is 02:03:27 Yeah. On the best model in the world for a whopping six days. And chat GPT, it's still number one on the app store. Yeah, but I mean, six days, it was unseeded by Claude, which was also anthropic, which is also TPU potentially in the future. Yeah. And chat GPT, Microsoft, the head of Microsoft. AI Cloud, Tony, it's Docker 3, that Open Eye is training their next models on the GB300
Starting point is 02:03:52 MVM-D-L-Sem-2 that just went live in October. Actually, earlier today, the NVIDIA CFO said it's going to take six months, so I was a little disappointed in that. With six months for the training run? Yeah, well, she said the first models on Blackwell, like on the superclusters are going to take six months. So it's going to take time. But, but. It's going to be another six months. Open AI is going to get there. The Clod and Gemini benchmark gains with pre-training. That's the most bullish thing for the whole AI industry, right? AI adoption is the scaling laws are intact.
Starting point is 02:04:28 Everything's going to work out. And Open AI is going to get there when they build their next training on the next model. So going back to TPUs, thanks goodness, a shout out to Semi Analysis. They do the best channel work in the industry. everyone freaked out on Friday, right? They read that semi-analysis, oh, no, total wealth of ownership. TPUV-7.
Starting point is 02:04:51 They're going to destroy it. But, like, people that actually know the industry, it was flaming bullish for NVIDIA. It just, it was, like, so obvious in my face because Dylan and the semi-analysis, they said, wait a minute, the next TPUV-8 is not going to be that great. They lost a ton of people,
Starting point is 02:05:10 and the set function up in performance is not going to be that great. So you know what's going to be great? Nvidia's Vera Rubin, which comes out at the end of next year. So no company is going to switch. People are saying it's the Rick Rubin of Chip. Are they related? So anyway, so Vera Rubin is going to be dramatically better at the end of next year.
Starting point is 02:05:30 And even the ironwood, which just became generally available in their ramping right now, it's no one's going to switch over for one. It's a huge endeavor to put workloads from CUDA, Nvidia GPUs, and put them on. There's always problems when you put them on a new chip. Yes. And let's talk about TPU customers, right? Everyone freaked out that META might spend a few billion dollars in 2027.
Starting point is 02:05:58 That sounds like a lot, right? That's less than 1% of Nvidia's expected revenue. Sure. Nothing. And Ben Thompson was very smart and astute. He's like, who's going to buy the TPU? Who are the biggest buyers of AI chips? They're the hyperscalers, right?
Starting point is 02:06:14 So maybe meta will put a portion of their workloads 1% in the year's revenue. Is Amazon going to buy TPUs? Well, John just asked the CEO of AWS if he was going to buy TPUs. He dodged that question. He didn't say yes. There's no way in hell they're going to buy TPUs. They have their own tradium. They're not going to support their number one, like one of the number one.
Starting point is 02:06:36 Their arch rival. Yeah, they're not doing that. So is Microsoft going to buy TPU? You should have been like, yes, I'm going to buy one so I can like study it. Microsoft's not going to buy TPU. They're the number two player in cloud computing. And they're not. Are the neoclouds going to buy TPUs?
Starting point is 02:06:51 Now you're going to say, yes, Google has some neoclots. You know what happened with those neoclots? They're financially backstopping those neoclots. So Google is financially giving money and backstopping the debt for those neoclots. So there's a handful of small neoclots, but is core we've going to buy TPUs. Probably not, right? Who are the other customers of AI chips? Enterprises, companies, sovereign AI.
Starting point is 02:07:16 Yeah, anybody that wants to run like a fine-to-line model, some small model, something like that. Barrens. Barons. With a bite. So, like, if you just go down on our first principles basis and look at the customers of AI chips, they're going to stick with Nvidia. The millions of developers know Kuda. So you don't have to, you really need, like Dylan talked about this.
Starting point is 02:07:38 You really need, like, top-notch software-s sophisticated engineers that can, like, work with TPUs and learn jacks and all that stuff. So most people don't have those crackerjack engineers, right? So they're going to stick with NVIDIA because everyone's used to NVIDIA. NVIDIA is backwards compatible and forwards compatible. So, like, 20, 30 years of this stuff. And if you buy it, NVIDIA COLAF, the CFO talked about this morning. you can use it for training and they can use it for inference
Starting point is 02:08:11 and it's all on the same architecture and it's going to work. I talked to an AI startup CEO a few months ago. He tried AWS training. It looks a lot cheaper. Total cost of ownership. But then it crashed.
Starting point is 02:08:25 There were bugs. Their reliability. They couldn't figure out what happened and they just threw up their hands. I give up. No one is going to like if you have reliability problems, bugs, crashes.
Starting point is 02:08:36 The best thing about Nvidia is all that stuff has been ironed out over the last 10, 15 years. If you have a problem, you can figure it out. Yeah, it's like giving an F1 driver, like a car that is unreliable and saying like, hey, go race. Go race. Have fun out there. And then it's like, you know, D and F immediately. Spex is awesome.
Starting point is 02:08:57 It seems great. But then when actually build your business on it, you put the future of your business onto something. The number one thing, it's not price. It's like it better. Oh, better work. It better work. And with the video, it works.
Starting point is 02:09:12 Yeah, but react to this idea that Dylan Patel was joking about as TPU is a stocking horse. So this idea that Sam Altman is already saving 30% on his Nvidia purchases effectively because just the threat of going to TPU is enough to get NVIDIA to make an investment or slightly discount in one way or another. I don't think that's reality, and I don't think that math actually works because I think he's confusing the AMD deal where AMD gave free warrants to Open AI, right? First of all, the deal's not done. Sure. It's a letter of intent. None of these deals are done.
Starting point is 02:09:51 They're not done. AMD's done. They signed an agreement where they're giving away a percentage of their company through these free warrants. The Nvidia deal hasn't been signed yet, and they actually, language into tank queue that it might not happen. Sure. No, yeah, I saw that. Doesn't Open AI have to buy AMD chips in order to get the warrants? Yes, yes, yes.
Starting point is 02:10:11 And so it still could be that they don't actually end up going through with the purchase, and then they wouldn't get that. That's a good point. Yeah, yeah. So the whole, like, let's do a sidestep here with the circularity and all that stuff. All this stuff, it's like one gig at a time. There's milestones on Open AI. There's milestones on AMD, technical milestones.
Starting point is 02:10:30 They have to achieve certain targets. So all this talk about, you know, everyone loves the, big number that adds up five years of CAPEX. A lot. Like that, it could get, the leverage could be up or down depending on how things happen every each year of the way. So, you know, it might not be that big number if Open AI doesn't come out with an amazing model or AMD isn't able to hit the milestones they said for their next 450
Starting point is 02:10:58 MI chip, right? So, like, you know, don't worry about five years. like take it one year at time. Right now, demand is off the charts. Now, going back to the NVIDIA 30% discount, like, that's not how equity investments work. If NVIDIA does invest $10 billion, $10 billion up to $100 billion, say that, say that,
Starting point is 02:11:18 Nvidia gets ownership of the company. It's not like a freebie, right? You're giving away ownership of your company. So it's not really a discount. You're getting ownership of the company. So I don't really believe in this 30% discount thing because in video jensen will say they're investing to accelerate open AI and uh they they're looking forward to you know opening i i mean it's definitely creative it's definitely a new structure i'm just
Starting point is 02:11:45 trying to i would i would steal man in that like if i'm an entrepreneur and somebody comes to me and they're like i'm going to invest a hundred million dollars in your company over a series of milestones and you're also going to buy something from me i'm like yeah i'm taking some dilution but realistically like this is a way less of a headache. Like where else was I going to get $100 billion from in Open AI's case? Like it's a great, it's a great source of funding that, yes, it will be diluted, but the whole structure is all diluted all the time because of all the different ownerships.
Starting point is 02:12:18 Except for this kind of sentiment thing that we had the last few weeks. So Open AI hasn't had any problem in raising money for venture capital. Yeah, yeah, yeah, it's true. Yeah, yeah. It's not like Nvidia is the only source of funding for Open AI's. Like everyone wants in that revenue run rate. It's like $5 billion to $20 billion at the end of this year. So what was your taking on the code red?
Starting point is 02:12:38 What do you think about the code red? So I saw that you showed that Ashley Vance. Yeah. Yeah, Mark Chen. Mark Chen was talking about how they kind of focused a little too much on reasoning and their pre-training muscle wasn't there. Reasoning, we could talk about this later. Reasoning is like the biggest kind of accelerant of AI demand in the past year.
Starting point is 02:13:03 So I think it's actually really good. And supposedly Ilya was, you know, doing the research for reasoning. Yeah. Reasoning is awesome, right? But they kind of focused on reasoning the past year with 01 and 03. Sure. And now they're like, okay, we have to go back to pre-training. So Open AI knows that pre-training still works because Gemini 3 had great pre-training results and Cloud Opus 4.5 did.
Starting point is 02:13:27 So now they're going to do the pre-training. So they have their focus on one thing, and now they're going to do the other thing and make their model much better. I do agree that Open AI has been a little too maybe diluted. Like they're doing apps. They're doing hardware. They want to compete in AI infrastructure against Microsoft and Oracle. They want to compete in AI chips against Nvidia. I thought it was really interesting, like Satya repeatedly said.
Starting point is 02:13:57 said he wouldn't name who he's talking to, but it's like, I think it's important that we realize this is not a zero-sum game and this can be a win-win partnership. That was during the Anthropic Nvidia deal with Microsoft, right? Sure. He bet that a couple times. And I think the person that he's talking to is Sam all right. Right? Like, let's, let's, Nvidia, Microsoft made Open AI as successful. They were to partners.
Starting point is 02:14:26 Like, why are you competing with the partners that brought you to dance? Right? Let's go back, focus on making the best AI model in the world, and don't compete with Nvidia and Microsoft. Maybe five years from now, but, like, it seems a little aggressive to compete with them right now. Let's talk about China. There's been a ton of debate over Nvidia selling chips to China, legacy chips, older chips. We've gone back and forth on it so many times.
Starting point is 02:14:56 What's your current thinking about the best policy for Nvidia exporting chips to China generally? I think the best thing is to keep it one or two generations behind the current state of the art. Yeah. Like this is a really nuanced policy that people, you know, everyone's either hawkish or dubbish. Totally. Whatever. The best policy is to keep, I don't want to use the word that Howard Lutnik used that got China very upset and forced. forced China
Starting point is 02:15:27 to tell this company not to buy H20. But the best policy is to get China still on the Nvidia sack. So,
Starting point is 02:15:37 Nvidia gets $50 billion of revenue per year that can help R&D and fund R&D and make the chips even better. Like,
Starting point is 02:15:46 Nvidia and the U.S. already won, right? They had 95% market share. Like, why are we going to give $50 billion
Starting point is 02:15:54 of oxygen to Huawei and all these other Chinese AI chips companies that now Chinese companies that need to buy AI chips are going to buy Chinese AI chips. Why not keep China on the NVIDIA Tech stack one or two generations behind? Don't give them the best stuff, but maybe one generation behind.
Starting point is 02:16:14 I think that would be the best compromise for both sides. But I don't know what's going to happen. Where do you place a likelihood that the Chinese marks? market has opened up again at some point in the next 12 months. Maybe 50, 50. I mean, that sounds like a cop-out.
Starting point is 02:16:32 I was much more positive six months ago, but, you know, this has been just so crazy. First, the Trump administration banned H-20. Then they didn't ban it. They said it was fine. But then China was like, no, you hurt our feelings. We're not going to let companies buy the H-20. And then they ban it. Yeah, and then maybe Trump is going to let NVIDIA sell the H-200.
Starting point is 02:16:54 or a Chinese specific version of Blackwell that's kind of hobbled a little bit. Who knows? Like, NVIDIA needs to convince the Trump administration and then China to buy the chips. The worst part of it is China was willing to buy the H20, and it's just all the kind of geopolitics and hurt feelings, you know, that ship has stailed. So I don't know what's going to happen. But I do think the ideal situation is that Vyria could,
Starting point is 02:17:24 sell one generation behind, make $50 billion a year, and keep the competition from Chinese AI startups out of the way. And even understanding that at some point in the future, China's buying effectively zero chips from Nvidia, but it would be five, ten years in the future? It was like you have to assume that like... Right now is it. Go for it. The amazing thing is, it's 0% right.
Starting point is 02:17:59 And Nvidia's revenue accelerated. For the first time in two years, Nvidia's revenue accelerated in this latest quarter. And this is not talked about enough. This is the first quarter that the NVL 72 AI server has been available in volume. And then revenue just skyrocketed without China, which is incredible, right?
Starting point is 02:18:20 And that's why I'm so bullish over the next few years, because next few quarters, let's say that. Because this product cycle is gonna last at least three, four quarters. The key tell is the revenue acceleration first time in two years. And the other key tell is that the networking segment for Nvidia was up 162% year over year.
Starting point is 02:18:40 And typically a lot of these data centers and these neoclads buy the networking stuff six months ahead of time. So the next six months from now, like the GPU numbers for Blackwell and the NVL 72 server is gonna be It's just going to be bonkers. It's going to be off the charts.
Starting point is 02:18:56 And people don't talk about these NVS 72 AI servers. They're $3 to $4 million, right? There's 72 GPUs, 144 dyes, one and a half tons, 5,000 cables. And the prior version was 8 GPUs. So these AI servers, I call it the iPhone 3G moment. Do you guys remember the iPhone 3G? This is big for the Christmas shoppers out there. If you want a gift, it's a step up from,
Starting point is 02:19:23 the NVIDIA way, I recommend picking up an NVL 72. It's only $4 million. Yeah, but for the right 12-year-old in your life or the potential the intern, I think Tyler won't put it under the tree, but it could be fun. No, no, it's like it's like a Lexus. You put it in the, in the driveway with the bow on top. Yeah, yeah, yeah, yeah. That's the way it does.
Starting point is 02:19:45 With the foreg, you drop the forklift come drop. Exactly. I got you in NVL 72. Enjoy. And then we have the reasoning model thing where exponential compute and companies are actually seeing like huge precursor, 40% productivity gains, THH Robbins and 40% shipments, rock and mortgage, 80% reduction in paperwork, cost processing. This is like the next year, because of AI reasoning, because of the MDSM, that's why Amazon and Microsoft said, Every quarter this year, they raised their CAPEX.
Starting point is 02:20:23 And everyone's like, they're going to cut their CAPEX. No, every single quarter, they raise their CAPEX. That's because they're seeing the demand. And that's why Amazon and Microsoft are going to double their data center capacity over the next two years. That's crazy, right? In September quarter, more leasing, there are more data centers leased than entirety of 2024. This is like exponential function up. And people aren't talking about it.
Starting point is 02:20:48 They want to talk about TPUs. like destroying Indyria. What about some of the kind of demand guarantees that have been happening? Is that a concern at all? Do you think about it much? Is it not really? I mean, demand guarantees like you're talking about Nvidia and CoreWeave. Like when that happens, analysts every quarter on the conference call, like, did you use that,
Starting point is 02:21:14 you know, demand guarantee? Like, it's not happening yet. CoreWeave's five-year-old GPUs that everyone says are useless are 100% utilized. H-100, a massive cluster before it expired, probably a three-year contract, they got like 95% of the pricing. This is like unheard of. And the reason is there's overwhelming AI demand, and there's not enough capacity. Overwhelming AI demand, not enough capacity.
Starting point is 02:21:44 And people just are just, they don't care. about what's happening in the real market. This is real life facts, evidence, numbers, and video going from 56% revenue growth to 62% revenue growth on $57 billion with Darrow China revenue. I mean, we talk about the stock price being up 10x. The revenue is up 10x in like two years. This is like beyond history the last 30 years of following technology. I love how Evan, you're the only person. without Nvidia fatigue. You're just like, you're not bullish.
Starting point is 02:22:21 David Gagins of the David Gagins. They can't keep running. They can't keep running. This is not me just like making stuff up. This is like numbers are there right in front of everyone. You make good points. You make good points.
Starting point is 02:22:33 I like it a lot. We'll have to have you back on the show soon. This is a lot of fun. Yeah, let's do it. Let's make this a regular thing. Yeah. This is fantastic. To have you on finally.
Starting point is 02:22:43 Thanks so much. Thanks for all your report. The book is the Nvidia way. Get it at wherever books are sold. Get 10 copies. Give it to everyone in your life. Also, give the gift of fin.AI, the number one AI agent for customer service. Automate your most complex customer service queries on every channel.
Starting point is 02:23:08 Up next. Oh, yeah, we can just go straight into our next guest. Let's bring in. We have Tark from Kalshi with some massive news. Tark, great to see you. How are you doing? From the Alton floor. Stream.
Starting point is 02:23:20 Good to see you. Hey, guys. Thanks for having me. Very excited to be here. You are locked in. Look at that backdrop. Fantastic. Please, introduce yourself.
Starting point is 02:23:29 You've been introduced. Give us the update. What's the news? Let's ring the gong. Well, we just raised our Series E. We just raised a billion dollars. 11 billion. That's a great wind up.
Starting point is 02:23:41 Great wind up. I was waiting for the gong. Congratulations. A fucking sick moment. I was a going, guys. Yeah, great to have you on. I was thinking over the, I don't know if anybody had a crazier Thanksgiving holiday than you. It was, there's a lot going on last week.
Starting point is 02:23:58 So nice to come out of that with a, with a big announcement. But yeah, maybe kind of just update us on. I think everybody has been following the prediction market wars. The more important story, I think, is just how much. Some people are calling it bloodbath, actually. Yeah, I mean, just like it's been a battle field on the timeline. But yeah, I think like what's happening in the background is like this explosion of this, you know, new asset class that, you know, again, I think in your announcement earlier, you were saying a few years ago, there nobody really cared at all. And now, you know, you and the industry broadly have millions of users.
Starting point is 02:24:37 So it's pretty unprecedented. But yeah, what's what's been the latest on your mind? I mean, I think the thing that's happening right now is British markets, I think, have gone mainstream. I think every inch of evidence is pointing towards that. And I think that the thing that we're seeing is there's sort of one of these rare shifts in consumer behavior that you don't see often. Like, they don't happen. Like changing the behavior of a customer, the habits of a customer is a rare thing. And it's unique.
Starting point is 02:25:08 And when you see it, you have to really go after it with all your might. And it's, you know, there's like a number of things. that have to align for that to happen. And I think they're aligning for prediction markets. I think it's happening. And I think there's, you know, one factor is the fact that people are not really trusting the sort of legacy media and legacy sources of information. And they go to prediction markets to get smarter.
Starting point is 02:25:31 The other one is that they're legal now. You know, cashies took on this sort of battle over years to legalize this entire market and, you know, set it up as a legitimate financial asset so that anyone can participate. And three, I mean, I think we're all kind of sort of, sort of caught wildfire this year. I mean, I think the, we're seeing people, there's a little bit of this phenomenon where you cannot watch a sports game without looking at the Calci odds live and the Calci charts. You cannot talk debate about a topic about the future without, you know, talented somebody to put a position on Calci on the app. So it's a huge announcement. We're very
Starting point is 02:26:08 excited about it. And honestly, really feels like we're just, we're just scratching the surface of what production markets can be. One thing I've noticed when I'm watching a sports game is there's sometimes an integration with Kalshi, sometimes with a competitor. What's actually going on? You know, legacy sports book. Yeah. What is actually going on?
Starting point is 02:26:29 I feel like a lot of people who are just passively observing the timeline are seeing a lot of like announcements and partnerships with the partnership economy. And people are joking about it. Like what's actually going on? What's at stake with some of these partnerships? What have you done? and what does it actually mean? Because it feels like if you do a partnership with a specific league,
Starting point is 02:26:47 that doesn't necessarily mean that I can't get odds on that event somewhere else. So what is actually going on with the partnership economy? I mean, I'll tell you kind of our approach to this. So we are building, you know, our focus is building on a business. It's very metrics driven, you know, and sort of for context. So we're doing a billion and a half of volume a week now. Wow. And, you know, we're market leader by meaningful margin.
Starting point is 02:27:12 I think, depending on sort of how you measure it, so there's something around 80 to 90% of market share now. And I think any partnership we do, we bucket them in a bunch of categories, but they're all focused on actually driving legitimate volume and legitimate use case into the product. So I partnership with platforms like Robin Hood, I mean, Coinbase leaked, it's coming in December,
Starting point is 02:27:32 and prize-fix, Weble are kind of in that bucket. Then we have partnerships with a series of partnerships coming around news. One of them leaked this morning in the New York Times article. but they're also very one sentence 10 leaks everything leaks these days
Starting point is 02:27:49 you know we're just like nothing is news anymore it's like sort of you know it's all leaks but but the point is we're focused on things that drive legitimate use to the products and and then drive legitimate utility to
Starting point is 02:28:03 the partner and so whether it's a broker obviously you know this could be a big revenue line for them and if it's a news network it's a complement to the reporting that actually makes the reporting more accurate. And reporters love truth and prediction market spring truth. So you could see the synergies in how they fit. Okay.
Starting point is 02:28:20 Yeah, yeah, that makes a lot of sense. Yeah, what, yeah, I think some of the big news out of last week is that Robin Hood is entering and kind of potentially trying to verticalize the product experience on their side. What can you say about the, I guess, like how you see the strike. of the market evolving. You guys are in exchange. Robin Hood is a brokerage. Sounds like they're trying to actually build an underlying exchange themselves. How much should, how much should sort of observers of the industry look to how the stock trading and stock markets, stock exchanges have evolved versus prediction markets? Like, what does this market kind of look
Starting point is 02:29:06 like in five years, 10 years, as much as you can kind of pull out a crystal ball for us. I mean, maybe the basics is like, and you've seen this a little bit in AI, right? After you see the success we've had, it's basically indicative of like, okay, there's a massive market opportunity ahead of us. And when that happens, I think you're going to inevitably see a ton of competition. And generally in those markets, like the sort of massive surge of competition, whether it's brokers, there's some of the sports books like Daxons and Fanduel coming in. it's just usually a sign that there's a lot of good things to come for that market. It's a sign that you have big companies reprioritizing their entire roadmaps to go all in after this.
Starting point is 02:29:52 And that's a positive for us. Like we're market leader in a market that, you know, everybody is trying to believe is going to be ginormous. In terms of the specific question of market structure, I mean, like, you know, we have obviously the exchange. We also have our direct products in some ways are competitive with some of our partners. And I think, you know, the same way that we're working with a lot of different brokers, where at times some brokers are going to sort of diversify and work with a number of different exchanges. And that's how these sort of market structure evolve over time. And the only thing that matters, the kind of the thing that stands out is similar to any other market is product.
Starting point is 02:30:24 And product velocity is, are you putting out products faster than anybody else? And are you putting out products better than everybody else? And I think Calci has had a pretty incredible track record of setting the pace in the industry. At least if you look at the last year, we've set the pace on the industry and everyone's following. And I feel pretty good about us continuing to do so in the next 24 months. How do you think about the market structure? I think everyone's wondering, like, obviously this is a new market. It's unlocking entirely new sort of asset classes.
Starting point is 02:30:51 And it's obviously big. Everyone's excited about the numbers. But is this a natural monopoly? Is this duopoly? Like, how many winners will there be? How do you even think about the market structure? Is there some return to scale? It's interesting.
Starting point is 02:31:08 I kind of, like, don't think much about that. Like, I think investors love to sort of, investors do this. thing where they're sort of going to rationalize all of it in five years, you know, everybody's going to be super smart about how they all figure it out. But like, look, I think that like it's a very nascent thing, right? It's, you know, like it has some similarities to ride share. It has some similarities to the Draftings Fandul era when that happened. It has some similarities to the online brokerage industry. And it has some similarities to financial exchanges like CME. So where does it fall? Probably somewhere in between all of these sort of buckets. And probably not exactly the same
Starting point is 02:31:41 as any of these other buckets. And I think that you'll see more of, I think with enough scale in financial services, but also true for any industry, everyone gets into everyone's territory. And so the only thing that matters, again, is sort of what companies are going to rise above the others in terms of product velocity and product quality.
Starting point is 02:32:01 And that's just what we're narrowly focused on. There's a question from the chat. Can you explain how external market making works on Kalshi? That's been a, for some reason, a hot topic. recently, but, you know, market makers are part of any financial market. You kind of need them to basically have liquidity in markets. And actually, Cali and prediction markets have less customer to market maker flow than traditional markets. If you look at options, for example, it's like the vast majority is, you know, Jordy to a market maker like Citadel, whereas
Starting point is 02:32:32 on Calci, actually, the vast majority is, you know, Jordy versus John. And then some of it goes to market makers. And it's an open, transparent orderbook where everyone's competing on price. And we have actually a separate company called cash trading that trades on the exchange, but they're very small percentage of any liquid markets. Really, their function has been for new markets are a little bit weird. Yeah, that makes sense because if it's some really, really niche thing, who's going to put in the first 500 bucks? Exactly.
Starting point is 02:32:58 And they're not very profitable. It's actually, we really, like, they're really focused on providing a good customer experience that we bootstrap markets rather than like any meaningful part of the business model today. and if we took it out, it would be actually a worse experience. So I think it's definitely not positive for the ecosystem. But it's a bit like Uber, you know, when the adverse interests got impacted. The taxis, they were coming out with all these reasons, right? Like, you know, about all these kind of random reasons, but I don't think there's much truth to it.
Starting point is 02:33:25 Yeah, so I'm sure you can't comment on any specific lawsuit. There's a number of them. But what has been the, I think there's quite a lot of prediction markets experts that have looked at some recent lawsuits against prediction markets and said, they clearly don't understand how this works. Can you comment at all in some kind of like misunderstandings broadly? Yeah, so we, what Calci has done is first regulate prediction markets as a financial instrument under this agency called the CFTC. People have been hearing more about the CFTC recently because it also regulates crypto. And that's one of the main financial agencies. There's the SEC that does
Starting point is 02:34:08 stocks and CFT that does commodities. And then we did the same thing with elections, and now we did the same thing with sports. And the way that it works is, like financial markets, those are regulated at the federal level. And so the law around these markets is just federal. They kind of report to a federal government and federal regulator, not a state government and state regulator. And there's a bunch of reasons for that, but it's kind of how the constitution was formed, which is some stuff makes sense at the federal level and some stuff is more local and
Starting point is 02:34:36 make sense at the state level. And we are one of these things that fall under the federal level. And federal law preempts state law. So if you are okay on the federal side, state law doesn't really kind of apply to that exchange. And that's why we have one regulator, which is the CFTC, our federal regulator. And again, like, I think it's normal with, like, when something so disruptive happens to an industry, the people that are adversely impacted are going to come after it and come up with all sorts of arguments for why it shouldn't exist or why, you know, Airbnb was terrible and all these different things. But at the end of the thing that drives it long term is, is this a great product on our consumers loving it and using it? And the answer is yes in this case.
Starting point is 02:35:14 Off of the success of Kalshi and Polly Market, there's been a bunch of net new prediction market startups that are created. Is there a possibility that this market like ends up having these sort of like niche maybe more like vertical marketplaces? Or do you think that the platforms that the greatest liquidity and the deepest liquidity will ultimately just absorb those sub-markets? It depends on how narrowly we define prediction markets versus broadly. I really think of prediction markets as kind of just like a next general, like expansion of financial markets to touch to anything.
Starting point is 02:35:57 Cali means everything in Arabic, but really if markets kind of progressively grew over time, Kalsi, what we did is just like kind of widened that set, dramatically. over what it could touch. So I could see some, you know, startups innovating on like specific verticals over time and doing reasonably well, but there is real concentration of liquidity and concentration of volume that happens
Starting point is 02:36:19 in these types of markets that is hard, I would say, to battle with. And so I think at least from that aspect, like I think the cards are probably mostly shuffled already. That makes sense. Last question. There was a viral clip of you talking about Donald Trump Jr.
Starting point is 02:36:39 Do you have anything more to share on his involvement? Because I was watching that and I was like, yeah, it's kind of like, hey, where are we going with this thing? It seems like politicians have a deep insight on how campaigns use these prediction markets, but can you share anything more about his involvement in the company? Yeah, I mean, look, first of all, that clip is a clip and you know how these clips are taken. Who needs context? Yeah, it's like, we don't need context.
Starting point is 02:37:07 You know, anyways, look, I think that, you know, we have done, like, one of the main products that took us mainstream was an election market. And that brings a lot of attention from politicians on both sides of the aisle. And you see it, you know, trauma at the time was using his prediction markets all during the election. And actually, Mamdani more recently was using his calcium odds pretty consistently during his election. And so in some ways, like, you're going to see a lot more, like, prediction markets are going
Starting point is 02:37:35 to touch financial markets, going to touch the news, and they're going to touch the political process because they bring more truth to all of the above, all of these categories. And in some ways it's good that we get more and more, I would say, like, politicians involved and, like, engage with these markets. The one thing I'll say about this, and, like, again, it's very, it's in the same bucket as the, you know, as the other things that we discuss where, like, there's industry dissidents that are against prediction markets that find all these different reasons for why prediction markets might be bad.
Starting point is 02:38:02 But the thing that happened is not this administration necessarily, even though this administration is pro-innovation, is we won that lawsuit on the election market, which has really redefined what the landscape, what the boundaries of what the financial market is. And that lawsuit was won, you know, is in the court of appeals in G.C. with relative, it's a very progressive panel. It was a panel of Democratic judges where we won three zero. So people want to make it out of it to be a partisan issue, even though I don't think truth needs to be a partisan issue. It's just, you know, these markets work. People love them, and they generate a lot of insight out of them. And I think that will win the way when the day at the end of day.
Starting point is 02:38:38 Last question from my side. How does the CFTC view when a market participant has some type of alpha or non-public information and they're betting on a market based on that information? From my view as somebody who like gets data from, you know, we work with polymarket, we look at, we use polymarket data on the show. if somebody has inside information and they're trading on that information, it actually makes the markets more accurate. So in some ways, as a user who's just like viewing markets, it's, I want people that have inside information on global events to be trading so that the markets
Starting point is 02:39:22 actually better reflect reality. But what is like the CFTC's view on that type of activity? Because like things get thrown around all the time, insider trading this or that. But I don't actually know what the actual law says. Yeah, that's actually a great question. It's a point of debate in this land. But I think there's some distinction. So Calci is a regulated exchange. So everything we do, in some ways, a lot of the laws and the rules are very similar to what you would expect in a New York stock exchange and some of the traditional financial markets.
Starting point is 02:39:56 The question of insider trading is interesting because what you just said could also apply to the stock market. Right. Like if you want to accurately price the stock, maybe we should that. instead of trading happen. Sure. And the reason why it's actually not allowed is because it makes the game unfair. It makes the market unfair. And if the market is unfair, liquidity dries out.
Starting point is 02:40:15 People just stop participating. Yeah. Right. And that's why you have to have reasonable rules of the road where people can reasonably expect to be treated fairly in this marketplace, where there's no kind of asymmetric or structural advantage for one participant versus the other. And we take the similar approach here. So if you actually have insider information, which is information that, like, you're not supposed to reveal to the public, you're not supposed to trade on it because trading on it is a way to reveal it to the public.
Starting point is 02:40:44 And so that makes kind of a more balanced, more fair marketplace. And I think we're very focused on that. But it's a very interesting question. It's one that the industry is battling with. But we take a hard stance on insider trading. Yeah, because if somebody goes and they go and they vote in a local election and they see like, okay, I talk to. I talked to somebody there and they said they were voting this way. And I talked to another person.
Starting point is 02:41:07 They also said they were voting this way. And then somebody trades on that information. Like, is it actually, like, is that, you know, how do you define that type of activity, right? It's like anybody could go down to the polling, you know, anyone could go down to the polls and kind of like, or voting center and just see, like, ask the same question, right? So anyways. Well, I was going to say it's the same as the stock market, right? If you go and sit in front of Walmart and count everybody that's going in and out and then, you know, during the day and forecast their sales from that, that's actually fair game. Now, if you call your cousin at Walmart and ask them for information they have internally that are not supposed to reveal to the public, that's inside our trading.
Starting point is 02:41:48 And I think we have a very similar line here. Yeah, yeah, yeah. That makes sense. Very cool. Well, super helpful. And yeah, congrats to the whole team. It's a pretty massive milestone. Huge.
Starting point is 02:42:01 And yeah, great, great getting the update. Thanks so much for taking the time. Thanks for having me. We will talk to you soon. Talk soon. Have a good one. AdQuick.com. Out of home advertising made easy and measurable.
Starting point is 02:42:12 Plan buy and measure out of home with precision. Our next guest is Matt Mullenweg from Automatic. He is in the Restream waiting room. Let's bring him in. They are. They are parent company of WordPress.com. Tumblr. I think are going to remain.
Starting point is 02:42:28 Welcome to the show. So, Matt, how are you doing? I think we have you on a hot mic. We might have you on a hot mic, hopefully not. Welcome to the show. We're about to come on the screen. Yes. All right, well, a little drum roll.
Starting point is 02:42:41 You're all about to experience TBPN for the first time. So, Matt, our audience is live. We're streaming on them. They're streaming on us. How are you doing? We're doing. Fantastic. How are you doing?
Starting point is 02:42:54 Good to me. Howdy. Thank you so much for, I know this is a little non-traditional. So we're kind of like two hours into like our big annual address, the state of the word. It's kind of like our state of the union speech. But thank you so much for allowing us to connect them. I'm kind of magic. A lot of folks in the room have never heard or seen TVPN before.
Starting point is 02:43:13 So this will bring a lot of new folks into your world. And I'm excited for some of your world to learn about WordPress. Yeah, give me the state of the word. And then also I want your personal word of the year. We've been debating what the word of the year should be over here. Ooh. So state of the word, and I'll say the state of the word is strong. Okay.
Starting point is 02:43:33 That's good. Let's hit the gong. We're hitting the gong for that one. Strong state of the word. We actually just did a live release of WordPress 6.9. So WordPress does major releases three times per year. We're able to do it right here on stage. We had a little button that we pushed.
Starting point is 02:43:54 We got to get it on next time. I love it. That was pretty fun. Don't worry, I didn't just ship it again. But, you know, one of the things about WordPress is it's not just built by one company, but it's a community of WordPress 6.9 over 900 contributors from all over the world, different countries, different languages, different companies all coming together. And so that was pretty exciting.
Starting point is 02:44:16 My word of the year, and actually a theme we were just talking about, is I'm going to choose freedom. So, powerful. As technology, like, starts to influence more. more and more of our lives, you know, how we travel, who we date, the things we learn, the news we're exposed to, you know, the sort of freedoms that are embedded in an open source license. I like to refer to open source licenses sort of like a bill of rights for software, gives you an annualable rights that no company or person can take away from you.
Starting point is 02:44:43 And that freedom and agency, I think, is really, really important and something that I think, you know, is technologists or builders that we should try to embed into everything that we do. Give us an update on Beeper. I was super fascinating. I was super fascinating. I was super fascinated by that product. I love, I love walled gardens. I also love tearing down the walls of gardens. It seems like a good shot across the bow of the, the I message, walled garden. How's the progress going there? Are you using the service personally daily? Are we going to see a lot of growth there? Well, obviously, I'm using a daily. So I would think of it not as like replacing a walled garden, but more like allowing your gardens to come together.
Starting point is 02:45:27 So I'm sure you like me, I have friends on lots of different networks. And some of them always love to use WhatsApp, and some of them always love to use, you know, Instagram or LinkedIn DM sometimes. I even get some interesting stuff there. And I hate it when I miss these messages, you know, because, you know, checking all the different apps sometimes or the notifications I might miss something. So think of it not unlike how email clients, you know,
Starting point is 02:45:51 can bring in lots of different email accounts. Beeper takes all the different networks where your friends already are and maps them together. Now the plus and minus is that it's not going to replace the networks. Like I still keep all the different sort of specialized messaging apps because, like, for example, if someone sends you an Instagram story, when you click on that, you're going to want to load Instagram, for example. So I think of it as complementary and hopefully even increasing the usage in a very small way right now. It's pretty nascent. But in the future, think of it as sort of a different interface.
Starting point is 02:46:20 So you might still have like the dedicated apps, but then having this all in one inbox that you can sort of manage everything tag people, have folders and does cool features like scheduled messaging across all platforms or even just like weird heuristics that are pretty simple to do but like show me all the
Starting point is 02:46:36 don't just show me unread but show me all the people I've messaged that haven't messaged me back yet. Oh yeah sure sure we've talked to some young hackers some startups who are building you know sort of beeper competitors and their whole value prop is like we've figured out a way to get it into the iMessage ecosystem.
Starting point is 02:46:55 Do you think that we need a new regulation there, some sort of law change or some result to actually open up iMessage, or do you think that with enough tricky hacking, it can be done? Well, technically, it's not hard. Well, it is hard. It's very possible to reverse engineer these networks. However, as we saw with sort of a previous iteration of beeper, If the network really, really doesn't want you to do that, it's probably not good to pick a fight with a trillion-dollar company.
Starting point is 02:47:31 So perhaps these things might happen to open source or something, but as a commercial company, I think ultimately you have to be somewhat respectful and try to complement these networks. So how Beeper works today is we don't support iMessage on the mobile or Android. In theory, we could, but Apple has indicated that's something they don't want. We do support on the MacOS clients. We have a way to integrate with sort of iMessage using some APIs that are available on macOS. And so on macOS, we can bring in your iMessage. Got it. But again, I'm building this for the long term, and we are a commercial company as well.
Starting point is 02:48:05 Sure. So, you know, we want to work with the networks. And, you know, perhaps there can be regulations like the European DMA are things that can encourage interoperability. But ultimately, I think that the... the sort of people who run these networks have to see a longer-term benefit for them. And for things like, you know, some of the other networks I mentioned that people works with, I think their business model and everything, the increased usage is really useful for them. I think for today, Apple's business model, particularly in the U.S., kind of the lock-in effect to the device business,
Starting point is 02:48:43 which is, of course, where they make a lot of money from my message, probably indicates that and less forced to, I doubt they will adopt sort of iMessage interoperability. But who knows? Sort of like they used lightning for a while and eventually got USBC and all over a life's got better. Who knows what will happen in the future? Talk about links on the internet. I feel like we're at a point in time where social media platforms are trying to keep users in their own applications so that they can monetize them to the full extent.
Starting point is 02:49:15 meanwhile you have LLMs which are ultimately doing a lot of the same thing they're taking content from all over the internet trying to keep users in the individual applications feels like WordPress in many ways is making moves to kind of like almost fight back against that I might have that incorrect but I feel like it's important if you're running a business independently online it's great to have people like on your own website so you can develop a deep relationship with them. But what is your view on that? We're very much anchored around X as a business. Obviously, X has had issues with links or chosen to demote them in the algorithm
Starting point is 02:49:59 over the last couple years. But give us kind of the state of the union on links. That's a broad one. Well, I will say X is actually a great example. And I've talked to Nikita about this. So they now, they've shifted some of the balancing of links, and they now have this really nice
Starting point is 02:50:14 in sort of app browser. So you've probably noticed that now. That when you load a link, you actually still have the ability to like like and reblog and everything. And I think that's kind of the future. So I do think that there, you can have things that are complementary because so much of the great content and everything is more on this open web. It doesn't have to be like fully embedded in the app.
Starting point is 02:50:35 But that is sort of a technological change. So I would say actually point to X as someplace where I think things are going in the right direction. Although I do agree that's sort of time when links got. really de-boasted and everyone had to do it as like a reply was kind of weird and sucked. So for WordPress publishers, you know, we support so many different types of websites and different types of websites I think might have different motivations. So for example, a popular plugin for WordPress is called WooCommerce. It's the e-commerce plugin.
Starting point is 02:51:02 It actually runs on about 8.9% of all websites in the world are now running this e-commerce plugin. You can think of it like an open-source Shopify. And if you're selling something, a merchant, you don't, you just, just want to sell the product. You might not necessarily care that someone comes to your website to buy it. So some of the new things that are happening in partnership with Open AI and others, where we're allowing products to actually be like browsed and bought inside of the LLM are pretty exciting. I also think that the incentives of these open source chat bots in particular are very complimentary to the open web. So for example, like if you're on Amazon, Amazon really wants you to say or eBay or Etsy or something like that.
Starting point is 02:51:42 They want you to stay in their marketplace on their system. But when you think of how Google works and sort of the growth of Google and the open web, they have their search pages, but they also would link out. And that was the whole part of their business model and how they grew. We're seeing that with the chatbots as well. And in fact, something I talked about a little bit earlier is that the traffic from bots, both from them crawling but also user-initiated actions is exploding and has already surpassed sort of human traffic, and it'll be interesting to see where that goes in the future.
Starting point is 02:52:12 So there's never a better time, I think, to invest in having a domain, but also invest in publishing. And, you know, just like you might have a direct relationship, like, for example, I suppose I could get like a, you know, chat GPT to summarize today's TVPN episode, but it's more exciting to watch it. I think that creator is developing a direct relationship and brand is going to be part of the future as well. Very, very cool. Well, there's so many more things that I want to ask, but I know you're in the midst of your own
Starting point is 02:52:38 presentation. So thank you for tuning in. come back on soon and thank you for having us. The view is spectacular as well. It's a pleasure to me. I love to come down and hang out when I'm in LA next. That'd be so much. Thanks so much. We'll talk to you soon. Great chatting. Have a good rest of your day. Bye. That was the first.com. Exceptional sleep without exception. Fall asleep faster, sleep deeper, wake up energized. That's our sponsor. We had 94 last night, John. I think I smoked to you again.
Starting point is 02:53:10 Lost your phone. Well, we have Jason freed in the stream waiting. Let's bring it in to the TV. There he is. Jason, how are you doing? Good to see you. Good. You?
Starting point is 02:53:21 Congratulations. Massive news today. Break it down for us. What's up? Was there big news today? I missed the news. What was the news? You're just calling out everybody.
Starting point is 02:53:29 Trello. Name and names. He's naming names. A lot of people don't do that. A lot of people say, oh, the competitors, the best in class solutions, the Gartner hype cycle. No, you call them out. You put them on the map.
Starting point is 02:53:40 We had some fun. Yes. So we launched a new product today called Fizzy, which is kind of a fresh take on Kanban, an old idea. Obviously, he's been around for a long time. But we have a different spin on things, different take on things, and felt like it was time to do something new and kind of bring it back to the basics and also add some fun and color and vibrancy, which is missing in the software industry. I feel like people might be colorful in a sense, but the products are very much the same. And so we wanted to do something different. And that was what we did today.
Starting point is 02:54:08 Why new name? Why not, you know, a new, new tab in an existing product? Right. Well, Basecamp, which is our biggest product, has Conbon in it. We call it card table there. But, you know, the thing is is that Basecamp is very popular, but it's, you know, let's say there's 100,000 accounts, right? 100,000 companies use it.
Starting point is 02:54:28 It's a small number in the end. And there's a lot of people who can use something like Fizzy that are not going to use Basecamp. Basecamp is a much bigger system. It's for bigger projects. And there's a lot of small things that people need to do and organize and track. And so building a small standalone thing just feels like it makes more sense, frankly, for this kind of thing. So do you have an idea of like who is the target market, startups, individuals, like you use this to plan your Thanksgiving dinner?
Starting point is 02:54:57 Yeah, I mean, the target market is me and us. Basically, we build things for ourselves. I don't think about who we're making things for because we're making things for us always. And the idea is that, you know, actually, let me just say this. I find the best products in the world are made by the person who's making them for themselves. That's been my experience, like enthusiast products. And then other people find them and other people discover them and you find out that you're like other people or other people are like you and they kind of dig it. And so we're always thinking about ourselves.
Starting point is 02:55:27 I said to someone this morning that I feel like TVPN is that way where sometimes when I'm driving home, I want to watch. I want to watch TVPN, but I'm like, we just made it. I just lived it. I should probably watch something else. So I never, I never watch the show myself. Sometimes you just call me and say, hey, we didn't have a podcast today. We do a podcast on the fly. Let me just talk about tech news more.
Starting point is 02:55:51 I'd love to, I'd love to know about the actual process for building the product. Who was staffed on the team? How many people? What time period? When did you start? Do you have a designer, developer? Is it all just, what's the prompt? I imagine you just use one prompt for this?
Starting point is 02:56:08 One prompt. All it was. All you needed. Yeah. So, you know, what's interesting is we actually also open source this. So this is fully open source. It's a SaaS product and fully open source. So you can run it yourself for free.
Starting point is 02:56:21 Which means you can go into GitHub, actually, and look back at the very first commit about 18 months ago and see everything we did along the way. All the changes we made, all the dead ends, all the starts and stops, exactly who was involved on our team over time. And it's changed. Typically we have two designers, one or two designers on something. Then there's other people who chime in here and there who jump in here and there.
Starting point is 02:56:44 Different programmers jump in different times. But it's fully documented, which is very rare. You'll almost never ever see this in commercial soft, basically almost never, sometimes, but almost never. Especially going back to day one, what ends up happening is you can do this thing where you can basically, on launch day. You can clear the log, basically. And then from that point on, people can see what you're doing. But we opened it up from day one about 18 months ago. So it's actually all in there.
Starting point is 02:57:08 The team sized in total, probably about six people worked on it here and there over 18 months. But for the most part, it's usually two or three people working on something at a time. How do you think about pricing these? Yeah, I feel like as in 37 signals fashion, pricing will be opinionated. So I'm excited to hear how you guys approach this one. You know, we don't really, well, we have a price, but I don't know if it's the right price. Never do. It's 20 bucks a month. Unlimited users, unlimited usage. One price. No chart, no table. No contact us. Just a price tag. Like if you wanted to bought a pair of jeans or peanut butter, it'd be like, how much is it? Talk to the sales rep. They're going to look you up and down. They're going to say, well, how much should this person pay? Right. What watch are you wearing? All the things, right? So it's 20 bucks, but we give you a thousand cards for free. So there's no. time limit on the trial. You get a thousand cards for free. And if you never use a card is like a, you know, like a to-do item or something. Sure. If you never use them up, it's free forever.
Starting point is 02:58:09 Okay. And you can also run it for free if you want to run it yourself. Open source. Yeah. Yeah. So we're basically just serving as a host. If you want to just turn it on, sign up and be going. We'll host it for 20 bucks. Currently, look, this is an introductory price. We could change the price six months from now. If we do, we'll let people lock in where they were. We're not going to change prices on them. But we might raise it. I don't even know what we'll do. But we wanted to pick a number that was fair. The other thing I wanted to do is I wanted to price this more like an accessory. This is not the only tool.
Starting point is 02:58:39 The software industry is interesting because it thinks that whatever it makes, it's the only thing anyone ever needs, right? The thing is people need a lot of different things. And so Fizzy's not going to be the only thing you have. It might be one of the many things you might use. And so we kind of priced it that way. It's like an accessory. 20 bucks a month, kind of a no-brainer, unlimited users, cancel any time, no upfront anything.
Starting point is 02:59:00 and it just feels like that's the right place to start. We'll see it where we end up, but that feels good for now. If I pay you to host it, where is it hosted? China. No, so it's hosted. We have a few different data centers, so it's not the, well, it's in our hardware. Yeah, what I'm getting at is like, it would be easy to just throw this on ABS, but you're the one company that doesn't just do that. That's right.
Starting point is 02:59:27 So we have a data center in Chicago. We have one in Amsterdam. We have one in North Carolina. So we have in a few different spots. And it's all on our hardware and other people's data centers. We rent space and data centers. That said, again, you can also, if you just don't trust us, don't want us to do it. You can put it on your own stuff, including like a simple droplet, like a digital ocean, something.
Starting point is 02:59:49 Whatever you can find that it will host something basic will work for this as well. I mean, you actually can host it in Alibaba Cloud if you want. It's open source. That's the whole point of open source. could put it on. You could. I hope someone does. There's an AI company that recently had a code red. Have you ever had a code red ever once? Not like that. Not like a competitive pressure code red. Let's make sure we kind of focus on this competitor. But we've like screwed up and had to have all hands on deck to fix something. I mean, there was a moment. Did you learn? Did you ever learn the, like, did you ever get overly fixated on a competitor and sort of of like learn that because because there's there's like that's like why see like uh just law right like
Starting point is 03:00:37 don't overly focus on competitors like you're probably not going to die as a company because of your competitor you die because of i think they say like indigestion or something like that right most wounds are self-inflicted yeah exactly but but sometimes you have to to actually have a lesson be fully ingrained you have you have to learn it the hard way i'm curious if that was ever the case. I think there was one time way back when we used to have a product, we still have a new product now called Campfire, but way back in 2006 we launched Campfire,
Starting point is 03:01:11 which was a real-time chat, group chat. And back then we could not shove this down people's throats. Like nobody understood group chat for a business. It just was very, very hard to sell and to move and was a very small product for us. And then Slack came out, and I saw it. I remember, oh, shit, like, yeah, they nailed it. Like we just, yeah.
Starting point is 03:01:31 It was crazy because them nailing it was, it was IRC. Like I used IRC back in the day. And the hashtag channels, like everything, like there were, all the primitives had been like battle tested in IRC. The other thing is Slack doesn't feel like that outside of the world in terms for even from a, I'm sure you have opinions on Slack's like design. But it doesn't even feel that. Like you guys probably could see that and be like, oh, that that's like like the design was opinionated. and, you know, fun. It felt fun. Slack felt fun.
Starting point is 03:02:02 I mean, IRC, of course, is very geeky and whatever. But, yeah, the fundamentals were there. But Slack had a wonderful onboarding experience. It felt fun. They had great integrations. They just kind of, like, totally leapfrogged us in that world. And that was, like, fine. But it did.
Starting point is 03:02:16 It was the first time I felt like I felt that sort of nervousness in my stomach. Now, I didn't feel it against our business because Basecamp is a very different kind of product and it was fine. But it was campfire specifically because I was frustrated. I was trying to figure out how to make it better. And then I saw them come out like, oh, shit. Like, yeah, that, that's how you do it. So that was one time. But I just don't think there's any reason to focus on competitors.
Starting point is 03:02:42 I just don't, you can't control them. You don't know what they're going to do. You don't know if they're going to be around in three months or three years. You don't have the same economics as they do. So it doesn't really make sense. Like, for example, I'll take, hey, our email service, hey.com. we have 40 somewhat thousand paying customers for Hay, right? Which is if we, if you were Gmail, it'd be an absolute abject failure to only have 40,000
Starting point is 03:03:05 paying customers. They're going to shut down. They've been shut down years ago. In seconds, right? But for us, it's a multi-million dollar business because we have 60 people here. So for us, it's a great business. So like, I can't go, well, Gmail is killing us. They're not killing us.
Starting point is 03:03:17 They're doing their thing. We're doing our thing. So I think you've got to, in my opinion, the only person you actually compete with are your own economics. Like, it's not a person, but the only thing you compete with are your own economics. If you can make it work, if you can make it viable, you're fine. If you can't, then you can't. Your costs. You compete with your costs. You competing with your costs. Yeah. Every business needs an AI note taker. What are your opinions on AI note takers? If they join the call, are you admitting them or are you letting them stay? I'm pretty harsh. I always let them sit out in the cold.
Starting point is 03:03:47 I never let them in. We don't, we don't have meetings. We don't, so I don't even, I couldn't even invite one in if I wanted to. We just, we don't, we don't do that. But I have, I will say, I have been in a few calls recently that other people have set up and there's been like an AI transcript and it has been quite handy. It's really pretty impressive when it works really well. Strangely, Apple can't seem to get voicemail transcriptions to work at all. Have you seen? Apple is just struggling with all the, all the basics on transcription, even just talking to your phone and like, whisper works. It works in the chat, GPD app. It works everywhere else. Apple just has not implemented it properly. And it's, and it's not, it's not crazy AI God. Like, it's literally just
Starting point is 03:04:27 take the words that I'm saying and write them down verbatim. And that is a huge, and that's a huge benefit because if you're in a business call, sometimes I just want to search the actual transcript. I don't even need you to summarize it or put action items or go do things for me. Not agentic, none of that. Just actually write down exactly what I said so that when I say, you know, you know, we had, you know, when I say AWS or whatever, I can go search. for when that happened in the transcript. And a lot of companies just haven't been able to implement that.
Starting point is 03:04:56 It's been weird. I agree. I think frankly, that is one of the best use cases. It's not even AI, though. It's just, it's great transcription software. It's very, very handy.
Starting point is 03:05:06 And I think, like, this is the thing, like, it's, it's, transcription software's been around for a long time. It's gotten better and better and better, but it's not like AI, really, you know. I mean, it is very useful. In other ways, it has been AI for 20 years. It's been the original AI in many ways, you know.
Starting point is 03:05:19 It's like, throw a bunch of data at it and try and, estimate what things are. Even like OCR, these similar things, they're just, they're not a GI. They're AI in the sense, they're narrow. It's the recommendation algorithm on YouTube or TikTok or in Netflix or, you know, this specific, you upload a, you take a picture of a receipt. Does it understand the text in there, even if it's kind of a dark photo? Yes, that's specific narrow AI. And that's great. But we need to actually get those things working on our phones. I agree. I agree. We left AI out of busy, by the way.
Starting point is 03:05:52 We made a disconscious effort. We actually had some in for a while and pulled it out and had it back in and pulled it out. I'm just like, I want to remove stupid from this. I don't want to add intelligence. I'm going to remove stupid from the software. So it's just so straightforward that it just works. And you don't even feel like, God, I wish I had AI for this or for that. So V1, no AI.
Starting point is 03:06:11 We'll see what happens down the road. Again, it's open source. So the really interesting thing with Fizzy is that there is a world where you can just actually sit back and do nothing on AI. And if AI is real and valuable to your user, they will get it stuffed down their throats via their OS, via their browser, because Atlas is going to be trying to jump up. Perplexity Comet is going to be trying puppeteering their fizzy. And the rest of the system that they're using,
Starting point is 03:06:38 whether it's their phone or their laptop or their desktop, it's going to bring the AI to bear with computer use. And so you might never have to build it. I think so. In fact, this is actually interesting, really quick. recently OpenAI added a base camp connector to chat GPT. And we didn't even do anything. So they did all the work.
Starting point is 03:06:57 And they just sent us an email saying, hey, we're launching this base camp connector in a few weeks. Like, great. I'm like, this is fantastic. We don't have an MCP server. They just did it. And so I just think more, to your point, I think more and more of that's going to happen, which is it's going to be available in the OS or someone else is going to do it or whatever.
Starting point is 03:07:12 And to spend all this time to build it into the product specifically, I just don't feel like it's the right, the best use of initial, an initial V1 should be focused on the product itself and not the other things that it could possibly do. Again, later on, maybe there's stuff that comes in. Maybe people via the open source version submit some PRs that have some AI stuff. We'll see where it goes, but we didn't need it for V1. Yeah. There's just always a question of where the AI lives. Like, do you need to go and pre-train your own model to answer questions? Or if you set up a good knowledge base, well, you just get sucked into the next pre-trained automatically. And if we can just go to chat GPD and ask about you and you'll be there.
Starting point is 03:07:49 Anyway, Jordan. I want to keep hanging out for an hour, but we do have to wrap the show because we're going to look at a studio. We have one last question from David Sennar? Yeah, one last question from our mutual friend David Sender. Could we get a risk check? What watch are you? What are you rocking on launch day? I might be the only person who coordinates their watch with their software. It's possible. So I'm wearing today, I'm just wearing, I'll take it off because I don't know how to quite hold it up otherwise. This is a vintage Hoyer from 1974, which is a birth birth year watch. Let's see. Hang on. Hang on. Hang on. Hang on. Hang on. Let me see. The focus is hard. But there you go. There you go. There we go. I love the orange.
Starting point is 03:08:33 So it's colorful. Fizzy is colorful. Fizzy's full of color. It's the most colorful watch I own for the most colorful product we've ever made. I knew. I knew you. I knew you. I knew you. I was I literally said, I knew you were going to match. I knew it was going to be intentional. This is so good. It's a little sad. It's a little bit. It's a little bit sad.
Starting point is 03:08:51 It's fun. It's fun. It's joy. This is joy. This is amazing. I don't have like a, what, like a green. Why are you guys wearing a green jacket a few days ago? What was that about?
Starting point is 03:08:59 It was Shopify. Black Friday. We were celebrating commerce online. And so we wore. Oh, just green for money? Solid green suit. No, it's the Shopify's signature color is green. Oh.
Starting point is 03:09:10 I didn't even know that. Yeah. Shopify's green. Yeah. Yeah. Okay. It is a little confusing because we use a dark green in our brand theme. And so it actually paired up pretty nicely. We also have yellow suits for when we, for when there's big ramp news. We will wear solid yellow suits. Yeah, you've probably seen that. Yeah, you've probably seen. Those are fun. I've seen that. Hard to, hard to miss. Uh, well, Jason, uh, open invite to the studio. We'd love to hang out for like a full hour. Everybody. Everybody. Everybody, uh, let's do it sometime. I love to. I think I got an email about about that. So we'll figure that out. Amazing. Appreciate it. All right. Thanks for you. to the whole team on the launch. Talk to you soon.
Starting point is 03:09:44 Talk to you soon. Thank you. Talk to you. See you. Bye. Bye. Get Bezell.com. Shop over 26,500 luxury watches that you're not going to believe it, but this
Starting point is 03:09:51 is actually the next ad read up. Fully authentic in-house by Bezell's team of experts. And we got to close out the show. So I'm going to tell you about Wander.com. Book of Wander with inspiring views. Hotel Grated many of these dream beds, top tier cleaning 24-7 concierge service. There are so many more posts that I want to get to. But there's a lot.
Starting point is 03:10:09 There's a new arena mag out. You got to go to arena mag. it out. We are featured in this arena mag issue, 0-06, the three-martini lunch. We had Julia on the show, of course, to talk about it. But now it's, it's in print. There's a lot else going on. And we'll be back tomorrow. Sorry to cut it off. Thank goodness. I would be in a very bad place where we weren't podcasting tomorrow. But fortunately we are, so we'll see you tomorrow. Leave us five stars on Apple Podcasts and Spotify. Thank you for hanging out. Goodbye. Have a great evening.

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