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

Summary

TBPN Podcast Summary

Episode: 🔴 CODE RED 🔴, AWS CEO Joins, Tae Kim Tells All

Date: December 2, 2025
Hosts: John Coogan & Jordi Hays
Notable Guests: Matt Garman (AWS CEO), Tae Kim (author, The Nvidia Way), Tarik (Kalshi CEO), Matt Mullenweg (Automattic/WordPress), Jason Fried (37 Signals)

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Episode Overview

This exhilarating episode covers seismic shifts in technology and finance, with key insights from industry leaders. The hosts open with a detailed profile of Rheinmetall’s explosive growth amidst war-driven defense spending, then seamlessly weave in expert interviews examining AI industry “code red” moments (notably at OpenAI), AWS’s AI product plays, the ongoing GPU/TPU infrastructure wars, the future of prediction markets, and product launches in software. The episode balances rigorous industry analysis with humor and memorable moments, all while charting the latest in Silicon Valley competition, business models, and cultural anecdotes.

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Key Segments & Timestamps

1. Rheinmetall’s Rise in the Defense Industry [00:19–14:32]

• Hosts give a whirlwind 3-act history of Rheinmetall, now Europe’s fastest-growing defense company.
• Act 1: Legacy arms maker, forced into non-military goods in post-war periods.
• Act 2: Re-armament and key supplier as Europe, post-Ukraine invasion, massively ramps defense spending.
• Act 3: The role of CEO Armin Papperger—dubbed “the white-haired Goliath”—in transforming Rheinmetall into a global powerhouse despite facing an assassination plot.
• Notable stats: Market cap zoomed from €5B three years ago to $80B today; guiding for $58B in sales, 20% margin by 2030.
• Quote:

  "Rheinmetall's stock is up 15x since Russia's full-scale invasion of Ukraine in 2022, giving it a market cap of 80 billion, roughly on par with US rivals." —Ryan [10:52]

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2. E-commerce & Black Friday/Cyber Monday Insights [12:14–13:43]

• Discussion with friends at Ridge on the boom of BFCM sales, despite a Cyber Monday Shopify admin outage.
• Harley Finkelstein’s Shopify sales stats: $14.6B in 2025, up from $6.3B in 2021.
• Consumer spending and confidence appear robust despite economic volatility.

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3. Anduril and Defense Tech Philosophy [14:39–19:15]

• Hosts break down Wall Street Journal coverage of Anduril’s fail-fast culture; Palmer Luckey’s defense of aggressive, venture-style R&D over “bureaucratic BS.”
• Quote:

  "If you plan to pass every development test, you'll move slowly and expensively. It's optimal to fail many dev tests." —Blake Scholl [18:01]

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4. “Code Red” at OpenAI – Cultural Impact and Leaks [20:26–34:43]

• Gavin Baker’s take: rapid trajectory changes, industry on “Code Red” after Gemini 3’s launch.
• Sam Altman’s internal “code red” leak, with hosts riffing on metaphors (“Baja Blast Gemini,” hospital color codes) and why leaks occur.
• Quote:

  "If you're a CEO under scrutiny, never say 'Code Red'—say 'lock in,' brothers. Lock in." —Ryan [21:39]

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5. Model Wars: OpenAI vs Gemini vs Claude [34:43–51:49]

• Deep dive on ChatGPT traffic woes post-Gemini, benchmarking arms race, and questions of whether OpenAI’s business model (free/ads vs subscriptions) is sustainable.
• Interview highlights from Mark Chen (OpenAI) about reasoning, scaling, and competitiveness.

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6. AI Infrastructure: Nvidia, TPUs, and AWS [54:41–115:01]

Ben Thompson's Framework [54:41–90:05]

• Stratechery’s “empire strikes back” analogy: Google’s Gemini 3 seen as threat to Nvidia/GPT dominance; importance of user aggregation for moats.
• Quote:

  “The more unique buyers of your product you have, the stronger your moat, because it's hard to... you have to convince each one of them.” —Ben Thompson (quoted by hosts) [76:35]

• Google’s competitive edge: data, infra, ad networks; debate over who can reach ad-supported LLM scale first.

AWS’s Roadmap – Interview with Matt Garman (AWS CEO) [102:40–114:41]

• AWS unveils “frontier agents” for software development/ops, Nova 2 proprietary model, and new Trainium 3 chip.
• Matt Garman highlights “mid-training” (customers bring their data into pretraining), open-source SDK for Trainium, and massive infrastructure growth (3.8 GW new capacity added).
• Quote:

  "As we're scaling incredibly rapidly... we have more demand than we have supply today for AI." —Matt Garman [114:13]

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7. Investing in Infrastructure: Tae Kim on Nvidia's Moat [115:02–142:43]

• Tae Kim (Author, The Nvidia Way, Barron's): Nvidia’s “winning culture,” directness, and internal meritocracy.
• Refutes Nvidia doom narratives, arguing TPUs’ splash is overblown: “This has been happening this entire 10x move up… The media loves to latch onto the latest, greatest thing to worry about.”
• Attributes Blackwell’s expected success to maturity, customer trust, software stack, and developer loyalty to CUDA.
• China export policy: "Best to sell slightly-outdated chips; $50B/year funds Nvidia’s R&D well."
• Quote:

  "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." —Tae Kim [128:42]

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8. Prediction Markets Go Mainstream – Interview with Tarik (Kalshi CEO) [143:11–162:05]

• Kalshi closes a $1B Series E at $11B valuation; prediction markets on everything are going mainstream.
• State-regulation vs federal for new financial products, handling legal challenges, insider trading risks.
• Quote:

  "Prediction markets have gone mainstream. Every inch of evidence is pointing towards that." —Tarik [144:45]

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9. State of the Word: Matt Mullenweg (Automattic/WordPress) [162:07–172:55]

• Word of the year: “Freedom.” Open source is a digital Bill of Rights; WordPress 6.9 release live.
• Beeper's progress, challenges integrating with iMessage, and the shifting landscape of links/traffic as AI bots crawl/summarize web content.
• Quote:

  "As technology starts to influence more and more of our lives... freedoms that are embedded in an open source license—sort of like a Bill of Rights for software—give you inalienable rights that no company or person can take away." —Matt Mullenweg [164:52]

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10. Product Launch: Jason Fried Unveils “Fizzy” [173:18–189:44]

• New Kanban tool launches, built for “ourselves,” open source from day one; $20/mo flat pricing.
• On competition: focus on own economics, not the competition; “most wounds are self-inflicted.”
• Memorable Moment: Fried coordinates watch to match software color for launch.
• Quote:

  "The best products in the world are made by the person who's making them for themselves." —Jason Fried [175:02]

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Notable Quotes & Memorable Moments

• On AI Business Models:

  "Launch the Ads product. Launch the Ads product. Get it out. Come on!" —Ryan, channeling Ben Thompson [77:51]

• On Organizational “Code Red”:

  "Never say 'code red'—say 'lock in, brothers. Lock in.'” —Ryan [21:39]
  “I'm maybe the only person that's really excited about ads in ChatGPT.” —Ryan [48:19]

• On Nvidia’s Resilience:

  "The number one thing, it's not price. It's like, it better work." —Tae Kim [128:54]

• On Market Structure:

  "The only person you actually compete with are your own economics." —Jason Fried [183:09]

• Memorable banter:

  • Joke about “Baja Blasting Gemini” (Mountain Dew reference) as the next motivational meme for OpenAI.
  • Jason Fried’s “wrist check” — launching Fizzy while wearing a 1974 orange Heuer watch to match.

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Thematic Takeaways

• Moats and Aggregation: Owning end users (800M+ for ChatGPT) delivers lasting tech moats, regardless of “best model” churn or infra advances.
• AI/Defense/Economics Collide: Whether artillery shells or consumer LLMs, swift adaptation and operational excellence remain the winning formula.
• Code Red and Cultural Signals: Language used at the top of an org (Code Red vs “lock in”) deeply affects internal and external perceptions; leaks and vibe shifts are both cause and symptom of disruption.
• Meta-Competition: Whether cloud chips, open source, or productivity SaaS, the true competition is almost always internal efficiency, not the nearest rival.

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For Further Listening

This episode is a masterclass in the interplay of tech innovation, business models, and company culture at scale. Don't miss Tae Kim's breakdown of Nvidia’s moat, Matt Garman's articulation of AWS's next AI phase, and Jason Fried’s candid product-building philosophy.

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[End of Summary]

Transcript

[John]

You're watching TVPN.

[Ryan]

Today is Tuesday, December 2, 2025. We are live from the TVPN Ultradome. The temple of technology. The fortress.

[John]

Fortress finance, the capital of capital.

[Ryan]

Ramp.com baby. Time is money save. Both easy to use. Corporate cards, bill pay, accounting, whole lot more all in one place.

[John]

That's right.

[Ryan]

Why is no one talking about Armin Popperger? He's the CEO of Rheinmetall. And they've been on an absolute tear. We're, we're of course going to get to code red. We're going to talk about OpenAI, but we talk about OpenAI 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 COVID of the business section of the Wall Street Journal. When I think high growth defense companies, I usually think Anduril or Saranic or there's so many other companies that are growing very fast in defense tech. Ryan Matal's been on an absolute tear. They're now basically the same size as Lockheed Martin and General Dynamics and it was a small company just a few years ago. So Rheinbutall, they make, you can see the gun that they make in that picture. They make big 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, to $80 billion in market cap. We gotta ring the gong. We gotta warm up the gong. 80 billion market cap. They've been on a tear, but they had, and there's been like three, there's 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 3 Act story about Rayn Matal. 3 Act Gemini, Google's most intelligent model yet. State of the art reasoning, next level vibe coding and deep multimodal understanding. So first they had a head start. This company they actually started 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. They, 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, World War I breaks out. But then after the war, they got a pivot. They got a pivot because the Treaty of Versailles forces them to switch to non military products. They say, hey, cars, make some trains. They get fixated on trains and also typewriters.

[John]

Not the first, not the first dudes.

[Ryan]

To get fixated on trains.

[John]

Happens to the best of it.

[Ryan]

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, it's 1935 around. There they are, they're starting to get back into weapons and ammo production. They can't stay away. Oh, who are they rearming? The Wehrmacht 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 air raids. They need to rebuild the company from scratch. So after the second war, they get banned from making weapons again until 1950.

[John]

Keeps happening.

[Ryan]

And so they have to go back to making typewriters. They keep getting relegated to typewriter like you guys. No more guns.

[John]

That's enough.

[Ryan]

You have to make some typewriters. And so they get back into defense tech in the 50s, 60s. The German armed forces gets reestablished in 1956. And by 1979, Rheinmetall 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 and 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. So Russia invaded Ukraine on February 24, 2022, about three years ago. Rheinmetall was around 5.5 billion market cap then. And three days later, Olaf Scholz, the Chancellor of Germany, Germany gives what's known as the Zeitenwald Zeitenwende speech, which is literally translates to turning point. So he says, this is a turning point. Europe has been invaded. We, we now have a foreign army on European soil. Even though Ukraine's not part of NATO, it feels like Russia is expanding. If they just keep going in the same direction, they're eventually gonna be in our hometown. So we gotta do something about it. And what does he propose? He doesn't just say, hey, this is a big deal. He says, no, we're actually going to invest $100 billion 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 GD on defense. But basically it's this major turning point where Europe goes from spending, you know, sustainment levels, okay, we're going to spend this much every year to 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 Rheinmetall does. And so revenue Helsing is sort of.

[John]

Born out of that era.

[Ryan]

Helsing is like the newer version of Rheinmetall. Rheinmetall is like the old, you know, roll up. It's been around for over 100 years. Helsing, I think, was starting.

[John]

Yeah, Helsing was 2021 was most recently in the news because they raised, I think $600 million from Daniel.

[Ryan]

Right? Yeah.

[John]

Sparked controversy, of course. A lot of people in the Spotify world, the world of music, just think that defense tech is default.

[Ryan]

Oh, I didn't realize that there was actually backlash.

[John]

Totally.

[Ryan]

I didn't see that.

[John]

You know, if you're an artist and you, you know, believe in peace at all costs, you're going to probably be against that. But.

[Ryan]

Well, it depends. Maybe if you're, you know, pod or you're, you're, you're, you're some other, you know, musician that was played during the war on terror, you could be very pro. The Helsing investment just depends. But yes, I understand overall. So revenue's 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 SAL of $58 billion and an operating margin of more than 20% by 2030. So they have like almost AI growth level numbers of everything. It feels very similar where there's a, 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's now sort of a megatrend and they are in position to capture a ton of value as long as they can execute the. The big question is what winds up happening. But the third leg of the stool, the third important piece in this story is the current CEO, the man no one is talking about until today, Armin Papperger. He's been called a white haired Goliath. I love that cnn.

[John]

Can we pull that up a picture?

[Ryan]

Just randomly threw that in. Pop it through.

[John]

There he is.

[Ryan]

There's some other photos. And last year he was targeted in an assassination plot by the Russians.

[John]

What?

[Ryan]

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. There were a number of different attacks, but fortunately American intelligence discovered the plot and informed Germany in time to stop the attack. And now the white haired Goliath is.

[John]

Ryan in the chat says this feels like a pa. Hey Dad. I can assure you it's not. John woke up this morning, we were at the gym and he's like why is no one talking about Rheinmetall? And decided to write about it in the, in the, in the newsletter today.

[Tae Kim]

That's funny.

[Ryan]

No, he's on the COVID of the Wall Street Journal. And so, so, so they stopped the attack. And so Russia clearly sees Armin Pappinger Papager as a critic as critical to the European defense ecosystem. But separately there is 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, Rheinmetall may or may not be able to absorb as much of the demand as they're planning to. They have lots of integration to do between all their different acquisitions. And also with a potential end to the Ukraine war.

[John]

Yeah, it feels like the stock would just immediately trade down on news of a peace deal.

[Ryan]

And it has even on rumors of a peace deal. Yeah, exactly.

[John]

Yeah. It's down 15% over the last month.

[Ryan]

Yeah. But they're scaling up. In the Wall Street Journal it says earlier this year Armin Paper opened a new factory that will allow his company to produce more of an essential caliber of artillery shell than the entire US defense industry combined. Surrounded that day by dignitaries including the head of the North Atlantic Treaty Organization, NATO, the Rheinmetall CEO is riding a wave post Cold War military spending that is reshaping the global arms trade. Rheinmetall 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 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, oh, 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, 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.dev code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster. Rheinmetall's stock is up 15x since Russia's full scale invasion of Ukraine in 2022, giving it a market cap of 80 billion, roughly on par with US rivals. And when he took over the job, he started this job in 2013. So he's been CEO of Ryan Matal for 12 years. The company was 1.6 billion. Overnight success. Overnight success, Right. Sort of like what happened Lisa Su, 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. But back to Ryan Matal this month, Ryan Matal set out ambitions to quintuple sales by the end of the decade to the equivalent of roughly 58 billion billion. Pat Berger, reflecting on his long tenure at the company, told investors that seeing such figures was like a wonderworld. 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?

[John]

Kind of get the gist.

[Ryan]

I get the gist. He's happy. I'm happy for him. Good job.

[John]

We had a buddy of ours who actually name him. I was going to keep him anonymous, but it's just too funny.

[Ryan]

Somebody's proposing 2.6 is proposing the TBPNX Standard Oil X Rheinmetall collab.

[John]

We said we were talking about, we were texting with Sean Frank and Connor McDonnell at the Ridge yesterday about how their Black Friday 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 incredible reaction to a successful Black Friday.

[Ryan]

I'm so glad it went well for them. I mean, the. The Wall Street Journal did report that on a busy Cyber Monday, outage at Shopify halts transactions. Shopify experienced an outage on Cyber Monday that interrupted transactions for some merchants, but it sounded like it was not affected.

[John]

Well, so it was that. The. The real issue is the admin panel went down.

[Ryan]

Okay.

[John]

A lot of people out because you're not able to log in and, like, see what's happening.

[Ryan]

Yeah, of course. And also, like, even if. Even if everything's working as standard as expected, like, that's the day you're just refreshing the admin panel all day because you're just like, how much money am I making? Like, this is really critical. Right?

[John]

Yeah. So, yeah, there were some reports that a handful of merchants had actually had features on their site go down, but I didn't see any.

[Ryan]

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, while it does seem like Cyber Monday and Black Friday, Black Friday, Cyber Monday broadly just went very well. Like, it just. It just seems like consumer confidence was up, revenue was up, spending was up.

[John]

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. 2022 was 7 1/2 billion. 2023 was 9.3 billion. 2024, 11 1/2 billion, and then 2025, 14.6 billion. So combination of execution at the. At the company level and execution at the Shopify level, and then obviously the market plays a big role as well.

[Ryan]

Yeah, it really did seem like. 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 is there an AI bubble? And how big of a bubble? What will happen?

[John]

Somewhat of a CO going on.

[Ryan]

It has been a code in the world.

[John]

Before we jump into that story.

[Ryan]

Profound. Get your brand mentioned in ChatGPT. Reach millions of consumers who use AI to discover new products and brands.

[John]

I was going to say kind of the Anduril was covered in the Wall Street Journal. The Wall Street Journal has been been doing Quite a lot of defense tech coverage. Anduril 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 and D. Anduril has a more traditional like venture style model where they raise VC dollars, they spend that money to test and develop products. And so they gave a quote that was like we do fail a lot, but we do fail a lot. The extra context that was necessary was that that's not happening on the, on the taxpayers dime. And it's part of their 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 OpenAI in the last 24 hours where sounds like an internal, internal meeting was leaked. We are wondering like what is it we can.

[Ryan]

Yeah, let's, let's actually, let's actually read a little bit more on, on the Wall Street Journal anduril thing. Cause 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. So Wall Street Journal came out with this story. We do fail 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. I think it's actually a very.

[John]

It's their next campaign.

[Ryan]

I think it's a very key cultural. I think it's like a don't work at Anduril type moment. It makes a ton of sense in terms of like the culture of like fail fast. This is, this is not new in Silicon Valley and yet it's still being reframed as new. I'm surprised that there's like alpha here still. But let's see. Palmer Lucky says the valid reasons for slowness are bureaucratic BS and cowardly executives who cater to snide analysts 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 heck. 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.

[John]

Almost getting close to a fire every single weekday.

[Ryan]

Yeah. They obtain satellite imagery that reveals the damage to the grass on the weapons test range. The other. The other examples of this story are similarly obscure.

[John]

John, you're telling me that the grass was damaged at the explosives testing ground.

[Matt Mullenweg]

Yeah.

[John]

You're telling me something. You're telling me there was an explosion at the weapons testing facility.

[Ryan]

Yes. Wild. The other examples in this story are similarly silly, absurd. Oh, no. An engine sucked in a piece of fod. Stop the presses. Autonomous boat behaves exactly as designed and stops moving when it receives a faulty command and are all hit by a 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 mainly. There's a good post here from Blake Shoal, 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 headline suggests a hatchet job, not an honest report on an attempt to do things differently and better. Yeah, I still just think we do fail a lot. Is just. It's so ripe for a billboard campaign, a T shirt, a hat or something. Because if you like, the whole thing with Silicon Valley is that you should fail 99 times and succeed once. Because if you succeed once and fail 99 times, it's a million times better. It's infinitely better than zero failures, zero successes. You will take a ton of failure for one success. And that's the whole ethos.

[John]

That's the American ethos.

[Ryan]

Yeah, it's the American ethos. It's the technology ethos. There's a lot there. Anyway, back to. Oh, actually, we can wrap up with. You can go read the Wall Street Journal report on Armin Pappager. Pappager, if you want. We got to figure out how to pronounce this name. He did have one fun line in here, which was, what did he say? He said something like he said, referring to. So now he's basically the same value as Lockheed Martin in General Dynamics. And he said on the US companies, he said, they come to me 10 years ago. It was a different story. And so he's just flexing the fact that he's now big Enough that he requires. You can go visit him because he's.

[John]

Like, made it always a good sign.

[Ryan]

Yeah, he's taking a little victory lap and there's some other funny things in here, but we can go and 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. So let's head over to red alert territory.

[John]

Gavin Baker, responding to the reporting, says October 1.4 trillion in spending commitments. November rough vibes and December Code Red. Life comes at you fast. It certainly has felt. It certainly has felt fast ever since that fateful podcast.

[Ryan]

Yes, that was a crazy turning point.

[John]

Although there was plenty of conversation prior to that around what the trajectory of OpenAI would actually look like.

[Ryan]

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. Says debt obligations come at you fast. And it's like, that's not really what's happening here. The Code Red leak from the information reported, it was clearly like some sort of all hands that Sam Altman was holding a town hall with the rest of the OpenAI team. And he's kind of just saying, like, lock in. That's what he should have said. Never say Code Red. You gotta say lock in, brothers. Lock in.

[John]

Don't say rough vibes.

[Ryan]

Don't say rough vibes.

[John]

Code Red.

[Ryan]

Say lock in. Say, we're taking that hill. We're storming their fortress. We will grind Google Gemini team into paste and we will crush our enemies. We will see them driven.

[John]

Before hospitals learned this lesson.

[Ryan]

Yes.

[John]

They used to say Code Red.

[Ryan]

Yes.

[John]

That meant there was a fire in the hospital and that you would probably want to figure out a way to get out.

[Ryan]

Yes.

[John]

They started. Is it Code Blue?

[Ryan]

Yeah. Now they will say Code Blue. So if you hear Code Blue in a hospital, yell Code Red. You need to be worried. You need to worry. But 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. So he's saying it's not that bad.

[John]

But don't you think they just retired? I think they just retired.

[Ryan]

Yeah. So he's saying I'm using retired phrase. I'm not saying Code Blue. If I was saying code, you could.

[John]

Have used Code Brown, which is a hazardous spill.

[Ryan]

Okay.

[John]

Which Gemini 3 spilled on the timeline. It's very hazardous. We Got a code Brown.

[Ryan]

Yeah, we got a code Brown. That's a crazy. Is that real or is that some, like, meme? Generous.

[John]

Ridiculous. I'm reading the hospital emergency codes.

[Jason Freed]

Okay.

[Ryan]

Okay. Well, anyway, let me tell you about Restream One livestream. 30 plus destinations. If you want to multi stream, go to restream.com Cha Ching. No, I think if you're a CEO who's under incredible scrutiny, like you're Sam Altman 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. What happened?

[John]

Yeah. So to give people context, they're 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, on the team. Just over and over and over, relentless. Like email, cell phone, Instagram, DM, LinkedIn. Just like constantly, constantly, constantly flooding, hoping that at some point this person just says, like, fine, like I'll the name.

[Ryan]

With you beat reporter comes from them trying to beat you down. That's the whole point.

[John]

Is that true?

[Ryan]

That's where it comes from. No way.

[John]

Are you messing with me?

[Matt Mullenweg]

Yeah.

[John]

Okay, okay, okay.

[Ryan]

I have no idea, but I like the idea of it. It's like they just try and beat down new employees. They try and beat you down. I got a beat reporter on my team. I was like, on my tail. Yeah, yeah. No.

[John]

I mean, it's certainly what it's become.

[Ryan]

There is a little bit of it. No, no, I think there's be reporting. There's gumshoe reporting. Gumshoe 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. 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 drumbeat. Like every day you report on the same thing. And so it's about consistency. It's not. What are you laughing at now, Ryan.

[John]

In the chat, if you work at an AI 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. I bought us a bunch of Code Red.

[Ryan]

Yes.

[John]

I want you all drinking it every day. It's time to really focus.

[Ryan]

Yes.

[John]

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.

[Ryan]

Just leave. Just go make 10 times as much money in a different lab. If you don't like your employer, just bounce and make more money. Why are you sitting there leaking and just dragging your company down? Don't you have stock options?

[John]

Yeah. I'm so confused.

[Ryan]

It's a molecule, 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 OpenAI on the timeline, which we should get to from none other than Blake Robbins. Blake says OpenAI is operating on a different level. Play that sound cue, Jordy. 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.

[John]

This was on October 6. Sora was, I think number one in the charts at that point.

[Ryan]

Yes.

[John]

It's now 21.

[Ryan]

Yes.

[John]

Pulse was got some excitement early on, but I think people are a little bit not feeling like as excited.

[Ryan]

Yep.

[John]

Atlas launched and then it's hard to really gauge what, what adoption has been like. I. I know some people that love it.

[Ryan]

So. Eric Suefert on October 6 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, social network operator, a commerce engine, a hardware company? Because it's hard to do all of that well. And then Eric goes back and finds his old.

[John]

And they're trying to. They're still like very much care about competing in code gen. Right. 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 of how are you going to support the 1.4 trillion of commitments was we're automating science. And we're making and we're making and we're making like consumer electronics. And the reason that didn't. To me, that was kind of like a concerning answer because Google has been doing those things for years.

[Ryan]

Yeah. But they've earned the right because they.

[John]

Have 25 years funding it with massive cash flow.

[Ryan]

Yeah. Hundreds of billions of dollars in revenue and so much cash just to go around. And it's Always been this academic lab and this sort of 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.

[John]

They were funding that with cash. So they were funding these initiatives with cash flow.

[Ryan]

I believe so.

[John]

And even though they've been doing it for this long, it's not like Sundar is going out there and saying, guys, we're actually going to do it. We're going to do an extra hundred billion next year because we're automating science and we're, we're doing this new consumer electronic device.

[Ryan]

Yeah. No, no, it is crazy. Let's continue. First, let me tell you about Privy. Privy makes it easy to build on crypto rails, securely, spin up white label wallets, sign transactions, integrate on chain infrastructure all through one simple API. I have a plan 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. What do you think?

[Tyler]

I think people are underestimating the possibility that Code Red, it was actually red was past tense of read. Oh, they're talking about the code that was read by the model.

[Ryan]

Oh, yes.

[Tyler]

What was the code read in this scenario?

[Ryan]

It might have been.

[Tyler]

You were talking about the next agent.

[Ryan]

That was doing Code Chen. 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. 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 he's extremely competitive. He doesn't want to lose. He's going all out right now. And that one of the ways he's dealt with the talon wars is to just go to everyone on his team and say, hey, I'm not going to match dollar for dollar with meta. If you want to make ten times as much money, yeah, you're free to leave. You can just get. 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 better and we will be bigger. And he also clarified, interestingly, that although there was a big raid and a lot of people from OpenAI did go to Meta, he was saying like, there's been, there's been. He was basically like, there's a lot of poaching that's happened from OpenAI generally, like whenever someone starts a new lab, they always go to OpenAI. They're like, we need at least one OpenAI guy to know how they do it. Right. It makes, 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 the loyal lieutenants. Yeah, yeah, his, his, his lieutenant stuck around. It was sort of interesting. But he did say that he also, he sort of echoed Sholto and said that he believes that pre training, there's still low hanging fruit there, that OpenAI will be doing new pre training runs, that they have seen that scaling is holding, that there's no platform.

[John]

He also said they have models internally that outperform Gemini on benchmarks.

[Ryan]

Yes.

[John]

And obviously he caveated that by saying benchmarks aren't the only thing that matter. So I do think, I mean, it's worth sharing.

[Ryan]

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 OpenAI's research chief, Mark Chen. 90, is it?

[Tae Kim]

Yeah, yeah. So to speak to Gemini 3 specifically, it's a pretty good model. And I think one thing we do is try to build consensus. The benchmarks only tell you so much. And just looking purely at the benchmarks, 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 and.

[Matt Mullenweg]

I.

[Tae Kim]

Think everyone probes the models in their own way. There is this math problem I like to give the models.

[Ryan]

This is funny.

[Tae Kim]

I think so far none of them has quite cracked it. Even the thinking models just tell us. So. Yeah, I'll wait for that.

[Ryan]

Is this like a secret math problem?

[Tae Kim]

Oh, no, no, no. Well, if I announce it here, maybe it gets trained on it's going to get so saturated to speak to Gemini Theory specifically. It's a pretty good model and I.

[Ryan]

Think, I think this is looping. One thing we. Yeah, loop having a secret math problem that you give every model to assess. It is pretty elite. I keep reflecting on. So let's read what Prins is saying here. So, new interview with Mark Chen from OpenAI. Ashley Vance, the interviewer has apparently been spending a lot of time at OpenAI, including sitting in on meetings. He seems to be writing a book and he seems to think that OpenAI 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, 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 $100 trillion, you can give it one more IQ point. It's like, yeah, that would be an example of scaling holding. But no one's going to make that trade off. No one is going to be like, yeah, I'm down totally spend the 100 trillion.

[John]

Okay, so what Sam said in the internal Slack memo.

[Ryan]

It was a Slack memo.

[John]

Yeah.

[Ryan]

Okay.

[John]

Because he was directing more employees to focus on improving features of ChatGPT, such as personalizing the chatbot 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, have been very loyal to 4.0. Altman also said this is in the Informations piece.

[Ryan]

Did he mention Baja Blast?

[John]

He hasn't specifically said Baja Blast, but I think he's kind of alluding to it.

[Ryan]

He's warming up to talking about Baja Blast.

[John]

Other key priorities covered by the code red include ImageGen, the image generating AI that allows users to create variety of photos. You had included in your newsletter last week that you've been going over to Gemini specifically for Nano Banana.

[Ryan]

Yes.

[John]

So I wonder if this is a broader trend.

[Ryan]

Does this actually matter? I think it does. I think that the image generation functionality, like fundamentally what LLMs are doing, 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 a crazy thing but there is a world where they say hey, yeah, we're not going to focus on that. We're actually going to just, just vend in Nano Banana. But we are going to be the front door, the aggregator and we're just going to be.

[John]

The actual Runway in the background, right?

[Ryan]

Yeah, yeah, yeah. Hand it 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 claim for a While that potentially OpenAI has a strong hold on the consumer market to the point where if they swapped out the underlying model they would still accrue 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.

[Tyler]

Mean I think that especially makes sense in the context of images and video because they're just so expensive.

[Ryan]

Yeah.

[Tyler]

Like I think a Nano Banana Pro image is like, I think it's like 10 cents.

[Ryan]

No way.

[Tyler]

It's really. Or okay, that might be per like a thousand or something.

[Ryan]

But it's still, it's still.

[Tyler]

They're really expensive. Videos are even more expensive. Videos are like really, really expensive.

[Ryan]

Oh.

[Tyler]

So I think it makes more sense in that scenario because you would imagine that it's just so expensive to vend it yourself. It's like you're spending so much resources on that.

[John]

Yeah.

[Ryan]

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. AI is coming for you. Prepare accordingly. Have you seen this Jordy?

[John]

I did see that.

[Ryan]

You did see this one?

[John]

Yeah.

[Ryan]

Did you look at the image closely?

[John]

No.

[Ryan]

Okay. Is it, it's one of the funniest images I've ever seen. So basically this image, it has a.

[John]

Walkway with like a 40 foot drop to the ground.

[Ryan]

I mean it's not quite that bad, but it's close.

[John]

Yeah, I just, I just, I didn't. I don't buy the, the theory that architects are cooked just because you can generate like a floor plan or designs for a home. Just because the actual process is.

[Matt Mullenweg]

You'Re.

[John]

Dealing with a city, basically. Right. And you're trying to get things permitted.

[Ryan]

Yeah.

[John]

It's not like the problem is just making pretty designs. Right.

[Ryan]

It's the classic. Let me see. I'm trying to put this in the chat. It's the classic. Like, 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 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.

[John]

Like, looks like a floor plan.

[Ryan]

It looks like a floor plan. It looks amazing. Like, it looks like. Okay, yeah, that's like, all the lines are straight. 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 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, the mud room. So first off, there's this mud room, mudroom and laundry with two bathtubs in it. Scroll up to the right. Okay, yeah, right there. So why do you have two bathtubs next to your coat closet?

[John]

Right in the mud room.

[Ryan]

In the mud room. And also, like, you can't go. Normally you come out of a garage, you go straight into the mudroom. But here you have to go into the main area, which is the gallery hall. And then you go from there into there. And so scroll to the left a little bit so we can see the.

[John]

What is the coat?

[Ryan]

So then you go to the. There's a powder room and then there's the coat.

[John]

Batu toilet.

[Ryan]

And why there are two toilets next to each other? Remember we were touring that facility and it had two bathrooms right next to each other with no line next to it?

[John]

Yeah, yeah, yeah. We were in the machine in the crazy office that had the machine. One of the bathrooms just had. It was like meant to be a private bathroom and it just had two toilets there. We were like, why the two toilets?

[Ryan]

Yeah, so it's like. So you come in through your main foyer, 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 go through this corridor to get to the rest. And so this master suite has three toilets. But then it gets better, dude, it gets better. So go over to the top right hand side because this is 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 with two sinks. Wait, three sinks, three sinks, no toilets. And then there's another bathroom and then there's a third with a third bathroom with a toilet. This is with ZFI sinks.

[Tarik]

This is.

[John]

You might not like it, John, but this is, this is architecture at its best.

[Ryan]

You have five sinks next to your two bedrooms which. And then also bedroom two doesn't have a, doesn't have a bed anything.

[John]

It opens into the gourmet kitchen.

[Ryan]

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 where there's 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 Trevor.

[John]

In the chat says bathroom scaling mods.

[Ryan]

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 the doors and they're like present.

[John]

What did the comments say? Did the comments say like, hey buddy, why'd you put, you know, three sinks in that one bathroom?

[Ryan]

Well, everyone gets that. It's a joke.

[John]

Oh, it was meant to be a joke.

[Ryan]

Yeah, yeah, yeah.

[John]

Okay.

[Ryan]

Yeah, yeah. This John guy like totally thinks it's so funny and is just like joking around. 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 plan, no kitchen, toilet. Then people just joking about all the different stuff. And I don't know, I mean, is AI going to help with architectural design? Of course. Is Nano Banana going to randomly one shot the perfect floor plan? No. Also no. But of course there's stuff. That's the funniest image it's so funny. So funny. Anyway, I was actually dying laughing at this thing.

[John]

Okay, back to the Code Red Vanta.

[Ryan]

Automate compliance and security AI that powers everything from evidence collection to continuous monitoring to security reviews and vendor risk.

[John]

DD DAS is adding fuel to the fire. He says this is why OpenAI is in code red. In the two weeks since the Gemini launch, ChatGPT unique daily active users, a seven day average are down 6%. He is sharing to be clear web traffic data.

[Ryan]

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, but even then 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? I would hope that I don't have that much spyware on my a Chrome browser that knows exactly where I am. Maybe it does, but I would think that OpenAI and Gemini and Google would be like, yeah, we're not letting you put a pixel on our site.

[John]

How is it, you know, do we.

[Ryan]

Should have someone from similar web on the show explain it to us?

[John]

Tell us your sources.

[Ryan]

Yeah, tell us everything. 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.

[John]

But I wonder if any of the Chrome extensions sell your data. I'm sure a number of them.

[Ryan]

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 it was written in.

[Tyler]

This is not true.

[Ryan]

Did I ever tell a story on the show?

[John]

I don't know.

[Ryan]

Tyler doesn't want to tell it. So Tyler gives us this. We use a Chrome plugin to track the show when we're sharing posts between us and this Chrome plugin. He Vibe coded it and he sends it over and I unpack it to install it. And I'm like, why are there Node modules here? That's usually for Node JS JavaScript on the back end. And he's just like, what are you talking about? And I was like, you don't know that you're using Node jf?

[John]

It's a good extension, sir.

[Ryan]

Because I think it was just so I trust Claude.

[Tyler]

I trust Claude to make the right decision.

[Ryan]

I don't even specify what programming language it uses, which is like pretty sick. It's actually extremely bullish for Claude and Claude code. It's really good. Anyway, 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, 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.

[John]

Is that why you were late for the gym today?

[Ryan]

But I was sneaking a peek at Sora while I was driving. If I die and crash because I'm looking at slop, this would be extremely depressing.

[John]

At a stop sign.

[Ryan]

Yeah, stopped. But there was one cool one which was more like pixel art, actually. And it was interesting because you remember the OpenAI Super bowl ad.

[John]

Yes.

[Ryan]

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. Very odd that SUNO and Sora are so close in name. I don't know how that happened. Maybe they should team up or something.

[John]

Wouldn't be the first time OpenAI has named something.

[Ryan]

Well, who?

[John]

Oh, yeah, similar. Yeah.

[Ryan]

IO, I don't know, but I don't know. I was seeing, like. I don't think it's fully over. You know, I think it's like it's in a. It might be in just a trough of disillusionment. You don't know. This could be. This could be a trough.

[John]

The trough is in a trough of disillusionment.

[Ryan]

The trough is in the trough. It's entirely possible, but clearly the vibes are rough and people are taking shots terminally online. Engineer says, just put the ads in the chat, little bro, in the chatbot. Because Sam Altman says OpenAI is making a very aggressive infrastructure bet with new partnerships.

[John]

Okay, but to be fair, this clip was from long time ago. That was, like, at least a couple months ago.

[Ryan]

Yes, yes, yes. And also so you can do both. What is interesting is that it's maybe.

[John]

It sounds like they're delaying.

[Ryan]

It sounds like they're delaying ads, which feels odd because I personally was. I'm maybe the only person that's really excited about ads and chatgpt. 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. But if they really are losing ground to, 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 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 RL'd into the model. Most people are like, wow. Contrastive parallelism. This is epic. I love it. Thank you. Like contrastive parallelism, antithetical parallelism. Like I've never. This is like a big, big, big phrase. Big words like this is amazing. And so I'm shocked that there would be such a. I'm not shocked by like a vibe shift on X and in Teapot with regard to how people have been skeptical of the OpenAI financing and so they've been looking for a crack to show and Gemini coming out and leapfrogging a little bit, even if it's just on some obscure benchmark they 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.

[John]

Do you think they have to explain the funding gap at this point or can we all just agree that maybe everyone got a little too excited?

[Ryan]

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 these things probably aren't as binding as we think. And so I feel like the OpenAI 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. Buco Capital bloke has been digging into the funding hole.

[John]

Apparently ChatGPT is also down right now. I just tested it. It's not down for me, but the chat says it's down. Well, X is saying it's down.

[Ryan]

Oh, really? Oh, wow. Time to Baja Blast those servers 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. We have to Baja Blast our way to the top of the App Store. So Aura team, I need you to Baja Blast.

[John]

It's time to.

[Ryan]

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 Baja Blast some funding into this company because apparently there's a $270 billion funding hole here. This is from a podcast between Ron John, who writes at Reed Margins, and Alex Kantrowitz at Big Technology. They did a podcast together. And here's the quote from Buco Capital Bloke says, squaring the total, it leaves OpenAI in a 270 billion, $207 billion funding hole. The math doesn't work. Maybe OpenAI 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, OpenAI does fall $207 billion short of the money it needs to continue funding its commitments. Right. So it has. In 2030, OpenAI free cash flow will be about 287 billion. That's like insane. This 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. 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. Everything just forms in front of you. Yes, you are building the bridge as you're driving, but that tends to happen when you're on that much of a tear. The bigger question is, can they actually. Free cash flow, $287 billion in 2030.

[John]

Amazon's free cash flow for 2024 was 38 billion. And let's see what Google's. Yeah, this is like 72. So saying that. That they're going to do three times more.

[Ryan]

Yeah.

[John]

Than Google and Amazon.

[Ryan]

So this is the HSBC report is modeling 386 billion in annual enterprise AI revenue by 2030. Enterprise AI revenue 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 are these contracts? Well, let me tell you about Fall, the generative media platform for developers develop and fine tune models with serverless GPUs and on demand cluster. 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 OpenAI with a post called Google Nvidia and OpenAI.

[John]

Would you look at that?

[Ryan]

And we thank Ben Thompson for always having an even keel. Highly recommend subscribing to Stratecheri. 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 Geordie Hayes who hasn't seen it because he hasn't seen any movies.

[John]

I've seen Star Wars, John.

[Ryan]

How many Star wars have you seen?

[John]

I have to have seen all of them except some of the more there's been some recent.

[Ryan]

All of them except some of them.

[John]

Well no, the more, the more recent ones are the like it. Hasn't there been like a new Star wars in the last.

[Ryan]

How many, how many Star wars are there?

[John]

There was. Is there six?

[Ryan]

Six? There's six Star Wars. That's how many movies they made.

[John]

Six. Like real Star Wars.

[Ryan]

There's six. There's six.

[John]

I'm gonna, I'm gonna. Hasn't there been like.

[Ryan]

Everyone calls it the Septilogy. Yeah, there's. There's six.

[Tyler]

Wait, aren't there are six.

[Ryan]

There's nine. There's three trilogies. There's the, there's the original trilogy prequel and then the sequel trilogy. And then there's also two spin offs.

[John]

Okay, so I didn't watch any of like the like new ones. But you watched the prequel trilogy, Rise of Skywalker.

[Tyler]

Doherty's talking about George Lucas directed.

[John]

Yeah.

[Ryan]

Okay, okay, so he's a Lucas head.

[John]

Yeah, exactly.

[Ryan]

Okay, so you've seen a New Hope.

[John]

You've seen real Star wars.

[Ryan]

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 about Star wars. But anyway, are you sure know enough to follow along with this analogy from Ben Thompson? He says you have Luke bored on Tatooine, called to adventure by a mysterious message borne by R2D2 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 leads him to the threshold of leaving Tatooine 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. 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 this 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, OpenAI and Nvidia. The first startup is called. The first is a startup called with the release of ChatGPT to be the next great consumer tech company. The other was best known as a gaming chip company characterized by boom and bust cycles. Driven by their visionary and endlessly optimistic founder 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. This is the cave of disillusionment. And are facing their greatest ordeal. The Google empire is very much striking back and I believe didn't ingen over at a 16z coin that the Empire Strikes Back.

[John]

Formerly he went independent.

[Ryan]

Oh, he's independent?

[John]

Yeah.

[Ryan]

Oh, I had no idea.

[Tyler]

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 GPT5, I think.

[Ryan]

Yes.

[John]

I think he wanted the 2025 vague post of the year no award.

[Tyler]

It's so vague that even after the release.

[Ryan]

No, no, no. I think this is it. I think this is it. It's Google's the Empire and he's launching.

[Tyler]

The thing that still doesn't make sense at the time because like OpenAI was like clearly in the lead of the models, like 2.5. I think 2.5 was the best jump.

[Ryan]

Not on cash flow. You know, who has more soldiers, who has more researchers, who has more TPUs. Right. It would be fair to characterize, it'd be fair to characterize Google as the Empire the whole time.

[Tyler]

I guess the founding of OpenAI, then Google is definitely the Death Star.

[Ryan]

Interesting.

[Tyler]

Isn't that their kind of origin story of OpenAI?

[Ryan]

Yeah, yeah, yeah it was. 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 packs and VAT compliance so you can focus on growth. So Google strikes back. The first Google blow was Gemini 3, 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. Time and money. Throw it in a ramp.com ad right in the middle of this article. I love it. Gemini 3'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. Nvidia, who reports earnings later today, is one is on one hand a loser because the best model in the world was not trained on their chips, proving once and for all that it is possible to be competitive without paying Nvidia's premiums. On the other hand, there are two reasons for Nvidia'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.

[John]

Did you know that Sundar was apparent like people were claiming that he had used the phrase code red back in 2022 at the ChatGPT was flopping.

[Ryan]

Yes, yes.

[John]

And so I'm remembering that now I missed it. Sundar came out and said he yes, didn't use that exact term but there was reporting that he did and I.

[Ryan]

Agree a rumor that he also said that he wanted to Baja blast Sam Altman out of the atmosphere, out of San Francisco, out of the atmosphere with a Death Star laser. Yeah, no, it is crazy.

[John]

I want to try to find more historical examples of Baja blasting.

[Ryan]

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 Nvidia, at least if they want to catch up. Secondly, and relatedly, Gemini reaffirms that the most important factor in catching up or 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 Tae Kim, author of the Nvidia Way, about that.

[John]

He's going to tell all.

[Ryan]

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 rumored deal with Meta, and third with a second wave of Neo clouds, many of which start as crypto miners and are leveraging their access to power to move into AI. So a lot of those Neo clouds, 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 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 OpenAI 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. 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, you know, is we're going to have the CEO of Amazon Web Services, Matt Garman on the show in just and AWS.

[John]

Announced a new chip and I don't.

[Ryan]

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 OpenAI meanwhile, is losing more money than ever and is spread thinner than ever, even as the startup agrees to buy ever more compute with revenue that doesn't exist yet.

[John]

Not mincing words.

[Ryan]

And yet, despite all that, and while still being quite bullish on Nvidia, I still like OpenAI chances more.

[John]

Whoa.

[Ryan]

Oh. Ben Thompson likes OpenAI's chances indeed. If anything, my biggest concern is that I seem to like OpenAI's chances better than OpenAI itself.

[Tae Kim]

Whoa.

[Ryan]

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. 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 CUDA and the associated developer ecosystem surrounding it. OpenAI meanwhile, had the best model, extensive usage of their API and the massive number of consumers using ChatGPT. The questions then is what 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 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. To that end, to the extent that 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 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.

[John]

They're using TPUs through Google Cloud. Yeah, but there's been no oh yeah.

[Ryan]

They'Re not buying them.

[John]

But still that implies more flexibility because you can just turn it on or off.

[Ryan]

Yeah, I'm talking about the actual like the TPU is an asic. It has literally less features than the gpu, like a gaming GPU and a 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 trade offs. Right. And so even though I don't understand it fully, I understand 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, I'm going back to exploring all sorts of different types of math that aren't necessarily optional.

[John]

Again, if you're buying TPUs through the cloud, you're effectively just buying cloud services. 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.

[Ryan]

Servers and chips on the scale thing. That makes perfect sense.

[Matt Garman]

Yeah.

[Tyler]

I think also historically tpus have definitely been more restrictive just because of the software was just, just not as good or it was closed sourced or whatever. And then yesterday Don't Patel was talking about how Google is slowly trying to open source more and more stuff. So you would imagine that in the future it should be much easier to use TPUs generally.

[John]

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 CUDA module I can use? Just time. Right? Flexibility is engineering work from Nvidia.

[Ryan]

Yeah, yeah, no, that's a really good point.

[John]

Point.

[Ryan]

So Cuda 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 the big is that the big company effect could play out with CUDA 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 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 simply not being worth the time and trouble 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 than large hyperscalers, found it worth their time and effort to rewrite 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. 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 CUDA wall as they 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 full circ. This takes this article full circle. This is from the previous Ben Thompson article in Sir Techery because in the before times I. E. Before the release of ChatGPT, 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 cases for those GPUs is very clear and those use cases are happening at much higher level, at a much higher level than CUDA 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 CUDA is higher than it ever has been, even if it is still distant for low level work. Particularly when it comes to training, Nvidia 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. 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 to whether they will have to give back more in future generations will depend on not just their chips performance, but also on re digging a software moat 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 G from TPUs might take share from GPUs is that for one to win, the other must lose. The real decision maker, maybe tsmc, which makes both chips and is positioned to be the real break on the AI bubble. Interesting. So ChatGPT and moats resiliency.

[John]

I can read through this one. ChatGPT in contrast to Nvidia, sells into two much larger market. The first is developers using their API and according to OpenAI 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 lock in, expanding from what they already always Baja Blast. And for a lot of companies that is openai1 I would caveat here. We were talking to a founder yesterday who off the show who was saying he immediately, as soon as Gemini 3 launched, spent like 12 hours, 12 hours just moving over to Gemini from OpenAI. So depending on the product, I don't know that API is always going to be super sticky. Say winning business one app app by one will be a lot harder for Google than simply making a spreadsheet presentation 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 every day. Multiple times a day in fact. Yes, Google helps this process along with its payments to its friends payments, 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 a excerpt from we.

[Ryan]

Can skip this one and continue at the bottom, the CEO of a hyperscaler can issue a decree to work around cuda. An app developer can decide that Google's cost structure is worth the pain of changing the model, undergirding their app app Changing the habits of 800 million people who use ChatGPT every week, however, is a battle that can only be fought by individ, individual by individual. This is ChatGPT's true difference from Nvidia in their fight against Google. Yeah, and so this I think is the most important takeaway 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. It's very hard to monopolize supply. But monopolizing demand is something that happens and the strength of habits is significant. 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. But for a lot of people, if they've, 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 is 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.

[John]

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 ChatGPT on mobile.

[Ryan]

And I mean, to be completely transparent, 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 save it locally and then cache that and then send it off, inference it and then come back. Unless you keep the app open, it will just give you a server disconnected error. I've gotten dozens of these and that's going to be a real. I think it should be something they should be able to fix in like a weekend. But you know, hopefully it's soon. But for a lot of people.

[John]

Logan.

[Ryan]

Yeah, well, they'll get it. But back to the moat and the map. 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. Okay, so that you can see where this is going with like Nvidia has five buyers and ChatGPT has a billion buyers.

[John]

And once it has advertised how many.

[Ryan]

Yeah, advertisement might be even more.

[John]

Right.

[Ryan]

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 argued that you could map large tech companies across two spectrums. The degree of supplier differentiation from Facebook, where the supplier is completely commoditized, just your friend on Facebook, to Microsoft and Apple, where the suppliers are somewhat more controlled. Yeah, there's the.

[John]

What a chart.

[Ryan]

The more unique buyers of your product you have, the stronger your moat, because it's hard to. Because you have to convince each one of them. And then second, the extent to which a company's network effects were externalized. Internalized network effects, or 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 profitably take a cut of 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 internalize 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 ChatGPT sits.

[John]

I wonder what he thinks then about them potentially kind of delaying ads and delaying ads probably punch in the air.

[Ryan]

Him and Eric Suefer are probably. And I'm right there with them. I completely agree. Boom. Launch the Ads product. Launch the Ads product. Get it out. 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 better over time. It Follows then, that ChatGPT should obviously have an advertising model. This isn't just a function of needing to make money. Advertising would make ChatGPT 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. 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 deepen OpenAI'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 can be bad, but these Instagram ads are pretty good. You know, he's, he's. And people are always like, he's backtracking. It's like, no, that's fine. Get, 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 surface 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 or Ferrari of Beverly Hills. No, you get an ad for the toaster that you were about to check out on.

[John]

I actually do. Like, half the ads I get on Meta are local dealerships in la.

[Ryan]

Yes, but importantly, not when you tied. It's not tied to search. And so ChatGPT can do the same thing where they can clearly show you 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 chopping that you're shopping for, like, right next to it. It's fine. And so I think that can work very well. Anyway, let's go to Google's advantages. It's not out of the 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, 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, so massive. And that's gotta be just the compound. And compound. I mean, we're uploading another three hours of video to YouTube today. You're welcome.

[John]

This one's for you, son.

[Ryan]

This one's for you, Demis. But the flip side is, like, they also see the entire Internet because of the way the googlebot scrapes. Like, the Google searching in Gemini is such a killer feature. Like, it's such a. It's such a killer feature if they can keep that on and they can actually surface that. Like, and, 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 Adeo, the AI native CRM. Adeo 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 Sofer did in a recent Stratecheri interview, two of the best collabing we 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, 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, particularly as the company signs deals for over a trillion dollars of compute. What are you doing Sam? Get the ads out. Put the ads in the chatbot. We love it.

[John]

Just put the ads in the chat bot and go.

[Ryan]

You gotta baja blast some ads into that app. You got to I want ads in ChatGPT, 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. Rheinmetall callback OpenAI'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 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.

[John]

I always so yeah, who, who. Both Gemini and and ChatGPT will have ads eventually.

[Ryan]

Yes.

[John]

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. They can just say like hey here's a pop up, do you want. Here's $10,000 of free ad credits. Try it out.

[Tae Kim]

Right?

[John]

It's like native. It will already be in AdWords. The example that I use is like how Zuck was able to take Instagram, which had a lot of users, 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, 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, keep Gemini on the frontier and deliver the best free, fastest text and image model, that's going to be very, very difficult to compete with. And so again, getting to ads faster feels like it makes more sense.

[Ryan]

I like that point. Ivory 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. 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 Arvind from Perplexity came on the show and he mentioned this idea of ads and 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, 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.

[John]

Sam Adman.

[Ryan]

Exactly. It'll be OpenAI has ads now or it'll be Gemini has ads now. And so you don't necessarily. 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 of advantage to being the second mover there. Right. Because 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, blah. Like, yeah.

[John]

I mean the harder thing is just how do you do it right? 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.

[Ryan]

I mean, there's plenty of surface area.

[John]

No, no, I'm not, I'm not saying there's no surface area, but I'm just saying like the right way to DO ads and LLMs is not clear yet.

[Ryan]

Yeah, yeah, I mean, they will 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 and it clearly knew everything about me. And it said, you're the host of TVPN and you've started, you 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, hey, we could retarget you with this. Let's put this in. And the same thing with OpenAI, with ChatGPT, 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. There's tons of surface area. I agree there will be a whole bunch of iterations on what the ideal ad looks like, but yeah, you can clearly get out. So. So let's go back to Ben Thompson. Close this out. Says the reason to be more optimistic about OpenAI is that an advertising model flips this on its head. Because users don't pay, 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. The hero of this site has been aggregation theory and the belief that controlling demand trumps everything else there's there. 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 OpenAI. 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 to infrastructure to R and D is so substantial that you understand why. OpenAI's founding was motivated by the fear of Google winning AI. It's very 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. OpenAI'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. Aggregators win new markets by being better. The open question now is whether one that has already reached scale 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.

[John]

That's his baby.

[Ryan]

Yeah, 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 take the leap first. Who's 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.

[John]

Yeah. Nobody's going to be like what Google is putting ads in a product.

[Ryan]

Yeah.

[John]

It won't be that surprising.

[Ryan]

So they should probably move fast.

[John]

We have some breaking news.

[Ryan]

What's the breaking news?

[John]

Jason Freed is joining the show at 2pm Surprise guest.

[Ryan]

Surprise guest.

[John]

He's launching Fizzy today. Kanban. As it should be, not as it has been. I will wait. We'll wait to talk about this till he joins in an hour and 20 minutes. So little surprise guest appearance from a.

[Ryan]

Legend calling out his competitors directly. I love when the founders do that.

[Tae Kim]

Founder Mode.

[John]

Founder Mode.

[Ryan]

Yeah, very.

[John]

Should we talk about John Gandrea leaving the company?

[Ryan]

He's out. I quit.

[John]

I quit.

[Ryan]

You like that one? I think that's probably been used before.

[John]

Some headline but Mar Subra.

[Ryan]

So of course Mark Gurman has the scoop.

[John]

I believe the Germinator.

[Ryan]

Germinators at it again. He says Apple AI cheap. John Gianandrea is leaving the company. Amar Subramania from Microsoft has joined lead AI under Craig Federighi. And so we should dig in a little bit to this history. So SWIX has a little bit of a deep dive here. He says Aman Brings a wealth of experience to Apple. He's quoting here. Having most recently served as CVP of AI at 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's not 16 years old, this is bearing the lead. He joined Microsoft AI four months ago. Wow, what a crazy turnover.

[John]

LinkedIn says six months ago, but who's counting?

[Ryan]

That's pretty fast.

[John]

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 Siri than Amar.

[Ryan]

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. Gurman does need to come on back on asap. I agree, Raghav. He was fantastic.

[John]

We'll get him in person. Hopefully before.

[Ryan]

So Gurman continues. He's, he says strange hire for a number of reasons, but it's hard to argue that the Apple job is a bad one. 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. I'm personally just excited to actually test drive what Gemini, how it works in Siri, how, how seamless that is. Because if it really is, just raise, press the bottom button, get Gemini and it's linked up properly and it doesn't have timeouts and it gets back to you pretty quickly. That's going to be a pretty powerful experience. That's definitely going to cut down on ChatGPT app usage for iPhone users, I would imagine.

[John]

Underrated threat.

[Ryan]

I would think so. There are so many moments where people.

[John]

Are counting out Apple.

[Ryan]

It's not. Yeah, I don't even know that Apple will benefit massively from this. It's not like they're gonna sell twice as many iPhones. They're already so big. It's not like they're gonna charge for it.

[John]

I don't think it's necessarily like especially bullish for Apple. It's an underrated threat for OpenAI.

[Ryan]

I would think so.

[John]

There's a lot of queries that all hit chatgpt on mobile that are not even like super economic, but it's just a lot of my usage around, like, hey, just trying to learn about something or research a product, etcetera.

[Ryan]

Yeah.

[John]

And if that's just like, again, one tap and you're in there.

[Matt Mullenweg]

Yeah.

[Ryan]

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. 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.

[Tyler]

Yeah, Yeah. I mean, I think the.

[Ryan]

Anything's possible.

[John]

You know, Apple's like, hold my beer.

[Ryan]

They're going to be like, every. For privacy reasons, every time you press the button, you have to E sign. And it's like, why are we doing that? Yeah.

[Tyler]

Like, the original, like, Siri kind of vision was like this very conversational AI, Right.

[Ryan]

Yeah.

[Tyler]

But I don't think Gemini has a real time voice model yet. Like, I'm pretty sure OpenAI is the only one that has that.

[Ryan]

Really? Really? Huh. I don't think that matters at all.

[Tyler]

Really?

[Ryan]

Yeah. I really think that just because that.

[Tyler]

Form factor feels like that would be the best thing to be on. You press the button on your iPhone.

[Ryan]

And then it's just on. And then it's just on.

[John]

Yeah.

[Ryan]

Yeah. 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 Gemini. That the Gemini team will not never be able to crack. Right. So they just have to build that. But honestly, I don't know that. That's certainly not how I would use it for most things. Most things I would say. Okay, I have one question. Get me an answer within a reasonable amount of time and maybe read it off to me or produce an article that's a pretty readable article summarizing the answer to my question. And then, yeah, maybe there is a back and forth, but I don't know. Oh, 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 it. I don't have an app.

[Jason Freed]

Large journalistic force headed towards you. Standby.

[John]

Tyler Anthropic is acquiring bun. What do you have to say?

[Tyler]

Yeah, I mean, this is definitely in line with their focus on dev. Stuff.

[Tae Kim]

Stuff.

[Ryan]

Okay, what is bun?

[Tyler]

Bun is a. It's like a. I don't know, it's like a bundler for JavaScript it's like a very dev.

[Ryan]

It has dramatically improved the JavaScript and TypeScript developer experience. They're going to make Claude code even better. I like that. Gabriel from OpenAI here is OMG in the chat, which is like a pretty crazy thing to 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 cloud code represents a new era of agentic coding, fundamentally changing how teams build software. 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.

[Tyler]

Well, so there are two ways to pay for Claude code. Either with your cloud subscription, where you get like Claude Pro or Claude Max, and there's a certain amount of tokens you can use, and then there's also you can just directly wire up APIs calls essentially to Claude code, and then you're being charged, like directly based on usage. So that's probably what that revenue is from.

[Ryan]

Yeah.

[Tyler]

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. 3/4 of your tokens are on Claude code. That means 3/4 of your $20 is counts as Claude code revenue.

[Ryan]

Okay, yeah, yeah, I'm not sure exactly. Yeah, I mean, I'm sure that they can. They can account for it.

[Matt Mullenweg]

So.

[Ryan]

It's founded by Jared Sumner in 2021. Bun is dramatically faster than leading competition. They say It's a breakthrough JavaScript runtime. Does it compete with V8? I'm very interested in, like, it's Node JS. It competes with Node. The thing that Tyler needs to learn.

[John]

What was that company that OpenAI acquired earlier this year for like a billion?

[Ryan]

I know the one you're talking about. Analytics or something.

[John]

Yeah. But again, I remember at the time people were like, oh, like OpenAI's competitors are not going to be happy about this acquisition.

[Ryan]

So that comment from Gabriel, 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, speaking of size, Alfred Lynn hit the.

[John]

Get that gong ready. John.

[Ryan]

What did he do?

[John]

Alfred Lynn comes in on the board of DoorDash, buys $100 million of DoorDash.

[Ryan]

Lynn said vanity. He's not done. Stewarding doordash. He's continuing to steward the company with.

[John]

$100 million buy and of course sends the stock up almost 6% on that. Pretty raw excited about it.

[Ryan]

He ripped. He ripped. What Is this? Another 4.6 million to donated to shrimp welfare.

[Tyler]

Okay, so they.

[John]

Yeah.

[Tyler]

Basically the story is in theropic. They were doing some research about smart contracts and so they had Claude Code try to figure out issues in smart contracts. And then I'm not sure exactly where the money came from. Maybe it was for bounties, but there's some way in which Claude code basically generated $4.6 million in like cash from finding these exploits. So then they just.

[Ryan]

Did it actually generate real money or is this like the hypothetical?

[John]

This is simulated testing.

[Ryan]

Okay. Huh. Simulated.

[Tyler]

Yeah. So it probably means that they could have like basically stolen $4 million from people, but they don't want to do that.

[Ryan]

Maybe they should have if they really want to get up the.

[John]

In other anthropic news, David Sacks says he's still waiting on Darios support after the New York Times piece was published. Sam Altman of course came in and said David Sachs really understands AI and cares about the US leading in innovation. I'm grateful we have him. Of course, Dario and Sachs 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 Garment, 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, designers are coming to him worried they're going to be sued and asking how to start fixing the issue. So let's pull this up up when we have a second or light because.

[Ryan]

I am very concerned about the amount of short wavelength light that people are.

[Jason Freed]

Exposed to nowadays, especially kids.

[Ryan]

The group of us that are shuffling around, some of them are saying this.

[Jason Freed]

Is an issue on the same level as asbestos.

[Ryan]

This is a public health issue. And it's big LEDs came in and.

[Matt Mullenweg]

People won the Nobel Prize for this.

[Ryan]

Very rightly at the time because they save a lot of 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 when we use them on the retiny looking at mice, we can watch the mitochondria gently go downhill. They're far less responsive. Their membrane potentials are coming down. The mitochondria are not breathing very well.

[Jason Freed]

Well, can watch that in real time under LED lighting.

[Ryan]

Under LED lighting at the same energy levels that we would find in a domestic or a commercial environment.

[John]

This is why I want to rig the studio with candlescent incandescent light.

[Ryan]

Incandescent. We're going back to candles.

[John]

Candle max.

[Ryan]

Let's do candlelight.

[John]

How about a hearth?

[Ryan]

This is the way.

[John]

If we put a hearth so we have lights above our heads that I'm sure are leds killing us. Slowly, softly. If we put somewhat a bonfire 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.

[Ryan]

That would be good. I like that. Let me tell you about TurboPuffer. Serverless vector and full text search built from first principles and object storage. Fast 10x cheaper and extremely scalable.

[John]

Turbopuffer is at Re Invent.

[Ryan]

Amazing. Fantastic. Well, we are joined by the CEO of Amazon Web Services, Matt Garman. Thank you so much for taking the the time to come and chat with us. How are you doing?

[Matt Garman]

Thanks guys for having me.

[Ryan]

Please take us through some of the high level announcements. Obviously it's Re Invent. Very exciting. Congratulations on all the progress. 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.

[Matt Garman]

Yeah, we had a couple of really exciting announcements today. A couple I'd highlight. First we introduced this idea of frontier aging 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 you have these autonomous agents that can help customers really turbocharge their software 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 in 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 understands 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 Trainium 3 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.

[Ryan]

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? Do you like the benchmarks these days? Do you think that we're sort of like post all the benchmarks 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?

[Matt Garman]

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, it's really focused on in a enterprise or environment where somebody's 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 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, can undo if you need to, can make sure that you're hitting your design requirements. And it really allows you and the agents, agents to operate in conjunction with each other and move really, really fast. And we're starting to build 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 can do vibe coding on Kiro as well, by the way. We think that that's just not sufficient.

[John]

For what the development's going to need.

[Ryan]

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. 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 and 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?

[Matt Garman]

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. 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. But you can. But if you send out 2 or 3 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're directing them, course correcting, etc. And so I'm excited about that. We've already seen these processes go off and work for multiple hours at a time, 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.

[Ryan]

Yeah. Yesterday we were talking to Vincent from Prime Intellect and they do some of this like, like fine tuning on smaller models and he has this thesis, I think that you share, that a lot of businesses will need to take a pre train 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. So how are they going to wind up using that tool in particular?

[Matt Garman]

I think they will and 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. No. And so the difference of what you just said is people take a pre trained model and they'll do RL after the fact and they'll try to do some, 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, those models will forget what they've 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 points percent trained or an 80% 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 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 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 gems. After that you can shrink them down and distill them. You do all those things, but on a pre trained model that deeply understands what your company does.

[Ryan]

And is that called mid training now? Is that the right buzzword for that?

[Matt Garman]

It's not like we're. And mid training is a different thing.

[Ryan]

Different things.

[Matt Garman]

It's the first time that anyone's ever exposed this idea.

[Ryan]

Okay, thank you.

[Matt Garman]

To deliver pre training checkpoints where we can mix in your data. No one's ever done this before.

[Ryan]

Very cool.

[Matt Garman]

It's the first time.

[Ryan]

Great. Well then yeah. On market structure, do you think it's self serve enough that large corporations will do it? Or do you need an AI lab? Do you need an AI scientist? Do you need someone who can write TensorFlow or PyTorch 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?

[Matt Garman]

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. I think we'll have some, some people where you have some experts that should come and, 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 technical person is going to go do this for sure, but, 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.

[Ryan]

Yeah. On the cost side, obviously you're working, you announced a new chip. I imagine that there's the emergence of some synergies across the models that you're developing, the software, you're deploying, the cloud and then also the chips. How are you positioning the Trainium 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 tpusc in the future?

[Matt Garman]

No, we, we definitely. Well, a couple of things that they're all to unpack. The first is we're very excited about Trainium and think it has enormous potential 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 Trainium 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, and we have a very tight partnership there. But, but we do think, and we're quite excited about what Trainium 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 of the pretty significant cost performance benefits that you can get from running on Trainium.

[Ryan]

How are you thinking about open source, the open source ecosystem that you need to build around Trainium? That's the big discussion with the TPU right now. The question of Google has some amazing folks. They have some amazing software folks. It seems like they don't necessarily need to open source everything. A lot of people are waiting to see how much the industry 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 closed source software to run efficiently on Trainium?

[Matt Garman]

Yeah, no, we're all in favor of having an open set of software to run On Trainium, in fact, we have our Neuron SDK which is open source today and allows everyone to contribute to that. We think that the, 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 Pytorch or other kind of open frameworks as well. So we collaborate across the industry on that and are big advocates of contributing to and, and supporting that open ecosystem.

[John]

Jordi, love to get your insight on just like general constraints for AWS as a business, what you guys are doing on the power side, is that a real constraint? Anything that you can share there?

[Matt Garman]

Yeah. As we're scaling incredibly rapidly, we recently announced that we've added 3.8 gigawatts of data center capacity in the last year alone, which is just an insane amount.

[Ryan]

Of data center capacity.

[Matt Garman]

Thank you and you're welcome. And, and so it's ramping incredibly fast and it's, it is a constraint. You know, we have more demand than we have supply today for, for AI.

[Tae Kim]

Sure.

[Matt Garman]

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, we think about power constraints, we think about networking constraints, data centers, etc. And so we're working really hard to try to remove every single one of those. And, and with an industry that's growing as rapidly as the AI one is, there's always going to be some constraint and we work really hard to keep removing blockers every time so we can keep growing fast.

[John]

Makes sense.

[Ryan]

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. We'd love to have you back on the show and go way deeper, but thanks so much and congratulations on all the massive releases. We're excited to dig in deeper and keep chatting about the them, but have a great rest of your day. We'll talk to you soon. Goodbye.

[John]

Cheers.

[Ryan]

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 Tae Kim, author of the Nvidia Way, and a Baron's senior writer joining the show. Take him the author of the Nvidia Way. Take him on the beat for joining the show 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 you got to ask right away. I did because it's the perfect time to talk to you.

[John]

Do you have roommates? No roommates.

[Tae Kim]

Guys, longtime listener, first time caller. I'm so excited to be on this.

[Ryan]

I'm so excited to have you here. Reminder, everyone go buy the book. Seriously. Seriously. Christmas is coming. I can't imagine a better gift for everyone. For a four year old, for even. Yeah, I know what my son's getting. He's getting the Nvidia way. Jensen Wong teach him young copies, multiple copies. No, seriously, get, get 10 copies. Give them that.

[Tae Kim]

Teachers, a lot of teenagers have, have read it. Like it's amazing and they reach out and it's an inspirational entrepreneurial book that a lot of parents are giving to their kids. So, yeah, definitely.

[John]

I love your, your headset, by the way, because we're actually developing our own TVPN headset because this is just like, this is the, this is the ideal, ideal setup.

[Tae Kim]

I was telling my friend, I don't care if I look like a dork. My hearing is going so like I get locked in when I have the head. So I could hear everything.

[John]

No. And it's wired. The worst, the worst is AirPods. AirPods 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.

[Ryan]

It's not code red over there. He's Baja blasting. 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? Set the table for us so then we can go into the opportunities and challenges with that framework in mind.

[Tae Kim]

So the first thing I found out about their culture is it's very blunt. 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 up process that gets ossified. Nvidia is the complete opposite. Like things are not going well, he'll chew you out in front of the whole company. And that kind of blunt mentality I think 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 an agility. When I Talk to people at intel or Google. Like the biggest problem they have is meeting paralysis. And you need to get sign offs from like five different executives at Nvidia. Like you have a meeting, Jensen makes the call, he seeks out the right information and you move. So there's this agility at Nvidia. 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?

[Matt Mullenweg]

Recruit?

[Tae Kim]

And from the beginning, like Dwight Dirks, 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. Like I really enjoyed working with him. And he just almost ruthless in a sense. He just goes after him and then recruits them, bring people aboard. So this meritocracy, agility, speed and just getting rid of the internal politics, I think really separate creates Nvidia.

[John]

How has most of the team becoming millionaires affected the culture, if at all?

[Tae Kim]

I think they have. I think in the first 10, 15 years, like people started getting sports cars and putting them in the parking lot, but a lot of pizza cars.

[Ryan]

Let's go. That's the best news I've ever heard. That's fantastic.

[John]

Sounds like it's had an incredible impact on the culture.

[Ryan]

Jobs finished. Okay.

[Matt Mullenweg]

Yeah.

[Ryan]

You can, you don't need to respond, you don't need to say anything more.

[Tae Kim]

I think winning culture breeds winning and people want to stay with winners. Right?

[Ryan]

You want to win on the track then.

[Tae Kim]

A lot of the people I meet in terms of colleagues, they work for a company for five years and the chip doesn't work out and you just wasted five, seven years of your life. So you want to stay within winning company. And Nvidia has been winning for 30 years. So it's kind of like winning, but gets winning. You get the talent and then the talent stays. There's so many, many top executives in Nvidia that stayed there for 25, 30 years.

[John]

And there's also, there's some benefit of people if somebody doesn't have a scarcity mindset, right? And they're just playing to win. Like they're just like, they're no longer thinking like, oh, if we can just get to that next milestone and get this secondary sale and if I can participate and if I can vest my two years and sell into the next tender offer, then 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 for the love of the game, basically.

[Tae Kim]

And a lot of these people that they made it, they could retire. They could have retired 10, 20 years ago, but they stay and work. Still work 80 hours, 100 hours a week because that's what's expected. Like even the marketing people, Nvidia are working 80, 85 hours a week. And that kind of mentality I think is different, different at the companies.

[Ryan]

Okay, let's shift into the competitive dynamic. I mean, Nvidia's been. I was revisiting the performance of the Mag 7 since the dawn of ChatGPT. It's been three years. Exactly. Nvidia, by far the winner. Top 10x on market cap. The next closest company, I think maybe 4x by comparison. And so the clear AI winner in the public markets. The most obvious AI trade that just completely ripped. Now there's this whole narrative of how strong is their moat. What does the TPU mean? Is the TPU gonna be significantly competitive? Is there gonna 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 gotta get a discount from someone somewhere and I'll go to Google maybe.

[Tae Kim]

I want to Talk about this 10x move, please. 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 Nvidia, the H100 problem, the transition to Blackwell, China, ASIC, Broadcom competition. So this stuff has been happening this entire 10x move up. And the media loves to latch on to the latest, greatest thing to worry about, right?

[Ryan]

Yeah.

[Tae Kim]

We had Deep Seek earlier this year that 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 compute. So I find it amusing, like the whole world kind of discovered that Google had a really good chip in the.

[Ryan]

Tpu, which they've been working on for a decade too.

[Tae Kim]

They've had it for 10 years.

[John]

Right.

[Tae Kim]

They offered it to clients in 2018. This is nothing new. Yes, the Ironwood specs, you know, which I always take with a grain of salt. With specs, even Nvidia, they talk about 25x improvement. With Blackwell One, it's more like I'm.

[John]

Really just focused on the name. Ironwood is. Goes pretty hard.

[Ryan]

It's pretty good. They got some good names over there in Google.

[Tae Kim]

Ironwood came out, all the specs came out in April. Like this is not all this stuff is, isn't new. And another thing I want to say is tpus their chips. Morgan Stanley estimates there was a huge decline in TPU shipments in 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 Nvidia's in trouble.

[John]

I think, I mean I think it was a Gemini 3. It was a, it was a Gemini 3 thing. People are like Gemini 3 is the best model in the world by the.

[Tae Kim]

Benchmark for a whopping six days and ChatGPT is still number one on the App Store.

[Ryan]

I mean six days it was unseated by Claude which was also anthropic, which is also TPU potentially in the future.

[Tae Kim]

Yes. And ChatGPT Microsoft, the head of Microsoft AI Cloud, Scott Grethery that OpenAI is training their next models on the GB 300 MBs some few 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.

[Ryan]

Wait six months for the training run.

[Tae Kim]

Yeah, well she said the first models on Blackwell like on these super clusters are going to take six months.

[Ryan]

So it's delay the singularity, it's going to be another six Open AI is.

[Tae Kim]

Going to get there. The Claude and Gemini benchmark gains with pre training. That's the most bullish thing for the whole AI industry. AI adoption is the scaling laws are intact, everything's going to work out and OpenAI is going to get there when they build their next training run on the next model. So going back to TPUs. Thank goodness a shout out to Semianalysis they do the best channel work in the industry. Everyone freaked out on Friday, right? They read that semi analysis. No. Oh no. Total cost of ownership TPU v7 they're going to destroy but like people that actually know the industry. It was flaming bullish for Nvidia. Like it, it just, it was like so obvious in my face because Dylan and the Sami analysis, they said wait a minute, the next TPU V8 is not going to be that great. They lost a ton of people and the, the step function up in performance is not going to be that great. 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 people are saying it's.

[John]

The Rick Rubin of Chip.

[Ryan]

Are they related?

[Tae Kim]

Anyway, so Vera Rubin is going to be dramatically better at the next year and even the Ironwood which just became generally available and they're ramping right now. No one's going to switch over for one. It's a huge endeavor to, to put workloads From CUDA, Nvidia GPUs and put them on. There's always problems when you put them on a new chip.

[Ryan]

Yes.

[Tae Kim]

And let's talk about TPU customers. Right? Everyone freaked out that Meta might spend a few billion dollars in 2027. That sounds like a lot, right? That's less than 1% of Nvidia's expected revenue. Sure, it's 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.

[Matt Mullenweg]

Right.

[Tae Kim]

Maybe Meta will put a portion of their workloads 1% Nvidia's revenue. Is Amazon going to buy TPUs?

[John]

Well, John just asked the CEO of AWS if he was going to buy TPUs. He dodged that question.

[Ryan]

He didn't say yes.

[Tae Kim]

There's no way in hell they're going to buy TPUs. They have their own premium. They're not going to support their number one like one of the number one arch rival. Yeah, they're not doing that. So is Microsoft going to buy two?

[Ryan]

You should have been like, yes, I'm going to buy one so I can like study it.

[Tae Kim]

Microsoft's not going to buy TPUs. They're the number two player in cloud computing and they're not. Are the Neo clouds going to buy TPUs? Now you're going to say yes. Google has some Neo clouds. You know what happened with those Neo clouds? They're financially backstopping those Neo clouds. So Google is financially giving money and backstopping the debt for those neoclouds. So there's a handful of small Neo clouds. But is Core Weave going to buy TPUs? Probably not. Right? Who are the other customers of AI chips? Enterprises, companies, sovereign AI?

[Ryan]

Yeah, anybody that wants to run like a fine tuned model, some small model.

[Tae Kim]

Something like that, 95% of those. If you just go down on a first principles basis and look at the customers of AI chips like they're going to stick with Nvidia. The millions of developers know Cuda. So you don't have, you really need like Dylan talked about this is you really need like top notch like software sophisticated engineers that can like work with TPUs and learn 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 Colette the CFO talked about this morning, you can use it for training and they can use it for inference. 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.

[Tarik]

Crashed.

[Tae Kim]

There were bugs, the reliability. They couldn't figure out what happened and there's like they just threw up their hands. I give up. Like no one is gonna like if you have reliability problems, bugs, crashes. 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.

[John]

Figure it out because giving an F1 driver like a car that, that is unreliable and saying like hey go, go race, go race. Have, have fun out there. And then it's like, you know, and.

[Tae Kim]

The specs DNF immediately specs look awesome. It looks, seems great. But then when actually build your business on it, you put the future of your business onto something you the number one thing, it's not price. It's like it better fuck better work. It better work. And with Nvidia it works.

[Ryan]

Yeah. But react to this idea that Dylan Patel was joking about at TPU is a stalking 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.

[Tae Kim]

I don't think that's reality and I don't think that math actually works because I think he's confusing the AMDTO where AMD gives know free warrants to open AI. Right. First of all the deal's not done.

[Ryan]

Sure.

[Tae Kim]

It's a letter of intent.

[Ryan]

None of these deals are done. They're. They're not done.

[Tae Kim]

AMD's AMD's done. They signed the 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 in the 10q that it might not happen.

[John]

Doesn't OpenAI have to buy AMD chips in order to get the warrants.

[Tae Kim]

Yes.

[John]

And so it still could be that they don't actually end up going through with the purchase and then they wouldn't get.

[Ryan]

That's a good point.

[Tae Kim]

Yeah. Let's do a size up here with the circularity and all that stuff. All this stuff. It's like one gig at a time. There's milestones on OpenAI, there's milestones on AMD, technical milestones. They have to achieve certain targets. So all this talk about everyone loves the big number that adds up five years of capex, The leverage could be up or down depending on how things happen each year of the way. So it might not be that big number. If OpenAI doesn't come out with an amazing model or AMD isn't able to hit the milestones they set for their next 450mi chips. It, you know, don't worry about five years. Like, take it one year at a 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 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 get getting. You're getting ownership of the company. So I don't really believe in this 30% discount thing because Nvidia Jensen will say they're investing to accelerate OpenAI and they're looking forward to opening.

[Ryan]

I going, I mean, it's definitely creative, it's definitely a new structure. I'm just trying to. 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 $100 million 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, this is way less of a headache. Where else was I going to get $100 billion from? In OpenAI's case, 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.

[Tae Kim]

Except for the this kind of sentiment thing that we had the last few weeks, OpenAI hasn't had any problem in raising money. Prevention. Yeah.

[Ryan]

Yeah, that's true. Yeah.

[Tae Kim]

It's not like Nvidia is the only Source of funding for OpenAI like everyone wants in the revenue run rate, it's like 5 billion to 20 billion at the end of this year.

[Ryan]

So what was your take on the Code Red? What do you think about the Code Red?

[Tae Kim]

So I saw that you showed the Ashley Blue Dance interview. Really interesting. 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. So I think it's actually really good. And supposedly Ilya was doing the research for reasoning. Reasoning is awesome. Right? But they kind of focus on reasoning the past year with 01 and 03 and now they're like, okay, we have to go back to pre training. So OpenAI knows that pre training still works because Gemini 3 had great pre training results and Cloud Opus 4.5 did. 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 OpenAI has been a little too maybe diluted. Like they're doing apps.

[Ryan]

Sure.

[Tae Kim]

They're doing hardware. They want to compete in AI infrastructure against Microsoft and Oracle. They want to compete in AI chips against Nvidia. Like I thought it was really interesting. Like Satya repeatedly 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 name and this could be a win, win partnership. That was during the anthropic Nvidia deal with Microsoft, right?

[Ryan]

Sure.

[Tae Kim]

He said that a couple times. And I think the person that he's talking to is Sam Altman. Right. Nvidia. Microsoft made OpenAI as successful. They were the partners. Why are you competing with the partners that brought you to the dance? Right. Let's go back back. Focus on making the best AI model in the world and don't compete with Nvidia. Microsoft maybe, maybe five years from now, but like it seems a little aggressive to compete with them right now.

[Ryan]

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. What's your current thinking about the best policy for Nvidia exporting chips to China?

[Tae Kim]

Generally, I think the best thing is to keep it one or two generations behind the current state of the Art, this is a really nuanced policy that people, everyone's either hawkish or dovish. The best policy is to keep, I don't want to use the word the Howard Lutnick used that got China very upset, set and force China to tell its companies not to buy H1H. But the best policy is to get China still on the Nvidia stack. So Nvidia gets $50 billion of revenue per year. That can help R and D and fund R and D and make the chips even better. Nvidia and the US already won, right? They had 95% market share share. Like, why are we going to give $50 billion 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. Like, 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 by. I think that'll be the best compromise for both sides, but I don't know.

[John]

What do you think? Where do you place a likelihood that the Chinese market has opened up again at some point in the next 12 months?

[Tae Kim]

Maybe 50, 50. I mean, that sounds like a cop out. I was much more positive six months ago. But this has been just so crazy. First the Trump administration banned H20, then they didn't ban 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.

[Ryan]

The H20 and then they ban it.

[Tae Kim]

Yeah, and then maybe Trump is going to let Nvidia sell the H200 or a Chinese specific version of Blackwell that's kind of hobbled a little bit. Who knows? Nvidia needs to convince the Trump administration and then China to buy the chips. The worst part of it is, is China was willing to buy the H20 and it just all the kind of geopolitics and hurt feelings. That ship has sailed. So I don't know what's going to happen, but I do think the ideal situation is Nvidia could sell one generation behind, make $50 billion a year and keep the competition from Chinese AI startups out of the way.

[John]

Even understanding that at some point in the future, China's buying effectively zero chips from Nvidia, but it would be 5, 10 years in the future. It's like you have to assume.

[Tae Kim]

Right now it's go for it. The amazing thing is it's 0%. Right. And Nvidia's revenues accelerated for the first time in two years. Nvidia's revenue accelerated in this latest quarter. And this is like not talked about enough. This is the first quarter that the NVL72AI server has been available in volume and then revenue just skyrocketed without China. Which is incredible. Right? 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 going to last at least 3, 4/4. 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. And typically a lot of these data centers and these NEO clouds buy the networking stuff six months ahead of time. So the next six months from now, like the GPU numbers for Blackwell and the NVL72 server is going to be. It's just going to be bonkers. It's going to be off the chart charts. And people don't talk about these NVs 72 AI servers. They're three to four million dollars. Right? There's 72 GPUs, 144 dies, one and a half tons, 5,000 cables. And the prior version was eight GPUs. So these AI servers, I call it the iPhone 3G moment. Do you guys remember the iPhone 3G?

[Ryan]

This is big for the Christmas shoppers out there. If you want a gift that's a step up from the Nvidia way I.

[John]

Recommend or you want to bundle something.

[Ryan]

Picking up an NVL 72.

[Tae Kim]

Yeah, it's only $4 million, but for.

[Ryan]

The right 12 year old in your life or the potential, the intern, I.

[John]

Think Tyler and it won't fit under the tree, but it could be fun. Keep it in the.

[Ryan]

It's like a Lexus. You put it in the driveway with the bow on top. That's the way it does with the fork.

[John]

You drop the forklift, come drop.

[Ryan]

Exactly. I got you an NVL 72. Enjoy.

[Tae Kim]

And then we have the reasoning model thing where exponential compute and companies are actually seeing huge cursor. 40% productivity gains, C.H. robinson 40% shipments. Rocket Mortgage. 80% reduction in paperwork, cost processing. This is like the next year because of AI reasoning, because of the MDSMD2. That's why Amazon and Microsoft said every quarter this year they raised their capex and everyone's like they're going to cut their capex. They're going no. Every single quarter they raised 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 few years. That's crazy, right?

[Ryan]

Yeah.

[Tae Kim]

In September quarter more leasing. There are more data centers leasing the entirety of 2024. This is like exponential step function up. And people aren't talking about it. They want to talk about tpus like destroying Nvidia.

[John]

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?

[Tae Kim]

Not really. I mean demand guarantees like you're talking about Nvidia and Core Wheat. When that happens, analysts every, every quarter are on the conference call like did you use that demand guarantee? Like it's not happening yet. Like Core Weave's five year old GPUs that everyone says are useless are 100% utilized.

[Ryan]

Right.

[Tae Kim]

H100amassive cluster before it expires. Probably a three year contract. They got like 95% of the pricing. This is like on a hard heard of. And the reason is there's overwhelming AI demand and there's not enough capacity. Overwhelming AI demand, not enough capacity. And people just, they don't care about what's happening in the real market. This is real life. Facts, evidence, numbers. Nvidia going from 56% revenue growth to 62% revenue growth on $57 billion with barrel China revenue. I mean these are bonkers numbers. 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.

[John]

I love how you're the, you're the only person without Nvidia fatigue. You're just like, you're not bullish.

[Ryan]

David Goggins of you're the David Goggins.

[John]

I mean they can't keep running. They can't keep running.

[Tae Kim]

This is not me just like making stuff up. This is like numbers are there right now.

[Ryan]

You make good points. You make good points. I like it a lot. We'll have to have you back on the show soon. This is a lot of fun.

[John]

Yeah, let's do it. Let's make this a regular thing.

[Ryan]

Yeah.

[John]

Super fun to have you on finally.

[Ryan]

Thanks so much for all your reporting. 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.

[John]

Up next.

[Ryan]

Oh yeah. We can just go straight into our next guest.

[John]

Let's Bring in.

[Ryan]

We have Tarik from Kalshi with some massive news. Tarik, great to see you. How are you doing from the office floor? Good to see you. Hey, guys, thanks.

[Tarik]

Thanks for having me. Very excited to be here.

[Ryan]

You are locked in. Look at that backdrop. Fantastic. Please introduce yourself. You've been introduced. Give us the update. What's the news? Let's ring the gong.

[Tarik]

Well, we just raised our Series E. We just raised a billion dollars, $11 billion valuation.

[John]

Great Wind up. Great wind up.

[Tarik]

Honestly, I was waiting for the gong.

[Ryan]

Congratulations.

[Tarik]

Fucking sick moment. How's it going, guys?

[John]

Yeah, great to have you on. I don't. I was thinking over the. I don't know if anybody had a crazier Thanksgiving holiday than you. It was. There was a lot. There's a lot going on last week. So. Nice. Nice to come out of that with a, with a, with a big announcement. But. But yeah, maybe, maybe kind of just update us on. I think everybody's has been following the prediction market wars. The more important story, I think is.

[Ryan]

Just how some people are calling Bloodbath, actually.

[John]

Yeah, I mean, just like it's been a battle on the timeline, but yeah, I think what's happening in the background is like this explosion of this new asset class that again, I think in your announcement earlier you were saying a few years ago nobody really cared at all. And now you and the industry broadly have millions of users. So it's pretty unprecedented. But, yeah. What's been the latest on your mind?

[Tarik]

I think the thing that's happening right now is prediction 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. 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 retrusting the sort of legacy media and legacy sources of information, and they go to prediction markets to get smarter. The other one is that they're legal now. You know, cashiers took on this sort of battle over years to legalize this entire market. And, and set it up as a legitimate financial asset so that anyone can participate. And three, I mean, I think we're all sort of, we sort of caught wildfire this, this, 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 cashier odds live and the cashier charts. You cannot talk debate about a topic about the future without, you know.

[Tyler]

To.

[Tarik]

Put a position on Kalshi on the app. So it's a huge announcement. We're very excited about it and honestly really feels like we're just scratching the surface of what prediction markets can be.

[Ryan]

One thing I've noticed when I'm watching a sports game is there's sometimes integration with Kalshi, sometimes with a competitor. What's actually going on?

[John]

Legacy sportsbooks.

[Ryan]

Yeah, what is actually going on? I feel like a lot of people who are just passively observing the timeline are seeing a lot of announcements and partnerships with the partnership economy and people are joking about it. 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, 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?

[Tarik]

I mean, I'll tell you, kind of our approach to this. So we are building, you know, our focus, 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. And you know, we're market leader by meaningful margin, I think, depending on sort of how you measure it. So we're 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 like actually driving legitimate volume and legitimate use case into the product. So our partnership with platforms like Robinhood, I mean Coinbase leaked, it's coming in December and price fixed Webull are kind of in that bucket. Then we have partnerships with a series of partners coming around news. One of them leaked this morning in the New York Times article.

[John]

But they're also very one sentence, ten leaks.

[Tarik]

Everything leaks these days. I just like nothing is news anymore. It's like so, 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, and then drive legitimate utility to the partner. And so, you know, 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, you know, reporters love true truth and prediction markets bring truth. So you could see the synergies and how they fit.

[Ryan]

Okay, yeah, yeah, yeah. That makes a lot of sense.

[John]

Yeah. I think some of the big news out of last week is that Robinhood 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 structure of the market evolving? You guys are an exchange, Robinhood is a brokerage. Sounds like they're trying to actually build an underlying exchange themselves. How much should sort of observers of the industry look to how stock trading and stock markets, stock exchanges have evolved versus prediction markets? What does this market kind of look like in 5 years, 10 years? As much as you can, can kind of pull out a crystal ball for us.

[Tarik]

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. This sort of massive surge of competition, whether it's brokers, there are some of the sports books like Draftskins and Fanduel coming in, it's just usually a sign that there's a lot of good things to come for that market. Right. It's a sign that, like, you have big companies reprimanding their entire roadmaps to go all in after this. And that's a positive for us. Like, we're market leader in a market that, you know, everybody is starting to believe is going to be ginormous in terms of a specific question of market structure. I mean, like, you know, we have, obviously the exchange. We also have our direct profit product, 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 over time, 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, that kind of the thing that stands out is similar to any other market is product and product velocity is are you putting out products faster than anybody else and are you putting, putting out products better than everybody else? And I think Kashi 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 in the industry and everyone's following and I feel pretty good about us continuing to do so in the next 24 months.

[Ryan]

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 and, and it's, it's obviously big. Everyone's excited about the numbers, but is this a natural monopoly? Is this duopoly? Like, like how many winners will there be? How do you even think about the market structure? Is there some return to scale?

[Tarik]

It's interesting, like, 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 like all figured 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 rideshare, it has some similarities to the draftings fanduel 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 as any of the, any of these other buckets. And I think that you'll see more.

[Tae Kim]

Of.

[Tarik]

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 what companies are going to rise above the others in terms of product velocity and product quality. That's just what we're narrowly focused on.

[Ryan]

There's a question from the chat. Can you explain how external market making works on Kalshi, that's been for some.

[Tarik]

Reason a hot topic recently. But market makers are part of any financial market. You kind of need them to basically have liquidity in markets and, and actually Kalshi 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 Jordy to a market maker like Citadel, whereas on Cash actually the vast majority is Jordy versus John and then some of it goes to market makers and it's an open, transparent order book where everyone's competing on price. And we have actually a separate company called Cash Trading that trades on the exchange. But they're a very small percentage of any liquid markets.

[Ryan]

Really.

[Tarik]

Their function has been for new markets are a little bit weird markets.

[Ryan]

Yeah, that makes sense. Because if it's some really, really niche thing, who's going to put in the first 500 bucks?

[Tarik]

Exactly. And they're not very profitable. It's actually they're really focused on providing a good customer experience that we bootstrap markets rather than any meaningful part of the business model today. And if we took it out, it'd be actually a worse experience. So I think. I think it's definitely not positive for the ecosystem, but it's a bit like Uber. You know, when the adverse interest got impacted the taxis, they were coming up 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.

[John]

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 reason, recent lawsuits, again, against prediction markets and said they clearly don't understand how this works. Can you comment at all on some kind of misunderstandings broadly?

[Tarik]

Yeah. So what Kalshi 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. And that's one of the main financial agencies. There's the SEC that does 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, which is some stuff makes sense at the federal level and some stuff is more local and makes 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 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 Airbnb was terrible and all these different things. But at the end of the day, the thing that drives it long term is is this a great product and our consumers loving it and using it? And the answer is yes, in this case.

[John]

Off of the success of Kalshi and polymarket, there's been a bunch of net new prediction market startups that are created. Is there a possibility that, that, that this market, like, ends up having these sort of like niche, maybe more like vertical marketplaces? Or do you think that the platforms with the greatest liquidity and the deepest liquidity will ultimately just absorb those submarkets?

[Tarik]

It depends on how narrowly we define prediction markets versus broadly. Like, I really think of prediction markets as kind of just like a next generation, like, like expansion of financial markets to touch anything. Kalsha means everything in Arabic. But really if, like, if markets kind of progressively grew over time, Kalship, 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 in those type, in these types of markets. That is hard, I would say, to battle with. And so I think, at least from that aspect, I think the cards are probably mostly shuffled already.

[John]

That makes sense.

[Ryan]

Last question. There was a viral clip of you talking about Donald Trump Jr. 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?

[Tarik]

Yeah, I mean, look, first of all, that clip is a clip and you know how these clips are taken.

[John]

But, you know, who needs context?

[Tarik]

Yeah, it's like we don't need context. It's a complete, you know, anyways, look, I think that, you know, we, 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, Trump at the time was using his prediction markets all during the election. And actually Mamdani more recently was using his Kalsha 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 to touch financial markets are going to touch the news and they're going to touch the political process because they bring more truth to all the of the above all of these categories. And in some ways it's good that like 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 discussed where like there's industry dissidents that are against prediction markets that find all these different reasons for why prediction markets might be bad. 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 D.C. with relative. It's a very progressive panel. It was a panel of Democratic judges where we won 3 0. So people want to make it out 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 them and I think that will win the, win the day at the end of the day.

[John]

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 gets data from. We work with polymarket, we use polymarket data on the show. If somebody has 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, I want people that have inside information on global events to be trading so that the markets actually better reflect reality. But what is the CFTC's view on that type of activity? Because things get thrown around all the time. Insider trading this or that. But I don't actually know what the actual law says.

[Tarik]

Yeah, that's actually a great question. It's a point of debate in this land but I think there's some distinctions. So cash 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. 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 a stock, maybe we should let insider trading happen. 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 up, people just stop participating. 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. And so that makes kind of a more balanced, more fair marketplace. And I think we're very focused on the that. But it's a very interesting question. It's one the industry is battling with. But we take a hard stance on insider trading.

[John]

Yeah. Because if somebody goes and they go and they vote in a local election and they see like, okay, I talked to somebody there and they said they were voting this way. And I talked to another person, they also said they were voting this way. And then somebody trades on that information, like, is it actually, like, is that.

[Matt Garman]

That.

[John]

How do you define that type of activity? Right. It's like anybody could go down to the polling. 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.

[Tarik]

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 for. From that, that's actually fair game. Now if you call your cousin at Walmart and ask them for information they have internally they're not supposed to reveal to the public, that's insider trading. And I think we have a very similar line here.

[John]

Yeah, yeah, yeah, that makes, that makes sense. Very cool. Well, super helpful and yeah, congrats to the whole team. It's pretty massive milestone.

[Ryan]

Huge.

[John]

And yeah, great, great getting the update.

[Ryan]

Thanks so much for taking the time, Scott.

[Tarik]

Thanks for having me.

[Ryan]

We will talk to you soon.

[John]

Talk soon.

[Ryan]

Have a good one. Ad quick.com out of home advertising made easy and measurable Plan Buy and measure out of home with precision. Our next guest, Matt Mullenweg from Automatic, he is in the restream waiting Room. Let's bring him in.

[John]

They are set up.

[Ryan]

Parent company of WordPress.com Tumblr, I think.

[Matt Mullenweg]

Are going to remain.

[Ryan]

Welcome to the show. 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 about to come on the screen. Yes.

[Matt Mullenweg]

All right, well, little drum roll experience. TVPN for the first time.

[John]

So, Matt, our audience, we're streaming on.

[Ryan]

Them, they're streaming on us. How are you? We'll clap too. Fantastic. How are you doing? Good to meet you.

[Matt Mullenweg]

Howdy. 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 imagining a lot of folks in the room have never heard or seen TVPM before. 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.

[Ryan]

Yeah. Give me the state of the word and then also I want your personal word of the year. Year. We've been debating what the word of the year should be over here. Oh.

[Tae Kim]

So state of the word.

[Matt Mullenweg]

And I'll say the state of the word is strong.

[Ryan]

Okay, that's good. Let's hit the gong.

[John]

We're hitting the gong for that one.

[Ryan]

The strong state of the word.

[Matt Mullenweg]

We actually just did a live release of WordPress 6.9. So WordPress does major releases three times per year. We were able to do it right here on stage. We had a little button that we pushed. We got to hit it next time.

[Ryan]

I love it.

[Matt Mullenweg]

That was pretty fun. Don't worry, I didn't just ship it again. But 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. Exciting. My word of the year, and actually a theme we were just talking about is I'm going to choose freedom. Powerful as technology starts to influence more and more of our lives. How we travel, who we date, the things we learn, the news we're exposed to, 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 inalienable rights that no company or person can take away from you. And that freedom and agency I think is really, really important and something that I think as technologists or builders that we should try to embed into everything that we do.

[Ryan]

Give us an update on Beeper. I was super fascinating. I was super fascinated by that product. 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 imessage 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?

[Matt Mullenweg]

Well, obviously I'm using it daily, so I would think of it not as like replacing a walled garden, but more like allowing your gardens to come together. So I'm sure you like me. I have friends on lots of different networks and some of them always love to use Wet app and some of them always love to use Instagram or LinkedIn DMs. Sometimes I even get some interesting stuff there and I hate it when I miss these messages because checking all the different apps, sometimes the notifications, I might miss something. So think of it not unlike how email clients 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, is that it's not going to replace the networks. I still keep all the different specialized messaging apps because 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 a different interface. So you might still have the dedicated apps but then having this all in one inbox that you can 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. Don't just show me unread, but show me all the people I've messaged that haven't messaged me back yet.

[Ryan]

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 figured out a way to get it into the imessage ecosystem. Do you think that we need new regulation there or 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.

[Matt Mullenweg]

Well, technically it's not hard. Well it is hard, but it's very possible to reverse engineer these networks.

[Ryan]

Yeah.

[Matt Mullenweg]

However, as we saw with Swift, 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. So perhaps these things might happen through 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 iMessage using some APIs that are available on Mac US. So on macOS we can bring in your iMessage.

[Tarik]

Got it.

[Matt Mullenweg]

But again I'm building this for long term and we are a commercial company as well.

[Ryan]

Sure.

[Matt Mullenweg]

So we want to work with the networks and perhaps there can be regulations like the European DMA are things that can encourage interoperability. But ultimately I think that the sort of people who run these networks have to see a longer term benefit for them. And for things like some of the other networks I mentioned that Bieber works with, I think their business model and everything they increase usage is really useful for them. I think for today Apple's business model of particularly in the US kind of the lock in effect to the device business, which is of course where they make a lot of money from imessage, probably indicates that unless 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 USB C and all of our lives got better. Who knows what will happen in the future.

[John]

Talk about link 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 they can monetize them to the fullest extent. Meanwhile you have LLMs which are ultimately doing a lot of the same thing. They are 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 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, or chosen to demote them in the algorithm over the last couple years. But give us the state of the union on links.

[Matt Mullenweg]

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've shifted some of the balancing of links and they now have this really nice in app browser. So you've probably noticed that now that when you load a link you actually still have the ability to like and reblog and everything, everything. And I think that's kind of the future. So I do think that 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 fully embedded in the app. 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 sort of time when links got really deboosted and everyone had to do it as like a reply was kind of weird and sucked. So for WordPress publishers, 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 an e commerce plugin. 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 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 OpenAI and others where we're allowing products to actually be browsed and bought inside of the LLM are pretty exciting. I also think that the incentives of these open source chatbots in particular are very complementary to the open web. So for example, if you're on Amazon, Amazon really wants you to say or ebay or Etsy or something like that, they want you to say in their marketpl place on their system. But when you think of how Google works and sort of the growth of Google in the open web, they have their search pages but they also would link out and that was a 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. So there's never a better time, I think to invest in having a domain but also invest in publishing. And just like you might have a direct relationship for example. I suppose I could get a chatgpt to summarize today's TVPN episode, but it's more exciting to watch it. I think that creators developing a direct relationship and brand is going to be part of the future as well.

[John]

Very, very cool. Well, there's so many more things that I want to ask, but I know you're. You're in the midst of your own presentation, so thank you for tuning in. Come back on soon and thank you for having us. The view is spectacular as well.

[Matt Mullenweg]

It's a pleasure to meet. I love to come down and hang out when I'm in LA next.

[Ryan]

That'd be fantastic. Thanks so much. We'll talk to you soon.

[John]

Great chatting.

[Ryan]

Have a good rest of your day.

[John]

See ya.

[Ryan]

Bye. That was a first.com exceptional. Sleep without exception. Fall asleep faster, sleep deeper. Wake up energized. That's our sponsor.

[John]

We have 94 last night. John, I smoked you again. Lost your phone. Well, we have Jason Freed in the restream waiting. There he is.

[Ryan]

Jason, how are you doing? Good to see you.

[Jason Freed]

Good. You?

[Ryan]

Congratulations. Massive news today. Break it down for us. What's up?

[Jason Freed]

Was there big news today? I missed the news.

[Ryan]

What was the news? Oh, you're, you're just calling out.

[John]

You are the new news.

[Ryan]

Trello naming names. He's naming names. A lot of, 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 called them out. You, you put them on the map.

[Jason Freed]

We had some fun. Yeah. So we launched a new product today called Fizzy, which is kind of a fresh take on Kanban. An old idea, obviously it's been around for a long time, but we, you know, 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 the 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.

[Ryan]

Why new name? Why not a new tab in an existing product?

[Jason Freed]

Right. Well, Basecamp, which is our biggest product, has Kanban 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. That'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, sense, frankly, for this kind of thing.

[Ryan]

So do you, I mean, do you have an idea of, like, who is the target market? Startups, individuals? Like, like you use this to plan your Thanksgiving dinner.

[Jason Freed]

Yeah, I mean, the target market is me and us, basically. We build things for ourselves.

[Tarik]

Sure.

[Jason Freed]

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. Oh, 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 and other people are like you, and they kind of dig it, you know, and.

[John]

So I, I always thinking about ourselves. I said to someone this morning that, that I feel like TVPN is that way, where sometimes when I'm driving home, I want to watch. I want to. I want to watch tvpn. But I'm like, we just, we just made it. I just lived it. I should probably, you know, watch something else. So I never, I never watch. Watch the show myself so much.

[Ryan]

Call me and say, hey, yeah.

[John]

Then we just make it. We do a podcast on the fly.

[Ryan]

Let me just talk about tech news more. 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.

[Jason Freed]

One prompt was all.

[Ryan]

It was all.

[John]

It was all you need.

[Tarik]

Yeah.

[Jason Freed]

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, 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. So we had. 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. Different programmers jump in at different times. But it's fully documented, which is very rare. You'll almost never ever see this in commercial software, 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, the team size in total, probably about.

[John]

Six.

[Jason Freed]

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.

[Ryan]

How do you think about pricing these?

[John]

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.

[Jason Freed]

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 went in and bought a pair of jeans or peanut butter.

[John]

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, much? How much should this person pay?

[Jason Freed]

Right. What watch are you wearing? All the things. Right? So it's 20 bucks. But we give you 1,000 cards for free. So there's no time limit on the trial. You get 1,000 cards for free. And if you never use a card is like a, you know, like a to do item or something. If you never use them up, it's free forever.

[Tae Kim]

Okay.

[Jason Freed]

And you can also run it for free if you want to run it yourself.

[Ryan]

Because it's open source. Yeah, yeah.

[Jason Freed]

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 want to do is I want to price this more like an accessory. This is not the only tool. You know, the software industry is interesting because it thinks that whatever it makes, it's the only thing anyone ever needs.

[Tarik]

Right.

[Jason Freed]

The thing is, is people need a lot of different things. And so. 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 price 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. And it just feels like that's the right place to start. We'll see where we end up. But that feels good for now.

[Ryan]

If I pay you to host it, where is it hosted?

[Jason Freed]

China?

[Ryan]

No.

[Jason Freed]

So it's hosted. We have a few different data centers, so it's not. Well, it's in our.

[Ryan]

Yeah. What I'm getting at is like it would be easy to just throw this on aws, but like you're the one company that doesn't just do that, right?

[Jason Freed]

That's right. 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, centers. That said again, you can also, if you just don't trust us, don't want us to do it, you can put on your own stuff, including like a simple droplet, like a digital ocean, something, whatever you can find that will host something basic will work for this as well.

[Ryan]

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. I could put it on.

[Jason Freed]

I hope someone does.

[John]

There's an AI company that recently had a Code Red. Have you ever had a Code Red ever? Once?

[Jason Freed]

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 have all hands on deck to fix something. I mean there was a moment I think.

[John]

Did you learn, did you ever learn the. Did you ever get overly fixated on a competitor and sort of like learn that? Because there's like, that's like yc, like just law Right. Like, 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.

[Matt Garman]

Right.

[Jason Freed]

Most wounds are self inflicted.

[John]

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, if that was ever the case.

[Jason Freed]

I think there was one time when 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, which is a real time chat. Group chat.

[Ryan]

Yeah.

[Jason Freed]

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, out and I saw it. I remember, oh shit. Like, yeah, they nailed it. Like we, we just.

[Ryan]

Yeah, 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.

[John]

The other thing is, Slack doesn't feel like that outside of the world. In terms, even from a. I'm sure you have opinions on Slack's like, design, but it, it doesn't even feel that, like you guys probably could see that and be like, oh, that, that's like, like, like the, the design was opinionated and you know, fun.

[Jason Freed]

It felt fun. Slack felt fun. I mean, IRC of course was, is very geeky and whatever, but yeah, the fundamentals were there. But Slack had a wonder, wonderful onboarding experience. It felt fun. They had great integrations. They just kind of like totally leapfrogged us in that world. And, and that was like, fine, but it, it did. It was the first time I felt like I felt. Felt that sort of nervousness in my stomach. Now I didn't feel it against our business because Basecamp is very different kind of product and was fine, but it was Campfire specifically because I was frustrated.

[John]

I was trying to figure out how.

[Jason Freed]

To make it better. And then I saw them come out like, oh, shit. Like, yeah, that, that, that's how you do it. So that was one time. But. But I just don't think there's any reason to focus on competitors. I, 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 some odd thousand paying customers for hey, right, which is if you were Gmail, it'd be an absolute abject failure to only have 40,000 paying.

[John]

Customers shut down, shut down years ago in seconds. Right.

[Jason Freed]

But for us, it's a multimillion 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. 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 that's not a person. But the only thing you compete with are your own economics. If you can make it work, you can make it viable, you're fine.

[John]

Revenue more your cost. You compete with your cost, you're competing with your costs.

[Ryan]

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?

[John]

I'm pretty harsh. I always let them sit out in the cold. I never let them in.

[Jason Freed]

We don't, we don't have meetings. We don't. So I don't, 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.

[Ryan]

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 ChatGPT 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 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, 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. A lot of companies just haven't even been able to implement that. It's been weird.

[Matt Mullenweg]

I agree.

[Jason Freed]

I think, I think frankly, that is one of the best use cases of.

[John]

I don't even know.

[Jason Freed]

It's not even AI though.

[John]

It's just.

[Jason Freed]

It's trans.

[John]

Great.

[Jason Freed]

Transcription software is very, very handy. And I think like, this is the thing. Like it's. It's transcription software has been around for a long time. It's gotten better and better and better. But it's not like AI really, you.

[Ryan]

Know, but it is in other ways. It has been AI for 20 years. It's been the original AI in many ways. You know, 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 per. They're not AGI. 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.

[Tyler]

I agree.

[Jason Freed]

We left this busy, by the way. We made a just conscious effort. We actually had some in for a while and pulled it out. And had it back in and pulled it out.

[Tae Kim]

Yeah, yeah.

[Jason Freed]

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. It just works and you don't even feel like, God, I Wish I had AI for this or for that. So V1 1, no AI. We'll see what happens down the road. Again, it's open source.

[Ryan]

People can. 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 users, 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. The rest of the system that they're using, 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.

[Jason Freed]

Yeah, I think so. In fact, this is actually interesting. Really quick. Recently OpenAI added a basecamp connector to ChatGPT and we didn't even do anything. So they did all the work and they just sent us an email saying, hey, we're launching this basecamp connector, like 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, 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. 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.

[Ryan]

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, will you just get sucked into the next pre train automatically and you can just go to ChatGPT and ask about you and you'll be there anyway.

[John]

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.

[Ryan]

We have one last question.

[John]

David Senra. Yeah, one last question. Question from our mutual friend, David Senra. Could we get a wrist check?

[Ryan]

What watch are you.

[John]

What are you rocking on launch day?

[Jason Freed]

I might be the only person who coordinates their watch with their software. It's possible. Okay, so I'm wearing. Today I'm just wearing a. I'll take it off because I don't know how to quite hold it up otherwise. This is a Vint, just a vintage Heuer from 1974, which is a birth year watch. Let's see.

[Matt Garman]

Hang on.

[John]

Whoa.

[Ryan]

Oh, birth year watch.

[Jason Freed]

Hang on, hang on, hang on.

[John]

Yeah, hang on.

[Jason Freed]

Let me see.

[John]

Focus is hard, but. Oh, there you go. There you go, there you go.

[Matt Garman]

There we go.

[John]

I love the orange.

[Ryan]

Thank you.

[Jason Freed]

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.

[John]

I knew I knew you. I literally said I knew you were going to match. I knew it was going to be intentional.

[Ryan]

This is so good.

[Jason Freed]

It's a little sad. A little bit. It's a little bit sad.

[John]

As I said, it's fun.

[Ryan]

It's joy. This is joy. It's joy. This is joy.

[Jason Freed]

I don't have like a what? Like a green. Why were you guys wearing a green jacket a few days ago? What was that about?

[Ryan]

It was Shopify Black Friday. We did. We were celebrating commerce online and so we wore.

[Jason Freed]

Oh, just green for money.

[Ryan]

Green suit.

[John]

No, it's the Shopify color.

[Ryan]

Signature. Color is green.

[Jason Freed]

Oh, Shopify. I didn't even know that.

[Ryan]

Yeah, Shopify.

[Tarik]

Yeah.

[Ryan]

Yeah.

[Tae Kim]

Okay.

[Ryan]

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 stuff for when we. For when there's big ramp news. We will wear solid yellow suits. Yeah, those are fun.

[Jason Freed]

I've seen that.

[John]

Hard to. Hard to miss. Well, Jason, open invite to the studio. We'd love to hang out for like a full hour.

[Ryan]

Everybody loving it.

[John]

Everyone's having a good. Everybody.

[Jason Freed]

Let's do it sometime. I'd love to. I think I got an email about.

[Tarik]

About that.

[Jason Freed]

So we'll figure that out.

[Ryan]

Amazing.

[Jason Freed]

Appreciate it.

[John]

All right, thanks for having. Congrats to the whole team on the line.

[Ryan]

Talk to you soon.

[John]

Very exciting.

[Jason Freed]

Thank you.

[John]

Bye.

[Ryan]

GetBezel.com, shop over 26,500 luxury watches that you're not gonna. You're not gonna believe it, but this was actually the next ad read up. Fully authenticated in house by Bezel's team of experts. And we gotta close out the show. So I'm gonna tell you about wanderer.com, book of Wanderer with inspiring views, hotel grade amenities, dreaming beds, top tier cleaning, 247 concierge service. There are so many more posts that I want to get to, but there's a lot.

[John]

We'll get to them.

[Ryan]

There's a new Arena Mag out. You gotta go to Arena Mag. Check it out. We are featured in this Arena Mag issue 0036, 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.

[John]

We will be back tomorrow.

[Ryan]

Yes.

[John]

Sorry to cut it off.

[Ryan]

Thank goodness.

[John]

A lot of fun.

[Ryan]

I would be in a very bad place. We weren't podcasting tomorrow, but fortunately we are. So we'll see you tomorrow. Leave us five. Love you on Apple Podcast.

[John]

Thank you for hanging out.

[Ryan]

Goodbye.

[John]

Have a great evening.