OpenAI’s $1T Buildout, Trump–xAI Alliance | Delian Asparouhov, Garrett Langley, Matan Grinberg, Francis Pedraza, David Paffenholz

Summary

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TBPN Podcast Summary

Episode Title: OpenAI’s $1T Buildout, Trump–xAI Alliance
Date: September 25, 2025
Hosts: John Coogan & Jordi Hays
Guests: Delian Asparouhov, Garrett Langley, Matan Grinberg, Francis Pedraza, David Paffenholz

Episode Overview

This wide-ranging episode focuses on the astronomical investments driving the current AI boom, how this compares to the dot-com era, the realities of building trillion-dollar infrastructure, geopolitical and industry impacts, and the emergence of novel business models and technologies enabled by AI. The hosts are joined by founders and VCs in the AI, public safety, recruiting, and enterprise SaaS space for spirited analysis and candid industry updates.

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Major Discussion Themes

1. The $1 Trillion AI Infrastructure Race

Timestamps: 00:00–28:20

• OpenAI's Ambitions: Sam Altman’s internal note revealed a goal: 250 gigawatts of compute by 2033, with infrastructure costs now forecast at $1 trillion (up from an initial $500 billion).
• Industry Parallels: Investments dwarf anything from the dot-com era—even when compared to tech bubbles, this moment feels unique due to the amount of cash (not just leverage) backing the buildout.
• Key Deals: Nvidia’s $100B investment in OpenAI (largely spent on Nvidia GPUs), massive multi-partner deals with Oracle, SoftBank, and CoreWeave, and announcements of hyperscale data centers (e.g., Central Park-sized facilities in Texas).
• Novel Financing: Many deals are via “non-binding letters of intent” and not-yet-finalized contracts, echoing negotiation strategies seen in the early Y Combinator “hard tech” days.
• Visual Scale: Per host John, “A single gigawatt data center is many football fields long, visible from space. It basically terraforms the earth.” (07:14)
• Comparison to US Power Usage: “Sam is saying just OpenAI, by itself, would use one-third of all power consumed in America in 2033” (07:59).

Notable Quotes

• John: “We’re not in the crazy, crazy debt era—big tech just has so much cash to fund the buildout.” (02:25)
• John: “Stargate was $500 billion and now we’re up at $1 trillion. Once you get into the trillion-dollar range, you’re approaching the GDP of some serious countries.” (27:30)

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2. Market Sentiment, Bubble Talk, and Investment Advice

Timestamps: 13:00–22:40, 69:33–74:43

• Bubble Analogies: Hosts and chat draw parallels with the late ’90s, but argue this is “different” due to funding structure and sheer scale (“all the richest people have voted and put all the chips on the table”).
• Retail vs. Institutional Risk: Data from boom/bubble cycles shows institutional/wealthy investors endure the biggest losses; retail is less exposed.
• Advice to Young Investors: Jordi warns, “Young millennials and GenZ are overly obsessed with investing… It’s a massive distraction from just getting better at your craft.” (18:44)
• Practical Tips: John recounts his method for forced saving, physically moving cash into a safety deposit box to separate it from spending/savings accounts (“build up a literal hoard of treasure… it’s incredibly satisfying” 20:43).
• How to Survive the Top: The value of durable growth, solid earnings, and not getting caught up in the risk curve; hypey, high-multiple private companies are most at risk in a downturn.

Notable Quotes

• Jordi: “Anybody who’s made a double-digit investment of their net worth in something liquid knows: it can be such an emotional rollercoaster.” (19:30)
• John: “There’s huge alpha in not even picking the correct asset—just getting the money out of reach of yourself before you can spend it.” (19:50)

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3. Power, Data Centers, and Supply Chain Shifts

Timestamps: 28:21–42:51

• Physical Footprint: “Gray towers of gas turbines have dotted the landscape… offering backup power… the site is larger than two Walmart supercenters.” (43:00)
• Data Center Jobs: Construction offers a temp jobs boom, but few long-term local jobs; 1700 permanent jobs forecast at “Site One.”
• Re-Industrialization and Outsourcing: US move toward “re-industrialization,” but the new wave of infrastructure creates far fewer jobs than old manufacturing.
• Stock Winners and Speculation: IBEX (formerly a Bitcoin miner) pivots to AI, stock surges as it aims to become a top power/data center provider (“about to control more power than the Hoover Dam” 14:05).

Notable Quotes

• John: “You can tell more about how a company is doing in D.C. by where their Gulfstream is parked than their lobbying budget.” (24:18)

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4. AI Job Displacement vs. Refactoring

Timestamps: 42:52–48:17

• Radiology as a Case Study: Andrej Karpathy posts on why radiology jobs have not been eliminated by AI—tasks are more complex; increased efficiency drives up demand (Jevons’ Paradox).
• Refactoring, Not Replacing: AI is adopted as a tool, changing the nature of work, especially where tasks are repetitive, context-independent, and low-risk.
• Engineering Workforce: Number of software engineers growing with the spread of tools like Replit, widespread prompting, and AI coding agents.

Notable Quotes

• John: “Deployment realities and institutional inertia mean AI-induced job change rolls out slowly—the world isn’t as simple as ‘replace humans with robots.’” (46:21)
• Jordi: “How different is copying & pasting code into Replit from what most junior developers do?” (48:17)

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5. Legal & Competitive Maneuvering: Trump–xAI vs. OpenAI

Timestamps: 49:16–53:51, 76:15–78:55

• Trump–xAI Lawsuit: Elon sues OpenAI for misappropriation of trade secrets, claims ex-xAI employees “admitted to stealing the company’s entire codebase” (50:11)
• Economic Warfare: “Seems like we are in the territory of economic warfare, lawfare…” (51:13)
• Internal Beef & Funding: Elon’s 2017 email resurfaces, threatening to cut OpenAI funding unless they commit to staying non-profit.
• Contracts With Government: xAI, OpenAI, Anthropic, and Google each land $200M government contracts—Trump admin “balancing” the big four regardless of politics.

Notable Quotes

• John: “The lawyerly society is coming out in this case.” (51:26)
• John: “All four of the AI companies also have $200 million contracts with the Defense Department… interesting the government clearly wants an oligopoly here.” (78:20)

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6. Industry Guests: Company Spotlights and Key Insights

Delian Asparouhov (Founders Fund)

Timestamps: 90:38–116:42

• TSMC Arizona as proof the US can airlift advanced industrial process
• Compared US “lawyer society” with Chinese “engineering society”—argues US is underestimated in manufacturing, still leads in deep, creative systems engineering (aerospace, commercial aviation, etc.)
• China’s strength: process knowledge and mass automated manufacturing, esp. drones and solar, but not always in “cutting edge” areas
• US has unique advantages in capital, agility, and importing talent due to openness and capital-richness

Garrett Langley (Flock Safety)

Timestamps: 122:38–149:45

• Flock’s journey: from demo-day mugshot to 700,000+ arrests enabled annually
• Launched city-wide autonomous security drones, poised to replace much “unarmed guard” spend
• FAA policy is main remaining barrier to fully automated deployment—autonomy is already there, e.g., one operator covers up to 30 drones
• Cost per citizen is surprisingly low ($22/year in best case) and proven to deter crime
• On humanoid robots: “Just way too expensive for most stores; wheeled robots get stuck or kicked over. Bipeds will ultimately win on efficacy—eventually.”

Matan Grinberg (Factory)

Timestamps: 151:03–160:24

• Factory’s “droids” now #1 on TerminalBench (coding agent benchmark), support all major LLMs not tied to a single model (“model agnostic”)
• End-to-end automation: not just code generation, but testing, docs, reviews—aimed at enterprise where software creation is more than just coding
• “Best software engineering agents will soon become the best agents for everything; code is how computers do anything.” (156:14)
• Announces $50M Series A with NEA, JP Morgan, Nvidia

Francis Pedraza (Invisible Technologies)

Timestamps: 161:02–169:29

• Raises $100M, scaling quietly to $134M ARR, profitability; newly “visible” after Meta/Scale deal
• “SaaS is like selling tools to bake a cake; we build the cake for you—custom AI deployments for enterprise/government”
• Epic Thremopylae analogy: beating Accenture/McKinsey “at the pass” by having the best engineering talent/platform

David Paffenholz (Juicebox)

Timestamps: 170:23–179:30

• $30M Series A for AI-powered recruiting: “Help companies win the talent war by surfacing talent they’d never otherwise find.”
• Combines diverse data sources (LinkedIn, GitHub, company data) with LLM search for new candidate discovery
• Sees “the race for talent becoming even more important as AI boosts individual leverage.”

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7. Product Launches & AI Feature Updates

Timestamps: 160:36–183:40

• OpenAI “Pulse”—A proactive, context-aware personal assistant in ChatGPT for Pro subscribers. “…keeps thinking about your interests, your connected data, your recent chats… You get a custom-generated set of useful info every morning.” (179:43)
• Meta AI “Vibes”—A short-form video generation feature within the Meta AI app, powered by MidJourney. Early signs suggest competitive video quality vs. Pika, VO3, etc.

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8. U.S.–China Tech/Trade, TikTok Deal, Geopolitics

Timestamps: 185:49–188:52

• TikTok Spinout: Trump signs order to greenlight TikTok’s US spinoff; ByteDance retains <20%. Oracle/Silver Lake consortium takes majority. “14 billion feels low… trading like a non-Meta, non-Google property.” (187:25)
• Algorithm Governance: Rumors suggest China keeps control of training, US does inference (“Algorithm with Chinese characteristics”).

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9. Bubble Parallels, Market Top, and Endnote

Timestamps: 69:33–74:43, 188:52–192:16

• Hosts debate similarity of the “AI bubble” to the dot-com bubble. “If this is so obvious… you’d think it would be priced in… but who knows, we’ll keep monitoring the situation.” (71:11)
• “Plateau of Productivity” vs. “Trough of Disillusionment”—are we eating from slop bowls or still on the way up?
• “Raise a fund at the top, don’t deploy, sell other positions… sit on a massive cash pile to monetize the next plateau.” (74:22)

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Memorable Moments & Quotes

• On AI dealmaking:
  “No one wants to be GPU-poor in 2025.” (26:03, John)
• On regulation and jobs:
  “You can build huge data centers in a few years now. That could create a precedent for other infrastructure.” (40:25, Jordy)
• On the meaning of industrial power:
  “America is capital rich, able to levy literally hundreds of billions for machine intelligence capex; we can afford to acquire whole groups of foreign talent for prices unheard of in their home countries.” (88:46, summarizing Arun/Rune)
• On AI agent productization:
  “The best software engineering agents are becoming the best agents for everything—because code is how computers operate.” (156:14, Matan Grinberg)
• On funding bubbles:
  “‘Raise a fund at the top, don’t deploy it, sell your positions, monetize the trough of disillusionment—then buy at the plateau of productivity.’” (74:22, John)
• On saving & spending:
  “If you build up a literal hoard of treasure, you open the safety deposit box and can see the wealth growing—it’s incredibly enriching, and it makes investing addicting.” (20:43, John)

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Additional Segment Highlights

• More AI Use Cases: Cache-based retrieval and cost-benefit of “deep research” queries discussed humorously (32:31–36:41).
• Job Market Reality Check: Andrej Karpathy’s post on why radiologists/software engineers are not being replaced—but their work is morphing. (43:00–48:17)
• Startup Pitches and Policing: Flock Safety’s journey from demo day arrest slide to drone-enabled crime prevention; lively chat about the future of humanoids/robots for public safety (123:13–135:55).
• Invisible Technologies Origin: “If the customer wants a cake, Silicon Valley will just sell them the tools and make them hire Accenture to assemble it; we build the cake.” (162:28–163:53)

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Key Takeaways

• AI infrastructure investment is scaling to unprecedented levels, with trillion-dollar projections and buildouts rivaling the GDP of major nations.
• The current AI “bubble” is likened to late ’90s dot-com exuberance—but with different risk dynamics due to massive cash on hand from big tech.
• The “real” AI economy is starting to trickle into durable, revenue-generating businesses—especially in overlooked sectors (janitorial, public safety, recruiting, field service).
• The US maintains a capital and systems engineering edge, even as China dominates process knowledge and manufacturing.
• AI-driven displacement of jobs is more complicated than theory suggests; new tools augment, not fully replace, skilled workers, at least so far.
• Businesses are converging on vertical AI/agent workflows, but true gain comes from full process automation (not just code-gen or chat).
• Geopolitical gamesmanship continues with US–China tech trade (TikTok, AI talent), but the deal flow and commercial value may matter more in the near term than who owns the best algorithm.
• Practical advice: focus on earnings and financial durability over hype; individual investors (and young founders) are cautioned not to get distracted by froth and FOMO.

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For Listeners

This episode is a must for anyone seeking to understand the scale, mechanics, and social undercurrents of the ongoing AI revolution—from the trillion-dollar facilities powering the tech, to the realities inside public safety, recruitment, and the enterprise. The guest interviews provide rare, practical perspective, while the hosts’ banter keeps the macro accessible and timely.

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Note: All quotes, timestamps, and attributions pull directly from the episode transcript for accuracy and context. Ad sections and non-content discussion have been omitted.

Transcript

[Jordy]

You're watching TVPN.

[John]

Today is Thursday, September 25, 2025. We are live from the TVPN Ultradome, the Temple of technology, the fortress of finance, the capital of capital. Good morning to everyone in the chat. Good morning to Gold Rock Raghav John, techno chief, of course. The post of the day is Alex Heath in Sources. I printed it. He says scoops. He's scooping. He says OpenAI is planning to bring ads to ChatGPT. Also in a message to employees, Sam Altman says he wants 250 gigawatts of compute by 2033. He calls OpenAI's team behind Stargate a core bat like research and robotics. Doing this right will cost trillions. He says. Well, hopefully he can save time and money with ramp.com time is money save both easy use corporate cards, bill payments, accounting and a whole lot more. All in one place we go. But I was thinking about what Sam Altman's projections have to say about the build out of AI. We're in pretty crazy times. Certainly lots of people are comping it to 1999. Lots of people are saying 1996. If they're bullish, the exact year matters a lot. I mean even 1999 I feel like.

[Jordy]

There were still some people are saying.

[John]

This time is different, 18 months, you know, but you know, the technology is even more magical than the Internet potentially. And of course the Internet already exists so it's easier to scale revenues as we've seen. And so my take on this was the AI deals are getting crazier obviously. This week we saw Nvidia is going to invest $100 billion in OpenAI, which in turn will be used to buy Nvidia GPUs. But we aren't fully in 1999 mode, even though a lot of people are saying that because big tech just has so much cash to fund the build out. And that wasn't quite what was happening in the dot com boom. In the dot com boom there was a lot more leverage. The price to Earnings ratios were crazy 10x higher on median. And so we are not in the crazy, crazy debt era. There's a little bit of that going on with Oracle, but it's not huge. The debt to equity ratios aren't huge. Insane yet.

[Jordy]

Yeah, yeah. Certainly players like Meta have tapped the debt markets. Right? They did an offering with blue out, but it is a small, you know, it's a, it's a. Some minority percentage of their earnings.

[John]

Exactly, exactly. Yeah, yeah, it's.

[Jordy]

Oracle went out this week as well for a $15 billion convertible debt offering. Yeah, debt offering. I'm sure that'll get filled quickly again because it feels relatively low risk even though they're forecasting well beyond what a traditional public company would be doing.

[John]

Yep. But the nature of the deals is getting more unique. It's different. I mean, we're seeing letters of intent now, which is just a very fuzzy.

[Jordy]

Or investments being announced that are still in discussion.

[John]

Exactly.

[Jordy]

This Nvidia OpenAI investment, if you read the print at the bottom of the.

[John]

It was a non binding letter of intent.

[Jordy]

Yeah. They're basically saying, we're talking about this.

[John]

Exactly.

[Jordy]

This is like the. But we haven't papered it yet for the deal.

[John]

Usually you go the opposite direction. You get the leaks, then you get the actual announcement. Once the deal is fully signed, the deal signs and then the press tour starts. But now we're putting the press tour a little bit earlier. And I keep coming back to YC Demo Day because at YC Demo Day, the letter of intent is often pulled out for companies that don't quite have the ARR or the DAUs to justify whatever they're trying to fundraise. And I wanted to revisit a story from YC Demo Day. My favorite YC letter of intent story, probably. Boom. Supersonic. Extremely. We've had Blake on the show multiple times. An extremely ambitious project to bring back commercial supersonic aviation. Basically bring back the Concorde. Boom was one of the first hard tech companies to go through yc. There were a few at the time. This was the Sam Altman era again. And they didn't really fit the current mold. They couldn't show a graph of DAUs or ARR, obviously, because they were. They hadn't even built planes yet. They were building, like plans to build planes. There's only so much you can do in three months.

[Jordy]

It was a founder bet.

[John]

Yeah, it was a founder bet.

[Jordy]

And Blake also product manager at Groupon.

[John]

Yeah, exactly.

[Jordy]

Got what it takes to take us back to hypersonic.

[John]

Yeah, yeah. So it wasn't.

[Jordy]

It sounds like I'm joking, but I'm totally not. When you see Blake's level of conviction and his inability to not go supersonic.

[John]

Yeah, but it wasn't like he was like former Lockheed and was spinning out some technology that immediately could just like piggyback on the shoulders of giants. Immediately.

[Jordy]

Like SpaceX, he had.

[John]

Yeah, exactly. He had to really build stuff from scratch and put the puzzle pieces together. And one of those puzzle pieces was a massive loi. And so he stood on stage and said, you know, you're going to think this is a sci fi project, you think this is a moonshot project. But the one thing that I can tell you is that I have an LOI. It's non binding, but it's for $2 billion. And so that was what went on the screen I think around there. And he had gone to Virgin, talked to probably Richard Branson and Virgin had optioned 10 airplanes in a non binding LOI and the deal value was roughly 2 billion. And so if it was fully exercised.

[Jordy]

Now, and I think, I think people generally believe this is a kind of business. It's like if you build it, there will be demand.

[John]

Exactly.

[Jordy]

There will be demand from the airlines, there will be demand from consumers.

[John]

But having the LOI understand means it shows that you can go in that room and convince them that if you build it, they'll buy it. And then, and then that leads to investors being saying, okay, well I will back you. And so booms had ups and downs, they had a down round. A lot of YC folks came back in, invested in the company again just to keep it going. And Blake's still at it. He's getting regulatory approvals, which we saw, and building planes one at a time. He's actually flying. And as loose as non binding Lois can be, they still help pull forward the future and can be a useful tool in making everyone around the table feel like there's mutual buy in. Because everyone's at least said, if this happens, I'm in. If that happens, I'm in. And if everyone commits and if the capital partners commit and the customers commit and everyone commits, then the thing should actually happen. And so the boom story for me underscores how unclear the path of technological development can be. Sam Altman is now guiding toward 250 gigawatts of compute at OpenAI by 2033, which is a staggering number. We saw a post which we'll get into. A single gigawatt data center is many football fields long visible from space. It basically terraforms the earth. And while many people are writing off Sam's projection as merely attempting to win the contest of saying the biggest number, his projections aren't entirely new to the world of AI compute forecasting. Leopold Aschenbrenner predicted a single training run cluster around 100 gigawatts coming online by 2030. So three years earlier, 1/3 the size just two years after. And then Leopold predicted in 2028 that there would be the first 10 gigawatt cluster, 250 gigawatts by 2033 lines up with that. But wow, America will look dramatically different if that comes to fruition in 2023. For reference, two years ago, the US was producing an average power in total for everything, not just AI of 485 gigawatts. And so Sam is saying that just OpenAI, if everything else stayed the same, would be one third of all power consumption in America for that entire year in 2033. Now, obviously, everything else is growing and there are other labs and you would imagine that Amazon and Anthropic keep up and Google and DeepMind keep up. And so it will be an entirely new chapter of the economic story.

[Jordy]

What are some of Elon's promises again? Or goals?

[John]

Yeah, I was talking to Tyler about this because I mapped out the power projections. This is straight lines on a log graph. Of course. Leopold is the taller bars here. Jordi, you can see this. And Leopold is projecting logarithmic growth, which is exponential growth. This is. Every tick on here is an order of magnitude bigger for gigawatts. And you can see Leopold is projecting a straight line on a log graph, basically exponential growth continuously based on, you know, how he's mapping out the few dates that he gave. He didn't give projections for every single year. Sam is actually. It's so funny because he's. The Sam story is framed as like 250 gigawatts by 2033. This is so insane. But he's actually sort of guiding towards deceleration. Like, you can see Sam's. Sam's darker bars here.

[Jordy]

He's being humble.

[John]

He's being humble relative.

[Jordy]

Doesn't want to. He doesn't want to, you know, relative.

[John]

To some other folks in the category. So, Tyler. Yeah. What did you find? Did you see anything from the other labs?

[Tyler]

Yeah, so I was trying to figure out, like, what all the other labs are doing, like what they look like on that graph. So none of them have done real kind of projections. Like, no one has said, like, okay, by 2035, we're going to have 250 gigawatts. Anything like that? Yeah. So for Meta Zuck, the big number that you could use for this is his at the White House dinner. 600 billion through 2028.

[John]

Yep. So it's an aggregate number. Yeah, but you have. But like they're only doing 50 or 60 now. And so to get to 2028, that's only three years away. So you have to do 50, 100, 200, 400, something like that. It has to ramp really Fast.

[Jordy]

Yeah.

[Tyler]

I was trying to figure out like what does that actually mean in gigawatts? Like what is the actual price that.

[John]

You could get out of convert the dollars to wattage.

[Tyler]

And so basically I used. I looked at Colossus 2, which is 1, maybe the 1 gigawatt. And then estimates are. This is like very like non accurate. This is totally guess, but like maybe somewhere around 15 billion.

[John]

Okay. To build that order of magnitude, 10 billion something. 10 to 20 billion. Let's keep it super vague. For a 1 gigawatt.

[Jordy]

Yeah.

[Tyler]

And so, so with 600 billion you.

[John]

Can do like maybe like around 60 gigawatts, 50 gigawatts.

[Tyler]

Yeah, like something in that if you.

[John]

Were to just copy and paste a bunch.

[Jordy]

Yeah.

[Tyler]

And, but that's, I mean that's like Elon, like Elon cruising. The most efficient. Like this is the fastest of all time. Like it took them like six months to get to 300 megawatts, which is like double the next fastest build out, which was the Crusoe OpenAI1.

[John]

Yeah.

[Tyler]

So I think it's probably. That's a little aggressive.

[John]

And Zuck's number was at the end of 2028?

[Tyler]

Yeah, it was through 2028, I believe.

[John]

Yeah. I mean the end of 2028 for, for Sam and Leopold, they're more thinking around 10 gigawatts, I think. So interesting to see if Zuck's projections kind of outpace what's there. I don't know.

[Jordy]

And you guys saw today, Core Weave and OpenAI expanded their contract to a total contract value of 22.54 billion.

[John]

22.4. Okay.

[Jordy]

Six and a half billion.

[John]

So it's a deal for ants.

[Jordy]

Praying and praying.

[John]

Yeah.

[Tyler]

Another thing you could use besides Leopold is the AI 2027 numbers.

[John]

Yeah, I was wondering about those.

[Tyler]

So if you look at those like once, like in once you get to 2027, after that the numbers like explode. It's like.

[John]

Oh yeah, that's the fast takeoff.

[Tyler]

It's like 30 trillion on. On data centers. Yeah, but, but through 2026, 2027, it's like around like 5,500 billion a year. And that's like 500. I think it's like 650 in kind of the end of 2027. So like you could imagine we're like reasonably on track for that considering Meta alone is doing around 600 over 20.

[John]

Yeah. If you aggregate all the labs.

[Jordy]

Yeah.

[Tyler]

So I think that's like fairly reasonable. So. Yeah, it's hard. I mean people are like. If you look at the timeline. Everyone is like okay, we're at the top. Like this is so bearish. But if you look at a lot of people who are like super bullish on AI, we're still broadly on track I would say.

[John]

Yeah. This is what, what Roon was saying how like everyone, all the richest people have voted and they've all said we're going all in, we're putting all the chips on the table.

[Jordy]

Not about immediate roi.

[John]

Yeah. And I mean honestly like if it's funded with cash and equity and not too much debt, there's a world where like you take the hit of maybe some stagnation and you get through and you are more of like the Amazon story than the next our story or I forget what. Yeah, I think I always forget the names of the companies that went away.

[Tyler]

Even in the bear case it's like there's the book Boom Byrne Hobart.

[John]

Yeah.

[Tyler]

Which is like bubbles are good because broadly like they don't affect like the normal economy because it's like all the.

[John]

It'S like the most risk on. Yes. Interesting takeaway from boom was that the common narrative is that like retail gets hurt the most in a bubble but in fact it is not retail. It is the wealthy that get the biggest haircuts because they are the most leveraged at the peak of the bubble and they have the most wealth to compress. Whereas the average American through the number of bubbles that Bernd Hobart analyzed is not super levered long. The most risk on asset at the time of the top. Jordy, what were you going to say?

[Jordy]

So there's a company called Iren. The company pivoting from bitcoin mining to being an AI data center company. Their stock is up tremendously. Andrew Wilkinson hit the timeline a couple months ago. At this point I think it basically like said I read it as financial advice but he was basically making his case. The stock is up massively since he came out and made the case for why he thought they were undervalued. He's. The current share price is $48. It's up. Let's see. Exactly. It's up from around like I guess 1718 I think when he more than double, triple. So it's up massively. He's now calling for another 7x because he says Iron is about to control more power than the Hoover Dam. 2,910 megawatts at 2.9 gigawatts. And so anyways he's now calling for the company to. Yeah, again 7 7x. Again he thinks that $300 per share could be a layup.

[John]

Yeah.

[Jordy]

He lays out a potential bear case. Right.

[John]

Okay.

[Jordy]

Given that he says if nobody want. If AI turns out to be a nothing burger and nobody wants Iron's Power LAN data centers and servers, that could be bad. Unable to. If they can't really capitalize on the demand because they just don't have. They're not. The data centers aren't configured to the level that they need to be to be great assets for either hyperscalers or other AI companies. So lays out some potential downside scenarios. But I do wonder if we'll see some of these companies that are trying to take a crack at actually competing with the hyperscalers as like cloud, you know, serious cloud providers. I do wonder if some of these companies will get to the point where they have a lot of energy and they basically just have to sell to another more sophisticated player that can actually take over and turn it into, you know, help it realize its potential.

[John]

Yeah. The chat is asking for an update on TBPN Merch if it will be available for our most loyal soldiers in the chat. So we gotta step it up.

[Jordy]

Yeah. We gotta figure out how to, how to make this happen. We. The first run of Merch, we didn't want to sell it. We had never made Merch as a company before and it didn't feel right to sell something that is not our core competency. But we had a meeting yesterday talking about the next run of Merch and getting that available by the beginning of this coming year. So stay tuned and thank you for your patience.

[John]

We gotta get restream on some merch one livestream. 30 plus destinations. They make our stream possible every day. Multi stream and reach your audience wherever they are. I had a friend that asked for some advice. If you're making money during the bull run, what should you do if you feel like you're at the top? What's the safest portfolio for a young person these days?

[Jordy]

Rotate into watches. Watches go entirely into Swiss technology.

[John]

Like if you're, if you're, if Your comparison is NFTs, like. Yes, like the watch market did actually draw down post NFT crash and there.

[Jordy]

Were people that converted NFT earnings into. And they probably did better.

[John]

I feel like the, what was it the Rolex market sold off by like 30% or something. But I mean a lot of NFTs.

[Jordy]

Went to zero still above retail and for most watches.

[John]

But yeah, I mean it feels like the, like there is a. There is, there's the existence of a risk curve. And the, the, the, the companies that are trading at the highest, you know, you just have to go back to the basics of the Warren Buffett stuff of like company with no earnings, trading at tens of billions of dollars. That's going to be the most dangerous, they will be most punished in a, in a down economy. Whereas a hyperscaler that still has enterprise licenses and huge ad business is going to fare better even if they get a haircut. We saw this with Meta during the last cycle. I mean, they traded down a huge amount, like almost 50% off the metaver, but built back up pretty quickly on the next wave. And then of course you got gold, you got bitcoin, you got real estate, you got plenty of things. But what would you counsel someone in their twenties making decent money to do with excess earnings?

[Jordy]

Excess earnings? I don't know. I think that the young millennials, Gen Z are overly obsessed with investing. It's all that a lot of people can think about and it ends up being a massive distraction from just getting better at your craft, your career, and just increasing your earning power. So I think the number one, I mean, I talked to the guys on the team about this. We're obviously talking about different private companies, different investments all day long on the show. And so it's easy to get kind of fixated and get kind of FOMO around this stuff. But anybody knows if you've made a sizable investment or, you know, if you've made an investment ever, that's like double digit percentage of your net worth and it's trading liquid that can be just.

[John]

Such emotional roller coaster.

[Jordy]

Yeah, just such a massive distraction from what, what you should be focused on in your 20s, which is just increasing your skill set, building your, building your network, like figuring out how you can increase cash flow. So. Yep, I don't know. You had a.

[John]

Well, yeah, my take was there's huge alpha in not even picking the correct asset, but just setting up your life so that the money actually gets into the asset before you can spend it. Yeah. And so when I started making Money in my 20s, every time I would get paid, I would go to the bank, I would take out something like $1,000 of cash and put it in a safety deposit box. And that just built up over time and I realized that if I was out on the weekends, I could not access it because you have to physically go to the bank to get the cash. And so I realized that if you're out with friends and they're like, oh, like, you know, should we, you know, spend all this money on whatever, if you have it in your checking account, you're like, yeah, no problem. If you have it in your savings account, it's like supposed to be in savings but you can just click one button and move it over.

[Jordy]

I remember being at like a teenager and realizing that your savings account was like literally one transfer away from checking.

[John]

It's ridiculous.

[Jordy]

Wow. This takes a lot of willpower to actually make it. Savings versus spending.

[John]

Yeah, exactly. Exactly. So if you build up a literal hoard of treasure, hey, it's incredible psychologically because you open up that safety deposit box and you can physically see the wealth growing, which is incredibly enriching. It's incredibly satisfying and it makes investing very much addicting. But even just going into your payroll provider and route, like usually you can route your paycheck to some sort of investment platform. Maybe public.com investing for those who take it seriously. They got multi asset investing industry leading yields trusted by millions. And then you can set up like Automated Buys on ETFs if you like the Mag 7, if you like gold, if you like bitcoin, like whatever you want, you can, you can have automatic investments happening so that you're not spending all your time trying to become like a hedge fund ideally, unless that's actually your life's work.

[Jordy]

The service that you would have liked is somebody you, you go and you give them cash and they even. They use a movie cash to give you, to show you the pile they take that they actually invest it.

[John]

That's a good service. But to access it you have to.

[Jordy]

Go, you can go look at the cash. You can, you can.

[John]

The physical key was really, really great. It was.

[Jordy]

I've never had one of those.

[John]

Yeah. Safety deposit box is underrated.

[Jordy]

Underrated. Do they still make those?

[John]

They do, yeah.

[Jordy]

Really have a little like a mouse. You have little.

[John]

It is, it is somewhat rodent coated to just be hoarding. Dragon coated potentially, you know, to hoard.

[Jordy]

Your pile of gold or could kind of cool and mysterious if it's all over the country. You know, like you've got a little stash in Dallas. You know, a little. Keep some in the bay.

[John]

Yeah. What do you think, Tyler?

[Tyler]

I know a lot of friends who have like a bitcoin like wallet and then they have the seed phrase in different safety deposit boxes all over the state. So they have to drive, it's like four hours to drive to every single bank.

[John]

That's diamond hands, baby. They're not paper handing anything. And so if they're just continuing to contribute to that the trick is that the cash flow typically comes in like monthly or every other week installments. And so how do you actually set up that so that it's happening on a regular basis but still inaccessible? That's a little bit tricky. Maybe someone can build it. Maybe someone can use Privy, our wallet infrastructure. Partner wallet infrastructure for every bank. 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. Barely. AI says. Looks like Nvidia and OpenAI will be paying zero investment banking fees for their $100 billion partnership.

[Jordy]

Some.

[John]

Some hit me with the so sad for the investment bankers we talked to carried no interest.

[Jordy]

He was telling us Wall street in. Cut Wall street in.

[John]

Come on, break us off. Break off Morgan Stanley. Make break off Goldman Sachs.

[Jordy]

Those guys need to break. It's really impressive. I mean it's just these sound deals at this scale is very cool.

[John]

Yeah, I mean that's what everything is. We talked about this with Nvidia, like spending like a few million dollars lobbying in Washington. But Jensen's there and founder to president, founder to founder, like that's the nature of these deals. It's always the nature of these deals.

[Jordy]

You got to price in the Gulf Stream expenses with the, with the lobbying fees.

[John]

You can tell more about how a company is doing in D.C. by where their Gulf Stream is parked than their lobbying budget. For sure. Where's the Gulfstream parked? Has it been at Mar a Lago? Has it been in dc? That's what's moving the needle these days. This screenshot says Altman and Wong negotiated their pact largely through a mix of virtual discussions and one on one meetings in London, San Francisco and Washington D.C. with no bankers involved. According to people close to the talks who declined to be named because they weren't.

[Jordy]

This was a multinational deal.

[John]

It was. They were going all over the world. London. They were probably talking about it in white tails. Remember they were in white tie and D.C. who knows, they might have been chatting to each other. I don't think they were both at Hill and Valley, but they might have been there overlapped at something or other. Maybe the inauguration. The arrangement calls for Nvidia to invest 10 billion at a time in OpenAI.

[Jordy]

10 billion dollar slugs.

[John]

They have 60 billion in cash and cash equivalents right now. So they can. Without generating any more free cash flow. They can just keep paying.

[Jordy]

That would. If you were Jensen, would you, would you lever up massively? Maybe become just entirely indexed to each other. Right.

[John]

I mean it's it's happening.

[Jordy]

Say if we go down, we're going down together.

[John]

There's more, there's more news about the AI K Retsu that's coming together. OpenAI partners with Oracle and SoftBank for five new US data centers.

[Jordy]

Seven gigawatts is and what's crazy is there's still, while they're doing this, yeah, they're doing deals with Broadcom, they're doing deals with Oracle, with Core Weave, Microsoft.

[John]

Still, I mean they're buying from everyone. It's. No one wants to be GPU poor in 2025. Going into 2026, you want to be keeping the GPUs cool. Not on fire. Not on fire. So Wall street journal says OpenAI laid out its vision for a vast 1 trillion.

[Jordy]

I think it's better if, if you, if you're scaling GPUs but keeping them on fire. If they're not on fire, partners are going to be looking and saying I.

[John]

Don'T want cold GPUs sitting there idle, just eating a hole in your balance sheet. You want to be maxing those tokens out, getting paid. Showcasing the development of a Central park sized complex 180 miles west of Dallas. This is from two days ago by Berber Jin in the Journal. OpenAI unveils plans for seemingly limitless expansion of computing power in Texas. Prairie Startup showcases ground zero of AI Boom and its plans to shepherd 1 trillion in infrastructure spending. So the trillion dollar number is getting thrown around for the first time because Stargate was originally 500 billion and now we're up at 1 trillion. Is that right?

[Jordy]

Yeah. And remember, even at 500 billion, Elon was basically saying hey, nobody involved here actually has the cash to do this.

[John]

Just wait until these stocks run up and Oracle's up 300 billion.

[Jordy]

Larry says hold my beer, I'm good for my 10. Hold my green juice.

[John]

I'm here for, I'm, I'm good for my half trillion.

[Jordy]

But yeah, once you get into the trillion dollar range, you're approaching the GDP of, you know, some, some serious countries. Right?

[John]

Serious countries. OpenAI disclosed it would ultimately need more than 13 times the computer the computing power of its first nascent site which is raising which is rising out of the Texas brushland. Frenzied construction here has turned a sea dirt into eight hyper futuristic data centers bringing online roughly 900 megawatts of capacity. More than 6,000 workers labor on the project each day, including electricians, plumbers and steel welders. Alternating between two ten hour shifts seven days a week. Wow, they are, they're. What is that, 2 to 10? 7? 2, 10 7. 2am to 10pm Seven days a week. Something.

[Jordy]

Yeah. People in the data center business see.

[John]

People with computer, that'd be nice.

[Jordy]

Computer jobs saying, oh yeah, I do996.

[John]

Yeah. I mean, I wonder if they have two shifts, 10 hours, does that mean they have two crews that are working 70 hour weeks? Are people taking days off or are they rotating their shifts so that you get a day off every quarter?

[Jordy]

I think they would get into pretty hot water. I don't think you could like run and say you're working seven days a week forever. I don't think employment law works like that.

[John]

Gray towers of gas turbines have dotted the landscape since the spring, offering backup power. On a tour with reporters Tuesday, Oracle and OpenAI executives showcased the 1,100 acre site calling at the largest AI supercomputing complex in the world. Outside, workers wearing dust masks and sunglasses shuttled around in buggies trying to shield themselves from the 100 degree heat. One of the buggies flew a flag that said, jesus is the answer 1100 not very AGI pilled. I thought we were getting God in a box. What's going on? Just Eliezer Yudajkowski shows up. He's like, no, no, no. Like they're building God here. You're building God. You're doing the thing. Like, what are you doing here? There was literally nothing here a year ago, said Anuj, who works on the OpenAI computing team. They also announced five new data sites, data center sites across the US built with Oracle and Japanese tech conglomerate SoftBank. It said the new facilities would help bring online nearly 7 gigawatts of power, enough for almost 8 million homes. Enough for for a lot of API calls from Devon from Cognition, the makers of Devon, the AI software engineer, crush your backlog with your personal AI engineering team. Company executives made it clear that the Abilene site was just the beginning, noting they envisioned a need for more than 20 gigawatts of computing capacity to meet the explosive demand for ChatGPT, which now has more than 700 million weekly users. I was laughing about, you know how in the ChatGPT if you fire off pro like GPT5 Pro, it kind of thinks for like 20 minutes and everyone's saying like, oh yeah, this is good. Like we want the agents to be reasoning for longer and longer. I feel like there's an opportunity for some startup just to be like, we've cracked the code, our model reasons for two days straight. So send us Your request and we'll get back to you in two days.

[Jordy]

And the agent just like is pretending.

[John]

So it's just like, yeah, it just.

[Jordy]

Has a progress bar, twiddling at some until the last 20 minutes and then.

[John]

Just starts going, no, no, no. Of course what you do is you, is you have the loading bar there and then secretly you have a human doing the work and you have a human that's like dealing with this.

[Jordy]

Well, I think the thing is like, the longer, the longer the period, the higher the expectations. And I just don't know that. I don't. I think that. I guess the thing that I would want to know is like if you're running a Deep research query for 20 minutes and then if you decide to run it for two days, how much better is it? Right.

[John]

Yeah.

[Jordy]

If it's 10 times better, could potentially be worth it for different types of tasks. If it's 30% better, is it worth the wait?

[John]

Yeah. There is a world where you just route it to the human. There's also the world where for the really low.

[Jordy]

Don't encourage this. People have already gotten into trouble.

[John]

Yeah, they have, they have. The other funny idea is for a lot of the, there have to be a certain set of queries that just get asked the same, like every single day. And they should just store those in a database and cache them. Because you have to imagine that every single day someone is asking like just going to chatgpt and lighting the GPUs on fire to just ask like, what's the capital of Illinois? Or what's the capital of California?

[Jordy]

Can you run a GPT like pro Deep Research report for what is the capital?

[John]

You can do it for anything. Yeah, you can. You can go to Deep research and fire off 20 minutes of compute and say, what is the capital of California? Answer in just one word. And like, it will just think for 20 minutes and then spit out Sacramento.

[Tyler]

Like it won't think that long. It like thinks based off how hard it is.

[John]

No, Deep research will.

[Jordy]

I just said what is the capital of California? Answer in one word.

[John]

And it's deep research.

[Jordy]

Yeah, it's doing a deep research query.

[John]

Let's see how long this takes. It's not going to come back in two minutes. It's going to cook for 10 minutes.

[Jordy]

All right. I was a little bit late, but I just started a timer.

[John]

Okay. What do you think?

[Tyler]

Also, there's a sense where the embeddings of facts is basically just the model already. You can just think of a model as a compressed Version of the Internet or at least non reasoning models. Yeah, so it's kind of like.

[John]

But wouldn't it be even more compute efficient to just do fuzzy lookup of of these questions and see if they sound.

[Jordy]

Siobhan in the chat says cache based retrievals are. Oh yeah, but apparently not here because GPT5 Pro, it's fully implemented. Okay. Okay. It reasoned for 47 seconds.

[John]

Okay.

[Jordy]

And it.

[John]

This is Pro. You didn't do deep research though. I want to see you turn on deep research and do it.

[Jordy]

Well, this is the Pro, which is research grade intelligence.

[John]

No, no, no. That's not the deep research I need thinking. No, no, no, no. You need to click on the little plus button next to the chat box and then check the box on deep research. Do they still have this? I don't know. They might have deprecated this. I think it's still there.

[Jordy]

It's still there. Still there. Okay, I'm doing a deep.

[John]

You're doing deep research.

[Jordy]

No, no, this is good. This is good.

[John]

Really verify.

[Jordy]

Just to confirm, are you asking for the current capital of California or are you interested in historical capitals as well? Let's see current capital.

[John]

Tell it to also design a a website in Figma. Think bigger, build faster. Figma helps design and development teams build great products together. Get started for free. While we're waiting for that, let's keep reading from the journal. Each gigawatt of capacity is expected to cost roughly 50 billion. Tyler. 50 billion per gigawatt. That's the number in the journal, meaning the company is laying the groundwork for at least 1 trillion in infrastructure spending. Demand is likely to reach closer to 100 gigawatts, one company executive said, which.

[Jordy]

Would be 5 trillion, which is roughly the GDP of Germany or Japan. Yeah. GDP of Japan is 4 trillion. Germany is 4.6.

[John]

Good luck. Good luck. Germany and Japan, you're getting left behind. You're part of the permanent underclass now. It's over for you.

[Jordy]

I feel bad for lighting the GPUs on fire for this. It says got it. I'll confirm the current capital of California for you and get back shortly.

[John]

And it's doing it's cooking. This is the real pitch for the.

[Jordy]

I'm getting my money's worth.

[John]

Brandon Jacoby in the chest is breaking. Jordy discovers the UX issues of every foundation model company.

[Jordy]

Fix it, Brandon.

[John]

Yeah, yeah. Aren't you doing consulting now? Brandon, you gotta get in the trenches. All these folks.

[Jordy]

If the labs haven't hit you up yet.

[John]

If someone who spends 10 hours a day studying this, reading Wikipedia. Just like how many drops of water did this use? How many fish had to go find some other stinks?

[Jordy]

Yeah, it should come back. And it's like thought for 15 minutes, put. Made two species extinct.

[John]

Lit. Lit 7 gallons of diesel on fire.

[Jordy]

Okay. It's checking all the sources.

[John]

It's good. I like a detailed report. I like to know that the AI did its job. Don't just sit there, clanker and riff off cash based retrieval. I want the deep research every single time.

[Jordy]

Even for one word fact.

[John]

Even for one word fact. I want you to be sure. I don't want any hallucinations.

[Jordy]

Well, I mean, this is a tough question too. A lot of people that aren't from the west coast or the United States would say, yeah, what's the capital of California? Yeah. San Francisco.

[John]

I was using this as an example about.

[Jordy]

I remember being. I must have been like 7 years old asking, like figuring out that Sacramento was the capital of California. And I thought that was the funniest thing ever.

[John]

Yeah, it is. It is hilarious.

[Jordy]

All right. It got it. It thought for 101 seconds.

[John]

That's not that long for deep research.

[Jordy]

It went for four sources. It did 19 searches. So this is why I can't trust, you know, everybody keeps screenshotting these Google trend reports.

[John]

Yeah.

[Jordy]

I'm not sure that Google has figured out how to exclude agents because this just did 19 searches for a single fact.

[John]

Yeah.

[Jordy]

And so if you're looking at the growth of queries on Google, you would think. And if a lot of people are asking this kind of question, every single keyword is going to be spiking.

[John]

Well, if you want to get your brand mentioned in ChatGPT, you got to go to profound.

[Jordy]

That's right.

[John]

Reach millions of consumers who are using AI to discover new products. Products and brands. Get a demo. I don't think we've figured out the final form of what financing for COMPUTE looks like, said Sam Altman. But I assume like in many other technological revolutions, figuring out the right answer to that will unlock a huge amount of value delivered to society and delivered.

[Jordy]

To OpenAI shareholders for sure.

[John]

Yeah. It is an interesting question because Dario was talking about how each training run looks great by itself, but when you put them all in one structure, it looks like you just have this never ending money pit. Because you spent $100 million on a training run, you made a billion over the next two years. You spent a billion on a training run, you made 10 billion over the next two years, you spent 100 billion on a training run, you make a trillion over the next year and there's a question of okay, how long until it just completely maxes out? Are there diminishing returns to these things? But even if the trends hold, you still wind up with this ever growing money pit that should act as like some sort of slowing down force.

[Jordy]

You would I think when you when you dig into this quote I don't think we figured out the final form of what financing for compute looks like. The question is like will this actually be a novel financial instrument or it will be remixing something that Wall street has used in mortgages.

[John]

Maybe it's debt, maybe it's debt, who knows.

[Jordy]

GPU backed securities.

[John]

The Tuesday announcement made it clear that SoftBank, once seen as a formidable OpenAI funding partner, has scaled back its ambitions. In the data center out which the Wall Street Journal reported in July, three new sites, one located near Abilene, another north of El Paso in New Mexico and a yet to be announced Midwest location combined with an expansion to the Abilene complex will be capable of delivering 5.5 gigawatts of capacity. Those will be built by Oracle. The other two smaller sites, one in Lordstown, Ohio and the other near Austin, Texas will be built in partnership with SoftBank and generate 1.5 gigawatts over the next 18 months. The first completed data center called Building One painted a pristine white that contrasts with the reddish dirt surrounding the site is larger than two Walmart super centers. Doesn't feel that big to me but certainly huge entering yeah the 1100 they.

[Jordy]

Said 1100 acres earlier in the article. That's under 2 square miles.

[John]

It is. Yeah. It is crazy how compressed this is huge when you're walking around but you know we're not in okay we're losing Yosemite over this.

[Jordy]

Yeah yeah we're not in the you.

[John]

Know in the full tarot forming I mean Elias Sutzkever told the what it was the San Francisco Chronicle that we could he could imagine a future where the entire earth is covered with solar panels if the trends continue.

[Jordy]

Gabe, Gabe in the chat says shout out to Lordstown Ohio factory used to build Chevys. Yeah your thesis or take re industrialization is happening. It's a lot less jobs and it's data centers.

[John]

Yep.

[Jordy]

But the white pill there might be that if we can build big data centers really quickly at the scale that traditional infrastructure projects would have taken 10 plus years. If we can do that in a few years it could create a precedent where somebody could decide, you know What I'm going to build this, this new.

[John]

Rail line in two years is a Walmart Supercenter. Really 1 mile long QSBS rollover saying that, that the, that the building's two miles long?

[Jordy]

Well, no, I was saying, I was saying the site is, is 1100 acres total. It's not. Which is like one 1.7 huge square miles. So obviously massive. But I don't think the building itself is anywhere near that.

[John]

Well, fiber lines snake across the data centers and underneath the ground, allowing the AI chips called GPUs. In case you were wondering, the Wall Street Journal's got you covered to talk to one another and complete requests more quickly. Proponents of infrastructure boom say it will bring hundreds of thousands of jobs and revive American manufacturing. In January, OpenAI unveiled a $500 billion dataset data center project, Stargate. We know about this. The reality is more mixed. While data center providers provide plentiful temporary construction jobs, far fewer people are needed once they, once they are built. Abilene Mayer said residents had mixed feelings about the site and its power and water usage, though some of the concerns have been assuaged. An Oracle executive said there will be roughly 1700 permanent jobs on site one the construction.

[Jordy]

I think the things that ends up being a little bit. Yeah disappointing is, is these projects get announced and they're saying we're going to spend $20 billion here and then we're going to create like a thousand jobs or we're going to create 300 jobs. And that is very significant. That will be good for the local economies in these regions. But not. It's not, hey, we're. Yeah, we're replace. You know we lost 87,000 manufacturing jobs last month. I think it was. We're not really making a dent in that data center.

[John]

It takes a lot. There's more news on the job displacement stuff from Andre Karpathy. He has a good post breaking things down. But first let me tell you about graphite.dev, code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster and get started for free.

[Jordy]

So Andre Karpath, that's debating, by the way.

[John]

What is Chad debating?

[Jordy]

They said Jordy is a cat, I'm a Cadillac. Not true.

[John]

John has a Cadillac.

[Jordy]

Somebody said I seem like a Dodge guy.

[John]

Hellcat, srt. I love it.

[Jordy]

Yeah, not quite. Never had a Dodge. I had a Ford Raptor which I loved. Was not super practical but it was a car that I wanted as a child so I had to get it at least once.

[John]

Yep. So Andre Karpathy says AI is, isn't replacing radiologists. Tyler, do you remember this prediction?

[Jordy]

Yeah.

[Tyler]

Was this Hinton?

[John]

Hinton, yes. Years ago, this was. This was what, 10 years ago now or something? Yeah.

[Tyler]

Because this was based off just like image classification. So this was like early on, like CNNs, like this was probably mid 2010s.

[John]

Yeah. So the expectation was that rapid progress in image recognition AI would delete radiology jobs, as famously predicted by Jeff Hinton now almost a decade ago. In reality, radiology is doing great and is growing. So what's going on here? Obviously, image recognition is fantastic. These algorithms are remarkable and there's been a ton of progress. So Andrej Karpathy says there are a lot of, in his opinion, naive predictions out there on the imminent impact of AI on the job market. For example, a year ago Andre was asked by someone who should know better if he thinks that there will be any software engineers still today, like a year from now, like this is how accelerationist this person was. And Andre says, spoiler, I think we're gonna make it. This is happening. This is happening too broadly. This post goes into detail on why it's not that simple using the example of radiology and I thought this was really, really interesting and it obviously applies outside of radiology. So first off, the benchmarks are nowhere near broad enough to reflect real actual scenarios. So even though you can classify cancer in a radiology environment with a whole bunch of training data very reliably, there's still tons of edge cases where having a human in the loop is advantageous. And then just in general, the job is a lot more multifaceted than image recognition. Like if you just think about the job of a radiologist, just it's not purely just look at image detect cancer, look at image detect cancer.

[Delian]

Look at image detect cancer.

[Jordy]

Yeah. Can you imagine if you were getting, God forbid somebody's getting seeing, going and getting seeing a traditional office of a radiologist and they're just watching a television screen that's reporting, telling them that something is wrong with them, using a voice model to explain it and then just.

[John]

Like, no, they're just in hinge mode. Swipe right if it's, if it's cancer, swipe left if it's not and they're just sitting there swiping all day. Obviously that's not the job of radiologists. There's so much more. They were doing research on what's changing, integrating new information, talking to different patients about all the different signals, what they could Be doing what they could be putting in their body, how are they feeling, what medicines they're taking? There's a ton of different stuff that they're probably involved in.

[Jordy]

Yeah. Anytime anyone gets any type of lab or report from a doctor, the first thing you want to do is talk to somebody that's an expert on that, your doctor, and have them explain it to you, the implications, et cetera, good or bad.

[John]

And then he highlights deployment realities. So regulatory, insurance, liability diffusion and institutional inertia. Like it just takes time to roll these technologies out. But the last one is super interesting to me. He cites Jevons Paradox. So if radiologists are sped up via AI as a tool, a lot more demand shows up. And so if all of a sudden the cost to get a scan or the time that it takes to actually do the scan drops, everyone will say, well, I want to be scanned all the time. I want to be on top of any sort of development medical that could be detected by a radiologist. And so he concludes by saying, I will say that radiology was, in my opinion, not among the best examples to pick on in 20. Too multifaceted, too high risk and too regulated. When looking for jobs that will change a lot due to AI on shorter timescales, I'd look in other places. Jobs that look like repetition of one rote task, each task being relatively independent, closed, not requiring too much context, short in time, forgiving, the cost of a mistake is low and of course automatable given current and digital capability. Even then, I'd expect to see AI adopted as a tool first, where jobs change and refactor more monitoring and supervising than manual doing, etc. Maybe coming up we'll find a better and broader set of examples of how all of this is playing out across the industry. About six months ago I was asked, I was also asked to vote if we have if we will have less or more software engineers in five years. Exercise left for the reader. What do you think he meant? Tyler, what do you think more? Yes, he thinks the number of software engineers will increase, but they will be using AI as a tool to lever. Yeah.

[Jordy]

I wonder if anybody's done a study on how many more developer people that have done software development this year versus last year. Has to be significantly more. Just because if you're using replit now you are a software engineer, somebody might want to get technical and say, oh well, if you're just prompting, you're not really software engineering. But how different is that from somebody getting their start and copying pasting lines of Code.

[John]

Wow. We got some news about TikTok. That China has more or less signed off on the deal and it has sent Larry Ellison oracle skyrocketing on polymarket to an 89% chance of acquiring TikTok. This will be an interesting story to see where it actually lands. Of course, you can go to polymarket if you want to keep monitoring the situation, as always.

[Jordy]

Should we talk about this new Elon lawsuit?

[John]

Yes, new Elon lawsuit.

[Jordy]

Elon Musk is. Andrew Curran is on the timeline sharing Elon Musk is suing OpenAI again. Second suit, this time for alleged misappropriation of trade secrets, intentional interference with pro perspective economic relations and unfair competition. So they say the desire to win the artificial intelligence race has driven OpenAI to cross the line of fair play. OpenAI violated California federal law by inducing former XAI employees, including Shu Chen Lee and Jimmy Frater and a senior finance executive to steal and share xai's trade secrets. The copy. And again, this is the lawyers from the complaint, right? The lawyers are not using ChatGPT.

[John]

Doesn't seem like it.

[Jordy]

This is handmade by hook or by Crook. OpenAI clearly will do anything when threatened by a better innovator, including plundering and misappropriating the technical advancements, source code and business plans of XAI. What began with OpenAI's suspicious hiring of Xu Chen Li, an early XAI engineer who admitted to stealing the company's entire code base. Wow, that's bold thing to admit. Has now revealed a broader and deeply troubling pattern of trade secret misappropriation, unfair competition and intentional interference with economic relationships by OpenAI. OpenAI's conduct in response to being out innovated by Xai, whose Grok model overtook OpenAI's ChatGPT models and performance metrics reflects not an isolated lapse, but a strategic campaign to undermine XAI and gain unlawful advantage in the race to build the best artificial intelligence models. What do you think, John?

[John]

This is why lawyers with English degrees are MVPs, according to Gabe.

[Jordy]

Yeah. Yep, Wordsmiths. Word sells.

[John]

It seems like we are in the territory of like economic warfare, lawfare. Who knows what this what actually comes.

[Jordy]

Up like Elon blending the Chinese way, the way of the engineer with the American way.

[John]

Yes, the lawyerly society is coming out in this case.

[Jordy]

Yeah, I mean easy, you know, obviously innocent until proven guilty with Xu Chen Li. Don't know if this is true or not. That he admitted to stealing the company's entire code base would be crazy and totally unforced error if he actually did something like that.

[John]

Yep. But, well, no matter what, you want to stay compliant, you want to get on Vanta, automate compliance, manage risk, improve trust continuously. Vanta's trust management platform takes the manual work of the security compliance process and replaces it with continuous automation, whether you're pursuing a first framework or managing a complex program. I wanted to revisit this internal tech email because this is. Is an important cornerstone of Elon's battle with OpenAI. So on September 20th of 2017, Elon Musk sent an email to the OpenAI team. The subject was honest thoughts. And he said, guys, I've had enough. This is the final straw. Either go do something on your own or continue with OpenAI as a nonprofit. I will no longer fund OpenAI until you have made a firm commitment to stay. Or I'm just being a fool who is essentially providing free funding for you to create a startup. Discussions are over. Interesting. And it's gone back and forth because here he's, he's sort of predicting.

[Jordy]

So in hindsight he somewhat probably feels like a fool for essentially providing free funding to create a startup. So.

[John]

And it's, it's been odd because the, the Ask has never, I mean at least that I've been aware of. Elon's never just asked for pro rata equity based on how much he put into the nonprofit. I think that creates crazy tax and legal implications. But that feels like what the Fair Ask would be like you were throwing out. Like if you put in 100 million and you just assume that the, the round that would have been done at that time would have been at a billion, you should get 10%.

[Jordy]

Right.

[John]

And here's 10% of the common or.

[Jordy]

The preferred or whatever. Remember?

[John]

But it's a win.

[Jordy]

Nobody. Like it seems like they hit it standstill with the for profit conversion. Right.

[John]

Because of Elon's lawsuit too.

[Jordy]

Well, partially. But also people are, you know, the governing body, the nonprofit governing bodies of California. We're not super excited about the transition.

[John]

Yeah. And so Matthew Berman was going back and forth with Elon because Elon took shots at Anthropic. He said winning was never in the set of possible outcomes for Anthropic. And Matthew Berman said, hey, Elon said the same thing about OpenAI. And Elon said, no, I never said that. I told everyone who asked in the beginning that I thought the probability of OpenAI beating Google was 1%, infinitely different from 0%. Good point. And then Elon says, after the defense of The Ancients, the Dota 2 win. I raised the probability to 10% that they would catch up. And Matthew Berman sort of of responded and unpacked the screenshots saying first, I'm a big fan of everything Elon has done to push society into the future. But I reread his emails with Sam Altman and Greg Brockman and it really seems like he told them they had no chance of succeeding relative to Google on January 31, 2018. So after that previous email we read Elon told Sam Altman and Greg Brockman, OpenAI is on a path of certain failure relative to Google. There are obviously needs. There obviously needs to be an immediate and dramatic action or everyone except for Google will be co signed to irrelevance. And it's played out very differently. They played their hand very well. They got the consumer application that hit product market fit out faster than Google only by a couple months. Like the Gemini app dropped, I think in February or March, just a few months after ChatGPT launched and the models have been neck and neck. It wasn't. I don't. Was it Bard that dropped?

[Jordy]

I forget which Bard was the response.

[John]

But I feel like the way I remember the timeline is that the ChatGPT website comes out and everyone realizes that just talking to an RLHF LLM is a great experience and magical and interesting and passes the Turing test. And Google had a bunch of models, Palm and Bard, internally, but they'd never really pushed them out in a meaningful way. And it seemed like ChatGPT kicked Google into action and led Google to actually productize a lot of their research that had been more tested and shared internally. Tyler, do you have more context there?

[Jordy]

Yeah.

[Tyler]

So it was Bard that came out right after ChatGPT, and Gemini was like the following.

[John]

Yeah, so they still had to do a rebrand, which is tough because then you have to reintroduce the product. Obviously it's grown a ton and we've seen that the Empire strikes back. Not a lot of that happening in the United States necessarily, but certainly international. Sort of an iPhone Android story happening all over again. Anyway, Magnus Carlsen tells Joe Rogan about how he treats chess as a hobby. He never wants it to feel like work and prioritizes fun and enjoyment. The thing is that chess has always been a bit of a hobby for me. He's one of the best chess players in the world. Of course, this is how Magnus Carlsen works. Once it starts to feel like work, then it's harder for me. Turn your work into fun and enjoyment. You'll never work a Day in your.

[Jordy]

Life you might get 14,000 likes on X. Like Dylan.

[John]

Yes. And Daniel Growing. Daniel says having known him for a while, I think Elon Musk is probably one of the least self disciplined people on earth. He just really enjoys problem solving. So he just bounces around from one project to the next, solving it, mogging them. Yes, of course. Growing Daniels, co conspirator, now runs Julius AI. What analysis do you want to run? Chat with your data and get expert level insights in seconds. Loved by over 2 million users and trusted by individuals at Princeton, BCG and Zapier. Bazelord says anyone who's naively calling bubble right now has not internalized the physics of our world. Most of them are simply ignorant about AI progress and its implications. Of course there will be fluctuations, but of course we could stumble, but history marches on. And he shares a chart of the world GDP over the last two millennia. And it's interesting because like you can take this in a few different ways. You can kind of look at this and say, okay, nothing ever happens. It's just a kind of a smooth exponential curve. But I'm looking and I'm seeing a hiccup there in the mortgage backed security crisis for sure where GDP shrunk globally or something happened.

[Jordy]

It's helpful.

[John]

Isn't that 2007, 2008, you know, you.

[Jordy]

Remember being, I was, you know, basically a kid at that time and it felt like I could sense the doom and dread in the, in the adults. Right?

[John]

Yeah, around that time, I mean from my perspective I was completely caught off guard by the, by the mortgage backed security crisis. Like it was because I wasn't following the markets.

[Jordy]

You didn't have capital.

[John]

I wasn't monitoring the situation.

[Jordy]

Yeah, you didn't have capital to deploy.

[John]

I lived in a house with a mortgage, so I was certainly affected. But, and, but, but if you go.

[Jordy]

Back in time, you would have, you would have, you know, raised and deployed a fund into single family.

[John]

But I wasn't, I wasn't seeing top signals. It was like I was introduced to.

[Jordy]

Were you in college?

[John]

I had the crisis. I graduated in 2007. So.

[Jordy]

From college?

[John]

From high school, from high school. And so the, when I arrived, I said I chose to study economics because I wanted to understand the crisis more. And so I was reading the Wall Street Journal trying to understand and I was introduced to like the collapse of Lehman Brothers, which I believe happened in 2008. Lehman, Lehman Brothers collapse, When did that happen? The bankruptcy, September of 2008. And so I graduated in 2007. And then so it must have been like sophomore year. So things were like melting down my.

[Jordy]

Freshman year, but it was kind of collapse of Lehman. Is that good?

[John]

Is that good?

[Jordy]

Did we not like Lehman?

[John]

I mean it was a very complicated crisis to dig into because it was all these layered financial instruments, mortgage backed securities and then collateralized debt obligations. So they would take one mortgage, they take a whole bunch of mortgages. This is the famous like Margot Robbie in the bathtub scene where she explains that you get a whole bunch of mortgages, you bundle them up, you securitize, you slice the different tranches of debt so that the best mortgages are in the triple A. But then as you keep re slicing them, they kept getting rerated as oh well, this is the best of the previous bad stuff. So that's good. And the best of the worst is the best. And the rating agencies had a really bad time throughout the. Because eventually the economy pulled back. Everyone got over levered, people were buying multiple homes and there was a whole mood in 2000-2005-2006-2007 that like average people, like the, the example would be, you know, when the, when the Uber driver is pitching you on Cardano, like it might be the top that type of thing. Like when your barber's telling you about the latest NFT drop, like watch out. The analogy then was people were saying like I'm making more money just owning my home and my home equity is going up by more than my salary. So like I bought a $500,000 home, I make $100,000 a year, but my home. My banker just called me and said, your home's worth 600,000 now. And the home prices were going crazy. And so obviously there had to be a correction and it crashed the entire global economy. And you can see it in the data today. But of course as we zoom out further, we will, you know, see less.

[Jordy]

Line keeps going up.

[John]

The line keeps going up, up. Well, D2C is cyclical but ever evolving. The back and forth locked in shares. This chart or this meme. Dropship Bros convert to supplement Bros. Which switch to dropship Bros. Which convert to supplement Bros. Which go back to dropship Bros. And back to supplement Bros.

[Jordy]

Supplements continue to be the economic engine of the manosphere.

[John]

Were we talking to the CEO of of Numeral Sam and he was saying he owns a supplement company?

[Jordy]

Yeah, he started a gummy supplement company back in the day.

[John]

That's still, he's like, it's still doing well. That's crazy. Anyway, Numeral sales tax and autopilot spend less than five minutes per month on sales tax compliance. If you're a drop ship bro. If you're a supplement bro, you got to pay your taxes. You got to get on numeral.

[Jordy]

Create. Damn. McCormick's company is on numeral. Yeah, he's a supplement bro.

[John]

Lucy is on numeral.

[Jordy]

Christina Cordova is quoting our interview with Christina's over at linear. Of course. But we asked Brett Taylor yesterday about the triple triple double double debate and how maybe that's not good enough anymore. He said the faster you grow is sometimes correlated with lack, with a lack of a moat. I'd rather bet on a durable, high quality revenue business and happy customers than just raw growth. Christina says fast ARR can be fragile ARR earned ARR tends to be sticky ARR. Not all growth is created equally. I think LINEAR is obviously they're a partner somewhat biased but of course they just.

[John]

For those who don't know, LINEAR is a purpose built tool for planning and building products. Meet the system for modern software development, streamline issues, projects and product roadmaps, but.

[Jordy]

Continue use the tool. Loved by OpenAI Mercury Retool Ramp scale anymore But LINEAR is a perfect example of like great growth but steady and just systematically earning the trust of pretty much every important new company in Silicon Valley over the last however many years. I think they're yeah.

[John]

Earned ARR. Yeah, it does feel like there's 2019.

[Garrett Langley]

Yeah.

[John]

There's like Carr rear its head recently. It's kind of gone out of favor but contracted ARR. Basically you have some sort of LOI or some sort of trial that you're counting into.

[Jordy]

Yeah. I mean the people that are abusing the ARR the most right now.

[John]

Disrespectful to the gap metrics.

[Jordy]

Well, I'll just say it's the companies doing data labeling and services for labs, right?

[John]

Yeah.

[Jordy]

Is that ARR all the companies that explode quoted out of.

[John]

I don't think that many of them are actually quoting ARR numbers though, are they?

[Jordy]

Are you kidding? I feel like almost every single one of them is saying yeah, we got to 100 million ARR.

[John]

Oh really?

[Jordy]

Did this or that.

[John]

I thought it was just like if you did 100 million because just say I did 100 million then that's true. No.

[Jordy]

And they're saying we're at 100 million ARR.

[John]

Sure.

[Jordy]

And, and they're, and they're using it I think as like annualized run rate. But if you dig into the business it's like they might have four 40% margins because they're actually having to hire.

[John]

Well, the margin separate from like ARR. With bad margins. Completely separate from ARR. With bad churn. Like, yeah, because I would. I probably. If you're underwriting it at a high multiple, you probably want to pay for lower margin. Lower churn than higher margin. Higher churn. Because higher churn means that like, if the business stops growing, it's going to start shrinking. Whereas if you have, if you have 40% margins but super low churn, you're super sticky. It's like, okay, well then at least the business will continue to grow. You're not building on a leaky bucket. You're not getting all the juice out of the bucket. You're only getting 40% of the juice. Since we're mixing analogies now, get the.

[Jordy]

Blender out these analogies.

[John]

But I mean, obviously these two metrics are linked. And you obviously will want high margin and extremely sneaky revenue.

[Jordy]

But if you're a company like linear and you see some. Which, which has like true ar earned ARR. And then you have companies out there saying, you know, throwing out these numbers around ARR. But they're reselling, re reselling GPU credits or something like that. It's, it's kind of, you know, stolen valor. Right, Stolen valor. Potentially true enterprise, you know, contracted.

[John]

Yeah, yeah. Where you're like, you could stop the growth strategies, stop the sales team, they could stay home and you're still printing. That's the gold standard of enterprise software. That's why we love that.

[Jordy]

That's why we get up every morning.

[John]

We gotta pull up this video from Paula Rambles. There's this guy on TikTok who video calls ChatGPT, shows that objects, asks how much Graham then weighs it. Before we pull up this video, let me tell you about the generative video platform for developers. Fall the world's best generative image video and audio models all in one place. Develop and fine tune models with serverless GPUs and on demand clusters.

[Jordy]

You can get access to our soundboard by going to tvpn.com sounds which is brought to you by our friends.

[John]

So let's play the video of this guy on Tick Tock. This is my hand.

[Jordy]

How you call this thing?

[Delian]

Yeah, I see your hand there holding on to that pen.

[John]

So, okay, how much gram is the pen. How much gram? Look, how much gram.

[Delian]

Well, it's a little tricky to guess the exact weight.

[Jordy]

Yes, guess, guess.

[Delian]

All right, I'll take a guess. For a pen that size, it's probably somewhere around maybe 500 to 700 grams, give or take.

[John]

GPT5 is smarter. No, no good.

[Delian]

Hey, it's all good.

[John]

It's not good, man. It's not good.

[Delian]

No worries at all. It's just a bit of fun guessing.

[John]

Look, I have this oil here. How much grams?

[Delian]

We're on a gassing roll. So for that little oil can, I'd say it might be somewhere around 300 to 500 grams brands, depending on how full it is. But let's see how close we get this time.

[John]

You said 300 to 500, man.

[Jordy]

I want accurate thing.

[John]

You know what I mean? I get it.

[Delian]

You're looking for something spot on. It's a bit of a challenge without a scale on my side, but hopefully that at least gives you a decent range.

[John]

How much gram?

[Delian]

Oh, you've got a mocha pot there. Nice.

[John]

Those little. How you call it?

[Delian]

How you call it? That's called a mocha pot. It's basically a mocha.

[John]

How much gram? Mocha pot.

[Delian]

So a mocha pot is usually pretty light. I'd say maybe around 400 to 600 grams, depending on the size. But of course you'll know it.

[Jordy]

I hope you're right.

[John]

What's the number?

[Jordy]

I hope you're right.

[John]

Ah, bruh.

[Delian]

Like GPT5 is. Is worse and worser than GPT4. Definitely here to do my best.

[John]

Best.

[Delian]

And I appreciate you rolling with it.

[John]

Yeah. This is your punishment, man. Talk with him.

[Delian]

Hey, Green Coco, Any idea where the Mayo sighting? Maybe it's just chilling out behind you in the fridge somewhere. What's the deal with the ketchup in the mail? Any condiment? Gossip we should know about?

[John]

They just talk. No. That's hilarious. That is not a Rocco Basilisk respecter. You should. Yeah, that's very rude.

[Jordy]

That guy's absolutely cooked.

[John]

Did anyone. Anyone see exactly what the numbers were? How close is it? Three.

[Jordy]

No, I was saying like 30. I. I was seeing 35 on the.

[John]

That can't be 35 grams, right? It needs to be. I have no idea. I'm worse than GPT5 for sure. If you ask me how much that pan weighs? I have no idea. Anyone have any idea? I have no idea.

[Jordy]

Who knows?

[John]

Anyway, HBO Max says nice. We still got a couple of months.

[Jordy]

Scroll down on this chart. It's charting 1998 to 2001.

[John]

What? This is just the NASDAQ and it's just following perfectly. Like, what are we doing here? This is crazy. How the correlation here is like insane. Is this on the same timescale? Too. Or is this, this is just a wild, wild chart that this is so similar. It lines up scarily accurately. But it's just so weird because like if it's this obvious, you think it would be priced in. You think people would pull back or do something, but who knows? We'll keep monitoring the situation. It will be interesting. Let me tell you about Turbo Puffer. We Puffin.

[Jordy]

We Puffin every bite.

[John]

Serverless vector and full text search from burst principles on object storage. Fast 10x cheaper and extremely scalable. Jordy loves his puffer fish.

[Jordy]

This puffer is used by Linear Notion.

[John]

Break it many more wpp.

[Jordy]

Wait, one thing, one thing on this chart to be clear, I think it's tracking very closely. Obviously you single out individual, you know, kind of points on the chart and it's a little bit ominous. But at the same time like Amazon went public in 1998. Right. So like you can do a lot to kind of like if you're the chartsmith here, to kind of like pick the dates to align it properly. Right. So yeah, I would. I bet you could align this to just other bubbles throughout history and find similar patterns. Right.

[John]

It doesn't really help though.

[Jordy]

I mean, I'm just saying like this.

[John]

Doesn'T get a couple months.

[Jordy]

Yeah, I mean, I'm just, I'm just saying like.

[John]

No, no, it does feel like it.

[Jordy]

Like if you started somewhat in 1990, you said, okay. That the dot com bubble began when Amazon went public.

[John]

Yeah.

[Jordy]

Then this doesn't line up at all. Right.

[John]

Sure, sure, sure. Yeah. You're kind of just selecting. I mean, yeah, I don't know, it's. They're like overlaying it deliberately as close as possible. But this does feel like, like the crazy part is that the previous earlier sell offs, the dip in 2023 to now is like that valley, that peak and valley seems to match as well. And then even like you can see earlier in 2025 we got the tariff sell off and that kind of tracks what happened in 2000 in like the year 2000. Exactly. Or maybe 99. Lots of people.

[Jordy]

Yeah. But then again, was there like. I don't know, I don't know. Well, something you should read.

[John]

Even if we wind up in history, disillusionment, we'll be slopping it up in the trough of disillusionment, grinding to the plateau of productivity.

[Jordy]

One we'll probably end up in a position where like we're only gonna eat fast, casual slop bowls until we.

[John]

Until when you're in the trough, you.

[Jordy]

Eat the slop until we get out of the bear money.

[John]

The slob bowl.

[Jordy]

Somebody, somebody had a great. I got to pull up this comment on Spotify.

[John]

Someone's asking how much the gong weighs. Gong. How much? Gram.

[Jordy]

How much gram?

[John]

And Aqua says mania is a crazy.

[Jordy]

Flaus on Spotify. Says wearing the white suits on an off day to rally the bull. Ultimate top signal might just be poking the bear.

[John]

Well, I'm in a gray suit today. I'm feeling neutral about the market. Could go up, could go down, who knows. But we'll be monitoring it here. In other news breaking from US tppn, WPP Media has signed Michael Miraflor as global evp. So congratulations to Michael Miraflor. He has been a fantastic champion.

[Jordy]

Massive pickup. Hopefully wore his TVPN hat to work today. Hopefully he's not in the chat right now. First, first, first day of work, gets a corner office.

[John]

Yes.

[Jordy]

Puts TBPN Fired up. Why not fired up, Leave it on in the background. Put some titles on. But big pickup and excited to see what he what he cooks on.

[John]

Always enjoyed his commentary and excited to see more of it.

[Jordy]

Paul Enright says in 2021 Mitchell Green from Lead Edge Capital, of course Mitchell's friend of the show. We got to have him back on again.

[John]

I texted him this morning. Get him on soon.

[Jordy]

He said, said to Paul this year will be remembered for the GPS that sold stock and distributed capital to LPs versus the ones that raised funds called capital and made new investments. Was a wonderful observation. I will never forget. Now feels similar in some ways. Why not both? Why not distribute capital, sell some positions and raise some new funds.

[John]

Yeah, yeah. I don't know the dynamics of that, but that does feel like the ultimate movement. Raise a massive fund at the top, don't deploy it, sell a bunch of positions, get out of the other stuff. Basically just be sitting on a massive cash pile. When you reach the trough of disillusionment and then monetize the plateau of productivity.

[Jordy]

Deploy into the trough.

[John]

Into the trough.

[Jordy]

Well you saw this chart yesterday. Somehow like one of injury's and slides from a fundraising debt newcomer Baby leak master.

[John]

Oh yeah, he got two decks.

[Jordy]

So a 16Z returned 15 billion or generated 15 billion in returns including their recycled fees and carry in 2021. That was biggest year on record by quite a lot.

[John]

Huge return. That's got to be a lot of coinbase. And who else got out?

[Jordy]

I think it was like Solana Avalanche. Right. Some of these. A lot of stuff I don't know.

[John]

Yeah, but Coinbase was a huge position and I mean, they deployed in all these different rounds. And then I believe Coinbase went out and was probably distributed at something close to 100 billion market cap. So something, something there. Andrew Curran has more updates on Elon Musk's reuniting with the Trump administration. Andrew says their friendship is slowly being reforged. OpenAI, Anthropic and Google already have similar agreements in place. OpenAI and Anthropic charge $1 access fee. Google charges 47 cents because the 47th president. Right. Isn't that it? That's interesting. That's cute. Elon is charging the government 42 cents for access to Grok. This is a Hitchhiker's Guide reference.

[Jordy]

Finally, a competition for who can say the smallest number in a lot of who can say the biggest.

[John]

You want to be on the barbell. The extreme ends charging the least and raising the most. Apparently that's how business works.

[Jordy]

Most capex least.

[John]

Have you seen the Hitchhiker's Guide to the Galaxy? Have you?

[Tyler]

No, I thought it was just a book.

[John]

They adapted it into a movie. The movie's pretty good, but the book's probably better. Have you read the book?

[Jordy]

I did read the book at one point, yeah.

[John]

The book's great. But 42, of course, is the answer to the universe, all things, everything. It's a fun reference. The Trump administration will offer artificial intelligence models from Elon Musk's XAI to federal agencies through a new partnership under the agreement with with the gsa, which oversees technology procurement. Agencies will get access to models such as Grok 4 and a new fast version called Grok 4. Fast. The deal follows a similar agreement with the other folks in the space. Automating staid government processes is one of the most promising applications for technology, fueling the battle to be the most popular tool for federal workers. All four of the AI companies also each have $200 million contracts with the Defense Department. Sort of interesting that all four. Yeah. So the government clearly wants an oligopoly here and is like, we're not going to really pick winners, which is crazy because Dario has been very outspoken about the Trump administration, and Elon's obviously been fully in the Trump administration's camp. Google has been a little bit quieter and has leaned left in the past. OpenAI. Sam Altman was kind of stayed out of politics, but then has been at dinners and was at the inauguration. And so you would expect, based on, like, the news of how close the foundation model lab CEOs are to Trump, like, just how many photo ops there have been? How many? How close have they been? You would expect a massive contract for Elon and a very small contract for Anthropic. And yet they all got $200 million equally. It's interesting. Just like they're clearly focused on, on having balance amongst the AI foundation.

[Jordy]

I want to see the usage in the government broadly and in the dod.

[John]

What are people using?

[Jordy]

I mean, if Everybody gets a $200 million contract, it's unlikely that they're going to be super evenly leveraged. Right?

[John]

Yeah. I wonder if they would use them for specific things. I mean, you would hope that like they're using Claude code over there for something and they're using ChatGPT for knowledge retrieval and stuff and then they're using Gemini for the things that. Gemini is great. Nano banana. I guess the government is just, hey, you don't need to come in for DMV photos anymore. $200 million for gray beams.

[Jordy]

Great memes.

[John]

Oh, great memes. Yes, exactly. But you would hope that, you'd hope that the government's using AI all over the place and they need an actual contract to make sure that it's provisioned and hosted in the proper way anyway. Fin AI, the number one AI agent for customer service. Number one in performance benchmarks, number one in competitive bake offs, number one ranking on G2. You can start a free trial. Lulu is chiming in about Rick Rubin. She says, I mean, just look at him. Can't media train this. Austin says the Beastie Boys, Ed Sheeran, Lady Gaga, Red Hot Chili Peppers, the Stropes. Rick Rubin has worked with all of them.

[Jordy]

Why is no one talking about Rick Rubin?

[John]

Why is no one talking about Rick Rubin? He's worked with all of them and is considered one of the greatest producers of all time. His process to creativity can be described as looking for clues. He has such a unique aesthetic with that massive.

[Jordy]

Always has the red. The blue blockers on those are blue blockers. Yeah. Oh, he's very.

[John]

Blue blockers are normally orange. Orange, but I guess those are just a dark orange that I'm seeing.

[Jordy]

Yeah.

[John]

Okay, well, what was else is going on.

[Jordy]

Your post here? There were accusations earlier that somebody was doing a paid post.

[John]

The post was deleted. So it was Mike Isaac at the New York Times picked up a device called a brick, which is a little NFC chip that they see. You see, everyone's seen this on Instagram, right, Where it's supposed to like brick your phone so that you don't be distracted and so you have the Willpower, just once to attach this to the back of your phone. It kind of magnetically attaches and it puts your phone in a do not disturb. Don't show me any of the addicting social media apps. Turn off everything. Let me focus, Let me cook, let me cook. Let me lock in. And so apparently, according to the original post, Mike Isaac picked one up off of an Instagram ad and said he actually loves it. It's helping him write. Of course. He writes for the New York Times. He needs to lock in and write a lot. He can't be distracted. He's also a prolific poster. Can't be caught on the timeline mid article when he's on deadline, so he posted about it. And a. Another poster, another poster accused him of doing a sponsored post without disclosing it.

[Jordy]

Undisclosed ad.

[John]

And if you know the New York Times standards and who Mike Isaac is, he's published a book that got turned into a movie or TV show. Like, he's probably not doing Spawn con for some D2C. Like, you know, electronics company, undisclosed. It's just like so much risk to so little reward. Like the post of him saying, like, oh, I got this brick and it's great. Like, it didn't get that many views. It's not like Brick would be like, oh, yeah, we're gonna sell 10,000 of these things off of this. Let's Pay Mike Isaac $100,000 to post this. This, you know, organic content, this fake content.

[Jordy]

He just, he likes technology.

[John]

Yeah, he likes technology. People like to post things that they.

[Jordy]

Test out, covers consumer tech.

[John]

Not. Not everything is Spawn Con.

[Jordy]

But I thought your post was hilarious. You said it's time to come clean. Responding to this allegation, John said, you need to admit that Brick paid you to dunk on this organic post to drive more impressions. This post is brought to you by Brick.

[John]

I do think there's something funny where you could potentially run some sort of, like, anti astroturfing campaign as a brand where you pay a bunch of influencers to accuse Organic UGC of being paid. And it drums up way more attention. And so I was riffing on that. But on this show, we don't do undisclosed partnerships. We do disclosed partnerships. It's like our partnership with Adeo, Customer relationship magic. Adeo is the AI native CRM that built, builds scales and grows your company to the next level. Get started for free. When we read an ad, you know we're getting paid for that. You know, we're not doing it for free. We're not doing it for the love of the game. We're doing it for the well, we.

[Jordy]

Are doing it for the love of the game.

[John]

We do love anyone.

[Jordy]

Nobody loves SaaS more than us.

[John]

That's true. That's true. Let's keep going. There is a lot of stuff going on. This was a really funny post because it gave me a total jump scare. I was talking to Brandon about it earlier. Ben Podgerski sounds like a podcaster's name potentially. Ben says this is correct, but we should take it to the natural conclusion. He was, I guess he was quote tweeting Rune, which we'll get into. But he says, like the Habsburgs of old, the USA should look for synergistic M and A not through immigration, but with entire polities. In this case, the obvious answer is merge South Korea in as the 51st to 57th states.

[Jordy]

Totally obvious.

[John]

The obvious answer to me when people talk about growing the United States, they talk about Greenland, they talk about Canada, Mexico, Puerto Rico, Fiji, the US Virgin Islands. There's so many different territories that are more closely aligned with the United States than just going all the way over to Asia and just picking up South Korea. But Ben makes the argument. He says merging South Korea in would resolve a wide range of defense, industrial trade and demographic crises. South Korea would not have to hem and haw about building their own nuclear shield. They'd be an inviolate part of the United States from the US from day one would have massive shipbuilding capacity, vastly improving national defense. And US companies could friction free contribute in the one spot where we genuinely have a technical contribution. Small nuclear power systems. The US's relatively healthy demographics could gradually backfill South Korea's catastrophic demographics. Maybe we could even teach them how to have kids again. The free flow of labor would allow Korean workers to train US workers without insane visa shenanigans. South Korea is neither unduly liberal or conservative relative to the United States.

[Jordy]

Small couple I like the thought exercise couple. Small potential problems here would place the United States directly on having a shared border with North Korea and be right across the Yellow Sea from China.

[John]

It is such a wild move. But he lays out a, you know, a thoughtful case.

[Jordy]

It's a cool idea.

[John]

I mean, maybe it's no coincidence that the most respectful TVPN derivative show inspired show is from Korea.

[Jordy]

That's right. Those guys know how to do it. Also, I love have you ever had bim Bimbap?

[John]

No, I don't know what that is.

[Jordy]

Popular dish in South Korea. It's like rice and protein.

[John]

It's have you ever been to South Korea?

[Jordy]

I have not.

[John]

I've never been there. Have you. Have you ever traveled anywhere in the world?

[Jordy]

Yeah.

[John]

Where?

[Tyler]

I've been to Ireland.

[John]

Oh, okay. Job's finished. Moving on. Ireland. World traveler.

[Jordy]

Luck of the Irish.

[John]

So this is all kicked off by Arun Post. He said Correct me if I'm wrong, but it seems like the theme of the Dan Wang book, who we had on the show and the general elite consensus now is that industrial process is a technology that lives in the heads of people and that it was a mistake to let so much quote unquote low value industry be offshored due to the tacit loss of processed capital. TSMC Arizona, which makes the most complex and valuable industrial production in the world, was a massive success. This was a huge surprise to me. I did not expect the TSMC build out. Everyone was saying like it's impossible to airlift TSMC. But they wound up producing 4 nanometer chips at great yields on par with Taiwan merely years after striking ground for the first time. This involved a generous federal subsidy and importing thousands of the great Taiwanese semiconductor experts despite unions trying to quell Taiwanese immigration and some culture clashes in the United States. Acqua hires of whole teams with process knowledge in their heads is very common. Zuck acquiring some of the greatest talent from other AI labs for massive numbers is just one example of this. Also seen in the full self driving wars between Uber and Google. Which was interesting because that is of course about the the Anthony Levandowski case that ended in a lawsuit that landed Anthony Lewandowski I believe in jail for a little bit but then he was pardoned and so he got out. But this it was more I feel like it was more than just process knowledge in that case because it was specific patents. And I'm wondering how much of a line you can draw between knowing a specific algorithm, knowing a specific something patentable, an actual process power. Process process knowledge. But it's certainly an interesting analogy to dig into. So Tesla + Apple + Big Pharma acquires industrial process companies all the time. America is very capital rich, able to levy literally hundreds of billions of dollars for machine intelligence. Capex we can afford to acquire whole groups of foreign talent for prices that are unheard of to them in their home countries. Tldr aqua Hiring foreign process knowledge for massive sums should be one of the primary goals of any re industrialization effort. Special visa categories should be made for to scoop up whole teams of Shen gens. Best the raids on the LG battery plants in Georgia are the exact Opposite of what we need ability to tolerate new arrivals is a technical edge of American capital to be able to assimilate foreign knowledge into to domestic industrial processes at a scale nobody else can countenance. I was hearing a story about how I think what was it? The Manus team relocated to Singapore and there's a world where they relocate to.

[Jordy]

San Francisco set up in the benchmark office. Satellite office.

[John]

Yeah, I mean there's something there. I don't know how important their process knowledge is, but certainly it worked for tsmc. I don't know how many more of those projects need to be done. Taiwan seems to be in uniquely precarious position whereas a lot of the South Korea tensions seem to be a lot lower. Like there's less geopolitical risk in south in South Korea. So there's less of a We need to move SK Hynix to America. But Tyler, do you have any thoughts on this post? I'm sure you saw it. What do you think?

[Tyler]

Yeah, I think it makes a lot of sense. I think politically it might be hard to do this but I've seen a lot of similar arguments just for like normal AI researchers in China. We should basically have some kind of like visa that just like imports them like instantly. And then it's like the. I assume the salaries over there are not comparable to like MSL level, like $100 million.

[John]

Totally. This is the real. This is the real AI paper clipping. It's not that you get turned into a paperclip, it's that you get Operation Paperclipped into a different country and we need to avoid our best getting paperclip to a different country and we need to be be potentially paperclipping other national champions. I wonder if there's something to do in. In in AI in not just AI but in the process power around solar. Because we've talked to Casey Hanmer about this. It feels like the vast majority of the cheapest solar panels come from China. We're maybe not. We don't have a national champion there yet. We're not catching up. But fortunately we have a guest who might be able to get us up to speed on this. We have Delhi Naspru helps from Founders Fund. He is back from paternity leave. He's in the Restream waiting room and he will be joining us in the TVPN Ultra Dome in just a minute. Let's bring in Delian. Oscar. UV how you doing?

[Jordy]

Yes.

[John]

Good to see you. What a boys.

[Jordy]

Daddy's home.

[Delian]

Daddy's home, baby.

[John]

Oh There we go.

[Jordy]

Got my swag.

[John]

I love that hat. How, how is it being a, a father of multiple now?

[Delian]

You know, I feel like you blow up your life once and then after that you kind of. You guys sort of figure it out where it's just like, yeah, you got the infrastructure and that's why God gave you multiple hands is, you know, one baby per hand.

[John]

Yes. But everything's good. Everyone's happy and healthy. Everyone's back to normal.

[Delian]

Oh yeah. Oh yeah. I mean, she's still only like a, you know, sort of month old so, you know, still requires, you know, some work. But yeah, in the grand scheme of things, happy, healthy, very grateful that, you know, all things pretty smooth.

[Jordy]

Yeah. Well, once, once she gets to two months, you know, it's cake.

[John]

You know, put her to work. She can come on. She can come on. Tvpn. We've got, we've. We've had three members of your household live on the show. We need the fourth.

[Delian]

That's true.

[John]

Well, actually your brother too, so that's true.

[Jordy]

5.

[John]

The Asperuhav clan is dominating.

[Delian]

I want at least 10 as Bro House on TV.

[John]

Yeah. What are your parents up to next week? We'll get them on really quickly. I want to get a general update on what's going on in your world, but I would be interested to hear your response to this. This debate that was going on on the timeline yesterday from Rune about TSMC Arizona being a good example of airlifting industrial process from one place to another. He kind of ties it to the acquisition of whole teams at MSL America having being capital rich, being able to actually afford to go and say here's a hundred million dollar offer to some great researcher come to America potentially. And it gets into the. Obviously there's a whole bunch of immigration stuff going on and cultural stuff, but did you have a reaction to that? Are there other industries where it seems like we need sort of a TSMC Arizona like project where we're just going to an international company and saying do what you do over there. Here.

[Delian]

Yeah. I feel like a lot of the reason people are discussing this so much on the timeline lately is because of Dan Wang's new book Break in Neck, where you know, breaks down basically the like. At least his argument is that, you know, China is the engineering society, where the sort of lawyer society and everything basically sort of stems from there, which I think is probably a little bit. You know, I like a lot of parts of his book. That actually particular argument is probably one of my, like, less favorite. You Know, sort of parts partially because like, look, there are things that China is obviously, you know, sort of very good at. I think it was, you know, hearing your last guest talking about like, you know, mass production of solar panels. They're obviously like, like phenomenal at that type of like commodity cost curve. Relatively complex but not deeply complex type of manufacturing. Right. Like they've stepped up from like, you know, the early days of Shanghai being, you know, sort of toys and knickknacks, et cetera, obviously now into like, you know, mass consumer electronics. Unitree is obviously like by far the best, you know, sort of humanoid robotics company and then obviously in solar panels. But there's you know, I think some limitations to their approach. Like, you know, when I think about it from like the aerospace perspective. Look, a Falcon 9 rocket landed for the first time a decade ago now. The Chinese basically like stole the IP in plants that, and clearly have something that is like the equivalent to a Falcon 9. And they're still basically doing the like early days of like you know, Starhopper, which was, you know, back or Grasshopper, I mean, which is like the SpaceX project in like 2013. I want to say that was just doing the suborbital little like hop ups and downs to practice for Falcon 9. And so I do think they like have this limitation when it comes to like, like deep, deep systems engineering and requiring some creativity that they like miss out on. And I think that's why you've seen them partially succeed in semis. Right? They're good at the like, you know, sort of last generation of semis and you know, sort of reshoring that to China. But I don't think you've really seen any progress on them, you know, sort of, you know, domesticating cutting edge, you know, sort of semis. Tsmc, Arizona, you know, is at least a very subscale version of being able to do extra actually some amount of cutting edge domestically. And I do think it sort of shows that there's just some breakdowns in Dan Wang's argument where like we are able to import that type of like, I forgot what he calls it like industrial process or process knowledge in the United States and even develop it ourselves. Right. The other area that obviously like we do quite well on, you know, it's not the perfect company but like look like the, you know, 99% of commercial airliners in the world are still developed by the west, right. You know, Boeing and Airbus and continue to be. And it's not obvious that China has really been able to displace that that the only other areas that I think about actively that you need to be reshored some amount of it is like hey, if we want to compete against China and Taiwan, it is going to be almost certainly like a mass scale production sort of game, more so than anything else. And so when you think about mass scale drone manufacturing, mass scale metal cutting, mass scale fighter jet production, that's something that we're obviously behind on. Even the munitions Ukraine has shown that like you know, artillery is back to being relevant again. It was not relevant at all in any of the like Middle east conflicts. But now with like, but now with like continuous, you know, Internet coverage and continuous basically, you know, spy satellites, you know, you can actually justify basically just like, you know, anytime that your, you know, enemy makes a move, you just artillery shell the crap out of them. And that's actually like back to being you know, sort of relevant on the battlefield. And they are far better. They have these like you know, lights off, you know, artillery shell production facilities that basically just like are 24, 7 fully roboticized, you know, produce way more than the United States can. And so I don't know those are going to be necessarily like the equivalent of TSMC where you're like taking somebody's preexisting industry and like dropping it here and that like there's not an obvious place to go import from basically for that type of stuff. So I think we kind of solve that on our own and obviously Founders fund, we're making some investments, you know, in that space obviously.

[Jordy]

You know, isn't it true too that in China like yes, there's flagship lights out factories that are truly cutting edge. The kind of thing we just don't really have here in the United States. But yet still the vast majority of manufacturing in China is just a lot of labor like you know, assembling cheap components.

[Delian]

It shifted. I think that's like a sort of decade out or a decade old sort of sort of thinking where it's like yeah, the reason that China won for a long time was because of just like the labor arb and cheap cost of labor when you talk to people.

[Jordy]

But I'm just saying like with the true, like we can't buy the like. When you talk about China's advantage of just being able to produce overwhelming mass right across every different sector. There's certain key areas where they are just light years ahead and then it's, they're still getting this massive benefit of even the components that get made that go to the lights out factory to be Assembled, you know, with robotics, like there's.

[Delian]

Yeah. I mean when I think about like their advantages in like you know, drone manufacturing is mostly due to automated facilities. Right. Like it's not because they like, you know, have a bunch of like, you know, sort of mass assembly, super precise, small hand, you know, sort of laborers or something like that. It actually is because when you think about like the PCB boards largely, basically fully automated, the like, you know, propellers that they make, largely fully automated, the battery lines largely fully automated. And so yeah, I just like when I think about like the edge that they have in drones, yeah there's maybe some amount that's like, you know, sort of this like assembly edge. But like I'd put that at like 5 to 10% of the edge, like 90% of the edges that they like have such deep process knowledge across all these individual like different, you know, basically like sub component sectors. And a lot of those are fully.

[Jordy]

Say again, like CO location effectively. Yeah.

[Delian]

And the co location is just you know, sort of wild.

[Jordy]

Right.

[Delian]

And this is also sometimes the problem with like the stuff in America when we like try and reimport it. It's like, you know, the CHIPS act. One of the biggest battles was like, like the, you know, the size of funding required support from a broad set of senators and congressmen, but then by default they want, you know, sort of jobs everywhere. And so it's been more difficult to fully, you know, sort of centralize all of the like you know, reshoring of semis in the United States into a sort of single location. Like you know, Arizona is definitely, you know, should have been impressive. But like, ideally it's not just the like fab. At some point you want to do like lithography there and a bunch of other parts of semis centralized there. But like in the United States we actually kind of have a bit of a CHIPS hub. Obviously still some amount in Silicon Valley. Austin's become like a, you know, sort of really big area. Ideally those would all be in sort of the same place rather than so spread out. And so it is just harder given that we're not like China that's willing to sort of like put their finger on a scale to a single city and just be like you are going to become like the guitar producing city and everything is going to be sort of based there. We don't do that.

[Jordy]

Need a new guitar executive order.

[John]

It does feel like we're starting to do that with the Neo clouds with some of the big data center buildouts. Abilene, Texas, like We're marshaling capital, but.

[Jordy]

That'S still led by individual dealmakers going and talking to these local governments and figuring out, yeah, can we do this here? Okay, no, I'm going to go across the state line over here. I'll do it over here. Sure.

[Delian]

They're chasing, yeah, we're just much less top down coordinated. But like, at the same time, I think you're starting to see like the faults and the breaks in that system, you know, in China. And Dan Wing talks about this as well, where it's like, look, you know, they clearly still excel in certain areas, but they've also like, I mean, like, think about it, even over the course of time that I've been a founder fund in 2021, like the number of unicorns being minted in China was starting to approach, you know, the United States and there's like some real risk and fear that it was going to supersede. Now, four and a half years later, you know, the Chinese venture capital ecosystem is effectively, you know, totally negligible. And so, you know, I do think that they've done a decent job on like, you know, sort of prioritizing the industries that matter the most. But also they're like, capital markets are like, you know, sort of way worse than they were, you know, sort of four and a half years ago. You know, they have re imported a bunch of, you know, sort of Chinese nationals from the United States back as scientists into China, you know, pretty good. But they've also like lost, you know, something on the order of. I forget what the number was. Like 25,000 Chinese millionaires like are, you know, exporting their capital.

[John]

They lost the Manus team. The Manus team's over in Singapore now. They might be working on a benchmark office soon.

[Jordy]

Yeah, well, speak, speaking of benchmark, I thought it was interesting, actually. Bill Gurley posted earlier, game recognized game. And it was a quote from the CEO of Xiaomi who said, we bought three Tesla Model Ys for disassembly and research inside Xiaomi earlier this year. What a great vehicle. And of course they're announcing like effectively a copycat.

[John]

But it's insane to just say game recognized game. It's game copies game.

[Jordy]

Yeah, just it's saying, saying the quiet part out loud is wild. But recognizing, I think also, by the.

[Delian]

Way, since I was last, I was last on was when I have been poking the benchmark bear, literally, basically, like since like, you know, a week or two after joining Founders Fun. And I remember early on I got a call from like, one, you know, one of the partners at FF being like, hey, like, look, just so you know, you're definitely making some enemies over there. And I was like, okay. And then they're like, but I wouldn't necessarily. Like, it doesn't feel right to tell you to, like, take these things down because, like, at the end of the day, we are founders fund and you are critiquing them for firing founders. And that is our whole ethos. So just know that what you're doing is definitely creating enemies and you guys are creating risk. So anyways, I've been poking the bear for like, five and a half years, and then it was just, oh, glorious to have, like, finally an official response from Tetan. And it was just like. It was an alley oop. It was the perfect response. It was like, how dare you not basically, like, you know, you know, control, you know, sort of company's choice and, you know, sort of, you know, capital provider. Like, why are you letting them take Chinese capital? And I was like, oh, my God, this is perfect. This is like the. Exactly. You don't even realize how wrong you are because you don't even realize that what you're saying is, why aren't you, as a venture investor, telling the founder to run their fucking company and that that's your critique. And I remember reading it, and I was technically supposed to be on this, like, one week, like, Twitter or whatever, like, you know, Detox. But then, like, you know, on Twitter.

[Jordy]

Being like, I'm supposed to be on a detox, but I'm about to go on a bender.

[Delian]

I got like five texts from friends being like, how have you not responded to this yet? And I read it and I was like, oh, my God, yeah, fuck this Detox, bro. Like, definitely fucking going in. And it was just like, it is, I think, either my top or second best day on Twitter in terms of joy provided for me. Like, like true, like existential, like, identity level. Like, as much as, like a child's birth. Like, that is a level of Jordan.

[John]

There's zero user regretted seconds.

[Jordy]

Like, the least regret of you would compare it to. Yeah. Holding your daughter.

[Delian]

Like it is. Yeah. I think roughly equivalent. The only other day that I've had that was that good was the. Like the day after the FTX blowout up. And I was the first one to really find and screenshot the Sequoia blog post about him playing League of Legends and getting that out. And it was just. That was just. That was incredible. It was just.

[Jordy]

It was.

[Delian]

It was like, I got to break news, I got to, like, poke fun at a competitor. I forced them to, like, have a response to all their LPs about it. They had to, like, take down that blog post. It was just like. That was like.

[John]

Weren't you also better than SBF at League of Legends?

[Delian]

Okay. I mean, like, AOC is better. Yeah, like League of Legends. So, like, the bar is very low. I just, like.

[Jordy]

But at least. At least you gotta respect some of the highly convicted investments in anthropic Robin Hood. You know, he was a gambler, but.

[Delian]

You know, yeah, dude, he was a good gambler. I mean, like, he just, you know, played the line a little too hard. But, like, yeah, there's a world where like, yeah, I forget who is telling me this. It was somebody that was basically responsible. Responsible for, like, brokering the, like, ftx, like, bankruptcy, etc, so they're like a, you know, Wall street, whatever, you know, sort of type. And they basically were like, yeah, like, if he had just lasted another, like, six months, the book, like, would have been totally fine. He wouldn't have got liquidated. And today, if he just held these investments that he made from, like, back then, he would be richer than Elon. Like, he would actually just be the richest person on the planet.

[John]

Wait, what?

[Delian]

And so it's just. It's wild to think that he was, like, on a knife's edge.

[Jordy]

Richer than Elon.

[John]

I don't.

[Jordy]

That's how he's putting up.

[John]

I. I haven't seen that actual number, but, I mean, I guess it makes sense with, like, the various positions he had.

[Delian]

Yeah, I think it was like, assuming that FTX continued to go, et cetera.

[Jordy]

And Solana, best possible scenario.

[Delian]

There were like, I mean, again, some of those, you know, moves were just like. It's like the anthropic position, I forget is, like, now, like, $25 billion.

[John]

I mean, the guy was insane. I don't know if you remember, but he went on Tyler Cowen's show, conversation with Tyler, and Tyler asks him, would you flip a coin where there was a 50% chance of humanity being completely wiped out? Or 50% chance that you double the prosperity of humanity, but it's 5149 the outcome. And he was like, I would flip it 100 times in a row, and it's like, that's insane. That's not how these things work. But he was like, the expected value is positive, so I must take the EV positive bet. And it's like, no, no, no, no, no. Please do not flip that coin. You're gonna wipe us all out. It's like 99%.

[Delian]

The best part of SBF having to go to jail is Dustin Moskowitz finally shutting the fuck up about ea. Thank God we can stop talking about positive things.

[John]

Yeah, it's wild. Well, speaking of net EV positive things, is it no longer net EV positive to invest in a company that's growing revenue? Triple, triple, double, double, double? Because I have a lot of friends that have been doing that. They previously they were saying I'm about to IPO my company, but now they're thinking of shutting down. Because according to the best venture capitalists.

[Jordy]

Delian'S a fan of 00000.

[John]

But yes, I want your reaction to the state of the software markets. It's sort of an ev. Take a little.

[Jordy]

Have you, have you done a pure SaaS deal this year?

[Delian]

I did just do like a like basically pure vertical AI SaaS.

[John]

He had to do one.

[Delian]

He had to help myself.

[Jordy]

Vertical SaaS. Underrated. Criminally underrated.

[John]

That's.

[Jordy]

He literally talked every VC. It's like you just go invest in the foundation model layer, go invest in hard tech, leave the vertical SaaS for me.

[John]

That's great. But yeah, overall thoughts on the triple, triple, double, double, double. Being out of date with how fast the foundation model companies are growing, I had this interesting thought that it's like you could be running a janitorial company and if you have have a foundation model as a client and they're growing 10x, you're going to be cleaning 10 times as many toilets, your revenue is going to be 10xing because they're 10xing. And if you just like are a barnacle on the side of the massive whale, you're going to see massive growth. And I wonder if like that, like.

[Jordy]

What that means because we're investing in the barnacle economy.

[John]

The barnacle economy. But in general, like, you know, what are your thoughts?

[Delian]

Yeah, I think with this stuff all the time from like the space perspective too, where like, you know, you can get diluted into this world where it's like the space economy is growing, but if it's only a bunch of other space startups, startups like, you know, trading revenue back and forth, you can like prop that up for like quite some time, trading a dollar back and forth, but at some point it needs to connect into like the rest of the ecosystem. Right. And so, you know, I think there was, you know, some, you know, memes and jokes going around, you know, sort of yesterday about the like Nvidia Oracle, OpenAI, whatever, 100 billion investment, et cetera. And it's literally just like the same dollar effectively going, you know, sort of in circles over and over again. And that can, you know, sort of work, but, like, that can also blow up. And we just, and I think we talked about this in maybe even in the last interview. It's like you have this crazy dynamic where, you know, the percent of GDP being invested in this category is like, you know, the equivalent of like, at the railroad bubble, etc. But a lot of the companies that are doing this have like, these cash flows from other very large businesses that are driving towards this. Right. You know, Zuckerberg, I think, gave the quote where he's like, look, I would prefer to like, you know, waste hundreds of billions of dollars, miss.

[Jordy]

Spend a couple hundred billion.

[Delian]

Yeah, spend a couple hundred billion rather than lose the machine God race. And so it's just like the level of. It just. It's like nothing we've ever seen before in terms of like, like the super cycle of, you know, sort of capital going into this. Maybe that has the roi, maybe it doesn't. When I think about it from like, the investor perspective, I mostly think about it from twofold, which is like how you should analyze any business, which is basically like, quality of revenue and like, you know, you know, in terms of like, durability of that revenue. And then, you know, the competition, for example, the margins, you know, sort of on that revenue. And so I'll maybe provide like, one example that I think is very strong and one that I think is like, a little weaker. You guys have had, you know, sort of Melissa, you know, John Ludic, you know, sort of wife on for Cybernetic lab labs. I think of that as a great example where, you know, she has really great revenue growth and I believe it to be very durable in that most of her revenue growth is coming from things that are totally decoupled from the, like, insanity of like, you know, Nvidia, OpenAI, etc. Circles. Like it literally is janitorial companies, right? Effectively H. VAC, plumbers, etc. Those people's revenue, their growth, etc. Like, is completely, like, economically decoupled. And so in some ways then Melissa's revenue is completely economically decoupled from the entire AI hype wave. And so when I think about, like, oh, okay, let's say imagine a world where all of a sudden, like, you know, the Mag 7 decide to, like, you know, reduce deployment into data centers and like, foundation model training by 100x next year. Which companies are affected by that? Okay, well, like Core Weave I imagine is going to be affected by that. Oracle definitely going to be affected by that. OpenAI anthropic definitely going to be sort of affected by that.

[Jordy]

Yeah, you look at, you look at, at how many companies are now indexed to OpenAI, right? You have Broadcom, Oracle, Softbank, Cor, Weave. Like these are.

[John]

There's a lot of them.

[Jordy]

A lot of them.

[Delian]

And I think as an investor you have to take a little bit of like a bifurcated strategy where it's like, it's, I think it's a generational index. And this is, you know, if there's one thing that I admire about Peter the most is he just does such a great job of. Even though he has lots of biases, particular, you know, preferences, etc. On one sector, another founder, another, he's very willing to very, I feel like soberly analyze the just like broad macro world and identify, hey, even if, like I don't love, you know, whatever boring SaaS software, etc. Or like the AI stuff, you know, you know, may not be real, still be willing to like, analyze it from a purely investment perspective and like take it on. And obviously we've done decent checks into this field versus, like, I literally like find my biases so strong that I can't even, like, I can't even motivate myself, myself to even spend time on it to like, you know, analyze it as an investor. So that's where I think about the you know, sort of, you know, durability perspective. And then there's like the margin, you know, sort of perspective which is like, how much, you know, competition is there. Right. You're seeing obviously in these foundation models where just like the token cost continues to go down, the margin never seems to really be improving. And a part of it's like there's a bunch of, you know, companies that, in capital that's going into this and you know, some of the, like, let's say like AI for, you know, whatever coding has maybe a bit of a similar dynamic where it is like, like, you know, a bunch of companies that are working on it, the foundation models working on it, et cetera. I don't think there's going to be like 15 AI for plumber, you know, sort of companies. Right. And so this is where Melissa both has this like great durability and great margins. And so I think you have to take this kind of bifurcated approach as an investor which is both like invest into the like index effectively now Our approach has generally been invest mostly into the thing driving the index, eg, OpenAI. And then you're like, you know, sort of counter strategy is invest in things that are totally decoupled from the index and like super far away. And then basically like nothing, you know, that much in like the, you know, sort of messy middle in between. And to go back to like the, you know, whatever 332 or whatever it was. I do think that in both categories, yeah, I do think there's some merit to it where it's like the growth rates and EV growth in these companies just do look very fundamentally different. And the bar is definitely higher. It's just been like. I meant, like, it's been very remarkable to watch Melissa and her company grow at a rate that just like, like, yeah, I just like, I, you know, if you had told me, you know, write the distribution of where you think Melissa's revenue growth is going to be. Like, once you, like, started the company, this is like the 99th percentile, you know, And I think it just speaks to how much of a wave this can be. And I think Peter talks about this where it's like the Internet wave happened, but then it still took like 20 years to get the integrated Internet integrated into the rest of the economy. I think you're to see the same thing, you know, sort of here where like, there might be not as bad of like an AI bubble crash, but the like, implementation period still may take. Might be more accelerated because just generally society is moving faster, but it may take 10 years. And it's companies like Melissa that are getting it integrated into like, the broader, broader society.

[John]

Have you seen any companies where they've done a good job? They're still in founder mode. They're, they're, they've grown like a base of business that then when the AI story came, they could actually act. They could act on that in a way that it wasn't like, you know, they're a public company and they need to go through this massive transformation of how they bill. But they can just add AI on top and then they're actually growing new quality revenue. Are you feeling that at all? What are you pointing to?

[Delian]

Let me figure this out. Sorry, I'm having to.

[John]

Oh, yes, yes, yes. Ramp.

[Delian]

Okay, there we go.

[Jordy]

There you go.

[Delian]

There we go.

[John]

Rampart. Com. There you go.

[Jordy]

Ramp.com.

[Delian]

You know, great company that has done a great job of like, look, they obviously, like, were growing very well before any of the AI boom. But like, I just remember this very particular. I think they've announced this now, so I'm not like revealing anything, right? They have their like, you know, AI agent, you know, basically product. But I remember the board meeting where Kareem and crew presented like the vision for it and I was like, oh, this is like what a very competent but like larger startup that is still fast moving, knows how to adopt things. Things does in this world where it's basically like, yeah, look, we have a bunch of people that obviously use what is a very beautiful interface that automates a lot of finance work, but it still requires people to go in, set up these rules, engines, do some amount of tagging, et cetera. We're just going to basically start to offer for some of our beta customers that are going to try this out. We're just going to effectively screen record what they're doing and start training AIs on that. And it's like I just can't imagine. But with if you're a net new company being like, I'm going to make AI agents for the CFO suite, it's like, well, but there's like a whole set of things you have to do. You have to have like the corporate card, you have to have travel expenses, you have to have this expense policy, accounting, integrations into the ERPs, integrations into their tax. It's like all these systems that you need to build that are more web 2.0 or whatever sort of systems and only when you have that and you have a ton of usage on it, can you then actually start to train the AI agents on top of that usage.

[John]

Right.

[Delian]

And so, so I do really, I've admired that a lot in Ramp. And so that's probably the one portfolio company that I've seen the strongest in. And then the second is this other portfolio company of mine, Sword Health, that had been doing this like basically AI sort of physical sort of therapist. But most of it was that basically you had these like sensors that were strapped on your body. You would go through your physical therapy routine and then like PT would basically then review your movement data set and like message back and forth to you and adjust it. That was a very obvious area where like they literally had years and years of training data set sets on how their digital pts are basically interfacing with patients. They basically like significantly up the ratio. I forget the exact number but like my guess would be something on the order of like. I remember when the company started it was like 12 patients per pt. I remember by like 2022 is like 1 to 100. And I think now it's something on the order like one to a thousand. And it is largely like the like, you know, AI, you know, sort of wave that has enabled them to do that. And especially because it's like this text back and forth literally with like a, you know, sort of physical therapist. But again, if you were starting from scratch, being like, I'm going to make AI agents for physical therapy, it's like kind of hard to do like, just that, the physical sensors, the distribution with like Fortune 500 health systems, et cetera.

[Jordy]

Yeah, we had a company on, I think a couple days ago called Filevine that raised $400 million. They were for 10 years creating just workflows for different law firms, SAS for law firms, SaaS for law firms. They have all the workflows, time tracking, conflict checks, et cetera, document storage. Now they can just, just add AI in a bunch of different places. And maybe they don't have their own foundation model, but like, Maybe Claude or OpenAI models become good enough. Right?

[John]

Yeah. Give us an update on space defense tech stuff that's happening in dc. It seems like there's a ton of deals there, but they're two orders of magnitude smaller than the AI. Sometimes it's like a billion dollar deal for palantir in the UK and people are like, I just heard about $100 billion deal over here from Nvidia. But there's some amazing stuff happening. What's been top of mind for you in Space or defense or D.C. generally?

[Delian]

Yeah, I mean, the, you know, sort of big macro story for the next five days is it seems like we're very likely headed towards a government shutdown. I think we've talked about this in some of prior appearances. Yeah, there's going to be a lot of people for a load rip. You know, we've talked about this in prior, I think.

[Jordy]

Can you imagine if we had a, a precedent like that in the private markets where like companies just routinely like, yeah, we're out of, out of cash, we're talking with the board, but everyone's furloughed. Everyone's furloughed. Just probably will be like five days, maybe like 40 days, you know, whatever.

[Delian]

Imagine, by the way, imagine like Xi Jinping coming out and be like, oh, yeah, sorry, like we couldn't like, you know, with my finance minister agree on a budget. And so we're shutting down the CCP for like, you know, it's just like, it's so funny to me that like, like they so badly want to usurp America and our system still has us regularly shutting down for extended periods of time, unable to the most basic facts of like, what should we be even like prioritizing and allocating towards? And we still kick their ass. We have the best capital markets, we have the best nation, the best freedom, the best fucking technology in almost every single area.

[Jordy]

If you're a career politician, it must feel so good to shut the government down.

[Delian]

Oh my God. I just, what I feel bad is like now that I. We're so like, I've already so deeply integrated in all these government programs, like, there's a lot of people that just like end up having to like, continue to do their job, but like, they just don't get paychecks. And it's like, and some of these people are like friends of mine now that like have worked in technology and are over there and it's like, yeah, like, you just kind of have to make sure that you have savings because like rent still keeps going, you're kind of still expected to work, but you literally just like don't get paychecks. And at some point you get some amount of back pay. But, but yeah, the reason we're marching towards it is like, look, we've gotten into this world where like, like, you know, I think it's something like four of the last 20 years we've actually passed like our budget on time. So the fiscal year for the government basically ends, you know, basically end of September every year. We effectively, for many, many of the last 20 years, we never end up, you know, basically actually figuring out what the budget should be. So we go into these continuing resolutions. But when you're in that state and you're doing everything so last minute, it means much more regularly we have shutdowns. So shutdowns are happening, you know, sort of more often. And so this year it's the Dems and Republicans going back and forth on like, you know, basically how much should be based just off the big beautiful bill. How much should the Dems have to fold on some of their asks around? A lot of it is healthcare spending basically related. And at least right now, tone in D.C. is there isn't an obvious going to be a path forward over the next week or so. And then Speaker Johnson isn't even necessarily releasing a schedule on when he's going to call everybody back to even fix it. It's an interesting place where, where you know, CRS and shutdowns generally favor incumbents. Right. And so, but what's interesting though this year is like now a bunch of the net new tech Companies are kind of the incumbents. Right. And so, you know, if you were Andrew in 20, whatever, 18, government shutdown, pretty painful. If you're like Andrew in 2025. Yeah, it's. I mean, you preferred for, you know, budgets to keep going, but like you can actually probably even continue to beat plan, etc. Even with, you know, sort of government shutdown. And so mostly what it makes it painful for is some of the like, you know, next gen companies that have been starting like the last year or two really, you know, sort of painful. So at least as somebody that's closer to an incumbent now rather than a two year old company, I don't mind the government shutdown, you know, so that much, if anything, it kind of gives me like more room to like, you know, get away from some of the, you know, sort of seed series A, series B companies. So, so Mr. Politician shut down away and we'll keep flying capsules.

[Jordy]

It's also if the government shuts down, then if it restarts, it'd be a bullish catalyst. Send us to new all time highs.

[John]

Close us out with a white pill. What's the best new development happening in defense tech space? Any positive news? Aside from the government stuff, the shutdown's kind of disappointing.

[Jordy]

Will you be buying the Unitree ipo?

[Delian]

That's depressing.

[Jordy]

Wait, no, here's what's depressing is it's going out at 7 billion. What does that say? If they're the leader and the market says this is a $7 billion company and we have companies that are worth 40 billion. If you look at Tesla, what premium does Optimus give to Tesla? We're clearly valuing the potential of humanoids more than at least the Hong Kong Kong stock exchange.

[Delian]

This is kind of related to like how I think you could use Unitree for peace, where if I were to provide like you know, sort of the analogy what Apple is to Foxconn, you ideally need some US company to be to unitree where it's like both the US Government and the CCP are not happy with the Apple Foxconn relationship. Right. The US Government is not happy that Apple does so much of its manufacturing with our primary adversary and would like them to ideally push to relocate more of that to more allied nations like, you know, Vietnam, India, etc. Which they're starting to do and do more of that in the United States. The CCP is not particularly happy that Foxconn puts in all this work, technology, process, etc. Ships out these iPhones and then that just ships A ton of profit dollars over to the largest company that's owned by their adversary. And so both sides are super unhappy with the relationship and yet the relationship has now persisted for like over 20 plus years. Right. And so, so I think there is the downside case of Unitree succeeds, you know, a lot in China and just makes like humanoid like, you know, soldiers that like end up, you know, invading Taiwan. That's like the downside scenario. The upside scenario is unitary becomes a contract manufacturer, but like an American company has way better foundation model AI controls, you know, sort of robot, whatever operating system and design and uses Unitree basically as like the manufacturer. And then you basically get into this like unhappy wedding on both sides in a way that actually makes it even less likely that basically China actually.

[Jordy]

Only, only downside is a sci fi scenario where there's a backdoor into the, you know, millions of humanoids that get deployed into the US and. Yeah, yeah, but, but my iPhone's not going to get up at night and stab me in the chat.

[Delian]

I mean, it could explode. And it's in your fucking, you know, I mean, like, look like you thought the Hamas fucking, like, you know, pagers were bad. Let me fucking tell you. There's like a little bomb in each of these and like you can explode like just government officials, you know, so could be tough.

[John]

Okay, I asked for a white pill. That was.

[Jordy]

And I got a black pill.

[John]

Close, but we'll get you next time. Delian, thank you so much for hopping.

[Jordy]

On, taking the time. Great to see you.

[John]

Congratulations.

[Jordy]

Congrats on the little one.

[John]

Give our best to you soon.

[Delian]

Later, boys.

[John]

Heard him talk about Eight Sleep. You can enjoy an Eight Sleep if you go to Eight Sleep.com, get a pod 5, 5 year warranty, 30 night risk free trial free returns, free shipping.

[Jordy]

How did we do last night, Jay?

[John]

I got cooked. I got a 78, I got a 76, I got a 73. So you beat me. 73. Our next guest is from Flock Safety, a founders fund portfolio company. Actually we have Garrett Langley. I'm very excited to come in from the Restream waiting room. Garrett, how are you doing?

[Jordy]

What's happening?

[John]

I'll let you take the intro.

[Jordy]

Welcome to the show.

[Garrett Langley]

Good.

[Jordy]

How are you doing? Great. We've been super excited to have you on first time. Why don't you give a quick interview introduction for anybody that's been living under a rock.

[Garrett Langley]

Yeah. Or hiding under a rock maybe, but yeah. Garrett Langley started a company called Flock Safety with a couple friends eight years ago and we catch bad guys. We will help local law enforcement make just around 700,000 arrests across the country this year, all violent nonviolent crimes.

[Jordy]

What was the. What year? How quickly. What was the time to first arrest?

[Garrett Langley]

Yeah, just under 60 days.

[Jordy]

So we were in.

[Garrett Langley]

Yeah, we were in YC and it was horrible because we had built this product, we had a couple neighborhoods using it, and we were like, dimaday is going to be a bust. Because, like, yeah, we built a camera, but, like, what else? And I kid you not, the week before, this guy broke into someone's home, stole a nice road bike. DeKalb County, Georgia, made the arrest. And so we went on demo day. We had one slide, and it was this mug shot. And we were like, we build cameras that do this. Please invest.

[Jordy]

Wow. We already had the mug shot. Yeah, yeah, better than, like, you know, we got 2,000 mrr. Mrr, yeah. Real world. Real world results. That's great. And feels more, you know, more critical than ever with everything going on in the world. What is. What have you guys been up to lately?

[Garrett Langley]

Yeah, I mean, so we're live in just over, like, 6,000 cities now, so pretty well deployed and building a lot. So we got into the drone business earlier this year, kind of at the end of last year. Earlier this year, we've now got drones flying all over the country. Just kind of launched that also for the private sector. So it might surprise you that private enterprise spends north of $30 billion a year on unarmed guards. I think drones are a pretty good alternative. They're cheaper, they're more reliable. And so now, like, if you're.

[Jordy]

And unarmed guards are effectively just providing, like, a deterrence. Right. They're not meant to engage, but they're just trying to show that there's. That you're not, you know, you're not alone, basically. Right. And so drone can. Can play a similar role and potentially even a better role if it can follow a bad actor or something along those lines.

[Garrett Langley]

Yeah, exactly. So when you think about, like, a retail example, which, if you're in the Bay Area, this happens a lot. Stolen car. Car gets stolen, they drive it to a Home Depot to target. We know that car is stolen today. We just notify 911. And depending on what city you're in, a couple minutes or 20, 30 minutes later, 911 shows up. Now, with our drone, that drone can get automatically dispatched off a rooftop out of a box, completely remotely, kind of teleoperated. You've now got live video streaming to local law enforcement inside their vehicle. This is the vehicle, this is the person. They're going into the store, they're leaving the store, whatever it may be. And so it's kind of the way to think about it is we just treat drones like a camera that can fly. So we're pretty good at building cameras. And now these cameras can fly and chase bad guys.

[John]

Can you give me some timelines on when, you know, the average American would be seeing just drones flying around? What scale we're going to see that? Are you bullish or excited about humanoid robots or wheeled robots? We've seen what Starship Technologies has done. There's a whole bunch of companies that are putting, you know, more like simpler robots on the ground. Like, what's the actual path and what kind of, of timelines are you kind of operating against?

[Garrett Langley]

So, I mean, the, the good news is that these drones fly high, so we fly 400ft up in the air.

[John]

Okay.

[Garrett Langley]

So if you're not looking up, you're not going to hear it, you're not going to see it.

[John]

Wow.

[Garrett Langley]

The other thing is our drones can cover up to 30, 30 square miles effectively. And so the sheer number of drones you need actually isn't that many.

[John]

Sure.

[Garrett Langley]

So I think about a county near me. It's the largest county in Georgia. I think it's just over 500 square miles. They're going to get 20 drones to cover the entire county.

[John]

Wow.

[Garrett Langley]

And that's a couple million people. Like, you're never going to see these things.

[John]

So you would probably wind up either partnering or building yourself like something that looks kind of like a cell phone tower has charging infrastructure. Maybe there's a human that goes out there and fixes parts if there's problems.

[Jordy]

Does it even need to look like that? Or can you just put it on a roof of like a Walmart?

[Garrett Langley]

Even better. Fire department. Fire departments are legally required to be equideployed in a. There's a federal regulation of the density of fire departments, which makes them a perfect place to also put drones.

[John]

Sure.

[Garrett Langley]

So you put them on top of a fire department. They're fully autonomous. They live up there. It's got H Vac. It's pretty cozy place to live is a drone. And then someone clicks a button from a computer just like you guys are on drone flies and then it can track the car, locks in, tracks the car, the human, it's locked in. You can do multiple drones to one operator. So even in a county like the one I'm describing, with 20 drones, you know, probably three or four operators at all times. But like they're covering 500 square miles. Like, insane coverage.

[John]

Yeah. Talk to me about some of the other robots. Robotic dogs, wheeled. Four wheeled robots, humanoid robots. Like, when does this happen?

[Jordy]

And before that, like, talk about autonomy timelines. Because if you're flying 400ft in the air, at what point there's not a lot else going on up there. I imagine you could build these to be pretty fully autonomous pretty fast.

[Garrett Langley]

Yeah, I mean, the autonomy is already there. The issue is the FAA regulation. It's like right now we are legally required to have a human click a button that says launch drone. And then they need to have a Part 107 license that says they can fly. And they're like an actual game.

[Jordy]

That's a pilot slice.

[Garrett Langley]

It's an easier version. It's maybe 20 or 30 hours of.

[Jordy]

Studying specifically for commercial drones.

[Garrett Langley]

Yeah. And I think it's good. But the autonomy is there. And the FAA has done a great job over the last few years of kind of like trying to catch up. They were a little slow for a while. They're catching up now. I mean, they're making better decisions. Like they're now allowing us to fly multiple drones with one operator. It used to be. It had to be one to one. It used to be able to. You had to be able to see the drone. Now you don't have to be able to see the drone. So in the case of that big county, that person sitting downtown, they're flying a drone 50 miles away.

[John]

Yeah.

[Garrett Langley]

And I think that makes a lot of sense. So the autonomy is there. It can autonomously track the car, stick to it, so you can avoid a high speed pursuit, but the FAA is going to make sure that it's safe. And I agree, like, safety is the most important feature we sell.

[Jordy]

Yeah. How much of a big thing? It feels like high speed chases are like definitely a bug. Not. Not a feature.

[Garrett Langley]

Right.

[Jordy]

Because it creates an entirely new danger. Right. Of. Of, hey, let's get. We've got one guy that stole a car. Let's get six cops driving super fast.

[Garrett Langley]

Super fast.

[John]

What can go wrong? Yeah, it's probably thrilling though.

[Garrett Langley]

Yeah, I think it's like, probably one of the highlights of the job if you're like an adrenaline junkie because, like, you're driving 90 miles an hour trying to like chase someone. No, it's definitely a bug. And I think most elected officials would agree as they've started to ban it, which creates all types of new conflicts. So I think high speed pursuits are a really good one. I think the other thing that we've been surprised by is the reduction in service calls. And let me try to expand on that, please. When you call 911, the average response time might be 30 minutes. And a part of the problem is it's just slow to drive. So we'll get there faster because of that. That is we don't have to wait in traffic. The other issue is that a lot of the times you'll call 911 and say, hey, these two guys are in a street fight. And then 20 minutes later those guys are gone. We still had to send an officer. They still had to look around. Maybe they go into the gas station and grab a Gatorade because they're thirsty. And all of a sudden like we've wasted hours of this officer's day. So one of the beautiful parts of the drone is actually it gets there faster and it can also remove that call for service from the backlog so that for actual critical incidents, we get humans there faster as well. I think the other one that I'm pretty excited about is we have a number of colleges that we work with that are using drones to help escort females at night back home. So you can call 911 and be like, hey, I don't feel safe. Like it's really dark, I just left this party. And you don't feel great. I think as like a 19 year old maybe doing that because you're now going to get in the back of a patrol car. Now in a couple of colleges we work with, they're pushing this out like hey, you can always call 911 and a police drone will escort you from home. And we'll have a video, we'll have eyes on you so that anything starts to look suspicious, like we're on top of it. And I think there's just a ton of use cases that we're just undercovering now to make drones just a more bigger part of our daily life.

[John]

If you run the, the like economic calculation on the 30 square miles for one drone and there's cost to service that and batteries versus do some sort of deal where every stoplight has a camera on it and you have have sort of coverage. 360 cameras on every single corner. Is there an economic calculation here that makes sense where the drone's more efficient or is it just more flexible? Like what are all the trade offs that a city or you think of?

[Garrett Langley]

Yeah, so the way we think about it is there's a certain cost per citizen that a city is comfortable paying to Eliminate crime. And we do think you can eliminate it. Like you can't eliminate emotional crime, like crimes of hate, crimes of passion, but the capitalistic crime. Like there was a really funny no Jumper podcast a couple weeks ago where the guy was like, those effing Flockers, they're making it too hard to commit crime in San Francisco. And I'm like, that, that that's the goal. Because like that guy knows.

[Jordy]

On a podcast, on a podcast.

[John]

Wow. He called you Flockers. That's hilarious.

[Garrett Langley]

It's brutal.

[Jordy]

Yeah, it's just about like, it's about making it so that you know, you've still do it, but it's not economically viable.

[John]

Random podcast. That's amazing.

[Garrett Langley]

Yes.

[Jordy]

That's product market fit. Getting called out on no Jumper for. For stopping crime.

[Garrett Langley]

For stopping crime. So when we look at that though, and like, you know, the. Probably the most deployed city we have is spending about $22 a citizen per year with flock. I think that's pretty reasonable, actually. Not that much money. It's a lot for that, that city. But I mean, as an individual, I believe that city is going to solve every single crime that happens. I don't think that's too much of a burden. But I do think it's about. You think about building a cake, you got to have different layers. You don't want just all cake, all icing. You want cameras, you want cameras that fly. You also need software, you need trailers because there's a more of a deterrence. So I don't think it's a one size fit all fits all. But for us right now, we kind of see that deployments where you're going to cover your perimeter with cameras that track cars, you're going to have kind of PTZs, penciled zooms for your major intersections and they're going to use drones to kind of COVID the whole city or county as an overlay.

[Jordy]

How. How do you.

[John]

Humanoids. Sorry.

[Jordy]

Yeah, I know we're going to get there.

[John]

I really want to know because cost per citizen is probably really expensive. We're seeing stuff from Unitree. There's companies in America. Optimus is far away. Just give me your humanoid take. Sorry.

[Garrett Langley]

So my humanoid take is like as it stands today, they're just way too expensive. So if you think about like an average retailer, some of them make a lot of money, right. If you think about like a big box retailer, they might. They might generate a couple million in Ebitda per location. But then you go to. Do you kind of go down market to you Know an Ulta Sephora, A Dollar General. Their box profit is just like not very high. They have a lot of locations.

[John]

Yeah.

[Garrett Langley]

But their individual stores are actually not very profitable. They can't spend more than a couple thousand dollars a year per store in safe tickets. I just don't see a world where other humanoids or dogs work there. And we're seeing that unfold as well. Where bigger footprint locations just have both more assets and more dollars. In my conversations with retailers in particular, the kind of two wheeled approaches have been laughed off. They get stuck in a corner, they get kicked over. The dogs are seeing more efficacy. And I gotta imagine like a biped, like humanoid is gonna be the most effective because that just sounds really scary.

[John]

Yeah.

[Jordy]

Well, now in it, and you see this, you can't kick. You can't kick them over.

[Garrett Langley]

You can't kick them over.

[John]

They come right back up. It's crazy.

[Garrett Langley]

Talk about a scariest situation. You're trying to rob a place. You try to kick it over and just stands back up and just looking at you just like, what next?

[Jordy]

It's gonna be like Dark Web, the shit poo down.

[John]

Yeah.

[Jordy]

Dark web tutorials of like how to get it stopped get around.

[John]

All of a sudden the, the bippers.

[Jordy]

That bring like, it's so sci fi, like you have to cut these cables on the back and it's gonna be wild.

[John]

Sorry, Jordy.

[Jordy]

Yeah, I was just curious about just like how you think about product prioritization. Because I imagine when you get in working with these cities and police departments and they start using your products and getting value out of them, they just start coming to you with like more problems with like hardware, software. But it feels like the drone opportunity is big enough that, you know, it's. It's probably hard to. That you have too many opportunities than you could probably pursue all at once.

[Garrett Langley]

Yeah. I mean I think we took the company from 1 SKU to 8 SKUs in the last 12 months that all have clear line of sight to 9 figures of ARR. Yeah, I agree. Yeah. The pipeline is there. The error is growth. Like it's kind of wild. This will be our first quarter, I think, where like our core business like won't be the biggest product line, which is kind of weird. I think that's a good thing for us because we're not decelerating on that side. It's just other products are really attractive. But I think it is. You're right. Like our bigger concern is the market adoption, not our ability to build. I mean this is A kind of enterprise Y type buyer where they're just only going to adopt things so quickly. So even like on the AI front, we have a lot of ideas, we've built a lot of interesting products. They're just, they're really nervous to adopt too quickly. And I think the example I always give is maybe you're trying to book a hotel and you call the hotel and you realize you're talking to an AI agent, but you're kind of like, I don't know, this is better than the alternative because I'm just trying to book a hotel. I don't know, man. I think when you call 911 and you're in the middle of a violent situation, I think there's something warming about knowing there's another human on their side trying to help you.

[John]

Yeah.

[Garrett Langley]

Not to say they can't be augmented with AI, but I think that's like a much more challenging societal question of what do we want humans to do and what do we want AI to do? And we are being conscious to not make that decision for the hundreds of millions of Americas we help keep safe.

[John]

Yeah. Just as a taxpayer, I would imagine that I would want the person to pick up, but I'd love for the calls to be transcribed and then AI to find patterns between what's happening and insights and analytics and all that.

[Jordy]

Yeah. There's also something strange. Like if somebody's calling 911 to report like a drunk, somebody that's obviously drunk driving. It's like you're taking up bandwidth from somebody that is a human that could be going elsewhere. It's like for, you know, maybe it's like you should. There should be no dial times a clanker immediately picks up and says, what's the problem? And then routes it either to a human or if, if it's less like, you know, if it's not like immediate, you know, some violent act is taking place, it can actually be solved by a voice, you know, voice model.

[Garrett Langley]

And I think that's the right approach. But yeah, I think to answer your question, like, we're pretty focused on doing three things for our customers. Solving more crime. Whereas right now it's about a 40% clearance rate for killing someone. So you got almost 50 chance of getting away with homicide. That should be zero. You should. Every single person that kills someone should go to jail. Nonviolent crime is even worse. We don't solve cases faster. It takes way too long to solve crime and we want to do more with less. Like most people. I don't Know, if y' all remember our grandparents, our parents, it was an admirable job to go into policing, to fire.

[John]

Yeah.

[Garrett Langley]

This generation doesn't view it that way. Which means 80 plus percent of police departments are understaffed against their budget and it's not getting better and technology's going to fill the gap.

[John]

Yeah, people have compared you to like the Anduril or Palantir, kind of like, I don't know, American dynamism companies or whatever.

[Jordy]

People have compared you to good businesses.

[John]

But I'm interested about, we talked to Shyam Senkar, CTO of Palantir, about some of the difficulties of deploying software into governments. And he gave the example that one time they built a beautiful piece of software, exquisite system, and they went to deploy it and the, the team on the other side of the government that was firing it up was trying to run it on a computer that had like 128 megs of RAM instead of like a gig. And so that was kind of the dawn of the Ford deployed engineer. And I'm wondering if you have any unique solves on how to deploy systems, how to deploy software. If you like the Ford deployed model or something else, what's working for you at actually getting your solution solutions into the field?

[Garrett Langley]

So really similar example I remember distinctly, we were like launching this product and the designer has a beautiful MacBook and this HD retina display. It's beautiful, right? Super expensive setup. And she's designed this super slick thing. And I was like, great, Mariana, you should go field test this. So I was like, this looks dope. Let's launch it. And she gets into a patrol car and It's a Panasonic Toughbook. It's a 13 inch screen, it's 1280 by 1024 resolution. And he's using it while he's driving 40 miles an hour. And I'm like, this product's not going to work. We got to go back. That is literally our. We've got, I don't know, hundreds of thousands of DAUs using this product now. And they're very happy. But that's their normal use case. They're driving, they're on a tough book. It's a tiny screen, it's low res, it's old. And so like you're pretty much treating it almost more like a mobile app, but like with a distracted teenager as your customer. And that's been pretty difficult because we want to build these like super high fidelity. You're just sitting at a desk all day doing your job. And like our Customers are in the field all day. So that one's been pretty tough. And then I also think the other burden we've done a good job of going around is just it in general city it is really tough to work with. They're really tough to kind of just like get going. So we tend to build everything we can to avoid it. There's some pros and cons to that, but so far I think it's been mostly pros.

[John]

How does that actually work? I imagine is that just like you're only looking for user licensing or like oauth or something. At some point you have to plug into the IT systems a little bit, I imagine.

[Garrett Langley]

Well, so it's a good example. Historically, everything in our world is on prem. We're one of the first cloud only solutions in this market. And early on that was painful because people are used to buying a piece of software. They install a desktop application. That installation requires IT support. And so building everything in the cloud, which for you all, it's like, well, obviously it was a very contrarian take seven years ago and now it's moving. But I mean we have a customer that just a few years ago moved off of paper records. They had filing cabinets. Imagine if you report a crime like, hold on, we gotta go find that file and that. This is a big city. This is a city with millions of people in it.

[John]

Yeah.

[Garrett Langley]

Just got off a paper. And I think In Maryland in 2023, the cloud became legal.

[Jordy]

It was legal, legalized cloud.

[John]

This is there people marching. We're going to protest for legalized. We love the cloud.

[Jordy]

If there's any cities that have still banned cloud, we will and we.

[John]

And we hate paper. The show is presented by Ramp, of course. And we are strong in favor of ending paper and going to the cloud.

[Garrett Langley]

Agree. But literally we didn't do business in Maryland until 2023 because it was illegal to be in the cloud.

[John]

Yeah. Did you ever get a test environment with a toughbook and a car that a designer could actually go and and drive around the parking lot of your office or anything like that?

[Garrett Langley]

No. We make all of our employees go do ride alongs.

[John]

Okay. Yeah.

[Garrett Langley]

It's so much fun because then you get to see the product in action, you get to meet the customer, you get to go catch some bad guys. It's a pretty fun way to spend eight hours.

[John]

Yeah. How are you thinking about data privacy where data lives? There's obviously so many advantages to being cloud based. But then you have some citizens who might say, wait, why is my image with this private company. I'm a taxpayer. I don't have a vote at your board meeting. I have a vote at my city council. How do you grapple with all that? What's the mood on the ground in various cities? What are the dividing lines?

[Garrett Langley]

I'm glad you mentioned cities. So our general stance is we don't write the rules. We create the levers for local politics to dictate. And so data retention is the easiest one. In some cities we work with, data retention is seven days. And every single data we capture is purged after seven days.

[John]

Days.

[Garrett Langley]

But then in some cities like Dallas, it's a year. In New Jersey, it's five years. A state legislation for five years. I don't care. I live in Atlanta. I think we're like at 30 or 60 days here in Atlanta. And that's up to the local politicians to decide, like, what makes sense for them. The other thing that we do that's pretty unique is every single action in our system is audited in perpetuity. So whether you're downloading or searching, you're doing something that's stored. So the city manager, the internal affairs bureau, those groups can actually say, hey, has anything nefarious been done? That's a big concern of people. So those two things tend to be a pretty. Pretty good levers for letting local politics dictate versus to your point, no one elected me to police chief of America. I just built a camera at my house.

[John]

I want to pitch you a startup idea that Blake Shoal, the founder of Boom Supersonic.

[Delian]

Boom.

[John]

Yeah, sure. He was thinking about doing this. Have you heard this story? He was thinking about building something before he started Boom, probably right around the time you were starting Flock. He wanted to make a smart stoplight that would have a camera on it and it would see, hey, there's no cars here. Why do I have a red light? Switch them. Feels like it would improve traffic flow. It's a situation we've all been in. You're sitting there at the red light. There's no one coming the other way. Flip the switch. Why is that a good idea? Is that something you could do? Is that something any company could do? Like, what's the market structure of the stoplight industry? Do you need to do some sort of private equity roll up? Walk me through your. If you were putting on a vc, how would you interpret that pitch?

[Garrett Langley]

My pushback on that pitch is to show me the incentive, and I'll show you the behavior. Who's getting promoted? Who's making more money? If we fix traffic, I don't think anyone.

[John]

Opportunity cost of the workers. It's all diffuse in the economy.

[Garrett Langley]

No, but this is the question.

[Jordy]

Don't you think a mayor could run on, hey, we have a lot of congestion here. We have a technology you'd have to do or something to show that, that you could reduce congestion if you had smarter traffic lights. Like, feels like some mayors don't.

[Garrett Langley]

Mayors get elected on two things.

[John]

Yeah.

[Garrett Langley]

Well, paved roads and low crime. That's it. So many things that matter. So, I mean, I think the product idea makes a ton of sense.

[John]

Yeah.

[Garrett Langley]

But I just go back to like, one of the only reasons why. Because you mentioned Andrel. When we were pivoting the business into local government, Trey Stevens was like, do not go sell to police. It's a horrible market. We tried it at Palantir. It's not going to work. It's not going to work. I was like, well, no, like, I'm a little bullish. He was an investor. He's an investor in the company. It's kind of nice. Might work. And what I didn't realize is systems like Palantir are too many steps removed away from solving crime at a local level. And like Flock had coincidentally built a product that solved crime right away. And so for a police department, crime is equivalent to revenue. So we weren't helping them save money, we're helping them generate revenue. And like, that does get a sergeant, lieutenant, a police chief promoted. That gets a mayor reelected. And that would be my pitch to Blake is like, we got to find a way to make sure this relevant to a mayor.

[John]

Yeah.

[Garrett Langley]

And like, just a little bit less traffic isn't going to move the needle and have them move off from having no technology and no cost structure.

[John]

Well, he's, he's busy building supersonic jets. He's got a good for now, but maybe, maybe that's the next thing he works on. I have a second startup to pitch you based on your answer to that question. Automated road paving startup. I go to the mayors and I say, road paving gets you paid and gets you in the job. Would that work? Is that a good idea? How would that play out? If you thought that process through, what advice would you give to a road paving entrepreneur?

[Jordy]

There was a YC company doing the little road.

[John]

I remember this. Yeah. But yeah, yeah, Walk me through your thought process.

[Garrett Langley]

So I actually think that's a great idea. We're working on something tangential to that. So one of the biggest issues is that to do what you're describing you have to know where the potholes are are. And cities have no idea where potholes are. And they rely on you calling 31 1, which I'm sure you both have done many times and said, hey, I'm just calling you to report a pothole.

[John]

Yep.

[Garrett Langley]

No you don't. And that also costs the city on average like $8 per call on a 311. So it's a really inefficient system. And so what we've been able to do is train our cameras to look for potholes. And so now we can actually report back general road conditions. And that is the beginning of the meal to say, hey, now we can actually be intelligent about where we should send people to go repave.

[John]

Yep.

[Garrett Langley]

And I think an automated robot that does the paving would be even better.

[John]

Yeah.

[Garrett Langley]

Yeah. I love that idea. I think I'm in.

[John]

That's amazing.

[Garrett Langley]

Thousand dollar check.

[John]

Fantastic. Well, you know where to reach him. He is of course.

[Jordy]

Oh, last, last wanted your reactions. We had a guy named Riley on yesterday who made a fine my parking cops. Did you see that?

[John]

Oh that.

[Garrett Langley]

That park was awesome.

[John]

Yeah.

[Jordy]

Yeah.

[Garrett Langley]

He's a little shut down and back up.

[Jordy]

It got shut down very quickly. I was impressed with San Francisco's reaction time on that. They shut it down like very quickly. But it's good fun.

[Garrett Langley]

Yeah, I'm a fan of it. I think most people don't pay for parking because most of the time you don't get a ticket. So.

[John]

Yeah. Well, thank you so much for hopping on the show.

[Jordy]

Great to get the update state.

[John]

Yeah. Congratulations on the progress and thank you for everything that you do.

[Jordy]

Yeah. Come back on any time.

[John]

Yeah, we'd love to see you. Have a great rest of your day.

[Jordy]

Let me with ten nine figure businesses.

[John]

Yeah. If you want to reach people in cities, you got to go to ad quick.com out of home advertising made easy and measurable. Say goodbye to the headaches of out of home advertising. Only Ad Quick combines technology out of home expertise and data to enable efficient seamless ad buying across the globe.

[Jordy]

Before our next guest joins, we did need to acknowledge that Mark Leonard has stepped down from Constellation Software.

[John]

Sad news for health reasons.

[Jordy]

We hope he's okay. Interesting timing. Basically called the top on.

[John]

Yeah, we talked to Carrie. No interest on the show. You can go pull that up if you want to hear our conversation with him about these private equity software, enterprise software roll ups. Mark Leonard was mixed on AI. Sort of unclear on on how it would affect the business long term. But the market did not like it and the stock fell off and the stock has fallen again on this very sad news. So we are of course sending him our best. The health reasons that he is stepping down for are unspecified at this time. So but please send your thoughts and prayers to. Thoughts and prayers, Mark Leonard. And we have our next guest in the waiting room, TVPN Ultra Dome.

[Jordy]

There he is, suited up.

[John]

How are you doing? Hello.

[Jordy]

I'm doing well.

[Matan]

How are you guys doing?

[John]

It's been too long. Yeah, we've seen you before in the TV panel. Welcome back.

[Matan]

Pleasure.

[John]

Give us the news. Give us the. Give us the 140 characters and the company refresh everyone and then give us the news.

[Matan]

Absolutely. So I'm Matan, CEO at Factory. @ Factory, our mission is to bring autonomy to software engineering. What that means, more concretely, we have built droids which are are autonomous software development agents. And more importantly, I'm here to tell you that they are the number one agent in the world. As we just released today in the terminal bench benchmark, which evaluates tools like Claude code, OpenAI's codec CLI, factory is number one.

[John]

Congratulations.

[Matan]

And also number three. And also number five. Pick any model you want. Factory is still number one. No matter how you slice it, our droids are simply the best agents in the world.

[John]

So excited to share that. What's the secret? What got you there? Is it pre training, post training, a bunch of RL stuff? Is it a data flywheel? Like what's, what's driving the growth?

[Matan]

Yeah, great question. So I think one of the biggest things is that most, if not all of the agents out there are built for one model in particular. So, you know, CLAUDE code is built to work with the Claude model. OpenAI's Codex is built for the GPT models. There are some other tools out there that aren't from the research labs that are focused on really like fine tuning their agent harness for one given model for any given step. But what we've done with our droids is make them fully model agnostic, which actually makes them more performant in the long run. It's kind of similar to if you were a human engineer and you only, let's say, studied one coding language, you would actually be a weaker engineer than if you studied all of them. It's somewhat analogous there in terms of how we've built these droids that now allows them to be the most performant with any model that you put in under the hood.

[John]

How are you viewing the market and the customer landscape? Automated software engineering that feels niched down from years ago, which was just the transformer based LLMs can write code. But as we actually dig in, we see that the needs of a Fortune 100 customer may be different than a mid market company, which is different than a startup, which is different than an SMB, which is different than a solo vibe coder, solopreneur. Where are you seeing opportunity in the market? How bifurcated is the market? It seems like you've wanted to be very general on the model side. Are you also trying to be general on the customer size side?

[Matan]

Yeah, great question. I mean, I think the thing that a lot of the other tools have missed is the fact that the further you go into the large, large enterprise, the less overlap there is between software development and coding. So for example, if you're a solo developer, your software development is basically just coding. You're not really doing code review. You're not doing that much in the way of documentation or testing or design docs. And so where we focus and why we call droids software development agents as opposed to coding agents, is that we focus on that whole end to end software development life cycle, which is really where, where a lot of enterprises are missing. Like there's study, there's the famous study that came out from MIT that said something along the lines of 95% of AI adoption efforts are failing in the enterprise.

[Garrett Langley]

I remember.

[Matan]

Yeah, exactly. And so, I mean, it kind of makes sense. Like if you think about software development.

[Jordy]

I love hitting you with the surprise sound effect. We'll get some more positive.

[John]

We're not bearish on you. It's just. That was good. It was perfect.

[Matan]

It was just too good. But you know, software development is a pipeline.

[John]

Right.

[Matan]

And if you focus on only one part of that pipeline, namely code generation. Yeah, and you expand that. I used to be a physicist. I don't know if you guys are big on fluid mechanics, but opening one part of a pipe and doing nothing to the others, you don't actually increase the throughput.

[John]

Sure.

[Matan]

You just create new bottlenecks. And so the reason why a lot of these efforts are failing for software development is they're focusing on just coding. But then that just punts the problem down to testing or code review or documentation. And that's why a lot of the other tools out there aren't seeing kind of the adoption and the real business outcomes that we are with the droids.

[John]

How do you see coding agents fitting into the consumer world? This might not be your business at all, but I noticed that the, you know, I've seen Incredible results just from asking a question that you could hit deep research with. But if I ask it to Claude Code or Codex, it can build an entire HTML Web page with JavaScript widgets and bar charts. And it just produces. It instantiates the information in a much cooler, it's interesting way. And I'm wondering how you're seeing crossover from advances in automated AI coding into a consumer world where they might not even know that they asked for code, but they got code. It's already happening a little bit. When you hit 03 Pro, it'll write some code to give you the answer. You don't even see it unless you unfurl the reasoning tokens. But how do you see that playing out in the mid to long term?

[Matan]

Great question. I think this is something that people aren't yet fully aware of, but this was actually the very first statement of our announcement, which is, is the best agents for software development are becoming the best agents for everything. And the reality is, because basically every problem can be broken down into some sort of software development problem. And you can actually take it from Anthropic themselves, literally. Yesterday, Alex Albert, the guy who runs Devrel at Anthropic, tweets out, you know, the best coding model will be the best model for many types of knowledge work code is how computers operate. Anything you do on a computer can be done through code. And this is really why Factory, being the number one software development agent, is really going to then lead to a lot of other tasks. And we're already seeing this in the enterprise. So we sell explicitly to developers, but already PMs, designers, even people on the operations side. So like finance, biz, ops, that sort of thing. We find that they're like sneaking their way in even though they didn't actually, you know, put any budget towards it. And they're starting to use droids kind of behind the back of some of the VPs of engineering. And this is really something that we've expected because of this fact that that code is really the language that computers speak. And if you want a computer to do something for you, you will eventually, through some means, need code.

[Jordy]

Couple, Couple questions. What, what models are you guys getting the most leverage out of today? Is it a mix? Are you, are you focused on. You said earlier, I think you're focused on a variety being. Trying to be model agnostic. But be curious where. Who. Who you're paying out on the back end.

[John]

Yeah.

[Matan]

So right now we achieved the number one score across the board on Terminal Bench with Claude Opus. But again, we are, you know, really focused on having the, the model agnostic stance because org by org, they might have different preferences. Also, what the best model is depends.

[Tyler]

What day it is.

[Matan]

Tomorrow there could be another new best and it's important that we have that ability to quickly swap them in. So that's one thing that I think is important. It's also even task by task, there are certain models that are better and we want to make sure that the user has that familiarity with the model so that they can go in and swap it out if there's a task that they're doing that GPT5 might be better for or it might be better for.

[Jordy]

You forgot to mention you raised some new money today.

[John]

Give us the news here.

[Jordy]

We got a gong here.

[Matan]

That is right. We have raised $50 million from NEA.

[Jordy]

JP Morgan and Nvidia JP Morgan.

[John]

Jamie Diamond's getting in.

[Jordy]

He couldn't. He couldn't help himself.

[John]

Couldn't help himself.

[Jordy]

Couldn't help himself.

[Matan]

Couldn't help himself.

[John]

I love it. Congratulations.

[Jordy]

That's our deposits, everybody. The world's deposits at work.

[John]

Talk to me about last question. We'll let you get back to your busy day. Talk to me about the branding. It feels like we just got the idea of an agent recently. Now you're kind of pitching droids. It's clearly your term for droids you're looking for. Yeah, yeah.

[Jordy]

People always talk about, you know, being. We're not.

[John]

How much of that is like a differentiation brand that you want to be specific to your company versus like a new coinage that you want to describe. A different way of working that you'd actually like to see other companies adopt. And if you were seeing the entire industry standardized around that particular piece of language, you would be happy. Or would you be like, hey, they stole our brand?

[Matan]

Yeah, I mean, I think generally, like agent as a term is here to stay. But the point is, as a kind of general purpose term, it's often synonymous with like poor quality or like a while loop wrapped around LLM calls. And I think what we want to do is to make good on our promise to customers, which is giving them that best agentic experience. And we do that through droids. At the end of the day, when you have a cold and you're, you know, your nose is running, you don't want a tissue, you want a Kleenex. Similarly with software development, you want the droids to come in there, right?

[John]

Okay. I love it. I love it. Well, well, congratulations on the round. Thank you so much for hopping by.

[Jordy]

Awesome progress. Thank you guys for having me.

[Matan]

Thanks.

[John]

We'll talk cheers soon. Let me tell you about Bezel. GetBezel.com, your Bezel Concierge is available now to source you any watch on the planet. Seriously, any watch. And we have our next guest in waiting.

[Jordy]

I guess we gotta wait to talk about this. Two new launches, one from Meta Alexander announced Vibes, which is a Meta AI app for short form AI generation generated videos.

[John]

Okay, yeah. YouTube launched something with AI generated shorts leveraging VO3 recently. What else?

[Jordy]

There's a new ChatGPT product called Pulse.

[John]

But Pulse, we will dig into that.

[Jordy]

Let's get into it with our next Francis over at Invisible.

[John]

Welcome to the tv. Francis, how are you doing?

[Jordy]

What's happening? Welcome to the show. Doing great.

[John]

Excited to be here. Thanks so much for hopping on the show. Kick us off with an introduction on you, the company. Any new news? You got to share. What's new in your.

[Francis]

Yeah, well, as you saw on Bloomberg, we've raised $100 million this year, which.

[Jordy]

Is a big turn of events. There we go.

[John]

Valuation.

[Garrett Langley]

Yeah.

[Francis]

Crazy thing that, you know, when you saw Meta acquiring scale, they had raised $1.8 billion and we had only deployed 6 million. We scaled profitably to 134 million of revenue last year.

[Jordy]

So that is wild. I remember I heard about you guys. I forget what context. I heard about you guys for the first time, but even this was probably two years ago, even back then I was like, you guys were somewhat under the radar. I felt like. But I heard some of your revenue numbers back then. I was like, what. How have I not heard about this company? But yeah, we wanted to invisible for not much longer. Yeah.

[Tyler]

No longer.

[John]

Buy the new domain. You're visible.

[Jordy]

Visible technology. Give us an. I mean, I'd be helpful to hear like where. Where you guys have. Have an edge in. In the market broadly. And then I. Yeah, I want to kind of. Yeah. Understand.

[John]

Yeah, yeah. Problem set core. Like what you're actually replacing, where customers are getting the most value. Anything like that would be super helpful.

[Francis]

So 10 years ago, when we founded the company, there was a question which is, if there's an app for everything, why isn't everything perfect yet? And Salesforce was the first SaaS company in 1999. For the last 25 years, every enterprise software company has been a SaaS company. And this has actually put customers in a pretty absurd situation where if the customer wants a cake, Silicon Valley will not sell them a cake. They will sell them tools to make a cake. And the customer then has to hire a systems integrator like Accenture to stitch together all these SaaS applications into an end to end solution that actually works for the business. And so that is what we were disrupting. And Palantir was not public yet, so they weren't a well understood comp. We were kind of like an ugly duckling because we were talking about AI services. And so it's just a fundamentally disruptive business model.

[Jordy]

So you were competing initially with someone like an Accenture to integrate existing software systems set, Right?

[John]

Right, yeah.

[Francis]

We build custom AI applications for enterprises and governments. And so you can think of this very different than SaaS like a triangle. We have the horizontal platform which is very powerful, but you have field engineers and field CTOs in a forward deployed motion that builds custom AI applications that actually solve the problem for the enterprise, the government. And our insight was that even though every solution would be custom, the horizontal platform would allow you to sort of build infinitely customizable software over time.

[John]

That makes sense. We've been seeing Marc Benioff and Dr. Karp going at it over various contracts. Salesforce, which you already mentioned, Palantir, which you also mentioned, are you in that knockout drag out fight? Have you found a differentiator around industry or size of problem or are you just going in the arena?

[Francis]

So Salesforce was founded in 1999, Palantir was founded in 2003. So way before the Gen AI era. So we're in a sense like the gen native way of doing this. We hired Matt Fitzpatrick who previously ran McKinsey's Quantum Black Labs and he's now our CEO. And after years of being capital efficient this round sort of enables us to go into a pre IPO motion. And yeah, if you're a public markets investor, you don't really have that many options for buying AI today.

[Jordy]

So.

[Francis]

And this is generally true for the enterprises, the customers themselves, if you want to build custom AI solutions, Palantir is like a data integration and decision making support company. So they really, they really focus on that. But if you have a problem in anywhere else in your business, how do you build a custom solution with world class field engineers? It's a very different type of engineer, very different type of go to market person, very different type of business that is familiar building custom solutions on the enterprise. Enterprises do not want their data to leave their systems so they need all the solutions to be on prem and containerized and we have the ability to build in that way.

[John]

Do you think that there's a shift in the AI era to large enterprises doing more of these sort of like semi custom solutions is that's going to be a continuing trend because it feels like last era was very much like rip out the old custom on prem solutions and go to some sort of like one size fits all cloud solution.

[Garrett Langley]

Exactly, yes.

[Francis]

And this is a reversal. We're going all the way the other way. And I think that's because enterprises ultimately need proprietary and custom solutions. So in the SaaS era, like I said, they were stitching together things and they had to do that with some combination of like their internal engineering function and systems integrators. Integrators and systems integrators are not tech companies. They're going to overcharge underdeliver, you're going to pay them by the hour. So their incentive is to bill you as many hours as possible without getting fired. And that's not really aligned with efficiency. And so in this era, I think enterprises are realizing it's going to be very, very difficult for them to build world class engineering teams and to build a platform like the one we have where we can take the best models, latest models, which we train, we have an AI training, training business and deploy them in the enterprise to actually solve the business use cases that they, that they have.

[Jordy]

Yeah. So how much should we read into you guys transitioning away from training? Is that a business that is.

[Francis]

We're not transitioning away. We are fully committed to training. So actually the move of meta acquiring scale basically cleared the field. And so it's an inherently oligopolistic market structure. Structure where there are a few players that have invested as much as we've invested over as many years as we've invested. And so we have like 20,000 experts and that number is scaling very quickly. We can hire like a thousand experts a week. So when you're asking a model a question about the chemical properties of silver or the history of Sweden or whatever, you're asking a model. We have PhDs, masters, experts in every subject that are training these models and there's evals and, and lots of inputs into making these models.

[John]

Great.

[Jordy]

Got it. So leveraging the experience on the training side in order to help the to.

[Francis]

Deploy in the enterprise.

[Jordy]

Got it, Got it. The business model for the deployment side is just going to repeat it back to you. So I understand is there's some period that looks more like services, but it becomes a piece of durable software that they can use for a long model.

[Francis]

Just like Palantir.

[Jordy]

Exactly. Yes. Got it.

[Francis]

Cool. AI services is exactly that way.

[John]

Yeah.

[Francis]

And that puts us in an investing mode. We literally invest in our customers. So we put, you know, field engineers, field CTOs in with our clients, and there's an investment period to build the solution. But once the solution's in place, that is very durable revenue.

[Jordy]

And so you're like a nightmare for someone like an Accenture. Some of these big consulting companies that don't really have the true expertise around training these models and you get to. And have a lot of organizational bloat. Is that right? Yes.

[John]

So.

[Francis]

Matt, who's our new CEO, we bonded over ancient Greek and Roman history, and he calls it the Battle of Thermopylae. Because even Accenture has. Has like a million people worldwide, has some huge headcount. If there's three, if the pass is only yay wide and there's 300 people at the pass, and we're always winning at the pass, then we're going to win every battle. In other words, if, you know, I believe our technology is superior, dramatically superior already to traditional systems integrators. So if you're a buyer and you're hearing Accenture's pitch and invisible's pitch, which one are you going to pick? The Battle of Thermopylae. Spartans win.

[John]

It's fantastic.

[Jordy]

Spartans are coming. Coming for it.

[John]

What a market. This is just a fantastic market.

[Jordy]

Awesome.

[John]

Well, congratulations.

[Jordy]

Congrats on all the progress.

[Francis]

Great to be on the show. Big fan.

[John]

Appreciate it.

[Jordy]

Thanks for having me. You said prepare to go public. What timeline are we thinking about? Is that multiple years out, is it?

[Francis]

We think in terms of how many hundreds of millions in revenue do you need to have before the story is just obvious to a public markets investor. So we really want to build a business for all markets. So the intrinsic value of the business, the ability to survive in any condition is key. And then we'll take it public.

[Jordy]

Awesome. All right, we'll come back on anytime. This is fun.

[John]

We'd love to ring the bell. Cheers to you.

[Francis]

Great to have you on. Thanks.

[John]

Up next, we have Jacob from. Sorry, David from Juicebox coming into the studio. Juice Box Restream waiting room. Juicebox has some fundraising news. The gong's already warmed up. How you doing?

[Jordy]

Welcome.

[David]

Thank you. Thanks for having me on, David.

[Jordy]

Good day today.

[John]

Introduce yourself. Tell us it picks.

[Jordy]

Kind of a good day to drop a cinematic launch video.

[John]

This is a good day for it, but take us through it. Introduce yourself. The company, the news.

[Francis]

Yeah.

[David]

I'm David, co founder of Juicebox. JuiceBox is an AI recruiting platform. We help Our customers win the talent war. And we do that by helping them find and engage the best talent. And yeah. Today we're announcing our $30 million Series A and previously unannounced $6 million seed.

[John]

Boom.

[Jordy]

Hit it a few more times. Few more times. There we go. There we go. Big day. Okay. AI winning recruiting wars. What is that? What does that mean?

[John]

How many? How many long until you're out of business because no one has a job anymore. If I thought AI was going to get rid of him.

[Jordy]

All the jobs. No silly, no silly questions. Are you working more with early stage, growth stage public companies? All the. Where are you kind of focused right now? As I saw. I admit I only saw half the launch video, so you had me up until whatever, 50%.

[Delian]

Nice.

[David]

Did you see the part with the zuck impression?

[Jordy]

I did see the zuck impression.

[David]

You made it through the important part.

[Garrett Langley]

Yeah.

[David]

We work with all kinds of companies ranging from founders doing their first hire all the way to growth stage companies. Few Fortune 500 customers as well. Some of those companies are Perplexity Ramp, Quora and a bunch more. I think the common thread for where we're able to add the most value is, is if the right person for the role is actually really hard to find. And that can be because they have a specific skill set, a specific set of experiences, something that makes them unique and uniquely positioned to really excel in that role.

[John]

I think of hiring as kind of like some sort of chain of events with different point solutions. There's actually finding talent job platforms. LinkedIn. Indeed. Then there's, you might want to send someone a test or have them fill out a form or process resumes. You need an applicant tracking system. I've seen other point solutions for send a video and then ask some questions and then process the video and let the user or the hiring manager kind of review videos. There's a whole bunch of different things. Do you see yourself as kind of a cross journey platform? Are you focused on a particular landing zone? Where's the product position today?

[David]

Yeah, it's a great question. I think of the recruiting space is really happening. Having two different ways in which you could add value. One is finding net new candidates, people that you wouldn't have discovered or wouldn't have gotten into your pipeline in the first place. And then everything that's carrying through the pipeline and optimizing that pipeline. And the latter is usually about like saving time and optimizing conversion rates and the former is about making sure the right talent is speaking to you in the first place. We're focused on that part. And so our goal is to help companies discover talent, talent that they wouldn't otherwise. And we do that by combining a bunch of different data sources and then using large language models to run the search and surface those profiles for you. And so if you think about what like Recruiter does today on say LinkedIn recruiter or like a typical search solution, they set a bunch of filters and then start reviewing profiles one by one. It's super manual, requires a lot of thought still to like think of what could make that profile a fit. And that's exactly the process that we're able to do with LLMs.

[Jordy]

So is this a direct replacement for LinkedIn recruiter? Are you trying to get people to just be able to.

[John]

Or do you Want to puppeteer LinkedIn with a screen recorder or API or something like widget? I don't know if they'd like that, something like that. I don't know. It depends. I mean there's been some companies that have done it successfully. Some of them got acquired by LinkedIn, but I don't know.

[David]

No puppeteering of LinkedIn. Most of our customers are existing LinkedIn customers. Our goal is to, to help you find net new talent and do so in a more efficient way. So it's really about kind of enhancing the workflow of the recruiter and enabling them to do that search. That would just be too manual or too time consuming to do otherwise. Like looking through 50,000 software engineering profiles is just not something that's like feasible. But for an LLM it's very feasible and can do it in a couple minutes.

[John]

So there are different pools of talent for. I mean we do media video production here. We might want to hire somebody who doesn't really have a LinkedIn presence, but they might have an Instagram account or they might have a personal website where they've done some, they put up their show reels or what they've worked on. Do you have crawlers that could go out and find those profiles on the Internet? Like how could I think about the surface area of you going out and finding me candidates and sourcing?

[David]

That's right. So we look at, at a bunch of different data sources for different types of roles. So I'll give two examples. One, on the engineering side, GitHub profiles a ton of value on those, especially where traditional LinkedIn profiles or resumes might be a bit more sparse, especially for engineers who don't put a ton of info on there. Githubs can be really rich and a really interesting Data source. Meanwhile, on the sales side, often what we see is customers want to find sellers who have experience selling at a specific type of buyer Persona. And so there it's actually a bit more about the company data, data, you know, what type of companies does their current company sell into? What type of a platform are they selling? Is it a SaaS product, is it a usage based product? And more. And so all of that information we enrich and we try to aggregate upfront so we can make those decisions for you and help surface the right profiles.

[Jordy]

There, there's another. They put an example, they have a tag on their site called Likely to Switch, which would be like you have a round of layoffs, funding or vesting timelines. You know, people don't really think about that. You can see like, okay, this person's been here for four years, they're probably getting a refresher, but they're vested out. That's pretty cool. What do you think? Do you have a strong thesis yourself around employment over the next, you know, 10 years? I'm assuming you know, Sequoia leading this round. I think that says Sequoia confirmed, not AGI pilled confirmed. No, but it says that we're still going to have talent wars in a decade. Right? That's, that's what that tells me. But how do you think about it?

[David]

Yeah, I think if you're AGI pilled, it actually means hiring the right talent is even more important. And the reason for that is that if you think about, of the output of a given person is usually constrained by their time, their previous knowledge and context and then whatever tooling they're using. And so if the tooling that they're using is getting exponentially better, they use LLMs to automate a bunch of the things they'd otherwise do. They're much more productive than they would usually do. And that's all a multiple of the person or like the initial person and their kind of raw capacity, having the right person in that role becomes even more important. Important because if AI, basically 10x is whatever you do, you want to have the highest baseline that you can add that 10x to. And so it gets even more important to have the right talent on your team. And if you think of that in the context of a software Engineer, if a 10x software engineer becomes 100x, you want to have as many 10x software engineers as you can. And so my view is that the race for talent will become more and more competitive as AI gets better and better. Because having the right people on Your team has that outsized impact and I think we're already seeing some of that in the War for talent and the AI labs, but I think more and more of that will trickle down into the rest of the economy as well.

[John]

What do you think about outcome based pricing famously used in the recruiting industry? Most human recruiters, even if they work for a firm, they might get one month salary as a bonus if they place someone successfully versus LinkedIn, which is subscription software completely not outcome based. What model do you think will dominate in the future and what are you doing?

[David]

Yeah, it's a really good question. So we have like a proceed pricing normal SaaS model, but then we also have an agent product which is priced per role that the agent works on. And so it's not quite outcome based, but it's more like usage based. How many roles are you deploying the agent for? For over time we want to get closer and closer to the outcome based pricing as is possible. If you think of recruiting agencies, it's pretty common to do like 20 to 25% fee of first year salary, which unlike a dollar value is much, much more than one could probably charge for a SaaS subscription. And so there's definitely a lot of things that are attractive there. At the same time, I think the market's maybe not quite there yet or not quite ready to pay for software on a say percentage of higher model though, you know, I hope we'll be able to push in that direction over, over time as well.

[John]

Fantastic. Well, congratulations.

[Jordy]

Super cool. Really insane progress.

[John]

Yeah.

[Jordy]

And congrats on the new round.

[John]

We will talk to you.

[David]

Thanks for having me on.

[John]

Have a good rest of your day.

[Jordy]

Thanks for coming on.

[John]

SAML launched a new feature today called Pulse. It's in ChatGPT, initially available to Pro subscribers. That's the $200 a month tier, right?

[Jordy]

Yeah.

[John]

Pulse works for you overnight and keeps thinking about your interests, your connected data, your recent chats and more. Every morning you get a custom generate custom generated set of stuff you might be interested in. It performs super well. If you tell ChatGPT more about what's important to you in regular chat, you could mention I like to go visit Bora Bora someday or my kid is 6 months old and I'm interested in developmental milestones and in the future you might get useful updates. Think of treating ChatGPT like a super confident personal assistant. Sometimes you ask for things you need in the moment, but if you share general preferences, it will do a good job for you proactively. This also points to What I believe is the future of ChatGPT, a shift from being all reactive to being significantly proactive. Completely agree with this concept and extremely personalized. This is an early look and right now only available to pro subscribers. We will work hard to improve the quality over time and find a way to bring it to plus subscribers too. That sounds compute intensive. That sounds like they're going to be running essentially an O3 Pro level query, a ChatGPT 5 Pro level query every night, asking based on what's going on in the news, based on what this person searched for, based on all the chats recently. Let's summarize and put together some sort of dossier for them and service that. So that's basically one big fire up the GPUs every single night. You got to get the customers to pay for it, at least in the short term. But what do you think, Tyler? You think you'll use this?

[Tyler]

It's pretty interesting. I'm wondering, is this the thing that Sam Alton was talking about of the compute intensive thing? They're rolling out?

[John]

He said this week we will be launching a couple compute intensive things. Some of those will probably be announced at Dev Day. This is one that he's just announcing this week.

[Jordy]

This feels like it's effective, effectively doing something like just kind of hanging out in the background. Hanging out in the background somewhat actively, somewhat passively, just gauging what your interests are. I can see this as almost like having a Google alert set up.

[John]

Amjad from Replit says, reminds me of Google now, but how do I get started? I don't see it in the app, so it's obviously rolling out slowly.

[Tyler]

You can definitely see like an agent being built built into this. That seems very natural.

[John]

Totally. And I feel like ChatGPT was already starting to sort of surface this concept of like, hey, do you want me to do this every week for you? Do you want me to do this every month for you? But I haven't actually set up any of those cron jobs and had it stick around and become part of my workflow. But I like the idea of it and I think that the big thing is just for retention. If every time you open the ChatGPT app in the morning, instead of just an empty box, you're greeted with like, here's some interesting stuff, or you're getting.

[Jordy]

A push notification or a push notification.

[John]

That'S going to be huge for retention.

[Jordy]

Or it's like, hey, this product launch, do you want to buy this? You want to buy this? Let's pull up this video from Alexander Wang. Let's just share vibes. A new feed in the Meta AI app. Let's see if they beat the the slop allegations. I think it's powered by Mid Journey, so it looks pretty cool.

[John]

Yeah. I mean Mid Journey fantastic model looks pretty good. Yeah. I wonder how this is actually gonna. So separate app is what he's saying.

[Jordy]

It's a new feed in the Meta AI app.

[John]

Okay. In the Meta AI app. So not, not you would expect this to be baked directly in Instagram. That's probably too much compute out of the gate to just drop it in as a filter or something or button Instagram because if you have a billion people pushing that button, you're just gonna get, get swamped. I think this beats the, the slop allegations. There's some cool stuff you could do with this. I mean video generation looks good. Looks looks VO3 level to me.

[Jordy]

I don't know.

[John]

Obviously these were curated and selected, but.

[Jordy]

We'Ll have to get in the app, Tyler, because before we do the show tomorrow, please use the app for like, I don't know, like 12 or 14 hours, something like that. Just straight, no, no breaks, wire headed. Just, just lock in.

[John]

Just lock in.

[Jordy]

Max. Max Conrad in the chat says, I'm tired of hearing about fundraisers without business metrics. Top line, bottom line, value created for customers. Good point. We're.

[John]

We want to push people.

[Jordy]

We want to push people harder. To say, if you want to come on, you got to get, give us some numbers. And if you don't got numbers to share other than the headline, we should have, we should have a very small credit to Juice. I think they've been actually crushing it, raising money.

[John]

Yeah. I mean that is a market where money flows very freely because you're as a business, you're ready to sign a check for $200,000 to hire someone as a software engineer. 150, you're like, yeah, I'll pay $10,000 to get the job done. $20,000. So the money flows quite freely. And that's why there's so many, many executive recruiters, software engineering recruiters that make a ton of money just working basically for themselves just as talent agents moving things around. Well, Meek Mill and Elizabeth Holmes were going back and forth on X. Elizabeth says, thanks meek, currently serving 137month sentence in federal prison, would love to work with you on reform. Here's some legislation I have drafted. Your story inspired me. And Meek Mill says, let me check your story out. And Will Brown says, Elizabeth Holmes, this Year is our year. Elizabeth Holmes. We can never forget this tiger. Meek Mill.

[Jordy]

I pray for times like this to rhyme like this. I know. Focus on it too.

[John]

It's a great one.

[Jordy]

Yeah. I think they're thinking about different aspects of reform. Well, maybe Meek Mill would want YC arrest where she has to lock in and just repeatedly build the device forever.

[John]

I like that we don't rap, but we do sing.

[Jordy]

Find your happy place. Find your happy place.

[John]

Tyler missed it.

[Jordy]

All right, I got me a second to kind of like.

[John]

Yeah, you want to try?

[Jordy]

Note there. Find your happy place. Find your happy place.

[John]

Book of wanderers Conspiring views, hotel grade amenities, dreamy beds, top tier cleaning and 247 concierge service. It's.

[Jordy]

Well, we got breaking news. Trump signs order to approve the Tick Tock deal, avoid the US ban. The chat was on it way before we were. And let's see. TikTok is poised to be spun off into a separate US entity to comply with the 2024 law requiring the China parent based parent company ByteDance to divest or face a US ban. Trump said, I had a very good talk with President Xi. A lot of respect for him. Hopefully he has a lot of respect for me too. And we talked about TikTok and other things, but we talked about TikTok and he gave us the go ahead. Under the deal, a group of US investors including Oracle and Silver Lake are set to take a majority stake in the new Tick Tock entity. Let's give it up for Silver Lake. Good to see them throwing some size around. As well as Oracle, ByteDance will maintain less than 20 in equity to comply with the investor ban law. Vice President Vance said the company will be valued around 14 billion. Feels low. Weirdly low.

[John]

Low. Just the US business. I don't know, I felt like. I mean we talked to Sean Frank and it sounds like they were losing a lot of money on TikTok shop and some of the. I mean the growth had probably plateaued with.

[Jordy]

Well, they were just losing money in general.

[John]

Yeah, but you got to imagine that that monetizes pretty well. It's such a big network, so much time on site. But yeah, it's. It's being. It's trading like a Snapchat or a Pinterest basically like a non meta property. A non Google YouTube property.

[Jordy]

Oh well, yeah, it's crazy.

[John]

Well, keep checking in on it.

[Jordy]

So TikTok valued less than perplexity. Okay, honestly, now I can see why Arvin was trying to get a bid in.

[John]

True.

[Jordy]

Yeah, so much better.

[John]

But yeah, I'm already at.

[Jordy]

Basically, Brad Adcock should have, should have taken a crack.

[John]

He could have absorbed, easily absorbed his market cap.

[Jordy]

Anderal could have.

[John]

True.

[Jordy]

There's a lot of companies that could have absorbed.

[John]

I'd like to see Palantir pick them up.

[Jordy]

Run, run the data at 14. 14 billion is crazy.

[John]

That is crazy.

[Jordy]

Crazy low. That's gonna.

[John]

I. I'm surprised the CCP said yes to this.

[Jordy]

Yeah. What's the, what's the catch? I mean, this feels like it's worth.

[John]

Like it feels like there's other chips on the table that are being traded around. Whether it's like rare earths or, you know, some sort of, you know, deal on tariffs or. This is such a multi pronged deal between different countries and stakeholders. The UN thing just happened and so there's a whole bunch of different pieces and the art of the deal is not, not a single iterated price, a single asset in the moment type thing. Could Truth Social have picked it up? Truth Social's right around there too. No, they've, they've fallen. They're in the single digit. Still a unicorn, right? Our president is still a unicorn tech founder, I believe.

[Jordy]

4.7 billion.

[John]

There you go. He's a unicorn founder, folks.

[Jordy]

When's earnings? On November 7th. So tune in. We got to lock it.

[John]

I don't think they do. JT gives a speech. He should.

[Jordy]

That would be crazy.

[John]

What you got, Tyler?

[Tyler]

Do we know? I think there are rumors that like the TikTok algorithm would still be governed by the Chinese, but then it would run on American hardware or something.

[John]

We're doing the inference. Yeah, we're going to do the inference. They'll do the training, we'll do the inference.

[Tyler]

It's like the algorithm with Chinese characteristics.

[John]

Yes, but I am somewhat bullish on the idea of doing some post training on top of their algorithm or doing some, some secondary like post inference. You see the ranking of the feed, you're doing analytics on that and seeing like, okay, like there's still some like propaganda stuff here.

[Tyler]

Was that confirmed that that is what's going to happen though?

[John]

I don't know. I don't know if that was confirmed. But there are. It's not a total black pill if the training still happens there. Because you can do so much post training, I think, and monitoring and even just having the data. You can start running analytics and understanding like what type of content is showing in what context. Like are there actual, like, you know, are certain trends or keywords or is there certain censorship of Certain ideas or promotion of certain ideas. At least if you have access to the data of what's being served, what TikTok users are watching, you can then understand. And then you can apply pressure or, you know, post training or anything else. Anyway, in other news, the Lucy nicotine vending machine has arrived at Palantir. This was a journey. I worked with Eliano on this and John says Palantir has a climate controlled Lucy vending machine for their employees in their office. And you're bearish. It was a lot of fun. So we'll be sending out a few more of those. Hopefully getting one in the TVP and Ultradome soon. Something last thing was the Financial Times has an article about America's biggest corporations. Keep talking about AI but struggle to expand. Explain the upsides. We'll dig into this another day. But they analyzed hundreds of filings that Suggest S&P 500 constituents are clearer about the technology's risks than its benefits. And another one of these data points of Fortune 500 companies being reticent to adopt AI. I'm not sure if it's just blanket bearish for Fortune 500 companies. If you're a big enterprise and you're not able to figure out a way to deliver, you know, positive roi, when a magical new technology comes along, it might not be a good sign for you. Jordy, what else do you want to talk about today?

[Jordy]

Yeah, I was just confused. I was trying to dig in and see. I didn't see a 16Z in the announcement anywhere.

[John]

Oh yeah, they were supposed to be right. Maybe they pulled out or something. I don't know. I like the idea of the Ben and Mark show just being hard coded into the first post algorithm. They got Rick Rubin on there. Show me some Rick Rubin, TikToks, some Torrenberg, little Chris Dixon in there, some KB. This would be a good TikTok algorithm.

[Jordy]

They still could be in it, but we'll see. Well, we can ask. It's out.

[John]

I hope the thumb is on the scale regardless of their ownership position.

[Jordy]

Putting thumbs on scales.

[John]

Big fan of thumbs on scales.

[Jordy]

Anyways, without further ado, we, I think, got to get on with Taipei.

[John]

I think we do. So I think we do.

[Jordy]

We will see you folks tomorrow. Thank you for tuning in.

[John]

Thank you for tuning in.

[Jordy]

Leave us a review on your favorite podcast.

[John]

Please do.

[Jordy]

If you're listening there and we love you.

[John]

We will talk to you soon.

[Jordy]

See you tomorrow.

[John]

Goodbye.