Google DeepMind Reorgs, Rainforest Discoveries, Monkey Prices Surge | Harley Finkelstein, John J. Giamatteo, Jeremy Allaire, Mackenzie Burnett

Summary

Podcast Summary: TBPN – August 5, 2026

Episode Theme:
This episode of TBPN, hosted by John Coogan and Jordi Hays, dives into a whirlwind of major tech news, with a focus on the massive Google DeepMind leadership shakeup, discoveries about ancient Amazon civilizations, a surge in monkey prices driven by biomedical research, the state of agentic commerce and financial infrastructure, and provocative interviews with Harley Finkelstein (Shopify), John J. Gimatteo (BlackBerry), Jeremy Allaire (Circle), and Mackenzie Burnett (Ambrook). Woven throughout are themes of AI’s impact across industries, the evolving tech landscape, and the interplay between innovation, organization, and regulation.

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Table of Contents

1. Google DeepMind Reorg: What Happened and Why It Matters
2. Ancient Amazon Civilizations: Lidar, Population Revelations, and Implications
3. Soaring Monkey Prices: Inside the Laboratory Supply Squeeze
4. Interview: Harley Finkelstein on Shopify, Agentic Commerce, and AI Agents
5. Interview: John J. Gimatteo on BlackBerry’s Pivot and Secure Embedded Systems
6. Interview: Jeremy Allaire on Circle, Stablecoins, and Agentic Payments
7. Interview: Mackenzie Burnett on Ambrook, AI for Deskless Businesses, and Growth Tactics
8. Quick Hits: RL Environments, Super Yacht Drama, and More
9. Notable Quotes & Memorable Moments

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1. Google DeepMind Reorg: What Happened and Why It Matters

(00:02–20:59)
Main Points:

• Demis Hassabis Stepping Down as CEO: Legendary AI scientist and DeepMind founder Demis Hassabis transitions from CEO of Google DeepMind to Chairman and becomes Alphabet's Chief Scientist.
  • "I've decided that now is the right time for me to hand over my day to day operational responsibilities at GDM so that I have the time and space to focus on the big picture..." — Demis (reading his statement) (05:54)
• Jeff Dean Departs after 27 Years: Chief Scientist Jeff Dean and Google Senior Fellow Sanjay Ghemawat leave to start a public benefit corporation, Discovery Loop, focusing on accelerating machine learning, science, and engineering progress.
  • "Jeff Dean is the Chuck Norris of computer engineering." — John (00:39)
• No New DeepMind CEO: DeepMind will now be led by CTO Cora (Cory Cavoulu), but with no standalone CEO, hinting at changing organizational significance.
• DeepMind’s Value and Integration Across Google: Rather than a siloed unit, DeepMind’s work on Gemini models is dispersed across products (YouTube, Docs, Gmail, Ads, Chrome).
• Loss of Momentum and Talent: Loss of key visionaries (Noam Shazeer, Jeff Dean, Demis) signals a possible gap in leadership and research talent retention.
  • "Who is going to fill that void from a leadership standpoint? How are they going to be able to recruit the best researchers in the world?" — Jordy (14:26)
• Google’s AI Struggles Despite Advantages: Despite leading research, Google is outpaced in certain AI applications, partly due to corporate inertia and conflicting business priorities (external vs. internal compute).
• Community Reaction & Internal Drama:
  • Notable subtweet from Susan Zhang characterizes DeepMind's leadership as "slumbering execs" and "terrorists", highlighting internal discord.
    • "If you're high enough up there, you can pretty much be a terrorist and hold orgs hostage..." — Susan Zhang (10:50)
• Speculation on Future Direction:
  • Host expectation that Google will shift to a capital partner (Nvidia/Amazon/Microsoft model) rather than full-stack lab operator.

Memorable Quotes:

• "Compilers don't warn Jeff Dean. Jeff Dean warns compilers." — John (01:50)
• “It's time for AI to prove its unequivocal value in the world. And what better way to demonstrate that than to help finally cure diseases like cancer?" — John, quoting Demis (12:25)
• "A lot of the initial energy around OpenAI was a concern that Google would control AGI." — Jordy (20:13)

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2. Ancient Amazon Civilizations: Lidar, Population Revelations, and Implications

(38:29–41:58)
Main Points:

• A new lidar survey uncovers thousands of geoglyphs in Acre State, Brazil, revealing a previously unknown civilization (Aquari) that may have supported 1.25–3 million people circa 500 BCE–950 CE.
• Advanced earthworks were likely ceremonial and civic centers, pointing to an interconnected society and a complex, engineered Amazon ecosystem—not isolated villages as previously thought.
• Lidar and sensor innovations continue to rewrite assumptions in archaeology.

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3. Soaring Monkey Prices: Inside the Laboratory Supply Squeeze

(33:58–38:29)
Main Points:

• The price for lab monkeys in China doubled in a year (to ~$26,000 per monkey) as research demand for preclinical testing, especially for next-gen biologics, outpaces breeding capacity.
• Implications: China as a drug discovery hub, animal rights debates, possible bottlenecks in biomedical innovation.

Quotes & Moments:

• "Do you think it's time to ape in?" — John (34:36)
• Infinite monkey theorem banter—tying randomness and LLMs: "Is it possible that our modern AI systems are monkeys just clacking a bunch of keys and this is just an AI bottleneck?" — Jordy (37:45)

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4. Interview: Harley Finkelstein on Shopify, Agentic Commerce, and AI Agents

(45:27–63:47)
Main Points:

• Shopify’s Blowout Quarter: $116B GMV, $2.6B revenue, $1.7B gross profit, strong growth streak (~30%+ five quarters running).
• Agentic Commerce Trends:
  • AI-driven traffic and orders up 3x; smaller, niche merchants benefit more than the big box stores.
  • Shopify catalog conversions with AI agents perform 2x better than general web scraping.
  • “Agentic” commerce levels the playing field by surfacing product attributes relevant to customer preferences (e.g., “Is this dress formal enough for a wedding?”).
  • "Agentic commerce is merit based. It is not based on who is supplying the most amount of ad dollars." — Harley (50:46)
• AI Agents for Merchants:
  • Shopify’s Sidekick and Autopilot help new merchants reach milestones and run operations.
  • 8% increase in new merchants reaching their 5th order within 15 days using AI onboarding.
  • Sidekick increasingly handles analytics, reporting, and optimization (bundles, SEO, best practices).
  • "We want to deliver the best practices across hundreds of billions of dollars of GMV everywhere that goes to Shopify to anyone using the platform." — Harley (59:12)
• Future Vision (2035 & Robotics):
  • Democratizing manufacturing with robotics will make it easy for anyone to launch new products and become an entrepreneur.
  • Example of “Gamerstown” app built atop Shopify’s billion-product API demonstrates open innovation.

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5. Interview: John J. Gimatteo on BlackBerry’s Pivot and Secure Embedded Systems

(64:47–78:39)
Main Points:

• BlackBerry’s Transformation:
  • Evolved from smartphone pioneer to embedded software powerhouse; now powers over 275M cars and a range of mission-critical communications.
• Key Markets:
  • Focus on secure, certified OS for automotive (“the Windows of the car”), industrial automation, robotics, and medical devices.
• AI Adoption:
  • Pragmatic, cautious deployment—especially in safety-critical code, with only selective use (testing, customer service, go-to-market).
• Cultural DNA:
  • Security, trust, and innovation have remained constant across BlackBerry’s history.
• Partnership & M&A Philosophy:
  • Works closely with ecosystem players (Nvidia, Qualcomm, Arm, Bosch) and considers M&A only if there’s a capability gap to fill.

Quotes:

• "If it needs to be safe, secure and certified, that's really our value proposition." — Gimatteo (70:02)
• “The operating system that powers all things that go on in the car, particularly on safety critical types of functionalities..." — Gimatteo (66:09)

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6. Interview: Jeremy Allaire on Circle, Stablecoins, and Agentic Payments

(80:01–97:26)
Main Points:

• Stablecoins Mainstreaming:
  • USDC is now core to global finance; 70% share in real-world payments, traditional institutions deeply integrating stablecoins.
  • "All of the financial system is going to be moving to being run by software on the Internet... programmable money all on open infrastructure." — Jamie Lair (Jeremy Allaire) (82:31)
• Agentic Economy Outlook:
  • Not just agent-driven purchases, but agents as units of labor—a forthcoming labor marketplace for AI agents to do actual knowledge work across organizations.
  • Infrastructure for reputation, identity, and payments for agents is growing.
• Adoption Patterns:
  • Growth in net new (stablecoin native) payment flows, especially where existing payment infrastructure is weak (cross-border, global treasury).
  • Gradual “upgrading” of legacy pipes via stablecoins.
• Physical Infrastructure:
  • Behind-the-scenes, major payment rails, custodians, and asset managers now run validator nodes for blockchain-based money, requiring high uptime and security.
• AI Risks & Regulation:
  • AI’s cyber capabilities raise the security bar for crypto infra.
  • Advocates open source / open protocol approaches as “in code we trust”.
  • Expects heavy regulation for AI and continued evolution in crypto oversight.
    • “These are foundational utilities for society and they’re now cyber weapons, if not other types of weapons... there’s going to have to be regulation.” — Allaire (95:20)

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7. Interview: Mackenzie Burnett on Ambrook, AI for Deskless Businesses, and Growth Tactics

(100:13–111:02)
Main Points:

• Ambrook’s Growth:
  • 8,000+ customers (up from 2,500 in under a year); expansion from agriculture to truckers, contractors, property managers, and nonprofits.
• Product Position & Unique Approach:
  • Positioned for the “messy middle” of businesses too complex for QuickBooks, too lean for NetSuite/Sage.
  • 50% of customers moving off pen-and-paper; plenty run with “finance teams of zero.”
• AI Adoption & Attitudes:
  • Customers are open but skeptical—winning trust requires evidence of practical value, not just hype.
  • “We’re bringing AI CFOs to folks who might actually be their first business software.” — Mackenzie (102:44)
  • AI empowers faster adaptation to new verticals, customizing context without heavy engineering lift.
• Compound Startup Lessons & Platform Play:
  • Inspired by Rippling’s approach—Ambrook is “vertical in go-to-market,” flexible in product.
  • Opened up APIs to let customers and partners build on top (e.g., hunting bookings for Texas ranchers).
• Go-to-Market Playbook:
  • Facebook brand awareness → case studies → partnerships with trade associations → regional podcast appearances → word of mouth and local density.
  • “In the counties where we have more than 1–2% market penetration, our CAC is half...” — Mackenzie (109:18)
• Company Timeline:
  • Founded in 2020; spent two years in lean R&D, launched to market in 2024, now scaling rapidly.

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8. Quick Hits: RL Environments, Super Yacht Drama, and More

(23:41–33:28, 97:52–100:02)

• Startup Billionaire vs. Yacht Broker: Revolut CEO accused of dodging $20M broker fee on $400M superyacht (humorous speculation, pontoon boat as running joke).
• RL Environment Startup Mechanized: Rumored $1.5B Google acquisition, indicating value in top-tier simulation/synthetic data for AI research.
• Superintelligence Model Release: Ilya Sutskever’s Safe Superintelligence rumored to have a model debuting soon—potential industry shakeup.
• Metamodels & Distillation: ByteDance's reported ban on US model distillation for regulatory reasons; Meta’s “Muse Code” release; Microsoft standardizing on GPT-5.6-SOL.

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9. Notable Quotes & Memorable Moments

• "Jeff Dean is the Chuck Norris of computer engineering." — John (00:39)
• "If you're high enough up there, you can pretty much be a terrorist and hold orgs hostage..." — Susan Zhang, read by Jordy (10:50)
• “I actually think now allowing anyone with some ambition to take the Shopify catalog and create their own interesting ideas...will happen in the next 10 days." — Harley Finkelstein (63:36)
• “If it needs to be safe, secure and certified, that's really our value proposition.” — John J. Gimatteo (70:02)
• “All of the financial system is going to be moving to being run by software on the Internet... programmable money all on open infrastructure.” — Jeremy Allaire (82:31)
• “We’re bringing AI CFOs to folks who might actually be their first business software.” — Mackenzie Burnett (102:44)
• Infinite monkeys/LLMs crossover: “Is it possible that our modern AI systems are monkeys just clacking a bunch of keys and this is just an AI bottleneck?” — Jordy (37:45)
• “Agentic commerce is merit based. It is not based on who is supplying the most amount of ad dollars.” — Harley Finkelstein (50:46)

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Timestamps for Important Segments

• 00:02 – Google DeepMind reorg & Jeff Dean departure
• 10:48 – Susan Zhang’s DeepMind subtweet
• 20:59 – Transition: Figma AI agents & CarPlay for pontoon boats
• 23:41 – Startup super yacht lawsuit humor
• 33:58 – Monkey prices & infinite monkey theory banter
• 38:29 – Lidar, Amazon ancient civilization
• 45:27 – Shopify’s Harley Finkelstein: commerce, AI, and the agentic future
• 64:47 – BlackBerry’s John Gimatteo: from smartphones to embedded safety software
• 80:01 – Circle’s Jeremy Allaire: stablecoins, AI agent payments, and financial infrastructure
• 100:13 – Ambrook’s Mackenzie Burnett: expanding deskless AI solutions
• 111:56 – ByteDance’s reported ban on model distillation

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Overall Tone:
Conversational, with rapid, insightful analysis, technical humor, and candid interviews. Hosts maintain their signature Silicon Valley optimism, skepticism, and willingness to probe under the hood of tech’s biggest stories—and scandals.

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For future episodes, visit tvpn.com. 5 stars on Apple Podcasts and Spotify!

Transcript

[Jordy]

You're watching the TVPN.

[John]

Today's Wednesday, August 5, 2026. We are live from the TVPN Ultradome. The temple of technology, the fortress of finance, the capital of capital. Let me tell you about ramp.com, time is money save. Both easy to use. Corporate cards, bill pay, accounting and a whole lot more all in one place. What just Happened at Google DeepMind? Crazy, crazy morning shakeup. A reorg. Stepping down, stepping up, stepping left, stepping right. There's a lot of different terms. We'll break it down, we'll explain the organization before now, what it looks like going forward, what this means, where this goes. So this morning, Demis Hassabis, the legendary AI researcher, the founder of DeepMind, a true scientist. A true scientist. The subject of Sebastian Malabai's book, the Infinity Machine, the infinite machine. He announced that he's stepping down as CEO of Google DeepMind. He's also stepping up into the role of Google DeepMind chairman and he will also be Alphabet's chief scientist. So is it a promotion? Is demotion? Is he quitting? Is he getting fired? Who knows? But the most important thing is that he's still there at Alphabet. He has a different role and that's what's important. What is the nature of this new role? Google CEO Sundar Pichai also announced that Google DeepMind chief scientist Jeff Dean will be leaving the company after a 27 year run to start along with Google senior fellow Sanjay Gemwat, a public benefit corporation to accelerate discoveries in machine learning, science and engineering. And if you're not familiar with Jeff Dean, he is the Chuck Norris of computer engineering and software engineering. There's a whole list of jokes around Jeff Dean jokes.

[Jordy]

Why don't you read some of them, John?

[John]

What are my favorite Jeff Dean jokes? There's a whole bunch. Any opportunity to repost the Jeff Dean Informatica link. Compilers don't warn Jeff Dean. Jeff Dean warns compilers Jeff Dean's keyboard, It only has two keys, a 1 and a 0 because he programs in binary. It's that type of thing. Unsatisfied with constant time. Jeff Dean created the world's first O1 over N algorithm so he can bend time. There's all these programmer jokes. I don't know, they're a lot of fun. He knows the last digit of PI, that type of thing. But he's been a legend. These were Jon Quora maybe 15 years ago, maybe more. People were so excited about him and for good reason. He invented tons of things.

[Jordy]

Jeff Dean doesn't call APIs APIs call

[John]

him exactly that type of thing. Very fun. So he's the lore around. Jeff Dean has been substantial throughout his entire career. He has been very key to so many different Google projects. Integral in MapReduce and actually being able to scale Google systems.

[Jordy]

Does this make any sense? Chuck Norris counted to infinity twice. Jeff Dean did it in parallel.

[John]

Ah, okay, yeah, that's kind of funny. It is a programmer joke, but I don't know. But yeah, it's just funny that he was able to have this level of aura at Google as like a non founder, just a great scientist. And it was so long ago, before there were, before there was so much attention on like talent below the founding team and below the investing team or whatever, you know.

[Jordy]

Truly a living legend. Yeah, Jersey will be going. Google Jersey will be going in the rafters.

[John]

Yes, sure.

[Jordy]

He's not done.

[John]

He's not done. And he's starting a new company which is very exciting because there's a lot of opportunity in machine learning, science and engineering obviously. So Google DeepMind CTO and Google's Chief AI Architecture Architect, Corey Cavoulu. I can't pronounce that, I'm sorry. Is being promoted to SVP and will lead DeepMind. So Cora is now running DeepMind. But interestingly, there's no new CEO of DeepMind. Which always seemed to be an odd decision because DeepMind was not its own reporting unit. Like when the, when quarterly earnings happen, you, you get YouTube numbers, you get Google Cloud numbers. And so having a CEO of those divisions made a lot of sense of those organizations. But DeepMind was always a unit that sort of cut across everything because the work that DeepMind does on Gemini and the models made a lot of sense to vend into YouTube. And now there's a little Gemini button when you're on YouTube and you can just go to a one hour long podcast and say when did they talk about this? And it'll just answer you. And so that was like a feature that was vended into that obviously goes into core Google search. Gemini models help with ads, they help with the actual Gemini products. Like they get vended everywhere. There's a Gemini button in Chrome, there's also a Gemini button in Google Docs. There's also a Gemini button in Gmail. And so it was never like its own, even though it was its own unit. Like the value that it created at Google was very cross organizational as opposed to, you know, the YouTube team has a CEO and they have revenues and they have ads and they have a product and yes, it's integrated into the other things, but it very much is a standalone organization, reports its own financials and has a CEO. So no CEO for DeepMind. At least in the short term, we'll see where it goes on X. Demis says the move will will quote, allow him to focus on long term strategy and accelerating scientific breakthroughs. He's done a lot of that already, including leaning into his work at Isomorphic to help cure disease. He fleshed this out more on Google's blog. He said, I've decided that now is the right time for me to hand over my day to day operational responsibilities at GDM so that I have the time and space to focus on the big picture and help influence what is to come to the best of my ability in my new role. I will continue to work closely with Sundar on the strategic and global AGI matters and to advise Corey, Josh and the GDM leads from our awesome new London platform 37 offices. As part of this transition, I will also be leaning into my role at Isomorphic where we are making extremely rapid and promising progress to accelerate our mission there even faster. As you have heard me say many times, I've always believed the number one application of AI should be to improve human health. That is a great message. Very different from the SpaceX S1. The number one application of AI is

[Jordy]

the power of the entire galaxy.

[John]

I mean there's that, but also just in the actual application it's like enterprise workflows, which is.

[Tyler]

Yeah.

[Jordy]

So the, at least. And so some type of shape, some type of shakeup has been expected for a long time. Google, the DeepMind organization, has, you know, made some real contributions to the space but has been lagging. It's been a point of embarrassment for, I would say for Google for, I would say a year plus. They've always felt behind even though they created so much of the fundamental research that is, you know, gone into this entire chapter of the, you know, and

[John]

certainly not behind on video. The video stuff's really good.

[Jordy]

Yeah, sure, three, but, but then you

[John]

get kind of tied up because the Chinese models are like actually we will do Mickey Mouse.

[Jordy]

Yeah. But here's the thing. At no point has Google been breaking out their true AI revenue in a way that gets shareholders excited.

[Mackenzie Burnett]

Yeah.

[Jordy]

And yeah, that's a good point. What would. Yeah, and there's just been so many, so many question marks. There was a moment, I mean over a year ago felt like Google had some real momentum and, but, but that momentum was very much lost and so there's this Question of, you know, when Gnome left, which was about a month ago, that felt shocked. That was like more shocking in some ways than even this. This feels like expected. And then to leave what, what feels like a hole in the organization is pretty, pretty wild. Stocks down, it was down 5% around the Open. It's, it's recovered a little bit. Just down three and a half percent. Yeah, but I mean the big thing is like they just started like Google as a company, I don't think was able to be at least sufficiently AI pilled. Right. They started selling compute. A lot of researchers, I'm sure we're frustrated with that. And that could have led to some of the historical.

[John]

Tyler over there thinks Nvidia shouldn't sell the chips if they're really AGI failed. The much more extreme version of Google should keep the TPUs for themselves is Nvidia should keep the GPUs for themselves. And yeah, I mean that was something that was discussed as. Okay, if you believe you're in the foothills of the singularity, you will want to scale your compute. If you're seeing traction in the products that you're making, you want to be GPU rich, you don't want to be selling TPUs to other companies. And so that's gotta be. There's gotta be some tension. But Google's a big organization. There's multiple organizations within Google and they all have different KPIs. So one team might say, yeah, my mandate is to sell as many of these as possible externally. Other people might say, my. My job is to keep as many of these internally. And there's a lot of debates there, so we'll see.

[Jordy]

Yeah, and obviously Google has made a massive bet on Anthropic and is becoming their largest financial backer, especially through some new reporting on some of the lease guarantees that they're doing. But anyway, still so surprising. Google, obviously one of the greatest companies of all time, has every possible advantage in this race and yet has just consistently struggled. Susan Zhang, who is currently on leave from DeepMind, posted a little somewhat of a fable backdrop. Kings all asleep slash on vacation while minions slave away. August 2024 first big fail. Fast forward. January 2025. Only competent VP bails after one terrorist lead demanding an even bigger slice of pie breaks the Camel's back. Summer 2025 a year ago. Second big fail. And king of terrorists climbs the ranks above the slumbering execs.

[John]

This is a Summer 2020 tweet.

[Jordy]

Summer 2026. Slumbering execs and terrorists who Only show up for successful announcements, move on, leaving just the king of terrorists behind. Lessons. If you're high enough up there, you can pretty much be a terrorist and hold orgs hostage while continuing to ask for more and more and more until there's absolutely no more aura or gold left to plunder and then just move on to greener pastures to do it all over again. And we'll leave it up to you.

[John]

This is a crazy, crazy post.

[Jordy]

Try to figure out who's who in this story. I don't. Doesn't strike me that Susan will be headed back to the company after this post. She says, I've been on leave since January. Got pretty burned out by certain people who just say yes to everything to avoid ever making a hard call and leave it all to the hungry minions to backstab each other until success finds a cursed hole to crawl out.

[John]

I mean, to be fair, I was looking at Tyler's alt account, and he talks about us like this all the time. He's always. He refers to you as the slumbering exact in me as the terrorist. I mean, I believe in free speech. I defend your right to say these things, Tyler. I am offended. But, you know, it's a wild, wild thing.

[Jordy]

One of the crazier subtweets from a big tech.

[John]

Yeah, but I don't know. I was never sure that she worked there. It felt like it was maybe like an alt account and it was just like an anon. But it does seem like. I mean, she's saying right here, I've been on leave from this organization, so I don't know. And somebody calls her the homer of our times. Well, it's certainly well written, certainly entertaining. Another interesting wrinkle here is if you look at what Demis was talking about writing about just a few weeks ago, it wasn't as much focused on the isometric scientific advancements. I know he's super deep in that, and that's what he's. He said he's been focusing on, and I love that message. He says it's time for AI to prove its unequivocal value in the world. And what better way to demonstrate that than to help finally cure diseases like cancer? 100% agree. 100% agree that if you get a new cure for cancer, you save someone's life and they can go and say, yes, I took the new cancer cure and I was cured. AI is doing its job. A lot of people will be very happy about that. Perfect. But that's not what Demis was writing about. A Couple of weeks ago. The last substantial piece that Demis put out was called the Framework for Frontier AI and the Dawning of New Age in which he argues for a frontier AI standards body that evaluates frontier models before they're released for risks associated with superintelligence. It's at the very least not crazy to assume that Demis's new role at Alphabet is maybe related to what he's advocating for in this essay. There's been a lot of back and forth in Washington about the interpretation of that essay and a lot of AI researchers have stepped up and said like, yeah, we basically agree with this, this framework seems pretty good. It includes open source models in there.

[Mackenzie Burnett]

Yeah.

[Jordy]

To me, Demis could be an amazing candidate as somebody to lead a new regulatory body.

[John]

Lead America as the president. You think he's running?

[Jordy]

Not quite, but I think we gotta

[John]

get a researcher in there at this point. Be great.

[Jordy]

Yeah. I mean the big question now is,

[John]

are you voting Dean?

[Tyler]

I'd vote for Jeff Dean.

[Jordy]

Yeah.

[John]

You know what I'm talking about.

[Jordy]

No. So big question now. So Jeff Dean is out, Noam Shazir is out, Demis is out. Who is going to fill that void from a leadership standpoint? How are they going to be, how are they going to be able to recruit the best researchers in the world? That's a big question mark. And so it does feel like it sounds like Google's investing in Discovery Loop, Jeff Dean's new company. Very excited to see what they do. But I wouldn't be surprised at to see Google just shift into more of an Nvidia style role as like a capital partner to a number of other labs as they continue to fall.

[John]

It's maybe more of like an Amazon and Microsoft role where you have a great business, you're also great at building infrastructure. You also have a semiconductor team and a chip team and you can play up and down the stack. But maybe, maybe you're not as focused on this like full stack, straight shot thing and you're partnering with other labs on different pieces of the puzzle. It'll be interesting to see where everything goes. Discovery Loop the mission over at Jeff Dean's new company, our mission is straightforward. We are building AI solutions that can automatically solve important problems in machine learning, science and engineering. By advancing the pace at which we conduct engineering and scientific discovery, we we can bring the benefits of science and technology to the world much faster. Ultimately, our goal is to build AI systems that act as deeply positive, empowering force for humanity, delivering technology solutions that improve people's Lives on a global scale. Good mission, fully support it. Excited to see what they launch. Also fun handle discovery loop. You can follow them on X at Disco Loop. AI Disco loop.

[Jordy]

I like it.

[John]

I like disc. You know, you don't think about disco and discovery having the same root. When I think disco, I think, you know, 70s disco dancing.

[Jordy]

I think panicking.

[John]

Panicking.

[Jordy]

Panic at the disco.

[John]

Yes, yes, yes, yes. For sure.

[Jordy]

Panic. Anyway, Pannequins at the disco.

[Tyler]

Disco is short informed of discotech, a French term that originally meant a library of phonograph records. So that's just etymologically not that related

[John]

to not that related.

[Tyler]

Yeah, maybe if you go far back.

[John]

Interesting. Okay, well, let me tell you about console. Console builds AI agents that automate 70% of it. HR and finance support, giving employees instant resolution for access requests and password resets.

[Jordy]

10 o' Bruss says Demos is ousted as DeepMind CEO and Jeff Dean and Sanjay are leaving Google to start a Neolab. They're all being very careful to frame these as positive shifts, but there's no way in heck Demis would have accepted this willingly. And there's no way Sundar happily accepted Jeff doing this as a totally independent new public benefit corporation rather than a bet under Alphabet. Tough to see an interpretation other than Jeff losing confidence and working on AGI under Google. Very bad.

[John]

We need a Sebastian Malabi sequel. We need a sequel over all. I would love for him to write a sequel to just and even zoom out and look at the AGI wars generally like he did in the power law about the early venture capital firms and how they all formed and battled each other. That would be great.

[Jordy]

Anyway, Rohan Anil over at Core Automation says pour one out for the big gift. It's so over. We did have a funny, brutal, funny moment with Google AI overviews. Yes. A couple days ago where it said that one of our friends was married to another of our friend's wife.

[John]

Yes.

[Jordy]

And it was quite confident in that.

[John]

It was.

[Jordy]

And I have no idea how. How it even thought of that.

[John]

Yeah, I think it was because they did a podcast together or something like that. Like they were linked in a blog post together or something like that.

[Jordy]

Doing a podcast together.

[John]

She wrote about him or something. Or wrote a profile and it just kind of put the names together. Very odd. Yeah. I don't know. Yeah, you have to wonder what it takes to get AI overviews into like a reasoning mode that can actually do the fact checking. So the hallucinations to die down because.

[Jordy]

Well, yeah, they have to figure out a Way to make that process so inexpensive because they're serving it billions and billions.

[John]

You know, that feels like more of an engineering problem. That feels like very solvable. It feels like they're on the right track there. So anyway, the excerpt from the Wall Street Journal article published this morning on Jeff Dean's departure. We wanted to build something differently than how things are built at Google right now. Google's infrastructure has very different requirements than the type of infrastructure we want to build for research. Sounds like they want a more flexible kind of infrastructure. Kind of like the infrastructure Nvidia provides. Nick Dorsey says over at Midnight Capital. Interesting. I wonder, I wonder what they will do. Of course they have to have access to whatever chips they want. They can't be completely locked in.

[Jordy]

Anyway, Nathan Lambert says major restructuring at Gemini will be studied forever as the incumbent. With all the advantages not being able to get going.

[John]

They got going. This is, this is not correct. They completely got going.

[Jordy]

They got going, but they certainly didn't build real momentum.

[John]

Yeah.

[Jordy]

And then he says PS OpenAI accomplished

[John]

their original goal spires of PS of the century.

[Jordy]

But yeah, backstory is that a lot of the initial energy around OpenAI was a concern that Google would control AGI and of fear from the various early participants around that scenario.

[John]

Yeah. Interesting. Well, yeah. New York Times has some nice photos. Mike Isaac. New York Times has really been on a run with the photo archive. They did a whole photo shoot with Leopold Aschenbrenner, sat on it, and then the hedge fund blew up and then they were able to trickle the out. It's true excellence over there.

[Jordy]

Well, let's switch over to some more exciting and positive news.

[John]

FIGMA agents meet the canvas. Your AI agents can now create and modify your FIGMA files with design system

[Jordy]

context and almost even more positive news, the moment you've all been waiting for. CarPlay is coming to Pontoon boats.

[John]

Let's go.

[Jordy]

Finally, finally, finally, finally.

[John]

Have you ever been on a pontoon boat?

[Jordy]

Yes.

[John]

Explain what, what context were you on a pontoon boat? What does a pontoon boat even look like? This is a terrible thing.

[Jordy]

It's for cruising. It's for cruising. Team, pull up a pontoon boat.

[John]

It's not, it's not like a mono hole, but it's not a catamaran.

[Jordy]

It's something between like a cigarette boat and a houseboat.

[John]

Okay, that's a really wide gap.

[Jordy]

Well, it's right in the middle. Okay, now you just kind of putz around.

[John]

Mastercraft Boat holdings today said it's adding CarPlay to its upcoming Crest and Belize pontoons. The company is working with savvy Navy to bring CarPlay and on water navigation

[Jordy]

to boaters and Mastercraft Boat Holdings Inc. Of course, a public company experiencing a God candle.

[John]

Wait, really?

[Jordy]

Up 0.72%. Up 18. 18 cents.

[John]

Okay, this is cool. This is very cool.

[Jordy]

See?

[Tyler]

Yeah.

[Jordy]

This is double decker.

[John]

Double decker. See, out in California, we don't know anything about these pontoon boats because these don't work at the beach, Right?

[Jordy]

Correct. But I was sort of correct. Somewhere in between a houseboat and.

[John]

Aren't you from the land of a thousand lakes? Right. Michigan. Isn't that the land of a thousand lakes?

[Tyler]

No, me. Minnesota.

[John]

Oh, you're from. Okay. Are you a pontoon boat guy?

[Jordy]

Pontoon boats are huge in Minnesota.

[John]

Okay. Yeah.

[John Gimatteo]

How many?

[Tyler]

They're for lakes.

[John]

They're for lakes. Basically. How many hours have you spent on pontoon boats in your life?

[Tyler]

10,000.

[John]

10,000 hours the man put in life's work on the pontoon boat. Apparently

[Jordy]

you're in the wrong job, buddy.

[John]

I think you got to become a pontoon boat.

[Jordy]

It is crazy to think of another life. Ben could have been the top pontoon boat salesman in the entire world.

[John]

This one comes with Apple CarPlay. Don't they call it boat play at this point? They got to come with something else. CarPlay. But they're doing navigation on water. Navigation like this.

[Jordy]

Okay, moving over to. Okay, we got the story of the day in technology. Yes, this is the story of the day. Okay, hit us, John. You know what I'm talking about.

[John]

Startup billionaire sued over super yacht broker fee. Everyone's talking about this. This is potentially bigger than what's going on at Google today in London, the billionaire founder of one of the world's most valuable startups recently bought a super yacht valued at an estimated $400 million.

[Jordy]

Yeah, Continue.

[John]

Replete with a glass bottomed swimming pool and a helipad. Do they make. Wait, do they make super pontoon boats? Can you get a $400 million pontoon boat? What does that do for you?

[Jordy]

Almost certainly.

[John]

Can you imagine just a 300 foot pond boat?

[Jordy]

The world will create infinite ways to make you part with your hard earned money. And I'm sure we. We could arrange almost half a billion

[John]

dollar pontoon boat team AI images. I want to see what $400 million gets me if I'm going all in on a pontoon boat. Want to really dominate Lake Michigan. Is Lake Michigan too big for a pontoon boat? No, because you said lakes. So any lake.

[Tyler]

It works Yeah, I think the pontoon boat is not for like big waves.

[John]

Big waves.

[Tyler]

It can't be like.

[John]

But there's not big waves on, on, on Lake Michigan. You can't surf or anything. I guess there's no.

[Tyler]

I don't think so.

[John]

Surf. Yeah. Anyway, so it was a $400 million super yacht. It had a glass bottomed swimming pool and a helipad. There was just one problem. According to this reporting in the Wall Street Journal, he didn't pay the broker's fee. That is according to a top luxury yacht broker who is now suing Nick Staronski, a co founder and chief executive of digital banking giant Revolut, alleging the entrepreneur went behind their back to avoid paying commission on a purchase they had worked on. Cecil Wright and Partners, a luxury yacht broker, filed the legal action in London's High Court over Staronski's acquisition of Nixie, a 335 foot vessel with four terraces. The broker alleged in a court filing that it was negotiating the purchase for Staranski when his team secretly contacted the yacht seller directly and agreed to buy the boat, avoiding roughly $20 million in standard commission. The amount the dealer now claims it is owned is owed. In January, Staranski's team allegedly told Cecil Wright to hold off. Let's see. I'm not going to flip through this. To hold off. Hold off. On contacting the vessel seller, Canadian billionaire and former hockey player Patrick David, and said they would talk again the following week, according to the filing. The filing claims that by next week, Staranski's team had already arranged to buy the boat directly from the David, bypassing the broker entirely. It was Cecil Wright that brought the yacht to Staronski's attention and introduced the Revolut co founder and the owner Matt Young says.

[Jordy]

Unbelievable. Taking food off the table of that luxury yacht broker's family.

[John]

A spokesman for the Sharonsky family office said, we are aware of the claim. It is without merit and it will be defined. He says he's not guilty. Nixie features a private wellness spa, indoor and outdoor cinemas, two movie theaters. Now we're talking. As well as a Japanese Teppanyaki grill, according to Boat International.

[Jordy]

Pull up this picture that Tyler just shared. I think this is what Nixie looks like.

[John]

Yeah, let's see it. When chartered, is equipped with a variety of water toys, including a luxury seabob water sled and inflatable blob launchers. Is this the pontoon boat? The luxury pontoon boat.

[Jordy]

Sorry, that's the $400 million pontoon boat. That Tyler just generated.

[John]

It's pretty good. I like it.

[Tyler]

I like it.

[John]

That just looks like a normal yacht. That doesn't actually look that crazy to me. I don't know. Staransky is one of Europe's highest profile startup founders. Founded in 2015, Revolut is now the region's most valuable startup with a recent share value share sale valuing the digital bank at $115 billion.

[John Gimatteo]

Wow.

[John]

Revolut, what a tear. Originally built around low fee foreign currency transactions, Revolut is widely used by international travelers and migrants sending remittances home. The company gained a full UK banking license in March after a lengthy battle. Wow. It took them over a decade to get a banking license. That is crazy. But they did it after a lengthy battle. Battle. Now they're looking to expand into the United States, having recently applied for a national banking charter. It's crazy. It's crazy that they can't go faster like Arabor got a charter so fast. And then there's been other, there's been other companies that have explored like buying a regional bank and then using that charter.

[Jordy]

It's almost certainly part of why Revolut is now such a massive company. Yeah, because they don't have infinite common competition in the way that many banks and neobanks have here in the US

[John]

earlier this year, Revolut reported record annual profits and a jump in its customer numbers. At the same time, Revolut said it remained focused on its goal of increasing its customer base to 100 million users by mid-2027 from more than 70 million currently. Well, good luck in the luxury yacht battle. Hopefully everyone gets what they're owed now. Everyone is compensated fairly. Hate to see people fighting over that. Let me tell you about Railway. Railway is the all in one intelligent cloud provider. Use your favorite agents to deploy web apps, servers, databases and more, while Railway automatically takes care of scaling, monitoring and security. AI's great reverse bank run. In today's newsletter, Joe Wiesenthal wrote about Leopold's Basilisk and what makes this particular mania feel distinct. People are betting on left tail outcomes without sacrificing the right tail of financial opportunities. Doomers are getting fabulously wealthy. Let's see what he's saying. Here's the deal. Historically, if you want to cut off your left tail, you also have to cut off your right tail. Or to put it more specifically, if you are up big on a stock position and you want to hedge your gains by buying puts, you can do that. But if you want to maintain your puts over time, you spend a lot of money and erase any upside gains that you might otherwise be making. Or you can. Or to put it even more generally, suppose you're afraid of the outbreak of war. Well, you can move to a rural farm and grow your own food, but then you miss out on the economic opportunities afforded by living in the city. People make these kinds of trade offs all the time, depending on what's worrying them. Pin that thought for just a second. One of the big questions with AI is whether it's just another technology or whether it somehow will be different this time. It's purchasable intelligence, kind of like purchasable electricity. Or is it something more like a sci fi novel where humans get replaced or eliminated in some way as businesses? The big American companies selling AI mostly operating as if AI is just another technology to be developed and solved. But we know that there's deep anxiety within the companies themselves that AI could play out in the way sci fi novels have expected for decades, and this sometimes is reflected in their governance structures. Here's one stylized fact though, that might argue for the it's different camp. If you are one of those people who's been reading AI philosophers and message boards for the last decade, familiar with paperclip maximizers since long before ChatGPT came out, you might have deep existential fears about something bad happening right around the corner. You might also have ended up very, very rich. With AI, there has been no trade off. The doomers who were early on accumulated emulating GPUs, or better yet, shares in GPU companies have done extremely well. The put option on humanity has become the call option on the technology. You could bet on the left tail outcome, not sacrifice anything financially. We've maybe had some shades of this before. For a while, Bitcoin was or had characterized as an end of the world hedge, a form of money for when the nation state collapsed and people made a lot of money on that bet. But a trader wasn't driven by by the fear that bitcoin was a world destroyer or take gold. Betting on gold at certain times protects you against hyperinflation. But the fear that came with the bet did not entail gold being the catalyst for doom. Something else would be the catalyst, but you'd be protected is different. The long feared catalyst for doom itself has presented an unbelievably profitable trade, at least so far. What's interesting about this is that he's sort of he's saying like the doomers got rich. There are plenty of AI doomers who did not join AI labs, did not participate financially, worked in nonprofits, just wrote books, worked on research, did not ever join anything that had economic upside. But I take his point that in general, if you were early to this, oh, wow, like, things are going to get weird, you probably were earlier on the train, and a lot of those people that were talking about, about AI and doom scenarios did wind up working at labs that did very well. So it's a good point. But there are some people that don't fall in this category. Long before we had the transformer architecture of GPT, people have been characterized theorizing about the risks of AI doom. One popular thought experiment is Rocco's Basilisk, a 2010 thought experiment. Wow. When was the last time we got a new thought experiment? I didn't know they were dropping new ones. And 2010, that seems kind of recent. Maybe there's like, I don't know, someone should come up with a new thought experiment. What's the most recent thought experiment that's really taken hold and been thought provoking?

[Jordy]

Golden retriever mode.

[John]

That's not a thought experiment. That's an axiom. That's a. That's a lifestyle. A thought experiment is almost like a paradox, something you can wrestle with. We got to come up with some new.

[Jordy]

I've been wrestling with golden retriever retriever mode.

[John]

You think it's a thought experiment?

[Jordy]

I think you can make it one.

[Mackenzie Burnett]

I don't.

[John]

I don't think it falls in the bucket of thought experiment. What do you think, Tyler? No. What are you guys laughing at? Are you doing more. More pontoon boats?

[Jordy]

Crazy text.

[Tyler]

I'm trying to find the most recently created.

[John]

Okay, Jackson, you are correct.

[Tyler]

Yes.

[John]

That is the most recent thought experiment. Good stuff. Anyway, let me tell you about CrowdStrike. Your business, AI their business, securing it. CrowdStrike secures AI and stops breaches. That's very funny. Okay, wait. Quick. We gotta switch gears because the price of lab monkeys in China is soaring as demand for preclinical testing outpaces supply. The price of lab monkeys in China is soaring as demand for preclinical testing outpaces supply. Do you think it's time to ape in?

[Jordy]

Do you think it's time to ape strong together?

[John]

Yeah. Yeah. Go long. The monkey trade. So this is the actual news. We got monkeys up here. There we go.

[Jordy]

The first picture was crazy.

[John]

Yep. But it is happening, and it is interesting because it tells you a lot about what's going on in drug testing, animal rights, obviously, and also just the. The broader economic market. So in June, a Chinese state Laboratory paid roughly $26,000 per monkey for a purchase of 40 animals, nearly double what similar animals cost a year earlier. The price has doubled in the last year of monkeys. Biotech executives say the same trend is showing up across the industry, driven by a wave of new biologic medicines and next generation therapies that require far more primate testing than existing breeding capacity can currently support. The shortage could become a bottleneck for China's rapid drug development ecosystem because many experimental medicines must still undergo studies in non human primates before regulators will allow them to advance. While regulated monkey farms have maintained relatively steady production, demand has accelerated much faster than supply. A similar imbalance emerged during the COVID 19 pandemic when vaccine developments sent prices sharply higher. But this time, the pressure reflects Chinese China's emergence as one of the leading centers for innovative drug discovery. The country now generates a third of the global pipeline of novel medicines and has become a major destination for clinical trials and licensing deals with US and European and pharmaceutical companies. So monkeys remain essential for making many preclinical studies because their biology closely resembles that of humans. We know the monkey has remarkable resemblance to our particular makeup.

[Jordy]

Yeah. But broadly, many people have said we have the minds of.

[John]

Yes, yes. So if they're working on a brain, typically they would test on a golden retriever, but yes. So this makes them one of the best available models for evaluating a drug's safety, how it moves through the body, its effects on different organs, and the potential for serious toxic side effects before human trials begin. While a shortage may slow some research programs, it's also a sign of an unprecedented surge in investment and innovation aimed at developing new, potentially life saving treatments.

[Jordy]

Tom in the X chat. How long would it take in infinite monkeys to make a one monkey billion dollar? Yeah, wait, that is an important question.

[John]

That's a good thought experiment.

[Jordy]

How long would it take infinite monkeys to make a one monkey billion dollar company?

[John]

There is a.

[Jordy]

That's a new paradox.

[John]

So there is a thought experiment related to this. It's the infinite monkey theorem. This is a real thing. It states that a monkey pressing key is at random on a typewriter for an infinite time will almost surely type any given text deeply relevant to LLMs. Are there any.

[Jordy]

Okay, get the tinfoil hat.

[John]

What do you think's going on?

[Jordy]

Is it possible that our modern AI systems are monkeys just clacking a bunch of keys and this is just an AI bottleneck?

[John]

Yeah. You. You think that when you go to ChatGPT, it's secretly a monkey on the other side.

[Jordy]

Yeah, yeah.

[John]

That. It's not a computer.

[Jordy]

Yeah, yeah.

[John]

No one really goes in the data centers. Could just be a bunch of monkeys on computers.

[Mackenzie Burnett]

You don't know.

[Jordy]

A bunch of monkeys and bananas.

[John]

You don't know. Okay. Well, there's also news somewhat related. Are there monkeys in the Amazon rainforest? Almost certainly, right? Almost certainly.

[Jordy]

Jack in the YouTube chat says, how long until monkey seed? What about monkey do?

[Tyler]

There's over 50 to 100 species of monkeys.

[John]

Monkeys in the Amazon rainforest. Okay. Well. A new lidar survey of the Amazon rainforest has uncovered evidence of a previously unknown civilization that may have supported as many as 3 million people challenging decades of assumptions about the region's ancient history. So, I mean, we talked to a friend of the show who was doing this, scanning the rainforest with light lidar, putting new sensor stacks on helicopters, flying them around on planes. But there's new evidence here. So. Using laser scanning technology capable of penetrating the dense forest canopy, researchers mapped more than 4,500 square kilometers of Brazil's Acre state. After flying over 4,400 kilometers of rainforest. The survey, which was published in Nature, identified 396 previously unknown geoglyphs, massive geometric earthworks made from deep ditches and raised embankments. The discoveries have provided the clearest picture yet of the Aquari civilization, which is believed to have emerged around 500 BCE and flourished until roughly 8. Rather than serving as permanent settlements, the earthworks appear to have functioned as ceremonial and civic centers where people gathered for rituals, political meetings and other communal events while living in nearby multifamily longhouses and cultivated crops such as corn and squash. Based on the number of earthworks and the labor required to build and maintain them, the researchers estimate that the civilization's population peaked somewhere between 1.25 million and 3 million people. The findings add a growing body of evidence that the ancient Amazon was home to a large interconnected society with engineered landscapes, not just small isolated villages, as many archaeologists once believed. Even more remarkably, the surveyed area alone contains roughly as many earthworks as earlier estimates suggest existed across the entire Amazon basin. If future lidar surveys uncover similar densities elsewhere, scientists may have to dramatically revise estimates of how many people once lived in the rainforest. Archaeologists still do not know why the civilization disappeared, though. The abandonment of these ceremonial centers between 850 and 950 CE coincides with the decline of several other major societies in the Americas, including the Maya. Very interesting. I wonder where else people can scan with lidar, find interesting things. Gotta go to Antarctica or something. I don't know. Well, in other news, Gorn is retiring from writing to start a company. Guern is the anonymous online writer. Is it gorn.org or gorn.net gorn.net Fantastic blog. He's done, I believe, only one podcast in history with Dwarkesh where he was anonymous. They used like a 3D rendered version of him, a voice changer to keep him anonymous. This is the website of Gorn Bronwyn. He writes about AI psychology, statistics. He also is, I mean he's written about self experimentation, bitcoin, all sorts of different stuff. He wrote an amazing piece about nicotine and all the deep dive there is very fascinating, very formative. When I was starting my nicotine company, it was very interesting. But he's starting a new company, so let's dig into what he wrote. Let's see. Can I pull this up? Where is it? I lost it. Gorn, Gorn, Gorn, Gorn. He has a locked account, so you got to go. Request to follow and then timeline app, open it back up. Where is it? Let me tell you about public.com, investing for those that take it seriously. Stocks, options, bonds, crypto, treasuries and more with great customer service.

[Mackenzie Burnett]

Guern.

[John]

Okay. He's retiring from writing to start a company. The company's first product for writing. His goal is to design is to. His design goal is a 100x increase increase in productivity. What would it take for a GA to make me 100, 100x more productive as a writer or thinker? Why 100x specifically? He says because 2 aiming at OOMs 2 aiming at OOMs is enough to hope to keep up for a while. And this goal will shatter ineffective band aid style short term design proposals. But it doesn't require solving the image AI alignment problem or value extrapolation. We do not need to be able to oversee millions of super intelligent AIs working autonomously for subjective millennia. Which is good because a GA can probably not do that. What would that look like for me, roughly, I think it would look like a GA enabling me to produce one to three worthwhile writings a day which are 100% written by it without loss of quality. Very interesting.

[Jordy]

I've heard enough.

[John]

100 million give them a billion dollars.

[Jamie Lair]

Yeah.

[John]

No, I agree. It is interesting that we've gone back and forth on is writing verifiable? I think it's a little less verifiable, but with feedback and different algorithms you can get there, but it just feels like the progress in mathematics is accelerating faster than the progress in Writing.

[Jordy]

Yes.

[Tyler]

And also, I mean, in this scenario, it's like, maybe it's easier to train a model to write one specific person to write good. Generally, that's much more amorphous. What does it mean to write well versus like, oh, this is in the style of a particular person. This is how they would think.

[John]

It also feels like there needs to be a sort of like a whole agent harness or workflow. Because writing is not just the last step of instantiating the rules. It's all the research that goes into it, all the different references, all the different links and things, and the way he will put together arguments, the way he structures these things. All of that is part of the writing process, even just narrowing down. Is this an essay or is this a shorter post? Longer post. All of these different decisions, they can probably be built into a system, but it will take take time. So that's what he's working on anyway. Let me tell you about Shopify. Shopify is the commerce platform that grows with your business, lets you sell in seconds online, in store, on mobile, on social and marketplaces, and now with AI agents. And we have the perfect guest to talk about Shopify because we have Harley Finkelstein, the president of Shopify, here with us in the TV and ultradome. Welcome back to the show, Harley. Congratulations. What a quarter. Insane stock chart. Take us through it. What's going on? Shopify it is.

[Harley Finkelstein]

Jordy. John, great to be back here.

[John]

Great to see you.

[Harley Finkelstein]

I don't know if. I don't know if the. If the ad roll and me coming

[John]

on together was completely coincidence. Completely coincidence.

[Harley Finkelstein]

Brilliant. Well, before the go, this was a monster quarter, no doubt. GMV was 116 billion, which is more than like the GDP of half the countries on the planet. Revenue was 2.6 billion, gross profit was 1.7 billion, and free cash flow was just over $650 million. Most importantly, I think is that, I mean, this obviously Shopify is at a huge scale and we delivered more than 30% across, across the board this quarter. And I think it's like our fifth straight quarter of 30% or more growth in GMV. So Shopify is doing well. And more importantly, importantly, the stores on Shopify, the merchants on Shopify are doing incredibly well.

[Jordy]

And really, really people talk about AI victims and in this situation, I think AI is a victim of Shopify.

[Harley Finkelstein]

I mean, you know, we can get into that. I actually think one of the more interesting parts of the call and we got into a little bit of it, but just around what is happening in Agentic that I think the question I got on the Q1 call was is this real and, and is this going to continue? And I tried to answer that question clearly, which is, yeah, it is early and yes, the volume is small in agentic commerce relative to $116 billion. But the trend is real and the growth is real. And funny enough, surprisingly enough, I should say the merchants that seem to be benefiting most from agenta commerce are not the big box stores. It is the long tail of these specialized independent businesses. And just on, on, on a gentic alone, traffic was up 3x. Like AI driven traffic to Shopify stores was up 3x, orders were up 3x. So not just traffic, but the actual orders themselves. And probably the most interesting is like conversion from our catalog. Shopify catalog was 2x more than sort of general AI scraping. So one, it is real, two it continues to grow. And three, it is disproportionately affecting the these smaller merchants. So you know, consumers are searching for like a standing desk for a small apartment or car seats that fit three across the backbench of a sedan. And I think that is a structural advantage for small businesses, which happens to be a big part of our merchant base.

[Jordy]

Okay, so yesterday we had the most feared lawyer in the world on our show, John Quinn. He was talking about a sort of current lawsuit between Amazon and Perplexity. Amazon sued Perplexity because Perplexity's bot was going on to Amazon.com finding listings for users, which I think is something that a lot of people, a lot of people want. But Amazon is not excited about that because they have a big ads business and if bots are crawling all over, they can't really serve or they don't have a way to serve ads to bots in an effective way. It feels yesterday I think there was a some type of action by the judge. I forget the technical term for it, but the judges, I don't think the case is fully decided yet. But the judge is effectively saying like an agent acting on the user's behalf to do something on a website is wildly different than just general. Like basically the, the way that we would historically view bots where like a company could say like we don't want your bots on our website, but we're entering into this new paradigm. It does feel like Shopify is in a really great position here because you guys aren't trying to monetize eyeballs in the same way. And you're not trying to monetize that to demand. You're just trying to get merchants in the position to sell a lot more products. And so how do you see this sort of struggle evolving on a more global level between consumers which want to use agents to buy products all over the Internet and these sort of big platforms and legacy shopping platforms that want to, you know, control attention on their websites?

[Harley Finkelstein]

Look, I think I did a search for myself in June. Bailey. We had a 10 year old, our 10 year old daughter. We want to get her a screenless phone to use. And historically I would have gone to a search engine and would have typed in screenless phone and I probably would have seen something like best Buy pop up and they'd have like eight different options from some big, big, big companies, electronics companies. Instead, just using chat on my own, I typed in looking for a screenshot for Bailey because it had so much context, because it knows me so well, because of all the conversation we've had over the last two and a half years. It actually pointed me right to the Tin can phone.

[John Gimatteo]

Yeah.

[Harley Finkelstein]

Tin can phone is a Shopify merchant. It took me right to the store.

[John]

I have like five of them. They're amazing.

[Harley Finkelstein]

They're amazing.

[John]

Amazing.

[Harley Finkelstein]

I never would have found that. I never would have found that.

[Jordy]

And this is a. That is happening with the string attached to it.

[John]

That's the metaphor.

[Harley Finkelstein]

That's the metaphor. But it's basically, it's wi fi enabled screen. This phone. It's really cool because I don't want my kids on screens. It's amazing. It works incredibly well. That is because agentic commerce is merit based. It is not based on who is supplying the most amount of ad dollars.

[John Gimatteo]

Sure.

[Harley Finkelstein]

And I think it's still like, it's still, it's really, it is a much better shopping experience. And I still think it could get better. In fact, I sent you gu some, some graphics here. Can you, can you pull up, did you have those, can you pull up the first one which is just the dress?

[John]

Yeah.

[Harley Finkelstein]

Okay, so I mentioned earlier. Just keep this on for a second. I mentioned earlier that right now if you look at the conversion from our catalog versus general AI search of scraping, our catalog converts 2x. This is what a scraping might, might actually show. Just simply the dress. Go to the next slide. Okay, so this is what we're actually building. This is these taste driven attributes, whether these articles, these products, you know, is it formal enough for a wedding? Is the fabric breathable? What's the wrinkle tendency if you're using it to travel? Sneakers, Are they suitable for an endurance race? This type of structured values Agents can actually read. It means that when someone's saying I want to buy a dress that's good for a summer wedding or, or a suit that needs to be formal enough or judging its formalness, this is where it is going. We announced this@.dev two weeks ago. But this is what we are building with catalog. We are building these incredibly rich product attributes that will make the shopping experience from a discovery perspective way better. And then what we're seeing is ultimately the journey compression is insane. So buyers arrive effect, you're ready to shop. AI referred to sessions land on product pages two and a half times more than simply organic search where they just go to the general page and they're perusing and they're browsing. That's not how it works with, with, with Agentic. Actually they're arriving right on the product page and they're using shop pay to check out. So the adoption like this is real and it's showing up in our numbers and both in traffic and orders. And I think Agentic is, is only going to get bigger from here. And I love the fact that these small niche companies like the Tin Can Phone seem to be the ones benefiting more than others. In fact, if you actually just compare 75% of all AI attributed purchases in Q2 on Shopify or from outside our top 100 categories. So it is not your I want yoga pants. It is, I want, I don't know, reef safe sunscreen that doesn't leave a white cast in my, you know, on my black leather, whatever it is. Sure, it's that type of stuff. And I think that means our merchants, I think will disproportionately benefit from this

[John]

because AI is still a little slow. There's a little bit of a cost to going down the Agentic search path. I would expect, I have been expecting that we will see disproportional agentic purchases for higher ticket items, more considered purchases. So you're doing research on a car. Yeah. Go lead 5.6 pro cook on all your features and figure out everything but you're ordering just another, you know, soda. You're not going to go and down the agent like system for that, at least in the short term. Are you seeing any of that or do you expect that to be a factor?

[Harley Finkelstein]

Yes. So for sure, products that require more deliberate purchasing intent and more research benefit from it too. But I would tell you to expand your, your perspective there. It's not just, it's also products that are very much for, it's a particular product for A particular use case. It is not necessarily I want to buy a T shirt. It is I want to buy a high end T shirt with a GSM count that is more than you know, that keeps me warm. Like when I go out at night in New York City where it knows your location, it knows the weather in your location. And now it actually pulls from your entire conversation history and says you probably want a James Purse T shirt. Which is my favorite T shirt.

[Jordy]

Yeah. The other thing I've been doing, I think you maybe discount consumers willingness to wait or do things in order to save money.

[John]

Right.

[Jordy]

This is not. You don't strike me as the kind of guy that ever was doing like credit card point maximization or like chasing coupon codes around the Internet. But a lot of people are. And a lot of people like want to buy something and then they're thinking, okay, how can I get the best price on this? I saw a pair of sneakers a couple days ago that I really liked.

[John]

Yeah.

[Jordy]

I found them for sale and I just took a screenshot of the, of the product page and I said find me this sneaker in my size at the best price.

[John]

Oh, interesting.

[Jordy]

And it went and found three different

[John]

options so you might land on a Shopify.

[Jordy]

And what was interesting is it actually took me to StockX and it was like, hey, by the way, this is selling for below retail stockx so you should just get it here. And I ended up saving whatever, 50 something dollars. Right. And so that even though that was like probably took 30 seconds. Sure, sure, like 30 seconds to save 50 bucks.

[John]

Yeah.

[Harley Finkelstein]

I mean especially if you have some sort of like reminder like hey, these are the sneakers I want. They're a little too expensive for me right now. I would love you to let me know if something else comes up. And now it basically runs a query every couple of days to see whether or not it's being discounted as well. So even though that's not a deep research product, you actually are doing deep research on the pricing of it as well. But the other thing also that came out of the call today which, which I don't know if it, it necessarily got. Got picked up and it's worth sharing is. We've talked about Sidekick on the show before and I said ultimately the goal for Sidekick is that it makes merchants more effective, more efficient, helping them reach their early milestones faster or make better decisions. All the, you know, all the things that, you know, when I was selling T shirts on Shopify or you know, you were selling nicotine patch Doherty, like you Know that all that stuff, the silly ad spend we made on performance marketing that just didn't convert that ultimately the goal was to, to alleviate all that as well. And what we actually talked about today was when you actually look at the onboarding guidance when you're just setting up a store on Sidekick, on Shopify, we actually saw an 8% increase in new merchants reaching their fifth order within 15 days. That may not seem like a big deal, but on a massive base of Shopify new merchants that are constantly coming on, the fact that they're getting to their fifth sale faster is, is remarkable. And so we think not only is, is that going to get better for new merchants, but then as merchants also grow in scale, it's not going to be about setup anymore. They're going to be using Sidekick to become more like, to do more things like analytics or reporting or to find new opportunities. And therefore all the mistakes that we all made when we were building our own e commerce businesses 10 years ago simply go away. And so you'll have more people starting and more people growing faster. And as that happens, Psychic just keeps getting smarter and smarter.

[John]

Yeah. So like break that down more for someone who's actually running a Shopify store today. How close are we to the world where you show up, you have a budget, and Shopify can sort of agentically for me, take a budget and spread it across Facebook and Applovin and Google Ads and load balance everything. The stuff that you wind up hiring an agency for sometimes and then maybe they get a little clocked out. Then you hire a person and it becomes a job. And a lot of small merchants might not have that computer capacity, but there's a mate. You're picking up pennies off the floor if you're doing it properly.

[Harley Finkelstein]

Yeah, so, so I mean, so that, that is, that's already happening to some merchants some of the time. We have something called, we announced, called Autopilot, which we announced in our last edition, which effectively allows you to give us your ad budget and we will go and find the most effective uses for you.

[John]

Yep.

[Harley Finkelstein]

But in terms of like. So there's different stages of usage on Sidekick for new merchants. The first job is getting that first sale and then the next sale and those. You guys know this. The first few orders, it creates incredible momentum. It gives, it gives you confidence. You become an entrepreneur when you have your fifth sale and it's not your mom or your neighbor. It's like some stranger who found your business. As the business then grows, we've noticed obviously setup accounts go down. Now they're actually using it to do things like reporting analytics. And over time what we're doing, Sidekick is actually proposing things like bundles for example, or SEO optimizations. You've implemented product creation. Then we have something called Pulse that lives inside Sidekick, which is effectively saying this is what's happening right now on your business. And these are some proactive ideas you should consider, like useful recommendations. You can accept them and if you do, Sidekick will implement them for you. Or it could be something as simple as moving your product page around or moving the buy button, you know, the shop pay button, further up the stack a little bit. But this idea is we want, we want to deliver the best practices across hundreds of billions of dollars of GMV everywhere that goes to Shopify to anyone using the platform. And then they can decide on their own if they want it. The reason that this is possible is because it understands unlike any other AI agent, it understands a merchant's products, customers, transactions, history. And that context allows us to give this incredible grounded advice in the realm reality of a merchant's business. And it's an advantage actually that just continues to compound. As more people use Sidekick, more merchants are able to get value from it as well. And I think the path forward is Sidekick will take on more of the work, not just with ads, but also selecting a 3 PL or figuring out, doing line skipping to figure out how to have the best deal on shipping. But this is really, I mean it's not just science fiction. This is really happening where you can put, put more and more your business on autopilot.

[John]

That's great. What a great time to start a company.

[Jordy]

In two minutes I want you to talk about the year 2035 and let's assume that you have a widespread use of robotics that can make anything that you could possibly imagine spread out all over the world, that can make custom products or one off products or small batches of products. I have so many different products like in my camera roll that I just made with ChatGPT images and I would, I would love to be able to make like just 5 of them or 10 of them or make one for myself and throw up a product listing, right? It could be something like sculptural or a piece of furniture or even something in consumer packaged goods. And I personally have a theory that as, as robotics bring down the cost of making anything, that there's so many people on the planet that have ideas that would create a Shopify store and if they could make you know, 10 or 20 or 50 or 100 of products really easily. They would become, you know, basically entrepreneurs overnight. You just about reducing that friction all the way. So like 30 years ago is quite a bit harder to sell products online. It was, it was, it was possible but again it was like clunky. Now it's easy to sell products online. It's still incredibly hard to make high quality products. Especially as somebody that's a new entrepreneur that doesn't have a lot of capital. So how are you thinking about the like the year 2035, assuming you know a takeoff in robotics.

[Harley Finkelstein]

Can you guys pull up Gamers town? Gamers like the gamer, like someone who's a gamer town. T O W N Just pull that up for a second. I want to show you something. I just saw this before the call, but this I think is fascinating.

[John]

This is very cool. Is this on Shopify?

[Harley Finkelstein]

Yeah, so I got it. This is so interesting. So can you pull it up here? So okay, okay, check this out. So this is an entrepreneur who basically took our catalog API. So a billion products, right? Like Alo is in here, Vuori is in here, Mattel is in here, Cannon Goose is in here. Everything is in here. And, and they also looked at every single store that obviously this entrepreneur is a gamer and said I want to pick across a billion products the most relevant, interesting merchandise for all these games like Minecraft. And they effectively, they took the catalog API like as the access point and now these developers can effectively just build their own stores with other people's products. So I think like, and it's, it's beautifully done. You can see it's like this great constellation type of shopping experience. So the fact that even before the year 2035, where maybe robotics help us with manufacturing, I actually think now that allowing anyone with some ambition to take the Shopify catalog and create their own interesting ideas. In this case it's for gaming, but there's so many other ones as well. I think that is like that will happen not the next 10 years, up in the next like 10 days. This is the first one I found.

[John]

I'm getting a full counter strike costume for sure. This site is amazing. Thank you so much for coming on the show.

[Jordy]

Very cool.

[John]

Always, always fantastic chat.

[Jordy]

Incredible quarter.

[John]

Ben, congratulations. What a quarter.

[John Gimatteo]

Great.

[Harley Finkelstein]

Thank you guys for the best.

[John]

Goodbye. Let me tell you about MongoDB. What's the only thing faster than the AI market your business on MongoDB? Don't just build AI, own the data platform platform that powers it. Our next guest is John Gimatteo from BlackBerry. He is the CEO and we're very excited to talk to him because BlackBerry has evolved many times and the company's been on a fantastic run. Thank you so much for taking the time to come chat with us. Would you mind kicking us off with a little bit of an introduction on yourself? And I want to sort of set the table on the shape of the business now for anyone who's been living under a data center and doesn't understand the current shape of the business.

[John Gimatteo]

Hey, thanks for having me on a program, guys. It's an honor to come out and talk a little bit about BlackBerry. 42 year old iconic Canadian company success.

[John]

That's right.

[John Gimatteo]

So a lot of deep roots in technology and a lot of different transformations over, over those 42 years. You know, so many people know us from the old smartphone days and the devices, but our transformation and pivot into embedded software and we could talk a lot more about that and the things that we're powering around the world and secure communications where we provide mission critical, mission critical communication capabilities, that's really what the new BlackBerry is all about. Those two categories in terms of serving the market.

[John]

Yeah, on, on automotive software, obviously it's a very high stakes in some cases life and death scenario based on the security of that software. At the same time, the theme of 2026 has been cybersecurity with advanced AI models showing really powerful capabilities that there. What have automotive leaders been coming to you to solve? How are they thinking about solving the problem of keeping automotive software secure in the modern era?

[John Gimatteo]

Yeah, great question, especially now is there's so much more technology going into the vehicles than ever before. The need for a rock solid mission critical secure operating system. And when you think about BlackBerry and our Q and A platform, think of it really as the operating system of the car. The windows of the car, the way windows is to the PCs around the world. The QMX operating system is really the operating system that powers all things that go on in the car, particularly on safety critical types of functionalities, from digital cockpit to adas to body control. All of these different domains of technology that goes into the car and the CPUs that power them run on top of a BlackBerry operating system. So we're proud to be powering over 275 million cars around the world today and, and growing millions over the years. And we got a tremendous amount of progress all around the world in Germany, Japan, Korea, obviously here in North America. China is one of our fastest growing segments. So a lot of exciting things as more technology gets introduced to the vehicle.

[John]

How has you as a CEO been grappling with this sort of story of token maxing? You get these new models, they're incredibly powerful. You have the opportunity to deploy them across the entire workforce, rewrite every line of code if you want. At the same time, this comes with a cost. You have a serious business to run with a bottom line to manage. How have you been deploying AI internally in a way that's maintained safety and security but also doesn't balloon cost, but does drive efficiency?

[John Gimatteo]

Great, great, great question. And that's, it's something we think about every, every single day. We are. The way I would describe it, we're pretty pragmatic about AI and how we use it because like you said, the, the applications, the car failure is not an option in a vehicle.

[John]

Yeah.

[John Gimatteo]

So we've got to be really careful about how widely we deploy AI as we build and enhance our existing operating systems and new products. So you know, one of the things that's in our industry you have to meet the highest levels of certifications. And in the car industry there's a particular Service certification of ISO 26262, very high standard. You can't even think about being deployed into a vehicle unless you deploy that for an AI agent and to, to try to meet that type of standard. It's a non trivial type of exercise. So we are thoughtful about it. We deploy AI to help us maybe test our products. We deploy it to help service our customers. We deploy it in our go to market activities. But in the actual core development, the code that goes in it, we're very thoughtful and limited about because of those certifications and the importance of it.

[John]

BlackBerry has been on such a fascinating historical journey. What is the area or cultural value or discipline or source center of excellence that you think has remained the most true throughout all of that. What is the narrative arc that actually brings coherence to a company that's operated more multiple markets over multiple decades?

[John Gimatteo]

Yeah, yeah, that's. Yeah. For a 42 year old company that has evolved in so many different ways. You know what I always tell people? BlackBerry has always been about security, trust and innovation. And even though the products and services that we sell to our customers today can't be held in the palm of your hands the way they might have been with a device that security, trust and innovation of everything that we do, from the products that we deploy to the services that we provide, to the support that we provide governments around the world, 8 out of the top 10 G10 countries around the world are still deploying BlackBerry's secure communications capabilities from mission critical types of applications. So if it needs to be safe, secure and certified, that's really our value proposition. Our 2,000 plus employees and contractors around the world are big hubs in Ottawa and Waterloo, Canada is where a lot of this technology gets developed. That's the pride of what we stand for and those are the values of what we stand for in terms of security, trust and innovation.

[John]

So I imagine that although different technological solutions, different products have evolved, there's always been a really, really solid operating bar for building trust with customers. Go to market sales, actually partnering really deeply with the companies that you work with. How has that informed your M and A strategy going forward? Do you have a particular philosophy of how you can bring a new product or company into the fold successfully?

[John Gimatteo]

Yeah, yeah, that's one of the things we do now that I don't know. We did it to a degree in the past, but I think we've really doubled down on it over the last few years is we really work very closely with the ecosystem to bring a lot of this capability to the market. So for instance, our biggest partners in the automotive sector, Nvidia, Qualcomm, arm, Texas Instruments, intel, big tier one operators like Bosch, take our technology integrated into their solution and deliver it to their customer. So whether it's the chip makers, the operating system maker like U.S. tier 1 providers, or the end customer like the auto manual manufacturer, having a comprehensive ecosystem approach has really been the way that we've, we've gone about it. So when we think about M and A, we look at, you know, what, what piece of the puzzle might be missing and we kind of put it through that filter. But I got to be honest with you, it's right now with the organic growth that we're seeing, the opportunities in physical AI with robots and medical instruments, there's a lot of organic kind of Runway for us to enjoy. So from an M and A perspective, if it fills a gap, if it helps us accelerate a certain category, I think we'll absolutely think about it. But right now, you know, the Runway that we have, we have a $950 million backlog in our UNEX operating system that's going to be deployed over the next five, seven years. So these are the types of things we think about when we think about

[Jordy]

M and A. Jordy, I want you to make a guess for us. Considering how embedded BlackBerry is with, you know, automotive manufacturers and other suppliers. What at, at what point do you think that every auto manufacturer in the United States that sells let's say more than 5,000 cars will have a functioning autopilot out of the box in every single one of their vehicles. What year?

[John Gimatteo]

Interesting. You know, there's 90, 90 million cars get made a year. 75% of those cars have basic fundamental technology like, like the media type of software that operates. 25% have more advanced technology along the lines of what I talked about. So taking it the next level around an autopilot and, and you know, autonomous applications and you know, I think that's well into, you know, the, the next decade of the 2000 and 30s early innings. There's a lot more technology going on and we'll see more and more of it get deployed. But I do think it's a little bit more of a journey than an instant thing that we're going to see in the next, you know, 18 to 24 months.

[Jordy]

Yeah, yeah, no, that's what I was, my, my estimate would be 2035.

[John]

Yeah. What are you seeing on the industrial automation side? The industrial, either robotics or just industrial equipment side. I mean we've seen Caterpillar is doing really well and it just feels like America is starting to re industrialize. There's, there's reshoring. There's also the data center build out, the AI build out. There's just more construction happening. It feels like. Is that showing up in your business? Are you seeing that with your partners? What is the nature of the changing landscape of industrial autonomy?

[John Gimatteo]

Absolutely. It's the general embedded space for us which includes things like industrial automation, robotics, medical instrumentation, surgical robotic arms that go on in the operating rooms today. These are all. While we've got a great footprint and presence and growth trajectory on the automotive side, these other use cases around robotics. So for instance your AMI amr rather automated mobile robots. Things that are, these are robots that are doing pick pack and ship in big scale manufacturing. Those are applications that would need a Q and A operating system. Sure. Based on the precision and the safety levels of things required. So it's the fastest growing segment. It's our fastest growing pipeline.

[John]

Oh wow.

[John Gimatteo]

And we think it's, it's going to help us fuel that next generation of growth here at BlackBerry.

[John]

Last question and we'll let you get back to your busy day. I'm interested to know how you've processed the the story of Palantir for deployed engineering strategy. This in some ways has always existed. There's always been deep partnerships with enterprise companies where employees of one company might be embedded in another organization as they're deploying a piece of software. Palantir took it sort of to the extreme. How have you thought about deeply integrating your actual workforce and solutions engineering into the companies that you're working with?

[John Gimatteo]

Yeah, I follow the Palantir. It's obviously working for them. They're just killing it right now and it helps them, I think, you know, with their cycles and bringing more products and solutions to the market. I think for us we're probably a little bit slower to adopt something like that, if I'm honest. We're a little bit more. Again, back to some of the safety certifications. There's dozens of them all around the world that we have to comply with. We take that really seriously and as a result we try to do as much of that in house as we possibly can. We got to a point where scale was really affecting our ability to get some of these solutions out there in a timely manner. I think we'd take a look at it, but at this point in time it's a little bit more of a made in Canada approach.

[John]

I love this made in Canada. Well, thank you so much for taking the time to come chat with us. Congratulations on all the recent success. Really impressive and really appreciate the time chatting with you. Have a great day.

[John Gimatteo]

So much for having me on.

[John]

We'll talk to you soon. Have a good one. Goodbye. Let me tell you about Cisco. Critical infrastructure for the AI era unlocks seamless real time experiences and new, new value with Cisco.

[Jordy]

Up next, missed an opportunity to pitch John on rebranding back to Research in Motion. Oh yeah. Because that is one of the best names in history.

[John]

It is.

[Jordy]

And it feels even more fitting for the current business.

[John]

Maybe, maybe. But everyone knows BlackBerry.

[Jordy]

David in the chat wanted to ask, has BlackBerry thought of renaming their company it's now B2B. A totally different offering than what people. I do think. I do think the current name probably holds them back.

[John]

Really. I think, I think it accelerates them a ton because even though BlackBerry was no consumer in enterprise, it was known as a much deeper solution that you would buy and deploy across like your entire.

[Jordy]

Yeah, but, but I would say that like the next generation of enterprise buyers associate the BlackBerry name with just losing.

[John]

Oh yeah, yeah, yeah, sure, yeah. Oh well. Well, our next guest is in the waiting room already. We have Jamie Lair from Circle. He's been on the show before and he's back in the TV Vinhl Jam. How are you doing, Jeremy?

[Jamie Lair]

Great. Great to see you. Absolutely.

[John]

Thank you so much for taking the time to come chat with us. Give us the update on Circle. Give us the update on, on stablecoins broadly. I want to go into sort of the knock on effects, how the air is helping, but let's start with the state of the business.

[Jamie Lair]

Yeah, absolutely. We, we reported our Q2 earnings today. I won't go through like all the numbers, but I think, you know, one of the things I talked about at the beginning of that is like we're going through a pretty interesting moment right now and, and that's really being driven by the fact that stablecoins are now becoming part of the actual dollar financial system. So the Genius act passed, this, this new law is going into effect and really the big trend that we're seeing is that, you know, all of the traditional players in the financial system, from the big technology companies to the payment companies to financial infrastructure companies, they're all starting to build on this. And so we're really poised obviously for that moment. USDC is today like overwhelmingly the most widely used regulated digital dollar in the world. Visa reported at the end of June 70% of real world stablecoin transactions happening with USDC. We saw record numbers in terms of minting and redemption of usdc. And so it's, it's, you know, sort of the backdrop is like stablecoins are working their way into kind of everything and at the beginning of next year it's sort of officially part of the financial system. So you know, that's, that's been going on and I think the other big shift that's been happening, and we talked about this earlier as well, is that we're kind of exiting the, you know, what I like to think of as like the speculative phase of crypto and we're moving into like a more mainstream phase. And actually there's a tipping point, data point that happened last week, which is that close to 75% of the volume traded on hyper liquid was actually real world assets. Tokenized stocks, tokenized commodities, other things. And no longer people who are like, you know, kind of going leveraged betting on bitcoin. It's actually this infrastructure being used for traditional assets. And that's obviously, I think a pretty interesting moment in time as well.

[John]

Interesting. How have you been processing the moves in the traditional finance Rails world? There's this talk of a new payments network that might compete with Visa. A bunch of the banks are working on this. Are they fighting the last war? Is, is this not a threat to you? Is this irrelevant? Is, is this maybe beneficial to you?

[Jamie Lair]

Yeah, I mean like, I think our philosophy, you know, basically for the last 13 years is like all of the financial system is going to be moving to being run by software on the Internet. It's going to run on open networks, it's going to be open source infrastructure, it's going to be machines that are, that are running that. And as obviously we see this convergence with AI, it's actually machines building machines that are running the financial system on the Internet. So I think that's looking backward, I think looking forward. This is about programmable money all on open infrastructure. These new, you know, software created money. Like stablecoins itself is actually software generated money. So I think that's where, where, where the world is going and, and where the velocity is going to happen as we go forward.

[John]

How are you thinking about the, I mean software created money. The AI agents, there's been a whole bunch of different sort of concepts. We were just talking to Harley at Shopify about the like the growth in agentic shopping, but it's mostly research and then it's handed off at Shopify. And I'm wondering do you have any visibility into where the near term killer use case within a very bright broad AI world that can do everything from, you know, probably figure out how to mail you a gold bar if you try hard enough to, you know, micro transaction streaming usdc. Right. There's such a broad remit there.

[Jamie Lair]

Totally. I mean this is a huge focus for us. I know we talked about in the past, but you know, right now, you know, there's these agent payment protocols like X402 and MP machine payments protocol. Right now like over 99% of the transactions that are happening are happening with USDC are happening on blockchains. So we're leaning pretty hard into that. And lots of companies from Amazon to Cloudflare to Shopify to Stripe and others are building on this. And so that's sort of happening. But I think our, our conceptual model and I actually talked about this earlier today, we have a whole roadmap we're publishing on this is we actually think that the real opportunity is not necessarily like agents that are out doing shopping. It's actually agents as actual units of labor. And so really looking at agents as cognitive workers and looking at agents that are actually the supply side of the agentic economy, which is essentially agents that you can discover that other agents can discover that can provide and conduct work. And really that's a whole infrastructure that has to be developed and that includes things like identity and reputation and marketplaces where these competitors be discovered. We've launched a bunch of pieces of this. There's over 900 services now that are available. It's across a huge range of things on the Internet that you can now do with agents and agentic payments. And so I think, you know, from, from, from my perspective the, the agentic economy in some respects is about the transformation of cognitive work into agentic execution and then how all that gets orchestrated not just inside a firm. There's lots of people talking about agent hardware harnesses and orchestration, but it's like cross firm boundaries. If I'm building a startup and I've got two or three people and I want to employ agents to actually work on my behalf and build things, we need an infrastructure to do that. And so I think it's actually, that's the looking forward model. The looking backward model is like, yeah, there's like research and shopping. The looking forward model is there's work that's executed. It's a labor market for agents that has to be established. That's what we're excited about.

[Jordy]

What does stablecoin adoption actually look like in a large financial institution? Because these institutions are using them in some ways, but there's all these different like flows of money. And I imagine that when you're talking to CEOs or your BD team is talking to management teams or individuals at these companies, you're probably identifying different flows and saying like this is a good use case for stablecoin coins. But I imagine there's a lot of basically payment flows that have been set up and maybe running for like 20 years and there's a system that works. And so how much of adoption is net new flows that are being set up, stablecoin native versus historical basically payment processes that are getting turned over to stable.

[Jamie Lair]

Yeah, it's really interesting. I mean I think we're sort of seeing this like incremental upgrading that's happening. And you know, you see this with like pretty much every payment company and every neobank in the world now has some kind of stablecoin strategy. They're integrating it into how they can receive pay ins or make payouts. You're seeing that with you know, companies like Metta who are, you know like making payouts to creators in far flung places around the world. You're seeing global treasurers who are starting to realize like, well wait a minute, I can actually move my capital around all around the world 24, 7. I can make payments into hard to reach places a little bit more efficiently. We're seeing big ERP systems and treasury management systems, adding stablecoin Rails as an additional option. So I think we're basically seeing the rails get added in all over the place. And a lot of where it's starting is, is sort of where it's been hard, you know, internationally cross border border and where there's demand for dollars. Right. I think there's also this sort of shift that's taking place. Digital dollars are very attractive. People want to hold them and so you see more demand side, you know, people who want to receive funds this way and want to keep it in that as well. And then within like the financial infrastructure, like the financial markets etc. I mean basically you know what we've seen happen is digital asset markets got all the big Wall street trading firms beginning to you know, know trade crypto and then they learned about 24 7, 365 collateral and the ability to move and settle stuff instantly around the world. Now that's starting to penetrate into traditional markets. And so you're seeing more and more, you know, the dtcc, you know the big kind of clearing infrastructure for securities standing up infrastructure where the cash settlement is actually happening with USDC because it's a, it's sort of on chain system. So we're seeing it work its way into the core of the financial system and we're seeing it out at the periphery of the way global payments happen. You know my view is obviously is like this is like a superior medium of exchange. It's programmable money and the unit economics are better, the user experience is better. So eventually we think this will obviously absorb sort of like digital media slowly absorbed and, and became a much, much larger thing compared to non digital media.

[John]

I feel like you're using infrastructure, financial infrastructure in sort of the, the ephemeral sense, in the metaphorical sense, not in the literal. Like we need server racks that are running the Rails. Right?

[Jamie Lair]

Yeah.

[John]

But I'm just interested, even if it isn't the, the most crucible moment for the business, what does the physical infrastructure side of the business look like? Is that fairly turnkey at this point? Has most of that engineering been done or is or is there still a work to be done to keep the network even moving faster and even more uptime?

[Jamie Lair]

It's a, it's a great question. So I mean so, so two things. So one is like Circle is a software company basically like we're a bunch of people of laptops. We make software. We deployed in clouds. It runs and it powers like all this stuff. But critically though, you know a lot of this money and the, and the, and the smart contracts they run on these blockchain network operating systems. So you do have this new layer which is these blockchain network operating systems. And actually today, you know, we announced with ark, which is the new blockchain network operating system that we've been building and launching, that essentially that the actual physical infrastructure is, which are often called the validators. These are the firms that run the nodes that actually run the compute, run the transactions for the data. The validators are actually we had a number of them around 10 or 11, which included, you know, the largest asset manager in the world, BlackRock, the two largest payment retail payment systems, Visa and MasterCard, the largest securities clearing and custody firm, DTCC. Global Banks, a whole bunch of others basically are running that infrastructure alongside us. That is actual infrastructure. These are data centers. These data centers have SLAs, they have uptime requirements, they have information security requirements. And so these new networks, these new network computers, which are these blockchain network operating systems, you have to run that infrastructure. And so we've actually built a model where there's like very high service levels where actually that infrastructure can kind of withstand the scrutiny of like a central bank that's saying, is this real money? Are these real financial market transactions that are happening and kind of meet the kind of assurance that is required to do that? And that is going to continue continually evolve. Like we're pumping a lot of transaction volume and stuff through this, but it's going to, you know, with agentic, with money velocity growing much, much larger, like we, we're going to need to continue to see that scale. But it actually is like there is a physical infrastructure layer to support these new operating systems as well.

[Jordy]

What concerns do you have for the, the blockchain and crypto industry broadly with new powerful AI models coming online that have cyber capabilities open and closed? I imagine that you guys have been super, super on top of this as circle, but there's so many, you know, small companies and blockchain organizations that have already been the target of various cyber attack.

[John]

There was some CEO that put 100 bitcoin in a wallet and said, like AI Labs, co hack me, come get it.

[Jamie Lair]

This is, this is, you know, crypto is cryptography, right? And so at the end of the day, like the whole concept is in code, we trust. I mean, that's literally the motto of crypto is like, we're trusting crypto, cryptography work. We're entrusting mathematics and smart contracts. And the execution environments are very, very sensitive types of code because they actually intermediate money. And so it is like high stakes. It is super high stakes. We saw, you know, a hardware wallet that had not actually, you know, had not used the best encryption methodology for its seed phrases actually has been drained. People thought it was in a hardware wallet. It's been drained over the last week, over $100 million of losses. So it's a very serious issue. We're taking it very, very seriously, not just for our own operations, but as like we bring Ark online and we put out this new operating system for economic activity. It needs to be hardened in a different way. The attack surface, the attack vectors, the kind of security that say I'm a startup builder, I'm developing an app that's going to deploy on one of these networks. You know, what do they need to be able to have some level of assurance that the code that they're deploying on these new types of network operating systems is going to work and be secure in light of these kind of new cyber capabilities. So it's like a whole new problem space. We're very actively working on that. Like it's, it's now like a critical part of our, our engineering and what we think actually is needed for builders too. Like builders, you know, have to kind of take this into account and it's very different world and that's changed.

[Jordy]

Yeah, and I do think that, you know, the, the industry's overall problems effectively become your problem as 100 as a regular 100% coin provider. Because it's just it, you know, the more hacks that you have, the more trust issues that people have. Yeah, technology and, and even if it's

[John]

on a completely different architecture, it could

[Jordy]

have even been a social engineering hack. Yeah, it's still badly, I mean we've

[Jamie Lair]

seen, seen, we've seen a real increase in attacks and even the social engineering attacks are often orchestrated now because it used to be you get these shitty emails that had broken English, but now the emails are actually well written and they have a better contextual understanding of who they're targeting. And so everything is just a different risk surface. And yeah, we think about the whole of the ecosystem, not just our own infrastructure because we can kind of have this, this broader role that we play.

[John]

Yeah, if I go back to sort of the early Bitcoin days, there were fight the small blockers versus the big blockers. I don't really remember all these details, but the Ethereum wing, you know, all these different people with really, really strong philosophical differences, huge economic interests at stake. It feels like over the last 12, 18, 24 months, the crypto community has sort of come together loosely and there's been some regulation that's been laid out. What do you think the AI industry can learn from the journey that the crypto industry has been on from a regulatory perspective?

[Jamie Lair]

Yeah, I mean, look, I think, you know, monetary infrastructure, financial infrastructure has always been pretty heavily regulated. I think, you know, we've always tried to walk the line between, you know, open permissionless infrastructure, open source technology. All this stuff is, is built around those, those, those themes and that thesis that's fundamental to the DNA of, of crypto is open networks, open protocols, open source software, all of that doing things out in the open. And so that's, that's just sort of philosophically there. I actually think it ultimately helps from a regulatory perspective the more, the sort of more open that you are, the more that everyone can kind of see what's going on. I think, you know, you know, so, so I think that's certainly something that can be learned and that has to do with this sort of open weights discussion vis a vis, you know, kind of, kind of labs and other things like that. But I, you know, I have my own views on AI and regulation and I think, you know, very clearly like these are foundational utilities for society and they're now cyber weapons, if not other types of weapons. And so the regulation, there's going to have to be regulation and supervision and registration and other stuff because the stakes are so high for society right now.

[John]

Yeah, it's interesting that you, you mentioned the, the openness being a, like, sort of correlated with like a bigger tent. And we saw that with Jensen from Nvidia putting out that open letter and getting so many names to sign on in a way that, that has not happened with other little regulated ideas of oh, should this state law or law or federal preemption, all those little things that the labs have been doing. Jensen was able to just come out with some, something that was very broad. Some people disagreed, some people didn't, but a lot of people sort of were like, okay, we're going to band together for this particular vision, which is interesting. Yeah, it does correlate to what you just said. Love it.

[John Gimatteo]

Definitely.

[John]

Well, thank you so much for taking the time to come chat.

[Jamie Lair]

Of course.

[Jordy]

Awesome progress. Great to see you.

[John]

Have a good day.

[Jamie Lair]

Thank you.

[John Gimatteo]

Cheers.

[John]

Goodbye. Let me tell you about the New York Stock Exchange. Want to change the world, Raise capital at the New York Stock Exchange. Couple quick hits before we bring in our next guest. Google. We missed it with the Demis news. That's obviously steamrolling the timeline. But there's also a story in Business Insider, Google is in talks to buy a coding agent startup called mechanized for $1.5 billion. Do you know that?

[Jordy]

Yeah.

[Tyler]

So it's an RL environment. So they basically build a bunch of these environments and sell them to labs.

[John]

Yeah. So Sean Kai Si says the first RL environment major acquisition outcome, mechanized for 1.5 billion makes a lot of sense when it's been in the data discourse for a long time that GDM's synth synthetic capabilities weren't up to OpenAI and Anthropics. Many of the recent departures from GDM and the other labs cited this certainly Mechanized, as one of the four players in RL environment markets that I would even consider to have some modicum of good synthetic data scaling and so identifying a problem with the organization with the build out, going and opening up the checkbook to the tune of 1.5 billion to potentially solve it. Still in the rumor phase. The other news we didn't really get to yet is Ilya Sutskever's company, Safe Superintelligence, is allegedly rumored to maybe be releasing a model in August. That's this month. And Chubby here says, I took a look at their website. They stated very clearly their only goal, their only mission is to develop super intelligence. That's their sole focus. In that sense, this model release will be far more than just another model release in some form. They must have achieved superintelligence if we take their statement seriously. So very interesting. See what happens there if it's pressure's on or if it's something that just sort of sits within all the other benchmarks. But we'll. We'll see. Good luck.

[Tyler]

Yeah, I mean, this was like very briefly touched on in the Gavin Baker Invest, like, best episode.

[John]

Yeah.

[Tyler]

So it's like, unclear,

[John]

you know, we'll

[Tyler]

see what actually happens.

[John]

Yeah, it's not like Ilia came out and said, like, we're launching get ready. They did announce some fundraising news with Nvidia and. And he did say that it's time to scale. Sort of the age of research might be over. And so we're thinking that maybe a product is coming, maybe a demo, maybe some evaluations, maybe some benchmarks. We love benchmarks. Maybe we'll be able to move the goalposts because I want super duper intelligence. I'm not settling for super intelligence.

[Jordy]

Well, let's not keep our next guest waiting too long.

[John]

Yes. Let's bring in Mackenzie Burnett. Match from Ambrook. Back on the show. Welcome back to the show. Mackenzie, how are you doing? Good.

[Mackenzie Burnett]

How are you guys doing?

[John]

We're doing fantastic. Congratulations. Give us the news. What happened?

[Mackenzie Burnett]

So excited to announce that we just raised $30 million. Series E. Congratulations. Yeah.

[John]

Locky Groom. What a great, what a great partner here.

[Jordy]

Jordy, I think it's been somewhere between six and 12 months since the last time you were on the show. Maybe on the shorter end. Talk about the progress. What have you learned about the state of American agriculture, the state of the industry that you're operating in?

[John]

Physical economy. Yeah. Have you narrowed the scope of the go to market motion or have you actually broadened it?

[Mackenzie Burnett]

Yeah, so we, so since we last chatted, we were, when we last chatted, we were Last summer around 2,500 businesses using Ambrook. Now we have over 8,000 businesses using Ambrook and a lot of them are in agriculture. But actually we raised the B in order to start to expand to other verticals in the real economy because we started to see a lot of natural adoption with we have over a thousand truckers on the platform, general contractors, property managers, nonprofits. AG is super diverse. So a lot of those customers started pulling us into their side businesses or their neighbors businesses or family members. So that's a big part of the focus.

[John]

Are customers excited about potentially not needing to work with like some behemoth legacy ERP system that might be less agile in the AI era versus maybe you have a smaller solution next now. But if you just look at the growth rate of the technology and your team and your product, they're going to be, you're, you're just going to naturally solve a lot of problems that come up over the next few years for them.

[Mackenzie Burnett]

Yeah, I think, I think our customers are already seeing that Ambrecht is a lot more tailored to the complexity of their operations. So there's kind of this messy middle that hasn't been venture back able for a long time. Which is if you're a business that's too complex for QuickBooks or spreadsheets, but you don't have the team or resources to onboard to a SAGE or net sample suite. I would say probably about, we estimate about 25% to 30% of America. American small businesses kind of fall in that messy middle where they're multi p and L, they have complex balance sheets, but they don't, you know, I think there's, there's some talking X about like building for finance teams of one. We're building for finance teams of zero.

[John Gimatteo]

Okay.

[Mackenzie Burnett]

And like, you know, that is bringing AI CFOs to folks who were. We might actually be their first business software. Like 50% of our customers are moving off a pen and paper. You know what to build and help them leverage. AI is a pretty different way of building than if you're building for a professional desk worker.

[Jordy]

Okay, so historically there was fintech companies that would make vertical solutions for things like construction and agriculture and trucking. And I'm sure you're now competing with some of these players. How much is AI allowing you guys as Ambrook to like go into these new verticals and create the specific features or workflows that are more relevant within these sub industries?

[Mackenzie Burnett]

Yeah, it's making it a lot easier to, to come with the right context layer I think for what folks need. So you can think of, I think Amber is not vertical SaaS, we're more vertical go to market. So under the hood we are actually look a lot more like a much more user friendly net suite or sage. 30% of our customers access Amrin exclusively via our mobile app. We definitely have like the best mobile app in the industry when it comes to accounting software because we had a bill for users that were not by their desk most of the time. We kind of call it the deskless economy. And so there's a lot of workflows that we had to build for. But you can kind of think of the ERP which we spent the past couple of years building as that agent context layer. Like if you ever had to build agents, the first thing you have to do is actually clean up all the underlying data. That's what we've done really well. And now we're building so that both that whole data layer is both human legible and agent legible. And those agents make it a lot easier to personalize or to otherwise speak the language of someone's business. Even if the underlying components or primitives are actually quite similar industry to industry. Which is why we've been able to expand so quickly without having to like build a lot of custom features for these different verticals.

[Jordy]

What is sentiment around AI for your customer? What kind of like how do they feel about AI generally? I noticed on the website you guys are not, certainly not leading the. Here's the new hot tool that's going to revolutionize your business with it, with AI, even though you're using it under the hood, I'm sure in a bunch of different ways. But how do they, how do they feel about it? Do they feel like it's a useful tool? Are they generally against it? What's Your read?

[Mackenzie Burnett]

I think our customers are generally open to it. I think there's just a lot of really healthy skepticism about whether AI is actually using useful, which is actually useful to them as a business owner. Which is actually quite similar to the conversation I think is happening on X right now, which is you have some folks that have been able to really understand how to build, but it requires a lot of infrastructure to be able to get there. And our customers don't have teams of engineers to be able to build all the things that they need in order to actually build their first agents. They're not going to be rolling their own, you know, agents on eve or something like that. So there's, there's a lot of work that we're doing to kind of meet people where they are. But I actually have been talking to a lot of our customers, just asking them about general sentiment toward AI and there is just a broad openness. It is just a little bit.

[Jordy]

Yeah, it's more like show me, show me down.

[Mackenzie Burnett]

Yeah, exactly. And there's a lot of things where I think if you. I think if you build it right, they will come, but a lot of people don't know how to build it right.

[Jordy]

I would say totally.

[John]

Parker Conrad, when he launched Rippling, had this idea of the compound startup, this idea that he had to build multiple products and not a single point solution. Do you like the term compound startup? Do you think it applies. Applies here? Do you think it's a relevant philosophy for the modern era?

[Mackenzie Burnett]

Yeah, I think there's a lot of learnings and talking to one, a lot of admiration for like Parker and the way that he thought about building, building that company. I think talking to a lot of friends at Rippling, I think there are some learnings to take from that and there are other learnings, which is in a compound startup you end up seeing a lot of different duplication of work. So there is actually some inefficiency within the company itself. And so when we've been thinking about Ambrook, I've been trying to take the elements of that that I think make a lot of sense, which is you build a platform that can enable sort of an emergent ecosystem on top. And that ecosystem can either be opportunities within the company or it can be things that our customers are actually able to build themselves. So one thing we decided to do a lot earlier, I think, than a lot of other players in the space was just to. Was just to give our customers access to an external mcp. And so we have customers now that are rolling their Own like with lovable or base 44 or something. Rolling their own apps for like hunting bookings for like one of our Texas ranchers, for example, and then pulling in context from Ambrook into that. And we're, you know, we're now letting people write that you know, will be letting people write back into the self. And I think that that's it. It allows for a lot more creativity outside the company, not just in. But if you think of yourself as a really good platform, then I think you can, you can get some of the benefit. A lot of the benefits of the compound startup.

[John]

Yeah, that makes a lot of sense. You said you're vertical in go to market. What is the playbook for entering a new market? Like if you're saying we're going to go after hunting organizations or trucking organizations, are you just dialing in the targeted ads and the messaging or are you going to conferences and hiring a whole new sales team?

[Jordy]

Keep booking the hunting trip. No, you're like, we're here for two days. Let me tell you about Amber.

[John]

Maybe that's it.

[Mackenzie Burnett]

Yeah, I know there's so the way that we've been finding this playbook starting to work and replicate across these different verticals are first you have to do a lot of brand awareness. That's the push and that can be Facebook. Facebook is actually super. Is still has a lot of art left within non SaaS, non tech industries. So a lot of brand awareness on Facebook. And then what you start to do is once you've got enough of a, a set of customers that are really happy, you start to do case studies and then take those case studies and you start to do build partnerships with local trade associations and then you start getting third party credibility rolling. We also go on a lot of really niche podcasts. This is not the only podcast that I also, you know, gone like the wealthy cowboy or, you know, and that has been really effective. And we also help on those and so helps them with brand awareness. And then you start to build it and then you start to get word of mouth and then you start to see the regional density kick in. So in the counties where we have more than 1 to 2% market penetration, our CAC is half of the counties where we have maybe 10 to 25 dips of market penetration. And so that spread is just social proof and word of mouth. So you have to kick start the

[John]

flywheel going, wait, how old is the company?

[Mackenzie Burnett]

So we started in 2020.

[John]

Okay, this feels like a very mature operating philosophy. Much more than six months in launch

[Mackenzie Burnett]

the product in 2024.

[Jamie Lair]

Yeah.

[John]

Okay.

[Mackenzie Burnett]

So we spent a couple of years, we spent one or two years kind of figuring out what product we wanted to build, keeping the team really lean. And then we spent, spent two years just sitting in a private beta with a couple of dozen of design partners.

[John]

Interesting. Interesting. Very cool. Well, congratulations on the round. Congratulations. The progress.

[Jordy]

Yeah, Good alpha. Yeah, good alpha on go to market.

[John]

Yeah, I like it. Lots of people taking notes. Thank you so much for coming on the show.

[Jordy]

Yeah, great to see you.

[John]

Have a great weekend. We'll talk to you soon.

[Tyler]

Cheers.

[John]

Goodbye. Let me tell you about Codex. Codex is a powerful workspace for getting work done with AI agents. Whether you're writing code, analyzing data, creating content, or automating business workflows, Codex helps you move projects forward from start to finish. Last story that I want to talk about, Jordy, if you got anything, let me know. But the founder of ByteDance apparently just banned his employees from distilling US frontier models. Which begs the question, what were they doing before? But according to this post, fears distilling U.S. models would trigger Washington. That there might be pushback in Washington D.C. over this. Obviously a lot of labs, they don't like getting distilled. We've seen all the complaints and it might put TikTok at risk again. Anthropic has accused Deepseek, Moonshot, Minimax, Zai, Alibaba, all of distilling Claude, but they haven't.

[Jordy]

I think, I think he's doing a little bit of comms and marketing.

[John]

He said we, we should be willing to sacrifice some short term gains for longer term goals. No distillation allowed. Even if we lose. Interesting story. Yeah, we'll see. We'll see. Maybe the distillation attacks will stop. Maybe they will continue unabated. Maybe Superintelligence can weed it out. If you're trying to distill anything else

[Jordy]

in the timeline from SpaceX earnings yesterday. Capital says Elon on the SpaceX call. It's probably also worth mentioning that our internal projections for reaching 1 trillion in revenue have moved up from 2031 to 2030. And Ryan Peterson says effort. We're making our 2031 goals. Our 2030 goals now too.

[John]

I love it. Well, there's another model that launched Muse Code from Meta Superintelligence. Mark Zuckerberg posted again on X the Everything app. Wait, I gotta follow him. Why am I not following him? Because he's just a new poster now releasing Muse code in beta today. It's a terminal coding agent that takes on complete software engineering tasks. Powered by Musespark 1.2, a coding agent, a coding focused model update and so I'm sure people will be benchmarking this, seeing where it stacks up, what it how it helps, how it prices out, where it's good, where it's bad, all those things. Over in Microsoft land, they're going all in on GPT 5.6 SOL. A Microsoft exec just sent an internal memo that's designed to end token maxing and makes OpenAI's GPT 5.6 SOL the default model for internal use. So that was line one on the Ed Zitron to Do list for Sam Altman. Make sure Microsoft likes the model and seems like mission accomplished. Any other news you want to go through today? Jordy? We can talk about the New York Times tomorrow.

[Jordy]

We'll see you tomorrow, folks.

[John]

Have a good day. Have a good Thursday. Is it Wednesday? Have a good Wednesday. We'll see you tomorrow.

[Jordy]

11am Pacific August 5th of your life.

[John]

5 stars on Apple Podcasts and Spotify. Sign up for our newsletter tvpn.com we love you. Goodbye. Peace.