Meta Connect: Top Takeaways, 𝕏 Timeline Reactions | Louis Mosley, Brendan Foody, Darren Mowry, Kayvon Beykpour, Mukund Jha, Noah Löfquist, Dan Lahav, Ben Milne

Summary

TBPN Podcast Summary – September 18, 2025

Hosts: John Coogan & Jordi Hays

Guests: Louis Mosley (Palantir), Brendan Foody (Merkur), Darren Mowry (Google Cloud), Kayvon Beykpour (Macroscope), Mukund Jha (Emergent AI), Noah Löfquist (Oftn), Dan Lahav (Irregular), Ben Milne (Brail), and more.

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Episode Overview

This packed episode of TBPN covers Meta Connect 2025, the launch and live demos of Meta’s new Ray Ban display glasses, reactions across the tech landscape, and a rapid-fire sequence of interviews—spanning Palantir’s UK milestone, booming AI agent infrastructure, live coding for consumers, start-up cloud dynamics, and latest in security and stablecoins. Hosts John and Jordi trade insights and timeline memes, while guests provide on-the-ground takes from industry-defining events.

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Meta Connect 2025 – Major Announcements and Takeaways

A. Meta Ray Ban Displays: A Decade after Google Glass

• New “Meta Ray Bans” announced, 12 years after Google Glass.
• Reflections on Google Glass's $1,500 price tag and its quick societal rejection due to privacy concerns.
  • Quote: “The world was not ready for the glass hole.” (B, 00:53)
• Discussions on the new glasses: lighter, more stylish, weighing just 69g.
• Google Glass’s infamous social backlash: “It’s a terrible feeling to be filmed by a stranger.” (A, 02:13)

B. Live Demo Drama

• Multiple failed live demos by Zuck on stage, especially the WhatsApp Video Call, caused buzz.
  • Jordi’s theory: Failure likely due to “simultaneous live streaming and video call overstressing the glasses.” (A, 07:14)
  • Hosts stress, in their hands-on tests weeks and months ago, “video calling worked perfectly—so real-world demo anxiety is real.” (A/B, 07:39)

Community & Industry Reactions

• Ben Thompson: "Live demo fails are good tech karma… you get rewarded for taking the risk and setting the bar low." (B, 16:55)
• Dylan Field (Figma CEO): “Live demos can fail. We’ve all been there. The tech is still awesome. Onwards.” (B, 15:57)
• Shiruya: “It takes real courage for Zuck to go live and potentially make a fool out of himself. Everybody’s a gangster in their controlled environment.” (B, 12:58)
• Mark Gurman: Compares to Apple’s Face ID demo failure—suggesting Apple prefers pre-recorded safety now. (B, 12:02)

Product Experience & Reviews

• Hosts, having tested the glasses, hail massive hardware improvements (lighter, more comfortable), and the seamless heads-up display.
  • Quote: “You really can wear these all day without any serious strain. They’re just slightly chunkier than normal Ray Bans.” (B, 08:10)
• The Verge: “…regret to inform you Meta’s new smart glasses are the best I’ve ever tried.” (A, 15:51)

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Meta's Roadmap, AI Integration, and Wearable Context

• AI remains in the periphery; wearable computing is deemed “underhyped” compared to AI.
• Discussion of "personal superintelligence" as the next killer app, especially for context-aware commerce (“order that” via camera, instant purchase). (B, 21:15)
• Shoutout: Neural band input (worn on wrist) impresses hosts for its comfort and potential as a platform input mechanism. (A, 25:01)
  • Quote (on neural bands): “It’s… the same motions you’re used to on an iPhone. You just don’t have a phone.” (A, 25:01)

Gaussian Splatting and 3D Capture

• Meta demoed 3D space scanning (“Gaussian Splatting”), notably scanning rooms and objects (hosts spotted their own brand logo as an in-demo “Easter egg”). (A/B, 17:36)
• Use cases: Real estate walk-throughs, automatic 3D game/street maps, novelty today but a strong pipeline to future generative environments. (A/B, 18:55)

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Timeline Reactions & Tech Culture Moments

• Apple, Google, Meta compared for their demo policies, product delivery timelines, and employee culture (Meta execs noticeably younger).
• Fashion at Meta: Instagram's leadership's outsized influence over tech x fashion, and the necessity of “VP of Fashion Partnerships.” (A, 35:44)
• Subsidizing Hardware: $799 pricing for the new glasses surprises many. Speculation: heavy loss-leading is acceptable to Meta (potentially $200+ subsidy per unit; echoes Oculus/Quest adoption strategy). (B, 33:36)
  • “They never need to make money on the hardware… It’s about owning the next platform.” (B, 34:04)

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Key Guest Interviews & Segments

Palantir’s UK Milestone [48:00–58:00]

Louis Mosley:

• $1B+ contract with UK Ministry of Defense for battlefield AI/data analytics.
  • “First billion-dollar deal Palantir has done outside the US.” (D, 49:12)
• Large investments in hiring and infrastructure in London (20%+ of global Palantir staff already there).
• Describes evolution from defense/intel contractor to broad public and private sector platform.
• Interoperability for allied defense systems is crucial, learning lessons from Ukraine.
• AI is enabling drastic increases in output per head—“90% of what used to take a FTE could now be done by AI.” (D, 56:34)

AI Agents & Data Labeling Boom [75:00–90:00]

Brendan Foody, Merkur:

• 19-year-old founders scale company to $500M in revenue in 17 months, supplying expert data labelers for AI agents.
  • “We turned around 25 Olympiad medalists in 24 hours.” (E, 76:02)
• Future: professional domain evals (e.g., coding, consulting), not just academic benchmarks.

Google Cloud AI Builders Summit [91:00–97:40]

Darren Mowry:

• Google’s cloud for startups program sees surging demand (credits burn faster as AI startups scale faster).
  • “Startups are using credits, but then they're like, I'm not going anywhere.” (F, 96:58)
• Gemini, Llama, Sonnet models—Google's “agentic” SDK gains traction.

Live Streaming Lore & Macroscope [98:00–122:10]

Kayvon Beykpour:

• Periscope’s origins; live streaming on mobile was “too early,” emphasizing async-first social as winning model.
• New startup, Macroscope: “X-ray vision for your company”—AI summarizing engineering output, code changes, etc.
  • “In five years every company will have an understanding engine like this. Today it’s meetings and spreadsheets for status.” (C, 111:03)

AI for Consumers: Wipe Coding & Computer Use Agents

• Mukund Jha (Emergent AI):
  1.5M apps built in months; target market is non-developers—the “consumer” side of AI coding, not (yet) enterprise. (G, 123:06)
  • “A billion people have ideas in their head… We want to help them launch.”
• Noah Löfquist (Oftn):
  Building agents that use a computer like a human (scheduling, email cleaning). Main challenge: building/generating enough task diversity data. (C, 139:54)

AI Security’s Next Frontier [151:37–159:06]

Dan Lahav (Irregular):

• Exits stealth as Sequoia-backed “first frontier AI security company”—builds high-fidelity environment to simulate/model/defend against both model- and agent-level attacks.
  • “AI attacking AI, bypassing Windows Defender, novel attack paths will outstrip traditional security baselines.” (H, 152:09)
  • Goal: “Platform to secure AI agents of the future.”

Stablecoins – Infinite Customization at a Dollar a Minute

Ben Milne (Brail):

• New platform lets institutions create and customize stablecoins on demand, interoperable with existing chains/products.
  • “It now takes a dollar and a minute to create a stablecoin.” (I, 160:47)
• Motivation: lowering cost, increasing revenue, and fun customization for money—echoing pre-1863 US banking with diverse local notes. (B, 167:26)

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Rapid Takes, Notable Quotes, & Timeline Memes

• Meta’s “mythical” project codenames (Orion, Prometheus, Behemoth) and their “double-edged sword” symbolism: “Every Greek myth is a double-edged sword. Like Orion, who gets cocky and is struck down by God.” (B, 29:41)
• Demo Culture: “Failing on stage is tough… no matter what we say, you need to experience these devices.” (A, 14:54)
• Apple’s slow pace: “Apple’s next non-display model likely announced late 2026 or early 2027. That’s slow!”
• Consumer spending inequality: Top 10% of US consumers now account for half of all spending—a record. (A/B, 59:39)
• Viral marketing isn’t everything: Meme videos with 50M+ views “generated almost zero downloads.”
• AI agent applications: Next 12–18 months about automating admin, “monotonous” tasks, real-world RL environments to define rewards.

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Other Highlights

• Iconic product tie-ins: “Domino’s Rolex Air King” franchisee rewards story. (B, 41:45)
• Media shakeups: Disney’s ABC pulled Jimmy Kimmel; late-night audience now skewing retirement age. (B, 45:02)
• Humanoid robotics race: Live timeline roast of a headless robot demo (“It’s not exactly Pixar-level cute… literal clanker”). (B, 73:13)
• Coachella shifting economics: Over 60% of ticket buyers on payment plans, lineups dropped early—potential signaling of festival’s waning heat. (A, 69:04)
• Iconic inflation resisters: Arizona Iced Tea and Costco hot dog, undefeated at $0.99. (B, 144:42)
• Legendary branding stunts: Limewire acquiring Fyre Festival brand for $245k (“What are they going to do with that?”) (B, 132:54)
• Retro OpenAI Brand Explorations: Internal logo exploration from Feb 2023—“Serif OpenAI font just feels like a packaged piece of software.” (B, 136:43)

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Concluding Notes

A goldmine episode, delivering:

• Insider access: hands-on with Meta’s wearables
• Sharp industry analysis: on platform wars, AI progress pacing, and demo culture
• Diverse founder interviews: spanning defense, dev tools, consumer AI, infra, and security—each dishing candid insights about growth, fundraising, challenges, and future vision.

For anyone tracking the future of computing platforms, AI agents, and digital work, this episode—through both its freewheeling panel and structured guest segments—is an essential listen.

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Memorable Quotes & Timestamps

• “The world was not ready for the glass hole.” (B, 00:53)
• “It takes a lot of courage for Zuck to go live and make a fool out of himself. Everybody gangster in their comfortable, controlled environment.” (B, 12:58)
• “You really can wear these all day without any serious strain. They’re just slightly chunkier than normal Ray Bans.” (B, 08:10)
• “First billion-dollar deal Palantir has done outside the US.” (D, 49:12)
• “In five years every company will have an understanding engine like this. Today it’s meetings and spreadsheets for status.” (Kayvon, 111:03)
• “It now takes a dollar and a minute to create a stablecoin.” (Ben, 160:47)

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[Explore further guests, products, and timeline memes in the full episode above.]

Transcript

[A]

You're watching. Welcome to TVPN.

[B]

Today is Thursday, September 18, 2025. We're back in the TVPN Ultradome, the Temple of technology, the fortress of finance, the capital of capital. Hello everyone.

[A]

Bobby, Kai Long since we have podcasted, it has been.

[B]

We had a bit of a dry spell. We fixed it. We're back. Thank you to everyone in the chat who's committed to never missing a stream.

[A]

All of you, Andrew Miller, Bobby Cosmic.

[B]

Parker, good to see you guys. Yesterday we were at Meta Connect 2025 and they launched the Meta Ray Ban displays. 12 years since the launch of Google Glass. Google Glass was 2013.

[A]

Did you ever get a pair?

[B]

I never owned them. They were fifteen hundred dollars at the time. I was dead broke, could not afford them. Probably would have bought them if I had the money, but I would have.

[A]

Cut your Runway by like 15%.

[B]

For sure. For sure. It would have been rough. But I did get to try them in San Francisco at the time and it was cool. Very small screen, very limited interaction. Some of the same demos, honestly. Messaging, maps, music, the usual, but way less stylish. Way, way less stylish. And very quickly, the world was not ready for the glass hole. The Google Glassware. Are you familiar with that term? It was one of my friends actually. I think he got like assaulted or something for wearing them. I don't know if he actually got like punched, but he definitely got accosted at a bar in San Francisco for wearing them. He was an associate in Dreesen Horowitz at the time.

[A]

Would they be perpetually recording?

[B]

No. So it was the same thing where you would turn them on and record. But they had this vibe to them in the, like in the world where it was like, oh, this is like the surveillance state. Like every. There's going to be a camera everywhere. And this is before, I mean, 13 years ago people or 12 years ago, people were not have their phones out, taking photos constantly. And so all of a sudden this idea that like you could be in a bar and someone would be taking a video or photo of you like automatically was pretty rattling to people. And so it was, it was like a pretty severe like rejection.

[A]

It's a terrible feeling to be filmed by a stranger. Just in general. I was at a restaurant a week or so ago on a date with my lovely wife and this person was basically documenting like the entire outside of the restaurant. We were sitting at an outdoor table and like repeatedly like panning over us.

[B]

Interesting.

[A]

While we're just sitting there.

[B]

Yeah, it's suspicious.

[A]

Yeah. It's just, it is a violation. Yeah, I'm all good if I'm in the back of the picture of the video that you're taking. But if you're like panning over and I become the subject of the video.

[B]

It is a little off.

[A]

And we don't.

[B]

Yeah, because it could be that you're. The rest of the video is just window dressing for an excuse to actually be filming you. For some reason you're like, why, why do you want to.

[A]

Yeah, what's going on here?

[B]

Just ask. Yeah, at the same time, I've been on the other side. Like we were at the airport and I saw this guy absolutely crushing sales calls with a full on headset on instead of just Bluetooth. You know, people who wear the AirPods or the Wired headphones. This guy had baseball headset with the microphone down in front of his mouth. He was just barking orders, locked in.

[A]

He was a LinkedIn general.

[B]

This is a champion. I love this guy. I'm so into this dude. I should have just asked and gone up and said like, can I do a professional photo shoot with you? Like I, I love, I respect your culture. Yeah, can I, can I, can I check out your rig and enjoy that? But I, I restrained myself and I didn't take a photo. I did, I did go up to you and say, hey, you gotta check out this guy, this killer. Maybe we got to recruit this guy.

[A]

We did take a lap and kind of investigate.

[B]

Yeah, he had his fingers in a lot of pies. Much like Rune. We printed a post today. We got Rune. He says of our own quote, yes, Rune says run has got his fingers in a lot of pies from the God Whispers of TVPN by Jordi and John. And I remember saying this, but I don't remember what pies I was referring to. I mean he has a job.

[A]

We don't even know what, what it means. But it is, it is certainly provocative.

[B]

But I'm glad he enjoyed it and quoted it on the timeline and you know, now it's printed forever. Anyway, ramp.com save time and money. Time is money. Save both easy to use. Corporate cards, bill pay.

[A]

It was absolutely fantastic watching you at your absolute best.

[B]

Yes.

[A]

Doing a ramp ad. Right. Walking up, I'm watching Zuck walk up the stairs. He's feet away from us and you're just barking, just barking. Ramp.

[B]

I love it. Like a carnival barker. Of course, yesterday the stream was only made possible by Restream. One live stream, 30 plus destinations, multi stream and reach your audience wherever they Are. Thank you.

[A]

We were actually everywhere. We were over on an Instagram.

[B]

Yeah. We did our first Instagram @tbp livestream. We're going to do a lot more there. Build out a full vertical layout. I, I think it's going to make a lot of distribution a lot easier. Reels get on TikTok. All these different things. Glad that everyone showed up for return to form TBPN Classic. Just. Just a couple good boys hanging out.

[A]

TVPN at its best right here in.

[B]

The ultradam technology brothers. Well, let's go through reactions to meta connect 2025. TJ Parker had a post. Meta execs are 20 years younger than Apple's and still willing to do live demos, unfortunately. Very bearish for Apple. It's a good take. There were a few. Yeah.

[A]

I mean the, the, the wild thing from, from the interviews, obviously you could find this out from just doing a little bit of research, but if you were just watching and realizing how young the Meta executive team is and how long they've been working together.

[B]

Yeah. Because they all were like. They were like 22 and they started the company and they joined like most of the people. The average tenure of person we interviewed was probably 15 years and they were all like in their 40s at most. But the drama on the timeline was around the failed demo. I don't know if we want to play the actual video. We were reacting to the keynote live, but we were talking and we kind of picked up on one of the demo fails. I didn't realize the second demo fail happened. Very bold.

[A]

But yeah, by the way, we're going to figure out how to do better keynote.

[B]

Sort of like reactions. Yeah, yeah. It's kind of crazy.

[A]

We were struggling with the audio.

[B]

Like we want to give you the facts. We want to let you hear what's happening in the keynote because that's when the news out actually breaks. Like they, like they don't want anyone talking about the fact that the new Meta ray ban display is 799. We kept almost leaking until Mark says that on stage. So you gotta wait until he says it, so you might as well just watch along. So anyway, bit of something to practice.

[A]

It was. It was obvious. I mean we were surprised, especially rewatching the keynote afterwards and seeing the moments where the demos failed. We were surprised because we got those demos.

[B]

Yes.

[A]

Multiple times. And they worked.

[B]

Yep.

[A]

And so we were kind of trying to. We were trying to figure out why that might have been. I think our theory for why Zuck's demo wasn't Working on stage is that the glasses were simultaneously live streaming.

[B]

Yeah.

[A]

And trying to carry out the regular functionality, the video call. So we were. We had done the video calling functionality with WhatsApp.

[B]

Yep.

[A]

Multiple times.

[B]

Didn't have a problem at all.

[A]

Had no problems at all. And so. And the first demo that we did was months ago. Right. So surprised that that happened. But also just like real time live streaming from first person is like very cool functionality.

[B]

Yeah. Although that's not something that they're launching.

[A]

Yeah.

[B]

So it's very odd that you could imagine they successfully live demoed a product that doesn't exist or a feature that's not live yet, which is live streaming from the glasses.

[A]

And you could tell the OS was like. Thought that the video was already pulled up.

[B]

Yeah, yeah. Because it was streaming or something like that. I think that one of the stories is like, they clearly went super hard on weight reduction. The display glasses. The Orion demo that launched last year, which actually also had failed a botch demo as well. It was. It was. It was chunky, but still very thin and light. And when you try it on, it feels great. But this is like remarkably lighter. Like 69 grams. Carmack. I thought Carmack's quote was a hundred grams for a headset and $100. Turns out he was saying 250 grams and $250, which is. I mean, 69 grams is way less than 250. So you really can wear these all day without any serious strain. They're like just slightly chunkier than just normal Ray Bans. And so. Yeah, let's pull up the actual demo and see exactly what happened here.

[A]

WhatsApp video call.

[C]

There we go.

[B]

So he's trying to kick off a WhatsApp video call is to Boz. Yeah, well, I. This is so bold. And you can't see it because we have our screw there.

[C]

I don't know what happened.

[B]

At this point. He's done this so many times.

[C]

Maybe Boz can try calling me again.

[B]

Whatever. They're having fun. All right, well, I got a missed video call. Okay. There's the actual video. And in the top corner, when he does the live demos, put this, like, massive bubble. This is like. This is a live demo. This is live. We're not faking this.

[C]

You know, it happens.

[B]

Or at least you know you didn't fake it.

[A]

So anyway, 4D chess, the next demo. Yeah, yeah, we'll be pre recorded.

[B]

Oh, yeah.

[A]

Train. They want to. No, I'm kidding.

[B]

No, no. The real 4D chess is that this sets expectations Low. It makes you go into it thinking I'm getting a dev kit like experience and then they can over deliver. So if you put on a, if you put on a pair of these, you're like, okay, yeah, like I'll probably be able to listen to some Music, but the WhatsApp video call functionality is probably not going to work. You try it, it works and you're delighted.

[A]

So, so it's a hard product to like demonstrate, right?

[B]

Yeah.

[A]

Really is something that you have to experience.

[B]

Yeah.

[A]

Because like even when we were talking to Boz, Boz had the display up the whole time.

[B]

That's crazy.

[A]

Got a message from Zach like right as he was walking up.

[B]

Really can't see.

[A]

You cannot see the display at all from the outside.

[B]

Yeah, well there was some, there were some good reactions in the timeline to the failed demos. But first let me, let us tell you about our newest sponsors. Privy wallet infrastructure for every bank. Privy makes it easy to build on crypto rail, securely spin up white label wallets, sign transactions and integrate on chain infrastructure all through one simple API.

[A]

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[B]

And we also have a new sponsor that the sharp eyed viewer might have noticed. They jumped in the ticker during the stream yesterday. Cognition, the makers of Devon, the AI software engineer crusher backlog with personal AI engineering team. With your personal AI engineering team. We're huge fans of Scott Wu and the team over at Cognition. We've had him on the show a bunch.

[A]

Organic superintelligence. Scott Woo.

[B]

Yes.

[A]

Productize it.

[B]

Yes. Yeah, he's had some fantastic calls about AI achieving an IMO gold medal. He's been ahead of the curve on tons of this stuff. Obviously went viral with the initial Devon launch and he's been, he's saved friend.

[A]

And now his partner with the Windsurf acquisition.

[B]

Oh yeah, that was legendary.

[A]

He saved the social contract.

[B]

Yeah, really, he, he saved Silicon Valley and so we're proud to support Cognition and Devon. So go head over and sign up. They're in ga. So let's go to Mark Garman. Remember, face id failed demo, essentially flawless for users. I wish Apple would go back to live, but I don't think it'll ever happen much. More reach now and they, and they definitely see taking risks for this type of thing is pointless. I don't think they're wrong. But on the flip side then you.

[A]

Have the Elon Cybertruck demo.

[B]

Oh yeah, the Elon cybertruck demo. That was a crazy one. And you haven't heard about. I mean there's been a lot of, you know, varying responses to the cybertruck but no one's complaining about their wins, their, their, their windshield's breaking or their.

[A]

Fortunately you don't have to use, you don't have to test your windshields as much as you have to test if your device can handle video calling.

[B]

Yeah, but it's true.

[A]

But yeah, certainly.

[B]

So yeah, on the, on the flip side, Shiruya says it takes a lot of courage for someone in Zuck's position to go live and make a fool out of himself. Everybody gangster in their comfortable, controlled environment. It's true. And you can see here the red pill for live demo in red there letting you know this is not faked. And there's been a lot of demos that have been sort of faked. I mean we're coming off the Apple intelligence where there were a lot of demos that shipped on varying timelines. There were ads that went out and features were promised and Mark Gurman wrote that big article. There's something rotten. Cupertino really put his whole reputation on the line to kind of every Apple.

[A]

Every Apple focused journalist basically put their.

[B]

Yeah. To say anything. It was rough, it was bold. And then Google had something similar where they demoed an AI, a real time video model that would interpret what you were seeing and then run through Gemini. But they sped up the wait time for the LLM which some people were like, oh, that's not fair. Although with that it's like they're going to speed it up over time. But there's always been, there's always been like, you know, criticism of the various trade offs of keynotes and I feel like, I mean this is not as bad as it could have been. It's pretty good. And overall it just felt like being there on the day. It felt like we weren't watching a movie or like an ad or a video. We were like part of a play because like you, Mark, Mark Zuckerberg and Diplo go running by you and then there's like the skateboarders and there's like this, this like dem with the crowd happened in one place and they move, they're moving around and like while we were on stage we could see Mark going from one thing to the next like actually very much participating in the keynote or the, you know, the event but in a very like moving around physical. It's just.

[A]

Yeah, it's tough. It's failing on stage is tough because no matter what we say, right when I was using, when I was demoing the display glasses, I could say, hey Meta, find me restaurants. What are some restaurants that are nearby? And on the heads up display it would pop up some options. I'd be able to select one with the neural band like super easily and it would just pull up a map and then it would give me perfect navigation. I could just walk, it would guide me to it. So having this experience, what they're selling is there's a lot of moments that you need to pull out your phone and what if you didn't have to sort of like take yourself out of the moment and you know, go like this. I think it's very telling that the Verge wrote this this morning they said, I regret to inform you Meta's new smart glasses are the best I've ever tried.

[B]

The new eight really know your audience. Total audience capture.

[A]

Just like, I'm sorry guys.

[B]

I tried a product so tech optimist and such a tech native blog and Neeli Patel I is like still running it. I think he started it and so like I don't think of the Verge as like having this adversary relationship with tech and yet like they had to frame in this way. It was very funny. Dylan Field, founder of Figma, had a more positive take. He said, congrats to the Meta team on today's launches. I saw some of the tech while it was still in, it's still in development. The glasses, AR interface, neural band and overall capabilities are extraordinary. And yes, live demos can fail. We've all been there. The tech is still awesome. Onwards. Dylan is of course the CEO of figma. We're partnered with figma. Think bigger, build faster. Figma helps design and development teams build great products together. You can get started for free. Ben Thompson also had a positive take. He says live demo fails are good tech karma because if you get rewarded, you get rewarded. Taking the risk for setting, for setting the bar low. There is a. There is a world. There's also something to be.

[A]

It's. You also have to understand like how confident you have to be in a product to go do a live demo for sure. Zuck didn't go out there being like, oh, there's. This is a coin flip, like 50%.

[B]

Chance it's shipping in two weeks. It's crazy.

[A]

Yeah. And it's just, I can't, I can't say it enough. It's so painful that like we use this functionality months ago at this point and so that's the way it goes.

[B]

Well, I was trying to break down, like, we talked to a lot of the meta team.

[A]

Wait, did you see the screenshot too, of inside the. They're doing the Gaussian splatting.

[B]

Yeah, yeah.

[A]

With.

[B]

Oh, yeah.

[A]

And you see the Lucy logo.

[B]

This was super cool. So 3D Gaussian splatting is cool. And now you can capture real world, real world spaces just by walking around in your meta quest headset. We did this demo as well. You walk around in the headset, it scans everything. They actually make it into this, like, kind of fun game. It takes about six minutes. So you can read, recreate your room, recreate anything. Tyler made a version of this just using his phone camera. It looked really good. It actually runs in a browser, but you can imagine this being really fun. But this was such a funny Easter egg that they put my nicotine pouch brand, nicotine gum brand in the octagon. And I don't think this was intentional. I think this is literally just. They went and scanned one of the octagons and our logos there, which is cool but fun to see. And it made me do a double take in the moment. The real time feedback ensures you don't miss a spot. Apple needs to get on this ASAP. I agree. @ the same time, like, I was standing in the. In the octagon and it was like, it was cool to feel like, okay, if I was here, how high would it be? It gave me a sense of scale. But there. There wasn't really like a game mechanic to it or anything.

[A]

Yeah. To me, me, this is what I brought up that I just care about. What. What kind of. Why would I. Why would I want to do this other than pure novelty? The best example I could think of is, is a real estate agent. They go. They scan a property.

[B]

Sure.

[A]

That they're. That they're marketing for. For lease or sale.

[B]

Yep.

[A]

And then people can just drop in and experience the home.

[B]

Yeah.

[A]

Like, actually from.

[B]

I see it, I see it probably more as like a pipeline to traditional 3D games and like traditional 3D geometry. Years ago, decades ago now, there was this game called True Crime the Streets of la, I think it. And it was like Grand Theft Auto. Nowhere near the level of game mechanics, nowhere near as fun of a game. But they did a full scan of Los Angeles and so you could go and find the TBPN Ultradome because it was a street by street replica of la. And I imagine that if you're able to do Gaussian splatting, you could bring that through to a generative 3D geometry pipeline and then create a game out of it. Seeing how these two technologies kind of merge, I think will be pretty important. I had a lot of fun with it and it was cool. But yeah, it's definitely in the novelty demo, I think. Overall I tried to synthesize the takes that I was pulling out of the meta team and I had three. One is just that wearables are under hyped because of how much focus there is on AI and so I feel like they're all. The entire meta team is very happy to swim in that lane where they're doing something cool that's not like, oh, it's got to be fast takeoff, got to be God in a box. Like the expectations are so high. AGI, asi. It's like, it's like, do they look nice? Are they affordable? Do they. Do the cameras work? Like it's pretty.

[A]

Yeah. Even yesterday the, the display up display is getting more hyped than live AI.

[B]

Totally.

[A]

And. And even though every gen AI product today is not, yep, 100% reliable and can have issues, the fact that you're just going to be able to walk around with this perpetual intelligence, humming along, getting to experience everything that you're experiencing, building that context in your life is underrated. And it says a lot that even in the current state they can run that. You get like an hour of battery life for like the truly live AI where it's just processing everything in real time, doing the translation functionality.

[B]

I didn't realize there was a full hour. But the other takeaway, we were digging into personal superintelligence, trying to understand what that means. This wasn't really a full AI event, this isn't llamacon, but it feels like personal superintelligence will definitely be a personal shopper. You'll be able to take a picture of something, say order that it'll go straight to the brand, maybe a Shopify integration, something like that check out for you, ship it to you. Or if you just see something on Instagram, you're going to be able to fire that off. Like we've seen the agentic commerce like outlined in semi analysis. We've also seen just yesterday or the day before, Sam Altman shared a screenshot where in the Dashboard for your ChatGPT app one of the tabs was orders and so they're clearly thinking about helping you order things. That's a huge way to take a cut of commerce on the Internet. Extremely valuable, extremely monetizable. So it Would be truly shocking if Meta was like, oh yeah, all of our customers, every brand that advertises, yeah, we don't want to continue the relationship in the AI age. Like obviously they're going to do that. So they didn't share too much there. But it's. But nothing, nothing, you know, nothing was shared that felt like that was not on the immediate roadmap. It felt like it was. And then the last thing that I was taking away was that basically like Lindy, Pieces of Cinema will be the first real killer app for VR. I think your prediction a year ago will wind up being correct. Multiple glasses. You will have something for action sports that plays in the, in the GoPro realm. Like the Vanguard. Yeah, the surfing, the ski goggles, that type of stuff will be action sports. Then there'll be the heads up display that you're maybe using when you're, you know, walking around, driving, doing whatever, answering messages, listening to music. And then if it's time to sit down, watch a movie. There will be an alternative to the, to the TV on the wall at a similar price point. Right now you can get 65 inch TV probably for like 500 bucks. I think you'll be in that same territory pretty soon. We talked to James Cameron about this. The level of fidelity watching his films. Avatar in 3D is just better in VR. He was talking about the quest 3. I think he's seen a demo of the quest 4. I think the quest 4 is going to have a screen that is at the level or beyond the level of the Apple Vision Pro, which was phenomenal. But they're going to bring all of their engineering prowess to. They're going to take the battery out, they're going to make it plastic. It's not going to have a screen on the outside. It's not going to have all this extra stuff. Maybe they'll do a neural band. Because if they do the neural band, the big thing with the neural band is that it takes, it's distributing the compute across your body. You don't want all the compute right on your bridge of your nose. That is terrible. That's painful. So take the battery, put it in the back. You know. Are they called croakies, the things like this? Is that right? Yeah, yeah. So like I could imagine croakies going over your meta Ray Bans or your, or your Oculus where the battery is actually kind of hanging dangling from the back of your head and you're getting extra battery life out of that and maybe that runs down your back. You Throw it in a pocket. Like what you do with the Apple Vision Pro. I think that was a good paradigm. I think the Apple Vision Pro, it uses hand tracking as input, but that means it has to have cameras that.

[A]

Look smart, that the charging case for the display, like, folds up flat so it can act as a regular case.

[B]

Yeah, that was cool.

[A]

If you have it at the right angle. Like those kind of iPads.

[B]

Yeah.

[A]

Screen protectors. Yeah, yeah. Neural band is also under hype from yesterday. Everybody wants to focus again on like, the actual glasses and the display. But I said it before, and I hope people, you know, you go to a retail store and demo these, try them out. But like trying the neural band, realizing how quickly you adapt to this interface, it's like this. Pretty much the same motions you're used to on an iPhone. You just don't have a phone and takes a little bit of getting used to.

[B]

Their pitch for it was, well, because it's not using a camera. You can use it out of view of what the camera would be if it was on your face. You can use it behind your back. I don't actually care about that. I think it's fine to put my hand in front when I'm adjusting the volume. I don't really see a value of putting it behind my back. I think the value is that you need some input sensor to capture what's going on with your hand. And it makes sense to just put that right next to the hand. And I think that even if it's just a couple grams, taking that off the face and putting it on the wrist is way better, way more natural. I do think it was interesting that Boz was saying that long term, the neural band could be an input device for other applications, and eventually they could open that up to developers. So you could have an app that uses the neural band as an input, or it could be a little bit more platform agnostic at some point. Very unclear where that actually goes. We were debating a little bit. We didn't get our firm percentages down. But between voice input, just speech to text versus handwriting, I think most people will be doing speech to text, But I don't know if that's just because I've been so. I dictate like a ton these days. I open up the ChatGPT app, I click on the audio mode, and I just talk and talk and talk. And then even if I'm not, a lot of times my prompt is just like, clean this up and make sure it's grammatically correct. Like, don't change it, don't rewrite it, just reproduce it and then I can just copy that into wherever I need to go. If it's a longer thing, I think that long term people will just be comfortable talking and you're able to talk in a very low whisper and it picks it up just fine.

[A]

Yeah.

[B]

The secret handwriting. I don't know how popular that's going to be. Maybe like 20% of total input.

[A]

I think it's going to be popular for short responses. Just need to be like, hey, do you want me to grab you a sandwich?

[B]

Yeah, well, there's also just.

[A]

Want me to grab you a coffee? Yes.

[B]

Yeah, well, there's also like the thumbs up. It dynamically selects emojis there. So you can just swipe and be like heart or thumbs up or thumbs down. So it is like in between. Just like send an emoji response, dictate something longer. Handwritings for something in the middle. I don't know how popular it's going to be. It's definitely like a lift. People are going to have to learn. It's like an entirely new input medium. But then again, speech to text is somewhat of a new input medium and people have figured that out. So maybe, maybe over the few years people bring that back. But I'm not sure if I would be leaning on that all the time. Maybe I'm just a terrible handwriting. So I don't know. Anyway, it was a fun event and thank you all for watching. Let me tell you about Vanta Automate Compliance, Manage Risk, Prove Trust Continuously. Vanta's trust management platform takes the manual work out of each security and compliance process and replaces it with continuous automation, whether you're pursuing your first framework or managing a complex program. Tower of Babel.

[A]

Yeah, let's start there.

[B]

So we were talking to Chris Cox, the chief Product officer at Meta, and he said that AI translation is Tower of Babel level. And it was a very funny. He used a very funny word, a judgment. He was like, with AI, you can take a judgment. And.

[A]

Well, that was in a different context.

[B]

It was in this clip. It was in this clip. AI can be used to scale a judgment. And I forgot what word he used and I asked him and he didn't remember and we kind of just moved on in the conversation. But I was. But Skooks is saying me when I don't know what the story of the Tower of Babel was about. The Tower of Babel story, of course, is humanity in the Book of Genesis used to all speak one language and then God fragmented the languages.

[A]

And so I think he was generally alluding to going back to.

[B]

Yeah, like, like, is it hubris for humanity to try and speak all the same language? There's always these. Meta loves these nicknames for projects that have. Or it could go either way.

[A]

A massive project that collapses under its own weight.

[B]

Yes, yes.

[A]

The other way to interpret that is. Okay, yeah, Glass, you know.

[B]

Yeah. Every code word is a double edged sword. Is a double edged sword. I mean every, every Greek myth is a double edged sword. Like just the Orion headset, their full augmented reality headset. Orion is the story of the hunter who gets so cocky, so much hubris, he decides he can kill all the animals and he's struck down by God and then sent to the heavens to exist as a constellation. The new data center is called Prometheus, which of course is stealing fire from the gods. And there's another Hyperion in one of those. The perpetrator of the hubris is sentenced to have his kidney or liver eaten by an eagle every day forever. There's a lot of like bad endings in these stories, but they also are like very powerful and cool names. Tyler, what's your favorite meta code word?

[A]

There's a lot, but I think there's. There's some Straussian reading where maybe Zuck is actually a doomer.

[B]

Oh yeah. Secretly he thinks that Prometheus, he will steal fire for them gods and be smited, perhaps. I mean, the behemoth thing was crazy because it's like behemoth llama. And do you remember the AI generated image that they used to promote it? It was like this very demonic, beefy, bulky llama. It was crazy.

[A]

Guys, how did this one get out?

[B]

And then it didn't get out. And then it was actually like it was too big to tame it. And like that is the story of the.

[A]

I know, but simply the image.

[B]

Yeah, the image was crazy too. And so, yeah, maybe just stick with like the version four, version five, I don't know. But then we get into numerology. Who knows?

[A]

I gotta try to find this. I have this. I'm putting this image in the chat, guys.

[B]

Tyler, do you think that they're subsidizing the cost of this thing? So Joanna Stern said, Wow, 799 for Meta's new screen equipped ray Bans and the neural wristband. I thought that was shocking. When they told us on Friday. Ben Thompson was shocked by this as well. Everyone's been reacting to just how cheap that is. The Orion headset, when they demoed it last year. The rumor that was going around was that it cost $10,000 to produce those. And so people were like, okay, yeah, so they'll get twice as cheap every year for five years or something, and then we'll be in the 750 territory. But this has a lot of the same tech and it's 799. It's half the price of the original Google Glass, which is crazy. Do you think they're subsidizing?

[A]

Definitely. Seems like really cheap. I was surprised that it was under $1,000. I don't know enough about the actual technology to tell, like, what the price would be, but it does seem like really cheap. There's so many reasons to make it as cheap as possible. Right? Just like One User Feedback 2, it can help them improve.

[B]

Oh, yeah, there's the Llama 4 Behemoth Preview.

[A]

Yeah, this is a picture.

[B]

Hey, it's a big llama.

[A]

I'm glad they transitioned.

[B]

It's kind of fun. I think it's kind of funny, but it is fun. It's kind of funny. A Jack Llama. That's something I would do.

[A]

You think somebody's sleep paralysis monsters?

[B]

It was kind of crazy.

[A]

It looks cool.

[B]

It looks. Definitely had great vibes when you chatted with it. It was goofy and laughing about the.

[A]

Fact that it was extremely metal.

[B]

But yeah, it is very. It's heavy metal. It's hardcore anyway. Much like graphite. Graphite.dev Code review for the Age of AI Graphite helps teams on GitHub ship higher quality software faster and get started for free. So on the subsidization thing, I mean, they're like, they're, they're saying like Red Arabian, the best selling product, but they're at the $300 mark, $400 mark. And I don't think they're selling tens of millions of those. I think they're selling like millions. So if you sell a million and you're subsidizing by 200 bucks a pop, it's like, okay, that's 200 million bucks. Like, that's fine. Like, Meta has no problem with that. In fact, they can.

[A]

That's AI researchers.

[B]

Exactly, exactly. So what they can do is they can say, even if they're even there, like, let's subsidize this by $1,000 and let's sell a million pairs. It's like, okay, they're gonna lose a billion. They probably can't sell 10 million or, or 50 million pairs, but they could just do a run of a million pairs at a Huge loss. And then just cap it and be like, yeah, we're out of stock. V2's coming. V2 comes and then they raise the price and they say it's even better and even lighter and even thinner. And then they slowly creep together.

[A]

But they never need to make money on hardware.

[B]

No, I don't think so.

[A]

Like, they never need to make. I don't think here. I'm sure they will if they keep executing like this, but ultimately it's just about. It's about owning. Owning the next platform. Signal screenshotted the stream and said Meta is so rich. They have a VP for just Fashion Partnerships and Michael Miraflor. I don't know if he's in the truth right now. Ava Chen has been at meta since 2015. Is the primary reason why Instagram is Instagram.

[B]

Let's go.

[A]

This should be common knowledge. You do not know Ball if you do not know this, especially if you've ever tweeted about tech and taste. I thought, I mean, I thought the post was funny. Signals post was fun. Obviously he's a friend of the show, but I thought it was funny purely because Instagram is the most influential platform in the world for fashion. They generate billions of dollars a year from fashion brands advertising on the platform. Like, of course they should have somebody. Like.

[B]

And you don't have to be many of them. We have a VP of logistics, a VP of production of. We have a chief intern officer.

[A]

We do.

[B]

And so, you know, you can. Titles are free. I don't know if you need to worry about that.

[A]

Yeah, I would be. I would be bearish if they didn't have somebody that was just focused on building. Because it's on both sides too. It's not just companies, it's. It's the creators. Right?

[B]

Yeah, totally.

[A]

The most. The biggest creators in the world. Many of them are advertising also.

[B]

I mean, think about the fashion partnership they've done. It's like a multi billion dollar deal with luxottica. They've taken a position, a major equity position in the.

[A]

Yeah.

[B]

With the entire strategy. Rocco on.

[A]

We can make.

[B]

He's a billionaire.

[A]

We're going to make face computers. Yeah, but they have to look good otherwise people won't wear them. Should we have somebody that understands the world?

[B]

Yeah. Also, also, just in terms of like the VP title, like, do you want like fashion partner analyst showing up to do a multi billion dollar deal with like the number one sunglasses brand in the world? Like, no, you want to send a vp. You want to send someone with a real Title anyway. Very silly, but fun. Everyone's having fun on the timeline. We'd love to see it.

[A]

We're promoting Michael Miraflor to Vice president of taste.

[B]

Yes, Vice President of Taste. Mark Gurman gave his take. He says he has a strong feeling these will be popular. I wonder if this will cause Apple to speed up its time. Now. I'm not anticipating Apple glasses with displays for a few more years. Their first non display model is likely being announced late 26, early 27. That is slow. That's a lot of time for Meta to. To iterate on this and actually get through. It's going to be a big. It's going to be a big fight. Google's talking about doing display glasses.

[A]

Wait, so G is saying they'll do a pair of glasses that just have a camera in them?

[B]

Yes, Yes. A competitor to Meta Ray bands. Yeah, I know. What do you get? Not that much. You do get slightly tighter integration with Bluetooth. So you will, you'll probably be able to pair them and unpair them a little bit more easily because AirPods are a little bit easier to pair reliably than the Meta Ray Bans. But. But as a competitor, Meta Ray Bans, it's camera, headphones, access to AI. Okay, so you get the Apple Ray Bans, which won't be Ray Bans. They will look like Apple products and they will have maybe a better camera because Apple's fantastic at cameras, maybe better Bluetooth connectivity and reliability there, but you don't get any other features. And then instead of talking to Meta AI, which is probably going to ship something really sick out of MSL soon, like you're dealing with Siri and Apple Intelligence, which we don't know the timeline for the V2 of that. They're kind of moving slow on anthropic partnership or something like that. But even though they have the ChatGPT integration, like I have not become comfortable using the Siri button to reliably query ChatGPT. I still open my phone, open that app every time.

[A]

Yeah.

[B]

And so there was also a rumor that they might partner with Gemini, which actually would be great because that model is fantastic. And so it'll be interesting to see where they, where they pencil out on that. But Meta seems to. I would be surprised if Apple can just come from behind and dominate.

[A]

Yeah, you have to look at Meta's advantages, which is like we own the platforms that you share content on. Yeah, right.

[B]

Yeah. Well, Julius, AI, what analysis do you want to run? Chat with your data, get expert level insights Julius. We love Julius, the AI data analyst that works for you. You can join millions who use Julius to connect their data, ask questions.

[A]

You should have had Raoul show up at Meta Connect and then just hop on the stream.

[B]

Yeah, that'd be great.

[A]

In the background.

[B]

Surprise. What else?

[A]

Aaron slowed off saying, start collecting training data right now. Put these on every manufacturing worker in America. Good. Yeah, probably smart. May as well. You could just do that. You don't need the display either. But again, Amazon is already saying, yeah, we're putting the. They're developing their own pair of glasses to put on their workforce.

[B]

Hopefully it's not a death knell. When, when Google glass pivoted to B2B, it was sort of like going out to pasture because they, they were doing Google Glass for consumer. They thought it was going to be this massive, like consumer adoption moment. There was a ton of hype, didn't go anywhere. And then pretty soon it was like, like Google Glass for enterprise. We'll use it in manufacturing context. That's not what Aaron's saying. But I would be personally worried if Meta started talking about, oh yeah, these are going to be really great enterprise use cases. They're not ready for consumers. Like, no, they need to be ready for the Instagram crap. It has to integrate with Meta platforms in order for it to be successful, in my opinion. Let me tell you about Fall, the generative media platform for developers. The world's best generative image, video and audio models all in one place. Develop and fine tune models with serverless GPUs and on demand clusters.

[A]

We should do a soundboard partnership with Fall. Oh yeah, anyone can.

[B]

Great.

[A]

Can generate TVPN like sound effects.

[B]

Well, we talked about Scott Wu earlier. He's in the timeline showing some love to Mark chen over at OpenAI. Mark, he said, so insane. You guys have no idea how hard this is. Mark Chen said we wrapped up this year's competition circuit with a full score on ICPC after achieving sixth in the ioi, a gold medal at the IMO and second at the Oder. Heuristic context.

[A]

I never see you at the heuristic contest. I was at the heuristic contest and didn't know your name.

[B]

No. Yeah, we gotta send Tyler to be our on the ground correspondent at the IMO and the ioi. Nick, I think that'd be great. Do some post game interviews for the contestants and then get them directly routed into the tier one VC firms. They're already getting calls from investors.

[A]

This was probably the biggest news of yesterday, but it went under the Radar. There is a Rolex Oyster that's Domino's Pizza branded.

[B]

And Andrew Reed says he's not a watch guy, but he might get this one. It's a 1970 vintage Rolex Oyster Precision classic men's Domino's Pizza watch. And we have the story behind it. The Domino's Rolex air King in 1997. They've done a.

[A]

Well, this is another one, apparently.

[B]

So. Domino's Pizza founder Tom Monaghan began incentivizing franchisees with Rolex watches when a high earning franchise owner earned the watch off his wrist by hitting a $20,000 sales week. Monaghan wrote in his 1986 biography Pizza Tiger. What a great name for a biography. Send it straight over to David Senra. I wore a Belova with our Domino Domino's logo on its face. A franchisee asked what he had to do to get that watch from me. I told him turn in a $20,000 sales week. He did it. And so he won the watch off of his wrist after that.

[A]

I wonder what the, what do you think the market value of that watch was at the time? Because he might have. Might have been an arbitrage.

[B]

Yeah. Just realizing, hey, well, we're about to find out. After that, Monaghan started rewarding top performers with Seiko watches and later up the stakes by giving away hundreds of $800 Rolexes. So in the 80s, we're talking a couple hundred bucks for these. But that's still a lot of money. Back then. Initially, turning in a $20,000 sales in a week at Domino's would earn a Rolex. However, as Rolex prices increased, so did the challenge. Domino's Cult Domino's continued.

[A]

Would you get it every time? So theoretically you could get one a week, a year?

[B]

I don't know. Yeah, I imagine if you just like pick the right location, set the right prices, have good traffic, like you should be able to put up, you know, fantastic numbers.

[A]

It's very motivating.

[B]

The Domino's in like Times Square has got to do tons and tons of revenue, right? Domino's continued to give out branded Rolexes, but a franchisee eventually needed to achieve $25,000 in sales per week for four consecutive weeks to win the watch. But the Air King and these, apparently there is one available on bezel go to get bezel.com. your Bezel Concierge is available now to source you any watch on the planet. It you can ask them for a.

[A]

Domino's Pizza meta exec team had some.

[B]

Tasteful absolute hitters yesterday. I clocked Boz had a great watch on Adam. Adam Mosseri had a Nautilus vintage aquanaut. The aquanaut on a black yeah strap. It was great. What do I have to do to.

[A]

Win a TVPN air King?

[B]

Oh, I don't know. We'll have to figure that out. Chat, let us know if you have any ideas for for Tyler.

[A]

We were actually debating whether or not we should do Q4 bonuses and watches and John's just for the record, John's point of view is that you guys would probably just want cash, but it.

[B]

Might be delivered in watches. We'll figure out.

[A]

We'll see. We'll see. The guys are clapping.

[B]

See Rolexes. Okay, maybe Jordy's onto something.

[A]

I think I might be on onto something.

[B]

Well, we have our next guest joining in just a few minutes. But first, like there's big breaking news yesterday. Disney's ABC is pulling Jimmy Kimmel indefinitely after late night. After the late night host's recent remarks about Charlie Kirk. The move comes as ABC affiliate groups told network they would be dropping the host. So this didn't come from top down from Disney. It came from some of the affiliates. Nexstar Media is one of the largest new the nation's largest TV owner said.

[A]

It would talk about OpenAI having a complex corporate structure, but I had no idea.

[B]

Sinclair is also involved. So Sinclair put out a statement. Mike Solana says so this didn't have anything to do with the FCC. There was a lot of debate over what the FCC's role was in this. Who was really putting pressure on there. There was a viral video, a clip of of Kimmel's monologue that went viral on Tuesday after he delivered it Monday night. There was a lot of backlash to that. And then this came up. Jason Calacanis, the host of the all in podcast, said executives at abc, like those at CBS wanted to fire these money losing late night franchises for years. Trump has even given them cover. Trump has given them the COVID they needed. When it was wildly profitable to back these same comedians a decade ago, the networks had no problem letting them mock our wonderful, amazing, tremendous, beautiful, brilliant and astute President Trump wink every single night. And so I, we got a little bit of detail on Colbert's financial situation. I have no idea what the financial situation was like at Kimmel.

[A]

Viewership ratings were dropping them.

[B]

We did hear that.

[A]

I think it probably tracked the basically that the, the mean that the audience on these networks is like retirement age. Right.

[B]

And so these 67 was the median age at CNN and that was like the lowest or something. It does feel like it gets harder to harder, harder and harder to monetize an older audience just because they're not as. They're not as profligate with their money. They're not just going and spending money on all sorts of things. They're not building AI companies, they're not using Turbo Puffer. They're not even in the. They're not even in the ICP for Turbo Puffer. They're not using and full text search built from first principles and object storage. Fast 10x cheaper.

[A]

Loved by Kirsten Scalable linear and our friends over at Readwise too. Some very important breaking news. Chinese Joe Wiesenthal has hit the timeline. Chinese Joe says familiar with American Joe when we first started raising awareness about Chinese Joe Wiesenthal just a few months ago, the legacy media and the corporate establishment laughed in our faces. Something tells me they aren't laughing any longer. Chinese Joe Wiesenthal so I and Geiger.

[B]

Capitalist is very bullish China.

[A]

It is. It is.

[B]

They're catching up to the US much faster than anyone anticipated.

[A]

Every country should have a Joe Weisenthal. They would be lucky to have one.

[B]

Yes, and every, every country needs a profound get your brand mentioned in ChatGPT. Reach millions of consumers who are using AI to discover new products and brands. And we have our first guest of the show from Palantir coming into the studio. Welcome to the stream. How are you doing, Louis? Good to see you.

[D]

Very good to see you guys. Thank you for having me on.

[B]

Thanks so much. Would you mind kicking us off with an introduction on yourself, a little bit of your backstory history at Palantir and we'll go into the news.

[D]

Yeah, sure. So I'm Louis. I run Palantir out here in the UK and Europe. You can tell probably from my accent that I'm British. And I've been at Palantir like almost a decade, so seen a lot of change, a lot of growth out here in the UK and Europe. That journey from a business that was very focused on defense and intel with a tiny bit of corporate, to now a business that's serving every bit of the public sector and every corporate sector you can think of.

[B]

And what's the news today or yesterday?

[D]

Well, the big news is. Well, technically, no, technically it was early UK time this morning. Okay, so you're not out of date.

[B]

There we go.

[D]

We announced a big, big deal with the UK Ministry of Defense. Billion dollars.

[A]

Billion dollar deal billionaires.

[B]

Congratulations.

[D]

Thank you. Thank you, guys. Well, it's the first billion dollar deal that Palantir has done outside the us. So it's a big significant milestone. And alongside that deal we also announced a big investment into the UK. $2 billion over the next five years, the creation of 350 new jobs and our European HQ for defense will be in London.

[B]

What does the $2 billion investment look like? Is that just the investment in the team opex Capex? How are you thinking about that?

[D]

It's all of those. And London is already little known fact. It's already home to about 20% of Palantir's headcount. So it's actually our second largest office globally. So we do a lot more than just support British customers from this office. We do a lot of product development and it serves as like the European and broader EMEA headquarters.

[B]

Yeah.

[A]

When did you realize that billion dollar deals were possible? Was it 10 years ago when you started? Was it five years ago? Was it more recently? It's a big number.

[D]

Yeah. I think, I always believed and I think we're only just getting started. You know, this is, you know, we'll look back in 5 years time I think and, and we'll think, yeah, those were small deals. You know, the power of the software is such, and it's meeting its moment. You know, the significance of this deal is, is it's, you know, we are the operating system for the modern battlefield and we've seen the US make that move. And the significance of the news today is, is the US's closest ally, the UK, making the same move?

[B]

Yeah. What's the mood like in the UK relative to the rest of Europe? We talked to Dr. Karp. Was that just last week or was it the week before?

[A]

The week before.

[B]

About the reception and what's going on in Germany. He of course studied in Germany and he was kind of joking about the lack of entrepreneurial talent and adoption and kind of getting with the program in Germany. But it seems like the UK might be a little bit more forward thinking. Walk me through sort of the view in Europe technology right now.

[D]

I think that's spot on. I think the UK is an outlier. We've got especially here in London, an incredible talent pool, especially in the computer science, software engineering domains. That's why Palantir has so many people here. It's why we do product development here. It's really access to the talent and you've got DeepMind, you've got, you've got a key, key parts of the, of the broader AI supply chain ecosystem are here and I think it Means UK is, is like the only country in the west, broadly defined outside the US that does have that kind of talent pool. And obviously the language helps speaking English, the connection to the US and, you know, we weren't alone, right? Today. Palantir is not the only company to have announced a big investment in the UK alongside President Trump's visit. We saw Microsoft, we saw Nvidia, we saw OpenAI, we saw Google, a whole raft of big tech make big investments.

[B]

How are you thinking about the work that you'll actually do? How concrete is it? How much can you share about what's actually in scope for this contract?

[D]

I can share bits of it. Obviously, a lot of it is sensitive operational details, but a key part of it will be what the UK is calling the digital targeting web. We, Palantir will be a component of that. It'll involve many, many other companies and players. And you could think of that a bit like what the Maven Smart system does for the us. So it's really your targeting infrastructure, how you connect up all your sensors, your, your satellites, your drones, all of your various data feeds with your effectors, you know, the stuff that you're going to use to shoot airplanes, tanks, missiles. And it's that data infrastructure that sits in between that. It's, it's the harness in which you then run all of the sophisticated AI and computer vision algorithms and, and so forth. And a lot of it is inspired and frankly, lessons learned from the war in Ukraine. Ukraine, where the same technology, our platforms have been, as you'll know, deployed by the Ukrainians day in, day out now for nearly three years. And those lessons are being learned and we're seeing the future of warfare play out in real time. And the significance of this is the UK government making a multimillion pound investment in that.

[B]

What was the precursor technology to Maven? I remember when I, when I dug into it, I mean, it was like controversial program here in the United States. And when I looked into it, it seemed like the precursor to using image recognition and computer vision to identify objects and images was thousands of Air Force airmen manually tagging and basically doing something that you would expect, like a data labeling firm to do. And it's not like the government wasn't trying to identify images, objects and images, they just weren't using technology. Is it the same thing over in the uk? What's the lineage of this?

[D]

Yeah, exactly right. And if anything, the problem is more severe because the UK is smaller and has fewer resources than the us so, you know, you're never going to have enough eyeballs to watch all of those feeds. So you need to find some way of automating that and surfacing something of interest to the human when, when that occurs, when that matters. That's how you're going to scale up.

[A]

Does this type of deal make the next five deals with other Western allies easier? Right. I'm assuming that it would be, you know, given it just becomes much more difficult to coordinate if allies are operating on different systems. But I don't know if I have the wrong framework for that.

[D]

That I think, no, I think that's, that's a, that's. I mean obviously I, I'd hope that's a likely scenario, but it's, you know, it's critical. And again, this is a lesson from Ukraine.

[B]

Right?

[D]

The interoperability is everything.

[A]

Yeah.

[D]

The ability to task, pass targets seamlessly between, between units, between allies. That is, that is the way we're going to confront and deter the adversaries that we now have in the West.

[B]

When we talked to Dr. Karp, he mentioned that because of the current structure of Palantir, because of where we are in the technological adoption curve, artificial intelligence, he did not expect headcount to grow significantly. Does this deal change anything for Palantir's UK office? I imagine it's like a whole lot more business. It might justify some hiring. Are you hiring? How do you think about actually supporting?

[A]

350 new hires? But that didn't feel like a huge number in the, I mean it just the efficiency of the platform.

[D]

It will, it will mean we hire, we will be creating jobs, but the output per head is going to grow even more significantly. You know, I think, you know, Ted Mabry, my colleague who runs the U.S. the global commercial business was just tweeting today about, about AIFDEs. So the, the forward deployed engineers we had that have historically been human beings is starting to, to, to replace some of the work they would have done manually in the past with AI. And you can just see a path now where like 90 of what used to be the day to day job can be done by AI. So then suddenly you've got 10 FTEs for every one you used to have. I mean the, the, the exponential here is crazy.

[B]

It's amazing. Well, congratulations. Thanks so much for coming on and staying up late to join the stream.

[D]

Not at all.

[A]

Yeah, Billion dollar deal. We have to hit this button for you.

[B]

Overnight success.

[A]

There we go.

[B]

Thanks so much for coming on the show. We'll talk to you guys.

[A]

Congrats.

[B]

Thank you. Cheers. Linear, Linear is a purpose built tool for planning and building products. Meet the system for modern software development. Streamline issues, projects and product roadmaps. Head over to linear the bond market has completely rejected the Fed's rate cut. We talked about this a little bit yesterday. Yields have ripped higher following an initial drop on the rate cut announcement.

[A]

The rate cuts had opposite prayer circle at this point.

[B]

Yes, mortgage rates will now spike. Mortgage rates were creeping down. This is not very good news. We're still talking about 0.1% of a move over the last day, but not in the right direction. So yeah, not fantastic. But of course that account is from QE Infinity, which is quantitative easing.

[A]

Of course, no bias there. Our post earlier on August 10 Leopold.

[B]

Age like a fine wine. Yep, we went, we were extremely bullish on Leopold and situational awareness back in August 10th. His fund topped $1.5 billion and posted 49% gains just for the first half of 2025. This was from filings. Whenever you're running a fund, you need.

[A]

To remember at that time there were some people saying like long intel what could. Is his fund already blown up?

[B]

Yes, yes, yes. And so SWIX shares a screenshot of what intel has been doing over the past year. They're up 28% and SWIC says, oh my God, he's going to destroy H2 2025. Too good.

[A]

Good year to have some situational awareness.

[B]

Macalise says everything reminds me of him and it's all green. Lines up and to the right. With a variety of stocks up 50%, 100%. He has fully nailed the AI trademark. Will Brown says, you could buy so much diet Dr. Pepper with $2 billion. I don't know if that's like Leopold's favorite drink or something. I don't, I don't get the Diet.

[A]

Pepper reference, but this stat was insane and a little disheartening. Yes, the top 10% of US consumers now account for half of all consumer spending, which is a record high up from about a third in the early 1990s.

[B]

Okay, so creeping up over time.

[A]

Different, different way to understand wealth inequality. And it just goes to show if you're, if you're building consumer products, you probably want to be building for that top 10% that are spending half of all dollars for sure.

[B]

And you got to pay your sales tax on numeral numeral HQ sales tax on autopilot, spend less than five minutes per month on sales tax.

[A]

And plus Numerol just announced a new round today.

[B]

Oh yeah, congratulations.

[A]

$350 million. There's series B earlier this year or Series A earlier this year. And we're gonna have Sam on tomorrow, live from the studio for his first, first ever guest appearance.

[B]

And it'll be in person for that still on Intel. Funny Journey. If you bought $10,000 worth of Intel 25 years ago, it would be worth $10,000 today. Absolutely zero movement over the past 25 years. Basically, it's a store of value. I guess there has been movement.

[A]

Of course, you got to factor in inflation.

[B]

And then it actually sort of ripped from 2010 up to 2021, but then it fell and went back up. But now it's climbing back up. And the big news in intel world is that Nvidia invested $5 billion.

[A]

They marked Trump up.

[B]

They marked up Trump. They marked up the US Taxpayer. Since now we all own intel shares. But this could be the start of something cool. This was what. Who was it? John at asianometry was proposing the idea that Nvidia would SECOND SOURCE the CPUs.

[A]

From intel because video is up 22% today.

[B]

Today. Wow. Is there China News?

[A]

Sorry, sorry, sorry, sorry. Not Nvidia. Intel.

[B]

Intel's up 22%.

[A]

I'm so used to saying, okay, Nvidia.

[B]

No, Nvidia can't be up 22% a day. It's so big. It went down 3% yesterday on the China News.

[A]

Back up 3%.

[B]

It's back up 3%.

[A]

3.7%.

[B]

Wow. Market thinks they're going back into China, baby. That Blackwells are gonna be shipping the B30s. It's happening. Bobby Cosmic is rooting for intel and says he loves.

[A]

Of course we're rooting for Intel. We're all rooting for Intel.

[B]

We're having Pat Gelsinger on this show soon.

[A]

This post is hilarious. Every AI app today, and it's a.

[B]

Box truck with a sprinter van inside. And then inside the sprinter van is a subcompact car. And this is just the nature of recursively calling various API abstraction layers. Probably the agent that calls the underlying.

[A]

LLM laughing at south park delays new episode hours ahead of airtime because creators didn't get it done in time. They say apparently when you do everything at the last minute, sometimes you don't get it done. Do you think this is because they were about to do something that that was gonna get them taken off the airwaves?

[B]

Maybe.

[A]

I think it's high stakes. I think a lot of people that are used to joking around are understanding that, at least in this period of time, jokes can have consequences. Blowback Yep. Cancel culture's back.

[B]

Cancel culture's back. It is remarkable that they, that they ship an entirely new episode that they. It's a, it's a produced animated show, but it's created around the news cycle.

[A]

And so real time.

[B]

I believe when they, when the Obama election happened, they had, I think they prepped two different episodes and then they were able to air the one that was corresponded with the, the correct winner or something like that because they had that episode up like the same day that Obama won, which was crazy. But hats off to them considering their track record. It's impressive. This doesn't happen more often.

[A]

That's what I'm saying. You really got a tinfoil hat moment. Tinfoil hat moment.

[B]

Yeah. I don't know that they've ever missed. Have they ever missed an episode. They must have at certain point and they do and they do go off air for a little bit and I'm sure they have stuff in the backlog, but it's crazy how long they've been at it. This has been what, 20, 30 years on the air. It's, it's one of those shows that I keep forgetting about. And then somebody shares like, oh, they did one about AI. You got to, you got to watch this. They do this about the thing that you really focus on. So you got to do it. So fin AI the number one AI agents for customer service. Number one in performance benchmarks, number one in competitive bake offs. Number one ranking on G2 founder.

[A]

No, I'm only able to find and one other instance where they had a official production delay for a new episode. Really was in 2013.

[B]

Well, Bryce Roberts says don't wait for more resources to have kids. John Woo broke it down, got 9,000 likes almost.

[A]

Yeah, this post went super viral.

[B]

Said my only regret in life is not having kids. Earlier when I was 27, I was going out four nights a week, working 12 hour days, six days a week, waking up at 5am daily for CrossFit kids would have been a breeze. Don't wait for more resources to have kids. Energy is scarcer than money. It's a good take. Thanks for blowing this up, guys. Follow me.

[A]

Yeah, the other, the other thing here is if you have kids younger, it just means you're younger when your kids are fully functional and independent. Right.

[B]

Also, I mean, there's just this idea that you like, oh, you need to like, you actually don't get to stop working when you have kids. Like, you actually do go to work and make more money. And so it's not just like, oh, you need to be retirement age or have like retirement money before you.

[A]

I mean, I think it's entirely a fixation that people have had in their mind forever. This idea of like you buy your first, you get married, you buy your home and then you have kids. And that's so ingrained in the culture that people just don't even care. Consider having kids.

[B]

Yeah, because of the house. Because house prices are so high.

[A]

Yeah. They're not in a position to buy a house. But I think, yeah, kids are nothing more. Nothing to motivate the grind set like a couple of pups.

[B]

Deeply motivating.

[A]

We got John Soundboard finally. He's trigger happy.

[B]

Amit, who we met at Palantir Dev.

[A]

Day, said, number one, Palantir retail soldier.

[B]

Yes. He said, imagine Brigadier told Jensen that if he didn't pump his intel bags, then he wouldn't be able to sell to China. Then Jensen saw the 60 billion they had in cash and was like, screw it. Put 5 billion into intel so we can ship to China.

[A]

Do you think this solves Jensen's China problem?

[B]

I don't know.

[A]

I don't know.

[B]

Because it's not a Trump issue anymore. It's a Beijing issue problem. So, so yeah, I don't know what, I don't know what Trump has left.

[A]

I mean, Trump up 36% on his first real trade size, pretty good. Makes you want to, you, makes him want to get him set up.

[B]

But there's a lot of, there are a lot of other, like, chips on the table that Trump can pull. There's rare earth, there's TikTok, there's all sorts of. What, what did you say?

[A]

Chips on the table?

[B]

Oh, yeah, of course, it was an accidental pun. But there are other places where if Nvidia rises to this top of the stack and becomes one of the most important American geopolitical issues and the mood around exporting chips and chip bands just kind of completely cools. And China has an ask. Well, then Trump can order the deal and say, hey, you gotta let, you gotta unban Nvidia locally. It is funny that we flip from America banning Nvidia selling to China to China, banning Nvidia selling to China. And it's like they both at one point were banning, but at different time horizons. And we're kind of going back and forth. But anyway, I think Jensen will figure something out. This is not the end of that story for sure. There's going to be, there's going to be chips flowing, flowing, flowing, flowing near shares that you can just copy trade Leopold's fund and triple your money in a day. The forums are public. It's crazy. The January 16, 2026, $24 call that Leopold put on is up 200%. So triple.

[A]

Is that good?

[B]

It's fantastic. Nir says absolute kings. I kneel grats on the extra billion.

[A]

Anyway, the Coachella lineup dropped two months early, and over 60% of attendees were on payment plans last year.

[B]

What does that mean that it dropped early? I don't understand.

[A]

Yeah, I think they maybe anticipate it's going to take longer to sell all the tickets.

[B]

Okay.

[A]

It used to be back in my day, in the heyday, it was weekend one was always fully sold out. The tickets would be selling at a pretty significant premium to retail pricing. And so. And I think last year, if I remember correctly, you could just basically buy. You could basically buy a weekend one ticket at below retail.

[B]

I wonder if that's a. I wonder if it's like a dynamic around, like, who is actually playing Coachella? Who's hot? Like, are there as many as you.

[A]

Drop the lineup you have?

[B]

Is the lineup crazy?

[A]

Sabrina Carpenter and headlining day one. Justin Bieber, day two. Okay.

[B]

But it's not Taylor Swift and the Backstreet Boys. They're over at the Sphere. So maybe the Sphere sucking the energy out because the Sphere tickets are selling great and they're. They're super expensive. So maybe people want. Want something new. Maybe Coachella's washed.

[A]

Should we do a live show from the Empire Polo Club this year?

[B]

I don't even know what that is.

[A]

That's where Coachella takes place.

[B]

Plays.

[A]

Oh, the polo field.

[B]

But not during Coachella. Just like at a different time or during Coachella. You want to be on stage next to. You want to be going up against the. I just want to be podcasting next to timeline. Yeah. Next to.

[A]

Interesting. Dario went out on stage and said he does not think we should be selling AI chips to China. Quote. I think it's completely nuts. It's very important that we should defeat China in this technology. Well, you got what you wanted because Beijing decided to make that decision themselves.

[B]

Yeah, Dario. Anyway, Adio, customer Relationship magic. Adio is the AI native CRM that builds scales and grows your company to the next level.

[A]

Also, sponsor team just went absolutely wild in here.

[B]

Max Siegel over at Privy, our latest sponsor says. Wow. OG Privy customer won an Emmy. Shout out. Dylan Abrascato and people pleaser doing some serious damage getting on chain projects represented at the pinnacle of media accomplishment. White Rabbit Just became the first crypto project to win an EMMY.

[A]

Imagine telling 2021 outstanding innovation and emergent emerging media Programming.

[B]

It's cool that they have a new for like a new award. That has to be a new award, right? That wasn't. That award can't have been around for that long. But people pleaser says, imagine telling 2021 crypto twitter that in a few years our producers and eth would get a shout out on stage at the Emmys.

[A]

Pretty remarkable. Let's pull up this video. Yeah, let's check in with Europe. Yeah, let's play the check in with Europe.

[B]

Why Europe?

[A]

Oh, I was onto the next post.

[B]

Oh, okay. I wanted to watch the Emmys video. If we have that one. I want to see. I want to see exactly how they frame this. But we can watch the.

[A]

I don't think that's the right video.

[B]

I think that's just a different humanoid robot.

[A]

Got the wrong guy.

[B]

Let's pull up the people pleaser Max Siegel post. And I'll tell you about Eight Sleep. Eight Sleep.com get a pod five. Five year warranty, 30 hours free trial, free returns, free shipping. It's good because you're home and you get to sleep in your eight sleep tonight. I know.

[A]

Finally.

[B]

It's always hard being away. Anyway. Can we pull up the Emmys video from the time?

[A]

I think it might have just been a screenshot. Am I off there?

[B]

People pleaser.

[A]

Okay, we'll circle back. Let's pull up this video. I put it in the chat of this humanoid.

[B]

This is Calvin, 40, the humanoid developed by the French company Wandercraft. And Chris says Europe is cooked. Lowell. I don't know why they're cooked. They're cooking if they're making robots.

[A]

Let's see.

[B]

Is it bad? I didn't actually see the full video. I hope it's not bad. It doesn't. Okay. It's picking up a tire. This seems fine. This is good. This is good performance. What's not to like? Picks up a tire. It seems useful.

[A]

Headless.

[B]

It is weird that it doesn't have a head. I mean, it's not exactly Pixar level Cute. This is a literal clanker. It's clanking around.

[A]

One of the comments is, was this.

[B]

Trained on folks over 40? Yeah, it does seem very slow.

[A]

I mean, I swear almost every humanoid company to date has just been training on like Biden.

[B]

They haven't been training. They're trying to train on Usain Bolts but, you know, it takes time to integrate all that.

[A]

They want the Best is holding out. He's saying, you can't train, you can't train.

[B]

He's, I'm locking up my training data.

[A]

He's like, you got to pay.

[B]

What do you think, Tyler?

[A]

I mean, the difference between this and the, the unitary demo or the demo on the unitary.

[B]

I don't think it was unitary.

[A]

That did that, where. Yeah, it was fighting and then. Yeah, that was, it's like pretty crazy, the difference.

[B]

Yeah. And someone was saying that that robot was like, was being tele operated. Like there's, there's someone in the background with like a controller controlling it. And Rune had a good point that was like, well, like telling it to move forward is like the easiest part. Like the hard part is like actually having a button to press to like pop up. Yeah.

[A]

You're not manually controlling that motion.

[B]

No, no. It clearly has some incredible, incredible ability. Like respond and understand its position and hop back up. It's pretty good. Well, I don't know, we'll have to check in with Wandercraft, see how they do. I, I, you know, this is better than nothing.

[A]

I don't know, I think they're, It's a good start.

[B]

You could keep going. We have our next guest, Brendan from Merkor, coming in the studio. Brendan, welcome to the stream. How you doing? I'm doing great.

[A]

How are you?

[B]

I'm great. Sorry we couldn't link up on Tuesday. You have some massive news. Introduce yourself, Break it down for us. What's the latest and greatest news?

[A]

Yeah, I'm glad you finally, you know, it's good. You get to the $500 million revenue mark and you decide. All right, I'll do some podcasts. Yes, exactly. Yeah.

[E]

So I'm Brendan, the CEO and co founder of Merkur. Started the company with my best friends from high school when we were 19. Scaled up a little bit to a million dollar revenue run rate, dropped out of college, started working with all of the AI labs and scaled from 1 to 500 million in revenue run rate.

[A]

In 17 months, which has been pretty wild.

[B]

Yeah.

[E]

And super exciting and surreal, as you can imagine. So very excited about all of the progress with the business. And the best is yet to come.

[B]

What was the first task you did? What was the first data you labeled? What was the first project to get from? How did you go from zero to one?

[A]

Basically, yeah. Name every piece of data.

[E]

Well, so I remember the very first. Let's see, there were a few. But the first meeting that really jumped out was when we were hiring Olympiad medalists because everyone was interested in how the models could become superhuman at Olympiad math. And so we turned around 25 Olympiad medalists in 24 hours. And I bring up this example because I wasn't completing the task successfully. I was obviously don't have an Olympiad gold medal in math, but it was, it was incredible to just see like how capable the models are. And this indication of the huge trend underway in the market away from low and medium skilled talent towards this super high skilled sourcing and vetting paradigm ranging from Olympiad math all the way to the thing software engineers and top investment bankers and consultants that help to push the frontier of models.

[B]

What was the, what was the onboarding process for those 25 medalists? Was this just like cold outreach or something? Like, how'd you actually meet these folks?

[E]

Largely through referrals, because we have a big pool of people that we've already hired on the platform and so the largest sourcing channel by far is that people we've previously worked with will send the link to their friends and we'll pay them 250 bucks for a successful referral to help grow the talent network.

[B]

It feels like most of the labs are, I mean, we saw this with OpenAI. Mark Chen was just posting that they basically dominated every hard programming and math competition this year. What are the labs interested in next?

[E]

Yeah, I think the largest transition is, and we'll share more about this in one of our product releases soon, but it's away from academic evals like olympiad math or GPQA for PhD level reasoning, and moving towards all of these professional domains of how do we measure what it means to be a great software engineer to build products? How do we measure what it means to be an investment banker that can do thoughtful financial analysis or a consultant that can help to segment a market? And these end to end evals over all of the professional capabilities I think will be one of the largest, most exciting trends in the market over the next year or two.

[B]

What's the shape of that task then? I mean, it's so vague, it's so much less quantifiable than what your score was on the imo. Although that's incredibly impressive. If someone can do that level of math, go build good software. Feels really unverifiable, feels really broad.

[E]

Exactly. And so that's why you need humans to define the stasis points. It's so much more difficult to measure. And so one way of doing it could be to build a rubric where the model can use the criteria to score the deliverable that's being produced. Imagine you Want the model to be really good at building a web app that looks beautiful. You could have rubric criteria for all of the different elements of said web app or whatever you're ultimately building. Having humans define the success criteria and using those verifiers as part of an RL environment to train models iteratively to learn how to optimize for those criteria is one of the enormous trends that we're seeing across all of the frontier labs.

[A]

How do you sort of plan with the team when you have overwhelming demand for a current product, yet simultaneously need to try to predict future demand in a way that I think normally when companies are doing traditional demand planning, it's very clear of, like, just how many customers can we reach with our current set of products and future products? But in your business, it's not always entirely obvious what the needs are going to look like even a couple years out.

[E]

Totally. I think that the most important thing is always working on the frontier. Frontier and understanding what are the leading indicators of what the entire economy is going to be doing soon and adopting soon and emphasizing that frontier in all of our product development and all of our investments is one of the most important decisions that we've made historically as sort of a framework for resource allocation.

[A]

That makes sense.

[B]

We were just watching a video of a French company, Wandercraft, making a humanoid robot. People were kind of joking about it. I thought it was pretty impressive. I haven't seen any humanoid robots out of France, but can you talk about what the data collection process for humanoid robots looks like now?

[A]

Yeah, specifically. A lot of, you know, we were at Meta Connect yesterday, talking with Zuck and Boz and the team, and a lot of people saw the announcement and they said, okay, a lot more people are going to have cameras on their faces soon. How valuable is this? Should. Should frontline factory workers be, you know, be collecting data today, or is that not necessary?

[E]

Yeah, it's interesting. The key thing for the models to learn is having a clearly defined reward. And so I'll give, like, a couple of examples of that and sort of the role that humans can play. The first one, actually, without humans is that I was at the. This, like, robotics office where they had robots that were folding laundry, and then they would have a vision model, look at the laundry to see if it was folded properly as the reward. So having that stasis point where you can have 100 different model trajectories, see which five trajectories are right, and then reward those trajectories so that the model increases its probability of doing that correctly in the future is very powerful. All the way to another example where models are proposing scientific experiments and then we need humans that we hire as contractors to run those experiments and the physical world report on the results and say how they did. And so I very much believe that models will learn from their experience and interacting with the real economy. But so much of that experience, similar to the way that you or I learn, is curated by humans and the way that, you know, we help models with running the experiment in the physical world and giving feedback, etc.

[A]

You tweeted the letters IPO a while back. What did you mean by that?

[E]

Well, I did, I did comment in parentheses below that.

[A]

Kiddig. I missed that part. I missed that part. Okay. It's all good.

[E]

Well, people, people took it seriously because I remember that I'm sure you got.

[A]

A lot of like frantic calls from bankers being like, brandon, you told me you'd tell me.

[E]

Well, it's funny because last year when we were a seed stage company, I tweeted IPO by end of year and everyone thought I was a little bit crazy because we'd raised our $40 million seed round or sorry, I tweeted, yeah, unicorn by end of year. And we ended up making it happen. And so people thought maybe this time was real. But I was just kidding about the ipo.

[A]

Gotta keep.

[B]

What's the shape of the business now? Obviously there's a huge amount of focus on the these expert networks and these really high skilled, specialized talent getting data from that and working through different problems and all the examples that you gave. Is there still a need from big labs for just the more traditional RLHF? Is this good? Is this bad? Thumbs up, thumbs down? Or has that been completely absorbed by just users of the users or also just the models themselves, like GPT5 or any of the other models, the frontier models, are they able to deliver the thumbs up, thumbs down if you need to do some sort of fine tuning on a specific problem?

[E]

Yeah, it depends on the lab. There's definitely still large investments that are happening in RLHF. However, it seems like it's more efficient to collect those via data flywheels in real world. And where you really need expert human involvement that's incredibly valuable is someone that will think about a problem for five hours and come up with this very structured framework for how to evaluate model success in a way that it's difficult to expect users of products to do in a reliable way.

[B]

Is that a reasonable way to think about a task? A single Task like five hours of.

[E]

That might be one way. But one thing I'm very excited about is that the time horizons of agentic trajectories will go up dramatically. Right. And so I think a lot of people initially think about AI in the context of what can they see on their screen on ChatGPT at any given time, but over time, and maybe using one tool with like online research, but over time, we're going to have the models working on problems that would take a human 30 days to do or 90 days to do that are using 10 different tools, are interacting with various employees in the companies. And we need environments for all of that. We need ways to eval and to measure success, to define the rewards. And that's going to be a very exciting problem space to continue pushing the.

[B]

Frontier of how do you or just humans generally fit into solving the problem of booking a flight or. Or ordering doordash? We've heard about these simulated environments, RL environments, verifiable rewards. Is it mostly designing the environment with the reward, or is there actually a process for someone who's just a fantastic travel agent to create a rubric or just actually do a ton of tasks to generate data?

[E]

Yeah, it could be. So one way you would do it for those kinds of browser use workflows is that you could have a simulated application and then a unit test that measures if the model effectively completed the task, to change the state and booking the flight or whatever the action is. Ultimately, you do need a human expert to help write what is that unit test. But my guess is that computer use will be solved relatively quickly in the next like, or at least in the next, like two or three years. And then there's going to be this much longer tale of sort of the broad space of knowledge, work and everything that we want to do of how do we get the model to build a startup or help prep for a podcast episode or whatever the workflow is.

[B]

Yeah. How do you think about solving problems that take, like, decades? Like, I always go back to, like, you know, health. There's certain things where, you know, the FDA does a lot of work to try and understand, you know, if you're consuming this particular ingredient for 50 years, how does that affect you? It feels like until we can simulate the entire human body and run it at a faster clock rate, that seems like something that you just can't really short circuit. We're already getting to longer and longer rollouts, and that feels like that might be some sort of damping function on how quickly we can compound but are there any promising strategy that you've heard for dealing with problems that just take a long time to actually understand the reward or understand the. Did the pass fail? Yeah.

[E]

The concern I would have with that scenario is it's so difficult to perfectly simulate the human body and how that would play forward. And so my guess is that for a very, very long time models will more so look at empirical analysis, however. Models might survey people that took certain vitamins or whatever drugs when they were a certain age and seen the impact that that's had in their analysis. But it'll be difficult to simulate in that case. There are other cases where it's like a well scoped physics simulation of how well does this ball roll down the plane or whatever we're modeling out that'll be easier to simulate and therefore for models to have an accurate understanding of how things will play out in the real world.

[A]

Jordy, what's. Are you guys naturally 996? Oh yeah, I always get this question, but I feel like you guys are probably more like, like nine, nine seven, like six is almost for the week. You guys are 20, 21. Like what, what else do you have to do besides, besides this?

[E]

Well, it's funny because we have actually never really mandated hours at the company. It was just.

[A]

That's how I figured. But there's like, like if you're ramping revenue from 1 to 500 million and.

[E]

It'S a lot of work.

[A]

Yeah, a little bit of time.

[E]

Exactly. So I think the way it started was our initial core team was working like seven days a week and everyone was in the office like super late, all this stuff. And so we initially gave that rough guidance because we wanted people to have a little bit more balance and going home earlier, et cetera. But obviously as, as the company's developed, I think it's important to be able to hire people that have families and even though they'll work hard on the weekends, they might still be at home. And so there's some of that as well. Still emphasizing a lot of intensity and you know, moving mountains for customers, but at the same time not necessarily being as input oriented and much more focusing on outputs.

[B]

How big is the team now? Like the full time core, not the network.

[E]

Relatively large. We're 250 people now. So bug fast. Yeah, exactly. Across the US and India and then a little bit across Latin America and the UK as well. But yeah, it's been exciting. Certainly a crazy feeling to start having all of these people in our new SF office and New faces that I have to meet.

[A]

So what kind of predictions are you going to make? Any numbers you're throwing out? You said unicorn by end of year last year. But what about going forward? Anything you're willing to, willing to take?

[E]

We could say Decacorn by end of year this year.

[A]

So that one feels like you might, might already had it in the bag.

[B]

But yeah, we'll have to call R for Rock to get the Congratulations. We'll talk to you soon. Good to get you.

[A]

Cheers.

[B]

Up next we have Darren Mowry from Google Cloud coming in. Big Google announcement today, big event over at Google in the global startups at Google Cloud world. Let's bring in Darren. How you doing, Darren? Good to see you.

[F]

Cool spot here in Mountain View. So it's great to be able to spend a few minutes with you.

[B]

Thanks so much for hopping on.

[A]

Looking sharp as well. Thank you for wearing, wearing a suit.

[C]

Thank you.

[F]

I had to brush off the suit. I had to kind of dust off.

[B]

It looks fantastic.

[F]

Somewhat presentable today, guys.

[B]

Yeah, it looks great. Take us through the event. What's going on today, what's been announced, who's there, everything.

[F]

Yeah, that's great. So we're actually in a, in a couple hours going to be kicking off our first, first global AI Builders Summit. And so we're going to have a couple hundred founders and builders here in this room, which I can tell you about if you're interested. A little bit.

[B]

Cool.

[F]

Google History here.

[B]

Yeah, that'd be awesome.

[F]

And then we're going to have a few, actually tens of thousands of startups and builders around the world joining us digitally as well. And so today we're having customers like Lovable Replit, Fireworks and others on stage talking about, you know, the problems they're trying to solve, but how AI is actually helping them complete, you know, completely revamp the industries that they're in. We also have some Google cloud and some DeepMind folks joining us as well to talk about kind of how quickly we've seen the evolution where we are now and we'll look around the few corners into what's coming. So some really great sessions today over the next few hours. So we're, we're excited about that.

[B]

That's great. Tell me about the history of the building. You said that there was something special about it. Yeah.

[F]

So we're actually in this place called Charlie's Cafe, believe it or not. And you guys probably know Google has been known perhaps having good food, good cafeterias for a long time. This was our first cafeteria named after our 57th employee, Charlie Hires. And so, in all seriousness, although it is a little bit of an urban legend, we actually do deeply believe in creating great spaces for people to come together and challenge each other, have good conversation and eat a little bit of good food too. I'll definitely admit that. But we're here in this space. We thought it's a perfect spot to kind of bring everybody together, talk about building and innovation. So it'll definitely be a great few hours.

[A]

Give us a high level on what the last year has looked like in your role, specifically around supporting startups that just have an insatiable demand for inference and all the other infrastructure needed to scale these types of applications.

[F]

No, it's a really good question. You guys should know I've been in cloud computing for a while. I was at another hyperscaler for a long time at the early days of cloud and I thought we were moving fast then until we've entered this AI revolution, right? Which I think the compression and the speed is like nothing I've ever seen before. Over the last 18 months we've definitely felt what I think we would really call like a seismic shift, frankly. The old school way of thinking about cloud through the lens of infrastructure as a service. All of a sudden people talking about all layers of AI from chips and infrastructure, right? Are we going to use Nvidia chips? Hey Google, what's up with this TPU concept that Anthropic is relying on?

[C]

Kind of.

[F]

What does that mean when you get to the model level? The fact that Gemini and what we're releasing with Veo, these are first class citizen models, as I think you guys can see in terms of performance, cost, efficiency. But the fact that we're building and going to continue to innovate on our models, but also partner with folks like Anthropic, folks like Meta to make sure Llama and Sonnet and others are, are also first class products that startups that are building on Google are able to use in a super integrated fashion. And then this concept more recently, right, which is this agentic, this agent AI. This is not a theoretical pursuit. I think it's interesting that when we talk to founders and they give us some feedback, the feedback they're telling us is the agent capability from Google. Cloud is a real capability. It's not a planned release of products, hopefully in the future, right? It's a fully integrated stack where startups have an SDK and an adk. They can build these agents, as I said, using first party and third party models, they can Publish them, distribute them, and we can even help them go to market. Right. So to this, to your point, the last 18 months, breakneck speed. I think we're all learning quite a bit as we go, but I would say the feedback that we're getting from founders and builders especially are a telling us we're on the right track, doing the right things and frankly, they're saying we're go even faster.

[C]

Right.

[F]

Help us do even more, even more quickly. So with Nano Banana, you guys may have seen that was released recently, these are things that are coming out of our DeepMind team and there's going to be further announcements again around agents and new models fairly shortly that are going to keep us very top of mind and very much a part of what startups are building every day.

[B]

Yeah, it's fantastic. Google's always been very, is a great partner to the startup ecosystem. Giving out credits. Do you feel like startups are burning through credits faster now in the AI age? I feel like I remember going through Y Combinator and getting some huge amount of credits and not really knowing what to do with them. Exactly. Yeah. Oh, they usually expire after a year. But I feel like with AI like you can, you can actually accelerate much faster. What's the mood been like from startups that you work with?

[F]

That's a really good point. When you think of our Google Cloud for Startups program, which does have a credit component, an engineering component, a support component, training, etc. We definitely have had a dramatic increase in the amount of startups coming to the platform. So that's first and foremost a really good signal to your point though, which I think definitely shows you understand this space is. Getting into these programs is one thing, even being approved for credits is another thing. But actively consuming the credits and building value, that's what the startups care about and that's what we care about. Right. So what I've seen now over my almost five years at Google Cloud is in the last 18 months, not only do we have more startups than ever in the program, they're consuming the credits extremely quickly and more importantly for us at least. And I think for these startups, they're staying with us.

[B]

Right?

[F]

This concept of I'm going to jump from one platform to another to use credits worked in a commoditized cloud world where you could go from a virtual machine to a virtual machine to a virtual machine. Now that I'm able to come to these startups and do what we talked about a moment ago of gpu, tpu, Gemini Cloudsonnet, Llama agents wrapped in Google cloud. We're finding these startups are using the credits but then they're like, I'm not going anywhere.

[B]

Right.

[F]

And so I think that is the true business case and value proposition behind these credit programs.

[B]

That's great. Anything else, Jordy?

[A]

No. Thank you for joining and have fun out there. Wish, wish we were going to be able to catch some of the talks ourselves, but we'll have to be there next time.

[B]

Yeah, we'll catch up with you soon. Taking the time.

[F]

Yeah, that's all right. Great seeing you guys.

[B]

Have a good day. We'll talk to you soon.

[A]

Cheers, Darren.

[B]

Have a good one. Up next, we have Kayvon from Macroscope coming in the studio. Also the founder of Periscope. We will bring him in in just a minute. In the meantime, let me tell you about public.com investing for those who take it seriously. Multi asset investing industry leading yields are trusted by millions. I like. Thank you. Jordy, what were you about to say?

[A]

Periscope was acquired by Twitter.

[B]

Yes.

[A]

And did that become live streaming? Live streaming?

[B]

Well, we'll get it from Kayvon directly. Let's bring him in to the TVP and Ultradrome from the Restream waiting room. Kayvon, how you doing?

[A]

Welcome to the show.

[C]

Hey guys, great to meet you.

[B]

Clarify Jordi's question. Tell us the story of Periscope. We'll work through to Macroscope, but I'm super interested in some of the, the Silicon Valley lore here. Yeah, just kick us off.

[A]

By the way, huge opportunity for somebody to buy up all the documents. Every scope with scope at the end, just every English word keeps the next company. You're going to be like, ah, I gotta, I gotta double down.

[C]

I might have, I might have already done it. I gotta tell you, actually, funny, funny thing. Nine years ago, almost to the day, nine years ago, we launched a feature called Periscope Producer, which is the same infrastructure that is powering this very broadcast right now.

[B]

Wow.

[C]

And our, our dream when we built Periscope Producer was literally for a show like TVPN to exist. It's sort of like the perfect blend of I production, live streaming content blended with the conversation of what's happening on Twitter. And you know, it took a while for that to come to fruition, but it just like makes me so happy and proud in a very emotional way to see everything you guys have done and to see it happening on Twitter. X that's awesome. So it's awesome. Congrats on all you guys.

[A]

Thank you for building the Bedrock.

[B]

Yeah. I mean, I want to get to Macroscope, but tell me more of the lore. What were the early days of Periscope like? What was the first go to market motion? There's all these famous. Back then, there was the era of Go to South by Southwest. This is the story of a bunch of social apps, including Twitter, where you get the early, kind of create a groundswell of tech, early adopters. What was the first product build? What was the story back then? How'd you launch the product?

[C]

I mean, if you want to go way back, the very first version of Periscope, A, it wasn't called Periscope, it was called Bounty, and B, it wasn't actually live streaming. Our first prototype was essentially. I sort of think of it as like a reverse marketplace for Google Maps. Like, you would drop a pin somewhere in the world and someone would take a photo. You would have some prompt, like, you would put a bounty on, you know, what's happening at the Tokyo Fish Market right now, and someone would respond with a photo. And that, to us was like a really cool way of trying to attempt to build, like, a teleportation device. We didn't know how to actually build teleportations.

[B]

There were so many fascinating, like, social apps, social mobile, local apps at that time. It was a big trend, and there were a whole bunch of different ideas that were experimented with. It was such a fascinating time.

[A]

Well, and it's. Yeah, interestingly enough, like, Instagram has, like, delivered effectively that functionality now. Or Snapchat, where you can teleport and see what's the vibe at this restaurant right now.

[B]

And if you click on the location that you tagged, I can see who else put pictures there if they're public. So, yeah, those features, you were clearly very early.

[C]

Yeah, I think Snapmap actually was probably one of the best manifestations of that early on. The R Stories feature really brought that use case to life for Periscope's journey. When we built that prototype, we realized A, just wasn't really interesting, and B, you have this liquidity problem if you're just dropping pins randomly in the world. And C, it didn't really feel like teleportation because a static photo is by definition old by the time you see it. So that's when we were like, let's flip this and make it press a button, go live. And rather than using static photos, let's try making it live video. And so that was one key thing that we did. And then the second key thing that we did that really made Periscope click was the floating hearts. I don't know if you guys remember, but, like, it was the first social network we had seen where you could have an infinite form of expression. It wasn't just pressing a button to like it. It was sort of an infinite amount of love. And we had this beta of 20 users. It was like our friends, basically, and some family and investors. And when we ship that version of the build that had live video with the floating hearts, it just was so clear to us that there was something here. And one of the early beta users happened to work at Corp Dev at Twitter. She invited Jack and Dick, who was the CEO at the time. And that sort of like, like put us on the radar with Twitter. And so we actually ended up getting acquired before we launched the product. There was no go to Market Motion that got us. It was just like a beta of 30 people and Twitter was like the 31st user.

[B]

Yeah, that team was crazy about the early acquisitions. I mean, vine had launched, but they acquired vine as well. They were very aggressive about picking stuff up early.

[C]

Top tier, picking companies, not top tier. At landing the plane on the integration. That's my tldr.

[B]

Someone called it a clown car, but we're not going to.

[C]

Someone you met with yesterday called it a clown car. That fell into a gold mine.

[B]

Gold mine. Which is a great quote. Anyway, I want to know, like, what do you think about livestream monetization? Like, we've, we have, we have ads running on a ticker. We've, we've, we've. We've brought through a bunch of, like the TV era aesthetics. But then we also do just host red ads. We don't really. That I'm aware of, get a big share of, like, programmatic ads. We don't do. I know Twitch. You can do like, I'm going to an ad break and it will play Programmatic ads. We haven't done that. We've heard a ton of stories about TikTok Shop and the live streaming sales stuff. We've joked that we want to be like that Enterprise SaaS.

[A]

Live commerce for macroscope. I got one license. I got one.

[B]

Yeah, one license here. Pick it up.

[A]

I got five seats left.

[B]

Five seats by now. I got 25 credits over here. I got an SDR.

[C]

I think you guys are an interesting place where you can sort of benefit from all of these models, right? You can do the pre roll, you can do the mid roll. You've got obviously incredible brand placements from some of the best tech companies in the world. And then I think also you have a unique vibe going where you can benefit from a lot of the monetization techniques that have become popularized on, on Twitch and TikTok and even Periscope. Early on we had this thing called Super Hearts which was like people could pay for in app purchases to fly Ferraris off on the screen or whatever. And I think you have enough super fans that watch this show that there's an end user monetization component in addition to what you're able to do with the big brands. I don't think there's many types of content that can benefit from all of those forms of monetization.

[A]

Did you, did you feel like you were. At what point? Like now it feels like Periscope was like extremely early. Even though, even though, like, like I think people anticipated live streaming would be big, but I feel like only in the last few years people at least the tech world is like woken up to how big live streaming is even outside. More so outside of tech. Right.

[B]

And on mobile too. I mean, that was one of the unique insights. There was a host of companies that were really focused on solving. I mean, Flickr existed and then Instagram was huge and then there were a whole bunch of video apps, vine one of them, like YouTube existed, but no one had cracked it on mobile. And it required actual deep insight into the user experience and also the engineering to understand how to get it to work on a phone, which wasn't as powerful as a laptop back then.

[C]

But yeah, yeah, I mean, I think there were a lot of technological problems to making mobile based livestreaming work well at the time. A lot of those problems are just solved now and somewhat commoditized. I mean, there's just like SDKs that let you do this really easily. I think my big takeaway, and you know, call me somewhat jaded on this, but I think what we learned the hard way is that a live focused social network on mobile that's like short form live video isn't tenable. Right. And that's what Periscope was. It was live only as distinct from like Instagram or Facebook Live at the time, that Live was a feature amongst the social network that let you communicate and keep in touch with people asynchronously. And I think it took us longer to build async forms of connection than it did take Instagram and Facebook building all of our features into their existing platforms. And so that was our sort of like hard lesson learned because we had a parallel track where we were trying to make Periscope integrate into Twitter. It was the whole thesis of the integration and it just took us way too long for reasons that we can get into, if you're interested, to make that integration come to life. And so as much as we grew from 0 to 100 million users in a year and a half, it was insane. But just everyone else built all the features. Everyone else built all the features quickly.

[B]

Yeah. What do you think about the lack of. Sorry, last question on Periscope.

[A]

Just I want to talk about macroscopes.

[B]

I know, but lack of screen sharing API on mobile. I felt like during the Clubhouse era that was something that was sort of missing. Was like you go to Twitch, yes, you're watching someone livestream, but a lot of the work is done by the video game that they're playing or the video that they're reacting to and being able to put something else on the screen so that someone doesn't need to just stand there and do an eight hour standup routine with no support for eight hours straight. That helps. And I felt like Apple kind of nerfed that or never really. And maybe it was just a hardware thing, but what was your take on like how important that was? Am I misunderstanding that? And how would it have played out if it was easy to screen share?

[C]

I don't know the state of the current APIs, but I know at the time, and this is probably like 2018, I want to say we did a lot. We actually built a bunch of integrations that let you share your screen, including from mobile. I think just the reality is it's such an edge case relative to what the vast majority of the use case for our product was people talking to people. Right. It was like 98% was that type of broadcasting and 2% was what you guys are doing, which is professional broadcast, whether it's from the NFL or TVPN or anything in between. And so I don't think that would have had a material impact for us as a use case. But I don't know if Apple did indeed nerf those APIs. That's news to me.

[B]

Yeah, I talked to a YC company once that was trying to do mobile Twitch. So you would screen share from the phone. Now people do that with like you take the video feed out of USB C, you route it through a PC. There are huge mobile gaming Twitch streamers, but they basically like are screen recording with a third party device. It's very common, complicated. It's not something they can do on the go. Anyway, sorry, I want to move on. Jordy, what do you Got, I, I.

[A]

I, I want to continue that conversation.

[B]

It's fascinating.

[A]

Limited time. Let, let's, yeah, let's switch gears to Macroscope. What Give, give us the, I don't know, give us a hybrid investor slash customer pitch. I want kind of a bit of both kind of long term vision as well as like why somebody should sign up today.

[C]

Yeah, totally. So I'll start with the like, like the sort of customer focused angle because it's, I think what resonates the most with me. You know, we think of Macroscope as X ray vision for your company. You know, we help you understand what's happening, how's the product changing, how's the code base evolving, what's everyone working on but just answered automatically and answered via the source of truth, which is the code base. For any company that builds software, the source of truth is the code base. If it's not in the code base, it hasn't happened yet. And if it is in the code base base, you know, AI and state of the art LLMs can do a really good job of articulating how things work, who did it, when it happened. And sort of our observation, having worked at many companies, both small startups that we've started and you know, very large companies like Twitter is, it's actually extremely hard to answer these basic questions. Like the classic what did you get done this week? Which is ironically very relevant to Twitter's history, is something that every leader thinks about constantly. Like so much of my job as a head of product at Twitter was literally just understanding what the fuck people were working, working on. And usually it's like the state of the art solution to this problem is meetings, issue management systems, spreadsheet trackers, just bugging engineers and asking them and sort of multiply that out. By an organization that's hundreds if not thousands of engineers, there's a lot of human capital waste that goes into this problem. And so our thesis is that this is silly. Like in a world of LLMs, there's a lot of amazing AI tools built for engineers, not a lot of great AI tools built for leaders. And so that's what Macroscope is trying to do. It's trying to be an understanding engine for your company that simultaneously gives leaders clarity while saving time for engineers. Right? It's sort of this interesting hybrid where we're solving problems that are paper cuts that engineers feel 50 times a day, whether it's automating their PR descriptions, doing AI code review, avoiding them having to go to status updates or write status updates, which there's nothing to engineer hate more than getting distracted from building something and instead reporting status through some game of telephone. And so we are simultaneously helping the leadership team get automated visibility while saving engineers a bunch of time. And we think that we're obviously biased, but there's just no way every company, in five years, every company is going to have a tool like this. Whether it's Macroscope or some other tool. It is just complete insanity to imagine that we are doing this the only old fashioned way.

[A]

So when did you actually start the company? Because you announced round yesterday with Lightspeed, our friend Michael. But imagine and you've been at it for a while.

[C]

Yeah, we started the company in July of 2023. Raised a seed round from our mutual friends at Thrive Capital and Adverb and GV and some amazing angels. Nice. And then. Yeah.

[A]

But to go back at that point in time, at that point the AGI pilled folks were saying AGI by 2025, SaaS is not going to matter. Fast takeoff. So did you never lose faith in enterprise SaaS? Feels like you had conviction that this type of thing was going to be important for a long time.

[C]

I think there's a lot of dramatization that goes into the shifting of the landscape and they make for great headlines and all that. I actually think that as every engineer gets turbocharged by AI and as like coding agents completely revolutionized how software gets written, I think this problem, the problem that Macroscope is solving only becomes more important. Right. Like if Companies are writing 10x more code and humans are writing less of it and humans are reviewing less of it, then it becomes even more challenging to understand what's happening. And ultimately like humans are slow accountable for the outputs of what a company is shipping and building. And so I think having this AI air traffic control system and understanding engine for what's happening with your company becomes even more imperative.

[A]

So the company is built like assuming that agents will get better and better and better and that humans will just stay at this like more and more at this global level of just kind of witnessing, okay, what are all my, what is my whole team doing? What's this player doing? It doesn't really matter if they're a person or an agent.

[C]

Yeah, today it's like 95% of the use cases are what are my humans building assisted with AI. And tomorrow, five years from now it might be 90% of it might be what have all my agents produced. And maybe 10% of that is like what have humans produced. But I think the problem that's Being solved is still fundamentally the same, which is what changed, what impact did it have have and where do we go from here? That's a never ending thing. That is the highest leverage thing. A leader, whether you're an engineering leader or a product leader or a CEO, those questions are always on your mind.

[B]

How do you think about the level of integration to the systems that you want to pull data for? I could imagine a Slack bot that talks to every, effectively acts as a middle manager, literally acts as asking people what did you do this week? And then they write their little status update and that gets rolled up and then that can be queried. I could also imagine something like a screen recorder super integrated into everything the employee is doing. And you can query did my employee send this email? You have full transparency and then a wide swath of trade offs in between for the level of abstraction integration you want into the systems.

[C]

Yeah, well the first thing I'll say is we're not not, we're not big fans of the. There's a surveillance stadium Panopticon. Yeah, we're not a fans of that angle. And like the last thing we want to build is a spy tool. So we don't imagine doing screen reporting or anything like that. But I do think having sort of extensive integrations with the stack that a company uses to build and manage their product is really important. Like today we've started with a few systems. We integrate with GitHub, we integrate with your issue management system. So whether you use Jira Linear, we integrate with Slack and we think those are the critical starting points. But it's just the beginning because the code base can tell you what you did and how it works. How does our billing system work? The code base can answer that question. It can't tell you why you did something. What customer problem were we solving with this feature is not in the code base, but it's probably in a Google Doc or a notion. It might be in a linear ticket. Likewise, who can see this feature is not necessarily in the code base. You might have a launchdarkly feature flag or a statsic flag that tells you, oh, this is available to 1% of users in Japan. But the code base can be the glue that then stitches into all these other systems. And we're building Macroscope in a way that allows it to be a conversational interface to all those questions and answers. Like today we have a Slackbot that lets you ask a question like the one I asked. Have we launched this feature? If so, who can see it? And we imagine over time, building all these other integrations that let you essentially get more insight into of what's happening and how things work.

[A]

How are you kind of setting goals with the team and forecasting? With Periscope, you built a viral consumer app. And today, even in developer tools, there's this intense. A lot of companies are growing ridiculously fast. Pretty unprecedented for B2B products. And so there's this intense pressure to show massive traction and adoption quickly. But Macroscope feels like a pretty complicated product that you're still going to need to be iterating around and figuring out where different types of companies are getting value. So how do you kind of set goals with the team and what does success look like over the next 12 months?

[C]

Yeah, I mean, it's a good question. And it's obviously early days for us. If you really sort of simplify our product down into two components, right now there's really two pieces. We have a code review feature which is relatively speaking, it's a more mature space. We are not the first code review tool, but code review is an enormously important problem for companies to solve. And I think that the heuristics around whether our product is working well for them are much easier to quantify. We released a benchmark as part of our launch yesterday, which sort of is one indicator of what we use to evaluate whether our code review tool is working. Like what percentage of bugs can we detect in a customer's pull request. And so we think about goals very differently for a product area like that, where we can measure ourselves in a very quantifiable way relative to competitors. Then we do the other part of our product, which we sort of refer to as status. We help you understand the status of anything happening in your product development process. That's way more greenfield. Right. Like we're not aware of really any other products like technological solutions to that problem. And so both our roadmap and how we think about goals for that part of the business is a little bit more greenfield. We're just sort of excited to push the envelope on where this goes and how we can solve bigger and bigger problems for customers.

[B]

Talk to me about where the budget is coming to buy Macroscope. It feels like with even zooming out broader to just the AI enabled SaaS market, there's a lot of products that don't neatly fit in with, okay, I'm going to rip out this and replace. It's a lot of adding something on top. We're seeing a lot of like the SaaS apocalypse. The seat based models Going away. But it feels like it would be hard to quantify this with like value based pricing. Like, how are you thinking about justifying a budget internally if you're dealing with a larger customer who's trying to kind of underwrite the value that Macroscope brings relative to the cost?

[C]

Yeah, well, so our buyer is, I would say half the time it's the engineering leader. So this would be like a CTO or head of engineering, and the other half of the time it's the CEO. And I think from a value standpoint, like if you're an engineering leader, you want your team spending as little time, time reviewing code and as little time dealing with production issues as a result of shipping bugs into production as possible. And so the value of even catching one production incident from an AI code review tool, I think is intuitively very easy to understand. We don't see customers asking the question of is a code review tool valuable? What they want to know is why is this tool better than all the competition? So I think that's just going to become, that's going to be more and more true over time, just given what's happening in the AI coding landscape. I think for the other aspect of our product, which is the sort of understanding layer it is, you know, relatively speaking, it's greenfield. Right. There is no product solution they're ripping out with ours. And so what we've seen resonate with our customers is you have an intuitive feel for how much time your team is spending in meetings and dealing with all the bullshit work around the work. And so I think the value proposition really is, is do I buy that this tool is going to help my team focus more on building and less on doing that work around the work and is that worth the price of entry? Which from our standpoint, again, the questions that our customers are asking is not is this valuable? The question is, does it work the way you say it does? Obviously that's where we have to do our job well. But I think anyone who's worked at a big company and has invested in solving this problem the, the old fashioned way knows that it's like the worst part of working at big companies and they would gladly pay any amount of money to solve the problem if it actually works.

[B]

Yeah. How do you think about Generative UI or actually like I could imagine some people want a text result of, they want to chat and ask how are things going? Someone in the chat said this is more of a progress bar. And I could imagine someone wants to see a dashboard, a progress bar. Stats do you think in the future you'll be able to instantiate exactly what the particular manager wants to see. Kind of like a dashboard of what's going on in the organization.

[C]

I think there's lots of interesting vectors here. One is just oftentimes we're describing in words how a product is changing. And there's nothing more powerful than just showing how the product is changing. So whether that's integrating with Figma and showing you the integration mockup that just got shipped, or whether it's actually running the code, like a lot of times think about what an engineer does when they ship a feature. They ship the feature, they go into Slack and they literally record their local branch and a mock up of the product and they post it in Slack and say, hey, I just shipped this thing. It merged into staging. We should just automate that. Right? We should literally automatically run the product and show you the thing that just got shipped and save the engineer the time from having to do all that. So that's like one angle that there's. And the other is sort of what you were saying, which is kind of like in the appropriate time generating dashboards or some other visual manifestation of some status update. I think all of these things are possible. We have to sort of pick our punches in terms of where we start. But yeah, humble beginnings.

[B]

Well, thanks so much for coming on the show.

[A]

It was great catching up with. Come back on again anytime.

[B]

Yeah, I love Silicon Valley lore and I'm very excited to about what you're building. Congratulations.

[C]

Thanks for having me, guys.

[B]

We'll talk to you soon. See you public.com, investing for those that take you seriously. I already told you about Public so I'm going to tell you About Ad Quick.com out of home advertising made easy and measurable.

[A]

You time the double sell button perfectly.

[B]

You did say goodbye to the headaches of out of home advertising. Only Ad Quick combines technology, out of home expertise and data to enable efficient seamless ad buying across the globe. We have our next guest in the Restream waiting room. Makund from Emergent AI. How are you doing?

[G]

Hey, I'm doing good. How are you guys?

[B]

Welcome to the show. How are you doing?

[A]

What's happening?

[G]

Super excited to be here.

[B]

What's going on today?

[G]

We actually launched our product three months back and one of our goals was to be on tvpn.

[B]

No way.

[G]

Yes. I love the show.

[B]

Thanks so much. Break it down for us. What are you building?

[G]

Yeah, so I'm Mukund at Emergent. We are building World's most advanced wipe coding platform for consumers. Consumers for non technical users. They can come in, prompt an idea and get a fully built live app that they can take to production. And we launched few months back. Over a million users have tried the platform. More than a million and a half apps have been built so far. We're going pretty crazily right now.

[B]

How do you think about sub like beachhead markets and sub markets There are platforms that focus on getting iOS app and test flight flight build a game, vibe code a website. Are the people that are signing up saying I'm going to start a business, I'm going to build an app that will be the foundation of some monetary thing or are we in the era of vibe coding apps as memes somewhere in between. Are you still exploring what do you think?

[G]

Yeah. So I mean we are the only platform that supports web app, mobile app and backend integrated in one and we have consumers coming from all parts of life life. We have business owners trying to digitize their business. We have entrepreneurs building their startup on emergent right now a lot of people are building apps that are monetizable right now and they are shipping them. And so it's a crazy spectrum of ideas on the platform right now.

[B]

It's amazing. A million users is a lot. What's the acquisition funnel? How do you actually get people? It's a buzzy space, it's a cool tech but. But I imagine it's hard to get people to go to your specific website. Like what's working?

[G]

Yeah, so I think people really love our product. I think that's what's sort of working really well for us. A lot of the acquisition is word of mouth today for us. The people are referring each other on the platform as they get successful app they refer each other. We also do a bunch of influencer marketing. So we use TikTok Instagram X to promote our brand and we partner with influencers and they're able to sort of create stories which resonates with their audience. That's something that is working really well for us as well.

[B]

That seems to be working really well these days. I feel like there's this interesting flywheel where maybe for the first time we're seeing influencers drive software adoption, software downloads. I mean we've all seen like VPN ads but we're in a new age where people are pushing like what is.

[A]

What, what's good retention in your view? Because obviously a bunch of people are going to come in, create stuff and then. But you know, 12 months from now how many of these people, what does success look like in terms of retaining?

[B]

So now I'm a real business.

[A]

I think the beauty of these things is somebody can come in in 20, 30 minutes, an hour, they can create something very cool. You don't need to retain all of them, you don't even need to retain the majority of them. But how are you thinking and kind of planning around that?

[G]

Yeah, so we have good retention on the platform. With month three, like roughly 40, 40, 50% of users are still on the platform. We have a very strong power user behavior where top 10% of the users are spending a lot more money on the platform who are building serious apps, they're taking them to production and there our attention is north of like 80% right now. So we think it's still early days. But I think what's going to happen is a lot of people are going to come on the platform because we also take care of deployment. We host these apps on our platform, they're going to stay with us on the platform. And what's also happening is as they build more, they want to add more feature. As they get more feedback from, from the users, they come back to build more on the platform. Still sort of early sort of days, but we think that you can build a pretty large business around these power users who are trying to launch their app, launch a new business or a new idea to the world.

[B]

What do you think for business model consumption based? Do you want to get people to spin up an app, subscribe and then you're acting as their hosting provider? Long term a lot of people build websites and then they'll, they're happy with them and they don't actually have a lot of feature requests. We've seen Squarespace and a bunch of other companies, they're templated based but they wind up being great businesses because people are happy to continue managing on WordPress or Squarespace. What business model makes sense in the Vibe coding AI era?

[G]

Yeah, so for us most of our apps are actually full stack web apps, which has backend databases, mobile apps. So what we are seeing is a lot of users coming and adding features to them and building them. I think in a steady state a lot of these users you'll have a power law where top x percent of users are going to deploy big apps, have breakout success on the platform and those are going to be continuing to be on the platform and the business is going to get built around those people.

[A]

Do you expect enterprise vibe coding or consumer prosumer vibe coding to be more Competitive in the long run. And do you think that companies should try to do both or pick a lane?

[G]

I mean we are very focused on consumer. We think these are two separate markets require separate sort of person. For example like a lot of our users they call GitHub. GitHub. Right. So we have to really think through who we are catering to. We have a lot of education baked into the product which tells them what is API like how to sort of look through errors and things like that. So I think these are two different sort of swim lanes and of course there's an intersection of middle where like small teams use us as well. But, but largely like, like we are very focused on consumer market right now.

[B]

Very cool.

[A]

That's refreshing to hear because we've had a number of, of other platforms on the, on the platform and they always say oh yeah we're, we're doing consumer but we're really like you know, a lot of you know basically not, not really admitting that they're two separate markets.

[B]

Yeah, I feel yeah, there's a lot of growth masking like a lack of. Of actually understanding what the product will be when it's mature.

[A]

Yeah. What the long term market looks like.

[B]

Exactly.

[G]

I mean when we started we thought like, I mean relation that we had that like a billion people have ideas in their head like how do we sort of bring that out, how do we sort of help them launch and we think it's going to show a new sort of economy and we just want to be part of that.

[B]

Well, congratulations.

[A]

Thanks for great to have you on.

[B]

Coming on the show. We'll talk to you soon.

[A]

Keep us posted on the progress.

[B]

Have a good rest of your day.

[A]

Cheers.

[B]

Vittorio has a post here. It's happening for the first time in history AI designed a complete genome and it has been proven functional in the lab Many of the most come Samuel King yes, this is going to get a lot of people going. Many of the most complex and useful functions in biology emerge at the scale of whole genomes. Today Samuel King is presenting the pre print generative design of novel bacteriophage with genome language models where they validate the first functional AI generated genome. Fascinating.

[A]

In other news Dylan Field shared a leaderboard of ranking a bunch of different vibe coding tools. Figma make came in second place number one in our hearts but also featuring Lovable at 3.5, Bolt at 5 base 44 at 8 and V0 and Replit of course.

[B]

This is so interesting. I didn't know that you could do rankings here but I Guess they did blinded pairwise matches. So I guess they're human judged as an eval. They sent them out, give it the.

[A]

Same prompt or something like that.

[B]

Yeah. And it's like how much do you. Yeah. So various prompts and then show to results to.

[A]

This is just like how LM arena works.

[B]

It's LM arena for vibe coded websites.

[A]

Yeah.

[B]

Very cool. Well, congrats to Dylan Field over at Figma. Rune has a great post here talking about the anthropic mea culpa Sholto posted. We're sorry and we'll do better. We're working hard on making sure we never miss these kinds of regressions and building trust with you. And Rune says Sholto has a Japanese sense of honor to his customers. I love it.

[A]

Love it. Yeah, the comment, the comments.

[B]

Yeah. You were saying that people were really, really upset about Anthropic and it's interesting.

[A]

Because yeah, it was hard to suss out was it like extreme power users or was average user actually had.

[B]

What was your. Was your take, Tyler?

[A]

I think it was definitely like power users like API.

[B]

So if you like kind of built a business on top of anthropic and then there's regression and you have downtime reliable. Got it.

[A]

Sometimes it's like really slow.

[B]

Sometimes responses are just like. Yeah. And they. And they. They did not say that this was like they ran out of GPU capacity, something like that. Right. This is. This was more in like they. They shipped a new. A new version and it resulted in down time. Right. So it was very much like not on the. Not on the capex side of the business. It was more on the actual like development that they did.

[A]

Yeah, I think so. I mean they made it. They made it very clear like we do not. We will not degrade performance of the model just to serve more people. So I think there might have been some aspect of there being like not like just not enough GPUs.

[B]

Yeah, I mean it's certainly been like demand's been skyrocketing. Brown paper bag in the chat says Claude. Copy subs are mad. Big mad big, big mad. Well, you know what's not down Wander. Find your happy place. Book a wander with inspiring views, hotel, great amenities, dream guides, top tier cleaning and 247 consular service. It's a vacation home, but better. Also in other news, Limewire has acquired the Fyre Festival brand for $245,000. And Liquidity said my phone got a virus from reading this tweet that is. I have no idea what's going on here. We need to do a deep dive on Limewire. We need to get the red string out and figure out if we're like, what is Limewire still doing? What is their business? Why are they acquiring the Fyre Festival brand? What are they gonna do with that? I feel like there's something to be done with the Fyre Festival brand. Like Fyre Festival is a big enough brand. There's been a documentary at this point, people know it that, like, if you were able to buy the brand for 245k, you could potentially do a marketing stunt with it that would generate half a million dollars in value. Maybe. But it does seem like it's got to be really, really inspired because Fyre Festival, the tech conference, the brand is pretty bad. The brand is associated with.

[A]

Yeah, it's one of those things. If you're gonna put all the effort into getting into creating a real world event, that's not embarrassing.

[B]

Yeah.

[A]

Why not just kind of create a new brand that totally. It's not. Not.

[B]

I don't know, maybe. I mean, you could.

[A]

It's attention getting.

[B]

Yeah.

[A]

But yeah, the. I mean, this had. This had been on the market for a while.

[B]

It was like with the brand Fyre Festival. Oh, I had no idea.

[A]

Billy McFarlane, did you.

[B]

Did you go to Fyre Festival, Tyler?

[A]

I did not. But I think the main. Like, whenever I see stuff like this, he was too poor and then he was too rich. But I think you could see some kind of like Enron thing where it's like. Yeah, it's a marketing thing and then it's coin crypto.

[B]

Yep.

[A]

Yeah.

[B]

Oh, Bee co. Careful out there. Watch out for Fyre Festival coin. How is Enron doing?

[A]

The meme coin.

[B]

Yeah, the meme. It was meme coin. It was a publicity stunt. Taylor Lorenz did some crossover video production with them. The team behind it seemed like genuinely great comedian videographers. But then it took a really odd.

[A]

Turn.

[B]

As things always do when they turn into meme coins. It was a funny bit. For a little bit. It was a funny idea leaning into Enron. Certainly fertile ground for jokes. Everyone's familiar with Enron. I saw people buying old Enron merch years before this brand revitalization. You could see them doing something funny with Fyre Festival, or you could honestly see the value of that brand just being. Producing more content about the failure of Fyre Festival, instantiating that. There's been a documentary, but maybe you buy the brand, you get the rights to do more with it and so you can monetize. That way and actually lean into the fact that it has a lot of baggage. It's like a negative. It's a negative association.

[A]

Yeah. You would hope they could have done something more with this iconic brand.

[B]

Yeah. Did you see this comparison of the thickness of recent iPhone cameras next to each other? We were really in the bulky iPhone era. The iPhone 5 completely flat, no bump. The iPhone 6 gets bulking season. The iPhone 6, they called. They said it was a camera bump or something and we didn't know what we were in store for. This is a. Well, now it's called the plateau. That's the official term, the plateau. I don't think Apple Comms wants you to call it a bump.

[A]

I just ordered. I just.

[B]

You ordered it?

[A]

I just ordered.

[B]

What color?

[A]

I just got the silver.

[B]

You got the silver? Silver.

[A]

I think that the orange, if it.

[B]

Was in ramp yellow, it would have been. Done deal.

[A]

Done deal.

[B]

But orange is a lot.

[A]

Yeah. I kind of liked the orange less and less as time went on. Unfortunately, I ordered it late. Now I have to wait till like mid October.

[B]

Oh, they're selling out. So that's bullish for Apple. I think so.

[A]

We like it for the stock.

[B]

Yeah. I mean, that seems good. What about you, Tyler? You itching for one or are you satisfied?

[A]

He just got a new. Yeah, I just got a new phone.

[B]

So you're happy?

[A]

Yeah, I mean I had an 11 before. So this is.

[B]

Oh, yeah. You jumped forward in the future, like seven years.

[A]

Yeah.

[B]

That was great. 17 Pro looks pretty good. Did you see the Latest on the OpenAI brand exploration?

[A]

The latest. This is from February of 2023.

[B]

That's a decade ago in AI terms area. I've never heard of this firm before, but really, really cool work.

[A]

John Palmer for firm.

[B]

Amazing.

[A]

He had a. Has. Has a crypto company.

[B]

Okay.

[A]

Backed by.

[B]

So Aria says Brand Exploration for OpenAI with Sam Altman February 2023 Two logo concepts. A circle and a monogram alongside broader exploration for ChatGPT across brand and product. And this just like threw me back to the 90s. Like, it's just remarkable. It feels like old Microsoft, old Apple, old Mac. I kind of get why they didn't go this direction, but like sort of beautifully nostalgic. And Sam Altman commented on it. He said, fun to look back at this exploration with aria on the OpenAI brand. This work partially inspired the circle that we use and love in our products. The Serif OpenAI font just feels like a boxed piece of software. This feels like throw this logo on it. Sell it at Best Buy. One ChatGPT, please. I'll take version five and I'm good for the next two years. They got a CD key in there. Lock it in. But the. The OAI logo on the. On the right there on the top right is. Is wild. This is. It's a very loud design.

[A]

I think they should re release these as. As like merch for the.

[B]

It'd be great. Yeah, yeah, yeah. It's. It's a little like of. Of like. Yeah. It's just so retro, in my opinion.

[A]

You see this post from Kaz over at Opendoor this morning? We filed an 8k to say that my and Open Doors X accounts would be used to talk with our investors. We've also parted ways with our former external PR agencies. When we want to talk, you will hear from us. Not paid professionals who don't share our mission.

[B]

I didn't realize that you had to actually disclose that in the 8K that you're planning to post should be God given, right? But yeah, Kaz is on a tear. I'm excited to hear more from him and his plan.

[A]

The top comment. You're a God. He says I'm not. There's only one God. I'm just praying very hard that he gives me the power and the perseverance so I can fulfill his will.

[B]

Let's go, Cass.

[A]

Good job rallying retail. Did you see this?

[B]

What else?

[A]

This movie coming down the line.

[B]

I haven't seen the movie. I saw news. Jackson Dahl said. Ladies and gentlemen, we have what seems to be an absolute banger on our hands. The movie is called One Battle After Another. It stars Leonardo DiCaprio. It's in theater team movie night 26. That's what I was thinking. It's in IMAX.

[A]

Get the tuxes ready, boys.

[B]

Task for the team, guys. Figure out when we can all go see this movie together in imax. Get the tickets today and get us.

[A]

Without further ado, we have our next.

[B]

We have our next guest in the Restream waiting room.

[A]

Got carried away. Sorry to keep you waiting, Noah.

[B]

Welcome to the stream, Noah. How are you doing? We got lost in the timeline.

[C]

Good.

[B]

Are you going to the Google event today? Break it down for us.

[C]

Oh, not right now. I got busy with work. But I'll be at a dinner tonight.

[B]

Oh, fantastic. Fantastic. Too.

[A]

Locked in.

[B]

Locked in. Well, what are you locked in on? What are you building?

[C]

So it's often we're building computer use agents. So we're training foundation models on how to use a computer like a human to really automate any type of work.

[B]

What's the secret sauce? How do you differentiate? It's a complicated industry.

[A]

You train the model and then you say hit the keys in the right order to make me $100 million. Don't make mistakes.

[B]

Don't make mistakes.

[C]

Yeah, exactly. We don't allow it to make mistakes.

[B]

That's the secret.

[A]

There's big consequences.

[B]

But I mean right now is the barrier to computer use just scale? Is it algorithms, is it data? Like what are the key inputs to getting good results?

[C]

It's really a mix. From what we've seen, a lot of these things kind of combined but a big part of it is actually the data. There's not a lot of really good data to use.

[B]

Where do you get more data? Who are you going to call?

[A]

Well, I think a lot of it.

[C]

Can be synthetically generated. We worked on these pipelines back in April for our first model release where pretty much our entire data set was just synthetically generated. And then I think obviously you have things like you can label your own data, you can collect it or you can get it from products. So you need to use a combination of everything.

[B]

Computer use is so broad. I mean it can mean everything from like ordering doordash to playing a video game. What's the low hanging fruit like, what is the next step that feels solvable in the 12 to 18 month time horizon?

[C]

Yeah, I think the first few tasks that you really need to solve are these monotonous type of tasks which are like, like pretty easy for a human to do. Like cleaning up your email inbox to like scheduling your calendar.

[B]

Sure.

[C]

To finding all of your receipts in your email. Like things that are very low level which like cognitively it's not like super advanced.

[B]

Why do you need a, why do you need a computer usage for that? I feel like email calendar. These products have existed for decades. They have APIs like they can be interacted with via JSON.

[C]

Yeah, there's actually a lot of like software out there which like either has really bad APIs or things or different types of products where you need to use computer use to really interact with it efficiently. Usually because they might just have broken APIs straight up.

[B]

So do you expect in the future people will be like oauthing into their email on a virtual machine and then letting you hang on to the cookie or the login in, in in some VM for like a long period of time? Because it feels like Apple's not going to let an AI agent run on my app and that's how I use email mostly.

[C]

You know I think like, I think what we're going to see is like we're going to see a mix between like the current LLM paradigm where it's like you use things like structured outputs, you use APIs together with computer use. And in the future I think models are going to jump between both and they're going to do really efficiently. So it will just kind of depend on what the input is.

[B]

How do you think about your place in the stack? Do you want to partner with Google? I know you're talking to them. Is the goal to build applications on top or stay as this like point solution, work with foundation model companies? Like how do you see your customers developing over time?

[C]

The way I view it is that computer use is still very new. So there hasn't been any product that has really taken off in the space. Like there was ChatGPT operator, there was cloud computer use, but none of these have really taken off like immensely like just normal chatgpt and, and I think initially it's going to just be that you provide an API to a very good computer use model which you sell to enterprises, you sell to startups that are working on in different industries really across with different customers and different vendors. And then eventually what we're looking at is if this can somehow transition into a more consumer facing product as well.

[B]

Well, it sounds like the dinner tonight will be a steak dinner, a sales dinner. Hopefully you can get some customers. Thank you for stopping by.

[A]

Yeah, thanks for watching.

[B]

We'll let you get back to your busy day. We'll talk to you soon.

[A]

Cheers.

[B]

Have a good one. Did you see the Arizona iced tea account posted legendary link up Arizona and the Costco CEO and then it's just inflation. What? Because Arizona is always 99 cents and then the Costco hot dog is always 99 cents. Look at these two. The founder of Arizona is still cooking too. And the Costco CEO. They're just boys.

[A]

Inflation literally doesn't exist.

[B]

It doesn't. It's fake.

[A]

It's made up.

[B]

It's in the computer. You can just not print a sign that says the hot dog costs more and it will stay the same cost.

[A]

Just hard code the pricing into the register.

[B]

Yeah. Look at this. Costco Don. Don and who? And Rob. Don and Rob. Dream picture. If you know them, introduce us. We want to have them on the show.

[A]

Had you ever seen this picture before? Tracy Alloway.

[B]

This is iconic. I had no idea this existed.

[A]

Financial crisis, crises. Most iconic picture.

[B]

This is a fantastically iconic Picture.

[A]

She like.

[B]

Hammered it up a little bit, I think. A little bit. I mean, it's not like she lost, but the chart.

[A]

Everything's looking red.

[B]

If anything. Crises are pretty good when you're in the news business. But we love to see Tracy in an iconic photo. What a fantastic. What a fantastic insight with the Dell computer. Rocking the Dell.

[A]

She was in the trenches.

[B]

Staplers. And it's unclear what she's looking at. Some sort of Bloomberg terminal. But it's just all red. But I have no idea. It doesn't look like a stock chart that's red. It just looks like a lot of red cells in a spreadsheet or something. I have no idea. We'll have to ask her what she was actually looking at and how real this was. I mean, it was a stressful time for everyone. Even if you're in. Even if you're in media and you have more to report on as the financial crisis is unfolding. Like, I remember reading the Wall Street Journal every day during the global financial crisis trying to understand what was going on. And like, there was no lack of news. There was tons of interesting things happening as people understood what was going on at Bear Stearns, what was going on at Lehman Brothers. These are storied institutions that are collapsing. You want to hear about what were the decisions made by the board members who was involved? Like, what was the plan for the bailout? What's the government? Government's response. But it's still stressful no matter what job you're in. But what an iconic picture. What do we have next? Ryan Peterson is in Arena Mag. You got to go. Subscribe to Arena.

[A]

I saw this. I thought I was looking at the COVID of gq. It looks fantastic looking at the COVID.

[B]

Max Meyer stepped into write. Ryan's Worlds Flexport CEO Ryan Peterson on the craziest year for global trip. With trade chaos and the rush for companies to implement AI, there are few executives in higher demand than Ryan Peterson. Flexport builds technology for logistics freight forward. He's been on the show a bunch. The Flexport office is full of curios from the worlds, from the world of logistics. I love a curio. We have a lot of curios in our museum of business.

[A]

We do.

[B]

The hallways are decorated with posters that Ryan Peterson himself generated by ChatGPT. On the engineering floor, we got a cardboard model of the Ever Given that you remember the Ever Given story.

[A]

Back to your point on Relics, Dylan was saying that a friend of his, the only Zuck signature signed object that he's Aware of that. Traded hands traded at 100k.

[B]

Oh yeah.

[A]

So there was a Zuck signature.

[B]

Yes.

[A]

Hands went for about 100k which would put the game hit gong probably in the eight.

[B]

Seven figures. Eight figures, I'm thinking.

[A]

But never sell it.

[B]

Yeah.

[A]

Because it's going. It's going in the.

[B]

We did have a plan to engrave on the Gong a contract and not show him that. So when he was signing, he would accidentally be signing a contract to onboard Ranch. That would be the real goal. I don't think that would go over well, Nathan.

[A]

I don't think. I don't think.

[B]

Keep it in the comedy sketches.

[A]

I suppose we'll have have much problem there.

[B]

Yeah.

[A]

Built Rewards built their own TV show short form series called Roomies. They release on TikTok and Instagram. I'm gonna guess that Adam Faze did this.

[B]

Oh yeah.

[A]

Because he does these types of things companies. I'm gonna message him.

[B]

Yeah, I gotta meet him. His name keeps coming up and I want to know more.

[A]

Yeah, we should have. We should actually.

[B]

Yeah, I'd love to have him on the show and meet him. But yeah. Built Rewards founded by Ankur, Jane Cashback or what Credit card points on paying your rent is the pitch. But pretty, pretty remarkable to actually get. Get a. Like a scripted series actually run. Running. It's pretty hard to do. Most people that can. They can do this level of.

[A]

We'll see how quickly he gets back.

[B]

Get him on the show right now. We'll see.

[A]

Derek Thompson says AI is overrated. He says my baseline case is that the AI being built right now is overrated. Soon it will be a disappointment, then it will be a bubble. And by the2030s it will be world changing. Self driving cars are a model for this. In 2015, I heard autonomy was five years away away from taking over the roads. In 2020 they were nowhere. Even in 2022, you could say they were a huge disappointment. Now they're quietly a revolution. Driverless taxi usage in California grew 8x in one year. And Waymo is expanding to other cities.

[B]

Truth Zone. Tyler Cosgrove. What do you think?

[A]

He's not just wrong, he's unpatriotic.

[B]

Whoa.

[A]

Shots fired.

[B]

Where the shots fired. We know how.

[A]

Amateur over here. First time, first time. First time on the decks. Yes, you're. Now you're just hitting random stuff. That's, that's, that's, that's offensive.

[B]

All right, easy. Don't go. Well, I mean it's not that crazy. It does feel like we're in some sort of like the last, the last 1% takes 99% of the time. You know, we got 80% of the value and, but that's not enough. And so the last 20% getting take 10 times as long.

[A]

I know. I mean we, we don't have a Dyson Sphere. How are we getting 80% of the value? We're only getting like a 10,000.

[B]

So what's your timeline for a Dyson Sphere? You think we're gonna have a Dyson sphere in two years?

[A]

Two is a little close.

[B]

He's saying 2030. That's only five years away. I guess. He said the 2030. Yeah. So that's a whole. What's your, what's your Dyson sphere timeline?

[A]

In my lifetime.

[B]

In your lifetime, yeah. Okay.

[A]

Well, yeah.

[B]

Oh, so. So if you lose the bet, you won't be around to make do. You won't be.

[A]

Yeah. In my lifetime.

[B]

In your lifetime? I think so, yeah. I could see, I could see it by 2100 potentially. But it's a lot of work. A lot of lot needs to happen to get, to get the Dyson sphere up there. It's going to be a lot of rockets going to the sun.

[A]

Well, we have Dan. Let's bring in our next show from regular. What's going on?

[B]

How you doing?

[H]

Hey, it's such a pleasure to be here. I've asked Sequoia what to prepare for and they've told me that this should be the most fun, exciting, fast paced interview. So I'm, you know, just like shoot at me.

[B]

Let's keep it quick. Introduction, what do you do?

[H]

We are irregular. We just came out of stealth yesterday. We are the first frontier AI security company out there. Our goal is to be the counterpart to the OpenAI's and anthropic and GDMs of the world. We're already working with all of them to create the security strike of the future.

[B]

Yeah, what does that mean? I mean there's already a ton of security companies out there. I see them when I walk through the airport. They're all thinking about AI. How are you positioned differently?

[H]

Yeah, it's a great question. So the thing that we're actually building is a high fidelity simulator that allows you to put in any model in it and essentially just see how different scenarios in order to attack the model or whether the model can attack other targets. So for example, we were the first in the world to see jailbreaking that AI was doing to another AI. Or alternatively just like seeing how AI can bypass things as Windows Defender in order to just hop from one endpoint to the other. What is unique and different about us is that we're working very closely with the labs out of the assumption that what AI is doing right now is simply not a story. And security is about to have a huge paradigm shift moment, which if you think about it, it makes sense because enterprises are probably going to look very different in the next few five to ten years. So naturally the security stack is also going to look very differently as well. So we are using this high fidelity simulator to find the novel attacks and to build the next generation of defenses a few years in advance.

[B]

Why do labs don't want to do this internally? It feels like something that they have responsibility for. They have tons of. I mean, they get questions on Capitol Hill about this. Like if they outsource it, that seems like a very tricky thing.

[A]

Yeah, but I mean it's not, not entirely outsourcing it. Like they have to care about these things. Same thing that, you know, I think every, every company does. It's like you want to have your own security practices and protocols, but simultaneously have partners that can help you see things in a different way. But what do you think exactly?

[H]

It's a great question. If you think about it. You know, there is a thriving security industry already that is very mature and you know, most companies are using, you know, the great of the security world right now, the Palos, you know, just like the crowds, like etc. Even though they're external to the companies. And the reason is that we're about to encounter what is potentially the greatest security challenge ever, just because we're innovating at such a fast pace and there's so much work to do. So we kind of think about it in terms of the differentiation from the inside to the outside, is that there are some defenses that you would want to put on the models themselves bake into the neural nets, and that's clearly lab territory. But some defenses are going to happen on the AI agent side and some defenses will have to be in the environment. Just because if you believe that we won't be able to do secure by design to AI, that means that some of the defenses will have to be implemented on the enterprise side in the environment. Otherwise you won't have any defenses beyond what the frontier companies are going to bake into the models. And because there's so many different verticals and scenarios and context that you need to put in, there is a lot of effort that needs to be created in order to create defenses across the entirety of the stack and we're working side by side in order to make sure that whatever the labs are not doing, we are going to do in order to create the next powerhouse of security.

[A]

What does a regular look like over time is one way to think about it is like network to detect rogue agents, right? Is that a potential kind of scenario that you guys would be helpful in preventing? Or what is the surface area of the product look like over time?

[H]

Yeah, thanks for the question. So I'd say that indeed one of the scenarios that we are covering already today, we are doing things as understanding and monitoring AI network systems in order to see if they go out of bounds. But our view is that something deeper is going on here and that the entire infrastructure will need to be replaced. I'll give a concrete example around that. So just like anomaly detection, that's a huge part of the security stack right now. Right. But how does it work? You have a baseline and you're seeing whether a model is or just like whatever you're trying to monitor is doing something which is outside of what you would expect as the normal behavior behavior. But if you don't know how an attack is going to look like, you don't have a proper baseline. And as an outcome of that, our view is that the first order thing to do is to create a strong research infrastructure that would allow you to essentially figure out and map the novel attacks that are unique to AI, see what are the gaps in the current security stack and start to fill them in from wherever and just like build a new platform that's going to be the platform to secure the AI agents of the future. So our hope and our ambitions are high. We believe that there is a place to create a huge company that is new around security, very much like we started as part of the transition to the cloud and checkpoint started early on, just like a few decades back when people started to implement networks in enterprises. And usually when infrastructure is changing, you have just like a window of opportunity to create the company that is going to be able to create a platform to secure that infrastructure end to end. And that's our goal and that's what we want to do around AI.

[B]

Do you think it's more. Are you more worried about the rogue AI, the AI that just randomly decides independently to try and break out of its environment? Or more bad actors thinking that if they can get an LLM to do something inside of an OpenAI environment or inside of a Google DeepMind environment, that they can extract some sort of value, like who is inciting the attack.

[H]

So ultimately it's both. I think in the near term it's the latter. So it's much more likely that we'll need some human interaction in order to elicit AI capabilities to push them more dangerous scenarios. And I'm much more concerned right now about it's like terror organizations getting access to advanced AI systems that are already, if you look at like the system cards of OpenAI and Anthropic, they put the capabilities around bio and chemical models being able to just actually help in order to produce them at higher risk levels over time. Which makes me personally just concerned about what happens if some bad actors are going to have access. That's also true on the commercial side that the more that we delegate to AI, if malicious actors are going to gain access, there is potentially going to be be a whole new wave of viruses. And I think the near future is AI augmenting attackers and being used as part of just like the attack surface over a longer horizon of time. We need to also make sure how we take care of just like rogue actions that are done by the AI itself.

[B]

Sure. Well, good luck to you. Thank you so much for hopping on the show.

[A]

We will come back on I expect in the next, at least in the, you know, the next two years. Probably this year there's going to be some, some type of event and we're going to think we got to call Dan to break this down but hopefully you prevent it before it ever happens.

[H]

It will be my pleasure both to prevent it but also to come back on the show.

[B]

Thank you so much.

[A]

Let's do it. We'll talk about this in progress. Thank you Dan.

[B]

Bye bye. Jensen Wong is a huge Nano Banana fan. Love to see that. And Sundar Pichai quote posts him and says mine too. It made his day. They're both very happy. Also Joe Gebbia is shouting out breathe Realm.

[A]

Yes. I threw this in here. New air freshener company. The team when we moved into the studio bought a bunch of air fresheners.

[B]

You immediately threw them in the trash.

[A]

Throw those away, they release a bunch of toxic chemicals into air that you then breathe that then go throughout your body. Sarah, my wife actually invested invested in this company years ago. So it took a while to get out to launch.

[B]

But cool to see the new standard of air care. Go check it out. Saffron citrus and Verbena Santal.

[A]

Sounds delightful. Well, next up we have Ben from Braille coming in the studio working on stablecoin infrastructure.

[B]

Welcome to the stream. Ben, how you doing?

[A]

What's Happening.

[B]

I'm doing good. Good to see you guys.

[I]

Thanks for having me.

[A]

Great to have you kick us off with an introduction to see you again. Actually, I think the last time we spoke was probably 2022. Feels like a decade ago.

[I]

Yeah, I think I might have been trying to shill you on doing something with stablecoins. And we were trying to get started, to be honest. It also takes a minute if, you know.

[A]

Yeah, yeah. Catch us up to. I mean, since it's your first time on the show, quick history on yourself and then we'll get into braille and everything you've been working on.

[I]

Yeah, cool. Well, hey, guys, I've been building fintech companies for, I think, longer than fintech's been a word. I worked on one for about 10, 12 years. Took a couple of years off, kind of went for a long walk in the woods, and then kind of started trying to think about what's next. And when we were workshopping ideas, it became pretty obvious that, you know, like, blockchains were going to surpass traditional databases in terms of, like, speed and cost, which is great for financial transactions. And stablecoins were the obvious way to fill the space, but they were just super expensive to actually create. And so when we started, it was kind of like the litmus test or the baseline was like 100 million bucks in two years to create one of these things. It took us two and a half years to do it, but we got it down to a dollar and a million minute where any business or anyone that wants to go launch a stablecoin can go launch it. And basically the reason people love these things is because it reduces cost and makes revenue.

[A]

Okay, first question, why? Why do we need infinity stablecoins?

[I]

Sure.

[A]

You have a good answer.

[I]

I mean, it's why do we need anything? It's like there are lots of different types of T shirts in the world. Why do we need so many different types of T shirts? People like to customize things. And I think that we now live in a world where customizing your own type of money is possible. Some group of people are going to do it because it's just fun. Other people are going to do it because it's a good business decision to reduce costs. Other will do it because it's a good business decision and they're going to make a bunch of revenue. And so generally speaking, the reason people, I think are going to create more of these things once the beer comes down to actually create more is just that they're fun, they reduce costs and they make Money.

[A]

What is the actual mechanics? If somebody goes to Braille XYZ today and creates a stablecoin, like what's happening under the hood?

[I]

You know, it looks and feels a lot like using like a traditional fintech product. It's almost like you're just depositing money. If you've ever used PayPal, if you've ever used Venmo, if you've ever used Coinbase, if you have a Circle Mint account account, it's the same for all these tools you just put money in and in our case, you get a custom stablecoin back out and then you can go use that in your business. You can exchange it with any number of other stable coins. You can use it on, I don't know, 10, 12 different blockchains and it's compatible with our assets, Circle assets, Paxos assets. So it's like it just works with all the popular stablecoins.

[A]

And then once it's created, let's say somebody creates a thousand, thousand dollars worth of a new stablecoin. How does swap functionality work when you have these sort of new pairs so.

[I]

It'S all actually built in. So when a new stablecoin gets created and deployed, it's all reverse compatible. So let's say that you go create your own stablecoin, you've got 1,000 bucks sitting there. You can use the APIs to swap it in between 50 other stables. Again, some even that we don't issue at really no cost. And you can swap it at the speed of basically the chain confirmations so there's no slippage. And it's, you know, like we, we think pretty ideal in that way. And then obviously as these programs start to grow out into defi, there's a need to work with customers to set up different liquidity pools and things like that to make sure that they maintain peg, work with them on, on ramps and off ramps or building into fintech apps and all that good stuff stuff. But, you know, all solvable problems. All these things are like impossible to imagine five years ago and now all the tech is sort of like right there off the shelf to use for people.

[A]

What are the key kind of customers that you're excited about working with today? Kind of. What are the categories?

[I]

We work a lot with blockchain ecosystems. So we just launched LightSpark. We're doing a lot of work right now with Canton, which is like an institutional, privacy focused blockchain. And you know, there are like eight more of these in development. I think we've done another 12. And then there's, there's kind of like a fast follow once the chains are implemented to what are the use cases on the chain for us a lot of that is like payments. People love these things because reduces costs, increase revenue. It's like a revenue source the neighborhood had access to. In a pre stablecoin world there are embedded finance applications which is just like building on blockchain infrastructure instead of kind of the last version of things. And then there are all these other kinds of trailing use cases. But right now we see a ton in the blockchain ecosystems, a lot in payments and a lot in embedded finance financial institutions as well. But let's be honest, those are a little bit more hypothetical.

[A]

I think at the moment you have.

[B]

Status of those state based stablecoins and.

[A]

You mean like US states?

[B]

Yeah, yeah. Wasn't it Montana that launched one and it seemed like, well America already has this stablecoin USD. I was kind of confused.

[A]

Wyoming I think.

[B]

Wyoming maybe.

[A]

Yeah, you got it.

[I]

It's, it's, I think it's frnt in Wyoming. And you know it's even like once you can launch these things, states want to launch them themselves, banks want to launch them themselves, fintech companies wants to want, want to launch them. And the rationale for it is always the same like reduce costs, make money, you know and maybe the fun side is customization. You know developers like to customize and so I think that's why we really believe like there's just going to be a number of these things. And one of the challenges is just making it interoperable between the deployments and then making it easier for developers to build it into their app. And you know, our sort of like value add is we just take care of the regulation and we just take care of the tech so that you can build whatever product you want to build on top of the new stablecoin.

[A]

Any predictions on stablecoin market caps over the next few years? I mean there's a lot flying around from tradfi trying to just understand the opportunity to people that are more crypto native that are super bullish themselves. But how are you thinking about it?

[I]

I think the number goes up gentlemen. It's like you guys know how big certain name brand fintech apps are. As these name brand fintech apps roll out their own blockchains and their own stablecoins coins, the market cap of crypto generally is going to move. And so suddenly these new corporate chains, they're going to be top 10 top 20 chains the day they're rolled out at least in terms of AUM and stablecoins deployed on that chain. And so in a world where most of the world is still off chain, it's like imagine what happens when the repo market comes on chain. You can't even compare what's possible in terms of where we're at. At least I don't think to compared.

[A]

So yeah, that makes sense.

[B]

Well, thank you so much for hopping on the show. We'll talk.

[A]

Congratulations on the launch. It's great to see.

[B]

Have a good day.

[A]

Good to see you Ben.

[B]

Thanks guys. Good to see you Bobby. Cosmic in the chat has a point that I think I agree with all the. All these different coins remind me of pre1863 currency in the US before the National Banking act of 1863. Banknotes were issued by thousands, thousands of different state chartered banks which often had weak oversight and issued notes that could lose value or be difficult to exchange outside their local areas. And I do wonder if there's some sort of like, you know, network effect. I mean it's like everyone spins up their own stablecoin and then you need interaction between all of them. So then like someone's trying to take an extra cut at some point and maybe like it all trades through and everyone gets lower cost. But if there's one standard for like interchain exchange, then they could take a, then they could take a cut. It is odd that we're in this like explosion of stablecoins at this point. But everyone's sick of paying high transaction fees, I suppose.

[A]

Yeah. I think the, you know, my immediate thought is I can understand why every institution and company wants a stablecoin. If you're a fintech company and you're moving a lot of money, I can understand that.

[B]

Yeah. I mean at the same time it's.

[A]

Like there's a lot of different types of companies where of course they would want a stable coin but are they providing value to the users? Right.

[B]

Yeah. The promise of many stablecoin projects though was like hey, use ours. It's low fees. So it's like is that the arbitrage that you go even lower fees, fees below because it's not 3%.

[A]

Right? Yeah.

[B]

That was the original pitch for Bitcoin was like it should cost nothing to. It's electronic money, it costs nothing to move.

[A]

But they're definitely going lower. Braille is going lower in the stack.

[B]

Right.

[A]

Circle was like, here's we're going to issue the stablecoin and we're going to give you infrastructure to leverage them and then this is going to a layer deeper and just saying we'll just make you the stablecoin itself.

[B]

In other breaking news, Clulee mentioned us in their blog on going viral and shared some stats about TVPN posting a lot of clips with views ranging from 5k to as high as 500,000. There's a reason for this. Some of the content does not deserve to go viral. Roy Lee is stressing the idea of that you cannot inherently make an undeserving tweet go viral. Viral sense gets you from 1 to 100, not from 0 to 1. He's stressing the importance of being able to identify viral concepts. Obviously they put a ton of work into the content that they post, but the interesting takeaway here is what are the benefits of going viral? There are only 2 top of funnel for your users 2 to get your mission seen by potential hire. Importantly, virality does not equal top of funnel only converting content will get you downloads and you must make sure your viral bets are converting or at least have a chance to be in the future. Which is interesting with Cluli because it's a two step act. They need to go viral and entertain and create something that's like funny or controversial or something that everyone watches. But then they also have to get you to go to the website, download and pay for the product here.

[A]

Where does Clulee stand? Cluly has more than enough consistent usage that we can reliably test every single one of our new features against a pool of users and know where the product is retentive and where it is not. Cluly is post PMF in a few areas, interviews, certain quizzes and homework that require an undetectable AI students that's that's enterprise clients who've spent time building out content custom workflows for but conquering any of these will not end in the grander vision. We have our eyes on the ultimate computer interface for multimodal AI. Same same vision that Zuck has his eyes on.

[B]

Yes with AI mode for the meta.

[A]

Always on live AI. Yeah we need faster Roy says we need faster magic moments and larger tangential consumer markets. To that end we spent the last few months working on making sure the product works for are more general users. There's a magic moment that exists with Cluli but does not exist for all the markets that interest us yet. The truth is it is actually quite hard to build software that feels truly magical to everyone. It takes a lot of time that feels honest, that feels honest. And I don't think anybody would disagree.

[B]

There's an interesting stat in here. He says in fact some of our meme viral videos the most views, 50 million views generated almost zero downloads despite being viral. So conversion if you're using viral marketing, conversion actually matters. There's probably a question about built rewards did that big TikTok campaign. They have 88,000 followers, 1.4 million likes on their roomies series and the headline numbers look really good. This could be extremely high converting it could be extremely low converting it's an open question as to and when you're doing viral marketing, you have to understand that the bottom of the funnel matters just as much as the actual views and top of funnel.

[A]

Totally.

[B]

Any other breaking news you want to cover?

[A]

I don't think so. I think everybody's relaxing after a busy day yesterday.

[B]

Yes. Well, we will see you tomorrow.

[A]

I can't wait to get back on the mic.

[B]

Fantastic day. We'll see you on Friday.

[A]

Thank you, folks.

[B]

Have a good rest of your day.

[A]

Great to see all your names. We'll see you tomorrow.

[B]

Goodbye.

[A]

Bye.