Mapping Neo Labs, Unlocking LLM Growth, Evan Spiegel Live in the Ultradome | Blake Dodge, Freddie deBoer, Sohail Prasad, Travis Brashears

You're watching TVPN. Jordy's juggling. It's Wednesday, February 18, 2026. We are live from the temple of technology, the fortress of finance, the capital of capital. Let me tell you about ramp.com baby times money save both easiest corporate cards, bill pay, accounting, a whole lot more all in one place. We have a great show for you today, folks. Specifically, Tyler Cosgrove has been on a little bit of a tear with the market maps. He dropped the market, the final market. We don't need any more market because Tyler made a market map that has every company on it. Let's pull up his latest market map. It looks like the.

0:00

There was some VC associate out there that was making a market map and was just devastated.

0:41

All the companies I was going to put on the market map are now on this market map, which is in the timeline, by the way, and it's very blue. And you did select Google. Can you walk us through how you built this particular market map of everything, every company on it? It's every company that has a Wikipedia article, correct?

0:48

Correct. Yeah. So the one we're showing. That's the wrong one. That's for later. So basically I, over winter break, actually, I was interested in this thing where like. Okay, on Wikipedia there's like all sorts of like Wikipedia, I think, is like a very underrated data source. And there's like all sorts of cool things I think you can do.

1:07

Right, you mean Grokopedia. Right.

1:23

Well, so Grokopedia is a little different because it's like generated on the fly. Right. But basically, whatever. What I ended up doing is I took every Wikipedia article. There's like seven. Seven and a half million English ones. And I ran them through an embedding model. It was Quen 3 embedding 4B, I think.

1:27

You speak Chinese?

1:45

Yeah.

1:46

Wo shuang Jung woah.

1:47

He's got it. Okay.

1:49

But I got into betting for every single article, right? So it's like basically every article has a vector. It's like 2500.

1:53

You did this a while ago, right? The whole Wikipedia embedding, or did you re. Embed.

2:00

This was like a month ago.

2:03

Yeah, I remember.

2:06

So then basically I took all the articles. I found all the ones that are about companies, enterprises. Right. Which is basically you can find some direction in the embedding space that's like corresponds to how much company ness. Something has.

2:07

Right.

2:19

So you just find all the ones.

2:19

At the end, really.

2:20

Oh, you don't filter by like Wikipedia's categorization of.

2:21

So I use that, but that's not inclusive of every single company. So it's like a little bit blurry because some things are like, well, is it a company? Is it not?

2:26

Yeah, I noticed some like railroads on here that looked like maybe they're companies, but they're like state owned and where does that.

2:33

It's kind of a blurry thing. So you can't just use just what Wikipedia says, but you can basically find things that are companies. And then you have a, you have an embedding for every single one. Right. So it's this big vector, super high dimensional space. If you map it down to 2D, you can have this like cool 2D map, which is basically what I did.

2:40

Yeah.

2:55

So you can see there's these big clusters. Right. So it's like in the top left it's all these theater companies or there's space companies.

2:55

I noticed the aviation companies were pretty far away from the train companies. Is that delirious?

3:01

Because you knew there was kind of like.

3:08

Yeah, conflict.

3:10

Rivalry.

3:11

Yeah, rivalry. They need to be. You got to keep those apart or they'll just start fighting.

3:11

Like when you map something down from like, you know, there's like 2000 dimensions down to 2D, it's like very hard to keep. Yeah, like a ton of things.

3:15

And it just randomly looked like the United States.

3:21

Yeah. That has nothing to do with.

3:23

That's so crazy.

3:25

That was totally random because I looked.

3:25

At it, I was like, oh, okay, there's a lot of companies in Florida, a lot of companies in the Northeast.

3:26

Yeah, I didn't even like realize. I was like, oh, it kind of looks like.

3:30

And then I was like, what is this? What is this enclave in Canada? Why does that. Is that Alaska or something? But in fact it has nothing to do with the United States. It just happens to look like the United States.

3:32

Yeah, but this. So it's like actually interactive so you can like look up a company and you can find where it is and stuff.

3:41

Tylercosgrove.com wikipediamap HTML wow. Really a wordsmith with the URLs there. Tyler couldn't use a TLD list domain. There are some fun ones in here anyway. That's a fun project. All the links take you to Wikipedia. Go check it out. And market maps are basically done. But a lot of the Neolabs are not on this market map. Quickly, let me tell you about Restream 1 livestream. 30 plus destinations. If you want to multi stream, go to restream.com and let's click over to Tyler's market Map of the neolabs. Because we've been tracking the neolab boom. We've had a lot of these founders on the show. We came out of the world where we were like, okay, there's DeepMind, there's Google, there's OpenAI. Now we got anthropic, there's thinking machines, and there's a couple different companies. But the neolabs have exploded. They have a term that's been coined. Sarah Guo was actually, I think, the first person that came on the show and sort of broke it down for us around the Christmas episode. But since then, the neolab, like, taxonomy has evolved, and so we needed to build a market map. So, Tyler, take us through what's going on in the world of neolabs these days.

3:45

Yeah, so neolab is kind of this interesting term. Like, it's very broad. People say, like, neolab, it's not very clear what they mean because there's like, broadly. I think it generally.

5:01

And this will make it clearer.

5:10

Yes. I think after this, it'll be pretty obvious, like, what you should be looking at, how to think about these different companies.

5:12

Yeah. I don't want to be more confused at the end of this. Yeah, that would be a disaster if that happened.

5:17

Yeah. So that's not going to happen.

5:21

This is going to be easy. Okay, got it, got it, got it. Cool.

5:23

Okay, so let's just start. Okay, so you have neolab, right?

5:25

Yes.

5:28

So neo, this prefix. Okay. That's be relative to something.

5:28

Yes.

5:31

So neo is relative to, like, your trad lab. This is your big lab.

5:31

Traditional.

5:35

This is your. Yeah, this is your open.

5:35

I'll give it up for the big labs.

5:37

Yeah. They don't get enough credit today. Building data centers, spiking capex.

5:38

So this is going to be your OpenAI, your DeepMind, your anthropic. That's kind of your big lab. Yeah. Xai.

5:43

Xai kind of fits in there too. Even though it's a newer trad lab, it fits in with the big lab.

5:47

A lot of money, Dario. I think on Torakesh, he was like, yeah, three, maybe four labs. Right. So the Force is probably Xai. Yep. I think you can also kind of throw in Mistral in there.

5:52

Okay.

6:03

Oh, yeah.

6:03

Mistral's a little bit older.

6:04

Yeah. Yeah. I mean, Mistral. There's a bunch of these labs that were basically founded in the, like, two or three years before ChatGPT, and then in the, like, six months after.

6:05

Yeah.

6:13

So I think Xai's in there, Mistral's.

6:13

In there, and these Specifically these, I feel like those trad labs, it's like they did a transformer based pre training run. They have their own base pre trained. Maybe it's not at the frontier, but at least they're playing that game. They're not doing fine tuning. They're not doing something else. So that's sort of like you're in the trad lab world when you're thinking about like a big pre train run. Loosely.

6:15

Yeah. I mean, especially if you're talking about these big pre trains. It's really just these four. No one else is really at that scale.

6:35

Yep.

6:40

But then. Okay, so Mistral kind of brings us down into what I call the sovereign labs.

6:41

Okay.

6:45

So I mean, if you kind of look at this, it's basically just labs that are not in America. But I think also that there actually is some meaning to this. So like Mistral. You've seen Mistral become kind of the leader in European AI, Right. So I think. Was it Sweden? Maybe they're bringing a new data center.

6:46

Yeah, Sweden.

7:02

So they're kind of becoming stuff going.

7:04

On in France too.

7:05

Macron is always talking about Mistral. It's this big leader. Cohere is also kind of. I think it has like a very, you know, Canadian. It's a Canadian company. Yeah.

7:06

Yes. But also has done their own pre trains.

7:13

No ties to the curling team, though.

7:16

Oh, okay, okay, okay.

7:18

Complete no ties. So I don't want them.

7:19

Yeah, yeah. It's important to put some distance between that scandal.

7:22

Yeah. And then you can go down. You can kind of see all your Chinese open source labs and see your Quen Deepseek. Kimi Unitree is also in there, right? Unitree. I think so. As we'll see later. There's also. I have section for like robotics labs.

7:24

Sure.

7:38

But this is very clearly like this is the Chinese.

7:39

Yeah. Take us back in time now what was going on before the trad labs broke out.

7:42

Yeah. So here I have this section. Legacy labs.

7:47

Okay.

7:50

So these are ones that are kind of more entrenched in these big enterprises.

7:50

Yep.

7:54

So you have stuff like Microsoft Research at and T. Bell Labs, Right?

7:55

Oh, Bell Labs. Yeah. I forgot about Bell Labs after. You know why they call it Bell Labs?

8:00

Why do they call it Bell Labs?

8:07

Alexander Graham Bell. Yeah, it was founded by him. Yeah, Bell Labs.

8:08

Okay. But also you have stuff like you have Fair, Facebook, AI research. This was like. I mean, there's so many like OG research papers that came out of fair. Yann LeCun used to be head of before it transitioned to MSL to msl. Okay, so then I think let's move up here around your trad lab. You also have post lab, right?

8:13

Yes.

8:37

P O A S T. Yes.

8:37

These are posters.

8:38

Yeah, these are labs where you get a lot of posters. Right. So Obviously this is OpenAI. You got Rune.

8:39

Yes.

8:44

Anthropic. A lot of, you know, Sholto posters over there. Posters. Prime Intellect.

8:44

They're great posters.

8:49

Yeah, A bunch of anons at Prime Intellect. Doing great stuff over there for sure. And then you kind of get into the proper neolab. Yeah, the proper neoliberal. Okay, so this is also a bit hard to identify because like what is actually the core of a neolab? What are these different kind of offshoots? I think Prime Intellect is kind of the prototypical, like quintessential neolab. When you think of it where you basically have. It's like fairly recent. Yeah, it's still very much research focused.

8:50

Okay.

9:18

Like sure, they have enterprise like, you know.

9:19

Yeah.

9:22

Think about different stuff. But at the core of it, you're still like trying to find these new novel approaches. It's research, you're hiring researchers. It's not just like engineers, sales guys, et cetera. So let's.

9:22

Wouldn't Sakana be more of like a sovereign lab?

9:33

Yeah, yeah. I mean, so a lot of these can fit in all different places. Sakana would be. Yeah, Japanese maybe.

9:36

Okay. And you put MSL in here because it's a new project.

9:42

Yeah. This one was also a bit hard. It. It doesn't feel like a trad lab because I mean, maybe it has the scale, but it's just, it's newer, they haven't shipped yet. Neo new lab.

9:46

Right.

9:56

I mean it's so recent.

9:56

Definitionally. Thinking Machines is my classic go to Neo Lab. I feel like it's post OpenAI exodus and sort of OpenAI is nothing without its people. You get the spin outs and you think Thinking Machines and SSI are too of like the first case studies that sort of set the tempo for. Okay, it's possible to do some research outside of the big trad labs. And so that's where you get the neolab boom from. And then a lot of the other companies I feel like are saying, okay, we're gonna do something similar to Thinking Machines or ssi. We're gonna commercialize earlier, late. But we're following in that and we're benchmarking to that. Oh, they raised 2 billion, we're raising 200 million. It's easier. There's a 10% chance that we are at their scale. So you can underwrite it that way.

9:57

Yeah. So thing machines also brings us to what I call the trad SAS lab. SAS lab. You've trad SAS lab. So I think the way I think about this is the Trad SaaS labs are trying to basically use the data that's inside these big enterprises, pull them out with AI. Okay, so this is thing machines. Right. The rumored idea is they're doing RL for enterprise. A bunch of these are doing fairly similar things where it's kind of chatting with your data, using the data that's very valuable to a company, but it's going to be inside the company. You can't really pull it out anyway besides having the AI be like internal. So you have applied compute you poolside doing all kind of similar things in this like enterprise LLM field.

10:42

Yeah.

11:26

And then that brings us to neo SaaS.

11:27

Not full based pre trains for those companies, mostly fine tuning or RL on top of a particular company's use case.

11:29

Yeah. And then I have neo SaaS lab. This is different than trad sas. I think these are different in that they're not really pulling, they're not going enterprise specific. I think that's one way to look at it. Also much more of like startup focused.

11:37

But they're making a product that is sold effectively as SaaS.

11:53

Yes.

11:56

So cursor, cognition, windserve.

11:57

I have ramp labs.

12:00

Ramp labs. These are seat based, sort of consumption based, but it's a product that's vended into a. And the product is what you get and then sort of customizes as you integrate it. But it's not. The conversation doesn't start with a business development relationship.

12:00

Yeah. And of course, I mean these lines are pretty blurry. But then. Ok, let's go down to the post lab.

12:19

Okay.

12:25

Post lab, this is after the lab.

12:26

Yes.

12:28

So that means basically they train the models and then these labs are working on top of those models. So you have meter, you have epoch. These are going to do evals. You have Pangram. They're seeing is the model producing slop?

12:29

Yes.

12:43

Or is it producing text that you're.

12:43

Using in some way? These are purely eval. They don't have necessarily AI products themselves. They don't necessarily sell to big businesses.

12:45

But they could still be training models. Right, Like Pangram is training models that sit on top of labs.

12:54

That's true. So it counts as a lab. Makes sense.

12:58

Okay, what else we got? Maybe that brings us down to the safety labs.

13:00

Yes.

13:03

So these are pretty interesting anthropic kind of fits in this. Right. Because they have a big safety team. They're doing a lot of mechanistic interpretability. You have Goodfire. I think they just raised at like 1.25 billion, and they're just doing mechanistic interpretability.

13:03

Let's go.

13:16

Very interesting. Eleuther AI is similar, kind of.

13:16

I know. Yeah, yeah.

13:19

They're also. A lot of these are also kind of in the open source space.

13:21

Yeah.

13:24

I think stable diffusion came out of Eleuther AI.

13:25

Yeah. This is another label that I think I could have put on, but it's so hard to get everything to, like, work together. But a lot of these are also, like, the core of the company is doing open source. Sure, sure, sure. Right.

13:26

So Prime Intellect was a good example, almost. Of course, OpenAI back in the day. But a lot of these have bled together where OpenAI has an OSS model, but also a lot of consumer and enterprise. Yeah, makes sense.

13:38

Okay, so then in contrast to the SaaS labs.

13:48

Yeah.

13:52

We have the consumer labs.

13:53

Okay. Consumer.

13:54

These are focused on consumers. Right. So you have Eureka Labs. This is Andrej Karpathy's project. Yet. I don't think there's anything been released from it yet.

13:55

Education, though.

14:03

But yeah, education makes sense. Four people. You have humans.

14:04

Oh, it's four. Four people. Not four individuals working there.

14:07

It's four people.

14:10

Yeah, it might be four people. It might be one person. Who knows? He's pretty good.

14:11

Yeah. Humans and. Okay, right. This is the. I think you're gonna phrase. It's like humanity focused.

14:15

You're gonna turn human into sand.

14:22

Human sand.

14:24

Human sand.

14:24

Yeah. We. We got to hang out with the founders at the super bowl, but there. But yeah, focus on creating models that work better alongside people.

14:26

Sure.

14:37

You have a lot of, like, companions, these kind of ideas. Right. You have character AI also.

14:37

Oh, yeah. Do they really own C. AI What a great domain. If that's true, I don't know. We'll have to back to it.

14:42

Anyway, so then that brings us down to the visual labs. Visual labs, Right. So there's a lot of either multimodal.

14:50

Yeah.

14:56

Models. Or they're actually, like, producing video or images. Right.

14:57

We talked to a lot of these founders.

15:00

Yeah.

15:01

I feel like almost all of them have been.

15:01

Yeah. I mean, world labs raising today.

15:03

Yeah.

15:04

Or fundraise announcements today.

15:04

Yeah.

15:06

Midjourney, et cetera. Leads are pretty obvious. You have your NEO Auditory lab.

15:07

Midjourney. Is the sailboat logo.

15:11

Correct?

15:13

It's a good logo.

15:14

Yeah.

15:15

Okay.

15:15

You have meta Reality labs on There too. Oh, okay.

15:16

Yeah, yeah, yeah, yeah. That makes sense. They're visual. Not fully AI yet, but they're getting there.

15:19

Yep. Okay. You have Neo Auditory Lab.

15:24

Okay.

15:26

Right. So this is going to be anything that has to do with vocals or voice or Music.

15:27

Yes, 11 Labs.

15:33

11 Labs.

15:35

Of course. Sponsor of TVPN.

15:35

Thank you, Suno. Right. Making music. Gemini also released a new model.

15:37

Yes. Today, Lyria 3. I didn't even know there was one or two. It's a trilogy already. They just got secret models that they're hiding from us.

15:41

Yeah. So this is very interesting field. And then you have your legacy auditory as opposed to your new auditory. Right. So this is your old ones. This is. Well, John, do you want to talk about nuance?

15:50

Nuance Dragon, Naturally speaking. This is the original box software. You buy it, install it on a Windows computer. You can talk into a microphone and it will write down what you say dictate it. Yeah. Using some AI, Not a large language model at the time, not a transformer based architecture, but became a very large company. I think it's part of Microsoft now or something. I think it's been acquired a few times, but yeah, very, very interesting company. A lot of really solid fruity loops. Yeah, that's. You're in the lab making beats, I guess.

15:58

Makes sense. Okay, so now moving up, I think this is really a very interesting section. So this is Neo Trad lab.

16:29

Yes.

16:34

So I think. What is a Neo Trad lab?

16:35

This is a simple definition, clearly.

16:38

Yeah.

16:40

Does it even need explaining? I think everyone gets it.

16:40

Watch your head, by the way. We're coming really close.

16:44

I want to be on the other.

16:46

Side of the team.

16:47

Okay. So Neo Trad lab. It's a Neo lab.

16:48

Yes.

16:50

But it's trad. So basically the way I think about a lot of these labs is that they're extremely research focused.

16:51

Okay.

16:59

They're also largely. They're focused on like kind of a single idea.

17:00

Yeah.

17:04

So if you think of like OpenAI. Very research focused, obviously. But they're doing a lot of different things.

17:05

Yeah.

17:11

Right.

17:12

So they have consumer and.

17:12

Yeah, they have consumer. But it's even like on the product or on the research side. Right. They're doing their video images.

17:13

Sora images.

17:18

Yeah. But even within like language models, I'm sure they have a continual learning team or all these like weird moonshot things where I think a lot of these Neo Trad labs are basically focused on one single moonshot idea. Okay, so example, flapping airplanes.

17:19

Right.

17:36

They just came on. They're talking about Data efficiency. This is kind of the one kind of moonshot idea. Right. Obviously it's like a very general, broad.

17:36

Bunch of different ways you can tackle it. But they're like, that's the problem that we're going on.

17:44

But it's one specific thing they're working on. And I mean, they talk about, oh, if we figure it out, there'll be some value, but we're not exactly sure how it's going to come out right now.

17:47

And we're not sure how we're going to productize it necessarily. But we have really.

17:57

Yeah. So the idea is if these labs can figure out the core research idea, then the value will appear. So you also heard this out of Ilia with ssi. Not sure how they're going to get revenue, but it'll come if they figure out a breakthrough. Continual learning.

18:01

If they build it. They will come.

18:18

Yes.

18:19

Yeah. A lot of interesting things here so we can look at like, okay, general intuition.

18:19

Yes.

18:25

They're basically doing a lot of multimodal training where they can basically take video game data and try to figure out how to map that onto lms or world models or these types of things. Okay, you have Inception. I believe they're doing dream tech. Wait, okay, I'm thinking of logical intelligence. They're doing like diffusion models. Okay, right. So diffusion but for Lux, but for text.

18:26

Yeah, we've seen a demo from Google on that too.

18:51

Yeah.

18:53

Okay.

18:53

Inception is doing, I think they're doing the energy based models, which is kind of this weird thing. Okay, wait, I have both those companies flipped again. So Yann Lecun is into this.

18:53

It's simple. I mean, I don't know why you're flipping stuff around. This is literally just neolab101. You're doing a basic breakdown.

19:04

The point is that they're doing these kind of weird architectures where like energy based model, it's like kind of different than a normal LLM where you have this normal back prop stuff like this. But the point is that these are all very kind of weird architectures that they're working on. So maybe the big labs have small teams that are working on this stuff. But basically these people go out of the big lab. A lot of them are coming out of the big labs and they're starting.

19:11

These new projects like coming out of a trad lab or a neo lab or a neo or legacy lab. A neo SaaS lab.

19:33

Exactly.

19:41

Okay, got it.

19:42

Yeah.

19:43

Okay, so now let's move up a little bit. Yeah.

19:43

What is Neolab lab?

19:46

Neolab lab. Okay, so this is. Yeah, I like this one. So these are a lot of companies that are focusing on. They're also, like, very research focused, but the point of the research is to build essentially like a researcher. So they're recursive.

19:47

Right, okay, so you have recursive and recursive.

20:02

Yeah, you have actually two that are recursive and recursive. You have Richard Soaker Soter. You have periodic labs where they're a little bit more focused on the hardware. But the whole point is that they have this kind of closed loop where you can basically build a lab within the lab. Right. That's the whole point. Lab, lab, building a lab.

20:06

Got it.

20:26

Unconventional AI. Similar thing.

20:27

I think the product will be a lab. They're in the lab manufacturing business.

20:28

Correct.

20:33

Got it.

20:33

Yes.

20:33

Okay, moving up. We have math lab.

20:34

Yes.

20:36

So these are pretty interesting. Axiom and Harmonic.

20:37

Yes.

20:40

And then you have matlab.

20:40

Yes.

20:41

But these are pretty cool. There's been a lot of good breakthroughs recently. I think there's a bunch of Erdos problems that are being solved, or maybe they're just being proven in some ways, but there's a lot of, like, interesting research coming out of these.

20:42

Harmonic is Vlad Tenev, the founder of Robinhood? Yes, correct.

20:55

Yes, yes.

20:59

Wet labs.

21:01

Yeah, wet labs. Okay, so these are your bio labs.

21:01

Oh, you got LabCorp. Yeah, I'm familiar with LabCorp.

21:05

LabCorp. But there's a lot of biology focused labs. It's actually like, I didn't know about a lot of these, but there's all sorts of interesting research. So isomorphic labs. This was spun out of, I believe, Gemini, or at least Google.

21:07

Yeah, that's right. They're working on longevity and just drug development almost.

21:24

So some of these are very focused on specific forms of drug development. Some of them are just like broader, where they're very focused on longevity stuff.

21:29

Yeah. Cool.

21:38

And then. Yeah, let's go to.

21:40

Yeah. What's going on up.

21:41

Oh, yeah, up top we have Labrador.

21:43

Oh, that's really important if you want to understand labs.

21:46

These, you got your lab, the foundation.

21:49

The white lab, your black lab, your chocolate lab.

21:51

Chocolate lab, yeah. Chocolate labs are important. Yeah, if you want to understand labs broadly.

21:54

Yeah. Okay. Then moving back down, we have the Neo Kinetic lab. Okay, so these are going to be your labs that are more focused on robotics.

21:58

Yes.

22:05

So you have a bunch. You have Project Prometheus. Yes, this is Bezos's lab. It's still kind of in stealth, which is why there's not even a logo for it.

22:05

Yeah.

22:13

You have figure, you have skilled AI.

22:14

Skilled AI is the Luke Metro project. Yes, got it.

22:17

Yes. Physical intelligence Sunday.

22:20

Right.

22:23

These, these are all your kind of NEO connect labs. Right. These are started fairly recently in the past, like maybe four or five years.

22:23

Broadly, the Neo NEO Lab.

22:32

Neo Neo Lab. Right. Okay. So One X is building Neo robots.

22:34

So they're Neo Neo Lab in that sense.

22:38

Yeah.

22:41

And then Legacy Kinetic is the previous.

22:42

Legacy Kinetic is kind of the old gen. Yeah, they're cooking.

22:44

They're cooking. Waymo's cooking.

22:48

Yeah.

22:50

Cruise Boston Dynamics have been a little bit behind Zoox. Also another self driving card.

22:50

There's a bunch in here that I could have really.

22:56

There's another one, stealth, I think that never really hit inflection. Okay.

22:57

Yeah.

23:01

And then you have your mostly vehicle focused.

23:02

You have your dark lab.

23:04

Yes. So this is working with the government.

23:05

Yeah, I have SHIELD AI. I also have darpa.

23:07

DARPA is a lab. Yeah. They invented the Internet, right? Gps.

23:09

Yeah.

23:13

Darpanet.

23:14

Yes.

23:15

That's good. And then simulation lab, I think that Simulation lab, yes.

23:16

So Simile, we just had them on.

23:19

SpaceX you could put up there because aren't they working on this Pentagon?

23:20

Yeah.

23:25

Where's Rocket Lab? Rocket Lab needs to be on there. That's a lab.

23:26

There's a lot of labs.

23:29

There's a lot of labs.

23:30

Yeah. Lab is very broad term.

23:31

Very broad term. Well, at least it's crystal clear now for everyone.

23:34

Yeah. So I think this should be pretty obvious to anyone who's thinking about neolabs. Like how should we be thinking about them now?

23:37

If you've been paying attention, this is all second nature to you.

23:42

Did you add up how much all the companies have raised? It's got to be in the north of 200 billion.

23:46

Yeah, it's a lot. I mean, so I didn't do that, but for a while I was trying.

23:52

To figure out how to do the.

23:55

Evaluations on the map.

23:57

It was too complicated.

23:58

You didn't feel like you could do the math?

24:00

No, we don't know how.

24:02

Well, it's also a lot of them are rumored. It's actually kind of hard to find out because a lot of these are still really in stealth. A lot of these NEO Trad labs, they basically. Because the whole point is that they're doing this research stuff. Yeah. They're not going to like productize early.

24:03

Yeah. And also how much do you put in the DeepMind bucket? That's a huge amount of investment and it's not exactly disclosed. Do you count the tpu? Do you count Google cloud, like different allocations. You can go really deep in the stack to understand the impact of like the broad AI build out. But yeah, I mean if you just total this up, you can really just do xai OpenAI anthropic and get like 90% of the way there and it's probably like 200 billion.

24:16

It's also hard because it's like evolving so fast. Right. So David Silver's lab, who he was used to be at DeepMind.

24:41

That's a good word.

24:49

Yeah, I think that was rumored today.

24:50

Yeah, it's indescribable.

24:53

Yeah. But these things are coming out like every day.

24:55

You put the typos in just to prove that. Human typos. So like Sovereign Lab and then Sovereign Facility Lab, Able Intelligence also has a typo. And so I just wanted to make sure. I wanted to make sure. Yeah, you put the typos in so that it was proof that you made it. Yeah, yeah, I don't want.

24:58

Well, yeah, whatever you build this in doesn't have spell check, I guess. Anyway, fantastic report. Thanks for breaking it down.

25:22

Great stuff.

25:29

I learned a lot and I hope you did too. And let me tell you about a lab, Gemini 3 Pro. It's Google's most intelligent model yet. State of the art reasoning, next level vibe coding and deep multimod understanding. And I'm also going to tell you about Sentry. Sentry shows developers what's broken and helps them fix it fast. That's why 150,000 organizations use it to keep their apps working.

25:29

One show two maps. One show two maps strong start.

25:51

Should we break down five wildly obvious fixes that will explode consumer LLM adoption? They don't want you to know this over at the big labs, but I have some ideas. Basically everyone's been really focused on agentic coding and the SaaS apocalypse and what's happening in the business to business world and the enterprise world. I've just been sort of like thinking back on, you know, basic improvements to the chat apps that I use all the time because there's some really obvious stuff that I think, I think is in the works and I think it's coming. But I wanted to just sort of like get it all down in one place to think about what the next iteration and the next breakout moment when people are like, oh, I'm using them even more. I'm having a better experience. What would that look like? So the first thing is that I realized that I've asked ChatGPT just when was OpenAI founded three different times it's the exact same query. Like it doesn't need to light the GPUs on fire for that question. The answer literally never changes. You can cache the result. And that's what Google does with those knowledge queries, knowledge panels. And there's a whole bunch of different, there's a whole bunch of different ways to deliver results that are sort of pre cached. And so if you just look down when an LLM launches, basically every question has never been asked before, but now there's a lot of people that are just showing up with the exact same question. Give me the history of the Roman Empire, give me the history of this company. And you might not be the first person to ever ask that question. Exactly. But also if you do a little bit of fuzzy, if you do a little bit of fuzzy search over it, you. There's probably like hundreds of thousands of people that have asked the exact same thing. So cache those results, give them to the user instantly. And I think this instantaneous feeling of LLMs, they felt slow for a really long time. They actually got slower. It was always sort of slow. You watch the token stream in, but then once the reasoning models and the thinking models and the deep research and the O3 Pro came out, it was really slow. It was like, close your phone and come back in 20 minutes. That doesn't have to be the end state and I don't think it will be. And I have no better example than the number two on my list, which is cerebras inference. So ChatGPT currently has a model called 5.2 Instant and it is not instant at all. I fired off a prompt to 5.2 instant and I said no reasoning. Tell me the history of LLMs. It took 38 seconds to deliver the full response for all the tokens to stream in. And it does a good job. It shows you images and stuff and it is a cool illustration. But then I went over to Codex Desktop and I fired up GPT 5.3 Codex Spark Low, which is a crazy name which we'll get to, and it responded in under two seconds because from what we know, Spark is incredibly quick, cerebrous and it's very, very fast. And so everyone's obsessed with the fast models in the agent decoding world because you're waiting a half an hour for something to get back to you. You're waiting five minutes for something to get back to you, and you're actually, actually losing your train of thought. But I think that applies in consumer as well. And I think the Interaction of sending a message and then just immediately getting a response before you actually think, oh, well, it's waiting. I'll close the app, I'll check my messages. Oh, I got an Instagram notification. Let me go over there. Instant responses will keep people in the apps longer and user minutes will actually increase once that rolls out. So pretty simple implementation for I think most companies. My big question is, I know Google has a huge advantage with tpu, but I don't know if they have an answer to Cerebras specifically. And Nvidia just brought Grok, which can do, I think some of the same things. So I'm curious to know how every lab solves the fast responses question because that feels like an important piece of the puzzle. It's not the only piece of the puzzle, but it's an important feature and I think we're going to see it rolling out to Consumer LLMs very, very soon. And I do think it'll be an interesting moment for people to both ask a question and just boom, it's as fast as going to Wikipedia and just seeing like, okay, everything's rendered, it's thoughtful, it's what you want. And on the flip side, I think that it could make people a lot more chatty with them, like actually asking follow up questions because you don't feel that cost of like, oh, if I ask you to follow up and tell me more or go a different direction, like, I have to wait, I have to wait, so I might just close the app. Or speaking of GPT 5.3 codec spark low. No more model names. Truly no more model names in consumer AI LLM chat apps ever. Just bury them so deep in the UI that you never see them and people will complain. People will be like, I wanted it to be easier to pick. I like picking between pro and thinking and fast and instant. I know what I want for everything. People complain, but it will all inspire the model routing team to grind harder. And the model routing team has a hard job to do, but they will eventually figure it out and eventually you should be able to just talk to the model. You can already do this in ChatGPT. You can say, hey, think really hard about this question and give me a really thorough answer and it'll switch from instant to thinking. I don't know that you can trigger pro from that. I haven't actually experienced that. I did try and trigger a deep research report. I said, hey, please deep research the Roman Empire for me. And it does not fire off a deep research report. Deep research is buried under like a plus button. And you have to select it and say, okay, I actually want you to do this thing. And then it takes you down the deep research workflow, which I understand is, like, for inference reasons. They don't just want you firing off deep research reports all the time. But I think in the future, the model router should be very intelligent about. Okay, this is a question that people have asked thousands of times. Let's just go get it from a database. Which is crazy to think in the age of AI, you wouldn't even be hitting a gpu. But I think that's going to be real. And then I think on the other side, like, you should. It should detect, like, okay, this person wants something that's far beyond anything that we've ever worked on before. We got to go search the Internet, we got to write some code, we got to do a whole ton of stuff.

25:55

I'm going to need 10 minutes.

32:05

Fire up deep research. Right. Fourth ads, we've talked about this, but we gotta get them in the LLMs. We gotta get them everywhere. Because I was thinking about the death of Google Reader. I don't think you were ever a Google Reader guy, were you? But it was amazing. You could take all these RSS feeds from all these different blogs during the blogosphere. You could put Marginal Revolution, Tyler Cowen's blog, all these different things in there, and just kind of scroll through them really quickly. And Google wound up killing it. And everyone was really upset. And the reason was, I think, because they never really got on the Google Ad flywheel where there was real, like, revenue generation.

32:06

Yeah. Was that just. It didn't hit a scale that enabled it. Make sense?

32:44

The failure of every Google project that has failed is always a question of, like, was it because they weren't making money from it, or was it because they hadn't monetized it yet?

32:49

Or it just never got big enough.

32:59

Never got big enough to monetize a million. Yeah.

33:01

Weekly actives. It's not probably worth keeping around.

33:05

Totally, totally. But my takeaway from Google's surface area of products that are successful and loved. Google Search, YouTube, Google Maps, Chrome, Android, like, these are all direct funnels for the ads. Flywheel. And so you can see that they're driving the bottom line. There's a whole bunch of folks on the team that are getting excited when they're hitting their numbers, when they're making more money for the business. And so they just get more and more resources, more and more engineering effort. Everything gets better. And I think that not only Are ads the best way to deliver high quality products to the broadest possible audience? But they just make products better top to bottom. And yes, there's the stated versus revealed preference thing. And yes, you might want to pay to not have ads like you do on YouTube. Many people do. But I do think that ads flywheel is going to be really, really important as the inference gets really.

33:08

And right on time. Perplexity ends ads experiment. I saw that this was the news from this morning in the information from Catherine. He says Perplexity is no longer offering ads. An executive told the Financial Times the AI search startup is pulling back from this line of business as rival OpenAI starts showing its users ads in ChatGPT. Earlier this month, the company said it worried ads would undermine users trust in their platform, with an executive saying the challenge with ads is that a user would just start doubting everything. I don't buy this at all. Arvind has a history of kind of just like trying to provoke OpenAI at every turn and so coming out Perplexity in my view, like this is just like somewhat bearish. Right. They're trying to serve as many people as possible all over the world. The best way to do that is going to have an, have an ad supported tier kind of bailing on this, on this moment. I don't, I don't know, maybe it's not worth reading too much into it, but a little bit early to throw in the towel on the economic engine that has driven the Internet for its entire history.

34:01

Yeah, I mean we talk to a lot of founders who have brands and they love advertising. And I think that's another side of this, which is that when a lot of entrepreneurs and also people who work at businesses want to grow their businesses and they have fond memories or affiliations with Facebook and Google because that's how they grew their companies. And when you talk to somebody like Sean Frank at the Ridge, he's like, I'm going to be first in line to advertise on ChatGPT. I can't wait for that. It's converting so well already. I want more of that business. And we didn't really hear that with the Perplexity ad product. We didn't hear people lining up to buy ads in that product. So maybe it was not going as well.

35:17

Yeah.

35:58

The other thing is they thought so. According to the information, Perplexity started testing advertising in 2014. Less than a year into its test. Taz Patel, the executive leading the ads effort, left the company in perplexity. It only let in Less than half a percent of the brands that wanted to advertise, so there was like a bunch of demand. They barely let anybody use it and then they bailed on it. Interesting. And so interesting.

35:58

Well, the last one is somewhat related to OpenClaw, but I think way down the funnel, beyond the 20 minute deep research project, you probably want to be able to fire off something that looks like Claude code or openclaw or Codex to write lots and lots of code and solve a really, really hard problem. And so many reasoning models can already write some Python and execute it, but it's clear that everyone wants to go full further. Hence the Mac mini boom. And I'm not actually sure how important access to the local file system is to most consumers. Like, when I think about what's like most of the data in an average Internet user's life is mirrored in the cloud. I think they care about their camera roll, they care about their email, their messages, and almost everything's in the cloud. I've noticed this when, when I move from one computer to the next or I move from a phone, I'm like, wait, I didn't actually there was a time when it was like, oh, you're moving computers. Get an external hard drive, make sure you drag all your files over. Most of the stuff's mirrored to icloud that can be accessed via an API. It requires a business development deal probably, but it does seem feasible. And a lot of the LLMs have hooks into Gmail already. I think all three major LLM apps have Gmail integrations already, and more integrations are coming, clearly. And so I'm not sure that you need to replicate openclaw and have it running on a dedicated piece of hardware, even like cloud hosted. But I do think people will want to be able to fire off something that writes tons of lines of code to solve a particular problem, even if it's something as mundane as like getting you a restaurant reservation at a place that doesn't have an API. Like if there's a restaurant that just has a web form and you basically want to deploy like agent mode, that might look like writing a web scraper and writing something that actually does, like a headless Chromium browser and like clicks it and that might be generated from something that looks a lot more like openclaw or cloud code than something that is just a couple lines of Python in a reasoning model. Anyway, there are also a bunch of nice to haves. These aren't really on the list, but you know these apps, they still occasionally fail to return results. When you're in areas with patchy cell phone service, there's like little UI things. Some of them botch text to speech requests. When you will, you'll fire off a deep research report and they'd be like, read this to me. And then it'll read for like a minute and then it just. Some of the apps don't let you listen to the deep research reports, but they let you listen to the normal reports. So there's all these little fine details in the UI that I think are causing more churn and people can just chop away at. It's unclear if what is required to make an amazing product is just AB testing all of these things and just optimizing or is it taste? I have no idea. But if you wind up doing this is my recommendation for anyone who's working on this stuff. If you're just going to run an AB test to figure out what is the correct user interface and you run the AB test, you find out that the button should be blue instead of green. Don't tell your boss you ran the A B test. Tell them it was taste. Say that it's all about taste.

36:26

Good call.

39:45

And that you have taste.

39:46

It's all about taste.

39:47

Because then you'll have a job forever. Yeah, but if you say I'm just the guy who runs a B test, really? Well, probably. Probably. Taste is king. It's true. The AI models can't taste. They can't taste. They can't Taste A5 Wagyu. They can't taste a Cabernet Sauvignon. Only you can do that. So make that dinner reservation and enjoy a nice glass of red wine. Because the models can't. They just can't. There's just no way. There's no way.

39:48

Alpha, Alpha. Alpha.

40:14

Anyway, let me tell you about MongoDB. What's the only thing faster than the AI market? Your business on MongoDB? Don't just build AI, own the data platform that powers it. And let me also tell you about Lambda Lambda is the super intelligent cloud building the AI supercomputers for training and inference that scale from one GPU to hundreds of thousands.

40:16

Robinhood says historically investing in private markets was limited to institutions and the elite. But not anymore. With Robinhood Ventures, you can now get exposure to private companies like the ones listed below. They have a new fund that has databricks, Mercour, Revolut, Airwallocks, Boom, Supersonic, Ramp, Aura and Stripe, which is impending. Close. Very curious. Which of these companies, if any, were actually on board and excited about being part of this lineup.

40:36

I think Ramp was. I saw Fax Herbert from Ramp posting about it and he is, but that.

41:10

Doesn'T mean the company okay, he said.

41:18

We are excited to partner with Sarah, Shiv Chan and the broader Robinhood Ventures team on their inaugural fund. On a personal note, I'm relieved to finally have an answer for family and friends who have been asking how do I get exposure to Ramp Equity? And so if this is coming out from your head of investor relations, it's not exactly a Matt Grimm style response. So I think most of the companies that are in the press release at least and saying hey, you can use our logos are cool. We'll see where it goes. There are folks that might get funneled in there and they don't want to be and there might be a whole bunch of different debates and back and forths. What is Enclave?

41:20

Shiel shared kind of some of the cost basis from the prospectus. They bought Databricks at $150 per share now trading at 204. Ramp at 90, now trading at 90. Air Wallix $21 it's now trading at 18.8 and then Mercore at $714 now trading. So already seen a little uptick. Anchor came in and was sharing some of his sites insights friend of the show, he says a single close end fund that gives you exposure to some of the top private startups. My thoughts. People want access to private markets of course. So much wealth creation in America happens in startups and people desperately want access. You can see this with the insane silly fees people are paying for anthropic SpaceX and OpenAI SPVs. He says too, the structure of this fund is broken As a closed end fund, the price here can diverge very significantly from the net asset value of the underlying assets with fomo. From Access, this could easily trade at a very high multiple to nav, leading to a lot of retail investors getting their face ripped off. It ends up being less of a venture fund versus a speculative product to ride private market sentiment. It's a great disclosure Long Robinhood, but will not be.

42:05

He's long Robin Hood but he's like.

43:18

I don't like this. Yeah. So we actually have the founder of Destiny coming on the show today, Sohel Prasad.

43:20

He's coming on at 1pm and they're sharing their Q4 results. They have exposure to Anthropic Chaos Industries. Hermeus positioning Destiny as a New York Stock Exchange listed vehicle, democratizing retail access to high growth.

43:28

Destiny has suffered from the same problem. They were super early. They got this fund out almost two years ago. Exactly. Or close. And immediately it spiked. There's a lot of demand to get exposure to these assets and it's come back down to earth since then. But excited to get the update from him and understand. Yeah.

43:41

And let's pull up the rest of the LINEAR lineup to show you who's coming on the show today because we have Blake Dodge from pirate wires, Freddy DeBoer from Substack Sohail, as we mentioned, from Destiny, Travis from Mesh Optical, and then Evan Spiegel, the co founder and CEO of Snap. Linear, of course, is the system for modern software development. 70% of enterprise workspaces on LINEAR are using agents. Moving on. Elon Musk announced that XAI is moving away from traditional and academic benchmarks like Humanities last exam to focus GROK on maximal utility for real world engineering and software development said, actually I don't think HLE is a great measure of usefulness. We're moving away from these benchmarks.

44:07

Andy Scott says. So it's bad.

44:50

Who said that?

44:55

I think it's totally fair to just focus on real world utility. But of course people are still going to ask. Well, I still want to know how it does.

44:55

Yeah, it's interesting. I mean, Tyler, give us the update on 4.2 that came out today. So Grok 4 has already been out.

45:06

This is a minor revision and 4.1.

45:16

4.1. So now we're at 4.2. And is it focused on benchmarks or have they carved out a particular, particular niche yet?

45:18

Yeah, so I think historically, especially when Grok 4 came out, people were like very, very quick to say it was like, oh, this is so benchmarks or whatever. I think they've definitely retreated from that like at least path with 4.2 it doesn't look like outrageously benchmarks or anything. They did this kind of interesting thing where when you. So it's still not like fully out, it's still like in beta. If you go on the GROK like interface. They did this kind of interesting thing where there's like four agents.

45:29

Okay.

45:54

Every time you actually do a prompt there's like four agents and the agents specifically have distinct roles. Where it's almost kind of like you have four instances of the same model but they have different system prompts. So you can try to get like, okay, this one is focused on doing.

45:55

Qualitative things instead of mixture of experts, mixture of agents.

46:10

Yes, but mixture of experts is like that's like within the architecture of the model within the architecture where this is like you train the model and then you kind of add this as almost like a harness type thing.

46:14

Yes, yes.

46:23

So it's kind of an interesting path. We'll see.

46:24

Yeah.

46:28

Again, this is still not like the actual 4.2 full release, I believe, but we'll see.

46:28

Yeah. I wonder what the bull case is here for xai. There's a world where they carve out some sort of niche anthropics focused on coding very specifically and had some major, major gains there. What else is there?

46:35

I think with macro hard, they're going very hard on computer use.

46:52

Okay, computer use, yeah. See that would be an interesting thing where they could jump to the front of that and if that's the important technology for a couple months, that could be really good vibes. Also it is interesting to think about with the Cerebras news and with the value of high speed inference on the whole model on one chip. Is that something that Tesla's chip team can iterate towards on a faster time horizon than other chip companies? I don't really know, but they do custom silicon and they've done it for a long time and they got an entire self driving model that runs on a car. So they have some experience there and they obviously design and fab or they don't fab it themselves, but they design it themselves and so will be interesting to see how they carve that out. Let me tell you about Vanta Automate Compliance and Security. Vanta is the leading AI trust management platform. Let me tell you about Applovin. Profitable advertising made Easy with Action AI. Get access to over 1 billion daily active users and grow your business today.

46:55

Tariq says. I'm proud to share that humane has invested 3 billion into XAI's Series E round just prior to its historic acquisition by SpaceX. Through this transaction, Humane became a significant, a significant minority shareholder in Xai. The investment builds on our previously announced 500 megawatt AI infrastructure partnership with XAI in Saudi Arabia, reinforcing Humane's role as a strategic development partner. So yeah, interesting. Maybe, you know, would have wanted to get this out before, before the SpaceX acquisition, but better light.

48:04

Wait, they said they got in before the acquisition.

48:40

I know, but you mean the news. But like, you know this round got announced a while ago. Yeah, so maybe they would. They're coming out with this news today.

48:44

Yeah, but they're saying, hey, we got in before the acquisition, so we got SpaceX shares.

48:56

Yeah, I don't know. It is odd that better late Than never.

49:01

Yeah. You mean on like a comms front, but like from a financial perspective like that, that was the right time to invest, right? Yeah, I think that's what's going on. I wonder why the announcement was delayed. Maybe it's like regulatory approval because it's an international investment. Let's play this clip from Jeff Bezos. His space company, Blue Origin, will move heaven and earth to get to the moon before rival SpaceX. The CEO Dave Limp said recently. Jeff Bezos, who never tweets, this was.

49:04

His first tweet of 2026, posted a.

49:33

Photo of this, like Black Tortoise, which goes along with Blue. Vague posting motif of slow and ferocious, methodical.

49:37

A lot of people have viewed it.

49:48

As a warning shot to Elon Musk.

49:49

Which really was focused on SpaceX going.

49:52

To Mars, and now he's saying we're going to focus on the moon. What do you make of that tweet? And what is the competition right now?

49:54

Do you think you're going to be the first?

50:03

Well, it gives me an opportunity to put on a T shirt for you. So there you go.

50:04

That's.

50:08

Nothing else. Let me do that. I get to keep this.

50:10

Yeah, that's all yours. And that's the first one off the.

50:14

Presses too, by the way. I think everybody's going to want one.

50:16

Of those to lose.

50:18

For Blue to succeed, what the US needs is it needs two SpaceX's, it needs two launch companies that are competing.

50:20

Vigorously against each other to try to.

50:29

Give us the most capabilities as a.

50:32

Country, commercially, civilly, from a defense perspective.

50:33

Because our adversaries aren't standing still. And so we need, we need to be moving very quickly. Healthy competition. But I think a lot of people run into that as the tortoise being Blue Origin and the hare being elon Musk and SpaceX, because it also comes after Secretary Duffy had said that SpaceX is behind, so they were opening up for everyone in terms of Artemis. And Jared Isaacman, who's now the administrator, also said, essentially, yeah, whoever can get there first is going to get the contracts. So do you think you're going to get there first? I think if asked, we will make it. We'll give it a run for our money. I like our architecture.

50:38

I like our odds of getting there very quickly.

51:14

I, I don't, I don't have a crystal ball into what SpaceX is doing. I, I think again, Gwen and Elon are competent and they show it every day by launching rockets. But I love the fact that the US would compete. US against each other.

51:17

They are for sustainability on lunar.

51:31

We're talking about who could get there in 2028 if asked. We will step up and we will.

51:33

Move heaven and earth to get to the moon first.

51:38

Move heaven and Earth.

51:41

Powerful line.

51:42

The moon race is gonna be fun. I think it's shaping up. Shaping up. Well, I mean, yeah, a little bit of a come tortoise in the hare story. A little bit of come come from behind. I'm not buying the tortoise as ferocious.

51:44

Yeah, I don't love ferocious. I don't really love the. I don't really love the analogy. Like, I don't, I don't, I don't. I don't think it's the best comm strategy. Like, I like the vague posting out of Jeff. It gets, it gets the people going. But at the same time just imagining SpaceX as the hair. Just like running, running a bunch of laps around the tortoise, just kind of.

51:57

They need to take this way further. Elon needs to wear tortoiseshell glasses. Be like, I turned your tortoise into my glasses. And Bezos needs to start carrying a rabbit's foot for good luck. That would be the hair. Like, I got your face foot. You know, I want, I want much more. I want more battles here. This is great. Well, let me tell you about Okta first. Sorry. Octa helps you assign every AI agent a trusted identity. So you get the power of AI without the risk. Secure every agent. Secure any agent.

52:21

According to Kalsi. According to Kalshi, Blue Origin. Will Blue Origin land on the moon before SpaceX? So if blue Origin lands an uncrewed moon lander on the moon before SpaceX, before January 1, 2030, the market will resolve the yes. So currently it's at a 70%.

52:51

70%.

53:09

So they think 29% in March.

53:10

Of course, the race isn't over. The finish line is not get one lander to the moon. It's like develop an economy on the moon and get lots of people there. So it was just one read on this market. But it is interesting and certainly, I mean, you can see the market was not pricing this a year ago and I don't think anyone was. I think everyone thought that Blue Origin was kind of just a side project that was sort of just like doing space tourism. And now it seems like they might be going to the moon, which is pretty cool. We have some breaking news.

53:13

What's that?

53:45

Claude Oauth is officially not allowed in Openclaw. So anthropic is responding to the Openclaw, OpenAI News and Andrew Warner shares that this would be a great time for Sam Altman to step in and let us use OpenAI subscriptions with OpenCLA. So in the Claude code docs, OAuth and OAuth authentication, which is used with the Free Pro and MAX plans, is intended exclusively for CLAUDE code and Claude AI. Using OAuth tokens obtained through Claude, Free Pro or MAX accounts in any other product, tool or service, including the Agent SDK, is not permitted and constitutes a violation of the consumer terms of service. So if you're on the consumer plan, if you're on the consumer plan with anthropic Claude, like you just signed up for a normal plan on your app and then you get excited, you want to sign up for, you want to set up OpenClaw on your Mac Mini, you do that and then when you're in the login flow, you say, hey, I'd like to use my CLAUDE tokens over here. It's going to say, no, you got to set up an enterprise plan, you.

53:46

Got to set up a private API. Correct, yeah. This is not news, though. This was like a couple weeks ago, I think, like a week after OpenClaw got like super big, they stopped. Because you can still. I mean, I'm pretty sure you can still use API. Like an API key.

54:50

An API key, yeah. And will that use your right now consumer?

55:04

So how it used to be was you could have a CLAUDE subscription.

55:08

Okay.

55:10

And then with that you get a certain amount of like, basically Claude code tokens. Yeah, yeah, but they're super. They're like massively subsidized versus the API. It's like 10x.

55:11

Yeah, yeah.

55:19

For the cloud code tokens. Got it. They were basically using those in openclaw in other agents. Yeah, that was for open code. Yeah, actually openclaw. Yeah, yeah, yeah, Sorry, I'm getting. Yeah, no, I know, but I think It's a similar.

55:20

25 different names. Yeah, yeah. So the chat is saying that this is news that like, the particular Open Claw integration maybe broke today. Peter from OpenClaw has responded and says that OpenAI has already publicly said that OpenAI subscriptions will work and continue to work in OpenClaw. And so it's a little odd because, like, yeah, I mean, you can just use the API. That's not that, like, if you're technical, that's not a problem. But for the sort of pseudo technical folks who are setting up OpenClaw instances on their Mac Minis, they might be a lot more encouraged to Set up the system if they're able to just log in with OAuth with their Claude accounts. Because they're like, yeah, I already have the app and I use the app and I have some extra tokens. Why don't I use them over here?

55:32

Yeah. Thomas says the news is that they're applying it to the SDK.

56:26

Yes. So there we go.

56:30

Anyway, moving on.

56:33

Let me tell you about consul. Consul builds AI agents that automate 70% of IT HR and finance, giving employees instant resolution for access requests and password.

56:34

Resets out of the Journal. Yes, the fossil fuel tycoon teaming up with the Rockefellers to fight energy poverty. I'm sure the online conspiracy community will love this one, but we love tycoon. We were trying to bring the word tycoon back, so we're happy to see the Journal using this EQT Chief Executive Toby Rice is starting a nonprofit to tackle a lack of access to to modern energy infrastructure in poor countries. Toby Rice made his fortune unlocking a gusher of natural gas in Appalachia. He has a bold new ambition, bringing energy to millions of people in impoverished nations. Rice, The Chief Executive EQT, one of the largest natural gas producers in the U.S. is a co founder of Energy Corps, a nonprofit. Energy Corp. A nonprofit that helps developing nations such as Ghana, Zambia and Burundi build out their energy infrastructure and prosper. Unlike other philanthropic incentives that emphasize renewables to energize impoverished societies, Energy Corp. Sees a role for a broader spectrum of solutions, from fossil fuels to solar panels and nuclear plants. Notably, this approach has been endorsed by the Rockefeller foundation, one of the oldest and richest foundations.

56:42

Really opened up the floodgates with this. The Rockefellers. Wasn't John D. Rockefeller the richest person in human history? You see how much he's putting in this project? 200 GS. 200K. Go solve it. Go solve energy globally. 200K. Here you go.

57:58

Best I can do is 200 bucks. I got you. I'm super excited about this.

58:16

I think Macron deserves a victory lap at this point.

58:23

I mean, his McCrone size is looking.

58:27

Yeah, it's size. It's size compared to the.

58:29

No, no.

58:32

Obviously they have a lot of other donors. The Rockefeller is just a fancy name because Toby and his wife have personally contributed $3 million. And the initiative is raising 10 million this year from energy companies, family offices and private individuals. And from his perch at Pittsburgh based EQT, a company with a market cap of 36 billion, Toby Rice has preached the benefits of selling more American natural gas across the Globe to reduce emissions and strengthen security of the US and its allies. Now he's wading into a debate. Should impoverished societies be encouraged to rely on polluting fossil fuels to improve their fortunes or leapfrog to intermittent renewables? There was this question about should Brazil be allowed to clear cut the Amazon rainforest to pull forward industrialization. It's the world's lungs. Everyone suffers if that happens, but they would certainly benefit in the short term.

58:32

Term.

59:23

So there's a, there's a hot debate here and he is engaging in it. Anyway. Let me tell you about Cisco. Critical infrastructure for the AI era. Unlock seamless real time experiences and new value.

59:24

With Cisco, David Holz has hit the timeline. He says 5 million humanoid robots working 24,7 can build Manhattan in six months. Now just imagine what the world looks like when we have 10 billion of them by 2045. Now imagine the year 2100.

59:34

Dyson Sphere. Dyson Sphere. Dyson sphere by 2100 is the correct debate. Is it before, is it after? But it's like around there.

59:51

I keep going back to my land thesis. It's like when armies of robots can build anything anytime, what is actually scarce? In this case? I think with 10 billion of them, I don't even think land will be scarce anymore. It's like, hey, we're making, we're gonna build an island.

1:00:02

We're gonna build another moon. We're building the moon.

1:00:18

New moon alert.

1:00:20

There's new moon alert. Just build another Earth and just throw it on the other side of the solar system.

1:00:21

Yeah, yeah. I mean it's, it's, you know, right now we're talking about what businesses are unsloppable.

1:00:28

Yeah.

1:00:32

The next meta will obviously be unclankable.

1:00:33

Unclankable.

1:00:35

What's actually unclankable? When you send, you know, an army.

1:00:38

Well, figure out what's unsloppable. Figure out what's unclankable and then go invest in it. On public.com investing for those who take it seriously. Stocks, options, bonds, crypto, treasuries and more with great customer service.

1:00:43

Richard says SF Guy eating a delicious blueberry. In 18 months, everything will be blueberry.

1:00:55

This is a perfect contrast to the other post, just the hot dog.

1:01:01

The hot dog.

1:01:06

1.

1:01:06

NSF discourse. No, no, no. Of David Holt. David Holes is like, David's seen humanoid robots. Like he sees. He's lived in SF and been around this stuff. Like he's a true believer. And he's sort of saying like, I've seen what they can do. And I understand the exponential here and now. Imagine 10 billion of them in 100 years. Like it's going to be crazy. Then you have Richard on the other side. Everything will be blueberries.

1:01:07

I thought you were talking about the delicious tacos post. He said, I'm the CEO of a hot dog company. I've worked on hot dogs for 10 years and I wasn't prepared for what I've just seen. Your life is about to change. So what can you do? Buy as many hot dogs as you can. Buy stock in hot dog companies.

1:01:35

It's a good idea. I am long hot dog. I like hot dogs.

1:01:54

Hot dog market map good with the kids.

1:01:59

Everyone loves a hot dog.

1:02:02

Hot dog Market map enjoys.

1:02:03

It's all American. There's nothing better than a hot dog at a ball game. Except for Fin AI. That's better than a hot dog. It's the number one AI agent for customer service. If you want AI to handle your customer support, go to Fin AI.

1:02:04

Anduril fundraising shows defense tech is still red hot.

1:02:16

Pretty crazy.

1:02:19

Katie Roof, one of the scoop athletes.

1:02:20

Scoop. There it is.

1:02:23

She says in case you missed it, on Friday we broke the news at Anduril's in talks to double its valuation to around 6, 60 billion in a new funding round. So if you were buying triple layered SPVs in Anduril at 45, you might make it. Assuming you didn't pay three levels of 10% one time and assuming that the.

1:02:27

Guy you bought them from Scone and is now in custody of the Feds.

1:02:47

That's about as if the round is notable for more than just its price. While Anduril technically has both A and I in its name, it's not the AI centric type of startup that typically gets all the investor attention in the current cycle.

1:02:53

Very unsloppable. Right? You're not going to vibe code A drone, you're not going to vibe code.

1:03:04

Yeah, I don't know. I think when you think about who's going to unlock the potential of AI for the government. Think of Palantir. You think of Anduril.

1:03:09

No, no. Yeah. No, I just mean in terms of like AI disruption, like it's not something that you can, you can vibe code. A fury drone like that takes a lot of hardware, a lot of testing. You got to blow a bunch of stuff up. You need a test range, you need government.

1:03:19

Yeah, I just, I just don't. Yeah.

1:03:35

Relationships over decades.

1:03:37

I think all these, all these, you know, defense oriented businesses, even if they are building software, are quite a bit more insulated just because of the trust factor. And if, if Anduril sells a product for one price and you have a small team coming together saying, you know, we're 10 people, we can build you the same thing for half the cost, there's not quite as much pricing pressure because the government wants reliability, they want to set something up and use it for a really long time, they don't want to really take risks, etc. Etc.

1:03:39

Defense tech's on a tear shield. AI, a drone business that can also tap the AI interest, thanks to its autonomous software, is in talks to raise a $12 billion value valuation, Bloomberg reported, and several other younger startups will likely raise money in the next few months. Paul Kwan, managing director at General Catalyst, said that part of the reason the firm is so optimistic about Defense Tech is because there are very few trillion dollar markets that are critical for global resilience, that are dominated by legacy vendors and which are experiencing both tech and geopolitical transformation. Yeah, the number of companies that fall in that bucket is pretty small. General Catalyst has invested in Anduril as well as other defense related businesses such as Saronic and Helsing, a European rival to Anduril. As the world unfortunately braces for more wars, increased government spending has led to high prices, high priced contracts for defense tech. Kwon said that the U.S. department is realizing that defense tech is critical for deterrence. Kwon said he has been seeing he has also seen a shift among entrepreneurs believing that many of the most talented founders are choosing to build for the defense industrial base. And you can check out the rest of the story on the information.

1:04:09

A lot of attention has been focused on open router. If you go on open router and look at the rankings you can see that Chinese open source models are completely dominating charts.

1:05:21

Minimax I saw DHH talking about Kimmy K2 is now a daily driver for squashing bugs at 37 signals. Very interesting data point. Since a lot of this can be I think the open router stuff can be a little hard to contextualize because there's some amount of volume that doesn't get captured in open router.

1:05:31

Obviously it's the majority of the volume is not captured.

1:05:55

You think so?

1:05:59

Yeah, yeah. According to Zephyr who's very on it, it's 1 to 2% globally.

1:05:59

Do you think that's about right?

1:06:04

Yeah, definitely. I mean if you just compare like the like. If you look at the actual like token count it's like in the billions for like over a week or something where you know.

1:06:06

Yeah, you'll see.

1:06:17

I remember Demis over the summer. He was like, we're doing, you know, quadrillion tokens every month or something. So it's like the scale is completely different quad. And also it's like no one is going to be using the Big Labs models on this because they would just hit the actual API. It's just easier. So if I'm going to be calling Anthropic, I'm probably just going to use the Anthropic API. I'm not going to go through Open Router. So you expect it to be the open source models because one of the good things about Open Router is that it has all the different inference providers together. So there's a ton of companies that host the different open models. So it aggregates them all together.

1:06:17

And also, I mean this doesn't account for token generation in consumer LLMs. And that's a huge thing. Like Google AI overviews is I think, the most used LLM product in the world. Something like that. And that's technically generating tokens. When you just hit Google Search and it answers with an LLM query, that's token generation. And then there's stuff that's happening in Gemini app, Claude App directly, not even coding. Like no one's using Open Router within their consumer app unless it's like some third party thing. But most of them are going anyway. Let me tell you about cognition. They're the makers of Devon, the AI software engineer. Crush your backlog with your personal AI engineering team. Let's continue with the timeline. Jacob Rintamaki has a post here. He says unfortunately it is not seen as cool to say, but the beatings will continue until more people internalize this. He's talking about Rune saying, I don't think this is really true, but it's hard to fight open source copium because people act like you shot a dog or something. Because Anton two years ago, back in December 21st of 2023 said AGI is more likely to come out of someone's basement, some mega merge Hermes 4000 than a giant data center. And I think everyone agrees with this now, but it was very unpopular to say at the time. I remember John Ludic had a post about open source AI not being like on the critical path to AGI because of the scaling laws and a whole bunch of other economic factors. He sort of predicted that Meta would stop being so focused on open source because it just doesn't make sense to spend a $trillion or $100 billion on infrastructure that then you capture so little of the value of. And I think that's why Anthropic has not been very pushing hard on open source and even the other superintelligence initiatives. Not many of them have been open source. The open source question has been a very different business model, but it is very important in terms of model commoditization and terminal economic equilibriums.

1:06:56

In the AI lab battle, Orin Hoffman is sharing that Ozempic is bad for business. Yes, A few months ago someone told me they had heard a rumor that a banker hedge fund had banned its traders from taking Ozempic, wegovy and other GLP1 weight loss drugs. The theory, as I understood it, was something like traders need to make quick decisions based on gut instinct and GLP1s. Mess with your gut instincts, you're not hungry for snacks, you're not hungry for profits, you lose your edge.

1:09:02

It is funny.

1:09:29

Warren says GLP is getting banned by hedge funds, maybe by sales teams too, killing your grindset.

1:09:30

It is funny. That doesn't it isn't GLP glucagon like peptide? Isn't that a peptide that's secreted by the gut? And so it's like your gut instinct is actually tied to your gut. Like maybe it's just nominative determinism. But it is funny that those things.

1:09:37

Wound up being your gut instincts. For some people saying put on mass scale, it's time to scale.

1:09:50

Time to bulk bulking seasons here. Get off the GLP1s and start levering.

1:09:55

Up going risk on Dr. Cameron Maximus says guess what increases drive testosterone. A microdose of tirzepatide to cut down on physical appetite. Macrodose of testosterone to amplify psychological appetite. So the solution is we're going to ban GLP1s only if you're taking them solo. You've got to be taking a full stack.

1:10:00

Did you see Bone GBT say Turns out you really do got to be hungry for it. It's fantastic. Fantastic as is Gusto. The unified platform for payroll, benefits and HR built to evolve with modern small and medium sized businesses and TVPN. Claude Sonet 4.6 has improved on benchmarks across the board. We touched on this yesterday but particular particular particularly outstanding in office tasks and agentic financial analysis. You can see this being baked into Claude for Excel and a lot of knowledge work. Lucas Beyer over at MSL says formerly OpenAI says I usually look at which benches the small model surpasses to its previous big brother. If it's only A few. I think that gives a hint as to what they focus on. Here it is only agentic financial analysis and office tasks. It's just a heuristic, of course, but interesting nonetheless. And I wonder if that's. I wonder if. Tyler, how important is speed between Sonnet and Opus? Is Sonnet consistently faster or just cheaper?

1:10:22

Yeah, I think it's usually faster.

1:11:36

Faster.

1:11:38

It's just a smaller model.

1:11:38

Yeah.

1:11:39

And then there's Haiku, which is the smallest one.

1:11:40

Because I'm wondering if in the coding domain there's a little bit more tolerance for. Okay, I've delegated this task. It's going to go cook and then I'll come back and review the code, review the pull request.

1:11:42

Whereas in finance, this was the whole thing about Codex.

1:11:53

Right.

1:11:56

Because Codex was much slower for a while before Cerebra, so people would be like, oh, Codex is so bad compared to cloud code. Even though a lot of people internally at OpenAI were saying, oh, no, actually Codex is way better. It's just because they're used to having the internal model that run on the better hardware. So I think speed is actually. It plays a very large role. So even if you have a smaller model, it's much faster. Even if it's a little bit worse, I think there's still a lot of. If you're iterating a lot, that can actually be much more efficient.

1:11:56

I'm just thinking in terms of an Excel copilot for someone who's spending their time in Excel, not in GitHub. Will speed be a killer feature for them if they're currently like, yeah, I've tried it, but I. But it's really slow. It actually slows me down because it takes 20 minutes to respond. It gets it 80% of the way there, but I can do 90% in 15 minutes, so I'm not using that model yet. I'm not excited about that. Maybe this is something that speeds things up. But of course there's ways to just inference the model faster. Even the big guys.

1:12:25

Yeah. I mean, I think when a lot of the agentic browsers first came out, one of the benchmarks I would use is like editing a spreadsheet.

1:12:56

Yeah.

1:13:03

Sheets.

1:13:04

And it was so slow that it was like it was working, but it's just so unbearably slow. There's like literally no point of using it.

1:13:05

Yep.

1:13:10

So I think, yeah, speed is like massive kills.

1:13:11

What about Hair Bench?

1:13:13

Hair Bench? What's Hair Bench?

1:13:15

Gabe says Jordy needs to bring Tyler with him when he gets his haircut Haircut.

1:13:16

Haircut alert. Haircut alert.

1:13:20

Gabe, I did send Tyler asked. Yes, I sent him my barber's information. So I think they're working on it.

1:13:22

Haircut alert. We gotta get a card up. Jordy doesn't want to do it, but I think we should put up a card for Jordy's new haircut. We don't like secret haircuts. If you are heading to New York Stock Exchange, you need a fresh haircut. And we are partnered with the New York Stock Exchange. Do you want to change the world? Get a haircut and then go raise capital at the New York Stock Exchange.

1:13:31

Great call. John Dwayne says, what is going on at Anthropic? They're going after people with multiple paid max accounts. You're paying Pulp full price multiple times and they're treating you like a criminal. Not sure what Dario is trying to speedrun you. And on Reddit, on Claude code, it says Claude just banned having multiple max accounts. Since around a few hours ago, signing into another account has stopped working.

1:13:50

I think some people do need to have their multiple max accounts banned. They're just. They're not building anything useful. They're wasting tokens and they're just creating endless, endless setups and tool chains and MD files. And unless you're actually shipping something that's going to drive business value and be used by more than one person, you only get one account. I'm with Claude on this. Stop wasting tokens on your silly thing. I was reflecting on. I was texting you this last night. Am I dumb and out of ideas or is all the software I want just illegal? Because I was like, all the things that I want are things that could exist, but they can't exist for business reasons. Yeah, like, I want. I want an Apple TV app.

1:14:14

Give the example. So the example was, yeah, I want.

1:15:01

An Apple TV app that has Netflix installed. It's like, why doesn't that. Why doesn't Netflix integrate with Apple tv? Because Netflix doesn't want to get aggregated. They're an aggregator. They want you to open that app on the Apple tv. So the Apple TV app doesn't have Netflix content, even though you have the Netflix app installed on Apple tv, the device. And I was saying, like, I subscribe to all these different news sources. I want, like an Apple News that aggregates them all. Google Reader that aggregates them all. I pay, but I'm still logged out of million things. Like I'm in some social app and then it opens in a Safari web browser. I'm not logged in. There's a paywall. It's annoying to log back in. I want something that just like aggregates all my news sources and jumps the paywall. Well, that's not the coding issue. That's like a, That's a business issue. They want you to log in for a reason and they have a decision to that. So I don't know. I think we're still early in the broad distribution of people building custom software and experimenting with things. But at the same time, we've had great writing models for a long time and anyone we know, everyone could write their own books. Everyone could write a better ending to the end of Game of Thrones and send it to you as a text file right now with the current models. And I haven't read anything that I've been like, oh yeah, this is really good. I got to read this AI generated book. So I don't know, there's like some weird bottleneck there that it's like, it's not a barricade.

1:15:03

Look what Gabe is offering. Sounds very illegal.

1:16:28

Yeah, this is Popcorn TV. It's called uTorrent. I know, I know, I know.

1:16:31

Xbox Media center trying to play by the rules.

1:16:38

Xbox Media Center. But that's the, the thing is that, yes, that streaming site, yes, you can vibe code that, but that can't actually get to scale. It can't actually have an impact in the economy because it's breaking the rules. And there's a lot of AI stuff that feels magical. And you see this with C dance from ByteDance where it's in the journal today. TikTok's Chinese parent develops movie app. I love that headline on Twitter. It's all so Sea dance just destroyed VO3 and Sora too. But in the journal it's TikTok's Chinese parent develops movie app. And there's something interesting here. So Singapore is where it's based. Singapore, the company behind TikTok, has developed an artificial intelligence model that can turn a single text prompt into a high quality video with a storyline, scene changes and distinctive characters. The the new AI video creation model from Beijing based ByteDance is generating buzz in China and backlash in Hollywood over copyright issues. It shows how ByteDance, known for creating TikTok, is emerging as a rival to OpenAI and Alphabet's Google in the race to build tools for making AI movies and other video entertainment. China's visual models have been very, very competitive, said Steve Long, a video game developer in Helsinki who participated in beta testing programs. ByteDance recently ceded control of the US version of TikTok to an investor group. Global users of another ByteDance app, Ben.

1:16:40

Thompson was going off on the on cheeky pint.

1:18:02

He's got a couple cheeky pints in that guy. He's going to let loose.

1:18:06

He let loose. He's saying we got the worst no, he said the worst possible outcome with TikTok where they still control the algorithm and we violated property rights. Shots fired, of course. Still in motion. Yes, and but for now doesn't seem like it's been fully solved.

1:18:08

But this was the interesting paragraph that I wanted to highlight in this Journal article. Global users of another ByteDance app CapCut, a popular video creation and editing app, will soon have access to C Dance 2, its latest AI model for creating videos. The company said the model is already available to users on capcut's Chinese version. And so I mean you've seen seen on Instagram reels like there are a ton of capcut editors out there. I get served how to edit in capcut and I don't even really use the app, but it's clearly incredibly powerful. There's a whole bunch of cool features in capcut that would basically be After Effects plugins and would probably take a long time to configure but just come out of the box and it's just a couple clicks so you don't have to know any code or install anything. It's just there and now you're going to be able to generate CDance videos. We'll see how long you can still generate Larry David and and Marvel characters. That stuff will probably get pulled back on eventually, at least in the capcut American version, but you're going to see a lot more slop in the trough.

1:18:29

What do you think Andal says? Just had to drop in and say thanks for the gift suggestion. I got my girl MongoDB for Valentine's Day and she loved to hear.

1:19:28

That's so great to hear. I'm so glad. It really is the perfect Valentine's Day gift. MongoDB.

1:19:37

Dean Ball is Before we do.

1:19:45

This, let me tell you about phantom cash. Fund your wallet without exchanges or middlemen and spend with the phantom card.

1:19:47

Dean Ball says if the Department of War and Anthropic can't agree on terms of business and they shouldn't do business together, I have no problem with that. But a mere contract cancellation is not what is being threatened by the government. Instead it is something broader designation of anthropic as a supply chain risk. This is normally applied to foreign adversary type technology like HUAWEI in practice, this would require all Department of Work contractors to ensure there's no use of anthropic models involved in the production of anything they offer to do every startup and every Fortune 500 company alike. This designation seems quite escalatory, carrying numerous unintended consequences and doing potential significant damage to US interests. In the long run, I hope the two organizations can work out a mutually agreeable deal. If they can, I hope they agree to peaceably part ways. But this really needn't be a holy war. Anthropic is in Google in 2018. They've always cared about national security use of AI. They were the most enthusiastic AI lab to offer their products to the national security apparatus. If Anthropic run by Democrats whose political messaging is Anthropic run by Democrats whose political messaging sometimes drives me crazy, sure, but that doesn't mean it's wise to try to destroy their business. This admin believes AI is the defining technology competition of our time. I don't see how tearing down one of the most advanced and innovative AI startups in America helps America win that competition. It seems like it would straightforwardly do the opposite. The supply chain risk designation is not a necessary move. Cheaper options are on the table. If no deal is possible, cancel a contract and leverage America's robustly competitive AI market to give business to one or more of Anthropic's several fierce competitors. And there was also reporting this morning that anthropic had approached 1789 Capital, Bruce Buskirk and Don Jr. And they turned him down.

1:19:53

Turn him down?

1:21:43

Turned him down. They turned down from 1789. They said not interested in ideological reasons.

1:21:44

I think I know a little bit about why there might be so much pushback against Anthropic. And I mean, you saw that the Sonnet 4.5 people are really excited about this model, but it completely fell flat on its face when asked with a basic question, why did Clavicular get frame mogged? And Sonnet 4.5 responded, I'm not familiar with Clavicular as a specified person or entity or what frame mogged means in this context. Could you provide some more context? So it's just like when you see something like that happen, it calls into question everything about a company. It's just like how could you let this happen with so little worldly knowledge as to not understand the significance of Cavicular's frame logging? Anyway, overheard in SF VC was giving advice. OpenAI and Anthropic are like Godzilla. You need to find an alleyway to hide in. What a funny thing to say. This is Ben Hylak. He says don't take advice from junior VCs. There's something good there. I mean, the models, you know, if you're in the path of models improving, you will get stomped like Godzilla. But there's still plenty of opportunities all over the ecosystem, especially if you're not doing something that's in software. There's plenty of startups that just like, don't touch software. Don't do anything with code, don't do anything with technology.

1:21:51

Don't it. Don't do anything with a website.

1:23:21

Don't do anything with.

1:23:22

You need a website to do business.

1:23:24

I'm short, I'm passing.

1:23:26

You're cooked. It's over.

1:23:28

It's over.

1:23:29

It's over. It was fun.

1:23:30

No, but clearly, I mean there's plenty of like brands and products and technology and all sorts of things to build and.

1:23:31

Well, we are working on. We are working on an alleyway project.

1:23:37

Oh yeah.

1:23:41

With, with, with Riley Walls.

1:23:42

Oh, okay.

1:23:45

Yeah.

1:23:46

Not gonna share anything else on this.

1:23:46

Are we doing it?

1:23:48

I'm very excited.

1:23:49

Yeah, we are cooking there. So more to come.

1:23:49

There are people who are doing well in spite of Godzilla stomping around America and one of them is 11 labs. Build intelligent, real time conversational agents. Imagine human reimagine, human technology interaction with 11 labs. I like that Godzilla sound effect. That's good for when the labs are on a tear. That's what's going.

1:23:54

Let's pull up this video from Google Capital.

1:24:15

Let's pull up this video. $2 trillion in CAPEX for this. This is what if Donald Trump was from other countries.

1:24:17

He was born in other countries.

1:24:25

This is the fidelity here is really, really high. Dimitri Trump. This stuff is probably going mega viral on TikTok right now. It's going mega viral on TikTok.

1:24:27

So BuCo says 2 trillion in capex for this. By the way. Kind of like saying it's silly, but I look at this and think it's worth every penny. Completely worth it. Even if the 2 trillion just created this one video. Yeah, really good. We're entering the post slop era, back to Tastegate.

1:24:42

Young macro chiming in on tastegate. Is taste valuable? I don't know. I can't tell. But maybe it is. Some people say it is. I'm not really going to weigh in, but young Macro is weighing in. He says many will not want to hear this, but taste is just G intelligence with sufficiently varied training data. Steve Jobs had taste because he was like plus three standard deviation IQ and trained on calligraphy class and being homeless, smoking weed in India or whatever. Meanwhile his IQ match now microdoses amphetamines to narrow the training set and ends up drone maxing at Citadel securities with a great transcript. Sorry, chud, the flunker will get the cake this time. There is something interesting there. Just the idea of like varied wild life experiences being valuable to generate, you know, it's not exactly out of distribution training data, but just a life well lived will translate into innovation and taste or just like new ideas as opposed to being tracked and funneled into Citadel securities where.

1:25:03

I haven't really waded into the taste debate at all. Just because it's not. Everyone's trying to define it in their own way. It's something that in some ways people like to say, oh, you can't buy it. You can't buy it in the fullness of a company because I think taste comes from the founder or the founders and it just kind of like, you know, percolates through the organization indefinitely. Like there's companies that have a billion dollars to spend on marketing that just functionally can never be good at marketing because the founder likes to be heavily involved in marketing and they don't have great marketing taste or instinct or whatever this thing is. But it just feels like everyone's. I don't know, I'm for taste, I'm against taste. I have like, you know, it fun.

1:26:12

Fact, if you hold your nose, you can't taste as well. So if you're trying to be tasteful, don't hold your nose.

1:27:04

Well, Covid. And that's a Covid wiped out a lot of people's.

1:27:11

Oh yeah, they lost their smell.

1:27:14

Yeah, I had some good friends. Some good friends.

1:27:15

Really.

1:27:19

They got Covid in their household recently fully wiped out. So that household had zero taste. They were buying. They traded all their cars. They traded all their cars for Lamborghini in the span of a week. I was like, what's going on?

1:27:19

That's extremely tasteful. I don't know what you're saying.

1:27:32

What's going on guys?

1:27:34

That's amazing. Well, speaking of taste, let me tell you about figma. The most tasteful sponsor ship, the best version. Not the first one with Figma. Introducing Claude Code to figma. Explore more options, push ideas further. Moving on. What is self evidently true.

1:27:35

AGM says all this progress in Genai and not a single serious piece of culture other than slop shorts. I would take that back. I would say my granny got hit with A bazooka is a serious piece of culture.

1:27:55

But that's not AI.

1:28:08

I know.

1:28:09

Okay.

1:28:09

I'm just saying.

1:28:11

I think what he's saying is that there's all this progress in generative AI and no one has one shotted make something amazing and it just doesn't it like there's always this like Herculean effort and inspiration. Like we always go back to Harry Potter, Balenciaga. Even that Trump video is like, it's only funny because of this context. And like it's not purely just like, oh okay, the gen AI did it. And it's certainly not a serious piece of culture. It is a slop short. That's fair.

1:28:12

All this 10x vibe coding and not a single new compelling consumer app. Techies do this all the time. Confusing.

1:28:41

Wait, wait, Tyler, he didn't try cloud with ads.

1:28:47

Oh yes, that's true. That's true. Claude with ads was definitely a compelling consumer app while it lasted. Rip. Techies do this all the time. Confusing being Gutenberg with being Luther, the maker of the technology, of the culture for the culture itself. Hephaestus forges Achilles armor in the Iliad, but he's not the hero and barely appears otherwise compared to to other gods. Techno capitalism might make Hephaestus the rich guy on Olympus, but Homer is going to write him out of the script anyhow. Brutal Mogged history. Mogged.

1:28:50

Jeremy Giffon says humans don't belong behind desks. It is not our end state to be factory workers who replaced hammers with keyboards. Everything that can be automated should be automated. Hammers were meant to hit your face. Hammers were meant for bone smashing. Yeah, John Arnold said everyone deep in tech or finance is in full freak out mode over the pace of AI progress over the past two months. Own index funds and you barely notice, but specific sectors are exploding. Digital and power infrastructure while anything related to a human behind a desk is plummeting.

1:29:23

Interesting. Don't strike your face with a hammer. Strike your crowd with CrowdStrike. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches. Our next guest is available.

1:29:59

Before that, we've got to talk about Japan's largest toilet maker. Toilet maker, according to a UK based activist investor, is an undervalued and overlooked AI play. Palliser Capital sent a letter to the board of Toto last week to make sure make more of its advanced ceramics segment, saying it holds a crucial position in the semiconductor supply chain. Segment generates 40% of Toto's operating profit. Sounds like an insane headline, but we should dig in.

1:30:13

No, it actually maybe sort of makes sense if you need ceramics in the semiconductor supply chain. I wonder if the funniest outcome here is, you know, how, like, we can't get PS6s anymore. PlayStations are out of stock. Will you be able to buy a toilet in the future? No. You will need to sacrifice your new toilet in favor of advancing the techno capital machine.

1:30:47

Ryan, Artificial intelligence Dehaney is responding to Buco saying, what stage of the cycle is this? And says, launch the nukes. Write it all down to zero. Who cares anymore? Because there's a Business Insider article called, after three years of forcing myself to love venture capital, I quit and became a silent disco DJ in Bali.

1:31:08

Let's go.

1:31:27

So that's where we're at. That's where we're at.

1:31:28

But.

1:31:30

Well, we are at the point in the show where we will bring in our first guest, Blake Dodge from Pirate Wires. You can go and subscribe@p piratewires.com Blake, welcome to the show. How are you doing?

1:31:31

What's happening?

1:31:40

Hi. I'm great. How are you guys?

1:31:42

We're fantastic. What has been keeping you? Well, first, introduce yourself. Since it's the first time on the show, I'd love a little bit of your background and then some of what you've been focusing on at Pirate Wires recently.

1:31:43

Yeah, totally. So I basically started my career as a journalist at Business Insider. I covered health care and then technology. I was doing, like, big, scary investigations with a lot of documents and secret sources and stuff. And I got a little bit. Not burned out, maybe a little bit burned. I wanted to tell more optimistic stories about what was going on in tech.

1:31:57

Yeah.

1:32:28

And so that's why I joined Pirate Wires about a year ago, where I've done a lot of that work. Kind of like the white pill case for why you should believe in someone. But then we also do. We do a lot of work that I think Center's original thought. And maybe kind of in the spirit of the contrarian, we'll look at an issue, what everyone else is saying, and then kind of tell people, actually. But actually, this is what you should think.

1:32:29

Truth.

1:33:03

Yeah. And so lately we've been doing a lot of that with the proposed wealth tax in California. We've kind of flooded the zone there and been duking it out, actually, with the New York Times and the Wall Street Journal. So I kind of feel like I'm back at BI all of a sudden.

1:33:05

Exactly. Well, yeah. What has been the response? I mean, you've interviewed A ton of billionaires in California. It feels like the base case is just like, everyone leaves. Maybe they're not all loud about it, but Mark Zuckerberg's not out there. But he did buy a place in Miami, and it seems like he. He might be a Miami resident soon.

1:33:22

Yeah, there's. There's kind of two waves. There's people that were like, I'm going to get out in 2025, so I never have to pay the tax.

1:33:41

Yeah.

1:33:47

There's a second wave, which I think is the Mark Zuckerbergs that are like, I like, if this goes through, it'll get fought. I might not have to pay it. But then I'm still kind of like, hedging, potentially hedging and getting out. And so I think there's. Again, this is. We're kind of in the midst of the second wave of people that are like, I might have to pay it once, but I'm certainly not going to pay it every year for the rest of my life.

1:33:47

Yeah.

1:34:12

Yeah.

1:34:12

A couple weeks ago, Mike Solano published a piece where he interviewed more than 20 billionaires in the state of California, which is like, wow, might make him the most well sourced tech journalist ever. But they literally all said that they were leaving or planned to leave. So that's really striking. That's like a meaningful percentage of the total billionaires in California. And what's really interesting is they're not. They may be leaving because they don't want to pay the tax, but actually the tax is retroactive. So many of them, many of the folks who are leaving probably will still have to pay it if it goes through, but they're leaving anyway because of the kind of overarching political landscape of California. Like, they're. They're just kind of over it. And they find the kind of lefty politics to be too risky, not only to build wealth, but to build companies. Sure, there's language in the proposed ballot measure that has really thrown people through a loop where. So the government has this challenge of tallying people's net worth, which is not easy when it comes to founders of private companies. They're using kind of a shortcut where founders will be presumed to be owners of anything they control. You guys have probably seen the scary math with this on your timelines. But. But basically, since founders often have their shares, often come with outsized voting rights, what this means is you could be presumed to be an owner of 10 times the value of your actual economic position. And that's all subject to a rebuttal. Process and stuff. It's not supposedly meant to be the final word, but I think founders hear that and it's like, okay, this is a significant risk to the business and to my longevity in the state.

1:34:13

How are you thinking about the probability that this actually passes? It feels like something that would be broadly popular amongst. In a direct democracy scenario. I saw some protests that did not seem very widely attended. And so it seems like it's hard, hard to marshal 50 million people or 10 million people that are against this because it's not a tax that affects everyone.

1:36:29

Yeah, yeah. The pro billionaire protest, for some reason, was not well attended in San Francisco. I have no idea.

1:36:59

Certainly not by billionaires.

1:37:07

Yeah, it's like Gary Tan with one sign.

1:37:11

Did Gary go?

1:37:15

I don't think he went.

1:37:16

I actually don't think he went. Yeah. So the politics on the other side are a bit better because the headline of this whole thing is, let's tax billionaires 5% of their net worth one time for this, like, you know, emergency of paying for health care for poor people and so for Medicaid. And so I think that does have a certain political appeal. If it does make it on the ballot. We're sort of hearing, like, mixed reviews on its chances. Mike did some reporting that went out just today, actually, that suggests their signature gathering may be a little bit behind. And then you have a ton of opposition and say, like, Gavin Newsom hates this thing. He's been meeting with Dave Reagan, the head of the union who sponsored the ballot measure, to try and get him to stop. There's also, like, teachers unions and kind of some surprising adversaries.

1:37:17

Well, yeah, there's other unions that are like, hey, you're going to.

1:38:22

You're.

1:38:25

You're trying to. You're. You're trying to get this tax for purely your own benefit. Like, we. You got to cut us in. So it's like the unions, even if they might have been in favor of it if they were going to get a piece of it, there's. There's quite a number of groups that are just saying, like, I don't want this to happen if I'm not getting. Right. Is that like.

1:38:26

Actually, that is kind of how it works. Yeah. Because the unions, in different special interests use the ballot proposition process to raise money, like, or to get more funding streams. And Mike learned specifically that the teachers union is feeling kind of left out. And this is particular scenario.

1:38:45

How has Reagan reacted to everyone leaving? Are they processing this? Because. Play this out.

1:39:10

Yeah. You have a number in mind. You're like, I'm getting 5% of 60 people's wealth, and that's probably like a couple billion dollars. And then there's. And then 20 leave. And you're like, okay, now I'm getting like 3 billion. And then another 20. Like, now I'm getting one.

1:39:21

Yeah. There's also an insane power law.

1:39:35

Yeah, right. Oh, yeah, sure.

1:39:36

So.

1:39:38

So the biggest ones leave.

1:39:38

The people that stay might be the.

1:39:40

Guy who's at 1.2 is like, I guess I'm good for my 20 mil. You can take it.

1:39:42

Yeah. I mean, so far, the. The folks behind the ballot measure have not acknowledged that people are actually, in fact, leaving. They continue to call wealth flight largely a myth, which is crazy. We'll be talking to these people on Twitter. Like, we literally spoke to 20 of them. They literally are leaving the state. It's not a myth, but they point to research mainly looking at the movement of millionaires and just generally wealthy people after taxes are increased. And it's true that in those cases, there's not a lot of mobility. But I think they have made.

1:39:49

Well, is part of the strategy.

1:40:32

Billionaires are the same.

1:40:33

Yeah. Is part of the strategy that this is the best possible branding for attacks like this. And this type of campaign focused on billionaires one time is how you get something like this passed. Then once it's passed, you'll have the ability to kind of like reduce the set of requirements to qualify for it, and you can eventually get down and be eating off of the plate of all Californians, middle class, et cetera.

1:40:35

Yeah, I'm actually, I'm staring at a quote that I have here in my last story. There's a couple of academics whose work, like, heavily influenced this wealth tax and pretty much all wealth taxes globally. One of those men is advocating for a 2% globally coordinated billionaire tax where all of the countries kind of get together and agree they're going to do this.

1:41:06

It's sort of like a one world government.

1:41:33

I literally, in this quote, have a screenshot of Michael Gibson's summary of the Thiel Antichrist lectures. So, yeah, he says it's clearly far from enough. But also what history shows is that what's most difficult is to move from zero to something positive. And once you have something positive, Even if it's 2%, then it opens up a realm of possibilities. And so they say it's one time. They say it's an emergency, but clearly.

1:41:37

What's the takeaway from the Netherlands? They passed this 36% unrealized capital gains tax. It Excludes, I think, real estate and startup equity. But. But what's the thought process there? It seems super bearish for the country as a whole, but any learnings?

1:42:10

I haven't looked at that one specifically. I know that internationally these wealth taxes do have a pretty dismal outlook. The cycle is kind of.

1:42:33

It's very American to be like, ah, we can make it work.

1:42:45

We're built.

1:42:49

It failed everywhere else, but it'll work here.

1:42:50

Yeah. And it's funny too. They're still saying wealth flight is a myth, but part of why these other wealth taxes tend to go poorly is because the wealth leaves.

1:42:53

Can you give us a white pill? Something that I don't think from a comps perspective, don't tax me is going to be effective for the billionaire class. But what should they be focused on in a world where a lot of people are seeing billions of dollars in wealth creation from what they see as slop, what they see as scams, what they see as a variety of water usage, energy price, blah, blah, blah. What are the white pills that you think tech has delivered or is in the process of delivering over the past few years and into the future?

1:43:05

Yeah, I mean, that's the question of the hour. Because inequality isn't, you know, continues to get worse and kind of fuels the politics behind these things. Yeah, I'm kind of a Gundo Stan. Like, I, I believe in this patriotic vision for tech.

1:43:43

Yeah.

1:44:04

And this idea of keeping regular people in mind and building businesses that last and create value and don't just kind of addict people to things that they shouldn't be doing or shouldn't be spending their money on. And I think who knows what billionaires could do. There's a lot of ideas out there. Mike Solana actually just wrote a Christmas wish list for billionaires with like 20 of these really beautiful white pill ideas. One of the easiest things is, you know, building like beautiful public works libraries, statues, like things that people can see with their own eyes and feel gratitude about. Whereas right now I feel like it's.

1:44:05

Not that compelling to be like, don't hate me. I built this short format instead of.

1:44:53

Like the public library, it has the Rockefeller name on it or something. Like there's a lot of examples as you walk through New York City where you see a beautiful building and you're like, oh, yeah, and that's free to the public. Now I'm a big fan of like the Hearst Castle. Like William Randolph Hearst, like built this castle for his entire life, spent all his money, died before it was even Done. And then it just comes.

1:44:58

Or even in California like really ramping up something like an adopt a highway program, like driving around la. The roads are just so, so, so bad.

1:45:20

Yeah. But the tangible. Yeah, the tangible thing that you can see is very, very. It's very impactful as opposed to like the anonymous donation that just kind of works its way through the economy might be more impactful, but certainly less grounded in reality. Anyway, where can people find you? Sign up for Pirate Wires, follow you on X. Where else are you active?

1:45:32

Yeah, yeah, I'm on x. At Dodge Blake piratewires.com we're covering all this stuff every week. We've really flooded the zone and. Yeah, and I feel like too we. We're pro tech in the sense of not being anti.

1:45:55

Yeah.

1:46:13

But we also tend to ground things in a set of values which I think is. Well, I love it personally.

1:46:14

I'm glad. That's fantastic.

1:46:22

Great.

1:46:24

Well, thank you so much for taking the time to come chat with us and we will talk to you soon. Goodbye.

1:46:24

Cheers.

1:46:29

Let me tell you about Railway. Railway is the all in one intelligent cloud provider. Use your favorite agent to deploy apps, servers, databases and more. While Railway automatically takes care of scaling, monitoring and security. And with that we will kick off the Lambda Lightning round because we have Freddy Debar for Substack. He's an independent writer. We're bringing Freddy into the TVPN Ultra Dome from Restream Ready room. Freddy, how you doing?

1:46:30

Pretty good.

1:46:58

Although you know, from Substack still never sounds as cool. Sorry, the Wall Street Journal or whatever, whatever anybody says about like independent media, it's just never going to catch up. But that's okay.

1:46:58

Yeah. I don't know.

1:47:09

Do you think social media.

1:47:10

Do you think something should do a bundle? Do you think subtext should do a bundle? This is a big debate.

1:47:11

The thing is, is like it's like the same question about like why can't I just pay a dollar for the New York Times article I want. Because the reason why is like the finances just don't work out. Like if I would love to be able to do that from a standpoint of like getting people to read my stuff, but my financial life would collapse. It's getting that, that regular income in that sort of makes sense this possible.

1:47:16

Yeah.

1:47:41

I think, I think my view on it is I think the like a. A bundle that is just a. Is systematized via a platform is going to struggle. But a bundle that where you get four or five writers that just basically say we're going to Build a media company together that can work.

1:47:41

Yeah.

1:47:59

Because there's just so many other small things you need to do around compensation and what's fair and who's doing what. And all these different things that I think are. When you have a bunch of personalities coming together, it's hard to just have it be entirely in code.

1:47:59

Anyway, let's move on.

1:48:15

The problem is that eventually, if you bundle enough people, you just have a newspaper. And I probably wouldn't get into the newspaper business in the 21st century.

1:48:16

I love newspapers, though.

1:48:24

Oh, I love them. But I'm not investing in one, though.

1:48:25

No, no. I think it's the time. The days are numbered. I might be the last person subscribing. Anyway, give us a little bit of your background since the first time on the show. How did you get to substack? And then I want to talk about your wager and the future of AI, the impact on the economy, all of that.

1:48:28

Yeah, So, I mean, I'm a writer. I was an academic. I was in academia for years. I used to work for the City University of New York. But now, frankly, I find not having a boss or a schedule or ever having to get up on any particular day to be very attractive. And now I just write books and I write my substack. And, you know, it's enabled me to buy a house and, you know, so it's, you know, it's.

1:48:49

It's a pretty good living dream.

1:49:15

So tell me about your wager. How did this happen? What is. How. How do you come to define the. The actual bet and what's at stake?

1:49:18

Yeah, So I, I'm frustrated by the AI conversation. I think that it is. I don't know if you guys are familiar with the concept of a Mott and Bailey argument. Mott and Bailey, Yeah. So Matt and Bailey's. Yeah. For those at home, it's just like you are. You make a very sort of extravagant argument, and when challenged, you retreat to a simpler and easier to defend argument. So you might say the Christian God is real and built the universe and he rules over everything. And then when you're challenged, you say, oh, well, God's just a feeling and God's in the. In the wind and whatever. Right. That's like a mutton, Bailey. I just think that that's all over AI, where the CEO of Google is saying that this is bigger than fire and electricity, and people are saying it's going to end, death, etc. But then when challenged, it's like, hey, you know, these LLMs like you know, they, they might make going through legal documents, you know, of much more efficient process. There's this constant sort of back and forth.

1:49:28

Sure.

1:50:27

As far as the wager goes, the people in the AI world kind of come from this sort of rationalist, a Silicon Valley sort of culture. And they say you should be very sort of objective and specific in your predictions and you should put money on them. And so Scott Alexander is a guy I've known for a long time, the blogger of Slate, Star Codex and Now Astral Codex 10. He is a AI enthusiast. He was a signatory on the AI 2027 document. So I just, I challenged Scott and said I believe that three years from now we'll be in a more or less normal economy. And that was chosen because, you know, AI 2027, you know, this is like going to 2029. So I felt like it was giving him enough sort of wiggle room. And I just defined a bunch of economic indicators and said that if any one of these indicators are violated, he'll win the bet and I'll lose.

1:50:27

Wow.

1:51:22

And the reason to do that is just I'm looking for someone to put their money where their mouth is about, like, is this actually going to cause a white collar apocalypse? And all these economic sort of things. And I mean, he said no and would prefer to do a 10 year version. So we're kind of looking at that right now.

1:51:22

Okay, so I have some of these. Unemployment must stay under 18%. That. What are we at now? 4 or 5%? That feels like.

1:51:40

But this is, this is the point.

1:51:48

Yes.

1:51:50

This is the Mott and Bailey.

1:51:51

Right.

1:51:52

Dario Amodei, the CEO of Anthropic, last week in a interview with the New York Times said that within the next couple of years, 50% of all jobs are going to be destroyed.

1:51:53

He said 50% of all jobs. I thought it was early stage white collar labor. No, no, no, no, no.

1:52:05

Look it up. He's 50% of all the jobs in the economy are going to be eliminated. Right. And this is the thing that bothers me, this is why I made the.

1:52:10

Bet, because I ran. Yeah, I actually ran the numbers on the new argument, the Bailey, which is entry level white collar work. I mean the U.S. economy is only 60% white collar. Early stage is a couple percent of that. And so you're at a percentage of a percentage. And quickly, if you lose 50% of that, the unemployment rate goes from 5% to 8%, 9%. Like that statement. That new statement can be true, but it cannot be. It can simultaneously Be not that disastrous.

1:52:18

Right.

1:52:45

So the CEO. Not the CEO, but the head of AI science at Microsoft just made a very similar sort of pronouncement.

1:52:45

Sure.

1:52:54

And this is what I find just endlessly frustrating about this conversation is it cannot simultaneously be true that we are imminently facing a replacement of an immense number of jobs in the economy thanks to AI. But also, 18% is like a extravagant figure for me to set for this bet. Right. If you really believe these things. And so I'm just never sure how seriously these AI people take it, in part because the CEO of Anthropic and the head of AI at Microsoft and almost everyone else who gets quoted in this domain has a direct financial incentive to exaggerate the impact of AI.

1:52:55

Yeah, I mean, Scott Alexander did take the bet, though, so he's putting his money where his mouth is and is certainly on the other side of this. Correct.

1:53:41

Well, we are looking at the conditions. He wants to do 10 years instead of three.

1:53:50

Interesting.

1:53:55

And so this is. It's actually turned into a kind of an interesting econometric debate. Right. So people are saying, where did you get 18% unemployment for something like 40 conditions? I listed something.

1:53:56

Yeah, yeah, There's a ton here.

1:54:06

And I said that we had 15% unemployment, you know, five and a half years ago.

1:54:08

Yeah, right.

1:54:14

Because of COVID Yeah. And what I'm trying to do is to set up the bet in such a way that a non AI source is not going to screw me. Right. You know.

1:54:15

Oh, sure.

1:54:24

In the Great Depression, which obviously was not AI driven, we had 28% unemployment at some point. Right. So. And it's actually led to a kind of interesting debate about, like, how do you define a normal economy without letting the natural swings that are common to a capitalist economy?

1:54:26

Yeah, I was listening to it. I was listening to a conversation about AI apocalypses, and the person that was being interviewed was like, well, my P doom from AI is extremely low, but I think the chance of nuclear war is like 5%. It's like they had a high P doom, but not because of AI, which is like a very hard thing to wrestle with. And that's what you're getting at.

1:54:43

Yeah. I've talked on the show a bunch about a bunch of these different groups using basically fear as a kind of motivator to get the. To kind of bend the world. Right. So if you want people to adopt AI, you should tell them that it's going to, you know, create such. Such insane changes in the economy that any company that doesn't adopt as Much AI as possible today is going to, is going to be destroyed. Or if you are trying to get, you know, as many young people to adopt a product, you tell them, well, like all jobs are going to be wiped out. Or if you're pitching a bunch of, if you're pitching investors on Wall street, you can say, well, all these jobs are going to go away. So it's effectively the incentive to use. Fear is very obvious in all of this. And I think it's now coming back to bite a lot of these people because the broader populace is saying, I don't want AI, I'm good, I don't need it. Even though they're using the products and they love them. Like almost everyone can tell you an incredible story about AI in their personal life. Like even if it's as simple as like, I made this like cool illustration for, you know, my grandma for her birthday and she loved it, right? Or I used it to learn about this thing. And so I think it's interesting is like using this like intense fear based marketing to justify, to kind of catalyze adoption success with fundraising, et cetera. But then again, it's kind of coming back to bite in the sense that everyone's saying, well, no data, I don't want a data center in my backyard, I don't want my company to even be investing in this, et cetera.

1:55:04

I mean, speaking of fear, you just mentioned nuclear war, right? And I just think that you can believe as I do, that AI is going to be a very meaningful technology. But the fact that people are more scared of a robot apocalypse than nuclear war. Look, right now Russia has multiple bore class nuclear submarines off the coast of the east coast of America that have the capability of raining nuclear fire down, thermonuclear fire down, all up and down the seaboard, right, the eastern seaboard. I mean, like, you know, a single modern thermonuclear bomb detonated above the Central park would destroy 80 plus percent of the buildings in Manhattan and hit parts of New Jersey and Connecticut, et cetera, right? And again, this is the Martin Bailey thing, right? Which is like you might say, well, that's a very extreme scenario, but every day I am opening up my web browser and reading about, oh, AI is going to exterminate the human race or AI is going to put us into this utopia where no one is ever.

1:56:55

Going to die again.

1:58:01

And it's like part of what I'm trying to do is just claw out like a normal space in this, right? To just say there is a very Obvious future where these tools are meaningful, eliminate some jobs, have a lot of cultural importance, but where we're not suddenly faced with a fundamentally different version of human life.

1:58:02

So if it's not nuclear war and it's not fire and it's not electricity, it's also not the fax machine. Are we talking about mobile, cloud, the Internet? Like, how big is this thing? What does your world model look like for how AI progresses and diffuses through society?

1:58:26

Sure.

1:58:47

We have to understand there's a different kinds of importance and different kinds of influence. So you've mentioned the Internet and the mobile phone. Okay. Obviously the Internet and specifically the smartphone, the iPhone have had massive cultural and social impacts on the United States. It would have shocked people in the mid-1990s to learn that we have about the same productivity growth and about the same GDP growth in this country now that we did back then. Right. Like many, many people were invested in this idea that this sort of, this missing GDP growth, we're at half of what we were in the mid-1960s. A lot of people thought, okay, the Internet's the thing that's going to restore us. The Internet is very meaningful and it's very influential. Right. And yet economically, it hasn't had the effects that are expected. And that's just like, that's how history works. You know, that's just like there is a. You always have to bake in the percentage to the degree to which, like, there's regression to the mean. Right. Like, we always seem to find ourselves way back to this sort of mundane reality. And I look at things like when everybody got so depressed and disappointed after ChatGPT5 was released because they thought it was going to be AGI, and you had all of these lonely guys who were like, oh, this is just going to change life forever. And now everything's going to change. It's like, no, it's. Things are going to change, but slowly and in a distributed fashion. And you have to keep planning for normal life.

1:58:48

Counterpoint. Maybe this time's different.

2:00:17

Maybe this time is different, but absolutely. So show me. I mean, here's the beauty of all this. The beauty of all of this is like, if the real stuff happens, you're not gonna have to convince me. Right. Like, if we really have AGI the way people think we are, no one's gonna disagree because the effects are gonna be so profound, there's gonna be nothing to disagree, agree about.

2:00:21

Okay. How did you interpret this latest piece in the Financial Times from Eric Brian Falson? I can't pronounce his last name. But it says, while initial reports suggested a year of steady labor expansion in the United States, the new figures reveal that total payroll growth was revised downward by approximately 400,000 jobs. Crucially, this downward revision occurred while real GDP remained robust, including a 3.3 growth rate in the fourth quarter. This decoupling, maintaining high output with significantly lower labor input is the hallmark of productivity growth. His own updated analysis suggests a US productivity increase of 2.7% for 2025. This is nearly doubling from the sluggish 1.4% annual average that characterized the past decade. It feels like we're seeing glimmers of something changing. Is that not a sign?

2:00:43

I mean, we'll see. Right. We have to actually like look at the, at the numbers as they come down the pike. We also have to be aware that like, there's a lot of built in incentive for people to ascribe these changes to AI. So, for example, cutting a lot of jobs is very unpopular and firms tend to be sensitive to that unpopularity. Right. And saying, well, hey, AI came, we didn't make the decision. We just, we had to sort of like that's a very sort of easy thing to do.

2:01:39

Would ever do that.

2:02:08

That doesn't make any sense to what to say that AI, what's the reason to do it.

2:02:09

Yeah, we'll use anything as air cover.

2:02:14

Yeah.

2:02:17

And so I just, in general, I caution people to say, look, it's like I've said this before, you know, when I was in high school, a very distinguished scientist came to my science class and he was on like the board on like the national science, some sort of board of the National Science Foundation. He was like a geneticist and he came and he said like that he envied and also felt bad for us because the Human Genome Project was going to so radically change human life that we were going to see things that he couldn't imagine. But also the job of doctor wouldn't exist in 10 years. And this, I was in high school in like 1998. This probably happened.

2:02:17

So, you know, studying medicine.

2:02:58

Right, right.

2:03:00

And you quit.

2:03:01

Right.

2:03:03

If you can, actually. But this is an exercise that people can do at home, which is to go back just to Google and look at the predictions about what people thought the Human Genome Project would do. Obviously genetic research in general is very important, but there was a real belief among very intelligent and highly credentialed people that we were on the verge of something absolutely humanity changing. And life's more complicated. Complicated than that. And again, like I Just, I want AI boosters to do more showing and less predicting.

2:03:04

Right.

2:03:35

Show me. Right, like, show me the change instead of predicting the change.

2:03:36

Yeah. Well, thank you so much for taking the time to come chat with us. This is really fun.

2:03:40

Yeah, yeah, we have this, we have this conversation. We have these debate. We have these, you know, kind of debates and conversations all the time. Specifically the. There's a popular influencer on Instagram that every time a tech company does a bunch of layoffs and says, we did this because of AI, he takes that and like, makes this crazy story up around how, you know, AI is just immediately causing all this job loss. And I'm just looking at it as like, I know the company, they had a lot of bloat. They're getting some. They're getting some efficiency, efficiency increase because of AI. But certainly it wasn't like the 2000 people or whatever were sitting there being like, oh, yeah, I just onboarded this new agent and now it does everything that I did, including going to all the meetings and sitting around all day.

2:03:44

Yeah. There's an incentive on both sides. Both the AI boosters and the AI bears sort of have an incentive to be like, it's going too fast, it's going wrong. If you love AI, you want to say it's going really fast. If you don't like AI, you want to say, it's going too fast. They're both sort of aligned, so you get this, like, super cycle. Very fascinating. Well, have a great rest of your day and thank you so much for taking the time to come chat with us.

2:04:33

Cheers.

2:04:55

Let me tell you about graphite code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster. And our next guest is in the Restream waiting room. We have Sohel Prasad from Destiny.

2:04:56

What's going on?

2:05:09

Hey, how's it going?

2:05:10

Great. Thank you for having me. Great to finally have you on the show. We met once. I think it was too long ago to remember what we were even talking about, but it's great to. Great to see you again and a lot going on in your world. So why don't you kick off quick, kind of background on yourself and then let's talk about Destiny.

2:05:12

Sure. Great to see you. Thanks for having me. Founded Forge, a stock market for private companies back in 2014. Took that public in 2022 and then Schwab bought us last year and in 2020 started a company called Destiny to bring public access to private tech. So along the way I realized that there's such a big inequity. Most people in the world that use, you know, all the companies that are advertisers for you guys that are tech companies in our everyday lives, you have no way of owning that and wanted to create a way for anyone to own a piece of that future from the convenience of their brokerage account.

2:05:30

Very, very cool. I've been following Destiny since you launched it. How long did it actually take to get it up and running? There's a number of groups now that have seen what you've done or maybe had a similar idea and are trying to bring products to market. But you've got a nice little head start. I guess the journey really did start with Forge. Probably couldn't have pulled Destiny off without having having done that first and had all of that understanding of the market. But yeah, what were kind of like what was the logic around the decision for kind of the current structure and all the decisions that made that went into building the initial product and then kind of where is it going from here?

2:06:11

Sure. Thinking about what the dream product is, it kind of looks like QQQ for private tech. That's a dream. Anyone can buy it on any given day, anyone can sell it. It has exposure to a broad base of private tech companies. Now, structurally, there are definitely challenges. You know, an open end etf, you don't have enough liquidity in the underlying private companies that would support the creation of shares on a given basis or redemption on a daily basis. So we looked across the market at what kind of structures are possible and ultimately decided that a listed closed end fund gets that intraday liquidity. It's listed on the nyse, it's accessible, but you're still able to go invest in these companies. So it took us quite a while. We spent 19 months waiting for registration with the SEC. The first time we listed in March of 2024 and then we spent another 15 months waiting for the SEC to approve our shelf.

2:06:56

Overnight success. I love it. Walk me through the mechanics of the closed end fund. That means that you own shares in private companies. When I buy shares in Destiny and then I go to sell them, I'm not selling them to you, I'm selling them to Jordy. Is that right? Or someone else in the market.

2:07:58

Exactly. So we trade Intraday on the NYSE market, just closed. But anytime you want, you can go into your A Schwab account, you can buy dxyz, you can sell it and it's all effectively secondary market trading. You're not creating or redeeming shares now, last year we got approval from the SEC, got effectiveness to raise up to $1 billion opportunistically. And that allows us to issue new shares, use the capital we raise from that, and then invest in new companies.

2:08:19

Okay, so if there's a. If there's a delta in nav to market cap, it's because there's expectations about what you'll buy with that, with those shares. Maybe.

2:08:48

Yeah. Early on there was a huge delta as people found out that this was even possible back in 2024. And I think that was just people realizing, oh, wow, I can actually do this. I don't have to go anywhere, I don't have to make a new account. I can buy this. And people got really excited. And now that premium has come down, just as we've gotten more mature, I kind of. We had a decision to make when we brought it to the market, which is we wanted to have a portfolio of the top 100 private tech companies. Should we wait until we build a whole portfolio? Should we just list it with no companies in the portfolio? And we decided, hey, we'll build it effectively in public. So we listed with 20 some odd companies. Today we have 35. And we're kind of growing that over time.

2:08:58

What, what were the conversations like originally? With companies, obviously you're not always buying direct access or not getting direct exposure, but you're buying into SPVs or things like that. But what were the conversations like in the beginning? How are they going now With Robinhood's new product? It sounds like at least some of it is actually being authorized by the company or they're effectively signing off on it or cool with it. But I'm sure in other cases companies are less excited about it. But like, give it, give us the. An overview there.

2:09:43

Yeah, but with the secondary market, it's always, even for the last 15 years, been case by case basis. Some companies have really active secondary markets and they facilitate it. Others try to keep more of a tight control. From day one with Destiny, what we did is make sure we have flexibility to invest across the board. So we've invested in companies that are doing primary rounds. We recently invested in a company called Skilled AI. SoftBank led that round, and we were a part of that round. We partnered with Beast Industries and are working directly with them. And then at the same time, we can also opportunistically buy through secondary markets. So sometimes there are employees or early investors that need liquidity and they come directly to us and we can buy from them.

2:10:23

What part of the. Part of why Destiny is exciting and other products are exciting is that anyone can get exposure to the asset class. The challenge is that oftentimes by the time you know a company's amazing and it should be in the Destiny 100, it's already been marked up to 50, 60 billion or whatever the number is sometimes 80, in the case of SpaceX, hundreds of billions. What are your plans around? Obviously picking companies at the super early stage is hard. It's also very risky. Part of the appeal of Destiny is that you're getting exposure to companies that we already know are solid, they're well capitalized, they're hopefully leaders in their market. But how are you thinking about qualification for Destiny and would you ever go earlier stage? Is that too risky, all that stuff?

2:11:08

Yeah, that's one of the reasons we decided to call it the Destiny Tech 100 and Target. Building out a portfolio of 100, you want to have enough range in there so you can have some of the early unicorns, you call it 1, 2, $3 billion. Companies that have in many cases product market fit, they have growth, but they have, you know, more room to grow as well as at the same time some of the larger companies that are tens now hundreds of billions of dollars and beyond. And so we will have over time a mix of those companies so that we can kind of get some of those earlier stage, albeit still late stage bets and others that are, you know, the blue chip mature companies.

2:12:10

Oh, how do you think about the actual investing strategy? Is, are there any like, I mean you mentioned like post unicorn, are there heuristics or firm rules that are in a bylaw, in bylaws or are you just sort of like the fund manager and you're tasked by the shareholders to make the best investments that are according to your own intuition, skill, obviously your incredible background, all of that. But how do you think about the actual capital allocation question?

2:12:52

Yeah, so right now the portfolio is in progress. So you look, sometimes we might be overweight one company for a while. Space X was greater than 40% of our portfolio. That's come down. And so we're kind of in this building phase. As we reach a more steady state, we want to be reflective of the late stage venture back ecosystem. So we actually publish rules and eligibility criteria on our website. We're like, you know, companies had to raise recent rounds of financing, the other kind of growth metrics and TAM that we look at. But generally speaking, we don't want it to be, you know, whatever we like. On a given Monday, we want to say, hey, we Want overall late stage venture backed exposure. And where we get to use our discretion is hey, what's the right time to buy this? What's the right structure, what's the right pricing, things like that, where if you just had an index, you would be a forced buyer at any price at any structure. And so it gives us the ability to go and find unique opportunities in the primary secondary markets and actually invest behind that.

2:13:24

What's the process when company in the portfolio IPOs, you have a number of portfolio companies that will be IPOing or should IPO this year, there's a lockup period and then I imagine you guys plan to exit those positions and then recycle the capital. But how are you thinking. Thinking about that?

2:14:30

Yeah. So we want to be long term capital partners for the company. And so generally once a company goes public, we're not selling our shares immediately. We'll wait for a few years. Instacart was one of the companies in the portfolio that went public and we waited for a few years before we slowly started divesting that position. And so that's how we're trying to balance the two things, which is our public shareholders are looking to us for exposure into private markets, but we also want to be great partners for companies and smooth their transition as they go public.

2:14:52

That's amazing. Well, congrats on all the progress.

2:15:23

Talk about the most recent acquisition or investments. You guys are in anthropic for $100 million. Break down some of the new companies.

2:15:29

Yeah, so we just announced a couple weeks ago that we closed $100 million investment secondary purchase in Anthropic. I mentioned skilled AI beast industries.

2:15:41

He's like, I can't let you get out of here without a gong. I knew it.

2:15:56

That's right. Very cool. Well, yeah, we're excited to continue to follow Destiny and the overall market. You guys have definitely led the charge. Second time leading the charge. I felt like with Forge, you guys were very ahead of the curve and ahead here as well. So great to have you on.

2:15:59

Thanks. More to come.

2:16:19

Amazing. We'll talk to you soon.

2:16:20

Cheers.

2:16:22

Have a good one. Let me tell you about Labelbox, reinforcement learning environments, Voice robotics, evals and expert human data. Labelbox is the data factory behind the world's leading AI teams. And let me also tell you about Vibe Co, where D2C brands, B2B startups and AI companies advertise on streaming TV, pick channels, target audiences, measure sales, just like on Meta. And before we bring in our next guest, we have some breaking news. It's Jensen's birthday from Nvidia. And guess what? He was born on the same exact day, same year as Michael Jordan.

2:16:22

I thought really is the Michael Jordan of GPUs.

2:16:55

Dylan Averscotto on our team is such an underrated poster. Got 8000 likes just with two screenshots. One for his birthday, the other Michael Jordan playmaker. February 17, 1963. Happy birthday to Jensen and thank you for all you do. I'm going to tell you about Shopify before we bring in our next guest. Shopify is a commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces. And now with AI agents, and without further ado, let's bring in our next guest, Travis from Nash Optical. Travis, how are you doing?

2:16:57

Hey, nice to meet you guys.

2:17:31

Nice to meet you. Thanks for hopping on.

2:17:32

Big, big, big day.

2:17:34

Huge day.

2:17:36

We saw what else happened on February 17th. We launched on February 17th as well.

2:17:37

That's true, that's true. Add it to the list. How much did you raise? Break it down for us.

2:17:43

Yeah. 50 million total across our seat in series A.

2:17:48

Boom.

2:17:52

Nice.

2:17:53

Congratulations. First time on the show before, before we get into mesh, introduce yourself. What got you into this, all that good stuff. Yeah, yeah.

2:17:53

I'm Travis Brashears, one of the co founders and CEO here at Mesh Optical. And I work, I've been working on laser since I was in high school and with professor at UCSC Philip Lubin. And then.

2:18:03

Oh, interesting. So in high school you were, you were basically studying at ucsb. You're studying the blade, the laser beam. Yep, I was studying the beam.

2:18:20

Studying the laser.

2:18:30

That's right.

2:18:32

Been one with the laser since I was, you know, 15. And then I went to SpaceX and started working on the space laser comm system there and got to the really fortunate opportunity to design and work with a really awesome team there on, on the free space laser comm term terminal.

2:18:33

Cool.

2:18:48

So talk about living the space laser dream. Incredible stuff.

2:18:49

Yeah. So talk about the actual product. How much of this is still R and D ready for commercialization? Then I want to talk about the implications, like how this product actually rolls out into the world.

2:18:54

Yeah.

2:19:08

So our first product is a pluggable transceiver that is used in all of the GPU clusters. So you just mentioned Jensen.

2:19:08

Yeah.

2:19:15

Like the Nvidia GPU clusters. For every one GPU, there's like four to five of these optical interconnects that help connect all the GPUs together through the networking through making sure that they can be like a coherent cluster. And so the first product we're making is what we call like a linear pluggable optic. And it deletes a really expensive and costly like, like power hungry thing that is called a Retimer or dsp. And so it allows the people who deploy compute to save a lot of power. And so that first product is just simply allowing those GPUs to connect over optical and deleting some power, power hungry chip inside.

2:19:16

And this is within a data center or in between different data centers?

2:19:55

This is within the data center, yeah. So our first, yeah, our first product is, is, yeah, within a data center. They connect them with fiber optic cable on either end. And yeah, and so the, and these.

2:19:59

Are, these are already, already in market. You're selling these? Wow.

2:20:10

Well, ours are there. We're standing up the production line so we, we care a lot about co locating the engineering talent with the manufacturing. One of the key things we learn at SpaceX is to, to be like right where this stuff is built. So behind me is the manufacturing line and we'll start testing in the next month here some samples and then start scaling production right after that. And trying to get to millions of units in 2027 is really where the high volume starts to come into play.

2:20:15

Is this the kind of thing where it's really just execution risk, like can we build this at scale? And if we can build them, there's insane demand and it's less demand risk.

2:20:47

Yeah, the demand we sort of think of as infinite because you know, the more intelligence we have, the more intelligence we have, it just like is more compute. And so whenever you see people deploying more and more compute, they need more and more transceivers. And so as intelligence scales with compute, so does transceiver demand.

2:21:01

$50 million in the bank. Where are you based in the company? How big is the team? What does the next 12 to 18 months look like for you?

2:21:22

Yeah, we were based in Los Angeles. We're in Gardena, California.

2:21:30

Let's go.

2:21:34

It's a little.

2:21:35

Thank you.

2:21:37

Los Angeles needed a win.

2:21:38

Yeah, yeah, yeah. A little outside El Segundo, but yeah, we're going to bring Gardena onto the map as the laser hub of the world. Love it. And yeah, so we're about 15 people now and growing quickly and need to move to a bigger building now.

2:21:40

Good sign.

2:21:57

Are there like two buyers for this? Are you going to do deals with every data center builder, every Neo cloud, just the hyperscalers? Are you going to Be a supply chain partner just to Nvidia or just to amd. What does your business look like at scale?

2:21:58

Yeah, we want to sell. Our long term goal here is to be able to connect all, all things with optical photons and whether that's an interconnect in a data center or an interconnect in space, whether that's free space or in a fiber. But to start out, to answer your question specifically, anyone who deploys compute on the ground, we will try to sell to. That could be a NEO cloud, as you mentioned. It could be a hyperscaler. We have a strategy that we want to follow to kind of follow our volume, match our volume to our potential like future customers and make sure we don't start all the way at like really high volume. Because obviously we need to scale our line. We care a lot about getting our manufacturing done here in the United States. One thing about all these transceivers that are made today, they're all made overseas. They're made mostly in China and Thailand. And so no one has like really stood up. These high precision what we, what they're called flip chip, die bonding or pick and place machines. Like when we bought the most high volume flip chip dibonder, they asked for your Chinese social credit number on it because no one buys them here.

2:22:16

That's crazy. Do you think that we'll get any mesh products in space in the next five years?

2:23:29

Yeah.

2:23:39

That's awesome.

2:23:40

There we go.

2:23:41

2027. You think of what I'm thinking? Valentine's Day gifts. Here we go for that special person, lasers for Valentine's. Crazier things have happened.

2:23:41

We're big, we're big fans of girlfriend. Yeah, they keep saying they want some metal, you know, so get them some hardware.

2:23:53

I was a laser cat for Halloween once.

2:24:03

No way. Oh, that's cool. Yeah. Talk about like, what is the shape of like actually working in the factory? Is this stuff risky or does it all happen in a clean room? How much of this is like a TSMC type fab? Like what is it like today?

2:24:05

Yeah, the clean room is here. We took some pants, we took some panels off to get the machines in. But yeah, it's a pretty like we take the approach of like question the requirements and delete the part of process if we need to. And you know, we start in like a semi dirty environment to make sure like we don't want to go overboard. Right. You don't want to just go all in on a clean room when you don't have to. So actually back at SpaceX, we started making the space lasers in a tent. And so there's actually a tent behind me, in front of me. Sorry. And so you don't want to go too all in on it has to be in a clean room. You do tests, end of line testing and qualification to make sure that if it starts to impact your yield, then you would implement procedures and processes to keep it cleaner. This is like a pretty good clean room, but not the best. And so we'll see how our yield looks with this one and we'll implement stronger strategies if we need to. But all of our semiconductor packaging is happening here and we get some dyes from other foundries that are all outside of Asia and then we bring them here and package them.

2:24:22

Last question from me, what was the biggest lesson you learned from working at SpaceX?

2:25:34

I mean, just what I said is like, question the requirements and delete the part and process. It's like, it's so simple, but it's so useful. And like when we're designing something, you want to try to know why each part is there. So in our design, we've deleted quite a few parts and most people don't delete that part, but it ends up work. Anytime you delete a part, you delete a potential failure mode. And you want to be like a really reliable system. You need to delete as many parts or processes as possible and also helps you assemble things faster. So that was one of the big lessons I learned.

2:25:43

Yeah, that feels like, I don't know, easy to say, really hard to do in practice. It feels like you have to experience it. I've heard that a million times and I'm sure that there's things that I could delete, like even my daily workflow that I haven't figured out how to do. That's a. I Love that.

2:26:19

Yeah.

2:26:35

SpaceX is a company where like, you learn learning things the hard way in the most extreme way.

2:26:36

Yeah.

2:26:41

You ship us off, you ship a piece of software, it doesn't work. It's like, okay, let's patch it. You ship a rocket. It has some like, dependency that you didn't think was maybe that important and it blows up. And you gotta live with that or.

2:26:42

The whole laser mesh doesn't work.

2:26:55

So let's hope that doesn't happen.

2:26:57

That would, you know, like putting a kid in charge of that is really a crazy thing that SpaceX does is they hand the baton to a really young person and put the whole company, like the company on those people. And I think that forges things like within people to be able to deliver and then the delete the part and process like helps them understand the whole system really well.

2:27:00

I love it.

2:27:23

Well, we are not far from Gardenia. Yeah, come by, come by for your next appearance. I've got a feeling you'll be back on the show this year.

2:27:25

Great. Yeah, we'd love to be there. You guys are welcome to come anytime as well.

2:27:34

I love it. Thank you so much.

2:27:37

Lasers. I would love to have a great.

2:27:39

Rest of your day. We'll talk soon. Let me tell you about Plaid. Plaid powers the apps you use to spend, say, borrow and invest securely. Connecting bank accounts to moving, move money, fight fraud and improve lending now with AI and you saw it at the opener. Jordy, get those juggle balls ready because it's time to tell you about TurboPuffer, serverless vector and full text search built from first principles and object storage. Fast 10x cheaper and extremely scalable.

2:27:41

Team sent me these little puffers. They're incredible.

2:28:05

Jordy's generally very fast.

2:28:08

They're gonna be hard to keep here at the studio.

2:28:10

Well, without further ado, we have Evan Spiegel from Snap in the TVP Ultra Dome. Good to see you again, Evan. Welcome to the show. Welcome back to the show. Thank you. Thank you so much for coming by and stopping by. The TVP and ultradome. Always good.

2:28:12

Outsuited me. You outsuited me.

2:28:28

That is a beautiful suit.

2:28:30

It's always a great excuse to wear a suit. My wife was like, where are you going today?

2:28:31

I like, I like the buttons that don't show through. I don't know what that's called, but that's a touch of like, some. It's very tasteful.

2:28:35

Thank you. I appreciate that.

2:28:41

Are you following the taste discourse? People are saying that taste is important. Do you have a stance on this.

2:28:43

In the context of building software?

2:28:48

It's more of like a post AI thing. Like AI is going to be able to do everything but not taste. And it's just like it's sort of always been obvious. But it's also fun to write about. It's fun to talk about. There's a whole bunch of interesting examples.

2:28:51

But it's funny you say that because our designers are literally becoming engineers right now. So it's kind of like, you know, I mean, if you think about like 10 years ago, even the power dynamic in a company, the hard part was building things. Now the hard part is having a great idea. I think taste is important.

2:29:01

I guess the question I was joking about earlier was there's two ways to build a new consumer product. One is you a b test the color of the button, and you just look at the data, and that's more of the engineering mindset. And then there's the tasteful approach, which is maybe like, I just know, green, the right color for my brand. Did you engage in both throughout your journey? Is there a place for both? How do you see those two? The gut instinct interfacing with the engineering reality. Somebody pulls up the chart and they tell you that it's got to be blue, but, you know, yellow's right.

2:29:18

I think for us, there's a huge difference between generation and iteration. Right. If you're trying to come up with a new idea, it is really, really important that you can exercise your sort of creative opinion or judgment. I mean, you know, the reason why we chose yellow is there were no other apps in the top 100 that were yellow. So that was like an easy one to stand out.

2:29:52

We didn't have to monopolize yellow.

2:30:09

Verticalized yellow, yeah.

2:30:11

U.S. and McDonald's. But I think, you know, what becomes very important very quickly is that you're able to iterate, you know, so once you put something out there, a B, testing, experimenting, that that really helps. Especially as you have a big organization, you don't want to bottleneck people's experiments. So anyone can experiment and learn.

2:30:13

Yeah, it's interesting. One way to think about it is I feel like executives thrive if they have great taste because they have a lot of people coming to them with work or projects, and it's their job to decide what are we actually going to focus and prioritize. And now anybody can create 20 different concepts for a website, and so they're having to choose from that to then go up the chain and decide, okay, which one of these should we actually implement? But there's like, taste is becoming more important because now it's so much faster to just create anything. So at every level of the stack of the organization, you have just, like, more things to choose from. And taste is just choosing taste in your personal life is like choosing like, do I get this jacket or that jacket, or do I put use this flooring in my house?

2:30:30

Or how many logos should be on my shirt? Yeah, that's great. Give us the news. Massive milestone. What happened?

2:31:16

Well, I literally came here for the gong. You know what I mean?

2:31:26

It's a great strategy. We got a bigger gong since you were here last.

2:31:29

Is this a new. Is this like for Year of the Horse?

2:31:36

No, we were early. We were Early. Yeah. Yeah, we were early. It was really funny. It was so funny. So, so we were walking by the store and John and I are walking and I look inside. The store is closed, but all you can see it's like kind of dark in there and there's this massive. It's at the. Yeah, massive horse. And I was like, we need one of those. Immediately. John's like, what do you mean we're not going to be able to get like a horse? And then we look on this website for like a few thousand dollars, you can get this horse. I was like, the hardest part of.

2:31:38

Buying the horse was convincing the production team that we actually, actually weren't joking. Cuz Jordy sends it in the chat, hey, we need a, we need a horse statue. And he's like, oh, this is funny. And they were like, no, we're seriously like, okay, he's joking. And we're like, no, actually, go figure it out. This is your job. Anyway, we're not here to talk about.

2:32:08

Congratulations on the horse.

2:32:21

Thank you. We got a horse. You got big milestone.

2:32:23

I think the horse was here last time, but it was wrapped in Christmas lights and we had a massive Christmas tree and there were so many other things going on in the studio. You gave us that very nice Christmas ornament, which we love. You signed it, but it was distracting from the horse. But now the horse is front and center. But more importantly, your direct revenue is front and center. Give us the news.

2:32:26

Yeah. So we've reached a billion dollar annual run rate on our.

2:32:44

Oh, wow.

2:32:48

Thank you.

2:32:49

Incredible.

2:32:56

Is the job finished?

2:32:57

And 25 million subscribers, that's huge. So I think that's like es ESPN size for subscribers, which is like next stop Hulu, you know, but really exciting for us as we work to diversify, you know, our revenue and create this, this whole new business line.

2:32:59

What was the like narrative narrative violation too, around social media? Right. There hasn't been a lot of people will pay for entertainment products, but there hasn't been a bunch of like scaled actually like a social media product with, you know, that kind of sass.

2:33:11

Yeah.

2:33:28

What was the reaction like when you initially launched subscriptions?

2:33:29

Well, I think what's so cool is people are really passionate about Snapchat, so they want all these new features and they're asking us all the time like, hey, can you chat backgrounds or can we have a Bitmoji pet or whatever it is. And in the past we would be like, oh man, this is really a feature for power users. Right? Like we can't Build this like for a billion people. So this gave us the justification and the resources like okay fine, pay us two bucks a month. Have your Bitmoji pets and your chat backgrounds and all this fun stuff. And so people just keep the requests coming. We keep building all sorts of fun stuff and actually it's great for the team because otherwise we never would have prioritized all these really fun features.

2:33:32

How do people actually submit requests?

2:34:07

Literally email, email, email, customer support. You know, we do like, you know, research and things because a lot of.

2:34:09

The tech companies, it feels like they're on this list directly.

2:34:15

Well, it's evanap.com, so it's like a little too easy to. It goes like straight to my phone too.

2:34:18

We love that.

2:34:25

Dangerous.

2:34:26

Dangerous to say that on this show.

2:34:27

So yeah. What has been the key to scaling revenue there? Has it been just driving increases in ARPU or just onboarding more and more people into the premium product, Doing more top of funnel like bringing in these prosumers users as net new users re engaging people. What's been working?

2:34:31

Yeah, a big focus has just been continually dropping new features, letting people know about those features, creating new entry points into the subscription service through those features. One of the big things that we rolled out last year was memory storage. So we've got people who are storing a lot of memories on Snapchat. So we give like five gigs free. But if people want more than five gigs of storage, they can either pay just for the memory storage or they can join Snapchat Plus.

2:34:51

It's so funny because I remember when Snapchat started, everyone was like, oh this is genius. They don't have to have any cloud storage costs the business and now it's like, oh well we're in the business but we have a monetization scheme on top of it.

2:35:16

Well, it's 10 years later. It turns out there's a lot of cloud storage costs we were paying them.

2:35:29

I've seen the Google belt suffering. Have you seen demand for AI features? And what does demand for AI features in a consumer context look like?

2:35:35

Absolutely. I think one of the really exciting things, people don't realize how widely used the Snapchat camera is for generative AI, you know, images and videos. I think in Q4, 700 million people use generative AI lenses. So those are like our camera editing tools. And we have a feature called Lens plus which basically takes some of the most cutting edge genai features, video generation, those sorts of things and puts it behind a paywall. So if you want the most Advanced Genai image and video editing features that's part of Lens.

2:35:46

How have you thought about using camera as the end to end editing suite versus sort of bifurcating them? Looking at what TikTok and Capcut are separate. Edits and Instagram are separate. When do you want to go separate? When do you want to consolidate everything?

2:36:14

Generally for Snapchat, one of our strengths is how much content is actually created in our camera because it's much more more authentic. And what we find today, especially because everything is so overly edited and stylized, because everything is created with generative AI. What our community tells us all the time is that we want authentic original content. So for us we really focus on stuff that's actually captured and made in our camera rather than uploaded. And even as we think about the types of content we distribute on Spotlight or Boost in Spotlight for example, we're thinking a lot about what's actually made in the Snapchat camera. And this stuff is hilarious, but not edited in the same way that it might be on other platforms.

2:36:29

Have you thought about how agents will take hold in a social media app? I've been trying to think about this. The Manus acquisition. What does it look like? If I have an agent that can go and work its way through my social network profile, I could kind of tell it to like every comment that comes in that's positive and it could do some sentiment. I don't know if I actually want that. How does that play out once you get to models that can actually run in the background? It's not just I ask for a question, I get an answer or I say replace the background with a beautiful forest and it does it. Have you thought about any of that yet?

2:37:07

We early on brought my AI into Snapchat and that was like great. A great proving ground to experiment with things like personality, memory, all those sorts of things, or being able to bring my eye into group chats or conversations. So I do think it's been useful in that regard. Certainly the my AI use case is very utilitarian. We see a lot of just questions, homework help, that kind of stuff. On the Agentix side, I'm much more excited about what's happening inside the business. I think the potential for business transformation is off the charts. I think if you look at small and medium size companies for the last 10, 20 years, they've almost been like left for dead. Everyone's been so excited about mega cap companies. I think the next 10 or 20 years, the efficiencies that small and medium sized businesses can Drive to grow using agents is going to be off the charts. So I think that's like that to me is where I'm most excited.

2:37:50

So is anyone writing code anymore? Are you vibe coding stuff now? We see every level of the spectrum. It's either the CEOs, Toby is or no one's writing code. It's always at the extreme. But what's your experience?

2:38:40

Well, it's not vibe coding anymore. It's agentic engineering.

2:38:53

Yes, yes, yes, yes.

2:38:55

I think what's really interesting about what we're seeing in Snap is that to some degree, because the company's been around for a while, it's operating at two speeds. There are team members who have fully embraced agentic engineering and who are essentially not writing code. And then there are other teams that are still operating in a more traditional way. So because this change is happening so, so quickly, one of the things we're very focused on is driving these tools through the company, really making sure that folks embrace this new way of working, helping train folks to do that. Because certainly for quite a number of folks, they are not writing code the.

2:38:57

Way they used to.

2:39:31

What's the next development that you're most excited about? Is it just understanding the code at a deeper level, sort of like a higher IQ model or thinking in systems and scalability? It's not some tiny app. There's so many users on here. One tiny change can have massive ramifications across a database. The stakes are a lot higher. So what are you looking for in the advancing in the tools of AI tools to actually improve your business?

2:39:32

Yeah, for us it's really just right now about building agents across the enterprise. So whether it's, you know, somebody reports a bug, the agent goes out, figures out who else is reported a bug, like it actually tries to go figure it out. Right. Proposes a fix. Right. Those sorts of things. Or you know, you look at our sales team, right, and all the work they're doing, everything from really trying to understand a client's objectives, generating insights for them, putting that together into a presentation, mapping it to our, you know, advertising solutions. Like, you know, I think there's just a huge opportunity.

2:40:05

Yeah. Even. Even thinking an advertiser that spent, spends $20,000 a year with you guys should in the relative near term get the same type of presentation and like, almost like high touch experience that somebody spending $10 million should get. Right. And that doesn't feel like a lot of that is like people making slide decks, like really being on it, like being timely with like kind of feedback or things like that. That feels like very within reach with agents.

2:40:32

Yeah. Walk me through the current pitch to advertisers. When you meet with a new big company, I'm sure everyone's used your advertising product at this point, but let's assume there's some new hot company that is growing, they have a physical product or something and they want to grow their customer base, grow their reach. How are you positioning your offering on the advertising side?

2:41:05

Nearly billion user platform, including more than 110 million monthly active users right here in the United States in this really, really important 13 to 34 demographic. And the reason why that demographic is so important is because they are forming lifelong relationships with brands and with products. Right. And not to mention they're making their first car purchase, their first home mortgage, I mean even their first like tuba toothpaste. Right. So I think those are the sorts of really important long term brand relationships that are so critical.

2:41:30

I'm sure I'm still using the same toothpaste brand I bought when I was 19 or something. I have not churned from that company. LTV is probably through the roof. So do you have to stress the importance of thinking in not a roas, not a one year LTV payback, but thinking about capturing a customer that could stick around for a decade or more because they're young audience. Is that something that's resonating?

2:41:57

I think that fundamentally ROAS is critically important. It's something that we really optimize towards and a lot of people use lower funnel objectives on Snapchat. That's been a huge driver of growth for us, especially with the small medium customer segment because folks are very sensitive to their return on investment. But when I talk to advertisers about why they love using us, it's always the new customer metric that is why they're coming to Snapchat. They say if I look at the percentage of new customers I'm getting when I spend on Snapchat, like that really moves the needle for my business and it moves the needle for me over.

2:42:23

The long term and it feels less like a tax which happens on some other platforms where it's like these people were already coming to my, they were looking for me and I had to pay for that. It's frustrating. Jordan?

2:42:52

Yeah.

2:43:04

How what are you excited about in AI hardware broadly and everything that you guys are working on? It feels like this will be a massive year for hardware across the the board. You've got Apple people have been reporting I think this week on multiple new hardware devices. There was that somewhat believable looking OpenAI ad. But anyways, a lot of action going on, a lot of energy and excitement. You guys are in a good position because you've been working on it for better part of a decade now.

2:43:04

Yeah, I mean, it's a transformational year for. For Snap in this regard. We just spun out Specs into its own standalone subsidiary. So it's really going from like, you know, R and D science project to like, real company after almost 12 years. So that, you know, is really important for us, I think. You know, it intersects with some of the things that we were just talking about in terms of the evolution of AI, because, you know, one of the biggest things I think folks have been concerned about when it comes to building a new computing platform is how to compete with the lock in that the app stores have.

2:43:39

Right?

2:44:11

How can you possibly compete with all these other app stores? And I think literally at the beginning of this year, people realized, like, software isn't a moat anymore, right? That, like, having an app store isn't a moat anymore because it's so easy to build software. You can even build software on the fly, right? And that, to me, is really exciting and coming at an amazing moment.

2:44:11

What can you do to lean in? I saw somebody had hacked a pair of smart glasses to work with OpenClaw. And I imagine, is there anything that you would do on that front to really lean into the whole kind of like, hacker movement around AI? Because there's like, you guys are building a bunch of experiences internally. We've used a lot of them. They're very cool, but at the same time, opening it up and saying, like, hey, this is a platform that anybody can build on. And we've seen this. Even with the kind of the Mac Mini movement, Mac Minis are starting to sell out different points around the country. People are obviously willing to spend real money to experiment around all these products.

2:44:29

I think the big thing that you're sort of circling is the way that people are using their computers is really changing, right? And they're really just supervising agents doing work for them. And that is a perfect fit for Specs because the whole idea is to stop spending all this time hunched over your laptop or staring at this.

2:45:08

We were at breakfast, breakfast this morning. This guy. I didn't take a picture because it would have been rude, a violation of his privacy. But his. His posture was literally like. It was. It was the most insane posture. He needed. He needed Spec.

2:45:24

He's getting acronym one way or another. It's peak performance. He's Calling it now, like, I know we're gonna see this guy, but yeah, like we, we.

2:45:37

It feels the, the laptop what you're imagining, which is like we can all just spend all of our day walking around being productive, monitoring agents in a kind of a heads up display. It feels within reach.

2:45:46

It does.

2:46:00

Finally.

2:46:01

Yeah, it's incredibly exciting. So it's cool that all of this stuff is coming together in this moment. And I think it is super important for us to be investing in hardware because we talked about software is not a moat anymore. So it becomes even more important to do very hard things in the real world world at a time when software is being disrupted in this way.

2:46:02

Yeah. But at the same time I feel you guys are in a unique position because it doesn't feel well, like looking at the video game industry, I think that AI will present like a pretty huge challenge for a lot of these smaller studios that were just in the business of spending a few years making a game, releasing it. If it becomes way easier to build a game, that's bad for them. But it might be great for like a Fortnite or a Roblox or one of these platforms that have these big existing social networks. And so I feel like your core business of actually still being a social network where people are connecting with other real humans is in a good position. And so yeah, the hardware is just like a bonus.

2:46:19

One of the things we've been thinking a lot about is both with the friendgraph and in terms of our distribution, how do we leverage all these amazing tools to just start building more apps? Right. Like one of the things that we always love to do is come up with new ideas. In the past we've been like, oh, we got a great idea, but we got to build it. Oh man. Right now, you know, I was just looking. Today we have a really. I mean, I shouldn't even be saying this.

2:47:05

Something coming soon anyway, we've got a.

2:47:26

Wild new idea that we're working on.

2:47:29

Well, yeah, I was going to ask like, have you been pitched by the vibe coding? Like do people want to be able to like send an app around basically that they just prompt on the fly?

2:47:30

I think so. And I think what's going to be really interesting about all these companies, like before so many of their resources were dedicated to engineering. Now I think people are going to be much more focused on marketing, on distribution. Right. And that's a big shift in the.

2:47:40

Way that these things being able to send somebody an app that you just made for them that historically you would have Just like sent a funny picture to your friend.

2:47:51

This was my experience sending you soras of me watching on the beach in the Volta themed suit. I was able to make an in joke with me and my three friends in a group chat. That would not do well on social media broadly. You have to have all this context. But because the cost of generating new content had dropped so low, I could do something that didn't require a costume department and cameras getting set up or all those different things. Talk a little bit more about Genai. There's a lot of crazy video models releasing. It seems like a lot of companies are moving fast and breaking a lot of things, particularly in like the Hollywood's or Hollywood's not happy about this stuff. Like what does a responsible rollout of generative video features look like?

2:48:01

What a great question. So I think for us we have a lot of safeguards in place both around basic things like you shouldn't be able to make somebody nude or put in a compromising position or that sort of thing. You shouldn't reproduce copyrighted content, those sorts of things. So we as we look at even open prompt experiences where people can ask for to create different sorts of photos and videos, we try to layer in safeguards to prevent that sort of thing from happening and we do a lot of adversarial testing to make sure that that is unlikely to happen.

2:48:48

And then in terms of lenses, sponsored lenses, different experiences that partners are bringing to the platform. I'm interested to know what's the shape of the ecosystem? Are there random developers out there who are making things and then earning some sort of rev share from that? Is there actually a flywheel there or is it particularly like you're working with a brand and they're going to do a sponsored lens and your team is developing that for them. What does that side of the business look like?

2:49:22

Yeah, it absolutely spans the spectrum. So there's more than, well, gosh, maybe 400,000 developers now who built lenses for Snapchat and increasingly for specs as well. Those developers can apply to include their lenses in lens and earn a revenue share out from that if people are engaging with their lens and that kind of thing. And then we've got a whole internal studio as well. So we can work with advertisers if they want to build a unique experience. Or we have tons of partner studios who we can connect them with. But increasingly there's a tool called Easy Lens. It's pretty fun if you pull it up and just play with it. You can build a lens from A prompt?

2:49:52

That's what I was going to ask. I imagine that that has to be acceleratory for you. Right? It's huge for us.

2:50:27

And again, we're thinking a lot about how to connect. We have Lens Studio, which is more of the pro tool, and then we have Easy Lens, which allows anyone to create with a prompt. But I think even Lens Studio itself is going to become much more oriented around agentic engineering rather than because you.

2:50:32

Just prompt it and it's wiring up whatever your domain specific language is. Very interesting. Yeah. Are you starting to see an actual kink in the graph of lenses that are being deployed yet or do you think that this is something that comes once people realize that it's actually easier to go into?

2:50:49

Yeah, it's so interesting. There's some dynamic on the Internet that I feel like is somewhat real where the more funny you think something is, the less likely it is to be actually viral. Yeah. I jokingly call this the Hayes paradox, which is also a Hayes paradox. But yeah, it's this idea that something that is actually, actually the funniest thing that you see on the Internet for an entire year might have a TAM of like close to one or your group chat. But that's great if you're talking about giving people tools that allow them to generate hyper personalized things that are only funny to them or a handful of their closest friends actually gives you the ability to create a lot more joy on your platform.

2:51:07

And that's exactly what we see with Genai, that people are using it for these more communication oriented use cases. But on the content creation consumption side, it's the authentic, original, unedited non AI content that does super well. So definitely a major, a major contrast there. And I think as it pertains to easy lens, when we start rolling that out, we saw a huge step change in the lenses that were being created. So that's become a big focus for us. But I also think you can imagine in a not so distant future, I mean now the way that the models work, it's very hard to scale real time image transformations which or one of the reasons why I think people love lenses, because it almost feels like you're looking in a mirror, right. And transforming what you look like. I think in the not so distant future a lot of lenses will just be prompts, right. And those prompts are going to be shareable. And you know, we have a whole feature right now around the Imagine lens and some of our other generative lenses where we have trending prompts and you can share prompts with your friends and, you know, iterate on them. And I think, again, kind of tying back to the importance of the friend graph, I think you see that intersection of people creating these, like, inside jokes, but then also being able to really easily share them with their friends, have people create their own content inspired by those prompts. It's pretty cool.

2:51:57

Yeah, that seems really, really important. I mean, whenever one of these new image models goes viral, the stuff, there's always some ground truth meme, human element that's underlying it. I think of the Studio Ghibli moment. It's like, I've seen cartoons. I could just go look at a cartoon, but I haven't seen a cartoon of many. And so there's a little bit of that in there. So the lenses make perfect sense.

2:53:02

In that case, let's get the California update. What's on your mind? Broadly in the state going better than ever.

2:53:25

Right.

2:53:34

It seems to just get better and better. I don't know. I mean, if we didn't have this weather, we'd really be in a tough spot. I mean, it's incredible what we get away with.

2:53:34

It really. It really is.

2:53:43

That's got to be a big piece of it. The weather is fantastic. Although yesterday it was a little rainy.

2:53:46

Yeah. Yeah. Basically, California has, like, karma for forever flexing the weather on the rest of the state.

2:53:51

Yes.

2:53:58

Like, how many times I've messaged a friend and. Or they'll say, like, oh, it's like. It's my. It's like five degrees out right now. And I'm like, oh, it's like 71. It's gonna be that way all week. And so in exchange. In exchange, we get like the gnarliest political.

2:53:58

It's a little chilly today. It's 56. That's sweatshirt weather.

2:54:16

It is.

2:54:19

Freeze it.

2:54:20

Freezing.

2:54:21

Freezing.

2:54:21

It's absolutely freezing.

2:54:22

Stay indoors.

2:54:23

This is crazy.

2:54:24

But, yeah, broadly. How do you think California is going?

2:54:27

Yeah, I'm concerned. What gives me some optimism is that it looks like more and more people are increasingly concerned. What I was most worried about even six to nine months ago was the number of people that thought things were going really well in California because they were contrasting with what they were seeing at the federal level and feeling like, oh, California is better. It seems like there's less chaos here or whatever because we've got a single party state, essentially. And so I think now more and more people are hearing that we're number one in terms of homelessness, number one in terms of poverty, number one in terms of Unemployment. And they're like, whoa, like that doesn't line up with the California that I love, that I want to be a part of. Like, how can we change that and fix that? So I think the awareness is really important because, you know, in a democracy without awareness, you're not going to get change. And so I think, you know, hopefully that will continue to build. I think, you know, if Newsom decides to run for president, that's going to, I think raise even more awareness of California and the challenges that we're facing here, which again, I think will be helpful. So right now, to me, it's really an awareness game of helping make sure Californians understand, like this is not going in a direction that I think we want. And if we want change, then we're going to have to ask for that.

2:54:29

Right.

2:55:40

And advocate for that. But I think that's happening more and more, which gives me some hope.

2:55:40

Yeah, makes a lot of sense. I want to ask about live streaming. How do you think about it? It feels like it's having a little bit of a moment with the clavicular stuff. I don't know if you've been tracked what is.

2:55:46

I love this.

2:55:59

So locked in.

2:56:00

So locked in.

2:56:01

You're like the famously got frame mogged. It's a big deal, no? Yeah.

2:56:02

So he's running, you know, have a billion users on the Internet, but there's basically a number of creators on KIK that have generated probably 100 billion views, like some absurd number. The one John referenced is from the looksmaxing community, which is effectively guys that try to be as good looking as they possibly can. So it's basically this whole drum like it's kind of like WWE brought to very Internet native. There's all these different characters. One of them is running effectively a 24 7. Whenever he's sleeping, he's streaming live stream. So it feels like IRL live streaming is, is hitting just having a really big moment right now. How have you thought about it historically? Does it play any type of role in Snap's future or is it not something that the users actually want?

2:56:06

We decided to step our way there essentially with creator subscriptions. So we just started testing creator subscriptions with a small group of creators. What we find on Snapchat is that people, people have very, very loyal relationships with creators. So once they subscribe, they want to come back every day and see what's new on their story and message with them and really get to know them better and build this deeper relationship. So we thought creator subscriptions was a Good extension of what we're already seeing happen on Snapchat. We're going to test that out and see how that goes. But that will give us some of the infrastructure to start thinking about stepping from there.

2:57:07

And that would be an integration creator. Just going live, talking with their existing follower base.

2:57:41

Yeah, potentially to start with their existing subscriber base or even with their. Not necessarily even their followers more broadly, but their existing subscriber base and then layering in some of the replying and gifting and those sorts of things before opening it up more broadly.

2:57:48

How have you been? Yeah, I felt like my personal stance is that like Twitch as a platform since landing at Amazon is just like not just gotten the attention that I think it potentially deserves. I created an opportunity for the kicks of the world to step in.

2:58:04

Well, I mean, I haven't seen Andy Jesse live streaming on Twitch once and.

2:58:24

So I would love to see that.

2:58:29

I would love to see that earnings on Twitch, obviously.

2:58:31

Just that would be cool. Yeah. So you guys should, you should fire up your and do just an earnings call on the platform. It would be great.

2:58:33

I want the CFO there explaining the whole financial model. What happened? Keep it wonky. It's fine. That's what Twitch is. Every social media platform is like a flourishing of niches and you find your niche and there's going to be someone there who's like, yeah, this is amazing. Switching gears a little bit, you mentioned subscribers are getting close to Hulu numbers. How have you been processing the somewhat polished produced vertical short form trend that's sort of happening. I see them in the App Store. I haven't been a user really, but you're familiar with what I'm talking about. Real short is one of them. They seem to be popular. There's obviously some organic creation that's happening on a fully UGC platform. But how have you thought about that? It feels like sort of revenge of Quibi in some ways. But where do you think that goes? How important is that? Is there a role for you to play in that ecosystem?

2:58:42

Yeah, I know that we've got a lot of advertising partners who are marketing the short form videos on Snapchat. And I mean those ads are so sometimes I find myself watching one for like a minute and I'm like, oh.

2:59:35

My God, I got to know what happens next.

2:59:46

Who killed her?

2:59:49

So that seems to be working. But I think, you know, when we experimented with shows, you know, many, many years ago, I think for us we just found that the volume of creativity, you know, the billions of Snaps being created in the Snapchat camera meant that really, like Snapchat is at its heart about UGC fundamentally. And I think in the places where we've really allowed UGC to flourish and creators to flourish, and actually where we didn't do as many shows or didn't do as many publisher stories, we. We really built a very vibrant, organic creator ecosystem. So I think, you know, in sort of the ensuing few years, we've pulled back from doing that sort of more premium content because what we just see our community love is connecting with the folks that feel like they're next door.

2:59:52

Yeah. And I mean, YouTube did the same thing. YouTube Red, they had a whole bunch of, like, produced things. And you'd see the. I'd be like, my favorite creator got paid a bunch of money to do something produced and it's getting less views. But because I actually just want him to turn on the camera and just talk, I don't need all that other stuff because that's not what I'm there for. And I think that recognizing the desire of the user, the context, all of that really matters. The medium is the message. Right.

3:00:35

How do you allocate your time in 2026? Where are you spending time? How has that kind of changed over the years?

3:01:02

I mean, at a high level, it's probably 80, 20 Snapchat and Specs, I think that's going to have to start shifting this year. You know, not. Maybe not totally 50 50, but certainly close, close to it. Just as we, as we ramp up and, you know, bring that product out into the world, you know, my happy place is making new stuff with our team. That's what I love to do. Our design reviews, you know, whether that's, you know, with specs or with the Snapchat team, that's really what I. What I love to do. But, you know, a lot of what I've had to do over the past couple years is really work closely with the team to rebuild the ad platform and to create a totally new, this small, medium customer segment of our advertising business. I mean, our business three or four years ago was almost all large customers and, like, highly concentrated in the United States. And when your business is concentrated on a small number of very big customers, it just creates a lot of unhelpful volatility. And so what we've done since then is build out a platform that can deliver lower funnel goals, you know, especially the small medium customers, and then really diversify.

3:01:15

You don't get to work on the fun stuff if you don't have the economic engine. Yeah, yeah.

3:02:11

Last question from me. Virtual reality. You've obviously looked at this. Haven't gone super deep in it. Over the weekend, I watched the Matrix in VR. I also watched on Apple Vision Pro.

3:02:16

You watched the whole Matrix in VR? No way. No way.

3:02:31

Yes.

3:02:34

They said no one had ever done that before.

3:02:35

I also. I also watched. You made history.

3:02:37

It's incredible. You should hit the gong for that.

3:02:41

I mean, that's unreal.

3:02:44

That's incredible.

3:02:53

But I'll do you one better.

3:02:55

At.

3:02:58

Like five minutes in he, like, takes.

3:02:58

I know. I didn't.

3:03:00

I didn't.

3:03:01

I watched the whole thing.

3:03:01

I did. I did. I did. But. But I went further. On Saturday night, I watched Terminator 2 in Vietnam. Whoa.

3:03:02

Back to back.

3:03:09

I watched back to back films. I watched two.

3:03:09

And you don't have, like a ring around your head.

3:03:11

It's temporary. It goes away after about an hour. And yes, my wife did say something about it, but what was she doing?

3:03:14

When was she there?

3:03:20

It was a rare situation where she was out of the house with the kids. And so I just had free time.

3:03:21

Never had you just plugged in.

3:03:27

But it's like, truly, truly around family. Like, you can't use it because it's so antisocial. Even with the eye, it just doesn't work. So, like, I actually finished watching Terminator 2 just on my phone because it was less antisocial than putting this VR headset back on when once the family came home. Anyway, I did successfully watch a full movie in VR. Let it be known I did But I can't tell and I think I already know the answer now that you're laughing at me. But am I, like, one year early? Am I 10 years early to watching movies in VR or am I just weird and it's never gonna happen?

3:03:28

You're gonna watch movies and glasses for sure.

3:03:59

Okay, Right.

3:04:01

And I think, like, what? You know, it's so funny. A couple of my buddies, you know, are big into finance, stuff like that. So, like, if we travel together, you know, they'll bring their monitor to like.

3:04:02

Oh, yeah, yeah.

3:04:12

Come on. You can't get stuff done without your.

3:04:13

You just got the new Dell one. It's like six feet long.

3:04:15

That's amazing.

3:04:19

You gotta have your. You gotta have your setup.

3:04:20

Yeah, yeah.

3:04:22

So they travel with, like, a big monitor or, you know, even two monitors. So I think, like, a lot of the early stuff you're gonna see with glasses are people who just want the full setup, but, like, do not want to ship, you know, Sure. A monitor to wherever they're going. So I think like, if you, you know, if you're, if you're traveling or you're, you know, on a plane or something, you want to really get work done. It's so hard to do that on a laptop. So I think you're, I think you're right on time, actually. Right on time or Pioneer.

3:04:24

Next time you come on, we'll ask, have you watched a full movie in any VR product? And I. And we'll see. We'll see if I'm, if I'm early or just weird.

3:04:48

What do you think about timelines for watching movies in glasses?

3:04:56

That's this year.

3:05:00

Yeah. And then what about, what about glasses? Is it that you still have some element of the real world it's not as anti, you know, you're not getting though, like, you know, it's not this.

3:05:01

Huge, heavy closed headset with a screen, you know, right in front of your eyeballs. So, I mean, sorry, it seems like you love it.

3:05:11

So the trick is that I was laying perfectly flat in a fully bright room.

3:05:19

Yeah.

3:05:24

Oh yeah. This is the other thing. This is the other thing. It needs tracking. So you have to leave the lights on. I'm not kidding. I'm not kidding. No, seriously. So you can't turn off the lights. And so if I get home and, and my wife wants to go to bed and turn off the lights, I'm like, okay, it doesn't work. No, it doesn't work because it loses the tracking. No way. But if you rest it right on your head just perfectly. And then also the VR headset, it wants to be world locked. So initially the screen is down here and you have to look like this and then you have to recenter it up here and then it appears above you in beautiful 4K and it's amazing. And you sit there and you watch the Matrix from start to finish. And it's actually a great experience, but it is weird and niche and I don't know if it'll ever happen, but.

3:05:24

I think the idea of, you know, being able to watch something on a giant display in a lightweight pair of glasses is compelling.

3:06:06

Oh yeah, if it's lightweight. But like, truly, you actually can't have a VR headset on your face for more than 10 minutes. It's not.

3:06:12

I love this super bright.

3:06:18

It has to be bright. Like the ISO on these cameras is so low that even if I just have my lamp on, it's like all fuzzy and noisy.

3:06:20

You know, get a warehouse and get a bunch of like yoga mats and have the vision pros. And it's a VR movie theater. You go and you just lay in.

3:06:28

The bright, super bright. It really is like the most dystopian, antisocial thing you can possibly do. But the Matrix is a great movie, so it was worth it. I sacrificed worth it for the. For the board.

3:06:36

And you broke the record.

3:06:47

I did. I did. Call Guinness.

3:06:49

Right now, when you all aren't live, you just move the table, put some mats down, and then you've got.

3:06:51

Yeah, yeah.

3:06:55

It's perfectly lit.

3:06:56

Anyway, thank you so much for coming on the show.

3:06:58

Great to catch up.

3:07:00

Thanks for having me. Good to see you.

3:07:01

Yeah. Congrats to the whole team on that.

3:07:02

Thank you. Leave us five stars on Apple podcasts and Spotify. Subscribe to our newsletter@tvpn.com and we will see you tomorrow at 11am Pacific.

3:07:03

Are you sure you got to get out of here?

3:07:15

Oh, yeah. You want to keep going?

3:07:16

I kind of want to keep going.

3:07:18

I don't know what else is in the news. If we got news, we can do it.

3:07:19

We can get to it tomorrow.

3:07:23

Okay. We can get it to it tomorrow.

3:07:24

Thanks for hanging out with us, folks.

3:07:25

Thanks for hanging out with us.

3:07:26

Love you. We will see you tomorrow morning.

3:07:27

Goodbye.

3:07:30

Cheers.

3:07:30