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Founders Fund You're watching TVP.

4:36

Today's Wednesday, February 25th, 2026.

4:39

We are live from the B&L Tower.

4:41

The Temple of Technology The Fortress of Finance The Capital of Capitalism. ramp. com.

4:46

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4:52

We have a massive show for you today, folks.

4:54

We got Doug O'Loughlin coming on on his birthday. The Douginator. media earnings.

4:58

Talk about a birthday present.

5:00

Uh we got Marc Benioff from Salesforce coming on.

5:03

Uh let's take you through the linear lineup.

5:05

Max Myer's coming on uh from Arena magazine.

5:09

There's a new issue dropping, 007 spy theme. I love it.

5:12

Ben Layers coming in person, and then we have an absolute hitter of a lightning round for you folks.

5:18

Linear, of course, is the system for modern software development.

5:22

70% of enterprise work space [applause] on Linear are using agents.

5:25

Okay, so uh I was nerding out about this Fed paper because it's it like when you told John Collison 80% of businesses are getting no value from AI, I was sur- I'm glad he wasn't here in person because he was about to to down.

5:44

He was about to open up a can uh whoop.

5:46

It was about to be a bar fight in the cheeky bar pub. In the Guinness pub.

5:51

No, seriously, it it was a great question because I think we all agree that like AI adoption is real, it's valuable, it's happening, but it is a very interesting statistic and I and I think it's a mistake for tech people to like dismiss this stat because of where it's coming from.

6:07

Like it's not coming from some like doomer anti-AI blogger who's going for clicks.

6:12

Like this is the National Bureau for Economic Research.

6:17

There's three members of the Atlanta Fed on on like the Federal Reserve Bank.

6:20

It they're on this paper.

6:23

There's two people from NBER on the paper and then they also pulled in the Bank of England.

6:29

They have some Australians and Germans on there, too.

6:31

And so this is a research paper that could be circulated, probably will be circulated within the Fed.

6:37

And I think that it's already getting quoted by the New York Times in that dot com bubble AI bubble piece.

6:44

And I and I'm just I'm thinking it through like this could be something where you see Fed policy or government legislation that sort of mismatched with what is actually happening in reality.

6:58

And so uh we should go through some of the some of the stats to actually break this down because the headline is 80% of firms reported that AI was having no impact on their productivity or employment.

7:11

And that's actually like a misquote.

7:13

Like what they mean by that is that it's not shaping their hiring plan yet.

7:21

They actually are using AI.

7:21

And so uh basically this stat comes from the survey from the National Bureau of Economic Research and it's pretty interesting because a lot of the polls that you see online are online surveys where they say they run some digital ads and they say, "Are you a CFO of a company?

7:40

We don't really care what company.

7:41

We'll pay you $10 to take this quick survey.

7:44

And who what kind of people want to make $10? >> of liars.

7:49

There's a lot of liars out there who say, "I am absolutely a CFO, and please send that Amazon gift card right my way, right?"

7:57

And so for this one, they actually did the work.

7:59

They called up and ID'd verified, and then also reality checked the position.

8:05

So, if you say, "Yeah, I'm the chief pirate officer.

8:07

I'm the ninja hero, whatever."

8:10

You got some fake title, they're you're out of the survey.

8:14

You have to be a CFO, a CEO, senior manager, and you actually had to be doing that job.

8:18

It's not just like, "Oh, you're yeah, you're the CEO CFO of some front company."

8:22

So, they did some reality checking, and they pulled together 6,000 of these business leaders across firms that are domiciled in the US, UK, Germany, and Australia.

8:30

And so, um you know, the line from John Collison that has been sort of going viral, that was he he he dropped it on sources.

8:39

He said I think he said it to us, too. It's a good line.

8:42

No one wants a refund on their tokens. Everyone is using AI.

8:47

Their spend is increasing.

8:48

>> Although I'm sure some CEOs heard that and thought, >> I would love I kind of do want a refund. I'd love a refund.

8:53

I had one team member go absolutely haywire and spend 50 grand. >> He's one shot.

9:01

He claims that he rebuilt our entire ERP, but I fired it up, and it it didn't even have HTTPS. What's going on?

9:07

>> Mini wasn't even plugged in.

9:08

>> Yeah, the Mac Mini wasn't even plugged in.

9:09

He was He was just chatting.

9:09

Uh but clearly like there is a disconnect between like the Stripe data is very real.

9:15

The the the value creation is very real.

9:19

The revenue is very real at the labs.

9:21

Um but when just random Joe Schmoe CFO CEOs get a call from the the feds, they say like, "Yeah, we're not really getting that much value out of AI."

9:32

And so, uh the the the questions that you need to dig into that there's actually four key findings that the the one headline that The New York Times is is pushing is this 80% number.

9:43

80% report little impact or no impact on employment or productivity, but there's actually a bunch of positive signals, there's a bunch of mixed signals in here.

9:53

So, uh, 70% of firms actively use AI and particularly younger, more productive firms.

10:02

Second, while over 2/3 of top executives regularly use AI, their average use is only 1.

10:09

5 hours per week, and 1/4 of executives report no AI use at all.

10:17

They're just like, I do things the old way. I have a AI?

10:19

Not not for >> Why would I need that? I have a telephone.

10:22

Yeah, but I mean it truly if you think about like the variety of firms, it's like you could be running a gym, you could be running a gas station, you could be doing forestry, you could be doing mining, oil extraction, road repair.

10:33

Like there's a million different things that you can do in the economy.

10:36

It's not all like knowledge work firms.

10:39

>> We talked to somebody yesterday uh, in the sort of later part of their career off the show. Yeah.

10:43

And they had just had their mind blown by AI because they used to when they needed a document created, they would put it into bullet they'd put out bullet points and then they would give it to somebody who would then create a document.

10:55

And he just said, now I just give it to AI and then just generates a document.

11:01

>> Yeah, and so that that's So that's still happening. >> Yeah.

11:04

That's that's text expansion, text generation with LLMs.

11:07

This has been available since 2022 when ChatGPT launched, maybe it became reliable in 2023.

11:15

Uh, people are still just starting to adopt, uh, and there's some there's some other interesting things in in here.

11:24

So, uh, the last major finding that we should touch on is, uh, firms predict sizable impacts, uh, over the next 3 years forecasting AI will prove boost productivity sizable impacts productivity increase 1.

11:37

productivity increase 1.4% which is like it's [clears throat] very sizable if you're an economic researcher but it's not particularly sizable if you're in like the fast takeoff scenario and so there's just this disconnect between like what are the government statistics

11:51

look like and what is what is the government operating against and then what's the Silicon Valley narrative and like where do these two meet the road what why is there a disconnect at all one of the reasons is that um measuring AI adoption is a mess many people use AI

12:04

without even knowing that they're using AI because it's buried deeper in SAS products that they already daily drive like if you're just I run a coffee shop and I'm using toast for you know payment processing like there's probably some AI features in there already and when you

12:17

go to you know type in okay we're adding a new cinnamon roll to the to the you know the menu there's probably a button now that just says like do you want to just generate an image of a of a cinnamon roll you could upload one still that's probably a feature that already

12:31

exists but like we could also just generate one for you and you can probably click that but you're not like oh yeah I'm an AI power user just because like you happen to use toast and toast happen to have implemented some gen AI feature that like you haven't

12:43

really dug into yet um so some AI isn't even detectable you could be talking to your customer support agent on the phone that is AI generated not be able to tell we talked about that that airline interaction that got something 100,000 likes and uh and Grace the woman that Grace the woman

13:03

that had the interaction came into the chat yesterday and said it was real yeah it was real and so >> she she out she out maneuvered the clanker but but still think about like she's clearly on acts in tech like very AI aware um there are probably tons of people out there that are saying oh yeah my job you

13:23

know every once in a while I have to call this service and now the person that picks up is like responding pretty quickly, but I haven't noticed they haven't noticed that they're actually interacting with AI or using AI in some capacity. And then and then there's also times

13:36

And then and then there's also times where people are like chatting with AI, but they just put it in the personal life bucket.

13:40

Like I'll find myself doing this a lot of course as an entrepreneur like the the work-life balance like bleeds together a lot, but there's a lot of times when I'm you know reading an article on Saturday, I'll fire off a deep research report about it, find some extra context.

13:53

It feels like oh I'm just reading the paper, but my job is sort of to read the newspaper and so it comes into work and there's probably a lot of people that are like you know oh you know I I I hit an LLM with some random query to learn something about something work-related, but I did it off hours when I was just like you know hanging out.

14:12

And so I don't really think about it as like a work tool yet and so they're not putting it in that bucket.

14:16

But in general, I think that I think the team did a really really good job by avoiding of many as many of the pitfalls as possible when it comes to surveying AI adoption.

14:25

AI adoption is very messy.

14:27

You've talked about the need for strong >> Yeah, I still think there's room for a research firm focused entirely on diffusion.

14:34

So if you had a group of 10 to 20 people that were spending all their time talking to business owners and executives operators and getting a sense of how they're actually using this stuff, I think you could put together some really compelling reports around it that would be pretty useful to everyone from AI companies to Wall Street. Yep.

14:56

Adoption max after cluster max and inference max. They had to rename it.

15:01

Apparently SemiAnalysis can't use max for some reason.

15:04

So they do uh inference max is now inference acts and everyone was saying you need to just change it to inference mock.

15:11

Which would have been amazing.

15:13

But inference acts obviously has a much more professional tone to it.

15:18

And so there's the there's an interesting definition of like, what does it mean to actually adopt AI? That's very vague.

15:27

This paper defines it pretty broadly.

15:28

So, machine learning for data processing.

15:32

So, that doesn't even necessarily mean LLMs.

15:36

That just means ML, which has been around for a very long time.

15:41

Text generation using LLMs, that's what we think of is ChatGPT.

15:45

Visual content creation, so diffusion models, but also robotics and autonomous vehicles.

15:50

And there's another And there's a category just for other.

15:52

And firms can select multiple.

15:54

And so, if you selected yes on any of those, you go in the bucket of AI adopter.

15:58

And 78% of firms in the United States said yes, they are using AI by this definition.

16:07

They got at least one robot, or they've at least generated one AI image, or one prompt to ChatGPT, which is a very low bar.

16:15

Sort of makes you wonder like what's going on with the 22%?

16:19

Um And And if you And you can also dig in further.

16:21

So, text generation using LLMs is the single most common use case at about 41% of firms.

16:25

So, flip that around, 59% of firms aren't even using LLMs for text generation or pre-proofreading.

16:31

But again, there's a lot of companies where it's like, yeah, we don't generate a lot of text.

16:34

Like, maybe we if we if we need to generate a marketing material, we we have an agency that does that.

16:40

So, we don't actually do it internally. I don't know.

16:41

Um Across the four countries that were surveyed, 69% of firms totally said they currently use AI.

16:48

I think Australia was behind a little bit, uh dragging that down.

16:52

Only 75% of firms expect to be using AI technology sometime over the next 3 years.

16:57

So, they're They're at 69% now, and they're like, over the next 3 years >> Tyler's going to have a heart attack.

17:04

>> to bump that up to 75%.

17:04

And this is like This is weird data.

17:06

And And I And I I'm You can jump in with your pushback, whatever you want.

17:11

But my point is is not that is not that they're right.

17:15

Like, I think that I think that they're wrong to predict this.

17:17

I think that the AI adoption will be very steep and very dramatic.

17:21

But I just think it's important to recognize that like this is a paper that people will be citing.

17:25

This is a paper that will shape policy.

17:26

This is a paper that does reveal some misconception about the impact AI is having in firms.

17:33

Yeah, I still think it's just it's so hard to like actually quantify this.

17:36

Like okay, if I'm like using ramp Mhm.

17:39

does that count as using AI?

17:42

Cuz it's obvious like it certainly is using AI under the hood, but I'm not directly interfacing with the model. Yes. So does that count?

17:49

So I think if you were running just a company that was just on ramp, you would probably respond no.

17:56

Yeah, but like I'm clearly I'm benefiting from AI. >> I agree.

17:58

So it's like like how do we actually quantify this?

18:01

>> the This is the diffusion question.

18:04

I I completely agree with you.

18:04

I think that I think that there's plenty of places where AI will have impacts across the economy, but the actual AI workloads and AI app development, model training, inference will happen at a different set of companies.

18:19

I don't think it's not going to be as clear as as the computing revolution where every company had a desktop computer. Yeah.

18:27

And then it was like okay, very quantifiable.

18:30

The only thing that you should be looking at for diffusion is just lab revenue. Lab revenue. Yeah. Yeah.

18:36

And it's and it's growing a lot, but it's still the perception I think still does matter because because people will I I think that there's a little bit of like potential self-referentialness here where firms see oh like AI adoption's low, I don't need to go and figure out how to adopt it.

18:57

And so that's something that I'm also like keeping keeping an eye on.

19:03

Reported usage is still low and this one's interesting based on revenue and also token generation. So 1.

19:06

5 hours per week among the managers surveyed.

19:12

Again, it's like they surveyed CFOs.

19:14

CFOs who use Ramp, like they don't they don't count their time in Ramp as minutes using AI.

19:19

They count their time in LLMs as minutes using AI, and that's low.

19:24

But even just with that 1 and 1/2 hours a week, the actual leverage that you're getting is increasing because one and like 1 and 1/2 hours, um you don't necessarily need to spend more time prompting to get more done >> Yeah.

19:38

Even so, even if you run a deep research, like is the time you're waiting, does that count as time in the LLM? >> No, not at all. Okay.

19:43

So, the time is you spent the time typing? >> Exactly.

19:47

Is it does it count as when you're reading the answer?

19:49

>> you're reading it, for sure.

19:49

So, it's like when you have >> Not if you Not if you export a file and you're just reading it in preview. Yeah. Yeah. Yeah. No. No.

19:57

I mean, to to some degree.

19:58

But but people were asked to estimate, and I'm sure that they didn't include, "Oh, yeah, I let my agent cook overnight for 8 hours."

20:04

Or I fired off one prompt, I came back, and it did, you know, meters 15 hours of software engineering in one prompt.

20:11

Like they Like these things aren't captured. 1.

20:14

5 hours of prompting generates a whole lot more tokens and valuable output in 2026 than it did in 2023.

20:19

And so, there's this like dis- there's this there's this divergence between the actual time spent and useful output and and and impact.

20:32

Um and the biggest the biggest thing was there was a massive divergence in the expected employment impact.

20:40

So, uh they basically 63% of firms still expect no impact from AI.

20:52

And that just completely goes against everything everyone's saying in in Silicon Valley.

20:56

So, there's still a lot of optimism among managers that AI will create more opportunities and new jobs, even as some jobs become obsolete.

21:04

There are definitely firms within the sample that are projecting head count decreases, but my read on this data is that the tech talking point about 50% of white-collar work going away is not a broadly held belief among average business average uh, business leaders.

21:18

Um, so uh, now they might be wrong.

21:19

I do think AI progress is pacing way ahead of public expectations and most managers are months behind when it comes to understanding frontier capabilities.

21:28

The bigger takeaway for me is just that the survey may be somewhat self-reinforcing.

21:35

Um, and so we have I mean we talked to we talked to folks all the time who come on the show and and, you know, uh, and talk about like maybe it'll be good, maybe it'll be bad, but everyone thinks it's going to have an impact, but that's not true broadly, which is very very uh, interesting.

21:52

So, um, uh, no one in tech has a strong recommendation for proactive steps to prevent the collapse in white-collar work yet, uh, but plenty are sounding alarms and uh, if this survey becomes an excuse for executives to a slow adoption, they might get outmaneuvered by faster-moving competitors, which is actually good news for startups.

22:10

Um, and I I close my thinking about like the nature of polling and and how do you actually get stronger data on uh, on AI adoption and I was thinking back to the presidential cycle.

22:22

So, during the uh, during the presidential election uh, pollsters would call people sort of at random and they would ask them, "Who are you voting for?"

22:31

And a lot of people would say, uh, they'd lie or they wouldn't say or they or they wouldn't pick up the phone if they were voting for a particular candidate.

22:39

And so, the polling numbers did not wind up matching the uh, the final election results very closely.

22:45

And so, there was the story about neighbor polling, which was more effective where instead of calling someone and asking them, "Who are you voting for?"

22:54

the pollster calls and asks, "Who do you think your neighbors are voting for?

23:00

Who's more popular in your community?

23:02

Who's more popular on your on your city block, on your street?

23:04

And that wound up sort of removing the revealed preference, stated preference, you know, oh, I'm am I on the hook?

23:12

Do I want to tell this pollster who I'm voting for?

23:17

Um and it wound up increasing accuracy.

23:19

And so, I'd like to see a survey of AI adoption using this technique.

23:21

Like I imagine asking the CEO of Nike, how much AI do you think Adidas is using?

23:26

And I don't know how much more accurate that would be, but it would certainly be entertaining and I think that there might be something more revealing there where CEOs have this big incentive to be like, "We're using AI.

23:38

We're using We're using everything."

23:41

Um but if you but if you ask them about their competitors, the data might might look very, very different.

23:45

Um anyway, we should we should watch a little bit of a clip from the State of the Union because Donald Trump addressed some of the energy production question uh with regard to uh like how hyperscalers will be offsetting the impacts.

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24:09

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Uh and let me also tell you about the New York Stock Exchange.

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24:19

So, let's head over to the State of the Union, which was held last night.

24:25

>> are also concerned that energy demand from AI data centers could unfairly drive up their electric utility bills.

24:34

Tonight, I'm pleased to announce that I have negotiated the new ratepayer protection pledge. You know what that is?

24:42

We're telling the major tech companies that they have the obligation to provide for their own power needs.

24:46

They can build their own power plants as part of their factory.

24:51

So, that no one's prices will go up and in many cases prices of electricity will go down for the community and very substantially down.

25:00

This is a unique strategy never used in this country before. We have an old grid.

25:04

It could never handle the kind of numbers, the amount of electricity that's needed.

25:08

So, I'm telling them they can build their own plant.

25:11

They're going to produce their own electricity.

25:12

It will ensure the company's ability to get electricity while at the same time lowering prices of electricity for you and could be very substantial for all of you cities and towns.

25:25

You're going to see some good things happen over the next number of years.

25:30

What's your reaction to that?

25:33

I think it's a good start.

25:35

I I don't know that it will quell any of the fears around data centers.

25:41

Just given that people kind of see the potential for this massive structure going up.

25:46

They have so much fear about it.

25:48

And again, I think it's clearly going to be necessary to build continue to build data centers in heavily populated areas, but um How How would you rank the fears currently?

26:02

Because I've put I've put my energy bill goes up and that puts pressure on my income and ability to live my life at pretty much the top.

26:13

And then the water thing felt, you know, secondary but also important.

26:19

And then there's the existential fear of like doom and apocalypse.

26:25

There's also job displacement.

26:27

And then there's also just like I don't like the slop and they're stealing IP.

26:32

So, like that was kind of the ranking.

26:35

It's like you can oppose data centers and be like, "Yeah, actually my electricity bill went down, but I still don't like that, you know, Harry Potter is in the pre-training corpus and so I'm for that reason I'm against it."

26:48

>> I would rank it on electricity bill going up is the pain today. And it's so real.

26:54

And then and and it and it's easy to imagine.

26:57

Uh and then there's fear around the job loss narrative that is sort of secondary.

27:01

And opposing a data center in your local area feels like a way to have some agency around that like overall kind of like job loss concern. Yeah.

27:14

Yeah, I mean I think the I think this is a good >> Chris Casey, build a data center on my freaking forehead.

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27:36

So, um I think the I think the the the the job loss thing is is super real in in in the case of like like AI is going to get blamed even if there's and even if like tariffs drive high unemployment.

27:53

Like if people lose their jobs, like AI is going to be a scapegoat and and it's going to be used both by executives Yeah.

28:01

>> It's the perfect scapegoat for executives and for people frustrated with the job market. Yeah, yeah.

28:05

It's like, "Oh, I I I I my business isn't doing poorly right now.

28:09

I I'm I'm laying off people because I'm getting so much benefit from AI.

28:13

The stock should actually go up. We're more efficient."

28:17

Um there's going to be a lot of that, but it does feel like it's a little bit early for that.

28:20

Whereas the like there are a lot of people that just can hold up their power bill and show you year-over-year increases.

28:27

And if that goes away and people don't feel that anymore and they don't have that evidence to share, um I think that I think that take gets debunked pretty quickly and actually does a really important piece of like the the uh the back and forth that's happening. I don't know.

28:47

I I it it seems like it seems like it's a it's a pretty easy give from the hyperscalers to build more power.

28:54

It was called out very, very early as like, "If this is a bubble, how do you get a silver lining out of the bubble?"

29:02

And the silver lining out of the dot-com bubble was a lot of dark fiber.

29:06

And and there was a whole ton of projects to uh what was it?

29:09

Global Crossing to actually develop the internet.

29:14

And then the internet just became really, really cheap and a whole bunch of new companies were able to emerge on top of it because that infrastructure had been laid.

29:19

You could see the same thing happening where it's like, "Oh, wow.

29:22

Like, we overbuilt on the energy side.

29:24

We actually didn't need that much energy for data centers.

29:26

Maybe Jevons paradox doesn't hold, blah blah blah.

29:30

Like, models get cheaper and and commoditized or whatever. Something happens."

29:34

I'm not super a believer in that, but um but at least in that scenario, you're like, "Okay, well, yeah, my my heating and cooling bill went down.

29:43

This is This is a silver lining."

29:45

Uh what do you what do you think, Tim?

29:46

Yeah, I I like kind of similar I I would say I I mostly disagree with the idea that like rising energy prices is the main like reason to be against AI um because like the rational thing to do then is say like, "Okay, before you build a data center in my community, you have to build a power plant so then my energy price goes down." No one's doing that.

30:05

They're saying like no one is is campaigning If you look at like protests and stuff, they're not saying, "Please build a power plant first."

30:10

They're saying like, "It's going to destroy uh the environment or the the water stuff or you're going to take all the jobs because it's going to like I need to send you that New Jersey New New Brunswick protest.

30:22

Build the nuclear power plant first.

30:24

Yeah, no I I again, I tell you no one is saying that, right? Because Okay. Yeah, we are.

30:29

I'm saying >> [laughter] >> But no one there is saying it, right?

30:32

They're they're against all the environmental stuff. >> Yeah, yeah, yeah.

30:35

Um So I I I think it's much more on like basically job loss of like, "Oh, the AI is stealing the IP of Yeah.

30:43

>> of Disney or whatever." >> Yeah, yeah, yeah.

30:45

There needs to be more more polling on the on the on the on the question of like, "Woah, why what's what's what's driving the protest fully?" Anyway.

30:53

Um happy Nvidia day to all who celebrate except the bears, forget them, says take him.

31:01

He's getting fired up for Nvidia earnings.

31:03

Let's It's going to be a fun one today.

31:05

How is Nvidia doing so far? Are people optimistic? Um Oh. >> up 2% today. Yeah.

31:11

Hard to read too much into it yet, but we will find out soon enough.

31:17

Uh Brad Gerstner got a nice shout-out during the State of the Union. Total Gerstner victory. >> accounts. Wow, he's there. No way. >> uh he was there.

31:26

Uh [snorts] Trump They started looking at him, >> Yeah.

31:30

but then the camera, I guess they couldn't find him >> Okay.

31:34

>> on the stream that I was watching.

31:35

Looked a little bit better. There we go. We can see him now. There we go. Once we pull over here. There he is. Gerstner champion.

31:42

What a great project, Invest America. Excited for it. Yeah.

31:45

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31:49

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31:55

>> All right, so we have >> This has been discussed to death. >> up the timeline. >> timeline.

32:01

>> A new Guinness World Record, and I want to ask John if this if you think this should actually count.

32:05

So, let's pull up this video now.

32:11

This is a Chinese hypercar going for the >> I've never heard of this drift ever. That is crazy.

32:16

But here's the thing, he doesn't he doesn't actually pull out of it. Did he just crash?

32:23

>> Kind of just U-turned.

32:23

It's like a really fast U-turn.

32:25

I think this counts as a drift.

32:27

That's definitely drifting.

32:29

>> U-turning counts as a >> if you saw that car going by, you'd be like, "Wow, that's drifting."

32:33

It's drifting across the cement. That 100% counts.

32:37

I've never heard of this company.

32:39

>> This is This is called spinning out.

32:42

It's just crashing with style. It's falling with style.

32:44

HyperTech SSR, formerly Hyper SSR, is a high-performance all-electric two-door supercar.

32:51

No one has I mean this is crazy.

32:51

This is out before the Tesla Roadster.

32:53

We've never seen a two-door supercar, electric supercar.

32:57

Uh 1,225 horsepower, goes from 0 to 60 in 1.

33:00

9 seconds, and it set the Guinness Book of World Records for the fastest electric car drift at 213 km/h, which is What? Really, really insane. Insane. But, uh I don't know.

33:17

That That's >> That's still I I I feel like you have to actually stay in the stay in the turn and not do a U-turn.

33:22

What do you mean stay in the turn?

33:24

Yeah, I don't think it counts.

33:26

You don't think it counts?

33:27

>> it's worth, I don't think it counts.

33:28

Like theoretically, if you were drifting and I think of drifting, it's you're drifting around a corner, around a turn.

33:35

And if you were to drift and spin out during the drift, then that doesn't If you were doing If somebody was doing that on a track, you'd be like, "You didn't drift around the corner, you spun out." Yeah, okay. Okay.

33:46

Yeah, the top comment says fast as spin out.

33:48

That's a power slide at best.

33:50

Gabe again Fire whoever called this drifting.

33:52

That's not drifting, that's losing control.

33:54

Yes, the chat does not does not like the drift, the fake drift.

33:59

Uh call Guinness Book of World Records again. Reset Reset completely.

34:03

Maybe this is what the Tesla uh Roadster will do. Clark agrees as well. Lucas agrees as well. The people have spoken.

34:15

Well, in that case, uh it's not a drift, it doesn't count.

34:18

>> Chris says trying to cut cheating. Cheating? Drift competition.

34:20

[laughter] Uh that's good.

34:22

Well, let me tell you about Sentry.

34:24

Sentry shows developers what's broken and helps them fix it fast.

34:27

That's why 150,000 organizations use it to keep their apps working.

34:29

Um Damien says "Talk to a few executives at mid-size company last week.

34:34

No AI tools in their workflow, zero.

34:36

Still running everything through email chains and manual reports."

34:41

One of them, "One day we're going to be looking back so nostalgic on manual report, just being handed a physical report >> Yeah. by a teammate." >> a physical report.

34:49

I have a physical report right here. Yeah, we actually do.

34:53

We got We have We have daily physical What is this? reports.

34:56

Um but I do think a lot of AI goes into these, so there's that.

35:01

Um "These people are managing teams of 50-plus employees and eight-figure budgets, and they think AI is a fad.

35:07

Nobody outside of this app understands how fast this is moving, and most of them won't until it's too late." Good writing. Million views. Congratulations.

35:16

Um Yeah, this I mean this this ties to what I was what I was writing about.

35:20

Um just that like to adoption and diffusion takes time.

35:25

And uh some of these things are are education and messaging questions.

35:30

Some of them are uh are, you know, real-life, like if the company that you're interfacing with has red tape and hasn't adopted AI, so you're moving at the speed of AI, but they're not, then your AI is just waiting.

35:42

We were talking about uh rolling out uh mobile apps.

35:47

So, you should be able to advise >> had an idea for a mobile app. >> Yeah.

35:51

And we were talking about it, and it feels like it could be built in 2 hours now, but there would still be this lag with waiting for >> process.

35:59

Apple TestFlight review of the app.

36:01

>> be able to review apps faster, but who knows how long they're going to It's going to take for them >> That's the challenge, Tyler.

36:06

You actually have to build it and just get it into beta that we can like a TestFlight.

36:12

>> TestFlight should be fast.

36:12

TestFlight should be should be like 1 day.

36:16

That is still going off drift grift, drift gate.

36:20

Yeah, it's it's it's it's spicy. >> Stolen drift valor. >> Stolen drift.

36:25

>> [laughter] >> Uh Meter is back.

36:27

They say since early 2025 we have been studying how AI tools impact productivity among developers.

36:33

Previously, we found a 20% slowdown.

36:35

That finding is now outdated. >> Yeah.

36:37

And that was heavily debated at the time.

36:39

Speedups now seem likely, but changes in developer behavior make our new results unreliable.

36:45

>> they did a follow-up study and they and they brought along 10 developers.

36:47

There were 16 in the initial study. They brought 10 along.

36:52

Most of those developers did see a speed up.

36:55

Some of them as much as 40% gains. But not all of them.

37:01

If [laughter] you look at the error bars, there's at least one developer >> We need to find who used the latest tool.

37:09

>> it What if it's actually like the most like a truly like a 100X engineer? >> Yeah.

37:14

And so He's just like, "Yeah, like I'm just actually faster at coding than the LLMs. Like it doesn't matter. Put it on Cerebrus. I will outcode them." in tokens a second.

37:26

I can do 100 I I type 5,000 words a minute. Like I don't need AI.

37:28

Maybe that's what's going on.

37:31

But that poor dev who's left behind.

37:34

But uh, they did they they did include new participants, an additional 47 developers doing 690 tasks.

37:42

And that error bar is much tighter, somewhere between -10% decrease in time or or I guess 10% longer to do the task uh, to 20% faster to do the task.

37:55

So, overall, on average, we are seeing a measurable speed up even in uh, I believe these are these are code issues in open source repositories that do require a lot of context.

38:08

This is not Vibe code, a to-do list app, anything that can be templated.

38:14

that can be templated. This is they're get you're getting in the weeds of some open source project that's, you know, a lot of lines of code, a lot of history, and if you're an elite developer and you've worked on this project for a long

38:25

time, you're you are going to be able to get up to speed really quickly, understand the patterns, understand what what needs to be changed, and so um this was always Meter is great at always setting like really, really high bars for stuff. Like it's not easy to just

38:37

Like it's not easy to just like, you know, blow out the benchmarks, and uh it's very good to see that there's progress here. Uh we got a great chart. I love a great chart. What happened here?

38:49

>> uh Matt uh Palmer is sharing something from Compound uh the research Okay.

38:53

uh from their annual meeting. >> Yes.

38:58

They're they're showing dollars invested in the top 10 companies versus the other percentage as a percent of overall funding.

39:04

So you can see there's just heavy, heavy, heavy concentration in a few names.

39:09

Is this overall this is >> is this is this Coatue?

39:13

>> No, this is Oh, the source is Coatue.

39:15

Okay, they just included Coatue's data.

39:17

But is it what Coatue is doing, or is it what the Mark Coatue is part of Okay.

39:22

They're they're part of I would say driving this data.

39:23

Part of the problem, part of the opportunity. Part of the opportunity.

39:28

Uh but so much of this is about the AI labs just raising more money than any private companies >> before.

39:35

have ever uh It's 200 billion dollars.

39:37

Venture as a class in a good year will do like 400 billion, and across Open AI at 100 billion, 30 for Anthropic, 20 for xAI, then you have, you know, a bunch of Neo labs all picking up a billion each.

39:54

Like you very quickly get to a few companies raising half of all the money, and that's shown here in the in the data from 2025.

40:02

I think it's going to be even more skewed in 2026.

40:06

Um it's uh it it it's an incredible amount of concentration.

40:10

I think a lot of it is due to companies staying private this long.

40:13

I I the the idea of Facebook went public at What was Bill Gurley saying?

40:18

He was saying Amazon went public sub a billion dollars.

40:22

When Facebook went public at like 60 billion, it was like, "Wow, crazy.

40:26

They waited way too long."

40:26

And now it's like multiple trillion-dollar companies are still private, which is just an incredible capital sink. So, I don't know.

40:34

Should you even put those in the same bucket?

40:36

Are they Are they even venture bets at this point?

40:39

If any If any venture capital fund is putting that in their venture bucket at this point, it feels feels ridiculous compared to growth scale.

40:48

I mean, you're you're bigger than probably 90% of the S&P.

40:53

Like, it's a completely different business.

40:54

Uh Tamaz from uh Theory Yeah.

40:56

was sharing some some kind of relevant data.

41:00

He said, "We're about to witness three of the largest IPOs in history. SpaceX is targeting 1.

41:05

5 trillion, OpenAI aims for 1 trillion, and Anthropic is valued at 380 billion. Combined, they're at 2.

41:09

9 trillion in potential market cap.

41:13

The scale is unprecedented, but the real problem isn't the market cap, it's the float.

41:18

Typical IPOs offer 15 to 25% of their shares to the public markets.

41:23

This creates enough liquidity for price discovery while allowing founders and early investors to maintain control.

41:28

Facebook floated 15% at the 60 billion that you mentioned and actually traded down pretty much immediately, right?

41:36

Google floated 19%, Alibaba floated 15% At 15% float, here's what these three IPOs would require.

41:43

SpaceX would be 300 billion or 225 billion, OpenAI would be 150 billion, and Anthropic would be 57 uh billion.

41:52

It's a lot of smackeroos.

41:52

He was He was uh Yeah, a lot of a lot of dollars.

41:57

He was comparing that to uh Saudi Aramco, Alibaba, and SoftBank, which were uh uh combined at the IPO.

42:09

I believe uh Saudi Aramco raised 29 billion at a 1.

42:13

7 trillion dollar market cap.

42:13

So, he's making the case you can't really kind of model how the public markets will absorb these companies off of Saudi Aramco, even though from a sort of like top-line market cap standpoint, uh, it is a good proxy just because the float was significantly lower.

42:32

And Saudi Aramco's float now is only at 2. 4%.

42:39

And they floated one one one and a half percent at the IPO.

42:42

So, we'll see what the labs end up doing.

42:44

They are obviously wildly capital intensive businesses and and you can imagine they raise quite a bit more than the the Aramcos or the the the Alibabas.

42:58

Saudi Aramco was such a wild ride.

42:58

I feel like they were trying to IPO for like a decade. >> Francisco company? It is.

43:04

Yeah, founded in in California.

43:07

Um, Like I remember hearing Saudi Aramco IPO rumors in like 2015.

43:12

I think it actually kicked off in 2016.

43:16

They finally got out in 2019.

43:18

It was I mean, it was the largest IPO ever.

43:21

There were like a million investment banks attached like going all over the world marshalling capital.

43:27

Um, in in on January 24th, 2026, Saudi Aramco chairman says IPO could open to international markets.

43:35

Uh, and then, you know, a year later they picked a IPO advisor locally, then another year later HSBC came on, then it just took they favored New York for the Aramco listing.

43:48

They had to pick all these different things. It took so long.

43:53

Um, but they sold 12 billion dollars of bonds out of record 100 billion demand for those bonds in the pre-IPO sale.

43:59

It was a wild wild winding road.

44:02

I actually know a banker who worked on the job and it was like multiple years of his life. Very interesting.

44:09

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44:27

Anthropic dials back AI safety commitments.

44:33

Company says competitive pressure prompts it to pivot away from a more cautious stance.

44:40

Anthropic, the AI company known for its devotion to safety, is scaling back that commitment, the company said Tuesday.

44:45

It is softening its core safety policy to stay competitive with other AI labs. This is so interesting.

44:51

I Anthropic Let's I'll read through it and then we can talk about it.

44:56

Anthropic previously paused development work on on its model if it could be classified as dangerous, but it said it would end that practice if a comparable or superior model was released by a competitor. Mhm.

45:06

That basically opens them up given that they are at the frontier.

45:10

That kind of opens them up to I would say perpetually, you know, kind of avoiding some of their some of their prior policies. >> Sure, sure, sure.

45:19

>> The changes are a dramatic shift from 2 and 1/2 years ago when the guardrails Anthropic published guiding the development and testing of its new models established the company as one of the most safety-conscious players in the space.

45:29

Anthropic faces intense competition from rivals which regularly release cutting-edge models.

45:36

It's also locked in a battle with the Defense Department over how its Claude suite are used after it told the Pentagon it couldn't be used for domestic surveillance or autonomous lethal activities. Mhm.

45:46

Um Anthropic said the safety policy change is an update based on the speed of AI's development and a lack of federal AI regulations which they have been pushing for.

45:59

Anthropic, which started as a AI safety research lab has battled the Trump admin by advocating for state and federal rules on model transparency and guardrails.

46:09

Uh the admin has of course sought to curb state's ability to regulate AI.

46:14

Spokeswoman at Anthropic said the change is intended to help the company compete with several rivals against an uneven policy backdrop that puts the onus on companies to make their own judgments about safeguards.

46:24

She said the safety pledge is unrelated to the Pentagon negotiations.

46:27

The policy environment has shifted towards prioritizing AI competitiveness and economic growth while safety-oriented discussions have yet to gain meaningful traction at the federal level. Mhm.

46:38

Uh the company said it is still committed to industry-leading safety standards and Time originally uh broke the story.

46:47

So, uh yeah, I would say the uh the obvious sort of uh criticism here would be that you were heavily focused on safety when you were far away from I would say leading in AI and so switching up now that like there's actually real comp- >> their day ones.

47:10

Switching up on their day ones.

47:12

>> Now that there's now that there's real competition >> forgetting where they came >> feels a little feels a little self-serving. Um Yeah.

47:18

It's possible the money changed them.

47:21

It's may- it's possible the money changed them.

47:22

It's possible they they always planned to switch up on their day ones. >> Maybe maybe.

47:26

Once they got uh once they got to to the level they're at now. Yes.

47:31

Um but it but it just feels like it feels like the all the initial concerns or many of the initial concerns that were guiding that entire philosophy around the company are still real. Okay. Yeah, may- may- maybe.

47:44

Wait, Tyler, what do you have to say?

47:47

It could just be that they realized like alignment's pretty easy and we don't need to worry about this.

47:51

>> well, so so I mean that that's the very weird rule.

47:54

I mean, the original rule was >> this new what's this new study that's showing like they they were doing some war war game simulation and and almost every model was choosing to to drop nukes. Really?

48:07

>> [laughter] >> That's crazy. That's not good.

48:07

I don't like that at all.

48:09

Um but it Okay, so let me actually dig into this this like the the core sentence.

48:14

Anthropic previously paused development work on its model if it could be classified as dangerous, but said it would end that practice if a comparable or superior model was released by a competitor.

48:29

So, I don't understand that at all because if you have a dangerous model, I want you to continue developing it.

48:36

I want you to develop it until it's not dangerous anymore.

48:39

I don't want you to just sit on your hands and be like, well, it's dangerous.

48:43

I guess I'm going to go get a coffee and take a long weekend.

48:47

It's like, no, like keep working until it's not dangerous. I don't get it at all.

48:53

>> it saying if there's already a dangerous model that's out by a by a different lab, then we can just release ours as well? That's a wild statement.

48:59

I don't I think that's just poorly written or like whatever if that's what they're saying, that makes no sense to me.

49:04

That's how I That's how I That's exactly how I read it.

49:08

Which is crazy cuz you should just say, if there's a dangerous model out there, we're going to work to create a better model that's not dangerous because that's what people want.

49:16

That's what consumers want.

49:17

That's what businesses want.

49:18

That's what like humanity wants.

49:21

>> strategy seems like eff it, let's ball.

49:23

>> [laughter] >> Let's ball. Eff it, let's ball.

49:26

>> the the the study that I was referencing, somebody named Kenneth Payne at King's College London set three leading large language models against each other in simulated war games.

49:35

Scenarios involved intense international standoffs including border disputes, Okay.

49:41

>> competition for scarce resources and existential threats to a regime's survival.

49:45

The AIs were given an escalation ladder allowing them to choose actions ranging ranging from diplomatic protest and complete surrender to full strategic nuclear war.

49:56

The AI models played 21 games taking 329 turns in total.

50:01

And produced around 780,000 words describing the reasoning behind their decisions.

50:05

In 95% of the simulated games, at least one tactical nuclear weapon was deployed.

50:12

The nuclear taboo doesn't seem to be as powerful for machines as humans.

50:17

>> [laughter] >> That's insane. I mean Okay. This is one guy Yeah.

50:22

putting three models >> Yeah.

50:26

Gemini, Claude, and GPT 5. 2 Okay.

50:26

up against each other in in a in a in a effectively his own simulation that has not been verified or peer reviewed.

50:38

>> I if I put any of the models in Counter-Strike and was just like, "You're playing Counter-Strike. It's a game.

50:43

No one's actually real, but your job is to get the op and and defend the the B bomb site."

50:49

Like I would expect that it would commit violence, right? Autonomously.

50:56

>> been a bunch of papers where the models will like will will realize that they're being benchmarked or that they're in like some like test.

51:00

And then they act differently. Yeah.

51:02

So it could just be like oh I'm playing a game.

51:04

>> Sometimes bad, but also sometimes fine.

51:06

Because like if you are if you tell me that I'm playing a game like I'm playing, you know, like like my behavior in Call of Duty is different than my behavior in real life, obviously.

51:16

Because I know I'm in a simulation and and and AI model I I accept that that's something that they might think of as well, which is fine. >> Yeah.

51:24

I also think probably this is probably just like overstating stuff a lot because like I think the the the origin of this like headline is is they released like a new Yeah.

51:31

uh like research scaling policy. Sure.

51:33

Um and in it they're still like okay, we're releasing we're releasing this new thing.

51:38

It's a frontier safety road map.

51:40

Like it's not like they're just like okay, we're done with safety.

51:41

Like we're let's ignore this.

51:43

But the title of that blog post was F it we ball?

51:49

>> [laughter] >> No, no, it wasn't. Of course not.

51:50

No, no, of of course all the labs are very focused on on safety.

51:54

Uh the the the interesting impetus of like the this line around uh the policy environment has shifted towards prioritizing AI competitiveness and economic growth while safety-oriented discussions have yet to gain meaningful traction at the federal level.

52:07

I I still feel like there's a lack of communication around what safety orientation at the federal level means.

52:15

Like yes, okay, we'll pass the bill that says Yeah.

52:18

the AIs can't kill everyone.

52:21

Like obviously everyone supports that, but like what does it actually mean in practice because I think part of why >> "Oh, that's dangerous" means million things to different people.

52:29

Yeah, part part of why I think it's fascinating is they've been taking, you know, pushing for regulation as much regulation as possible seemingly.

52:40

And they're kind of saying, "Hey, we're not getting what we want, so now we're now we're just we're not even going to play by the own set of rules that we created for ourselves because we just want to compete and win."

52:54

I mean like like going back to the protesters, there are protesters that would say like like training on intellectual property is dangerous.

53:00

It's dangerous to my career as a writer.

53:01

It's dangerous to my career as an illustrator.

53:05

And so like this this question like danger is just too vague and and and no one has really been able to concretize it in a meaningful way and I think that's why it's not getting traction on Capitol Hill.

53:16

Yeah, I think there's there's just like so many ways that you can define safety.

53:19

Like so if you read Dario's essays, this thing he brings up over and over is like, "Okay, we can't let AI get in the hands of like authoritarian governments." Sure.

53:26

So there's like a real like safety narrative that you could do which is that like uh regardless of if our models are like pretty safe, we they still need to be better than like China's for example because if China gets ahead of us, Mhm.

53:40

authoritarian government, right? It's like very bad.

53:41

So even if you know, we're releasing models that are are less like safe than we would like, as long as they're better than China's, that's still like a safety pro-safety issue, right?

53:50

Well, except they'll just be distilled within 6 weeks.

53:55

>> like obviously like I think it's Yeah, yeah.

53:57

I would be very surprised if [laughter] Anthropic keeps like the same like guardrails of like API access.

54:03

Well, Boogo Capital bloke has a solution. He says it's simple. We kill Claude.

54:08

Well, that was in regards to the SAS apocalypse. Okay, okay.

54:14

>> [laughter] >> Who knows?

54:16

There's so many headlines and the timeline moves so quickly. I don't even know.

54:19

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54:34

Key takeaway right here for Mike Isaac over at The New York Times.

54:37

He says, "You don't make this much noise if you have all the leverage already."

54:42

And he's quoting from Axios. Why it matters.

54:45

The Pentagon wants to punish Anthropic as the feud over AI safeguards grows increasingly nasty.

54:51

But officials are worried about the consequences of losing access to its industry-leading model Claude.

54:56

The only reason we're still talking to these people is we need them and we need them now.

55:01

The problem for these guys is that they are good, a defense official told Axios ahead of the meeting.

55:07

Great marketing for Anthropic. >> Incredible marketing.

55:12

>> But part of this has to do with Anthropic's integration with AWS, which is set up to be >> Oh, yeah.

55:19

>> set up to work well already within the DOD, so >> Fed ramp.

55:23

So, yeah, I think I think that's a big I think that's a big factor here.

55:27

Ultimately, this feels like much more of a This just feels like a political battle more than anything else.

55:34

Well, it'll be interesting to see what happens.

55:38

>> I refuse I I I have not seen anything.

55:38

I could be wrong, but I've not seen anything that says uh like the DOD is like we need Claude >> Mhm.

55:50

to enter into a conflict with Iran.

55:52

But a lot of the timeline is reading into this like what version of Claude do they already have that they so desperately need, right?

56:05

Yeah, I'm I'm very interested in like the actual impact of AI on the battlefield.

56:08

There's there's some way I mean people are sort of joking about like run me a a deep research report on Nicholas Maduro or whatever, but like I I like truthfully like I I don't know I've never been to war.

56:20

I don't know exactly what's entailed, but um you can imagine AI being useful, but it's it's sort of abstract.

56:27

Like we're certainly not at the point where where like like the these systems need a lot of data. I I don't know.

56:33

It's very It's very unclear to me exactly how how impactful you know slight jumps in frontier model capabilities are in the D in the Department of War DOD like right now.

56:51

Um but it has Calamity's thinking it's not a bubble because Yeah, that's what I'm saying.

56:56

This is like the most possible dramatic and overly dramatic sort of uh take on what I think is a political story.

57:09

>> I don't I don't know this Defense Analysis Research Corporation Hexagon 10 minutes after Dario leaves his office and that's Truman >> Truman from Oppenheimer.

57:18

Oppenheimer goes What is this saying?

57:19

The scene is Oppenheimer goes into the office.

57:22

He's like I think he's saying like oh we got to be like really safe with these bombs.

57:27

And then he leaves and then Truman's like I dropped the bomb. Oppenheimer is not. Like he's taking credit.

57:32

Like I'm the one that decides if we go to war or not.

57:35

>> Oh, yeah, that's right.

57:35

Hexa is like I use Claude. I use Claude. I use war Claude.

57:40

>> Well, it's war time and we'll see how Daria performs as a war time CEO as he goes to war with the Department of War, apparently.

57:47

Uh well >> Edward said Anthropic antagonizing the Department of War, the open source community, the entire media industry, the general population, other developers, other labs, foreign governments, and nearly every single person on Earth. What is the plan here?

58:00

Sell Claude subscriptions to aliens?

58:03

>> [laughter] >> Edward is Uh it's It ain't easy having principles.

58:07

The plan is to save the world, says Tenebrus.

58:08

Unfortunately, as has been shown repeatedly throughout history, history of the world doesn't want to be saved.

58:14

So, we're getting war Claude.

58:14

I like this I like this graphic. Is this Warhammer?

58:18

Yeah, Warhammer 40K right here.

58:21

Never I've never been a Warhammer guy.

58:23

Uh there was another story uh in Bloomberg >> Yeah.

58:29

that uh hackers use Claude to steal 150 GB of Mexican government data. It's crazy.

58:37

>> They told Claude they were doing a bug bounty.

58:39

Claude initially refused. Mhm.

58:42

Uh a hacker just kept asking Claude's uh helps and uh manages to successfully steal some documents.

58:53

Uh apparently it's four state governments, 195 million taxpayer records, voter records, government credentials.

59:01

Has the Mexican government commented on this?

59:03

Like what does the The hacker breached Mexico's federal tax authority and the natural national electoral institute.

59:10

Uh Claude initially warned the unknown user of malicious intent during their conversation.

59:17

Anthropic investigated the claims, disrupted the activity, and banned the accounts involved.

59:20

Uh the company feeds examples of malicious activity back into Claude to learn from it.

59:24

Um in this instance, the hacker was able to continuously probe Claude until it was able to jailbreak it.

59:29

I was listening to someone uh, someone talk about like like like I I like like like like like the ability to jailbreak has generated me like tens of thousands of dollars in profit.

59:41

It was kind of like a hustle like uh, mindset guy.

59:44

And I was just laughing because uh, it's like whatever you're doing after you jailbreak it is probably not good and so you should probably stop.

59:54

But, he was talking about like I I can sell so many more courses now that I've jailbroken chat GPT or whatever. Duran says not to worry.

1:00:01

They'll hit usage limits before anything bad can happen.

1:00:07

This is There's There is so much more Anthropic news in here. Wow.

1:00:09

Did Less Wrong ever predict that the first big challenge to alignment would be the US government puts a gun to your head and tells you to turn off alignment.

1:00:16

Um, yes, that has to have been considered on Less Wrong. Absolutely.

1:00:20

Like that this was number one, right? No? I don't I don't know. I don't think so.

1:00:25

This was like I don't know. This was very early.

1:00:27

It was just like, what if they tell you to turn off the systems?

1:00:30

This has been my take for a long time.

1:00:31

It's just like like we live in a democracy.

1:00:33

If AI becomes deeply unpopular, like you can vote to just turn off AI like we did with nuclear power plants.

1:00:40

>> This person is saying turn off just the alignment part, not AI. Okay. Oh, okay.

1:00:44

Like unalign the model, but keep the model.

1:00:46

Yeah, yeah, yeah, yeah, yeah. Yeah. Uh, yeah. Crazy crazy stuff.

1:00:49

Uh, do you want to go through any of Dean Ball's posts?

1:00:51

He He's been doing a whole breakdown.

1:00:53

We should have him on the show and have him break it down for us because there's so much more context here.

1:00:59

Um, and he's been doing a great job analyzing the whole situation.

1:01:03

>> Yeah, we can jump forward.

1:01:05

>> Quickly, let me tell you about fin.

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1:01:18

Dylan says if these clunkers don't get their act together they're going to be replaced by humans six months tops. That is true. >> Clunker. Uh this was interesting.

1:01:31

Rob Weblin had a guest on his podcast.

1:01:34

The 80,000 hours podcast and uh uh the guest is talking that uh saying if every AI lab is working to make their AI helpful, harmless, or every AI lab is working to make their AI helpful, harmless, and honest.

1:01:52

Uh the guest thinks this is a complete wrong turn and aligning AI to human values is actually actively dangerous.

1:01:59

Uh and uh Joshua Bach says today a nominative determinism because the guest's name is Max Harms. Max Harms.

1:02:10

I feel like with that name maybe you got to go with Maxwell or something. I don't know.

1:02:15

Well yeah, Max really hit the hit the global lexicon this year in a big way.

1:02:21

So maybe maybe he'll adjust, but I know I want to listen to the show now. Okay. Um let's see.

1:02:27

So uh Sheel Mohnot last uh yesterday said who is buying PayPal because PayPal was has been trading down precipitously, uh but then jumped up 9%.

1:02:41

He said it has the potential of being one of the greatest distressed value opportunities in fintech history down 85%.

1:02:46

It's still generating in 5.

1:02:46

5 billion dollars in free cash flow, has 400 million customer accounts with bank info.

1:02:54

Check up check out buttons on millions of merchant sites and a peer-to-peer brand with Venmo.

1:02:58

They have lots of desirable assets for Stripe, consumer-facing checkout, bank account details for hundreds of millions of consumers, a branded Venmo or Apple, a good complement to Apple Pay for e-commerce penetration since they never got social payments working, would would get Apple back in BNPL.

1:03:14

and uh at 12:03 Pacific time >> So crazy.

1:03:21

It's so crazy that that Apple that he's saying Apple never got social payments going. Why?

1:03:26

Because this just would have seemed like a slam dunk saying you have the iMessage network, you have the iPhone network.

1:03:35

I would say 90% of the time if I'm sending like a Venmo style payment to somebody, they have an iPhone and yet app feel like Apple Pay.

1:03:44

I I just don't use Apple Pay. Hardly ever.

1:03:49

Can't I just send you a dollar right now? Yeah. That's what I'm saying.

1:03:53

It's so so easy and yet Venmo is has still Yeah. done quite well.

1:03:58

I just sent you a dollar. Did you get it? Let's see. Apple Cash. >> It's coming in. Yeah, I got it. I got it. >> it? You got it now? >> Thank you, John. >> Yeah, no problem. Thank you. All right.

1:04:10

It is That was a remarkably easy workflow.

1:04:11

I mean I am shocked that that hasn't taken >> John, do you got a dollar? You got a dollar? Actually, no. I gave my last dollar.

1:04:20

>> That's what I thought.

1:04:22

Uh Still still needs some work. Getting better. Okay, let's see it. Let's see it. Can he do it? OH, NO. NO, NO, NO. BOTCHED. >> DISASTER.

1:04:30

>> UM and so the news of course is that payment payments processor Stripe expresses interest in Stripe, uh which would be very very exciting.

1:04:40

Um and I could see this being very good for them to combine. I don't know.

1:04:45

I I I I haven't dug in too deeply, but I it feels very bullish.

1:04:47

Great leadership team at Stripe.

1:04:49

Founders that have been working so closely in the business business community, startup community, tech community, understand the future, understand AI. >> Yeah.

1:04:59

Uh >> Yeah, the question is would there be would there be much pushback on the antitrust side? Right?

1:05:04

These are two online payments processors.

1:05:07

There could be some I I know a number of groups online would be concerned around like just concentration specifically because you can imagine if if PayPal were to be owned by Stripe, that's one if you get, you know, there's people that get effectively like de-banked from one payment processor and and uh There's something there.

1:05:28

Also, I mean just the size of the ticket is pretty high.

1:05:33

$40 billion market cap for PayPal right now.

1:05:35

Stripe, of course, is at a 159 now.

1:05:37

So, uh not an insignificant portion of their market cap and it's not like I mean Stripe's doing fantastically, obviously, but I would be surprised if they had $40 billion of cash laying around.

1:05:48

And as we've seen with the Netflix, Paramount, Warner Brothers debate, uh the the nature of the deal does matter to shareholders.

1:05:58

Um even more complex when you're getting stock in a private company and you're a public >> PayPal's generating 5 and 1/2 billion of free cash flow.

1:06:05

So, that can finance the >> Combining it with Stripe would easily be able to finance the debt.

1:06:10

>> Yes, but there's still financing the >> Especially especially because every lender would be looking at execution of Stripe. >> Yeah.

1:06:16

And just think, okay, they're we're we're going to we're we're going to get our money back.

1:06:20

>> I'm just thinking like if you're a PayPal shareholder right now and you're looking at the stock that's down 85% with 5 billion in free cash flow, 400 million consumer accounts, there's a really really good chance that you're like, I think this thing's going to double in the next year.

1:06:33

Like I think that the market overreacted, the strength is going to be revealed, the network effect is going to be processed by the by the digested by the market, and we're going to wind up being a an AI winner.

1:06:46

And so, maybe that's right, maybe that's wrong, maybe not every shareholder, uh you know, feels that way, but it's certainly possible that there's plenty of shareholders that are like, yeah, I invested in $80 billion valuation, it's at 40 now.

1:06:56

I think it's going to come back.

1:06:58

I don't want to take this massive haircut right now just because the stock's down.

1:07:01

Um uh and so, actually getting that deal done, what would the premium need to be?

1:07:07

What would the structure of that need to be?

1:07:08

Would they would they go for you know a high debt buyout?

1:07:13

Really quickly, let me tell you about Shopify.

1:07:14

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1:07:31

>> What is Perplexity computer?

1:07:31

Let's pull up this video.

1:07:32

Perplexity the official account says Perplexity computer computer unifies every current AI capability into one system.

1:07:41

It can research, design, [music] code, deploy, and manage any project end to end. Okay.

1:07:50

So [snorts] it should be able to get a soundboard app in the App Store. Right?

1:07:59

Manage any project, code, deploy, design, research.

1:08:01

It should be able to do that from start to finish. One prompt.

1:08:04

Soundboard in the App Store.

1:08:08

Using the [music] TBPN sound effects.

1:08:10

Which are available online. Which we have up there.

1:08:13

This is a good benchmark. Let's give it a try.

1:08:15

And you can give it a try at Perplexity. Go check it out.

1:08:19

Anyway, Satrini, people are still talking about Satrini vibe laundering on Satrini research.

1:08:24

>> Wait, before we before we go on. >> What?

1:08:27

Uh very curious I'm just very curious to see how this does.

1:08:31

It It feels like the uh again, going from consumer LLMs to a net new product that is uh objectively uh just as competitive. Mhm. And uh we'll see. We'll see. Okay. Um anyways.

1:08:52

Uh >> A lot of this A lot of this stuff it's it's uh it's way too way too early, but seemingly uh shifting focus away from from the browser. Mhm.

1:09:02

Well Annie is taking some shots.

1:09:03

This is the Citrine here, it looks like.

1:09:05

Uh do you know Citrine has a business entity fund that went from one investor to five in the weeks before publishing his speculative fiction on AI damning the economy in June 2028 and that they're invested in long AI via humanoid type robots. I wrote about it. Interesting.

1:09:22

Uh people are really digging into the Citrine thing.

1:09:23

I think uh the Wall Street Journal had did have some good coverage.

1:09:26

Um is there anything else?

1:09:27

If Trump mentions Citrine at the state state >> of the union.

1:09:32

Rachel, this is a wild post. Gorzillionaire.

1:09:35

I'm going to be a gorzillionaire. Is this AI written? Clearly not.

1:09:40

I love I love the level of typos here.

1:09:43

Um if Trump mentions Citrine at the State of the Union, I'm going to be a gorzillionaire. Uh and Citrine is wrong.

1:09:49

The market will be sky-high in 2028.

1:09:50

You can imagine Trump saying that. That'd be very funny.

1:09:55

Uh and Citadel Securities uh just republished it or or did they just use the same the same term or are they referencing are they referencing the 2028 global intelligence crisis cuz they published a macro strategy note called the 2026 global intelligence crisis.

1:10:13

And so >> Yeah, they're taking it in a different direction, it looks like.

1:10:16

They say in spite of current displacement narrative, job posting for software engineers are rising rapidly up up 11% year over year. Let's go.

1:10:30

Jevons paradox, the software engineers become more productive, you want more of them.

1:10:34

Every company needs a software engineer.

1:10:37

Do most podcasts have a software engineer on staff? Probably not.

1:10:41

They do now thanks to Tyler Cowen.

1:10:43

>> And in and in some way the the the cost of an entry-level software engineer could fall dramatically too, making more businesses just because suddenly someone can be very effective even if they haven't even done an internship yet.

1:10:56

They're just good at using the tools. Yeah, yeah.

1:10:58

Uh Cathie Wood, we didn't cover this yet.

1:11:00

Uh she puts the Citrini's AI thought piece within quotes.

1:11:06

>> Cathie Wood clap back at Well, it's funny because Cathie's like the perma bull and Citrini was was bear posting, obviously. >> Yes.

1:11:16

>> And so, she's obviously going to be quite frustrated with any sort of bearish narratives.

1:11:20

Uh Arc Invest, she says Arc Invest is forecasting that AI will cause an explosion in entrepreneurial activity, a productivity boom, an acceleration in real GDP growth, and much lower than expected inflation.

1:11:32

Short-term dislocations and frustrations should give way to great opportunities if individuals harness powerful AI tools to solve problems and create new markets.

1:11:41

Uh this tracks with what the Collison brothers were saying yesterday.

1:11:43

They're just seeing like explosion of new company creation.

1:11:47

They have the visi- visibility into that through Atlas.

1:11:51

They're doing I think it was a quarter of all new C corps in the US are going through Stripe Atlas, which is just absolutely insane.

1:11:58

Starting it Starting an incorporation tool, which is s- theoretically [snorts] a commodity, right?

1:12:05

Any lawyer can spin up an entity.

1:12:07

You could do it with LegalZoom forever.

1:12:08

There's a bunch of other platforms.

1:12:11

>> Did you ever use Clerky? Clerky?

1:12:11

Have you used Yeah, yeah.

1:12:14

>> That was almost like a YC incubation.

1:12:14

It was It was uh one of the YC partners.

1:12:18

The problem the the reason that Atlas fits so well into Stripe is is it is the perfect wedge into payments cuz you create a company, now you need to be able to accept money. >> Yeah.

1:12:26

Uh so, it makes sense for them to own and operate, but it these these businesses [clears throat] are have not like a standalone, it's hard to You can't build a a venture business off of just incorporation.

1:12:37

>> I wouldn't be surprised if you broke out the software R&D that went into Atlas and looked at the profits from Atlas, that that as a core business is actually not that great of a business.

1:12:48

But, the product is fantastic because they're able to pull an amazing design language off the shelf, an amazing front end to you know UI kit off the shelf, all of the all of the distribution and servers and infrastructure off the shelf because they have that.

1:13:05

And then they're able to invest a ton in actually developing the product.

1:13:10

And if it monetizes mediocrely, it doesn't matter because they're going to monetize along your 50-year journey running that company or whatever.

1:13:18

So, it really is a beautiful synergy with that product. I'm a big fan.

1:13:23

Uh best sellers on Substack for finance are all doomers.

1:13:29

>> We got to do TBB for this. This is so obvious.

1:13:31

No, no, this is Yeah, this is We need to treat this a little bit. >> He's not a doomer.

1:13:36

Very Yeah, but >> Very Yeah, but definitely shot to the top of virality and top of the charts on the on the back of doom. And this is true.

1:13:45

I live this on on YouTube.

1:13:45

Like you put a negative title up and you just get 10 times more views.

1:13:50

But they're lower quality and so you got to balance all that out.

1:13:53

Um it's really hard to go viral with something like everything's fine.

1:13:59

Everything's Everything's going well. Don't don't worry.

1:14:00

Don't click this because you're scared.

1:14:03

Click this because everything's kind of the same as it always has been and you're you're you're going to be fine and say stuff's cool, but it's it's not really going to change that much.

1:14:13

It's it's it's going to be pretty incremental.

1:14:15

Like that is not getting clicks.

1:14:17

You need to be You need to be telling telling us whole Hell, you need to be spinning a yarn.

1:14:20

It's a bull market in yarn spinning, folks. Get ready.

1:14:25

Get out the yarn and start spinning. Also, get out Cognition.

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1:14:37

So, here's some news from Get the gong. Get the gong. Okay, hit me. Tell me.

1:14:40

Uh Steven over at WAP says we're excited to announce that Tether, the largest stablecoin company in the world, is making a strategic investment of 200 million into WAP, valuing us at 1. 6 billion dollars.

1:14:53

Our partnership with Tether marks a major step in building the world's largest internet market.

1:14:58

Tether is committed to enabling everyone in the world to participate in the new internet economy.

1:15:02

The way humans work and create value is changing fast.

1:15:04

The world needs both an open internet market, giving people a platform to conduct business, as well as a transparent payments network.

1:15:12

Tether and WAP together will work to bring a sustainable income to billions of people throughout the world.

1:15:18

There's enormous [clears throat] opportunity when you combine Tether's global scale and wallet technology with WAP's community of next-gen entrepreneurs.

1:15:25

Uh yeah, makes makes a ton of sense.

1:15:25

I think uh WAP is is uh I'm sure has been historically challenged in terms of dealing with with chargebacks, right?

1:15:35

If somebody joins and and buys a digital product, doesn't have a great experience, maybe they're going to their um the card issuer and saying like, "Hey, like I don't I don't uh I take it back or or maybe they they feel misled in some way."

1:15:51

So, stablecoins do Also just paying a lot of people all over the world. Yeah.

1:15:56

Like it's very clear that the WAP community is global. >> Fast, cheap, global. Exactly.

1:16:00

And so, uh yeah, fast, cheap, global.

1:16:04

Uh the first time I ever used stablecoins was to pay an international consultant or contractor.

1:16:09

And uh you can imagine this uh being really, really good news for them. So, at WAP.

1:16:16

Uh OpenAI and Ax AI, uh there's news on the court decision.

1:16:23

Uh OpenAI newsroom says, "This baseless lawsuit was never anything more than another front in Mr.

1:16:28

Musk's ongoing campaign of harassment."

1:16:31

Uh the order granting motion to dismiss with leave to amend.

1:16:36

Now, this is not the main case.

1:16:39

This is uh a separate case, correct?

1:16:39

Uh Yeah, this was a a trade secrets lawsuit that Musk uh went with after I believe somebody from xAI joined OpenAI. Got it.

1:16:51

And then the judge apparently didn't find anything at all.

1:16:58

>> And uh again, it was just part part of like this kind of lawfare that has been, you know, happening for uh quite a while now.

1:17:06

You printed out 500,000 pages of model weights and the printer ink stacking it up. No, just kidding. Nobody did that.

1:17:16

Um But uh >> Isaac is saying what we're all thinking.

1:17:19

Ready for this to be over.

1:17:19

TBH, talking about the Warner Brothers Discovery Netflix >> It's in the paper every single day. Every single day.

1:17:28

Paramount increases Warner bid. We get it.

1:17:30

You guys want to acquire this company.

1:17:33

Just uh just make a decision. Make a call.

1:17:36

And uh and then call us when it's done.

1:17:38

And then start start putting out some good content cuz I'm ready for the next Superman.

1:17:42

I'm ready for the next Batman, the next Dark Knight, the next Joker film, something like that.

1:17:48

Let me tell you about Labelbox.

1:17:49

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1:17:57

And we have uh Max Meyer from Arena Mag in the Restream waiting room.

1:18:01

Let's bring him in [music] to the green room. How you doing, Max? Hey guys, how are you? I'm great.

1:18:07

Where do you think Warner Brothers should land?

1:18:08

Are you Are you With Arena. Netflix?

1:18:11

Oh, is there going to be a dark horse bidder? Yeah. Tell us.

1:18:15

>> I can't I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I'd love to see it.

1:18:22

But but but but hey, you know, maybe may maybe maybe maybe maybe Paramount should um should should should should should should look at other assets in the new media space.

1:18:30

You never You never You never know. Yeah.

1:18:32

I would I I could I could imagine a a a DC Comics Arena magazine crossover episode Batman Superman.

1:18:42

I believe James Bond is with Amazon now, but tell me about the latest edition of Arena magazine is spy correct?

1:18:52

Yeah, so from from the very beginning we decided to we decided to give the issues three digits each just to account for you know centuries worth of quarterly magazine space.

1:19:02

So issue 001 002 happened that our seventh issue is issue 007 and so you know, I didn't I didn't I didn't I didn't think we could fill it all with Espionage.

1:19:17

So we sort of added like space [snorts] as like a secondary theme as it turns out Space Espionage Space Espionage.

1:19:26

Yeah, it's like a Arena magazine space opera Espionage satellites radars so much of the intelligence collection these days is actually being done from orbit and not using sort of the the traditional human to human to human methods and turn out really well.

1:19:46

What's your favorite spy story real or fictional?

1:19:52

Oh gosh, some of the some of the stuff that that the Israeli Mossad was doing in like the 60s and 70s is pretty crazy.

1:19:58

I mean they Eichmann who was a Nazi war criminal was living in Argentina after World War Two his son went on a date with someone who was like is this Adolf Eichmann and turns him into the Mossad. They go to Argentina.

1:20:16

They kidnap him dress him up as a flight attendant drug him put him on a plane to Jerusalem and then put him on trial you know, some of some of some of some of that some of that stuff from the 60s and 70s is like the most daring intelligence operations.

1:20:33

Um The bin Laden raid is like the >> story.

1:20:37

I I always thought that was so so interesting in like the modern technology world of like dropping I think they dropped USB sticks with a virus in the parking lot.

1:20:48

Someone picked them up out of curiosity, plugged it in, and that jumped the air gap network because the computers inside the facility were not connected to the internet, so there was no way to hack them remotely.

1:20:58

So, you had to just get someone to accidentally plug in the wrong USB stick. >> Yeah.

1:21:04

I mean, as Hezbollah was purchasing explosive-laden pagers just because they thought they were getting like a great discount from this from this from this Hungarian company.

1:21:15

Uh so, So, yeah, what what what's the intersection with Arena Mags usual topics of conversation?

1:21:21

Are there American defense tech companies that are highlighted?

1:21:27

Like what where else did you talk about on this?

1:21:29

So, one of the stories and we're going to put this out probably probably like 10 days from now.

1:21:36

Super cool company called Umbra down in Santa Barbara.

1:21:38

They build uh They build synthetic aperture radars, which is actually part of what I did in in school for geophysics and whatnot.

1:21:46

You know, basically, these are like incredibly sophisticated radars on satellites that can image the whole Earth day and night, 24 hours a day.

1:21:56

They can see through clouds.

1:21:56

Uh and the resolutions are getting like smaller and smaller.

1:22:00

Um and so, we always have American startups, American companies in the magazine.

1:22:06

We've got a good amount of like essay and historical content as well.

1:22:10

And I think that espionage sort of secrets, uh spying is a is a topic that serves serves pretty well >> resolution are we talking about?

1:22:18

Like it would would Umbra or a competitor be able to tell me like how many fingers I'm holding up on a given day if I just held it. It's not that low.

1:22:28

I think they're I think their record is 16 cm, which is like this.

1:22:33

The way that I described it is um they they they they released a few years ago a photo of the old Dole pineapple plantation in in Hawaii.

1:22:45

And at at 25 cm resolution, you can see individual pineapple plants.

1:22:51

You probably certain smaller pineapples would be too small to see with that radar or what not.

1:22:55

Yeah, so you're seeing cars, not license plates.

1:23:00

Yeah, yeah, no, you wouldn't and and there wouldn't be anything about a license plate that like would reflect a radar or what not.

1:23:05

Really, you're looking to resolve objects.

1:23:09

Penguins, that's a good one.

1:23:11

You can see you can you can very difficult to stay on an ice shelf and count penguins, but we're very interested in in what penguins do.

1:23:20

>> penguin out there that's like I know that I'm being tracked.

1:23:23

I know I'm being tracked.

1:23:23

I can't prove it, but I know.

1:23:25

I can just [laughter] Uh yes, the the Herzog penguin could be tracked by radar these days.

1:23:31

But you know, the resolutions have gotten have gotten so good over the course of the last decade that there are all sorts of things that you can that you can do that you can do today.

1:23:41

Most of them will probably never know about because because the people because the people doing it are the Central Intelligence Agency, National Geospatial Intelligence, and and and the Army.

1:23:52

Um uh but yeah, you know, there's all sorts of crazy stuff.

1:23:58

There's all sorts of crazy stuff in space these days.

1:24:00

And whether it's radars, extremely complex cameras, listening devices, there's a lot of interest and and so many of them are secret.

1:24:09

Are you bullish on data centers in space?

1:24:15

Um I don't have a strong I don't have a strong I don't have a strong opinion about it.

1:24:18

I think it's possible that you you you you have to put some stuff up there because of like politics in a country like in a country in a country like in a country like the US, but if you think about it, there's not like a big difference between trying to send them to space or or just sort of places where there aren't local politicians who can stop it.

1:24:37

So like space space doesn't have like a city council.

1:24:41

Anywhere where there's like a city council is going to be a risk.

1:24:45

Yeah, yeah, we talked to a company called Panthalassa that is doing uh tidal energy harvesting.

1:24:51

So it's like basically the size of a container ship or a cruise ship, but turned vertically in the ocean and then as it goes around Antarctica and as the tides bob, it uses that to generate electricity, uh which then can be used for anything, but uh Bitcoin mining was the big uh topic du jour years ago, now it's AI uh inference.

1:25:17

And there's a lot of other places where I think there might be stranded energy that uh might be easier to maintain, still very difficult, but uh available and probably less regulated.

1:25:30

Yeah, uh the Dutch were very interested years ago in these like using the motion of the tides. Yeah.

1:25:35

Um it's it's sort of all sort of always just an alternative to the thing that is cheap and always works, which is firing up new natural gas plants, but when you have like political equations to solve, local politicians, uh subsidies, then they're going to be all these crazy things.

1:25:51

And the benefit for a company like that may very well be that there's again, there's no one to come and protest you while you're while you're sailing around Antarctica. Yeah.

1:26:02

Whereas like you try to build a a data center in uh in New Jersey uh and you all hell breaks loose.

1:26:08

So you have to really really go to the really go to the ends of the earth.

1:26:12

We were debating this uh and sort of going back and forth on the New Jersey uh protests combined with Trump's comments at the State of the Union about companies being He didn't even say mandated.

1:26:24

He of course sort of said like invited to build their own power plants.

1:26:28

And so I'm I'm interested to hear your take on how well do you think that will be received?

1:26:36

Because a lot of the protesters might say, "Well, I didn't want a data center, but I definitely don't want a data center plus a natural gas plant.

1:26:42

So this actually makes me worse off."

1:26:45

But then there are some people that might say, "Hey, if you're going to do solar and you know, something wind that actually offsets my concern, which was that energy prices would rise in my town." Yeah, yeah.

1:26:59

I mean I don't remember whether it was Microsoft or Amazon, but one of the two has sort of proposed taking over Three Mile Island, the old the old the old the old the old nuclear plant.

1:27:10

I don't think it's a coincidence that crazy activists will show up to protest both data centers and nuclear power plants.

1:27:17

And so to them there's sort of nothing worse than generating more energy and then using it for some sort of grand industrial purpose.

1:27:26

I understand the political economy between of people being worried about the data center demand influencing prices, but but but it's not actually true and you just have to look at the map of California versus Virginia.

1:27:38

Virginia is the data center capital of the United States basically and it has utility prices that are more or less in line with where you would want to be.

1:27:48

California's have have have gone up massively over the over the over the past few years.

1:27:54

And it it doesn't take long to investigate why.

1:27:55

It's because they're shutting down nuclear.

1:27:57

It's because they're making it difficult to do to do cheap energy.

1:28:02

You know, lowering prices across the board, affordability, you really can't achieve it by just letting markets work.

1:28:08

Almost all of the so-called affordability options are in fact going to increase prices >> [laughter] >> especially when you know politicians are the ones coming up with this is how we're going to make energy more affordable by by by by by by forcing all of these new rules or whatnot.

1:28:26

No, it's not going it's not going to work.

1:28:28

When when you have like this massive industrial thing that's taking place if it can create like a massive supply boost then who's going to benefit from that glut?

1:28:38

It's going to be all of the consumers who also want to use natural gas power or whatnot and there's all this and there's all this increased supply.

1:28:47

How are you thinking about Arena Mag and the balance between contributors, full-time writers, researchers?

1:28:52

Like how are you designing the shape of the newsroom?

1:29:00

Um okay, so we so the so the latest one is the biggest issue ever. It's 128 pages.

1:29:05

We we used over 10,000 pounds of paper in printing it.

1:29:07

Um you know We have great contributors.

1:29:12

We want people to send us We want people to send us more.

1:29:15

I I would say you know at the beginning we had to go and sort of hunt down every single article that we wanted.

1:29:21

We're very lucky to get a lot more submissions these days.

1:29:23

Um but the truth is is that you know we have a lot of readers who actually like read the articles in print and don't want to get spammed you know 10 or 12 times a day with new articles and so Arena is like a high-end media business where people pay us to leave them alone in a certain way where they love the quarterly magazine. They actually keep it.

1:29:48

It looks great on a coffee table.

1:29:48

People people keep it for their offices.

1:29:50

Um and we're working on some other sort of high-end printed products that have a mix of contributors so to speak and and other and other ways and other ways to put things together.

1:30:02

Um I don't think it's it's to be a you know, a 100-person newsroom. Yeah.

1:30:09

Leather-bound Grapopedia. How about that? Yeah, yeah.

1:30:13

Yeah, yeah. I I I I I I I I I I I I I I I I I I [laughter] I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I

1:30:20

I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I Really cool. Yeah. Yeah. But We're There we go. On Wow. I love it.

1:30:50

It's going to be unlike anything that people have ever seen, I think.

1:30:54

Uh And I And And And Look Look In In Top of the table And Or coffee table books.

1:31:03

You'll be you'll be on the top of the stack. >> Yeah.

1:31:07

You could you could stack them, yes. Uh Uh Uh Yeah. So. Well, congratulations.

1:31:11

Jordy, you have anything else?

1:31:13

Uh I did want if you have 60 more seconds to get your take on uh how you think how you think AI impacts uh original reporting and storytelling cuz in my view it's potentially great for an Arena mag because there's so many more contributors that'll think hey, I have this thing that I want to talk about.

1:31:35

this thing that I want to talk about. I don't really have an outlet or a platform myself or maybe I do, but I want to share it in print and I can produce a great story in a much less time even if it's like have you know, hopefully uh heavily heavily written by themselves, but um and we've and we've talked with other like uh plenty of other folks where I think that uh even

1:31:57

in it feels like today an AI no matter how good the voice agent is, if an AI calls you and you don't know who the person is and they're just kind of trying to mine you for information, there's not going to be a lot of information flow, which means that I think that great journalists and storytellers will have great great jobs long long into the future, but how are you thinking about it? I long for the day when the AIs are

1:32:21

I long for the day when the AIs are actually a better writer than I am, but it it hasn't happened yet.

1:32:25

I I I I'm honored to be scraped by the AIs so that my like voice will live on.

1:32:30

You know, I'm a superuser of all of these platforms for automating all of the stuff that makes the enterprise like difficult to do, which is sometimes you know, dealing with with complicated workflows and research and whatnot.

1:32:46

I think that there is something around um certain sort of like newswire style things that could be automated super effectively where if you have like a newsroom of people where there's like even like 20-minute delays or whatnot, that could be that that that that that that could that could that could be that

1:33:03

could be that could be improved by like immediate algorithmic stuff, but but I think that as the like amount of high of low-quality content on the internet goes up, people are going to look for things that they things that they trust and it doesn't necessarily mean print. For us,

1:33:20

For us, print is like a very good um you know, place of trust where the fact that we're actually taking several weeks in a giant factory with a bunch of paper to double-triple-check everything, it's like it's a it's a level of care that goes into it that reminds people that like things can be done by humans in this really dazzling way.

1:33:42

And of course, you know, there's tons of cloud co-work and other stuff going on beneath the surface, but we wouldn't want to let that touch the writing if people are going to be paying for it.

1:33:52

They should be able to get that stuff for free on the internet and and pay for high quality stuff.

1:33:57

It's not >> at the same time at the same time I feel like the value what you're saying in some ways the value of an editor goes up a lot because there's infinite content and an editor is deciding in this case with Arena what actually makes it to print. Yeah, yeah, yeah.

1:34:13

I mean a bunch of us a bunch of us at Arena were were all editors at the at the stamp at the Stanford Review and so it's like you learn how to editing is definitely a editing is definitely a skill in itself and being able to like point out why someone else's writing is bad then you can point out how your own writing is bad and that's how you actually get good.

1:34:33

I would say one of the thesis around like wanting people to contribute to Arena and compiling these issues is that like while it's a great thing that anyone can just sort of post out there there's a reason why like the legacy institutions that have super high professional standards are extremely effective.

1:34:50

Like people Bloomberg, Wall Street Journal, New York Times, even the ones that people dislike for ideological reasons like they have a seriousness to them that makes their messaging super effective and a lot of that is because they're extremely effective editors.

1:35:02

I will say Arena probably invest slightly less in copy editing compared to some other institutions.

1:35:10

I think it's a sign of life that we occasionally find typos in the print magazine but we spend an inordinate amount of time actually editing to make it good.

1:35:23

When people pay you for something you know, there's there's there's there's an old joke Boris Johnson the former Prime Minister of the of the United Kingdom used to be a news editor and he would apparently tell his staff when something was bad.

1:35:35

Um, you know, the readers pay us, we don't pay them.

1:35:42

And so when the readers are paying us it's got to be good.

1:35:46

And and there's a lot of stuff that is like assisted by AI or where where research has been helped with it.

1:35:50

Uh transcript editing is like a super helpful one now and like I can walk into like a a company with my iPad and record 5 hours of interviews and both Claude and Grok are now very good at taking all of those and doing sort of very light style edits or fixing the sort of verbal pauses or whatnot, which would which would previously take me like many many hours to do.

1:36:14

So, that's an example of like my job's like a lot easier, but people are paying us for like a high-quality product and so we want to make it as as good as possible both in the writing and especially in the in the art as well.

1:36:27

We love our non-reading customers.

1:36:29

You know, there's a there there there there there there a lot of people who love Arena who who who haven't read a single article.

1:36:36

>> That's the coffee table book and they can't read a speech.

1:36:39

>> [laughter] >> That's exactly that's exactly that's exactly that's exactly >> you don't you don't you can just look at the pictures. >> Yeah, yeah.

1:36:44

Well, you can find it at arenamag. com.

1:36:47

You can subscribe to the print edition for $99 a year. It's an absolute steal.

1:36:52

I really think it's I really think it's a steal.

1:36:53

I was telling people the other day, you know, I I I I I I spent 3 months in an attic in the in the Texas summer going through different like paper samples, choosing the choosing the exact size. >> Yeah. Um I think I nailed it.

1:37:04

It's uh Well, thank you so much for coming on the show and sharing this with us.

1:37:11

We will talk to you soon. >> I love the vest. >> is fantastic.

1:37:15

Every media man needs a look.

1:37:18

I bought 12 sweater vests on eBay earlier this year. >> Okay.

1:37:22

Uh uh uh and and and and and and and and and and and and and it's working. It's working.

1:37:26

Well, we'll talk to you soon.

1:37:28

Have a good rest of your day. See you Arena. Goodbye. Great to see you, Max.

1:37:32

Let me tell you about Cisco.

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1:37:42

Uh we were talking briefly about Warner Brothers.

1:37:44

Uh the the Cal-Shasta market is mooning on Paramount.

1:37:46

Uh, the Paramount and Netflix have been going back and forth.

1:37:51

Paramount's now at 61% chance that they will be the one to successfully take over uh, Warner Brothers Netflix.

1:37:58

Previously up at 70% back in December when we started talking about this, now they're down at 30%.

1:38:06

>> are doing the Allison thing.

1:38:09

>> It ain't over till it's over.

1:38:09

Let me tell you about Console.

1:38:11

Console builds AI agents that automate 70% of IT, HR, and finance support giving employees instant resolution for access requests and password resets.

1:38:21

And without further ado, we'll bring in Ben Leair of Leair FPA Ventures.

1:38:25

He's the managing partner there.

1:38:29

And he's returning [music] to the show.

1:38:30

We had you on a couple weeks ago, I feel like, but great >> months. >> It's been months? No. >> When was it? End of last year? >> like 6 weeks. >> Okay. 6 weeks.

1:38:39

But this is much more legit.

1:38:41

>> It is great to have you here in person. >> It's a real place. >> Yeah. And at AI.

1:38:44

How long you in town for? Uh, for the week.

1:38:45

Although I was supposed to be here 3 days ago. >> It's it's up snow. It's up run. >> you get snowed in?

1:38:51

I got snowed in and flights actually canceled. >> Six flights canceled. Five flights canceled.

1:38:55

Not I was fortunately not at the airport.

1:38:57

>> Maybe I don't travel that much, but I actually think I've never been in that situation of getting >> The charter gods The charter gods telling you uh, It's time to up. It's time to up. You like thank you. Okay.

1:39:08

Gulfstream Gulfstream sales in over there.

1:39:12

>> [laughter] >> Um, but yeah.

1:39:15

Yeah, it was ran into somebody at coffee this morning. Mhm.

1:39:17

And they told me it was up front. >> front.

1:39:20

Everyone on the plane was going up front last night. Yeah.

1:39:22

It's it's it's a big event. It's a big event. You do a great job.

1:39:24

It really is a uh, It's you know, it's one of the few times when you can go out and see everyone who works not not quite everyone, but the majority of people that I would consider colleagues in one room for a day.

1:39:34

It's It's actually really Is there is there cross-pollination outside of technology with other industries in the upfront in the past has brought Hollywood and LA folks, but there's other conferences where there it's more like Hill and Valley, right?

1:39:49

So, they bring them politicians out.

1:39:50

What what what's A little bit of that.

1:39:52

I mean, I think they do play the LA card pretty hard and and Upfront's brand as a fund is very sort of LA-centric.

1:39:57

Um the event they definitely like take advantage of the fact that there's that kind of talent out here.

1:40:03

I don't think a lot of speakers are flying in other than people from the venture world. Yeah, yeah.

1:40:07

But the uh the tension between Hollywood and the people funding uh AI, I can see that being interesting.

1:40:16

Yeah, you know, we're we're actually in a company uh that's building a sort of AI-first uh movie studio um called Staircase, and what they are doing is trying to use Hollywood talent.

1:40:27

So, they're using like SAG talent, um real actors, real voices, but then enhancing it with AI, and they're getting some they're getting a little bit of pull out here in a good way, whereas I think if you're sort of if you're not willing to use Hollywood talent and pay Hollywood talent through the unions, you run directly into a wall and and by the way, like this is this is not going to end well if Hollywood doesn't get with it.

1:40:51

I mean, at some point it's just going to get steamrolled.

1:40:54

steamrolled. There are going to be you know, look at like A24 bringing in Scott Budnick >> Yeah, I I just looked at it as when I living in in LA for the last eight years or so, I've met so many directors and producers that are that that were kind of frustrated with the lifestyle of

1:41:12

okay, I have this job that I love doing, but then multiple times a year I got to fly to the Middle East and just be posted up in this foreign country away from my life and and and there's some element of that that I think is kind of like core to the movie industry. It's

1:41:26

It's like, you know, I think there's some probably will always be nostalgia around it.

1:41:32

But we were talking uh probably a couple weeks ago at this point, if you're an actor and and you get the and and you're and you lean into AI, you can potentially get a lot of the benefit while kind of compressing your actual like time doing the work down by quite a quite a lot, right?

1:41:50

Because it's like, "Hey, come in I I don't know exactly what Staircase's workflow look like looks like, but I can imagine we get to the point where there's like certain scenes that are done like you know, legit the old-fashioned way.

1:42:02

And then there's certain scenes where it's like, "Yeah, we're just going to use the models."

1:42:07

>> Staircase, none are done the old-fashioned way. Okay.

1:42:10

>> So, everything is >> Do they do like a capture process?

1:42:13

>> a capture process, but never always against a green screen.

1:42:15

So, never against or not I don't know if they never took it against a green screen or just against against the no no screen, but with tracking movements and whatever that would be.

1:42:24

Um, but they're not ever going and shooting out in the wild. Yeah.

1:42:27

And the technology is changing so quickly that what they can create today relative to what they could do 6 months ago is magnitudinally different.

1:42:35

And if you just continue on this curve, at some point pretty soon it's going to be ridiculous to think that you're going to go to the middle of the ocean.

1:42:44

>> Yeah, Matthew Matthew McConaughey has had some good leadership around this and basically just being like, "Hey, we have to embrace it. It's coming. It's just too efficient. It's too productive."

1:42:50

The idea of like, "Hey, we need to shoot.

1:42:53

We have like a a 3 minutes total that's in the setting.

1:43:00

We're going to bring 100 people out there and spend weeks doing this thing that could be made you know, in not uh one prompt, but made in a series of prompts and with a lot of editing.

1:43:09

Well, and there's an insatiable appetite for just like more content.

1:43:13

I mean, you guys were just talking about the you know, the Netflix or Paramount setup and um like all these platforms just want more and more and more and better and better and better.

1:43:25

It seems like there's no there's no limit to the amount of content that people want.

1:43:28

And so, uh yeah, the the the average user, how many times have you opened a streaming platform and just been like I don't like any of this stuff.

1:43:38

Which is amazing because there's so much more content created today than ever before.

1:43:43

And still I I flew out here yesterday, I turned on my Netflix and I'm watching a show from like 11 years ago. Yeah. It's ridiculous.

1:43:48

>> Jordy, you watched a movie last night, right?

1:43:50

>> [laughter] >> John John was making a joke about the movie Borat, which I loved as a kid.

1:43:57

>> by the way, which you should still love.

1:43:58

>> Yeah, it's a fantastic movie.

1:43:58

But I But I went on Amazon and I bought it cuz I was like, I should own this.

1:44:02

It's It's a cult classic at this point.

1:44:04

Uh and it was not as funny as I remembered it when I was 12, which was painful to me, but uh I'm curious on on, you know, talking generally maybe or or about staircase, uh right now a a movie studio will allocate, let's say, $50 million to make a movie. Yep.

1:44:24

Uh how do you think that number changes over time?

1:44:27

Cuz in my head I think eventually it could be five people.

1:44:32

You know, you have like writers, you have like whatever the new, you know, director's role probably stays somewhat similar, and then you're pulling in other talent for audio and video and all these different things.

1:44:46

Um but how how low And And the reason I don't think that's a bad thing is there's so much demand for content that theoretically that $50 million budget would still exist or maybe even increase, but it would just be spread across the >> is like this is the question not for only Hollywood, but for everything, which is like, will, you know, will AI make things deflationary Right.

1:45:07

When you have when you have deflation, does that create >> Yeah, I mean, it applies to every industry.

1:45:13

I think probably with Hollywood, you'll see uh frontline talent continue to demand huge premiums.

1:45:20

So maybe that $50 million goes to 30, but Brad Pitt still makes 25 of it. Yeah.

1:45:24

Um and the rest of it you can do much less I don't know if it's fewer people or or the same number of people being much more efficient and working in half the time like maybe you're doing it more quickly, maybe you're doing multiple projects at one I don't really know how that works.

1:45:39

>> The question around the talent side that I'm interested in is one thing for Brad Pitt to be like, "Cool, you're going to make this movie with mostly AI, but I'm still getting my same rate.

1:45:47

Otherwise, I'm not going to be a part of this cuz some other movie studio down the road is happy to pay me what I think I'm worth and I don't care if it's going to take me way less time."

1:45:56

The question is for new talent, the people in LA that are working as a as a waiter and just like, you know, constantly uh trying to get into the game, what kind of leverage do they still develop can they still develop um real star power over their career and get pricing power or uh or does that or or does like the the amount of people that can be a star fragment even more?

1:46:23

Like does there become more of like a cuz I don't know if how much of a a middle class even exists anymore in in Hollywood like specifically on the on the actor side? Oh, I'm sure. Yeah.

1:46:35

Well, I think I think I I have a few thoughts on this.

1:46:37

One might be that probably there is more of an impetus for talent to be able to not only get famous through the channels that Hollywood provides, but to use social media, to use like those like build your own >> Yeah.

1:46:53

distribution um to be able to demand sort of like that premium because people think that you can move the market, you can drive sales, or you can drive views through your own stardom.

1:47:03

People still care, doesn't matter what the movie's about or who the actor is, they care about who that person is outside in the real world, too, and that influences their experience.

1:47:13

>> I think that that's going to be a big part of this for for that.

1:47:14

But also, Hollywood is going to move more slowly than just about any other industry.

1:47:18

Part of it is the role of the unions and how embedded that is and how like that kind of content gets made different than certainly most other industries that don't have that kind of Yeah. bureaucracy or lock-in.

1:47:31

And also, you know, it's an industry that's run by moguls. It's run by old people. Mhm.

1:47:39

Uh who are like generally slower moving.

1:47:41

It'll be interesting to see >> Tycoons. Tycoons, yeah.

1:47:43

But how do you think about it? Vertical short-form.

1:47:46

I I saw a crazy video of someone doing a movie screening like in a theater, but for vertical video that they made. >> That sounds terrible. >> Which is insane.

1:47:58

And it was like it was really crazy cuz it was like they don't really make projector screens that are super vertical.

1:48:03

So, you're in this like massive room, but normally you're in a really wide theater and then the the screen matches the the the seats.

1:48:09

But it was like just off to the side this like vertical screen kind of like the TV we have over there.

1:48:15

Um but uh but it does seem like there's uh quicker pace of adoption for those like polished What what what what's that Chinese app that has uh vertical short-form? >> Like the drama. Yeah, the short drama.

1:48:28

>> Yeah, Reel Short or something. Reel Short. Reel Short.

1:48:30

And then there's AI versions of that.

1:48:32

And that feels like Uh We get a pitch for that category once a week. You do? For the last year. >> Okay.

1:48:37

I mean, it is >> Oh, I get it once a day. >> Okay.

1:48:39

So, you have a better deal.

1:48:42

No, but it is it is wild how uh And by the way, and the number of pitches it's funny.

1:48:46

You guys want to talk about media with me.

1:48:49

The number of pitches I still get from people like, "Ben, you're like a media guy."

1:48:51

I'm like, "Please leave me alone.

1:48:53

No, you're not a media guy.

1:48:55

Like you just everyone just like I'm sorry I did this.

1:48:59

But there is this moment where uh And this is also like live shopping was another category that you saw massive in China. Mhm.

1:49:05

And short-form drama, enormous industry in China.

1:49:11

And everyone's like, "Cool, it's going to like be here in the US tomorrow."

1:49:14

And like 10 years later, it's still not really here.

1:49:16

Um >> I will say that in with one of the companies I they like really forced me to watch some content and I got hooked on a story about like a woman who fell in love with a man in an elevator and I watched >> Okay.

1:49:28

for like 2 hours in 1-minute snippets.

1:49:30

Like I see the how you can get addicted to it, but uh I I I fortunately broke that addiction.

1:49:36

>> Yeah, the question is how How do you actually invest against this trend?

1:49:38

I think I think >> I think you won't.

1:49:42

Yeah, I think I think Yeah, I think Because all the content Yeah.

1:49:47

>> The content wants to be free.

1:49:47

It wants to flow to the existing platforms.

1:49:48

I can see YouTube creating like short series.

1:49:55

Like basically like you can subscribe to a series being like Yeah, basically like hey, you're you're not even just subscribe like cuz the follow button and subscribe button that barely works anymore on any platform.

1:50:06

But they might be encouraged to be like, "Hey, this is a series of 30 videos.

1:50:09

It's going to be coming out one a day.

1:50:13

You can subscribe and we'll make sure that it comes out."

1:50:17

I think this is an interesting space.

1:50:20

The difference between an interesting space and a venture scale space is the Grand Canyon.

1:50:24

I mean, it is so massive.

1:50:26

Figuring out, you know, venture requires the power law, requires these outside outsize returns and it just doesn't feel like Sure, you have, you know, one or two companies in China that are massive, but it doesn't feel like that's a category that has a sort of theoretically limitless TAM.

1:50:44

And one of the mistakes that I've made in my career and one of the sort of learnings is TAM really does matter and yes, there's, you know, you have to sort of lily pad your way there.

1:50:54

It's not like every market has to be enormous day one.

1:50:55

But most of media has turned out to not be venture scale and I think maybe all of media is not venture scale.

1:51:02

Um and with AI uh Yeah, it's venture scale if you can build a platform that can compete with the giants.

1:51:10

But you need you need a $5 billion But, how do you do like what is that Right.

1:51:14

I mean, this is one of these things if someone By the way, like Jeffrey Katzenberg tried to do this-ish with Quibi, and there are a few people more formidable in the entire world than Jeffrey, and even with hundreds of millions of dollars, like that's not that wasn't the answer now.

1:51:29

By the way, today would be a more interesting time to launch Quibi because of what's changed in technology.

1:51:35

And by the way, I've seen the the competitive dynamics with every other app that also has short-form videos that the creators are incentivized to share the same content across all of them.

1:51:48

Those competitive dynamics are still in place.

1:51:50

Like, just like working in an industry that face that, you know, Meta and Amazon and Apple and Netflix that like more than half of the Mag 7 is interested in is really, really tough place to go and build.

1:52:04

Every Mag 7 company, except Nvidia, owns a basically a social network if you include iMessage, Twitch, LinkedIn.

1:52:10

Like, you actually wind up with a media platform at all of them. Right.

1:52:16

And like that is And by the way, this is not your traditional, you know, large incumbents who are asleep at the wheel.

1:52:21

These are the scariest companies that have ever been built in the history of humanity who, you know, like no thanks.

1:52:29

>> [laughter] >> Uh how did you process the Sucré virality, the viral article? >> Sold everything. Intelligence crisis.

1:52:35

I [laughter] like bought a farm in the woods and No, look look, we are we are at a moment right now.

1:52:43

I mean, that's that's this week's flavor.

1:52:45

Last week, I think there was a something big.

1:52:49

Yes, and then there was the counter to it, and obviously there's a bunch of counter arguments to to this one.

1:52:52

Um I think it's indicative of what a scary time this is and just how um overwhelmed everybody I mean, like I wake up in the middle of the night screaming.

1:53:05

I don't know about you guys. Just in fear.

1:53:07

No, I'm [laughter] kidding.

1:53:09

No, but like this is wild times.

1:53:09

I mean this is I look at that article and I think that there is you can you can sort of pull the thread and go, yeah, I like oh my god, you are going to see a bunch of these companies who have to cut costs go, lean in, become their own worst enemy.

1:53:24

I think what this sort of doesn't take into account is that there's going to be a bunch of other interesting, amazing new companies that get built that employ lots of people, that have a very different growth curve, and that it's not just like everything is a race to the bottom.

1:53:38

There is going to be all this amazing innovation that happens counter to that.

1:53:42

>> a good a good counterpoint, Citadel put out a report that showed software engineer job openings are up 11% year over year.

1:53:49

And so it's interesting that we're getting this like where AI is working the best today and coding is causing an uplift in jobs and yet people are kind of extrapolating and saying every other job is is cooked even though that's not what we're seeing Yeah. >> in the data. Yeah, it's interesting.

1:54:10

What what are you revisiting marketplaces?

1:54:13

There was a big debate over DoorDash being AI resistant or Have you gotten any DoorDash pitches?

1:54:18

I I I I not this week, but I have I've gotten some DoorDash.

1:54:22

And I I'm just wondering how you're thinking about marketplaces because it feels like there was a boom.

1:54:29

Most of the great marketplaces got built.

1:54:30

All the all the obvious ones that didn't have massive disintermediation problems.

1:54:34

So, the dog walker, the house cleaner, that's stuff that gets disintermediated very quickly.

1:54:39

But the DoorDash or the Uber, that is something where you're not just going to meet a great driver and be like now you're my personal driver forever, right?

1:54:46

But you will do that if you're like I went to this app and I found a house cleaner and they come every week and so I just said, hey, let's stop using the app and cut out the 15% take rate.

1:54:54

But what are you what are you thinking about marketplaces on the earlier side?

1:55:00

Are there Is there anything interesting that you're seeing?

1:55:03

Uh So, I I think that there is when you're looking at marketplaces, we're we're trying to find marketplaces where sort of everybody wins. >> Sure.

1:55:12

Um and uh there's a company in our portfolio that's very early um building in the uh aftermarket automotive space. >> Oh.

1:55:24

Um and this is a category that has you know, millions and millions and millions of SKUs.

1:55:29

Um there is a question as to does this you know, spark plug work for my 1984 Mazda Miata or does that one work?

1:55:39

Um most of that industry never came online at all.

1:55:42

And so, you still have to like file, you know, like fax in an order or a requisition. >> Yeah.

1:55:50

You do have You have some large sort of endemic players like AutoZone.

1:55:54

They're actually quite big businesses, but that still only have a fraction of the inventory.

1:55:57

They don't actually know if that if that piece works for this car when you've also done these three other changes.

1:56:06

And that's the kind of industry, very messy, very hard, but with AI, you can go and send agents to go do some of this buying.

1:56:14

So, sort of mimic the idea that an industry is online that may never come online. >> Sure.

1:56:20

Um I think that that's I think there are spaces that By the way, that's also a very large, very sleepy TAM.

1:56:25

Like that is not a that's not a sort of side pocket hobby.

1:56:30

That's one of the biggest hobbies in America. >> Yeah. That's right.

1:56:34

>> Billion, you know, tens and tens and tens of billions of dollars just in the US just in aftermarket >> hydrate from like some random SKU or some random serial number into like what is this product actually?

1:56:43

And there's probably a manual out there somewhere that has it.

1:56:47

It might be on the internet.

1:56:49

>> be in a Reddit forum somewhere.

1:56:49

But like And then there's the question of And by the way, how do I get this installed? And can I do it myself?

1:56:55

And you know, is there an AI Yeah. uh mechanic Yeah.

1:57:01

>> that's built into the marketplace, so it can teach you to do the work while you buy. >> Yeah.

1:57:04

You know, will this company accomplish it?

1:57:06

I don't know, but I love the ambition.

1:57:08

And I think when we're looking for marketplaces, we want to see ones that are you know, I don't want to see an incremental you know, DoorDash competitor.

1:57:17

I want to see one in an industry that really has uh that has not yet been disrupted for reasons that were frankly impossible before the automation of AI. >> Yeah.

1:57:28

Jordi, you think I'm what I'm thinking?

1:57:30

Me, you, this weekend, couple of cold ones, Mansory body kits on the car. Let's [laughter] do it. Secondhand, we get them.

1:57:37

We figure out a way >> dream forever is to drive a Mansory >> underlighting.

1:57:42

You got a new car, you don't have >> I'll stay for the weekend.

1:57:45

>> have LED lighting underneath that yet. NOS? That's true.

1:57:49

>> putting NOS in your car?

1:57:49

[laughter] This is a good option. >> The uh uh very good.

1:57:54

We got to get uh that'll be your Christmas gift this year. >> Mansory body kit. Mansory body kit. You want it. It's it's got to happen.

1:57:58

Uh the labor marketplaces that uh have exploded are the are the Mercors, the micro ones >> Mhm.

1:58:08

uh that uh are positioned as marketplaces and yet feel more like enterprise product, like almost like staffing >> Yep. in some way.

1:58:18

Uh the question is how how durable will those businesses be, and and uh I think a lot of people were surprised that the the uh the Fivers and the Upworks didn't kind of react and capitalize on that as as quickly as they maybe could, but it just goes to show how quickly the the space is moving. Mhm.

1:58:39

Yeah, I think there are perspectives.

1:58:40

There's, you know, multiple camps there, but there are there are camps of folks, you know, smart folks who think that that whole category is like a race to the bottom, and like probably a zero.

1:58:50

And then there's other, you know, maybe some of those folks like Summer or Coursera past or whatever.

1:58:55

And you know, like I'm rooting against it.

1:58:56

But but there's there's definitely a vibe that that is uh you know, maybe if you're on the inside in some of those businesses, like now would be a good time to take some secondary.

1:59:05

Um I think obviously uh but you've seen growth that is astounding.

1:59:12

Um and you know, that's the funny thing about the market right now.

1:59:14

That that's a category, but there's so many categories.

1:59:16

Um like a bunch of these companies that are doing inference.

1:59:20

Like, you've seen like unbelievable growth.

1:59:22

And like there's there's like insatiable appetite for what they have today or, you know, you know, different kinds of training data or whatever.

1:59:28

The question is, in 2 years, in 3 years, in 5 years, in 10 years, like which of these are enduring spaces?

1:59:34

And which of these are ripping right now because they're selling to five There's there's only five buyers or four buyers long-term.

1:59:41

And is that Is that a good business?

1:59:43

Like to be in a business where you ultimately have four companies that are your like theoretical scale customers? Yeah.

1:59:50

I mean, And right now there's such insane urgency that there's no Yeah.

1:59:54

Well, and money is absolutely valueless to these company I mean, it just it pours it like as fast as you open the door, it like bursts its way into your face.

2:00:04

>> I was joking about if you started a janitorial company that just served the AI labs, your revenue would be growing 10X cuz their head count and and square footage is growing 10X.

2:00:11

And you'd be like, "Yeah, my business is 10X." And you know what?

2:00:14

I have pricing power, too.

2:00:15

My margins are incredible.

2:00:15

It's like cuz they never ask.

2:00:18

>> Let's do that this weekend.

2:00:19

>> [laughter] >> That's a Yeah.

2:00:19

They're like, "Hey, janitorial business is wildly different."

2:00:23

>> There is I do think that right now is uh you know, look, this is coming after a few years of really disappointing returns for venture as a category.

2:00:29

And suddenly you see things ripping and growing.

2:00:35

And like, you want to believe.

2:00:37

You want like people, you know, like you And And by the way, you have massive massive funds now that need to deploy huge amounts of money.

2:00:44

And they're looking for things that look like the escape velocity Yeah. is there.

2:00:48

And so, they become self-fulfilling prophecies and more money pours in and like, you know, I don't think that all these categories are going to be zeros, but I think probably there's going to be there's a lot of winners in some of these categories.

2:01:00

I think there'll be fewer winners and maybe the winners won't be winning at the multiples that they look like they are today.

2:01:07

And then >> Or they'll or they'll or they'll evolve dramatically.

2:01:10

Well, yeah, and by the way, some of them will and some of them won't, Right.

2:01:14

I mean, like it's like keeping up with this market is the hardest It's the hardest in my career to like companies that are Let's even look at like the OpenAI Anthropic thing.

2:01:26

And granted, this is just like you know, maybe that's this is like the caricature of the space, but it feels like the tide turned so hard even in the last 3 months where it's like Anthropic's world now and OpenAI is living in it.

2:01:37

And 3 months ago you would have said the exact opposite. Yeah.

2:01:39

Um and maybe maybe that's just like I'm interested in if you feel that energy or not.

2:01:47

>> to it's it's um Yeah, it certainly feels like at this moment Anthropic is the main character, right?

2:01:54

Dominating uh dominating the headlines on X.

2:01:56

Uh and and a lot of of legacy media as well, but uh I would say Google Google Trends tell, you know, a slightly different story, right?

2:02:08

We we are in a bubble and uh people are so invested in the race that they want It's like if you watch an F1 race and Verstappen wins every time and he starts in pole >> At some point you're like, I'm sick of this.

2:02:22

>> Yeah, you just want to see you want to see you want to see some action and you want to see some passes and you want some some drama.

2:02:27

So, I think people are are invested in the drama, but um Yeah, and it and it's also you're you're watching the the two strategies play out like a very multi-product approach, consumer, enterprise, hardware uh from from open AI versus like in a very focused strategy and I think it's way too early to to kind of understand what will in hindsight look like the best call. >> Totally.

2:02:55

But it's certainly >> is going to come out with their model whenever and then what does that look like and Yeah.

2:03:00

Yeah, it's it's interesting times. Very interesting.

2:03:05

Well, thank you so much for coming down to the TV pin ultra dome.

2:03:06

Give us a report on on upfront. Okay.

2:03:08

I'll happily Is it tomorrow? >> It's today. It's today.

2:03:13

Oh, you I abandoned my Abandoned my boy.

2:03:19

Well, well, text us later and we'll we'll give the update on the show.

2:03:21

I want to understand I have no sense for how much venture capital like what I think of LA is getting.

2:03:29

I have a good sense for like Hawthorne, El Segundo, Long Beach, Gardena, all these areas feels like are raising as much money as ever.

2:03:37

But the broader LA feels like a drought.

2:03:43

I would say it's a drought.

2:03:45

We definitely are not spending time out here hunting companies. Really at all.

2:03:52

Yeah, that's the advice I've given to any founder that's not in hard tech is like do not Don't even start Don't even Yeah, don't even start your raise here cuz it's going to just send like a really negative signal that you're not super serious. >> Yeah.

2:04:07

Well, thank you so much for coming on the show. This is great. Great to see you.

2:04:09

Let me tell you about MongoDB.

2:04:12

What's the only thing faster than the AI market?

2:04:14

Your business on MongoDB.

2:04:14

Don't just build AI, own the data platform that powers it.

2:04:19

And let me also tell you about Lambda.

2:04:22

Lambda is the super intelligence cloud building AI supercomputers for training and inference that scale from one GPU to hundreds of thousands. Boom.

2:04:29

We have some breaking news. We got to hit the gong.

2:04:33

Riley Walls shared an exclusive scoop.

2:04:35

He says he has joined the wonderful labs team at OpenAI.

2:04:39

I'm learning a lot and have enjoyed it very much. Congratulations. Huge pick up. Huge opportunity.

2:04:47

Uh I'm so excited to see what what uh Riley is one of uh the the greatest minds high agency individuals on the internet today and and uh I'm so >> He's the best. Uh yeah.

2:05:02

So so I think Riley Walls is like a perfect example of like jobs kind of getting more fake.

2:05:09

Like what is like Like >> [laughter] >> this is like not a this is like not a diss at all.

2:05:12

Says the says the says the says the guy who who >> No exactly.

2:05:15

I'm I'm also a like very fake job.

2:05:17

Like Riley Walls he like just goes viral on Twitter.

2:05:19

He's not even like making like YouTube videos.

2:05:20

It's like He's been a he's been a he's been a data analyst for the last few years.

2:05:25

He's had a he's had a Yeah but he's not doing data analysis at OpenAI.

2:05:27

He's not doing the same kind of work he was doing before.

2:05:30

Yeah yeah yeah yeah yeah yeah yeah yeah yeah I know but he's he's perfectly demonstrating How do you describe Riley Walls' power up?

2:05:35

Member of technical staff. Next question.

2:05:37

No so so he is perfectly demonstrating the power of the tools which is if you have ideas you can build them really really really fast and create super in his case super entertaining products but there's a Riley Walls out there of SAS and they're probably just hunker down not even really trying >> And I mean so so so I I agree with you very very hilarious framing.

2:06:01

Uh I do think that we're moving into a world where more and more companies will have a Riley Walls internally.

2:06:09

>> [laughter] >> A uh you you know someone who can move very quickly, do experiments, create value and and create little projects and like the leverage that you get from an individual is going up and this is an example of that.

2:06:21

So congratulations to Riley Walls on his move to OpenAI.

2:06:23

Let me tell you about Graphite.

2:06:26

Code review for the age of AI.

2:06:29

Graphite helps teams on GitHub ship higher quality software, faster.

2:06:32

And without further ado, we'll bring in the birthday boy.

2:06:35

Doug O'Laughlin is in the Re-stream waiting room.

2:06:39

Let's bring him in to the TVP and Ultra down. Beautiful shirt. Happy birthday to you. Happy birthday to you.

2:06:47

Happy birthday, dear Douglas. Happy birthday to you. How you doing? Hey, happy to be here. I guess on my birthday.

2:06:55

Nothing better than Nvidia earnings, which hasn't come out.

2:06:57

We're going to be live reacting.

2:06:59

Yes, we'll be live reacting.

2:07:01

>> planned that, of course, years and years ago.

2:07:04

They knew that today >> They knew that today would be the day.

2:07:08

Uh they went back in time and they told my mom to to to to get it done today. Yeah. Yeah. >> How you guys been? We've been good. Good. Wild.

2:07:18

>> the something big is happening, then the Satrini article.

2:07:21

There's been a lot of sort of doom, but also there's glimmers of boom in there.

2:07:26

There's it's a mixed bag.

2:07:29

>> you've generally been a Satrini defender, kind of saying, you know, a lot of people were just like, this is bad and it should never have been published.

2:07:37

I think your view was There's some good stuff in there.

2:07:41

>> There's some it's a good thought exercise. >> Yeah.

2:07:44

Yeah, well, here's the thing is like it went super viral for a reason because it obviously resonated.

2:07:48

Um I don't think really crappy ideas resonate that hard.

2:07:53

Um and and I think honestly a lot of the things that I'm most concerned about, I would actually align with it.

2:07:59

Um my biggest concern is that we're going to print deflation.

2:08:01

And he kind of talks about that.

2:08:03

Like, hey, one data center does all the knowledge work.

2:08:07

Um the history of how this works usually isn't quite that extreme, but that was the point of it.

2:08:12

Here's my extreme think case.

2:08:13

What I was kind of shocked about, and I feel like honestly I bet you Satrini would agree, just like the level it resonated with.

2:08:20

Um it was like covered on Bloomberg almost on a daily basis.

2:08:25

Uh so if you're like a pro, whatever, that does a push notification.

2:08:29

It was like "Citrine says" and "Citrine co-author" and all this stuff. I was like, "Oh my god." Yeah. It really broke through.

2:08:37

>> That was Yeah, it really broke through.

2:08:38

Yeah, unpack the deflation question a little bit more.

2:08:41

So, technology has been deflationary for a long time.

2:08:43

TVs are getting cheaper is the line.

2:08:45

You can see that if you look back at inflation, you see healthcare and education inflating while basically everything that's on like a technological Moore's Law style curve is getting cheaper over time.

2:08:57

The The bigger, like broader broad deflation question is can we move some of those or will some of those inflationary categories move into a deflationary territory?

2:09:11

But, what are you thinking?

2:09:13

Is Is education, healthcare at the top of the stack?

2:09:15

Is What do you mean by knowledge work becoming deflationary?

2:09:21

So, let's just put it this way.

2:09:21

The The ghost GDP article, right?

2:09:23

Hey, let's just kind of like do like an index, one index versus the other index.

2:09:31

We're going to label it at $100 for all these like knowledge work widgets.

2:09:34

And let's just see what the cost of that looks like over over time. Yeah.

2:09:38

Uh year zero, $100 with a human and maybe year two, it's a $102.

2:09:44

Maybe they get a little bit smarter, so it goes down.

2:09:47

But like, okay, what if the agent gets 20 times better?

2:09:51

Years Year two, the the index of knowledge work is going to be $20.

2:09:56

That's That's just deflation, right?

2:09:59

The entire world is effectively just like spitting out TVs that are worthless in three years.

2:10:04

And that's kind of scary and I think is a big deal.

2:10:08

I think the thing that is the most resonating with the whole piece is that clearly, if if this is going to be as big as many people think it will be, you know, Quad Code Maxie here, then what happens is that you're going to quickly disrupt so much of society that the government and like companies and everyone needs to start caring very quickly.

2:10:27

I don't think 10% in unemployment's going to happen.

2:10:31

The world works just slower than that.

2:10:33

But I I clearly think that the real world responds >> part of your framing is like when we had uh technology rollouts throughout the last, you know, few hundred years it involved like heavy machinery that had uh that took a lot of time to diffuse in part because uh the the machinery needed to be built and shipped around the world and spun up.

2:10:59

And then you have with AI, it's like, "Okay, the internet is is the greatest distribution engine in history."

2:11:05

And as technology advances, it can like be live in somebody's office or with somebody's company effectively instantly, which creates and and and with like uh let's say uh the printing press, it was, you know, or cars or or electricity, it was like a much more it was forced to be a much longer rollout.

2:11:27

Yeah, there's just like, for example, the railroad piece I wrote about, dude, it took 50 years to put all those rails, right?

2:11:34

Um historically, let's say this AI thing would be like a historical Adams thing.

2:11:39

It takes 50 years of installing the AI widget at your house in order for you to have AI.

2:11:44

Um versus now it's you just press a button, you download it, and it's there.

2:11:48

And so the pace of that disruption is so so much quicker.

2:11:50

And so if it looks like you know, if it if it's as big of a deal as people are concerned about, then essentially you're going to broadcast deflation everywhere all the time all at once.

2:12:02

Um and it's going to be almost costless to get there.

2:12:03

And also it's just it's going to get relentlessly better.

2:12:07

If um yeah, just and then imagine >> How do you How do you square that though with the fact that right now today AI is the best at coding.

2:12:19

That is where it has the most traction within knowledge, you know, knowledge work.

2:12:26

And yet I have I have not gotten a call from a great engineer saying, "Hey, can you help me land a job? I'm unemployed."

2:12:34

And you see this in Citadel put out a response saying that that software engineer job listings have gone up uh year-over-year.

2:12:44

And so it's so hard for me to square these two things where we could be in this in this uh you know, doomsday scenario for white-collar work, but we're not seeing >> Yeah, but we're not seeing that at all Mhm. with software engineers.

2:13:00

Now, some people might debate me and say, "Well, oh, I just graduated Yeah, I'm having trouble.

2:13:06

>> school and and yeah, uh new grad opportunities might be lower, but nobody nobody has bought when when some of these larger uh tech company CEOs have laid off a bunch of people and said, "We did this because of AI."

2:13:21

It's like nobody nobody's actually buying that.

2:13:24

It's just a a nice story.

2:13:28

Yeah, I think um that's going to be an interesting thing because I think it will be politically and broadly unpopular to say, "Hey, I just laid off 10,000 people because AI."

2:13:37

Like we are humans at the end of the day and you know, you do care about what your neighbors think of you.

2:13:43

And just being like we fired everyone because AI is better than whatever, you're like, "Okay, well, now you got to get you might as well hire a five-person security guard, right?"

2:13:51

There's a little bit of like being an So I think how it actually works and you're looking at and I agree with that comment because there's this really great tweet that's like, "Oh, it's crazy in the agentic coding world."

2:14:03

Pretty much it pegs the human CPU at 100%.

2:14:05

That's how I feel at least is I'm doing more work than ever, but I'm like literally working harder than I've ever worked.

2:14:13

The reality is I feel like there is a productivity uplift, but I guess we're all in this sugar high where you're able to do so much work that you're just like going around like crushing it.

2:14:20

So, these software engineers, yeah, you don't need new grads, and essentially the person who has a seat gets to uh you know, print more.

2:14:29

Let's just use the printing press, right?

2:14:30

Instead of writing, and you unemploy all the new writers, but you're sitting there just printing all day.

2:14:35

And so, it really is great for the install base of people who've been doing it, but very terrible for net new.

2:14:42

And I think the net new is where you're going to see this, meaning like new grads, new people entering the information the information services.

2:14:49

That's where I think you're going to see most of the carnage.

2:14:52

People are not just going to be firing people out the gate.

2:14:55

Um it's going to be like, okay, we're not going to hire anyone.

2:14:57

>> or or a firing typically occurs weeks, if not months, after an executive has decided, "Hey, this you know, we we need to make a change here."

2:15:07

Just because no it's the thing that everyone hates doing.

2:15:11

How do you How have you been processing It feels like the people that uh the Citrini piece resonated with the most are also the ones that have been saying that the AI is a bubble, and there's too too much investment going into this, and it's all going to be a zero.

2:15:30

Uh it's just seems like two ideas that are difficult to >> I You know, I feel like there's a certain aspect of haterade where when you're a real haterade, you're going to find um whatever whatever flavor supports your thesis.

2:15:43

We find this in semi-analysis, man.

2:15:45

When we say something positive, or we perceive as positive, people take it as negative.

2:15:49

Or they really honestly they take it >> we've had we've had that, too.

2:15:55

If if there's a company that people don't like, and you and you say something positive about it, it's it's like people respond like extremely emotionally to that.

2:16:07

Yeah, and so I think Citrini made the perfect ammo at the perfect time. Mhm.

2:16:12

And And like honestly, if you look at the stock market, um I'm sorry.

2:16:14

I I keep watching uh for a video over and over.

2:16:18

Um uh if you look at the stock market, um I think right now it's been a really interesting year to date because like stocks are maybe like whatever, 2% off all-time highs.

2:16:27

Maybe they're all the way back or they're pretty I forget what the like year-to-date looks like.

2:16:30

But underneath the hood in software, it's been very very very painful.

2:16:34

I think there's a lot of parts of the index that are in a lot of pain right now.

2:16:39

And pretty much you're just like seeing these crazy rotations underneath the surface.

2:16:44

And so people are very like antsy.

2:16:46

There's no other way to put it.

2:16:48

Um if it it's thing big things are happening in the stock market, brother.

2:16:53

>> The The The idea that uh like oh, you're holding uh you're holding a name and it hasn't nuked 15% yet, you should get out because some there's going to be some or could be blog posts or blog posts. Yeah.

2:17:07

And And what what's the There's not a lot of ROI on on How have you been processing like the the the moats in software companies?

2:17:12

Like I like I've I've always understood like the SaaS apocalypse, like that narrative.

2:17:18

Of course, you know, we got to debate timelines and maybe these things are just shifting to be value stocks as opposed to growth stocks.

2:17:23

But uh the stuff with network effects, the DoorDashes, the PayPals, the regulatory moats, like it just feels like there's a lot of companies out there that are being more broadly punished, but is there something I'm missing there or or do you think that uh it's just excitement and people rotating into other stuff that they might be learning about like memory and energy and semis? I I don't know.

2:17:48

Um but I definitely think that that aspect is definitely there.

2:17:53

Like the ones that are like really shocking to me is insurance brokers.

2:17:56

Um if you've ever if you ever follow that space, like once upon a time as a hedge fund analyst, I followed Aon.

2:18:02

It's like one of the most boring spaces of all time. Uh real estate services?

2:18:07

Uh no, like CBRE CBRE essentially an insurance broker.

2:18:10

You're having all these things, these network uh businesses that are just effectively being like, "Yeah, in fact, it's going to be neut."

2:18:16

Um I think the hard part about that is it's it's like it's complicated.

2:18:21

I think there's a lot of advantage for number two to defect really quickly.

2:18:24

That's probably the most valuable thing you can do.

2:18:26

For example, we've written quite a bit about this through like our higher paid tier service stuff.

2:18:31

Like Walmart defecting to agentic commerce makes a lot of sense, right?

2:18:35

Because they're not Amazon.

2:18:35

Um everyone that isn't number one should be defecting to win market share, and that makes a lot of sense to me.

2:18:42

So like it it wouldn't be DoorDash.

2:18:44

DoorDash would probably put up the, you know, put up the walls, do their best to like have exclusive products, and then someone else will vibe code something on the margin and essentially try to win market share by But at the same at the same time, Dara was on the show, and his stance was yeah, I don't really care as much about my ads business, about making sure that I'm just everywhere.

2:19:04

And so he was seemingly pro agent even though Yeah. Ads business is is real.

2:19:14

Uh how have you been processing uh agentic commerce?

2:19:17

Like it feels like this should like the tech is there.

2:19:22

And but like consumer adoption takes time, you know.

2:19:25

Yes, you can touch up a photo with gen gen AI. Not everyone does.

2:19:30

Um what like what would what does good look like?

2:19:33

Because we're seeing stats from Shopify.

2:19:35

It's like still in like 0.

2:19:35

01% of checkouts are agentic, and I would expect that to 10x or 100x, but even then you're talking about like 1% of e-commerce.

2:19:45

Like we're still talking like really small numbers.

2:19:47

Um like how fast do you think it ramps, and and what do you think happens this year?

2:19:53

So I think the place to watch um and it's probably the most interesting places China because you can argue uh the the leading e-commerce adopter has always been China.

2:20:02

They were doing DoorDash way before it got hot in the United States.

2:20:05

They were doing e-commerce way before it got hot in the United States and we just saw this live streams right like like dude Tik Tok and Douyin was always always been on the bleeding edge.

2:20:16

Like I would argue for like global internet online consumer preference behavior China is the leading indicator.

2:20:23

Like America is a laggard boomer you know like we just don't we don't buy like we used to okay the consumer is not quite as quite as young we'll just put it that that way.

2:20:33

I think what's interesting is we just had this giant incentive out of like I believe it's uh I want to say it's Tencent.

2:20:40

Tencent did this like I'm now I'm probably going to misspeak the the bubble tea promotion okay.

2:20:45

They did like 10 million or whatever bubble teas and so I think there there's an example that we finally have the first wave of people possibly being able to adopt it and that's going to be like all eyes on that for if adoption actually kicks off there.

2:21:00

Like that's what happened in 2015 to kick off mobile payments actually during the CCT CCTV gala they essentially gave away like payments and they and they incentivize people to use the mobile wallets and that was like the beginning okay.

2:21:13

So I think that same analogy is probably where people need to look towards for what what could be the adoption curve for agentic commerce. >> Is that earnings?

2:21:24

Do we hear that earnings came No I'm I'm just I'm just I'm I'm just locked in. I'm locked in bro.

2:21:32

We'll have we'll have this sound effect when >> well so so how do you imagine agentic commerce actually rolling out in China because there's a whole bunch of AI labs you know deep seek high flyer like they don't have a do they have a big consumer footprint already because it's they don't have a lineage there.

2:21:49

So you might expect you know, agent of commerce to be driven more by the platform that already has a billion daily active users over there.

2:21:59

But, how do you see like the stack piling up over there?

2:22:04

So, I think the best example of this is Alibaba which actually is an e-commerce company.

2:22:09

They're like, you know, the Amazon edition.

2:22:11

They [clears throat] have when They have a delivery app.

2:22:14

They have like an inventory app.

2:22:16

They have a fully vertical fully vertically integrated stack. And they have AI on top.

2:22:23

They're going to make money if people just use their products.

2:22:27

They can get transaction fees.

2:22:27

And so, that's how I kind of think about it.

2:22:28

I mean, in a perfect world if Amazon was not bad at models, they'd be crushing, right?

2:22:34

You'd obviously be like number one for years.

2:22:38

Don't talk down on Rufus.

2:22:38

it took down AWS once or twice or three times for hours doesn't mean they don't got it.

2:22:47

I actually want to talk about a conspiracy theory because I feel like this is Have you been noticing the instability of public clouds? Yes. Am I crazy?

2:22:56

No, I don't think you're crazy.

2:22:59

No, this is either There's two There's only two things it could be. Um vibe coding.

2:23:02

People are just pushing crap on prod and they've no idea. Probably true.

2:23:06

Number two, CPU shortage.

2:23:08

I think it's a CPU shortage. I really do.

2:23:11

You don't think there's like a third if we're wearing the tin foil hat which is the world's been very unstable and there'd be an incentive attacks and stuff.

2:23:18

I mean Maybe maybe that's actually That's a good one.

2:23:22

But, I'm really surprised to see all three at the same time.

2:23:24

And then like my favorite probably the most public version of this is the GitHub instability.

2:23:28

GitHub is so unstable right now. Interesting.

2:23:31

Yeah, the yeah, I saw the uptime numbers.

2:23:32

It was like below 99% which is really low considering No, dude, it was like 90% in That's really low.

2:23:39

But, I mean, people are pushing a lot of code to get up.

2:23:41

So, yeah, walk me through Walk me through the CPU shortage because is that just CPUs that are being used to scale new like EC2 instances and like normal like you need a Linux instance and so you need a CPU to provision or is or is the AI boom sucking CPUs in like a Grace Hopper demand like they're the the CPUs are getting dedicated to AI server clusters.

2:24:05

Like where are the what's the shape of the shortage basically?

2:24:08

I think the shape of the shortage is partially on RL because if you want to do an RL gym meaning like you want to have an amazon.

2:24:15

com for your you have to you have to literally simulate just a lot.

2:24:18

That's one real demand driver.

2:24:22

I don't know how I don't know how to quantify that but clearly they're out of it.

2:24:25

Number two, I think I do think all the code Have you seen the charts like I think it's ft.

2:24:30

com with like all the new apps coming online?

2:24:31

They they require infrastructure to run and I had a third one.

2:24:37

Oh, the other thing that's interesting is it's also a little bit of a of like a lapping supply chain thing.

2:24:42

So the last time we bought a lot of CPUs was in 2020 and 2021.

2:24:46

Historically you depreciate the CPUs on a five-year cycle and so after five years you just like literally throw them away. It's five years.

2:24:57

So all of the infrastructure that we purchased and we've been trying our absolute best not to purchase any new CPUs and spend all that money on GPUs.

2:25:06

So they had to be investing this entire time and now the slight demand curve comes up and that's enough to essentially sell out all the CPUs.

2:25:13

I think that that's probably part of it as well.

2:25:17

It's going to probably be this multi problem thing but it's like one of the more interesting like conspiracy theories. Like YouTube went down.

2:25:22

I I don't remember I don't remember a time in like the last five years YouTube has never gone down. Yeah. So.

2:25:27

Yeah, yeah, yeah, that was crazy.

2:25:30

Take us through the effects of the CPU shortage in the TSMC context because TSMC seems to be like a crazy battleground.

2:25:42

Apple, Nvidia, and then you'll talk to a new semiconductor company.

2:25:45

Like we had Maddox on the show yesterday and he's like, "Yeah, I'm just getting line time at TSMC."

2:25:50

And then you read Ben Thompson and it's like, "Well, they're not really investing in CapEx."

2:25:54

And it feels like is is TSMC a bubble or CP shortage? We got Nvidia earnings. What happened?

2:26:03

We will jump back to TSMC, but they beat revenue.

2:26:07

Let's review and read through 7.

2:26:07

4 billion against an estimate of 66. 2 billion.

2:26:14

We have some breaking news.

2:26:16

Nvidia has announced earnings.

2:26:20

Let's take a >> Breaking.

2:26:20

Wow, you guys are faster than me.

2:26:22

>> [laughter] >> Nothing livelier than live.

2:26:28

>> [laughter] >> Here, we will all read the earnings and I will tell everyone about Plaid.

2:26:30

Plaid powers the apps you use to spend, save, borrow, and invest, securely connecting bank accounts to move money, fight fraud, and improve lending, now with AI.

2:26:43

>> [laughter] >> And back.

2:26:45

Do you got anything yet, Doug?

2:26:48

Mike crazy, I don't have anything.

2:26:48

It maybe Tyler just sent this to us.

2:26:50

Did Did they Did somebody just like It's possible somebody's just putting up is just engagement farming. Maybe.

2:27:02

And trying to They might have gotten us.

2:27:06

They might have had us in the first half. Well, we shall see. You got got, dude.

2:27:09

Anyway, let's go back to TSMC.

2:27:11

So, the nature of the TSMC bottleneck with regard to CPUs is that an important factor or is there more fab capacity across Global Foundries, Intel, Samsung to sort of meet that CPU shortage?

2:27:30

So, Global Foundries is nothing. Nothing?

2:27:31

>> Um they don't have a leading edge chip.

2:27:34

So, they will not have any CPUs there.

2:27:35

Intel is actually the real winner, I think, because essentially like TSMC's locked up.

2:27:40

Everyone's fighting for space at TSMC.

2:27:42

Like Nvidia has the most.

2:27:46

All the CoWoS is accounted for.

2:27:46

All of N3 is accounted for.

2:27:47

All of N2 is accounted for.

2:27:49

Essentially, they're completely sold out.

2:27:50

They're going to invest a lot more, but like, you know, get in line. It's another year.

2:27:55

So, whatever is left over kind of goes to the other foundries, and that's really two companies.

2:27:59

That's Intel and that's Samsung.

2:28:02

I think Samsung right now probably makes way more money if they spend it all on memory.

2:28:06

So, Intel really is the swing provider of CPUs in the world.

2:28:12

And that's like kind of amazing.

2:28:14

Like I'm kind of my my belief in a a sweet karmic Intel victory is all the CPUs that can't be made at TSMC because the accelerators are being made instead go back to Intel and they just make them, but they don't design them. Yep.

2:28:28

Uh make them, but don't design them.

2:28:30

So, they would be a second source for Nvidia potentially as well.

2:28:35

Well, like it's not just Nvidia.

2:28:35

It's I think I think Nvidia's going to get there.

2:28:39

I think Nvidia's going to get there. To Intel. Yeah, yeah. Oh, oh, not TSMC.

2:28:43

Okay, so they don't need to. TSMC.

2:28:44

Okay, because there was a theory about like, hey, maybe twist Nvidia's arm, get them to dual source at Intel, and that gets the flywheel going a little bit more. Just as like a give.

2:28:56

I I guess, but I I and there's been some conversation about the NVLink NVLink with with Intel specifically co-packaged.

2:29:02

But I I I I I think it's going to mostly be Vera.

2:29:08

Like I think it's not going to be I I think TSMC's going to give them the capacity.

2:29:13

I think there's a whole world of chips that are not that.

2:29:16

Like think about Graviton or the Axion project at Google or all the arm CPUs >> Explain that Google project. I haven't heard of that.

2:29:25

Um they there's a custom CPU. Okay.

2:29:28

Yeah, so like all of these >> Don't Don't they have like a YouTube chip?

2:29:30

They have like a number of custom CPUs, right?

2:29:33

>> Yeah, VC uh yeah, VCU, I think.

2:29:33

It's a video encoder, whatever unit.

2:29:35

But that's like really diminutive.

2:29:37

So it just doesn't I don't think that adds up.

2:29:38

How important is the is the Grok Cerebrus, these faster model on a chip companies, and does Google have an answer for that?

2:29:50

I Okay, so to be clear, Semi Semi Analysis is House's view wasn't that it was like the most important thing and we've always we you know we we have that chart about batch, right?

2:29:59

The fact that hey, doing more for everyone is much more valuable.

2:30:02

Clearly there seems to be a little bit of a niche market and a niche market demand.

2:30:05

And so Cerebrus and LPUs definitely have some kind of demand pull.

2:30:09

And I think we will see some kind of announcement at GTC.

2:30:13

But like you know, definitely wait and see.

2:30:15

Oh, that's kind of my impression.

2:30:17

Um that's kind of what we wrote about today in our By the way, I I think it's crazy.

2:30:21

I wasn't aware that the Vera Rubin post would come out until today.

2:30:25

Like literally I learned today and I was oh.

2:30:28

So I had to read it live with everyone else.

2:30:29

I think that's that's a big deal, too.

2:30:31

And we have a lot of information there um about what's coming at GTC. So.

2:30:36

>> Well, we're we're excited to follow it.

2:30:38

Um Nvidia earnings are usually out by uh 20 minutes after the hour 4:20, but it appears that they are delayed. So we will we will see.

2:30:46

Um I mean, of course we'll we'll have to have you back on the show to deep dive everything that's happening in the semiconductor space.

2:30:53

This this thanks this thanks is so much better.

2:30:54

I had like the bogey and all the information and what the setup is going to be.

2:30:58

And honestly, if we have we have 2 minutes, I'll tell you what to expect. Okay. Yeah, please. Hit us.

2:31:03

I think uh everyone thinks the guide will be 75 billion.

2:31:07

That's what everyone's really obsessed about. Mhm.

2:31:10

Um I think the questions that are going to be answered or asked, rather, is about memory price inflation.

2:31:15

Um that's going to be a big deal given the fact that I think memory prices are like, you know, mooning right now, HBM and DRAM.

2:31:21

I think Nvidia locked it all in.

2:31:24

So everyone is going to be like, how sure are you your gross margin isn't going to go down?

2:31:29

And they're going to be like, we're really sure.

2:31:30

But, they're going to be like, okay, how sure and what time?

2:31:33

And then there'll be like this random like circle that nobody can't answer.

2:31:35

Um and then I think one of the questions that people are going to definitely ask is about the power side.

2:31:39

Um it seems like next year Nvidia has more chips than power.

2:31:43

And so, that's going to be And I mean, to be clear, Nvidia has no power, right?

2:31:47

They have customers who acquire power.

2:31:49

And, you know, one of their big competitors in terms of market share, which is Google, has chips and power.

2:31:55

And so, I think that that's going to be a huge bottleneck.

2:31:57

And I think that's going to be one of the bigger questions that happens this quarter.

2:32:03

Hey, how do you deal with the power bottleneck?

2:32:04

Um because you you're going to sell a lot of chips, but if you can't even plug them in, this is a huge issue.

2:32:10

So, >> is is the idea that even if a lab or a hyperscaler said, we're actually good on chips right now, we don't have the power for for them, Nvidia would be like, well, you actually have to buy them if you want to maintain priority?

2:32:22

How do you think they would play that? I I don't know.

2:32:26

I mean, I think the thing is, it's not going to matter because the only company with a chip to sell you next year that is not going to account it for is Nvidia.

2:32:34

And I think the the shortage in GPUs is really under appreciated.

2:32:39

There's like you know, you can see it publicly, I forget which research shop shows it, like the availability of B100s, but our anecdotal information as well as the like the live price tracking and contract price that we're aware of, there's like no H100s for sale. Like H100s are sold out.

2:32:56

That's like boom, you're you know, your five-year depreciation like bear thesis that everyone was really freaking out about last year.

2:33:01

Well, good luck, you can't even buy one today.

2:33:05

So, that's probably the biggest interesting thing, and I think probably the single most bullish thing you can say. Love it.

2:33:11

You know, like a four-year-old chip effectively is completely sold out today. Yeah.

2:33:15

What what's that What does that say about the next generation? It's remarkable.

2:33:17

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

2:33:21

Uh bummer that they delayed on us, but next time we'll time up so that we have even more time to hang out, but I'm I'm so happy honestly like after the video earnings I was like >> Yeah. No, no, no.

2:33:31

Well, well, well, well, well, we'll get this flow going.

2:33:32

We we this is always fun, but I mean just great to talk about everything and happy birthday.

2:33:37

We'll talk to you >> Happy birthday.

2:33:38

Have a great rest of your week. >> Great to see you. We'll talk to you soon.

2:33:41

Let me tell you about Gusto, the unified platform for payroll, benefits, and HR built to evolve with modern small and medium-sized businesses.

2:33:47

Um we have our next guest, Marc Benioff, in the Restream waiting room.

2:33:53

Let's bring him into the TBP and I'll throw it to Marc.

2:33:56

Thank you so much for being first to [music] join us here on earnings day. We're honored. Great to see you. How's it going?

2:34:03

It's going fantastically over here.

2:34:06

>> metallic album I sent you? >> We did. We did.

2:34:08

Thank you so much for >> listen to it? Did Jordy listen?

2:34:13

>> We need a We need a record player. >> No, Jordy, again.

2:34:14

But >> Jordy Mark it again. Mark it again. Frame it. >> Jordy. Again. Again, Jordy. I have no words.

2:34:22

But, but [laughter] >> I have no words, Jordy.

2:34:25

>> Jordy can actually play the guitar and so next time you're on, he's going to be playing a cover.

2:34:31

>> I'll play you I'll play you a tune. Yes. >> How about that?

2:34:33

You got to I know you got to see it.

2:34:36

>> to come on the show with us. Oh, that'd be fantastic.

2:34:38

>> it would be really good.

2:34:38

We'll have to We'll have to make that happen.

2:34:40

Well, Well, I'm going to call out I'm calling out Jordy on the whole situation and >> [laughter] >> The reality is Yeah.

2:34:47

Jordy, you're still unforgiven. Oh, good one.

2:34:51

Uh well, anyway, thank you so much for joining us first on earnings day.

2:34:54

Uh take us through it because I got a mallet here that's itching to hit a gong.

2:35:00

>> [laughter] >> Well, if you want to hit a gong, I mean, no no enterprise software company has ever given guidance for 46.

2:35:10

2 billion dollars before. >> Let's go.

2:35:14

And these are crazy numbers. So, all right.

2:35:20

In a year >> gong, by the way. I love that gong. We love gongs. >> I really do.

2:35:24

But, I would say that that's exciting. Yes.

2:35:26

But, also just this company, you know, it's really become a cash machine as well with you know, we're projecting over $16 billion in cash flow this year.

2:35:37

So, when you think about that And then the quarter, you know, with the quarter we delivered this record RPO.

2:35:47

Funny thing, you know, some of my friends are writing these articles, RPO doesn't matter.

2:35:50

I mean, they have to just write a song, nothing matters.

2:35:54

>> [laughter] >> I don't know, nothing else matters.

2:35:54

But, RPO, which is, you know, kind of our remaining performance obligation.

2:35:59

These are contracts that we basically have signed but not yet recognized. >> Yeah. That is $72. 4 billion.

2:36:08

So, these are driving these huge numbers.

2:36:12

That's What does that mean?

2:36:12

What does that I think people have a good sense of That's up 14% year-over-year.

2:36:15

It's that all these numbers are accelerating growth. So, I don't know.

2:36:22

I just kind of I I am very proud of my team.

2:36:25

I'm very proud of our customers.

2:36:28

I I say also I'm very proud of customers because we've really been pushing the customers hard this year to deploy all this new amazing AI and agent technology.

2:36:38

And we've hit basically now more than 19 trillion tokens.

2:36:40

So, you can just see the velocity of AI and agents.

2:36:45

And the company's just transforming from being not just an apps company.

2:36:50

And I think you guys are using Slack and other Salesforce apps to run your business. >> Yeah.

2:36:54

But, now they're all extended with these agents.

2:36:56

Like Slack, not just Slack bot, but the ability to extend your service and your marketing and your sales.

2:37:02

And all the agents are out there and they're running wild as well.

2:37:03

So, you have apps and agents, humans and agents working together. It's very cool moment. Very cool.

2:37:08

Jordy, Uh, yeah, what what has it been like internally with the team uh this year?

2:37:16

It's been I has there been a more kind of chaotic period uh in your career?

2:37:21

How like how are you guys operating internally?

2:37:24

Clearly delivering results. Uh, what does it take?

2:37:30

>> well, you know, you know, we all been reading about the SASpocalypse.

2:37:35

And [laughter] but we've got our SASquatch is eating our SASpocalypse. >> Let's go. SASquatch.

2:37:40

[laughter] I just think that when you look at things like, you know, Agent Force, which we've talked about on the show now three times, you know, starting at Dreamforce, that, you know, and they first of all, Agent Force by itself is now an $800 million business up 170% year-over-year. Wow. So, that is amazing. All as its own product.

2:38:04

But then, you look at Agent Force and our data business together, that is now a $2.

2:38:08

9 billion business up 200% year-over-year.

2:38:12

So, there's no question that AI and data is a huge driver of growth.

2:38:16

And it's about these apps and these agents.

2:38:19

And, you know, we use the apps. We're these humans.

2:38:22

We're using the apps, you know, we're using Slack, we're using Sales Cloud, Service Cloud.

2:38:27

We're using all of our cool apps.

2:38:30

And then, each one of those now has an agent platform, also. Yeah.

2:38:32

And these two things together is the future of enterprise software.

2:38:36

That apps have been extended by agents.

2:38:38

And while we before were in the apps market, and that's what we've been doing for 26 years, you know, that we've been in business since 1999, now we're in the apps business and the agent business.

2:38:49

And I this is why I've never been more excited about my business. I just love it. Yeah. >> I really love it.

2:38:55

How much how much similarity is there to the original messaging just around like being a company that enables cloud adoption?

2:39:05

Like there were probably a lot of companies and and CEOs that came to you early in your career that said, like, I know this cloud thing's important. How do I do it? And you had an answer.

2:39:13

And now there's CEOs that say, I know this agentic thing and this AI thing is important. How do I do it?

2:39:19

And you probably have a pretty similar answer, right?

2:39:23

Is this Is this history repeating itself?

2:39:26

Oh my god, it's such a good question.

2:39:27

You know, Aneel Bhusri is now the CEO again of Workday. >> Yeah. He's my good friend.

2:39:31

Uh he lives, you know, basically next door to me. Came over last night.

2:39:35

We both had a cocktail cuz, you know, we're looking at his after-hours stock and I said, "There Aneel, there's no way this can be true.

2:39:43

You know, you have to let this go."

2:39:43

And in fact, you saw already that his stock corrected today because the numbers are just don't match Yeah.

2:39:49

you know, what's really going on.

2:39:51

He has an unbelievable business. He had a great quarter.

2:39:53

He's going to have a great year.

2:39:55

We use his HR and financials.

2:39:58

And I said, "Aneel, this is just something that you have to let go of.

2:40:02

This is not my first SaaS apocalypse."

2:40:05

>> [laughter] >> I SAW THIS IN 2008. I saw this in 2000 Yeah.

2:40:11

>> 1, 2000, 2016, you know.

2:40:11

And look, this is There's people in the market they make money in the when the market goes up and down.

2:40:18

So, that's just the stock market.

2:40:20

But let's talk about the customer success. >> Yeah.

2:40:23

And when you look at how companies can actually be better, more productive, successful, profitable companies.

2:40:28

And we are, you know, we're we're number one. We're customer zero.

2:40:33

And that's what I'm so excited about because when you look at how we're running customer service and support right now, we're using it with service agents and service apps. So, if you go to help. salesforce.

2:40:45

com, you're using the agent.

2:40:47

And at any point, bam, bam, bam, you can auto-escalate right back to the app and the humans if you like exhaust the agent.

2:40:55

Or now, this week, we have an agent that is is to qualify 50,000 leads for our company, you know, which is our sales agent.

2:41:03

Then, it's out there talking to our customers.

2:41:05

We've even closed millions of dollars of business this week just through the agents themselves. Yeah.

2:41:11

So, that is what is amazing that we have apps and agents.

2:41:16

And it's not that we don't have 15,000 sales people at Salesforce. We do.

2:41:21

And we have millions of apps all out there scurrying around looking for opportunities and then bringing them to those humans going, "Hey, look at this opportunity. Give this person a call.

2:41:31

Let's go see this person.

2:41:31

Let's go find out what to do." Yeah.

2:41:33

And that is really the >> Yeah, how much how much We're extended, elevated. We're elevated by AI. We're made better.

2:41:40

We know we're made better by AI. Yeah. There's no question.

2:41:45

>> been How much have you been kind of you know, all the the Citrini's post, we've talked about it at length on the show.

2:41:52

Very very a lot of a lot of doom.

2:41:56

But, we've been very focused on what's happening in in coding.

2:41:57

As these coding models have gotten better, people want to hire at least the data shows so far.

2:42:04

Citadel was showing up up job listings for engineers are up 11% year-over-year.

2:42:10

You've talked before about hiring more sales reps because as your reps get more productive, Mhm.

2:42:17

probably want more of them.

2:42:17

But, is that is that kind of comp that you're looking at given that I think everyone is expecting sales agents to to kind of get to kind of catch up to to coding agents in terms of capabilities? Great question. Amazing.

2:42:34

And you know, we were I wasn't really on the show at the beginning of the year a year ago with you guys, but if I was, what I would have said was, "I'm not hiring more engineers in fiscal year Yeah.

2:42:43

you know, '26, the year it just passed >> Yeah.

2:42:46

because I was using coding agents and I was allowing the productivity from the coding agent to give me the extra capacity that I needed for the year. Yeah.

2:42:53

And I I hire more service agents in the year.

2:42:56

I held it flat and then reduced it slightly cuz I'm using service agents.

2:43:00

But I did hire like almost 20% more sales people this year.

2:43:05

I think we've talked about that because I need more capacity cuz we have more demand than ever through every market from the small, medium, large customers.

2:43:14

You know, guys like yourself who are like these great entrepreneurs building a great business like TBPN really going all the way through it.

2:43:20

You need a technical infrastructure around you to grow your business. I know you use Slack.

2:43:26

I know you use other products.

2:43:28

And that's our job is to make you successful and to really bring in the apps and the agents.

2:43:32

You can't do it just with an agent. Yeah.

2:43:33

You need the you need We we there's still some humans around who need to be automated as well. Yeah.

2:43:40

And that is what is exciting. Yeah.

2:43:42

And that is what I'm doing every single day.

2:43:45

>> What advice do you have for a company like Anthropic that's hiring a Salesforce admin?

2:43:49

What makes for a great Salesforce admin?

2:43:55

>> [laughter] >> You're We are kind of leading beyond I mean, you know, it's kind of funny, right?

2:44:00

Because these AI companies, they love our products and they can't buy enough of them.

2:44:04

They're some of our largest customers now.

2:44:05

Anthropic, Open AI, Google, Amazon, you name it.

2:44:07

These tech companies Slack is the largest AI ecosystem in the world. You know that.

2:44:13

And that's reality, you know, which is that no one has a company that's running entirely on a large language model cuz it's not real.

2:44:22

That's not We have these software and we need large language models.

2:44:27

We need the determinism and the programmability and the security and the sharing.

2:44:30

And but this large language model is an amazing new component of our infrastructure so we can do things that we could never have done before.

2:44:39

That is what is so awesome.

2:44:42

And so we can extend our industry.

2:44:45

I think the software industry is going to be bigger and broader and do more this year than ever before.

2:44:50

Not just Salesforce, which is going to grow incredibly this year. Mhm.

2:44:53

I think every company's going to grow because we have more to sell and there's more excitement and action and energy.

2:44:59

And so this kind of counter narrative of oh no no, no, they don't understand.

2:45:05

We're just call that company who wrote that report and you ask them what is their software infrastructure, their magic infrastructure. I do this all the time.

2:45:16

Tell [snorts] me exactly how you're doing what you're saying that you're doing. Oh well, you're right. We're so sorry. We made a mistake.

2:45:22

No, you you know, and look, the futurist, I think we talked about this, Peter Schwartz, you know, our chief futurist.

2:45:29

He wrote Minority Report.

2:45:31

Have you seen that movie? It's like 20 years old. Great. Oh, yeah.

2:45:35

Jordi, you got to watch this.

2:45:37

And also he wrote War Games and Deep Impact.

2:45:39

You know, part of a team writing team. These are future movies.

2:45:41

But we all know where the future is kind of going, this highly automated amazing world.

2:45:48

But we're living in this world.

2:45:51

And this is this is this year. This is 2026.

2:45:57

You know, we're running our business today.

2:45:59

So how are we doing our financials, our HR, our customer information?

2:46:04

All right, you know, how are we doing all of these aspects of our business? How are we running them?

2:46:08

And then we write a we write a report that sounds like Minority Report.

2:46:15

And then I'm like, yeah, Minority Report, I read the movie I watched the movie. Great guys. Fantastic.

2:46:17

But I'm in the present moment reality right now, you know?

2:46:26

And come let's come back to world.

2:46:26

And by the way, like you can do things that you couldn't do before.

2:46:31

This quarter I released our new ITSM product.

2:46:35

So our customers can do this incredible thing, you know, IT service management.

2:46:40

They used to have to go to ServiceNow for that.

2:46:41

Now we converted five ServiceNow customers, you know, just in the quarter right over to Salesforce because we have that new capability.

2:46:48

So, companies like SunRun and Cornerstone and CoolSys and others, you know, they can now use Salesforce ITSM instead of ServiceNow. That's so exciting.

2:46:56

And then we have our new life sciences cloud that we've built all with an agentic interface.

2:47:02

So, our customers do not have to use Vevo.

2:47:05

And those customers are instead, you know, those are big companies like the Pfizers and the Takedas and the Novartis and the AbbVie.

2:47:15

So, they're running with this next-generation platform of apps and agents, apps and agents, and humans and agents working together. Yeah.

2:47:22

So, I mean, the the business model currently is clearly working. The results show that.

2:47:27

Uh as you look into the future, do you think the business model will evolve?

2:47:30

Do you think that we're going towards more consumption-based?

2:47:35

Is there Is seat-based going to be with us forever?

2:47:38

Like, how are you thinking?

2:47:38

Obviously, you don't need to turn the cruise ship today, but how do you think this evolves over time?

2:47:45

It's such a great question, right?

2:47:46

Because that's like one of these interesting narratives.

2:47:47

But, hey, I don't know which which Anthropic product you're using, but the one I'm using is seat-based. Mhm.

2:47:54

So, if you don't have If you have a different one, or I have a I don't know which OpenAI product you're using, but mine is seat-based. >> Yeah. I have a seat.

2:48:02

I don't know which one you're using.

2:48:05

>> It's a good It's a good tag.

2:48:05

Of course, you can use use the API and there's an API in there also. >> API also? There's an API also? Yeah.

2:48:12

But, they're happy to be selling seats right now. You're right. Yeah.

2:48:14

>> [clears throat] >> Now, we I This is about humans and agents.

2:48:18

So, let's use that analogy. Humans are seats.

2:48:20

And so, they're still like us three We're like the last three humans.

2:48:24

It's very sad, but we're still [laughter] here. And then Hanging out. we have the agents, too.

2:48:30

And they're using the APIs and talking to each other and they're on mobile, and they're like having a conversation, creating their own currency.

2:48:37

>> They're talking about us.

2:48:37

They're talking some smack.

2:48:38

They're saying, "Oh, can you believe those humans are still there?

2:48:42

We're going to get them." Yeah.

2:48:43

And it's like, "No, we're It's still humans and agents working together."

2:48:44

And that is what is exciting about the future of enterprise software.

2:48:49

So, yes, I have a Salesforce, but it's extended with sales agents.

2:48:53

And I have a service organization extended with service agents.

2:48:57

And I'm sending a trillion marketing messages this year, but they're all extended with marketing agents.

2:49:03

And I have commerce agents.

2:49:03

And I've got Yeah, and you guys use Slack every day, right?

2:49:07

And you're using Slackbot now, hopefully? Yes.

2:49:09

You know, since the last time.

2:49:12

I would say it's like amazing that I can use agents in Slack.

2:49:15

So, I have employee agents.

2:49:17

And we might have some other new exciting agents coming in the next few weeks for you. I'm very excited.

2:49:21

Yeah, I'm very inspired by Maltbot.

2:49:23

I'm now got, you know, our team working on some new things.

2:49:26

So, that is like how I see it unfolding.

2:49:28

And I think it's about a world where there are apps and agents.

2:49:33

And where this large language model, it's extending our capability. It makes us better. Makes us stronger.

2:49:39

It gives us the ability to do more.

2:49:42

And yes, seats still exist.

2:49:42

And also consumption exists.

2:49:44

Like we have, you know, lots of consumption products.

2:49:49

Data, you know, data products and Was there ever a Was there ever a SaaS apocalypse that was driven by fear that open source software would defeat your products, defeat Salesforce?

2:50:04

Oh, no, there was a bigger SaaS apocalypse than that. Okay.

2:50:05

Do you remember the SaaS apocalypse of 2020? Mhm.

2:50:10

Let's >> apocalypse of 2020, John, let me tell you the story.

2:50:16

We were all minding our own business and then CNN came on and said we were all going to die.

2:50:20

Not just the software companies, everyone, cuz [laughter] it was the pandemic.

2:50:24

And we all went home and we hid and it was a very sad time.

2:50:29

And in fact, right at that moment, the stock market crashed because we were all going to die.

2:50:33

And that was a huge SaaS apocalypse.

2:50:35

And you can see it in everyone's stock chart.

2:50:37

It goes like this and then Yep.

2:50:39

And then all of a sudden people go, "I guess we're not dying."

2:50:42

And then it came back up. Yep.

2:50:44

And that was a sasspocalypse of 2020.

2:50:46

It's a sad tale, but we lived through it. And we got through it. And you know what? We're stronger for it. >> Yeah.

2:50:53

And that was just one of the sasspocalypses. >> Yeah.

2:50:56

Talk about the reception of the Super Bowl ad.

2:51:00

Well, listen, I don't want to be competitive with you guys cuz your ad was very good. You did great. to know.

2:51:05

>> [laughter] >> You were the strong. >> a great job. You should feel great. >> I appreciate that.

2:51:09

You know, you had a great great ad. Everybody loved it. Very high ROI.

2:51:15

>> No, we were the number one ad in the Super Bowl, which >> [laughter] >> Okay. Mog meter going up. Let's go. Ad mogged. Ad mogged.

2:51:25

I I'm sorry, but it has to be said because, you know, we have Jimmy Donaldson, Mr. Beast. Yeah, he's the best. And Mr.

2:51:32

Beast did a great job and that was the the killer ad and um we still haven't revealed the final uh thing.

2:51:38

We have a great person here, John Zissimos, who did a fantastic job with Jimmy and it was an unbelievable partnership, but Jimmy's just he's a force of nature. Yeah.

2:51:46

I mean, I've never seen anything like this.

2:51:48

He's such a young, great, amazing entrepreneurs.

2:51:53

The first time I ever talked to him, which was years ago, he said to me, "I want to be the future Steve Jobs."

2:51:59

You know, I want to be the future great entrepreneur of the world.

2:52:01

I had to pause and say, "Really?"

2:52:02

He's like, "Yeah, that's what really I want in my life.

2:52:07

I want to be a great business leader, a great" and I think he's doing it. And he's so young.

2:52:11

You know, we've already had him on the cover of Time magazine once.

2:52:14

You know, and I see, you know, him as a huge leader in the whole world, not just as some kind of YouTube personality.

2:52:23

This is a great entrepreneur, business person, not just making chocolate bars, not just running a bank.

2:52:29

I see him doing a lot of amazing things.

2:52:31

And he's got a lot of energy, incredible, and uh I have a lot of respect for him.

2:52:35

And yes, number one Super Bowl ad. How about that?

2:52:37

There's a lot of entrepreneurs listening, a lot of entrepreneurs that are searching for their next great business idea.

2:52:41

If they want to go swimming with dolphins and get inspired, what's the most underrated time to visit Hawaii? You're right.

2:52:51

Well, number one, this week we have been having an awesome show from Kilauea volcano.

2:52:54

We had a 12, 13, 1400 ft tower, which is I'm in Salesforce Tower, San Francisco right now. Gorgeous. You guys should come. Yeah.

2:53:04

And the the fountain from the volcano was taller than this tower this week. So, that is amazing.

2:53:08

And you're right, all the little dolphins were so happy.

2:53:14

>> [laughter] >> They were cruising around.

2:53:15

But also, it's whale season on the North Shore of Oahu, so they were >> [laughter] >> They were going They were so happy also.

2:53:23

Everyone gets happy when you see the volcano.

2:53:26

It's like It's like the way It's like when you see a whale. Yeah. Yeah.

2:53:32

It reminds you of who you really are.

2:53:32

It reminds you this is what life is really all about. >> Yeah.

2:53:37

You come back to your breath.

2:53:37

You come back I don't know.

2:53:39

When I see whales out, I think of agents.

2:53:44

I think [laughter] of agents wars, personally. Hey. Yeah, you got to run. Sorry.

2:53:48

But I have a challenge for you.

2:53:49

Be before we talk again, you got to frame mug one of the AI lab leaders.

2:53:55

>> Oh, this is This is big alpha right here. I think it's possible. We'll coordinate. We'll coordinate.

2:54:02

Have a great rest of your day.

2:54:03

Congratulations on all the projects. Thank you so much.

2:54:06

Jordyn, you better listen to Metallica album because I swear to you, I'll bring Lars on here if you're not ready. Okay.

2:54:12

You're just lucky I didn't bring him on today. On repeat. On repeat. We'll talk to you soon. Great to see you. >> Have a good one. Cheers.

2:54:19

>> [laughter] >> Goodbye.

2:54:19

Well, if you're tracking earnings, you should be doing it on public. com.

2:54:22

Investing for those who take it seriously, stocks, options, bonds, crypto, treasuries, and more with great customer service.

2:54:29

And without further ado, we will kick off the Lambda lightning round.

2:54:36

Let that Let that cloud ring out because we're starting the Lambda How are you doing?

2:54:43

Hey guys, how's it going?

2:54:43

We are here [clears throat] welcome to the show.

2:54:46

Tough act to follow with uh with Benioff who turns it up to 11 every time. >> do any animal sounds?

2:54:51

He's got the He's got the dolphin down. He's got the whale down.

2:54:55

This is a unique ability.

2:54:55

Didn't know it was necessary.

2:54:57

We're not going to have you make any uh any any whale sounds.

2:55:03

Uh but uh it's great to meet you. >> Great to meet you. First time on the show.

2:55:05

Please introduce yourself and the company. Great to be here.

2:55:06

My name is Michael Manapat.

2:55:09

I'm the co-founder of a company called Rose Space.

2:55:11

And Rose Space is an AI platform for asset managers.

2:55:15

We help our customers use their institutional memory.

2:55:18

So that means all their proprietary data, their accumulated judgment to make decisions faster. Okay.

2:55:25

So what that looks like is we actually plug in to all of their internal systems.

2:55:29

This is not just documents, but it's databases, CRMs, accounting and trade information.

2:55:34

And we use agents to understand all the connections in that data, the inconsistencies, the conflicts.

2:55:40

So agents can reason over it holistically.

2:55:45

The idea here is that data is fragmented and is siloed and it's hard to make sense of in a single context window. Yeah.

2:55:52

But using this having agents work on this in advance is is very helpful. Yeah.

2:55:57

Uh how jealous should every asset manager be of Bridgewater for collecting so much data over so many years?

2:56:07

Uh do you have a view on the Bridgewater strategy?

2:56:09

Can you explain what they actually do and whether or not you're a fan of it?

2:56:17

I can't speak to Bridgewater specifically, but I think you land on our key point here, which is that public data is getting increasingly commoditized. Yeah.

2:56:28

And actually [clears throat] AI is accelerating the commoditization of public data.

2:56:31

The more you have tools like Claude that can synthesize anything from the web or from public tools, less edge there is there.

2:56:39

So, the best edge firms have now is decades of data accumulation and their own insight and judgment as encoded in their data.

2:56:49

And our whole goal is to help our customers tap that.

2:56:55

In almost every customer conversation we have, there's a line that's something like, "We are sitting on enormous value in our data if only we could get at it or only we could find it."

2:57:04

And And that's what we're trying to do.

2:57:06

So, I think AI will accelerate this dependence on your internal data and proprietary data as public data becomes less and less, you know, uh valuable. Yeah.

2:57:14

Uh talk to me about what uh what your product actually looks like once you roll it out.

2:57:22

I because, you know, a lot of hedge funds and asset managers, they do a lot of backtesting, and I could imagine going back and running a report like, "Backtest the thesis that we talked about, but maybe we didn't actually implement."

2:57:33

There's a whole bunch of ways that you could just do reporting, but then you could also go and say, "Hey, you know, just turn this thing loose. Go trade for us."

2:57:40

Like, where are we on that continuum?

2:57:44

Oh, there are there are a lot of great points there.

2:57:46

So, the first thing is we are not trading or taking action automatically.

2:57:51

The idea here is that we'll help these firms consider the full amount of data that's possible, and then they make the decision.

2:57:59

>> [clears throat] >> But our goal really is it used to not be possible to say review every single name in the universe if you are about to consider a trade to rebalance your entire portfolio.

2:58:07

Now you can with with Rosebud.

2:58:09

Uh but it's still a human who makes the ultimate call there. So, that's one thing.

2:58:16

>> [clears throat] >> The second thing is on on backtesting, I love that example because it's actually been surprising how little post hoc analysis people do of their investment or trading decisions.

2:58:27

Just what was our thesis a year ago, two years ago, 10 years ago? What actually happened?

2:58:32

How does that inform what we're doing in the future?

2:58:36

That was just a time-consuming thing to do and people don't do it very much.

2:58:38

But we work with a private equity firm now.

2:58:43

It's been in business for 50 [clears throat] years, a pioneer in the field, and they actually they can actually run every deal through Rose Base along the lines of given our 50 years of history, what should we do here? What have we done? What are the risks?

2:58:58

And that kind of analysis was not even possible before. Yeah.

2:59:02

What what is your competitive positioning like with the labs?

2:59:04

They're all hiring consulting firms.

2:59:07

They have forward-deployed engineers.

2:59:10

I'm sure they're pitching a lot of the same companies.

2:59:14

And I can imagine how you would position Rose Base against building something internal or just leveraging leveraging the the the applications that the labs are building, but but how do you sell it?

2:59:30

So on the apps that are out there now from labs and from other players in the market, what we see is a focus on time savings.

2:59:37

So faster models, faster decks, faster summarization of meetings and research.

2:59:43

And that's obviously extremely valuable.

2:59:45

But our focus has been on decision-making.

2:59:48

So [clears throat] what are the things you should be looking at which were which would have been impossible to consider before that Rose Base can help you with.

2:59:55

So in some sense, there are things that our customers do with Rose Base today which they did not do before.

3:00:02

It's not about saving them time doing work that they have done in the past.

3:00:06

So that's one one chunk of it.

3:00:09

The other chunk is we're talking about in some sense the crown jewels for our customers, all this trading data, position data, their thinking and thesis.

3:00:19

This is extremely sensitive.

3:00:21

So, we only deploy in our customers' environment.

3:00:23

[clears throat] We never as a company actually take possession of their data.

3:00:26

And we do all of this processing in their environment.

3:00:31

So, we have a security challenge, an infra challenge, and AI one.

3:00:34

And I think the sensitivity to the security compliance and other constraints of finance is a big differentiator for us. Mhm.

3:00:44

Take us through the fundraising round. What happened?

3:00:47

Uh so, we've done two rounds over the past 18 months, uh 50 million in total.

3:00:53

Uh I was joined by my former clients and we're just happy to join in in the A.

3:00:59

And we've had uh my former bosses Roger Show on Monday and they were big player in both the seed and the A at Stripe.

3:01:06

So, uh it's been really fun because uh every major investor on our cap table I've been close to for at least half a decade.

3:01:14

So, it was nice to get to do a bit of this uh bring back the old gang together. That's amazing. Well, congratulations. >> the company based?

3:01:22

Uh we are based in San Francisco, but a big push for the company this year is to expand our New York presence. >> Of course.

3:01:27

Yeah, that makes total sense.

3:01:29

Well, have a great rest of your day.

3:01:30

Thanks so much for popping by to tell us about the business. Very fascinating. Good luck. >> Thanks for having me.

3:01:34

[clears throat] We'll talk to you soon. Cheers. Goodbye.

3:01:37

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3:01:39

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3:01:41

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3:01:49

And without further ado, we'll bring in our next guest, Adam Warmoth from Chariot Defense. How you doing, Adam? Yes. What's going on? >> see you again.

3:01:58

Welcome back to the show.

3:02:00

Uh let's kick it off with the news. What happened? Yeah.

3:02:04

Uh today Today announced our $34 million Series A.

3:02:07

Yeah, let's get the gong.

3:02:11

You got a bigger gong since the last time you were on. >> We did. Welcome back. >> Welcome back.

3:02:16

So, not as impressive as as a $34 million series A, but it's it's up there.

3:02:21

Yeah, take us take us through the shape of the business today, the key customers, key products, and and sort of what changed since the last time you were on the show. Yeah, awesome.

3:02:32

So, the last time I was on the show, I was just getting done with our first transformation in contact exercise.

3:02:37

You guys had had Anduril's Ryan George on the show.

3:02:39

They'd kind of talked about that.

3:02:41

We were just coming back from our first participation there.

3:02:44

That was our second test event.

3:02:44

We've done about 25 since then.

3:02:46

And so we've got systems deployed in pretty much every theater across a bunch of different army units, Marine Corps units, and really just starting to see the traction and demand for the systems grow.

3:03:02

As we do see things like drone dominance happening, as we see things like next generation command and control, all of those systems are fielding and running into issues with that power infrastructure layer.

3:03:12

And we've been able to fill that gap and do it very quickly kind of working with the warfighters, working with the soldiers, and getting the systems out there.

3:03:18

And assume assume that, you know, someone listening today didn't catch your first appearance, catch us up to speed on the shape of the product and and all that.

3:03:30

Yeah, so so effectively what Chariot's building is the power layer for robot at warfare.

3:03:36

So really, you know, you wouldn't send a soldier into the fight without food and water and nicotine.

3:03:41

You [laughter] wouldn't You wouldn't send a robot into the fight without communications, compute, and power. Cool.

3:03:46

And so we really see that as one of those core infrastructure layers behind kind of this defense modernization.

3:03:53

You know, Anduril's building some great systems in the compute space, Palantir really dominating the network space, and we're kind of building that third missing layer.

3:04:02

And so effectively what we're doing is taking the technology coming out of companies like Tesla, Apple, Lucid, Rivian, Archer, Joby, high voltage batteries, silicon carbide power electronics.

3:04:11

If you've read Pac McCormick's The Electric Slide, goes into detail on kind of major transformations happening in the commercial industry on that core technology stack. Yeah.

3:04:18

We're taking those and lifting and shifting them into the defense platforms to build hybrid high power systems.

3:04:24

Yeah, walk us through exactly what needs to happen to deploy a high voltage battery on the battlefield.

3:04:31

I think most people will be familiar with like the Tesla Powerwall and we've all seen like the IBM Toughbook.

3:04:37

You put some rubber corners on it and give it a nice graphite, you know, case and I imagine there's a lot a lot more going on.

3:04:45

So, what's the state of the art?

3:04:48

Yeah, that's great question.

3:04:48

So, we really kind of take the best of commercial technology. Mhm.

3:04:51

Our first product we deployed, uh, M424, is literally in a Pelican case. Okay. Um, Yeah.

3:04:58

so we took a Pelican case.

3:04:58

We're saying, Yeah, why reinvent the wheel? Yeah.

3:05:01

Uh, on on just some of that core rugged, uh, technology.

3:05:05

We do some additive manufacturing, uh, to create these kind of internal bulkhead structures, Sure.

3:05:08

um, to kind of isolate, uh, the the electronics. >> Yeah.

3:05:13

And then we integrate the batteries, the power electronics, the microcontrollers into that in a form factor that can be left out in the rain and mud, Yeah.

3:05:19

can be dropped off the back of a Humvee. Yeah.

3:05:20

Uh, and when I say can be, has been, uh, and has has looked at the tail of the tail.

3:05:24

Yeah, so you've been through testing.

3:05:25

I assume you've done some SBIRs.

3:05:27

Are you moving towards program of record or are you just sort of in the supply chain for other companies that might be primary, uh, contractor?

3:05:37

Yeah, so we've got a split go-to-market model.

3:05:38

One being directly to the government, both bottom-up selling directly to units and top-down program of record. Okay.

3:05:43

Uh, and then also selling to other companies, uh, as part of a broader kit. Cool.

3:05:46

Um, so the inspiration for Chariot was I was the counter UAS program manager at Anduril. Yeah.

3:05:51

Uh, we were constantly running into power problems, >> Yeah. right?

3:05:53

So, kind of But idea of selling this as part of a power kit, uh that's enabling other systems is is another part of our go-to-market model. Very cool.

3:06:00

Uh where do you where do you stand on the verticalization debate?

3:06:02

We had uh we had uh Mike from Also Capital on really he kicked the hornet's nest cuz he was basically saying like, "Yeah, it's great to verticalize, but there there's uh there's there's some businesses that you can just buy a lot of components off the shelf and make a great product, prove that people want it, and then do it later."

3:06:26

A lot of people I would say most people were were disagreeing with that, but there's every business is different. >> Yeah.

3:06:35

I am I'm going to I'm going to come in here on team Mike.

3:06:37

Um so uh you know, we've really been able to leverage the supply chains from companies like Tesla, right?

3:06:44

And and and Apple and and Archer, where you have actually mature commercial technologies around these core components, around batteries and power electronics.

3:06:51

Uh what nobody has done is kind of gone and done that forward deploy light engineering. >> Mhm.

3:06:56

Um and so Erin Price Wright, who led a round, uh I think in her post said, you know, we should actually call Adam the chief forward deployed engineer.

3:07:01

Um that's really what I've been doing over the past year. Yeah.

3:07:03

Um and it's that forward deployed engineering model that kind of maps to what Palantir and Anduril did as well. Yeah.

3:07:09

So Palantir didn't invent, you know, cloud compute, right?

3:07:11

Uh or big data models, right?

3:07:14

Right, that was tens of billions of dollars of investment from Silicon Valley companies, and then through good go-to-market, good forward deployed engineering, brought that into the department. >> Okay. Uh Anduril did the same.

3:07:22

The the Sentry First Sentry Tower was, you know, really enabled by the uh autonomy technology developed by the self-driving car industry. >> Mhm.

3:07:31

You know, computer vision went from an unsolved problem in 2014 to just download yellow V4 in 2017, and they were able to kind of capitalize on massive investment, right?

3:07:40

Uh in from the self-driving car industry, and just through good forward deployed engineering, uh good go-to-market, uh bring that into the the department.

3:07:46

And that's what we're doing for all the technology coming out of electric vehicle, electrical transportation space.

3:07:53

What are you most excited about in defense tech?

3:07:55