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[Music] [Music] You came to this world to reach the stars.

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We came to this world to shape our future.

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We came to this world [Music] to reach the stars to shape our future.

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[Music] Reaching to feel the new Feel the music.

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[Music] [Music] If you let me feel [Music] for [Music] You're watching TVPN.

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Today is Tuesday, June 10th, 2025.

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We are live from the TVPN Ultra Dome, the temple of technology, the fortress of finance, the capital of capital. It's a great day.

5:02

We're doing WWC reactions.

5:02

I will run you through a little bit of the show.

5:04

We want to talk about the Meta Scale AI deal.

5:07

49% for just 14 billion dollars. It's a steal. You're getting Alex.

5:14

You're getting the SK the scale AI team. They're giving it away.

5:16

Uh we we're going to talk about the Glean fund raise uh competitor to open AI.

5:20

They're cooking in enterprise AI.

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Um some of the reaction there from uh what's going on in deep research and some of the uh advancements that uh open AI has been rolling out there.

5:33

Very interesting for Glean's business. Glean still ripping.

5:36

So, they're they're up, raised a big round uh today.

5:38

Uh they also got the CNBC disruptor list, 50 top startups.

5:43

We've had a ton of them on the show.

5:45

We're going to go through do a little underrated, overrated, maybe see who should be higher.

5:49

John, personally, I love them all.

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I think they should all be tied for first place, but CNBC ranked them one to 50.

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Hopefully, hopefully it was purely paytoplay and CNBC just kind of auctioned off the spots.

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That's that would be the most fair thing, you know. Agree.

6:04

But um uh and then we got a bunch of great guests.

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Uh we got Sai from Redpoint coming on.

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We have uh Kari announcing a massive uh what is it?

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Series C unicorn round at linear. One of our sponsor.

6:16

It must be their series C.

6:17

We got Bellki from A24 coming on.

6:17

Roy Bahhat from Bloomberg Beta coming on announcing a new $75 million fund. Metropolis. And then we got Andrew. This guy Andrew Hubman.

6:28

Andrew may have heard of him. Fellow podcaster. Yeah.

6:30

So, we're excited for the show today.

6:33

Uh, but let's kick it off with the timelines reaction to WWDC liquid glass.

6:38

Whatever says Juan, the most important thing in iOS 26 text is finally left aligned.

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You know, I saw people posting about this.

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You said this about like the center alignment, left alignment thing. I hadn't noticed it.

6:55

It looks a lot better left aligned. I don't know why.

6:57

I didn't know what I was missing. Huge improvement. We'll take it.

7:01

Uh yeah, so now text in iOS notifications left aligned. Huge news.

7:06

Also massive all the different version numbers are now uh they're doing car models. So it's iOS 26.

7:13

They jump forward a bunch.

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I believe we were on like 18 before.

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So they just skipped a bunch.

7:17

I can't wait to be in the thousands. We're in 2025.

7:18

It's the 20 and it's iOS 26 across everything. So unification there.

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Uh it's happened in in in Android a while ago, but now it's uh it's come to iOS. Um love it.

7:29

Uh again, a lot of people with negative reactions.

7:34

We're going to take you through some of the positive reactions.

7:38

Uh Steve Jobs would have cornered you in a dark alley and beat you to with a metal pipe if you suggested something like this. That's what Kitsy says.

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This was yesterday's reaction.

7:45

Today, some of the designers are coming out and saying, "Hey, let them cook."

7:49

There's there's a silver lining here.

7:51

There's certain there's certain examples that are really really gnarly.

7:56

So, so there's that one super viral one that's like really hard to see and then people put it next to the Oenheimer with the the blast.

8:01

I think that's a fake photo.

8:04

I think they adjusted the brightness on that.

8:07

I don't think that that's I think No, not a deep fake.

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I don't think there's any AI involved.

8:12

I just think that that someone went in there and was like, "Let me turn up the brightness for for effect."

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Uh, and I think that that's fake.

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And I think that also, again, this is this is a beta.

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This is something that they're going to be iterating on before it goes out to the masses.

8:24

They're going to think bit weird for a trillion dollar company to launch a beta instead of they should just say no this is an alpha. Yes.

8:33

But but but it makes sense in terms of like like if you are a developer and there's a and there's a significant change to the user interface, you want to bake that into your app so that you don't look out of place on day one when everyone updates. Yeah.

8:47

So, you got to get the beta into the hands of the developers so that the Airbnb app and the public. com app and the ramp.

8:53

com app save time and money. Time is money. Save both.

8:57

Easy to use corporate cards, bill payment, accounting, and a whole lot more all in one place. Go to ramp. com and travel.

9:01

John's favorite and travel. The travel is amazing. Favorite thing.

9:06

Speaking of which, we got to book our we got to book our hotels for tonight because we're going to San Francisco for YC demo day tomorrow. Tune in.

9:09

It's gonna be a massive stream.

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With RAM travel, you can book last minute and it's still a breeze.

9:14

It's really, really easy.

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Um, but yes, if you're designing an app, you want it to feel somewhat seamless with the rest of the UI.

9:20

And if there's UI changes, you gota you got to test drive those beforehand.

9:25

You got to make sure that those are right.

9:26

So, the big question, should we have our intern Tyler Cosgrove over there install iOS 26 beta?

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You know, it's potentially Hey, he's on the green screen. Something happened.

9:39

He's on the green screen.

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Uh, should we make Tyler install? Oh, there. There we go.

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that that's where he is really like I'm glad that you did the f false background for a minute and make it look like a green screen instead of showing the real Yeah, we wanted him to be more approachable. Yeah.

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So, we just put a green screen behind him as a fake background. Yeah.

9:56

But uh but but anyways, back to you. Is that uh Mkos?

10:00

Where where are you right now?

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Oh, this is just my my pool in my backyard. Okay, cool.

10:04

This is where you take sometimes, you know, sometimes fellow some of my friends will will go on podcasts.

10:10

They'll just use my backyard. Yeah. Yeah. Oh, yeah. That that's what it is.

10:13

Um, anyways, I would love uh I would love to uh watch you risk it all and install the update.

10:18

So, why don't you Are you willing to do it? I'll do it. Yeah.

10:21

He's gonna do it for the team.

10:23

He's taking one for the team. iOS 26 beta.

10:26

It could go terribly wrong because the bugs, you know, that the the thing with the beta is that you can't go back.

10:32

You can't you can't roll back to the non beta. Yeah.

10:34

And so you could be living with with a with minor grading bugs for like months until they fix it.

10:40

Now they fix it pretty quickly.

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I've done it like once or twice gone on the beta cuz I'm so excited.

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I want to try the new thing.

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This is basically intern hazing. It is hazing. It's in the modern era.

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It's the WWC versioning is set up. All right, Tyler. Well, you are brave.

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Okay, good luck with that.

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And uh get Why don't you get started and we'll start and give us uh give us the review.

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will be checking in with you to see how the iOS 26 installation process goes and um and and any any problems you run into there.

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Um we also have some other He's like I can't I can't read anything on my phone anymore.

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We also have some we also have some big show updates.

11:20

Not only do you have intern cam now we also have the breaking news camera. Let's go to it.

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Now this is crazy too because I can see you see this. Okay.

11:30

So this is the breaking news camera.

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When we have breaking news, we cut to the printer. Cut and it prints out.

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You can read the breaking news.

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Okay, you want to read that to us? Hold it up.

11:38

We have some breaking news.

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If we can switch cameras. What is it? So breaking news.

11:42

Snap to launch smaller, lighter augmented reality specs smart glasses in 2026.

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I'm excited for this from CNBC. Thank you to CNBC.

11:51

Uh, Snap on Tuesday announced its plans to release a sixth generation of its augmented reality glasses in 2026 as competition in the smart glasses market continues to heat up.

12:00

The maker of Snapchat said that its next generation glasses will be called Specs, breaking with the company's spectacles branding that it used for previous Drop the ales. Drop the ales. Just use Specs. It's cleaner.

12:14

Well, they they dropped the T, too.

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So, it's it's technically Drop the tackles. Drop specs.

12:19

Drop the tackles, just specs.

12:22

Uh, larger tech rivals like Meta, Apple, and Alphabet are investing heavily into cutting edge headwear devices. Yep.

12:29

Uh, so the last computer will be on your face.

12:32

So the most recent the most recent edition of Spectacles were released in September 2024 to developers only.

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That addition of the glasses was available under a leasing model that that required users to commit to paying $99 a month for a full year if you wanted to develop for them.

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So that's $1,200 guaranteed.

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Um and then if you want to keep it more, it's probably continues to be $100. So it'll be interesting.

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It'll run Snap OS operating system, which they developed inhouse.

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Um Snap said the developers will be able to incorporate Google's Gemini AI models into programs that they develop for smart glasses.

13:05

So some sort of Yeah, exactly.

13:08

So, you could see some where it's like, okay, you're going to get the glasses, you're going to build out, Google says, hey, that's where you're going with it. Okay. I don't I don't know.

13:17

I I think very unlikely, but um but still, you know, well, Snap's market cap exactly what uh Meta just paid for a 50% stake in Scale AI, 14 billion. Anything's possible. Spicy.

13:31

So, Snap's at 14 billion.

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Um the the stock hasn't really moved over the past five days on this news.

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Uh it's clearly Snap, you know, uh staying in the game with the WWC news, getting something getting a story out there that hey, we're still in the game.

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We're moving and we're doing cool stuff.

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And and I'm excited for this.

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I think we need more uh more innovation here, more people testing different stuff.

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And it's clear that with a new format, with a new uh paradigm of like what the product is, there's a whole bunch of interesting directions you can go.

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Whether there's an augmented reality display, whether it's voice only, whether it's glasses, glasses, whole bunch of different things.

14:07

Social media goats, both of them are just not the idea of not being a part of the next platform shift is just an idea they don't is a world they don't want to live in, right?

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It's they are, you know, both both um Zuck and and Evan are going to be, you know, competing. Yeah. And so fun.

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Uh could be interesting from a developer angle.

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Obviously, um, you know, nowhere near the budget of reality labs for what Zuck is working on with Meta, but constraints, they can be good, John. I agree. I agree. They can be good. I'm optimistic.

14:40

I certainly want to try it.

14:42

Um, anyway, let's go back to Liquid Glass.

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Ben Thompson gave a whole uh posted a massive article on strategy called Apples Retreat.

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Apple retreats, something like that.

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You should give it a read.

14:52

You should subscribe to strategy obviously.

14:54

Um, Apple's retreat to its core competency.

14:56

The headline feature of WWDC this year, this is from the latest Certe article, was liquid glass, a new unified design language that stretches across its operating systems.

15:05

I will reserve judgment on Liquid's glass aesthetics and usability.

15:09

Gruber likes it journalist on the horizon, but I am not one to install developer betas on my devices. But Tyler will. But Tyler will.

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That's why we have Tyler because I agree with Ben Thompson.

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It's extremely risky, but he's willing to do it.

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taking one for the team over there.

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I mean, the whole the whole TBPN army, he's he's really saying, "I will I will sacrifice my sword developer beta." The developer beta. It's okay.

15:39

If it goes really south, we'll get a we'll get a new phone.

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And it's always always a possibility, but good luck.

15:44

Hopefully, you make it through, Tyler.

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We'll be checking on you throughout the show.

15:47

Um, so, uh, first let's read Gruber's, uh, Gruber's, uh, overview of his reaction to Liquid Glass because we saw Timeline hated it.

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They said Steve Jobs would hate it. Let's go to John.

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I think part of it is is it was popular to hate on it. Totally.

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And because everyone loves when someone's on a downswing, they love just piling on downwards.

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And when everyone's on an upswing, they love just piling on upwards. It's not No.

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But I think I think it's also normal if a if a widely used consumer product does any type of meaningful upgrade.

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I mean this default is that there were pro meta or Facebook back in the day launching the feed.

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They're like I want to go back to just randomly looking at your profile.

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I don't want to see random all everything every change is always met with some sort of push back and then years later uh people wind up loving it.

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I feel like this is something that could grow on me.

16:40

I'm I'm reserving until we've fully beta tested it on our intern.

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If he gives it the thumbs up, I'm going to install it.

16:46

Uh so, let's go to John Gerber.

16:48

I mean, it's kind of it's it's it's kind of fun.

16:50

It's it's daring and brave and bold to do something like that.

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And uh you know, just because Tyler's doing it, you know, doesn't mean you shouldn't, you know, this this type of bravery that Tyler's exhibiting today, I think it might be one day like an exhibit in the computer history museum. Totally.

17:06

bravery he's he's exhibiting today will be in the history.

17:10

They might even name the next operating system. Cosgrove. Cosgrove. Mac OS 27.

17:15

Mac OS Cosgrove after Taho.

17:19

It's got an amazing ring to it.

17:21

It's got a nice ring to it and it just loads with this image.

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Like that's the default wallpaper for the daring and brave technologist who installed the beta on day two.

17:29

Did you know what everybody said? You're crazy. You're crazy. It's impossible. You're crazy.

17:35

You should never do that. But he did it. He took the leap. He took the leap.

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He lives to tell the tale.

17:38

So first, this is going back to Ben Thompson's piece.

17:44

First, handcrafted UI overhauls are the polar opposite of a probabilistic world of generative AI.

17:50

One, uh, is about deep consideration and iteration resulting in a finished product.

17:53

The other is about in the- moment token prediction resulting in an output that is ephemeral and disposable.

17:59

Both are important and creative.

17:59

But the downsides of that creativity, unfamiliarity and edge cases versus hallucination and false confidence are themselves diametrically opposed.

18:09

Apple's historical strengths have always been rooting and designing for finality.

18:13

In my first year of strategy, I did a SWAT analysis.

18:15

Let's give it up for SWAT analysis of the big tech companies and said about Apple and and I I think we've talked about this a bunch on the show of like generative AI is inherently imperfect.

18:27

Apple is about pixel perfection.

18:27

Uh so uh Apple's product development process is wonderful for developing finished products, but that same process doesn't work nearly as well when it comes to building cloud services.

18:38

Cloud services are never done.

18:40

They are best developed by starting with an MVP and then iterating based on usage.

18:43

This is precisely opposite of what it takes to design a piece of hardware and it's a big reason why Apple struggles so much with cloud services and why other services companies struggle with products.

18:54

The canonical example of this of course was when mobile mi was the mobile mi launch which was de delivered fully formed in which when faced with real world usage crashed and burned.

19:04

Apple's latest offerings are better but still suffer from too much internal development time per release.

19:08

This is a hard problem to fix because it touches the core of what makes Apple. I think it matters.

19:14

I I think it matters whether or not liquid glass is good because it will be a testament about the state of Apple strengths.

19:20

Uh the point of this article, however, is that WWC was a retreat to those strengths, which is good. This is a bull case.

19:25

They're not getting over their skis and and they will eventually I mean, if they're to win, probably defer to the other companies and play to their strengths and and and let let the other companies win in the places where they Tim just calling up Sam and saying, "Sam, I'm going to need 50 billion years for the Siri, it's yours. 50 billion billion. 50 billion.

19:49

You know, if you and Mossa could pull together the capital, we can make it happen.

19:53

I mean, I I keep thinking about Siri and I I I keep running through like what would it have taken to to just to just replace Siri with a frontier level, you know, simple response model, not even the reasoning stuff, just GPT40 level, you know, you ask it a question and it and it and it and it reads you like a basic response and not lose the other Siri functionality.

20:18

And I think that it need they need to kind of flip the paradigm because right now Siri is only it's basically all tool use. It's basically a router.

20:27

So it takes in uh you know you ask Siri uh what what's the weather going to be like tomorrow and it knows that you just and all it's doing is picking out keywords weather and it goes to the weather API internally and then tomorrow and it feeds that in and then it delivers that back.

20:45

like like uh chat GPT kind of flips that around by having the default interaction be much more generalizable and it can return kind of any result.

20:53

It can return a paragraph, it can tell you about a historical event or just talk to you and then if it needs to use a tool like web search to get you the weather for tomorrow, then it goes and calls that.

21:05

And so you need to kind of flip that around.

21:06

around. I was wondering about like like why hasn't uh like what what if I if you if you rolled back the clock and you were like okay Apple just wants to be in the game what would it take to launch a V2 of Siri and I was like well okay if they if they try to partner with someone under the hood without like they don't

21:26

even have the option of just saying we are going to partner with anthropic under the hood and it's going to be and it's going to be basically white labelled and no one will ever find out because there are just too many leakers like it will find out immediately and so Mark German will have the story immediately and everyone will know. So

21:37

So they won't be able to say like this is magically ours when really it's someone else's even if they're paying them to be and there's ton tons of NDAs like like they do with cloud services, right?

21:45

they do with cloud services, right? I don't actually know who's under the I think they I I I think they do a lot of that and I'm sure it's and then I think a lot of it comes down to the privacy angle is that they want to make certain claims about privacy and ESG and net

22:00

zero and stuff and so if they were to just white label another company that didn't have the same reputation in privacy or or environmentalism like people would just say wait wait wait but like Anthropic isn't isn't known for their privacy rules as much as possible so maybe they're training on my theory

22:17

results now and that's a whole that's a whole thing and they have to you know build up Anthropic brand to have the brand of Apple which is just I'm sure Anthropic is doing great but they're not known like Apple is in terms of how seriously they they take it and then in terms of uh in terms of acquisition

22:32

obviously there's all the antitrust stuff uh we'll get into this with a scale AI deal but uh every major hyperscaler except for Apple now has basically done one of these like interesting aqua hires of a foundation model lab to kind of juice up their AI efforts and uh and and it's kind of been a mixed bag. Maybe we see one from

22:49

Maybe we see one from Apple.

22:51

They certainly have the cash, but uh it would be a very very different it would be a departure from their current strategy.

22:56

Anyway, let's go to uh John Gruber over at Daring Fireball with his review of Liquid Glass.

23:02

He says, "I've got iOS 26 installed on a spare phone already." Oh, no.

23:10

He didn't even use the real phone.

23:13

Tyler, mistake number one.

23:13

never on your main phone. How's it going so far? Well, okay.

23:19

So, so I'm I'm going to download it. It's 19 GB. Okay.

23:20

So, my phone is not, you know, I only have 64 GB on my phone, so I'm going to I got to do a um you know, delete everything.

23:28

Yeah, I'm going to delete everything. Okay. Yeah. Yeah. Yeah.

23:31

So, you delete just go to your photos app, uh select all the images, delete them all, and then clear the trash and you'll make more memories.

23:39

Like memory, you could always make you're making more memories all the time.

23:41

Clear out clear out those images.

23:44

And um yeah, good luck if you on a more serious note, if you need um we'll cover your your sort of Apple iCloud plan if you need to get those images in the cloud so you can get Yeah, if you need if you need a backup, feel free to expense it on your ramp card.

23:56

Yeah, put it on the ramp.

23:58

Um so, uh Gruber says, "I like the new UI a lot.

24:01

In addition to just looking just plain looking cool, Apple has tackled a lot of long-standing minor irritants.

24:08

For example, the iOS contextual menu for text selections, the one with cut, copy, paste.

24:14

For years, there uh for years now, there have been a lot of other useful commands in there, including share at the very end.

24:20

But to get to the extra commands, you had to tediously swipe, swipe, swipe.

24:24

Now, with one tap, you can expand the whole thing into a vertical menu. Elegant. And I agree.

24:30

I noticed that that was getting like it was originally it was just like just copy, just just cut and paste. And it was pretty easy.

24:35

And then they added if you wanted to bold or italics, you had to swipe over and then click on that and then go to text effects.

24:40

And there were like seven different things eventually. Yeah, good good move.

24:43

Minor update, but important.

24:46

And this is what this is.

24:48

This is the polish that Apple's so good at.

24:49

And then he says, uh, there's some stuff in Mac O mass Mac OS 26 Tahoe.

24:54

I already don't like like putting needless icons next to almost every single menu item.

24:59

But overall, my first impression of liquid glass on Mac OS is good, too. It's fun.

25:04

And lots of little details are nice, joyful, and useful in an old school Mac. Mac OS Tahoe.

25:11

You'll love Mac OS Cosgrove. I'll just say that.

25:14

It's just gonna be a banger.

25:15

It's gonna be the best ever.

25:15

Uh there's an interesting article in here that Ben Thompson linked to by Sebastian Dewith uh about physicality, the new age of UI.

25:25

He actually posted this back on June 3rd before Apple refreshed this.

25:30

So, there's a lot of Oh, do we have some breaking news?

25:32

I just I just printed this out because So, this was a good post from Signal.

25:36

He says, "Watching this WWDC."

25:38

Thank you, uh, Signal for the uh, for the content, and I'm just happy to be back printing. It's amazing.

25:45

It's It's I don't know how we went a few months without it.

25:47

So, he says, "Watching this WWC felt like watching a dinosaur try to do ballet.

25:54

Technically and aesthetically competent, but spiritually spiritually lost."

25:55

They talked about Apple intelligence like they just discovered the concept throughout the presentation.

26:01

There was zero ecosystem thinking and no real attempt to rethink a single interaction model.

26:07

More importantly, there was zero sense of how to be relevant in a world where interfaces may disappear, apps get abstracted, and AI is the OS.

26:13

Apple still thinks in icons and widgets while the world is moving towards awareness, intent, and delegation.

26:20

It'll be interesting to see how much of a penalty they will pay for missing this boat.

26:24

Um, uh, another negative post.

26:28

Now, Signal did have a couple other posts that were more positive talking about good stuff.

26:34

No, and I think I think this is generally uh why I'm excited about Johnny and Sam's uh hardware project is it's an opportunity to rethink the device from the ground up with AI at the heart versus Apple which I think going back to uh you know Ben Thompson's position is smart to play their own game right now and understand that they do have the option of oxy auctioning the the sort of uh Siri out to the highest bidder at some point.

27:02

Yeah, I mean, Alex Heath, who we had on the show yesterday, had a good post who said, uh, this is so very clearly designed for an interface that sits on top of the real world, not a phone, something you would need for AR glasses.

27:14

And so, uh, this idea that it's a little awkward now when you see these images of these glass over the background of your phone display, it can look a little too transparent.

27:25

The the contrast ratios are all off.

27:28

Um, but if you think about if they're really going all in on AR, VR, and they want to project these screens over the real world long term, setting themselves up to really dominate there and not need to do another refresh. Yeah. Could be big. Could be big.

27:47

Anyway, Mark, spent some time. Yeah. With Trump. Yeah.

27:50

Trump is known for playing 4D chess.

27:53

Maybe Tim is playing a little 4D chess with liquid glass.

27:59

screen is going to be everything's going to be a screen.

28:00

We're just going to put They have they have a patent for a glass iPhone that that you can see through or something like that or or something that actually um would would would appear more like glass or appear transparent.

28:14

And a lot of the transparent I feel like a lot of the transparent technologies it's like the closest we're going to get to just true holograms is if you have a variety of devices that are that are projecting holograms into glass sheets.

28:27

And so maybe it doesn't start with your phone immediately because the battery needs to be right there. That needs to be solid.

28:31

But if you think about a display and you're projecting on that and doing kind of the the same wave guides that are happening in uh reflected augmented reality glasses, uh you could do that on a monitor or something like that.

28:42

And so that could be very cool.

28:43

Uh Mark German had a more positive take on WWDC.

28:45

says, "Excellent WWDC at cohesive story, deep integration and continuity across the devices, zero false promises, impressive new UI, and significant new productivity features on the Mac and iPad, but the lack of any real new AI features despite that being my expectation is startling."

29:02

And so people were expecting, you know, maybe there will be a new Siri, maybe they will move the ball down the field in AI, and they did not.

29:11

Um, Ben Hilac, of course, taking credit for it as always.

29:17

You know him from taking credit for the Jaguar rebrand.

29:18

Now he says, "So excited to see my my uh to finally see my work from Apple ship.

29:23

I was the head of design for the WWDC app notifications."

29:28

There's still a work in progress.

29:28

We've only had the last year to work on them. Stay tuned.

29:31

So, was this was this uh is this fake or is this real?

29:35

I think this is the brightness adjusted.

29:37

I think that they I think that whoever shared this image uh turned up the brightness or brought up the brought up the lows uh de basically decreased the contrast in the in the photos app like uh to make it look worse than than it actually would.

29:52

Uh but I mean even it doesn't even matter because even if this is the way it looks, this isn't the way it will look when it will ship to to to people because it's obvious and and and Apple doesn't make these like obvious mistakes like this, especially when it comes to design.

30:03

design. um they they might do something that is like rough in the short term but better in the long term like what I think is happening with the photos app where in the photos app they are understanding that in the future you won't want to scroll at all you will just search and search will be so powerful because every photo in video

30:22

will be tagged so thoroughly from AI and it will understand the context so much that you will just ask it to pull up a photo and it will do it immediately the problem is that right now people a aren't they switch that UX paradigm to actually go search first and second um and and and second just the tagging is not that good. Like I had a video clip

30:40

Like I had a video clip of Arnold Schwarzenegger from a movie on my phone.

30:44

I wanted to pull it up and so I searched like Arnold uh Arnold video and it couldn't find it because the clip that I had started with a black frame and clearly it's only indexing like the first frame and so if if you have like a fade in to a picture of your dog it won't get tagged. Something like that.

31:00

I don't know if that's exactly what's happening.

31:02

use the text search in photos quite a bit. Yep.

31:05

I I find it like searching Kugan if there's some document that has. Oh, totally.

31:10

The text search is fantastic.

31:11

And even even things like objects like I I the picture of a vending machine, you type in vending machine, it it'll do a pretty good job.

31:20

Sometimes it'll miss it though.

31:20

But that these these like generative AI things, they get to 99.

31:24

9% accuracy pretty quickly.

31:26

Apple's just a little bit behind on them, I think.

31:27

Anyway, if you're trying to upgrade your design chops, head over to figma. com.

31:31

Think bigger, build faster.

31:33

Figma helps design and development teams build great products together.

31:37

Uh, we'll go to on Figma.

31:39

Now, we'll go to we'll go to Willm.

31:41

He uh gives his review of Apple's liquid glass clearly hints at a clear interface.

31:46

AR glasses and unifies OS beyond devices.

31:48

Like iOS 7, I would be shocked if this version of Liquid Glass ships to everyone later this year.

31:53

Too many accessibility features for a company that pioneered it.

31:57

Unfortunately, this means it's going to be muddy slashblurry.

31:59

UI design feel used to be about function. This is decoration. Late empire feeling.

32:03

Uh, hate the trend of floating menus that seems to be happening everywhere.

32:08

It puts useless noise on the edges of the screen.

32:11

Ultimately, little of this matters when you can now just talk to the computer. Everything is computer. Anyway, um, interesting.

32:17

There's an interesting deep dive from uh, this Sebastian day with talking about some of the history here.

32:24

Speaking of iOS 7, uh he said, "On June 10th, Apple showed off what," this was in the spring of 2013.

32:32

June 10th, Apple showed off what would be the greatest paradigm shift in user interface design ever, iOS 7.

32:36

I remember exactly where I was and how I felt. It was a shock.

32:41

I love a designer who's just so in the weeds, they remember where they were when iOS 7 dropped. Had to be there.

32:47

Uh if there is indeed a big redesign happening this year, it'll be consequential and impactful in many ways that will dwarf the iOS over iOS 7 overhaul for a multitude of reasons.

32:55

The redesign is rumored to be comprehensive, a restyling of iOS, Mac OS, iPad OS, TV OS, Watch OS, and Vision OS in the intervening years between iOS's 7 iOS 7's announcement.

33:07

And today, iPhones have gone from simply a popular device to the single most important object in people's lives. So true.

33:13

The design of iOS affected and inspired most things around from the web from web to graphic design to any other computer interface.

33:23

That's why I figured I'd take this moment of obscurity this precious moment in time where its changes are still shrouded in fog to savor something wholesome naive writer of where things are going so I can let my imagination run wild.

33:36

What would I do if I were Apple's design team?

33:38

What changes would I like to see and what what do I think is likely?

33:41

And then he breaks it down the shaded age.

33:43

He goes back to the skuorphic era.

33:44

iOS started out as Can we pull up this?

33:47

iOS started out as the iPhone OS, an entirely new operating system that had very similar styling uh to the design language of the MacOSS Tiger dashboard feature. Yeah, I remember this.

34:00

You could just put the widgets anywhere. It was very messy.

34:01

All the sticky This was so fun as a kid. Yeah.

34:06

Messing around with all the different widgets. All the widgets.

34:07

And then you discovering discovering was great widget.

34:11

I I I couldn't I I legitimately felt like a kid in a candy store with widgets.

34:16

It was It was a beautiful time.

34:18

So, he says the the icon layout on iPhone OS1, it wasn't even called iOS then.

34:23

It was just iPhone OS, uh was a clear skuomorph, skuorphism was the was the buzz word at the time.

34:29

You might have heard that word being thrown around.

34:32

It might surprise you that it doesn't mean it had lots of visual effects like gradients, gloss, and shadows.

34:36

It actually means to that to make it easier for users to transition from something they were used to.

34:41

In this case, phones typically being slabs with a grid of buttons on them to what they had become. Phones were all screen.

34:49

So they could show any kind of button or interface imaginable.

34:51

And yes, there was a whole lot of visual effects in the user interfaces from iPhone OS 1 to iOS 6.

34:58

In this age, we saw everything from detailed gradients and shadows and simple interface elements to realistically rendered realtore tape decks and microphones for audio apps.

35:06

I remember this the realtore tape deck in the voice recorder.

35:11

Pretty pretty remarkable.

35:13

Uh and like when when the directions would actually be like a like a physical sign that you would see on a highway.

35:20

It was it was such a cool design language.

35:22

I mean there's it feels so not Apple now that they've spent 10 or 15 years post skuorphism but it was definitely unique at the time.

35:30

Having actually worked on some of the more fun manifestations of it during my time working at Apple I can tell you from experience that the work we did in this era was heavily grounded in creating familiarity through thoughtful extensive visual effects.

35:44

We spent a lot of time in Photoshop drawing realistically shaded buttons, virtual wood, leather, and more materials.

35:50

That became known as skumorphic design, which I find a bit of a misnomer, but the general idea stands.

35:59

Of course, the metal of the microphone was not in fact metal.

36:00

It didn't reflect anything like metal objects do.

36:03

It never behaved like the object it mimicked.

36:05

It was just an effect, a purely visual lur lacquer to help users understand the voice that the voice memos app worked like an microphone.

36:14

The entire interface worked like this so as to be approachable as possible.

36:19

Notably, this philosophy extended to even the smallest elements of the UI.

36:24

Buttons were styled to visually resemble a button by being convex and recessed or raised.

36:28

Disabled items often had reduced treatments to make them look less interactive.

36:33

All of this was made to work with lots of static bit mapap images.

36:37

The first signs of something more dramatic did begin to show on iPad.

36:41

Some metal slider slider sheen could respond to the devices's orientation.

36:46

So as you uh deleting a note or email did not simply make it vanish off the screen, but pulled it into a recycling bin that went as far as to open its lid and close as the document got sucked in.

36:57

I remember there was one that would like shred things when you deleted it.

37:00

They had a bunch of these fun ones.

37:02

And you can imagine that designers in that era being like, I'm uh today I'm moving on from Apple, you know, I was the designer that made the lid open and the thing swoosh into the can.

37:15

It must have been so delightful to just be a designer and just like focus on just that one interaction for like weeks, you know?

37:21

Yeah, that that became a critique of uh Silicon Valley was just like you're working on something like the idea that like something like this doesn't matter in in the grand scheme of things.

37:34

But beautiful things matter. They do. They do.

37:36

And even a feature like this, especially in the notes app of of an iPhone, was something that was being used millions and millions of times a day and and is worthwhile to make it beautiful.

37:46

And so there was push back when they went to flat design.

37:48

And the flat age started in iOS 7, introduced an entirely new design language for iOS.

37:53

Much uh much was written on it at the time, and as with any dramatic change, the emotions in the community ran quite high.

38:00

I'll leave my own opinions out of it mostly.

38:02

But whichever way you feel about it, you can't deny it was a fundamental rethinking of the visual treatment of iOS.

38:08

iOS 7 largely did away with the visual effects for suggesting interactivity.

38:12

It went back to quite possibly the most primitive method of suggesting interactivity on a computer.

38:18

Some buttons were nothing more than blue text on white background like the inbox button.

38:23

The home screen, once a clear reference to the buttons on phones of yestery year, was now much more flat looking.

38:30

One part owing to simpler visual treatment, but also a distinct lack of shadows. It is.

38:34

It is hard to look at this after looking at the at the last era.

38:40

Morphic error was was amazing. Goed. It was amazing. It was amazing.

38:45

Like I see why they had to move on in some ways because it was just like the the the the previous era felt, you know, like it started to feel dated. Yeah.

38:52

It felt like it feels vint it looks vintage today. Totally.

38:57

I'm sure the kids today will like jailbreak their iPhones back to to looking Yeah.

39:01

I mean, I saw I saw a a comparison of the of the original photos app, which which looked like a camera lens, and then the the flat design camera app had just a camera icon that was completely flat.

39:14

And now we're back to a camera lens in the new era.

39:20

And so, some of that some of that skumorphism seems to be coming back with the glass redesign, liquid glass redesign, but uh not fully.

39:25

You know, we're kind of splitting the difference.

39:29

We're going in a different direction.

39:29

I just looked up, do people still jailbreak iPhones? Yeah.

39:31

And uh Reddit says it's still possible.

39:35

The big thing is there's not much need for it.

39:37

A lot of the things jailbreaking was for have been implemented to iOS. Yeah.

39:40

Because the app store is so robust. Yeah.

39:42

So you can get you can get an app there's an app for that now.

39:46

There didn't used to be an app for it.

39:47

There were many many many many apps that were not available and on the first iPhone there was not even an app store.

39:53

So uh but why did shadows have to go?

39:55

They had they they had an important function in defining depth depth in the interface.

40:00

After all, looking at the screenshot above actually does it no justice.

40:04

The the new iOS 7 home screen was anything but flat.

40:06

The reason was that the shadows were static.

40:11

iOS 7 embraced the notion of a distinct visual layers and using adaptive or dynamic effects to distinguish depth and separation.

40:17

Why render flat highlights and shadows that are unresponsive to the actual environment of the user when you can separate the icons by rendering them on a separate plane from the background?

40:27

Parallax made the icons float distinctly above the wallpaper.

40:29

The notification center sheet could simply be a frosted plane pane above the content which blurred its background for context.

40:38

Johnny IV spoke proudly at the iOS 7 introduction on how quote the simple act of setting a different wallpaper affected the appearance of many things.

40:47

this was a very new thing and so they're not losing the depth.

40:50

They still they're bringing that depth and they're actually making the depth more more complicated with the liquid glass feature.

40:55

And some people are frustrated by that and but one thing that they're that they're highlighting is that it's intense from a computational perspective.

41:02

Everyone was saying like rendering all these new features is definitely going to hurt your battery life because it's so much more.

41:08

Although Apple is fantastic at integration and they're fantastic at this type of hardware and software integration and this these types of renderings, they will probably be very quick.

41:17

Uh and so I wouldn't I wouldn't expect a disaster, but I would I would I would expect uh a little bit more of a load just from the the graphic layer, although it will be heavily optimized.

41:27

Um also a new thing in the interface was that the UI Chrome was able to have the same dynamics.

41:33

Things like the header and keyboard would show some of the content they obscured shining the through as if it fashioned as if fashioned out of frosted glass.

41:41

While it was arguably an overcorrection in some places, iOS 7's radical changes were here to stay with some of its dynamic effects getting greatly reduced.

41:51

Parallax is now barely noticeable.

41:51

Over time, its UI regained a lot more static effects.

41:57

I I wonder how much parallax there is.

41:59

I don't really notice any right now.

42:01

I mean, I guess when you swipe around, you can kind of tell that they're on a different plane, but I I might have it turned off. I don't even know.

42:07

Um, more interface elements started to blend with the content through different types of blur, like the new progressive blur and the button shapes were slowly starting to make a comeback.

42:16

It settled into a stable state, but it was also somewhat stagnant.

42:21

For bigger changes, there would have to be a rethink. What would come next?

42:24

Couldn't simply be a static bit map again.

42:26

It would have to continue the trend of increasingly adaptive interfaces.

42:29

So he goes on to talk about um the age of physicality and vision OS and kind of where Apple's going and predicts a lot of of of what wound up happening.

42:39

So Ben Thompson to go back to him, he talks about Apple's retreat to empowering developers and partners.

42:44

This was your point about maybe Apple will be auctioning some stuff off.

42:48

We'll see how their service revenue grows over the next few years.

42:53

Um but first let's tell you about Vanta.

42:55

Automate compliance, manage risk, improve trust continuously.

42:58

Advantage Trust Management Platform takes the manual work out of your security and compliance process and replaces it with continuous automation whether you're pursuing your first framework or managing a complex program.

43:08

It's like a it's like a AI golden retriever for mitigating risk and automating compliance.

43:13

I mean it's it's literally a golden retriever turned into software. It's fantastic.

43:18

What the golden retriever does for your yard. Yes.

43:21

Bant does for your business. Yes. Yeah.

43:23

It's like having a golden retriever in the office.

43:24

Like you just feel safer. You you do. You do.

43:26

and you are more comp and you are safer.

43:27

Uh so uh Ben Thompson writes about Apple's retreat to empowering developers and partners.

43:34

Says that's not to say there weren't some notable AI announcement in announcements in Apple's keynote.

43:38

First Apple announced the foundation models framework.

43:43

Uh this is a quote from uh the Apple team.

43:45

This year we're doing something new and we think it's going to be pretty big.

43:49

We're opening up access for any app to tap directly into the ondevice large language model at the core of Apple intelligence with a new foundation models framework.

43:56

This was what I was asking Alex about Alex Heath from the Verge.

44:00

The question of hey there even if even if the models aren't frontier just the fact they're happening on device the speed is very important for a lot of these models being able to use a model without a connection to the internet.

44:14

people are still they're still missing internet on planes occasionally or or or they have patchy service.

44:20

Building an app that takes advantage of that and and opening that up to the developer ecosystem where you can get really creative and kind of start finding those like niche cases of where AI can help for certain things.

44:29

You know, we we we need the beer app, the I beer app of the AI era. It's coming.

44:36

We've been this development.

44:36

For example, if you're getting ready for an exam, an app like Cahoot can create a personalized quiz from your notes to make studying more engaging.

44:44

And because it uses ondevice models, this happens without cloud API costs.

44:48

So, if you're this like kid developer who doesn't who maybe doesn't have an economic model yet, you can build an AI product that only uses ondevice compute and you have zero you have zero uh like cloud costs, which is amazing.

45:04

I mean, of course, there's ways to charge way less attention than you should have. Yeah.

45:07

I mean, everyone was expecting it and it's great, but um it is very cool in terms of just you can now vibe code an iOS app that has some sort of AI functionality.

45:19

It's not going to be incredible.

45:19

It's not going to be frontier, but you can get something that's served into the store that only uses Apple's APIs and creates an experience that is that that is zero ongoing cost.

45:29

It's entirely hosted by Apple and runs on the device, which is amazing.

45:33

I I I think that that's very very exciting to see where people go with this.

45:36

Um they give another example of uh if you're camping off-rid pouring over the hikes you downloaded to all trails, just describe what mood you're in uh the mood you're in and all trails can use the ondevice models to suggest the best option.

45:50

So um doing doing things like recommendation algorithms on device much much faster, much easier.

45:57

Uh we couldn't be more excited about how developers can build on Apple intelligence.

46:00

And so it's important not to oversell the capabilities of Apple's ondevice AI models.

46:05

Of course, developers who want to create something that is competitive with the output of something like Chat GPT will need to use cloud-based AI APIs.

46:13

Of course, you got to burn the you got to burn up the H200s to get the really good stuff.

46:16

But um you know, it's like mid midw midwit intelligence on too cheap to meter.

46:22

Not quite not quite super intelligence too cheap to meter, but like you know it's a midway that's helpful.

46:28

Two digit IQ too cheap to meter. Too cheap. Really free. It's bullish. It's on the device.

46:33

Uh the real that reality however applies um to Apple as well.

46:39

Part of the folly of the initial Apple intelligence approach is that Apple was promising to deliver beyond state-of-the-art capabilities on the cheap using its users processors and power.

46:48

What is compelling about the foundation models framework is how it empowers small developers to experiment with ondevice AI for free.

46:54

This is what I was talking about.

46:55

An app that wouldn't have AI at all for cost reasons now can.

47:00

And if that output isn't competitive with cloud AI, then that's the developers problem, not Apple's.

47:04

At the same time, by enabling developers to experiment, Apple is the big beneficiary of those that discover how to do something that is only possible once you have an Apple device.

47:15

Second, Apple deeper deep deepened its relation its reliance on open AI incorporating chat GPT's image generation capability capabilities into image playground and adding chat GPT analysis to visual intelligence. That's cool.

47:27

There is still no sign of the long rumor Gemini integration or the ability to switch out chat GPT for the AI provider of your choice, but the general trend toward relying on partners who are actually good at building AI is a smart move.

47:41

Third, Ben Thompson writes, "Apple is incorporating chatbt much more deeply into Xcode, its integrated development environment.

47:48

This is their VS Code competitor that you need to use to write Objective C apps for the uh for if you're building iPhone software uh for building apps for Apple platforms.

47:58

Uh developers can also plug in other models using a API keys.

48:01

using a API keys. Xcode still has a long way to go to catch up to I AI AI first idees like cursor but again partnering with a foundation model makers seems like a much smarter strategy than Apple trying to do everything itself these are to be sure obvious moves but that doesn't make them any less important both in terms of Apple's future and also

48:20

with regard to the theme of this article Apple's initial success with the Apple 2 was because of thirdparty developers and developers were critical to making the iPhone a sustainable success trusting developers and relying on partners may be a retreat from Apple's increasing insistence on doing everything itself, but is a much is a is very much a welcome one. And so, um, people are

48:36

And so, um, people are also, you know, he quotes Marquez Brownley here, the Windows Vista update with Aerog Glass was a huge part of my childhood.

48:47

So, I'm getting serious flashbacks.

48:48

It does have a little bit of like the Windows glass vibes.

48:50

The biggest part of WWC was about with liquid glass, which has drawn some compar unflattering comparisons to past Microsoft operating systems releases.

49:00

Again, I'll withhold judgment until it ships.

49:02

But there is another Microsoft OS comparison I've been thinking about recently.

49:07

To me, last year's Siri disaster was a lot like Windows 8.

49:11

Windows 8 was an attempt to micros to leverage Microsoft's large PC install base into a competitive position in touch-based devices. And it did not go well.

49:18

Consumers, particularly enterprises, hated the new UI, and developers weren't interested in the platform without users.

49:24

Microsoft was forced to retreat and eventually came out with Windows 10, which was much more in line with the traditional Windows releases.

49:31

Apple has clearly missed the boat on cutting edge AI, but what I'm open to is the argument that this was a ship the company was never meant to board, at least when it comes to products like Chat GPT.

49:40

Meanwhile, I've long been convinced that Apple has gone too far in its attempt to control everything, even tangentially related to its devices.

49:49

To that end, I understand why many people were underwhelmed by this WWDC, particular particularly in comparison to the AI extravaganza that was Google IO.

49:59

I think it was one of the more encouraging Apple keynotes in a long time.

50:04

And that's what Mark German said as well.

50:06

Apple is a company that went too far in many areas and needed to retreat.

50:10

Focusing on things only Apple can do is a good thing.

50:13

Empowering developers and depending on partners is a good thing.

50:17

giving even giving even the appearance of thoughtful thinking with regards to Apple App Store uh is a good thing.

50:24

Of course, we want and are excited by tech companies promising the future.

50:28

What is a prerequisite is delivering in the present and it's a sign of progress that Apple retreated to nothing more than that.

50:34

Let's hear for Ben Thompson. Another great article. Nailed it. Very, very good. Hall of Famer.

50:41

Anyway, future Hall of Famer.

50:41

If you're looking for the apple of sales tax, get on numeral. Numeral HQ. Sales tax on autopilot.

50:48

Spend less than five minutes per month on sales tax compliance.

50:51

It's AGI sales tax, baby. Get on numeral. Yes.

50:54

Now, so do Sarah Guo at Conviction, former uh former guest on the show, friend of the show, uh said that Apple transcription is still so bad, so so bad compared to what's available on the market, they should be embarrassed. Okay, so I agree.

51:11

I am now in the pattern of if I want to send you a long text with a lot of thoughts, I will go to chatbt.

51:16

I will click the dictation button.

51:19

I will talk to it and then I will copy and paste that into the iMessage window.

51:23

Do you instruct chat GPT to synthesize it and organize it or you just I just use it for the transcript?

51:30

I just use it for the transcription.

51:32

I open up the chat GPT app. I let it transcribe.

51:34

I don't even John hits me with one of those John hits me with one of those bubbles that's like this long.

51:39

You actually don't do that. I I don't really notice.

51:41

You don't notice that I that I do it.

51:44

But even if I'm just saying like, "Okay, I I I'm I'm walking around.

51:48

I can't really stop entirely."

51:49

Here's what Here's what we're hitting in the gym.

51:50

Uh you wake up you wake up at 5:00 a. m. first thing. Transcribe the workout.

51:54

Five for five, 225 bench press. Yeah.

51:56

Uh so basically, um I agree it's bad.

52:00

The question is why is it bad?

52:05

because there are so many companies out there that they could work with, partner with.

52:12

There's a million different ways to solve this problem. Why is it bad?

52:14

And I was thinking that maybe part of it is let's say they buy a company uh that has amazing transcription and it is discovered that that company trained on data that it didn't fully have access to. Interesting.

52:30

All of a sudden, instead of going after some startup with $100 million raised and 50 million in the bank and you're going to take them for all your for all they're worth, you're going after Apple. Yeah.

52:39

And you can maybe get a billion dollar settlement.

52:42

And so that's like a huge liability and it's also potentially a PR nightmare because a lot of Apple customers care about the the AI training.

52:48

Adobe's had to be very thoughtful about this in the sense that like they're like, "Hey, look, we will let you opt into letting letting us train our image our models on your images if you're on uh Behance or one of these other services."

53:03

Um, people don't like the idea of of training just happening on their hard work generally.

53:11

And so I think that there's some PR risk, there's some legal risk, but I agree that they need to figure it out.

53:17

way less risk if they're just leveraging a vendor that is giving them even that even that is like it's tough for Apple because if they if it's like oh well they're working with this vendor and the vendor is not above board okay well now they're they're linked in the yeah but

53:32

they should also be able to go to somebody like scaleai or mercur like hey we want to build a transcription product and we're just going to make it ourselves I mean they face they like they face they face backlash when Fox Con has bad working conditions, right? And so if they are partnering with

53:50

And so if they are partnering with another company and then there's some viral news story whether or not it's real that that those people but everything Apple does carries risk. Yeah.

54:01

Even if they have great intentions and I don't I agree.

54:03

They need to figure it out.

54:05

And this is something that that just feels it feels so easy to move the ball down the field because they already have a transcription product.

54:11

They just need let's just make it better.

54:12

They just need to make it better.

54:14

What are the ways in which we can make it better?

54:15

It's clearly not the modern transformer-based architecture.

54:16

Yes, they need to do a training run.

54:18

Yes, they need to build some GPU data centers for it.

54:22

Yes, they need new training data, but there has to be a way to do that in an environmentally friendly PR compliant like like do it do it the Apple way.

54:30

I'm fine with that, but like you got to do it because this is such a basic functionality of a phone now.

54:34

And the fact that I'm going from one app to the other just to you just in just because the Siri button isn't the transcription is just not good.

54:41

Um, and and and that would be such an easy thing to just say, "Hey, hey, we're we're state-of-the-art in this because this is something that is actually uh improves the daily experience of the of the of the phone user." For sure.

54:55

Uh, and same thing with so so backwards to have to go in another app just send a me transcribe a message.

55:03

I Yeah, I mean, I'm I'm fine with them not inventing like the newest paradigm of like deep research.

55:09

It's like that doesn't that product doesn't need to come from Apple. Yeah.

55:12

But we've had good dictation and transcription for years now and it's open source.

55:17

And it's not even it's not even that it's just like open source.

55:22

I'm sure they can't just like vend the open source model in because of the license and all.

55:25

I'm sure there's restrictions on that.

55:27

Like you're not just going to give Whisper to the biggest company.

55:30

We should have somebody that that's a a big dictation head and and have them apply to get a job. No, no, no.

55:38

just somebody just a fan go, you know, an Apple fan goes joins Apple purely to just, you know, beat the dictation drum internally because I feel like it just needs to be a handful of people. Yeah.

55:49

That uh that are really power users.

55:52

Anyway, I wanted to highlight this post from Pirate Wires.

55:56

Uh they did an interview on April 16th with David Hanimir Hansen.

55:58

Uh that's DHH of Rails fame.

56:01

Uh he also works with 37 signals with friend of the show Jason.

56:07

Uh screen recordings of Apple's new iOS 26 liquid glass software design appear to show a jumbled difficult to read apps and incoherent home screen app animations for a company that built its brand on seemingly impossible feats of technology.

56:20

Apple now finds itself stuck in a self-perpetuating cycle, falling behind in the AI race, struggling to attract talent needed to catch up, and fumbling product releases.

56:31

Uh, Pirate Wires writer Blake Dodge diagnosed the company's problems in a May interview with 37 Signals DHH.

56:37

Read the interview in full on the site. Link threaded.

56:39

I recommend you go read it. I won't read it here.

56:44

You have to go subscribe to Pirate Wires.

56:46

Also, it has a lot of bad words, but it does he he really let loose and I'm sure there's a lot of insided state of affairs at Apple. Yes.

56:55

not not quite uh not quite family friendly material, but uh if you're an adult, head over, hit the subscribe button, check it out, and read in full because there's a lot of insight there.

57:05

Um anyway, that is uh the WWE reset recap.

57:08

We have uh seven minutes until our first guest.

57:10

I thought we were going to do that in 15 minutes.

57:11

Wound up being a 55 53 minute segment. Love it. Nice.

57:16

Well, should we cover scale? Yep.

57:16

So, Meta is paying 15 billion.

57:20

I thought it was 14 15 something like that for a 49% stake in scale AI that pays out investors and employees.

57:28

CEO Alex Wang is leaving to join Meta and head up a super intelligence lab.

57:33

Feels like those licensed and acquired deals at Character AI inflection and adept to avoid regulatory scrutiny says TA who's been on the show.

57:42

Um this is from the information.

57:44

Uh you got to hit the size gong 15 times for Alex Wang.

57:46

Let's hear it for a fantastic I just pulled out my uh your headphones.

57:51

I'm gonna need to let you hit the size. I will hit the gong. Where's the gong mallet? Oh, it's over there. Where's the mallet? It's over there. Here we go.

58:06

[Music] Technical difficulties.

58:08

Lots of difficulties, but we got we got it done.

58:12

Um, congratulations hits, John.

58:12

But that wasn't 15 hits, but it was one big one.

58:17

Uh, and uh, and it's very exciting.

58:17

I I'm I'm a big fan of Alex Wang. I've met him.

58:21

I interviewed him on stage at an event about a year ago.

58:23

And, uh, he has a ton of really deep insight into artificial intelligence, and I'm sure he's going to be an absolute beast in the board.

58:31

Do hopefully get a board seat. A boardroom general.

58:33

He's a boardroom general. Um, yeah.

58:35

So, so, so it's funny when when these the these kind of deals uh are relatively recent phenomena. Yes.

58:43

We saw this with Character AI to Google.

58:45

uh to Google, Adept to Amazon, Inflection to Microsoft, and now Scale AI to Meta.

58:51

And the interesting thing here, I was talking with an early scale AI investor this morning, and they just still didn't, you know, I think the deal is still in the works.

59:00

They didn't have full um insight into how exactly it was structured.

59:05

The question is Meta is paying $15 billion for 49% of scale AI and scale AI through that is losing their CEO. Sure. To Meta. Yep.

59:15

Now, Scale AI is a very big business. Yep.

59:22

They have a ton of customers uh that that I imagine are are going to want to continue to work with Scale AI.

59:26

The question becomes, what happens to the actual EV of scale AI in a scenario where half of it is owned by a hyperscaler who has very different incentive structure than a traditional acquirer.

59:40

The positive here is that didn't you talk to somebody at at character or adept or inflection?

59:44

character or adept or inflection? You talked to one of somebody who was I talked to I talked to what happened with character is basically like the cap table was effectively wiped out and reset and to my not wiped out cashed out to the very high valuation every ended up in a situation where they had this massive balance sheet no investors

1:00:04

like no preferred shareholders was effectively uh is effectively to my knowledge community or or sorry employeeowned and I don't think that's what's happening here But it is seemingly clear that um the uh founders, the team and the investors in Scale AI will be getting um paid out I would imagine proada based on that $15 billion um mark. And the and the thing that's

1:00:30

And the and the thing that's wild here is I mean I so it's an up round for everyone.

1:00:33

Everyone gets everyone gets cashed out gets a ton of money.

1:00:37

Alex gets to go work in like a hyperscaler in super intelligence and actually like take a run at some really serious like high technology. Yeah.

1:00:43

The thing that was ultimately surprising so Scale AI has more than $900 million in cash on its balance sheet at the end of last year according to financial information shared with prospective investors.

1:00:55

Uh they've raised more than 1.

1:00:56

5 billion from investors.

1:00:56

So they only burned 400 five 600 million of that like they kept more than half of it.

1:01:03

Uh the company made uh 870 million in revenue last year and expected more than two billion this year and uh it lost about 150 million.

1:01:13

So I mean doing doing pretty well.

1:01:15

I mean there is a world where where like scale AI as a company even though they're not wholly owned by Meta, they are independent and they have $900 million war chest and they can go build a great business and do a bunch of stuff there and then uh that the relationship with Meta can be a fantastic growth engine.

1:01:30

Yeah, this the the only reason this was surprising to me, well, I guess one, it's um scale AI was, you know, if you're if you're trying to build a a new research lab, they're probably going to need to still acquire a lot of other top talent.

1:01:46

You could imagine Meta going and and trying to bring in into you know, people from Anthropic or OpenAI into this new organization.

1:01:54

Um, but uh it felt like scale.

1:01:58

I I I do wonder if if Scale, you know, Scale's team could go back and and see Circle's IPO and the success of that. Yeah.

1:02:07

If they would have still done this done this deal because Scale AI could have ripped in the public markets. Yeah.

1:02:13

Circle IPO showed that the public markets are very receptive to pure play technology bets that that have great narrative around them. Yes.

1:02:23

and and I could easily seeing what circle has traded at I could see scale trading well beyond um uh you know the this valuation they're getting from meta. I agree with you.

1:02:36

The question is how does the liquidity picture what does the liquidity picture look like in that scenario?

1:02:42

They wouldn't the in insiders wouldn't have been able to unload 15 billion 14 15 billion like does that does that actually play out?

1:02:49

Um because yes, yes, the the stock could have traded up to a 100red billion market cap, but can you actually if you're an investor, can you actually get liquidity without crashing the stock if you're putting 15 billion of downward pressure?

1:03:03

Uh so yeah, it's a lot big question.

1:03:04

We'll have to ultimately huge pickup for for Zuck.

1:03:07

I think Alex, you know, will will continue to be um you know, execute uh very well and I can imagine he'll be a huge part of recruiting. Yeah.

1:03:15

Uh he's done a fantastic job.

1:03:18

He's like been everything.

1:03:20

He's been on everything from like the Theo Vaughn podcast to testifying in front of Capitol Hill and lawmakers. He's got a ton of range.

1:03:28

He's very able to storytell and do creative deals which increasingly are extremely valuable in the world where the AI paradigms like the secrets are known.

1:03:39

It's about, okay, how can you actually marshall the capital and and the will to build the hypers scale data center to actually go and and get Jensen to fork over 100,000 H200s on on schedule?

1:03:47

Um, I'm sure there's a ton of different uh things in the works.

1:03:53

Yeah, it's interesting for Meta, too.

1:03:54

Even if they're able to leverage the scale team uh to simply get better at ads, they can make back the the the 15 billion. Uh oh, yeah.

1:04:06

in there's a ton of different ways this works out.

1:04:08

Uh and I mean they clearly need a lot more reinforcement learning training data for to improve llama 4 because they need a they need a reasoning model um if they're going to stay in the game.

1:04:20

That's clearly the next paradigm and I mean like a big part of what we learned about uh from semi- analysis this week was that verifiable rewards are really important in reinforcement learning.

1:04:32

Scale AI pioneered that humanity's last exam.

1:04:34

they've been in like the eval game defining the rewards that you would work against in the reinforcement learning paradigm.

1:04:40

And so, uh, there's a whole bunch of ways that that plugging Alex and the scale team in makes a ton of sense.

1:04:46

Anyway, really quickly, let me tell you about Adio customer relationship ma magic.

1:04:50

Adio is the AI native CRM that builds, scales, and grows your company to the next level. Let's give it up. Go check it out.

1:04:57

And we have Let's give it up for ADO.

1:04:59

Red Red Point, our first guest, investors in audio. No, wait. Really? Yeah. What a coincidence.

1:05:05

One hand watches the other. Welcome to the show. How are you doing? Well, what's going on? Great, guys. Great to be on.

1:05:11

Huge fan of what you guys have built. So, this is exciting. Thanks so much.

1:05:14

Uh, would you mind kicking us off with a little bit of an introduction? For sure. My my name is Sa Lumar.

1:05:18

I'm a partner at Redpoint Ventures.

1:05:21

We're a venture capital firm in the Bay.

1:05:22

It's been around for over 25 years.

1:05:24

We've invested in companies like Netflix, OpenAI, uh, Stripe, but we're known for our infrastructure software investing.

1:05:32

So, companies like Stripe, Twilio, Hashi Corp, Cribble, Chain Guard, and yeah, that's been our bread and butter and and and walk us through what's going on today.

1:05:45

Yeah, so we're we're in San Francisco at AWS's Builder Loft.

1:05:47

We've partnered with NASDAQ to actually move the ex their exchange to SF.

1:05:52

So, in about 30 minutes, we're going to ring the bell.

1:05:57

Really about 150 people here. Yeah.

1:06:00

It's it's like it's like that Deliant tweet like move move Silicon Valley to Miami.

1:06:03

We just move Wall Street here. So, we're excited.

1:06:05

It's exciting day for us.

1:06:08

But yeah, this is our annual conference and we do it every year. That's amazing. But break down.

1:06:11

We got a hopefully you guys have we have a gong cam here.

1:06:15

Hopefully you guys have a bell cam set up, you know.

1:06:18

But um the gong might be better than the bell.

1:06:20

I think I mean yeah SF SF is very gongcoded. Yeah. Yeah.

1:06:25

Um well yeah I I want to know about the top themes uh uh for for the conference the top tracks the top discussion points what are people debating um for sure what uh uh take us from kind of uh where the discourse is and where the frontier of that discourse is going. For sure.

1:06:43

You know, we we created this whole initiative a few years ago to call out the importance of infrastructure software as standalone category.

1:06:50

It's it's it really is like the picks and shovels behind how software is consumed and delivered.

1:06:57

It's this invisible piece of software that we just take for granted.

1:07:01

Um when you when you buy something on Amazon, for example, there's some application that we open, but it's powered in the back by all of these dev tools and databases.

1:07:09

there's some global server taking in billions of bits of information and you need to secure it from all of these DOS attacks which happens millions of times a day and we just don't know about that.

1:07:20

So I guess across the whole application delivery life cycle there are just a ton of different infra tooling and it powers virtually everything we do.

1:07:28

So yeah we we take uh we we we do this conference every year to just shine a light on all the amazing innovation that's happening at the infrastructure layer.

1:07:39

So we we divide the world up into into four different subcategories.

1:07:43

Everything happening at the AI and model modeling layer, all of the data infrastructure tooling that needs to be built out around that, the cyber security vendors that need to protect that data and all of the developer tools that actually creates the software.

1:07:57

So we've been we've been doing it for uh this is our third year doing it and we also highlight basically the top 100 fastest growing private infrastructure companies.

1:08:08

we all get them in a room.

1:08:08

We have the C CEO of AWS, Matt Garmin, coming to chat today and the president of Gary of of YC, Gary Tan.

1:08:15

And so, yeah, it's a it's a fun day.

1:08:18

I have this I have this thesis I want to bounce off of you and get your feedback on.

1:08:23

It feels like DevTools infrastructure, it's less monopolistic.

1:08:28

It's And maybe that makes it easier for maybe not VCs to make money, but uh entrepreneurs to make money.

1:08:37

you just don't get steamrololled as much.

1:08:39

as much. Am I am I off there in in thinking that uh a lot of these dev tools markets are more oligopolistic by nature of the fact that hyperscalers are competitive and the different cloud platforms are competitive like what what is the current dynamic because I feel

1:08:58

like the narrative is always like someone comes out with some infrastructure or dev tool it's kind of a boring company it flies under the radar for six years and it gets and then oh it's worth a couple billion dollars and then it's worth like 2030 billion no one knows about Exactly. So, so, so we

1:09:09

So, so, so we break down like what structurally is going on there um why is it harder to build uh these crazy crazy monopolies and but and then is that narrative about like base hits being easier or unicorns being easier is that even real?

1:09:24

I actually know I I agree with that sentiment maybe a couple of years ago.

1:09:29

But if you look today, I mean look at cursor hit $500 million in ARR in in less than a year.

1:09:34

And I guess like dev tools, it's always been this like very sequent like if you think of DevOps, it's this very sequential process, right?

1:09:42

It's like you have if you have your engineers on one side, then you have your your S sur folks on the other and then there are there are tools for the the developers, there are tools for the incident response engineers and there are like these distinct stop gaps that exist across the life cycle, right? Yep.

1:09:58

But with these code generation tools like cursor and windsurf and copilot like they all started on the left and they started in the IDE where these developers are actually coding and but you can see the writing on the wall and where they're going.

1:10:13

So now you you're you're consuming and writing all these applications in the IDEs, but they're probably going to extend, right?

1:10:20

And they're going to start doing the code review stuff and then you're going to deploy the apps.

1:10:22

Like you can see it in Lovable, for example, with just like a simple query, you can go from that query to a full-blown production app that's live on a website.

1:10:30

So like before you needed like 10 different designers and engineers to do all of that, but now with just one tool, you can do that.

1:10:37

So I think I I think yes it's it's not been as monopolistic in the past but I think that world is changing and and like the clear horses right now in my opinion are cursor and anthropic in the coding world. Interesting.

1:10:51

And and so yeah I mean it's just crazy like two years ago like people were saying LLM all they could do is just spit out code like you couldn't actually write real software and impact software development.

1:11:02

Q two years later it I think there was this interesting stat like computer engineering grads face double the un unemployment rate of art history majors and it's it's it's just crazy seems crazy um h how do you compare and contrast the adoption of of uh AI versus traditional cloud?

1:11:24

I I know that you guys have done some some research around you know cloud adoption uh you know more than a decade at this point versus um even just the the the growth rate on on the token side. Yeah.

1:11:35

I mean it you know it's it's just incredible how how much faster the consumption is on the AI side.

1:11:44

on the AI side. I think a really good analogy or data point is if you look at the cost of EC2 like servers during the cloud the it got efficient like very very quickly and it allowed people to consume cloud software all across the board but when you look at the cost of

1:12:00

inference which I think is the equivalent to EC2 and cloud but inference for AI it's it's it's literally dropping like a 100 times faster than than the cost of EC2 but at the same time application patients are being built and consumed 10 times higher than it was during cloud. So it's like a thousandx

1:12:18

So it's like a thousandx more consumption at the end of the day.

1:12:22

So it's it's just it's just insane like what what's happening in the age of AI and and the markets itself like there's this massive services component that is going to be converted to product based software revenue because you can encapsulate all of that all of these workflows with software like LM are software at the end of the day and and you're you're taking these huge markets and you're making them available through software.

1:12:43

How are you thinking about competitive dynamics between sort of scaled infrastructure providers like data bricks and cloudflare and and companies in that category versus some of the upstart uh companies that are scaling rapidly but um you know still having to compete with these you know founder companies that are um you know basically uh they're not going to let uh they're not going to miss this sort of like platform shift. Yeah.

1:13:07

You know it's it's really interesting.

1:13:10

it's really interesting. I I think the existing infrastructure vendors they can actually embed the AI products in their suite like take like take vector databases for example which I think is is an incredible market still right and there's like all these use cases but is there a vector database equivalent of

1:13:26

data bricks yet like no actually what happened was that MongoDB extended vector search part of their as part of their suite so I think like but but like that's that's not to say like like for example like two years ago people would not have thought an ID like cursor would would be better than GitHub copilot. So

1:13:42

So I think there are pockets of the infrastructure market where sometimes the incumbents are going to win and they can just leverage their existing technology to extend their applications but then there are like AI native wedges like the IDE for example where there's tremendous opportunity for a couple of 22 year olds to come and create a 10 billion business in in two years. Yeah.

1:14:05

Let's stay on cursor windserf the new uh the new dev tools like IDE coding AI coding market.

1:14:11

Um what's I I'm I'm I've kind of been there's a little bit of a horse race going on.

1:14:17

You know, you're either a cursor guy or a wind surf guy or you're an investor in one.

1:14:20

Um, but as I talk to more and more of the founders, I just increasingly become convinced that this is such a growing market and it remains potentially oligopolistic that they might kind of all wind up winning in some way or at least returning investor capital and and making the founders uh fantastically wealthy and successful.

1:14:39

Um, how much of that narrative do you think is real?

1:14:41

Uh, we talked to uh Scott Woo over cognition.

1:14:46

We were like, "Oh, like uh OpenAI just launched Kodak like are you cooked?"

1:14:50

and he's like, "Well, we grew 40% last month."

1:14:52

And so it seemed like very much not so.

1:14:54

And we talked to another person who was saying that uh GitHub Copilot not the trendy tool at all at a $500 million run rate.

1:15:01

And so that in and of itself could be a public company I if it if it was spun out.

1:15:05

And so it feels like when when we're talking about doing something so net new, something so additive to companies workflows, there's just so much opportunity that it kind of just is like a rising tide lifts all boats.

1:15:19

But uh what do you think about that narrative generally?

1:15:22

Yeah, I mean if if you just look at the application with the strongest product market fit within the AI world, it's coding and and like the market itself, there are tens of millions of developers.

1:15:32

If you just assume moderate assumptions in what you pay them, it's like a $1.

1:15:35

6 trillion market in spent.

1:15:38

It's it's like it's absolutely massive.

1:15:40

It's like the mother of all markets.

1:15:42

And I think it's really interesting.

1:15:44

There there are companies going after certain pockets.

1:15:46

So you have the code the code generators living in your IDE and that's where the developers are today, right?

1:15:52

It's it's where the actual development happens.

1:15:55

So cursor it was just ma magic in a bottle.

1:15:58

It's tap tap tap and all of a sudden you have a full-blown production app and you save yourself countless hours in in in development.

1:16:07

Um, but when you when you can see where the world is moving, like all of these processes think about humans at the center, but it's like very very quickly we're think it's going to shift to having agents at the center.

1:16:21

And so companies like Cognition and Factory, they're not going to exist in your IDE.

1:16:26

Like you're just going to go tell it.

1:16:27

You're going to go tell an agent to go do something and it's going to come back and have a pull request and you're just going to approve.

1:16:32

So I think I think there will always be a need for software developers, but I think they're they're going to move increasingly from actually coding to being kind of these like orchestrators of of a product.

1:16:43

And I think like product managers, for example, are now enabled with these tools.

1:16:47

I think at the end of the day, like I don't I don't think it's going to Yes, there there's like some developers that might lose their jobs, but you're you're actually just making their their jobs a lot easier and there's just going to be a ton more software.

1:16:58

There's going to be more software.

1:17:00

If you're not Jevans paradox pled now, you never will lost.

1:17:06

reacting to the news today uh the scale uh AI meta deal.

1:17:09

How how do you expect the data labeling market to evolve now that now that in in in some ways one of the key players in that space is has other it will naturally have other priorities if you know half their their company is is owned by Meta who has um you know their their own goals around super intelligence. Yeah.

1:17:32

Look, if if you're the model providers, there are like two use cases that are just so clear that and and hair on fire.

1:17:39

One, that's like inference.

1:17:41

It's actually running these models. Two, it's data labeling.

1:17:43

How do you actually structure your data and clean your data and feed it into these models and such that you can actually advance uh the LLM?

1:17:52

And so, I think it's I think it's a brilliant acquisition.

1:17:54

And I think whatever the sticker price is, like it's we're we're going to look back, it's going to be like the Instagram deal.

1:18:00

Like you need accurate classified data to feed these large language models and for a variety of use cases.

1:18:08

There's so many data labeling businesses that we see like pockets in in hiring and and whatnot and and and coding and and like they're all screaming out of the gates like they go to like zero to 20 in like two months.

1:18:22

And so I think I I I think it it just makes a ton of sense.

1:18:24

And I I think it's I think it's a brilliant acquisition.

1:18:26

I want to get your reaction to WWDC.

1:18:28

Felt like Apple was kind of pulling back from some of the territory that they'd overexpanded into in artificial intelligence.

1:18:36

Obviously, it's a developer conference.

1:18:38

Do you think that there's opportunities for startups to uh build new companies even around servicing the nent AI for Apple environment?

1:18:50

You could imagine there is like there is no cursor for Xcode.

1:18:55

There's probably a way to solve that problem even just anthropic and their deal with Xcode. They're working on it. Yeah.

1:19:01

But but but there's probably some way to even advance that.

1:19:02

And then also just serving up models into you know iOS APIs that are like more tailored.

1:19:09

Like there's been a couple companies that developed backends that were specifically tuned for iOS apps in the past.

1:19:17

Some of those wound up getting sold.

1:19:19

So, how are you thinking about opportunities coming out of WDC or or just general reactions?

1:19:23

Maybe you don't even follow it at all.

1:19:25

You know, it's it's interesting when you look at when you look at like past platform shifts like the cloud, you you you first need like the workdays and service nows and Salesforcees running at massive scale like pushing the limits of of like cloud rails before you can before you can really understand what kind of innovation needs to happen at the infrastructure layer.

1:19:46

So, you know, our guess here with Apple and all of these apps that are built like you need the AI native versions of these apps that will start like hitting the limits of the underlying models before you can really understand.

1:19:59

So, I for sure it's going to happen but I think it's going to take some time.

1:20:02

Uh what is uh what's the discussion uh or what do you expect the discussion to be around agents?

1:20:07

There's great narratives around agents right now.

1:20:11

now. There's individual agent products that people use whether it's coding agents or or or sort of research agents but uh despite you know Salesforce you know marketing uh whatever their agent cloud agent force things like that it

1:20:27

doesn't feel like uh they maybe have broad adoption yet but a lot of promise so so how how do you think about kind of agent adoption um given uh you know there's people I think at the event from on the browser infrastructure side, agent, devops, all that kind of thing. Yeah, look, I mean, it's it's clear it's

1:20:44

Yeah, look, I mean, it's it's clear it's next paradigm.

1:20:46

I think we're just catching it in a point in time where they're they're stumbling agents, but like again, there are some clear use cases where it it's it's clearly working today.

1:20:55

Like if like cognitions agents, for example, there are low-level development tasks where like that is fully automated and the largest of companies know that, but like no one else really knows that yet.

1:21:05

And it's it's it's it's mind-blowing what's happening.

1:21:08

Same thing with customer support.

1:21:10

you have you have companies like Sierra and Decagon and that's just a use case that makes a ton of sense for agents to operate.

1:21:14

So I think as the agent infrastructure improves there are things like memory and context budgeting there all a lot of these like hairy infrastructure problems that need to be solved but ultimately also the agents are going to improve dramatically like from a year ago.

1:21:32

You know agents have just gotten so much better a year from now they're going to be even better.

1:21:36

So as agents improve all of the infrastructure around it improves like memory like I think very very soon there will be an agent for every industry. Mhm.

1:21:43

Do you think it do you think that uh it it ends up looking something like regular SAS or from a from a from a user standpoint in terms of you have sort of a dashboard or do you think there's potentially uh totally novel paradigms?

1:22:00

Yeah, you know, I I think UI is is just a big problem or or just an opportunity for these companies to kind of rethink how you surface these product and extend these products to your end consumers.

1:22:11

If you look at agents running in the developing world, in development world, they're just running in your CLI in the background.

1:22:19

Is that the best way to do it? I don't know.

1:22:20

Maybe voice is the best way to interact with them in the future.

1:22:22

So, I think I think that UI is still being re reimagined right now.

1:22:28

I'm I'm guessing what we have right now will be thrown out the window and and that these abstraction layers will be very very different in in a few years.

1:22:37

Yeah, the voice thing is interesting.

1:22:39

That was actually in that original vibe coding post from Andre Carpathy.

1:22:43

He says he doesn't even touch the keyboard.

1:22:46

He just uses whisper or some sort of like super whisper app.

1:22:50

He said and he just talks to it and just says, "Yeah, adjust the padding. Accept all."

1:22:54

Uh, you know, oh, there's a bug. Fix it.

1:22:57

And uh and and yeah, I mean I I it would be very it'd be super super weird because for the longest time the programmer was, you know, the keyboard was sacred.

1:23:07

It was don't have you don't even have a mouse.

1:23:11

Everything you do is on the keyboard.

1:23:12

You probably have an ergonomic keyboard.

1:23:14

You're dealing with carpal tunnel because you're on the keyboard so much.

1:23:16

And if we move to a world where the you still have a genius programmer who can understand the architecture, understand what questions to ask, what features to build, that type of stuff.

1:23:24

But the actual interaction day-to-day is is uh is via voice.

1:23:29

That would be a very very big shift.

1:23:30

It'd be very interesting.

1:23:30

Um anyway, I want to get your reaction to the the the news today that Glean re raised $150 million series F at a $7. 2 billion valuation. Now, will you say Glean? Glean. Yes.

1:23:42

Glean? Glean. Yes. So Glean their uh their whole goal is to uh enterprise search and I'm interested in particularly who are the beneficiaries up and down the stack because I imagine that they're in a position you know to

1:23:57

kind of say hey they stuff all your data in glean but they probably want to be more of an integrator uh and sit on top of your data lake on top of your your snowflake or on top of your uh uh you know your AWS installation or your and plug into your Slack. How are you

1:24:11

How are you thinking about um having tools that really allow folks in the enterprise to interface with all of the infrastructure that you have described? Totally.

1:24:21

And you know what's interesting is the the category isn't isn't new like enterprise search and like there were so many startups and there's this graveyard of companies that existed but I think the clear why now or at least the enabling technology was LLM.

1:24:34

So of course glean is going to benefit but like what's powering all of this are open ais and anthropics like really really powerful models.

1:24:42

Now there needs to be this layer of infrastructure that exists between the model providers and glean itself.

1:24:48

It's like the hairy problems like memory and caching and so those providers are going to win as well.

1:24:54

But ultimately the consumers also and these companies win.

1:24:57

It's it's it's amazing even for me like if I'm trying to search something in Google Drive like how long it takes to get something. It's degraded somehow. It's gotten worse.

1:25:06

Like I can't even see my email.

1:25:08

It it it's just like there's so many like cookies now that if I search for like Jordy, it'll find that in some random URL string and be giving me some like, you know, spam email I got. It's a mess. Yeah.

1:25:19

But you know, we we should expect and I think uh not I think is OpenAI is going to release a product here.

1:25:27

You will have like why why does there need to be an application on top of this? Oh yeah, totally.

1:25:32

I mean, they were they were teasing this a little bit with the uh uh what what was it the um the new the new I think there was a little a little bit of drama around uh different people not wanting other people to invest in Glean OpenAI but then there was also the there was also the the the latest news that um that deep research now can search across GitHub, Google Docs, Gmail, Google Calendar, SharePoint and so that's a competitor.

1:26:01

That's a clean competitor. That's competed.

1:26:02

They're just not saying it. And so exactly.

1:26:04

And so I think for the applications that make that there is strong really strong product market fit with the large language models.

1:26:09

We should expect the model providers themselves to move up the stack and address parts of these apps because I mean if you think about like the models themselves like yes they make a ton of money but they also burn a lot of cash because OpenAI is just trying to build that next frontier model.

1:26:23

So they're going to go where the consumers are like let me go buy Windsurf right and and be in the IDE.

1:26:30

let me go release something in the enterprise search space to compete with vendors like Glean.

1:26:35

But so I mean I think it's fascinating. Yeah. Uh I want Yeah. When when Yeah.

1:26:39

When are you ultimately or the CEOs that you're you're meeting with today?

1:26:43

When are you know doesn't I think there's areas in which people feel safe, right?

1:26:47

If they're working on like a specific application of LLMs with a bunch of deep integrations and workflows, people generally feel safe today.

1:26:55

But is there are you expecting a lot of dialogue around people just trying to assess like am I on the lab's roadmap and and really trying to figure out like at what point they're going to get you know sherlocked. Yeah.

1:27:09

You either have to be you have to be building on the right side of AI.

1:27:11

So if you're trying to solve for deficiencies in the model today and you're trying to build these things like very very quickly in a couple of months all of that tooling just didn't need to exist.

1:27:23

So you you just need to be building on the right side of AI as these LLMs become more powerful like your application itself should become a lot more powerful and how do you embed into workflows and also build all of the little hairy infrastructure things to empower all of that.

1:27:37

Yeah, it's interesting like ironically like rappers aggregation aggregating demand being a front door to AI like that's where a lot of the value has accred or at least like it it feels like the foundation model companies feel most threatened by those approaches versus the threat or just want to own them.

1:27:57

want to own them. they want to own them or they want to compete with them directly as opposed to the okay yes you leapfrogged us on capabilities that's much less of a threat then oh yeah you beat us on a benchmark that matters a lot less than than when people think of

1:28:12

this particular AI use case they go to this website instead of mine that's more threatening to the foundation model labs in my opinion totally you know a good analogy is that the hyperscaler hyperscalers like GCP aws and azure are

1:28:28

the equivalent of open eye and anthropic for the AI world and and if you saw what AWS did for example right with elastic they open source elastic was a very permissive license and they open sourced it and they started competing with elastic itself what elastic ended up doing was they they went to a much more

1:28:44

restrictive license but you still had AWS selling elastic's core product and then Elastic is also existing as whatever it is a $10 billion business today so I Going back to your point, I mean like it's not I don't think it's win or take all. I I think the model providers are

1:29:00

I I think the model providers are going to have a large portion of revenue and and spend here, but they're also going to be really exciting AI native companies that exist on top. Yeah.

1:29:10

Yesterday we talked to Vlad from In Physical working on uh API keys and secret management. Yeah.

1:29:17

Raised a $16 million series A from Elad Gil.

1:29:19

I wanted to know more about different strategies and approaches to building uh infrastructure plays that either play directly or alongside open-source strategies.

1:29:31

And so uh there's an open source package out there that's gaining traction.

1:29:35

How do you build a product or company around that?

1:29:39

Or you have a company that's built something. Do you open source it?

1:29:40

What are the different strategies that you're seeing? What's working?

1:29:44

What's gone out of fashion?

1:29:46

Uh, I just love some color on how to build either with or alongside open source in the enterprise.

1:29:52

Yeah, you know, I I think open source is a double-edged sword.

1:29:55

I mean, obviously we we've been fortunate to back companies like like Hashi Cororp and Click House and we've seen the commercial success of those businesses, but ultimately the for for these companies, the biggest competitor is actually your open- source project, right?

1:30:11

like like why do I need to go pay you millions of dollars when I can just try to do this myself and fork it?

1:30:17

And so for the open source companies out there, I I think you need to be really careful and just kind of understand where your product is going, the types of enterprise features that you could add that that buyers would actually want you to pay for.

1:30:30

Um Aliia data bricks, he has a good analogy here like like building a massive open source business is like hitting two home runs simultaneously.

1:30:40

one, you need an a really exciting product where there's a ton of open source traction, and two, you need to figure out monetization.

1:30:46

In the case of data bricks, you know, they had Spark, and it was great, but they had to figure out a way to make Spark really really cheap and easy to use and and and but they had to hit these two massive home runs to build a big business.

1:30:58

So, for the open source founders out there, I would I would say like really consider how you're going to commercialize this product. Yeah.

1:31:05

What what are the what are the case studies that people are coming back to today?

1:31:08

coming back to today? I remember learning the the history of Red Hat Linux built on top of Linux of course uh fantastic business wound up a public company uh then we've also heard the story of GitLab that went through Y Combinator became a fantastic business

1:31:21

data bricks has a similar story what other stories are people latching on to these days what are kind of like the the the the famous examples that people keep pulling from in this open source enterprise infrastructure world yeah I mean MongoDB is one Look at the success of that business. And what's really interesting

1:31:40

And what's really interesting is that they released their cloud product much later from from the actual open source.

1:31:45

It actually came right before the IPO and it's actually accelerated their revenue growth since.

1:31:51

It's the only company where that's the case in the enterprise software.

1:31:52

So, how were they making money before having a cloud offering?

1:31:56

Just Well, they they had an enterprise uh core version of of their open source, but like got it.

1:32:00

Then they also released a cloud self-hosted version of that product.

1:32:05

Hashi Corp is another example, right, with Vault and all of these systems.

1:32:10

And so there there obviously like companies that have been successful in doing this, but it's you you need to be really careful and you need to think about monetization.

1:32:19

Yeah, it just seems so dangerous because you're building on top of an open source product.

1:32:25

You know, this is going to be baked into Amazon and Google and Azure like very quickly, but at the same time, you're maybe a founder mode company.

1:32:33

you have a lot of really aggressive people that can go and move and launch new features that can just keep you a cut above and then yeah uh you know the the company says yeah I could get you know 80% of what I want on AWS but I want it to be perfect and so I'm going with you because you're the best vendor. Yeah.

1:32:51

Basically is is the total cost of ownership of having all of these developers internally and and trying to maintain this in-house is it much less than the actual service that they're providing the enterprise service.

1:33:02

If if that's the case, then great.

1:33:04

If if not, then you really have to reconsider this the strategy. Yeah.

1:33:08

Nothing's worse than having an open source installation and having to deal with like, oh, we got to turn it off and turn it back on.

1:33:14

It's much better to pay someone else to do that.

1:33:18

And then and then, you know, it just creates just really interesting dynamics with the open source community, right?

1:33:25

if if I'm only going to release features in the paid enterprise version and I'm going to kind of just stop releasing features to the open source version then your community is going to get upset and so like it's yeah you just have to be careful. Yeah.

1:33:36

Well, this has been a fantastic conversation.

1:33:38

Thanks so much for taking the time during the busy day to check in with us. Fun ringing the bell. Come back on again soon. Yes, this is great. Send us some photos. We'd love to see it.

1:33:47

Uh enjoy the rest of your day. Big gong. Yeah, big one. We'll see you soon. See you. Bye.

1:33:51

Uh whether you're looking to get exposure to MongoDB or Red Hat Linux, go to public.

1:33:58

com investing for those who take it seriously.

1:34:00

They got multiasset investing, industryleading yields.

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They're trusted by millions.

1:34:03

Oh, Jordan, you got a new campaign today.

1:34:06

How did you sleep last night?

1:34:08

Because I went on a whirlwind tour.

1:34:10

I fell asleep in my son's bed. So, I got two hours. It doesn't count.

1:34:17

I need Nate's sleep in his bed and then I can have Tyler vibe code up something that merged the two data sets together because I think I got like nine hours yesterday.

1:34:25

I'm feeling fantastic, but I only logged seven hours on my actual eight sleep. So, I got an 86. How'd you do? I got an 83.

1:34:32

That's two nights in a row. Oh, two nights in a row.

1:34:36

Let's hear it for John Kugan the sleep master. No one outsleeps me. No one outsleeps me. Don't even try.

1:34:41

Oh, we got some breaking news from the printer. Deathly ill.

1:34:44

We got some I'm going to be a hand model now.

1:34:46

This is uh this is going to be bad.

1:34:47

Okay, we got some breaking news.

1:34:49

Anderl has been placed number one on the CNBC disruptors list.

1:34:54

Congratulations to Anderl and Trey Stevens is jumping in on the timeline taking a shot at Sam Alman saying, "Ha, take that Sam Alman suck crying emoji."

1:35:04

Of course, they're buddies and and Founders Fund's an investor in OpenAI.

1:35:08

So, they're having some fun.

1:35:08

Uh it was crazy that Anderall got number one because OpenAI has what 10 times the market cap at this point.

1:35:14

But both fantastic companies.

1:35:16

You'll love to see them at the top of the list.

1:35:17

Number one and number two.

1:35:19

We should go we we should go through the uh the disruptors list because we have a little bit of time before our next guest.

1:35:25

Uh Ki from Linear is joining at 12:45. We have 15 minutes.

1:35:30

Let's go through some timeline reaction.

1:35:32

Let's go through some CNBC uh disruptors list.

1:35:34

I want to see who's going on.

1:35:36

So anyway, uh to to recap the Glean news, they raised $150 million, adding billions to their valuation. They're 70 7. 2 billion valuation now.

1:35:43

Uh very interesting to see them 7. 2.

1:35:48

And it was a who's who on the cap table.

1:35:51

The uh the CEO Arvin Jane really using the long post feature on X.

1:35:57

He gives shout outs to Wellington, Kosla, Bicycle VC, Geod Desert Capital, Archer Man Cap, Altcap, uh, Capital One Ventures, City Ventures, Code 2, General Catalyst, DST, Iconic, Institutional Venture Partners, Kleiner, Latitude Capital, Lightseed, Safoa, everybody's in.

1:36:16

So, this tells me that OpenAI didn't really get their way and not wanting to people to invest.

1:36:20

So what you are referring to is uh the fact that uh back in October of 2024 last year uh there's an article in Reuters that says OpenAI asks investors to avoid five AI startups including Sus uh Ilia Suskgiver's SSI sources say so as as global investors such as Thrive Capital and Tiger Global invest 6. 6 6 billion in open AI.

1:36:44

The chat GPT maker sought a commitment beyond just capital.

1:36:47

They wanted investors to refrain from funding five companies they perceive as as close competitors.

1:36:53

The list includes Anthropic, XAI, Ilaskver's new company, Safe Super Intelligence.

1:36:58

Um, and then uh where was the other one?

1:37:01

Two app two application firms, Perplexity and Glean.

1:37:07

And so this was kind of a funny moment because you know Anthropic seems like the direct competitor.

1:37:11

Glean was kind of just thrown in there. Yeah.

1:37:13

But in many ways, but it makes sense. I don't know.

1:37:16

In many ways, Anthropic is not trying to compete in the core. Yes.

1:37:22

You know, they're so AGI pill, they're not trying to compete.

1:37:24

They don't have they don't have a voice model.

1:37:27

They don't have an image model.

1:37:28

They're just focused on on that.

1:37:28

So, but at the same time, they are they are competitive and and you know, if you can keep your investors on your side of the table, it it there used to be like an unwritten rule in Silicon Valley that you only back one company.

1:37:39

Um, Open AI has just gotten so bit big.

1:37:42

They're effectively, you know, public company scale now. We are the market.

1:37:46

So to it's a hard ask to say yes, just don't invest in SAS, enterprise, other other labs. Just don't invest. Just don't invest. Take a year off. Take a year off. Take a year off.

1:37:59

Take a long summer break.

1:37:59

Get some take a six month spring summer break.

1:38:04

Just just spend put your whole team on getting into the massively overs subscribed round over there. Focus on that. Good luck. work on yourself. Work focus on yourself. Hit the slopes. No more investing. Focus on yourself. Yeah.

1:38:16

Um but this uh this news happened uh last week.

1:38:19

Open said we're rolling out chat GPT record mode to Teams users on Mac OS.

1:38:24

Capture any meeting, brainstorm or voice note.

1:38:26

Chat GPT will transcribe it, pull out the key points, and turn it into follow-ups plans or even code.

1:38:29

This was taken as a granola attack, but it also plays into uh the Glean story.

1:38:34

So, Signal said, "Granola is more of a social company than a B2B company, it punctured a norm.

1:38:40

No big player would have taken the risk of recording without permission."

1:38:44

But where Granola beautifully reframed it as productivity, intimacy even.

1:38:48

Once the social acceptability shifted, it was inevitable that infra players like OpenAI and Notion would mimic the mechanic under the same pretense.

1:38:55

This is the difference between product innovation and cultural mutation.

1:38:58

Tech can't move where the culture hasn't first been softened.

1:39:02

And so so interesting because Otter Do you remember Otter AI? Have you used them? I' I've used Fireflies.

1:39:08

I Otter was started in 2016. Yeah.

1:39:10

They they crossed 100 million ARR. Yes. This year. Yes.

1:39:16

And in many ways it's very similar to Granola.

1:39:19

similar to Granola. I believe I inspired some of these because I don't want to take too much credit because I didn't build anything but uh in in in 2014 I had I had a workflow where I would record uh I would record meetings audio I would record the audio of Zoom meetings or or Google Hangout meetings and then I would send those to a transcription service that was not using

1:39:43

AI at the time and I would use Zapier to automatically do this or Zapier and the guy and the team at Zapier uh reached out and they wrote a blog post about my workflow as being like a cool example of how to use Zapier in an interesting way and a couple founders reached out to me and said hey we want to build this as a product and one of them was Fireflies and it's like a banger company now too. Yeah. Um and Yeah.

1:40:02

Um and obviously it's massively massively enabled by AI uh and and only gets better and better.

1:40:08

Um but yes uh Kevin Wheel over at uh OpenAI the chief product officer uh said deep research can now search across GitHub, Google Docs, Dropbox, HubSpot, Outlook, Box and even more.

1:40:20

You can connect any chat to Google Docs, SharePoint, Dropbox and Box.

1:40:24

There's even an initial version of MCP support for HubSpot. This is big.

1:40:28

There's record mode in chatbt single sign on for chat GPT teams.

1:40:30

So they are firmly going into the enterprise.

1:40:33

Uh, and this was this was a point that people were making was that chatgpt for teams didn't feel like an enterprise product.

1:40:40

It it just allowed you to provision a normal chat GPT instance to an employee and say, "Hey, we're we're covering the cost."

1:40:48

Basically, it wasn't truly integrated.

1:40:49

Imagine how cool it'll be if we add someone to the to the TBPN team and they and they immediately get access in their chatpt to all of our internal documents, everything that we have about all of our transcripts, all of our all of our almost like an enterprise search product. Yes, exactly.

1:41:08

Somewhat like somewhat like Glean.

1:41:08

And so it was clearly on the road map and they and they work towards it.

1:41:12

Anyway, uh they're doing great.

1:41:13

OpenAI's number two on the CNBC uh disruptor 50.

1:41:15

Then you got data bricks anthropic at four canva at five ramp at six. Let's hear it for ramp.

1:41:24

Congratulations using ramp. Love to see it. No surpris at seven.

1:41:29

We got to get the founder on the show.

1:41:32

Very interesting company. Uh crime fighters. Crime fighters.

1:41:36

They solve a ton of crime in America.

1:41:38

More important than ever. Uh AlphaSense.

1:41:40

It's kind of like productized Gary Tan. Yes. Gary Tan is a service.

1:41:45

Uh, AlphaSense is at number eight.

1:41:48

They of course acquired Tigus and are a market research team uh market research uh uh firm intelligence juggernaut big advertiser on invest like the best. We'd love to see it.

1:41:58

How I was about to say I was about to say if there's a single company in I don't know. I'm cooked. Yes. I'm cooked. Yes.

1:42:06

But number nine Octopus Energy. Look it up. Give us a breakdown. Haven't heard of them.

1:42:09

Smarter, greener, fairer energy for every Texas home.

1:42:11

Is this a base power competitor? Interesting.

1:42:14

Isn't it Do they make batteries or do they make solar panels? Break it down for me.

1:42:17

I'll keep reading while you do some research.

1:42:21

So, I'm on the website and I still don't know how it works. Okay.

1:42:22

Well, all you need to know is that they're number nine.

1:42:26

Let's have the founder on the show.

1:42:28

Have him explain it to us.

1:42:28

We don't need landing pages, Jordy.

1:42:30

We get it straight from the source on this show.

1:42:33

Yeah, there's a bunch of graphics of Octopus. I don't know. Wait, really?

1:42:38

Is it Is it energy generation, energy storage?

1:42:40

Um, you do some research.

1:42:40

I'm going to read through some of the more.

1:42:44

They got Stripe at 10, Revolute at 11, Thrive Market at 12, Metropolis at 13.

1:42:49

We have the founder of Metropolis coming on the show in just a few minutes.

1:42:50

Why would you look at that? Trans uh Transarent. I haven't heard of this. They care. They're at number 14. We got to look up them.

1:42:57

Lead Bank, Fintex Fixer at 15. Haven't heard of them. Carbon Robotics. Weedtech.

1:43:02

We talked to the founder of Carbon Robotics. That was awesome. For health and care. Verta. Verta Health. What comes after GLP1?

1:43:11

That's an interesting company.

1:43:11

We'll have to dig into them.

1:43:12

Frutist the berry unicorn.

1:43:15

We got to look into Brutus. That sounds awesome. Seronic at 19. We know them.

1:43:20

Grub market is so what is the criteria for getting on this list.

1:43:26

Uh we will we will dig into that because it's definitely not revenue.

1:43:31

Uh there's a whole bunch of great companies on there.

1:43:34

You got Figma, Zipline, uh Sierra, Runway, Nonest is inspiring and inspiring.

1:43:40

Enjoyable and nutritious snacking.

1:43:43

Okay, Fruttus grows the world's most delicious berries, bursting with flavor, crunchy goodness, and freshness in every bite.

1:43:51

Okay, here's how they chose the list.

1:43:54

So, they're all proud any of these.

1:43:54

Yes, I love I I'll go out and say I I'm a huge fan of fruit.

1:43:59

I think it's one of one of It's fantastic.

1:44:01

God's greatest um inventions and gifts.

1:44:04

Uh, but have any of these fruit brands broken out?

1:44:11

Fruttist seems like they've broken out. They're on the list. Beautiful website. Beautiful website.

1:44:17

Uh, do you want to hear about how they chose the 2025 Disruptor 50? I got to know, John.

1:44:22

So, uh, they are all private, independently owned startups founded after January 1st, 2010.

1:44:25

They were eligible to be nominated.

1:44:29

Companies nominated were required to submit detailed analysis including key quantitative and qualitative information.

1:44:36

Um quantitative metrics include company submitted data on their sales, number of users, employee growth or lack thereof and more.

1:44:42

Some of this information has been kept off the record as it was used for scoring purposes only.

1:44:48

CNBC also brought in data from Pitchbook and IBIS World um and compared those based on the com on the industries that they are attempting to disrupt.

1:44:57

Uh there's a board of leading thinkers in the field of innovation and entrepreneurship from around the world along with newer a newer advisory board uh that ranked quantitative criteria by importance and ability to disrupt established industries and public companies.

1:45:13

This year the two advisory boards found that scalability and user growth were the most important criteria followed by sales growth and access to capital and community.

1:45:21

It's very funny that uh Anderrol's number one because like what are their user growth metrics?

1:45:27

Like that's not the metric for them at all.

1:45:29

like users are a relevant metro.

1:45:31

They're not looking at like mows and dows.

1:45:33

They're looking at like how many things did we build.

1:45:35

Um but still so fruit coming in.

1:45:37

I'm I'm still fixated on the fist because I guess going off of users, you know, they're selling a consumable good in in Whole Foods.

1:45:45

Um but uh tough tough go for, you know, companies like Scale AI which are down at at 20 28.

1:45:54

Um, so fruit is better than 18.

1:45:58

So, so yeah, if you were going off of this, you'd go short longest.

1:46:00

It's possible this is should be Meta's next target.

1:46:06

Maybe they should try to move up the list. Yes. And get them all.

1:46:08

They already have a deal with Ander.

1:46:11

They have an amazing distribution engine. Yeah.

1:46:13

Every other ad could just be an ad for berries or fruit.

1:46:16

And I I eat these things all the time.

1:46:18

And and it just be a good way to to really they could potentially turn Fruttus from the bear unicorn into a you know a deca unicorn. I love it. A deck of corn.

1:46:26

We need we we need more food. We need better food.

1:46:31

This is a this is a common common theme.

1:46:33

This makes a ton of sense.

1:46:33

Um so new for 2025, we can compare the way the two different advisory boards considered the importance of the list criteria.

1:46:39

While the two boards mostly agreed, the VC group thought that the size of the industry being disrupted was more important than the academics did.

1:46:46

with the latter ranking access to capital and community as more important criterion than the group that provides said access.

1:46:54

The ranking model is complex enough to be sensitive to these differences of opinion.

1:46:57

And perhaps more than ever, it makes good on the concept that companies must score highly on a wide range of criteria to make the final list.

1:47:05

Nominated companies were also asked to submit it important qualitative information about themselves, including descriptions of their core business model, ideal customers, and recent company milestones.

1:47:15

A team of CNBC editorial staff including TV anchors, reporters and producers and CNNBC.

1:47:19

com reporters and editors along with many members of the advisory board read the submissions and provided holistic qualitative assessments of each company.

1:47:30

Uh in addition, the VC advisory board assessed a small group of finalists as an additional component of the qualitative review.

1:47:35

Specifically, we asked VC the VC group to assess some of the companies that would if selected be making the list for the first time as well as to help in the consideration of high-scoring early stage firms, a a group of lower value.

1:47:49

Part of the criteria, they didn't want the top 25 to all be enterprise SAS companies because that doesn't it's not good for ratings.

1:47:59

It's not good for ratings. Not good for ratings.

1:48:01

So uh only 11 of the 2025 honor honores are pre-Chat GPT CNBC disruptors but most of that group and data bricks can and canva chief among them the uh the embrace of the new era is what has kept them here and so uh there were 19 first timers in either 2023 or 2024 companies are moving up they're moving down um but it's an exciting list.

1:48:25

Who else sticks out on this list?

1:48:28

We got to get some of these folks on.

1:48:31

A better ride to school from Zoom.

1:48:32

Wabby, how self-driving trucks see and learn. That seems interesting.

1:48:37

Appronic 5 feet 8 in 160 pounds all robot. Haven't seen them. Harvey's on the list. Lawyering up AI.

1:48:47

They got good pathy pathy phrases. Good lines.

1:48:49

Notion project project management.

1:48:51

Okay, we got project management for your projects.

1:48:54

That's kind of an odd one, but not the strongest. A bridge. Getting a doctor's note.

1:49:00

Isuu Isusu treating renters like owners. Shield AI the CEO on. Interesting. Uh well, very fun list. We love a good list.

1:49:09

We we're now that Conrad's out the Midas list has fallen from grace and we need new lists. But congrats to Ander.

1:49:16

Congrats to Open and congrats to everyone that made the list of the CNBC disruptive 50.

1:49:20

One thing's clear, you got to be an absolute dog to get on this list. Yes, you do.

1:49:26

Um, well, we have Ki uh from Linear coming in the studio.

1:49:31

Get the gong ready, John. Why don't you hit it? I will hit it for him.

1:49:34

We're gonna hit it a few times.

1:49:34

Ki, uh, before you before you dive in, uh, yeah, give us the numbers first. How much did you raise? How much did you raise? 82 million.

1:49:46

Low dilution round at a billion. We love to see it.

1:49:50

Um, uh, a lot of people would have said, you know, this was maybe an unlikely round.

1:49:55

You guys have been very very efficient.

1:49:57

Uh but it's a testament to to proving the haters wrong.

1:50:03

They said it couldn't be done.

1:50:04

Well, they said it could be done.

1:50:07

They said Ki would never would wouldn't do it.

1:50:08

It's great to have you on.

1:50:08

Um massive milestone for you and the team. How are you feeling?

1:50:15

Yeah, feel feeling great.

1:50:15

And yeah, I think it's definitely like um one of this like I think like all of our rounds has been kind of like interesting because since I think the seed round we haven't really needed the money.

1:50:26

So each round is kind of like we we're doing something different or or we signaling something to the market.

1:50:33

So it's a little bit always like strange to do these rounds because like I think like often like you celebrate it as a way to be able to do something more and I think like in the end we we'll do something more but also that like not a lot of changes like we we still keep building for the customers and um the things we're doing.

1:50:54

Talk about maybe some of the last rounds how they were unique and and what makes this round unique. Yeah.

1:51:01

Um I think we also like done this like interesting thing where we have kind of doubled down on each of the investors.

1:51:07

So Seoia led our seat round um back in 2020 and then we did a series A with them I think 21 and then we did a series B with XL in 22 and then now two years later or like about 3 years year later we we did a series C with them.

1:51:24

later we we did a series C with them. So I think there there's also like um I remember when I was talking to back in the day like around the seed round to a lot of seed round investors and I think like they they had this like they create this fear that these platform funds can be challenging and like there can be

1:51:44

this signaling risk and all kinds of things and I don't know if that's really true or I haven't I don't even know like when that has happened but I do know that it's kind of like interesting when you are working with this platform form funds, they can like double like kind of like lead two rounds in in in like kind of sequence. And I think the benefit

1:52:02

And I think the benefit there is that you can kind of push down the delusion because there is um they already have some kind of ownership and they like I think like a lot of times the with this game of like fundraising like the the actual absolute numbers don't matter like how much you raise or what the valuation is.

1:52:19

It's more like everyone's just fighting for their percentages.

1:52:22

And so if you if you kind of like work with the same investors, you have more like I don't know leverage or or there's a little more like flexibility on those percentages. Yeah. Yeah. Yeah. I mean it makes sense.

1:52:34

It also makes uh board construction easier because you're not adding 25 different board members from every fund.

1:52:39

uh on the platform fund thing.

1:52:41

I mean, it's clear that like that narrative came out of like kind of the clubhouse era where the company got marked up multiple times for by the same insider and and the metrics didn't really meet that.

1:52:51

Um was this more of a vibe round or an Excel round?

1:52:56

How are the metrics tracking? What what are people?

1:52:58

What are people watching?

1:53:00

Are they looking like is Mao Dow the key KPI?

1:53:03

You don't have to give us the actual number, but like what is most important?

1:53:06

Is it revenue, profit, EBIT do EBIT?

1:53:08

like what what metrics are are are most important for a round like this to get done in this era?

1:53:12

Um I mean like I think like all the later stage funds like or later stage rounds it it is about the growth and and the revenue.

1:53:20

Um I mean obviously different companies are different so like there might be like other other things but but for us since we we sell to companies it it generally like turns into revenue like we don't have a lot of like free users or free free customers or um every everyone is like a a paid customer.

1:53:38

I think it's like comes down to one is like kind of like the growth and the the kind of position we have in the market.

1:53:45

position we have in the market. we been able to capture quite a lot of the growth market these days like the early stage startup but also like the latest stage growth market like companies like ramp or mercury or brex or or um and even open AI which is I don't know like

1:54:02

if you categorize it as a growth company or like enterprise or what is that I don't know company behemoth yeah we need a new word to corn something like that yeah yeah I think like we I think like it comes down to like we we work with the best companies out there. Y and I

1:54:16

Y and I think like we also have like a lot of um people really love the product and like they really want to use it.

1:54:23

So I think like we have had a lot of opportunities that we could have additional investors join the board or like lead these rounds.

1:54:32

But for me at this point I think it's it's probably like in the next next like the next time around there's probably reasons to find someone new and like find someone with like some kind of specific or different skill set.

1:54:43

But right now, I didn't feel like that's necessary right now.

1:54:47

I think like the biggest thing what we're aiming for is that like we have this core business and and product going with a lot of like 15,000 customers like companies.

1:54:56

Um that I think that you love it.

1:55:00

I think that you love it. Uh the next thing is the the the kind of like the AI and how how you probably heard it this like a million times on this on this show but I think again uh the AI is like shifting the the market and and like how

1:55:16

things work and like how software is built and I think we often I like to do these rounds when we don't need to do it and we also like when we are about to hit something big and I think we were about to hit something big with this like yeah talk about some of the discussions around. Yeah. Talk about Yeah.

1:55:32

Talk about some of the the discussions uh you know with Excel and and some of the other partners and internally with the team around this sort of inflection point with agents because for the first you know you guys have had a bunch of integrations for a long time but this is sort of a novel type of integration.

1:55:46

And I know you guys are working with um you know Devon and Cognition and and other players and um you know that that feels to me like a lot of the uh linear position as a platform that can help manage agents feels like you know a major catalyst. Yeah. Um yeah.

1:56:06

So some some of those companies we've been working now but and there's a lot more coming.

1:56:10

I I don't have the exact dates yet, but I think we're also working with the bigger companies out there that are are building some of the like the like the model companies.

1:56:18

Um so hopefully those are coming soon.

1:56:21

are coming soon. So yeah, I think like the with the agents the idea is that we have this we have built this like end to-end workflow for like discovering and planning and building products and it's like kind of familiar to this

1:56:34

organizations and these product teams and I think like right now like we we started seeing this traction from our customer base and also talking to CTO's almost every CTO out there is thinking about AI like how do we we we I think

1:56:50

like the CTO's and and CEOs are writing these memos and like they know that they can help their organizations but the the problem now is like there's a lot of friction like the the solutions are not that like designed yet like it it's a

1:57:04

little bit hard to use some of these tools and or use this technology so the idea here is that like we have this familiar system that people already do use to to do their work and so we can easily introduce this agents and some of the other AI capabilities into it. So

1:57:19

So they don't have to like go somewhere else to do it, but they can kind of like continue what they're doing.

1:57:25

But now instead of assigning task or or like kind of like code bugs or something to humans or the teammate teammates, you can assign them to agents and then work with them to solve them.

1:57:38

So I think like the the the kind of like the idea there is that we want to make it as easy as possible for organizations to kind of adopt the AI or adopt these agents or adopt like the new technology.

1:57:50

Um because like a lot of the other companies are kind of like more building the underlying technology but then sometimes it's it seems like it's hard to for enterpris yeah orchestrate them.

1:58:03

I want to let you get back to building but I have I want to get WWC reaction.

1:58:06

We got to get your take on WWC.

1:58:08

I mean, Linear is a fantastic designdriven firm.

1:58:10

I'm sure that there was a lot of internal chatter in the Slack or in the in the in the in the group chats about WWC. How's the reaction? Liquid Glass. Liquid Glass. What's the take?

1:58:22

Give break it down for us.

1:58:24

Um, yeah, I don't want to go too harsh on it until I think I think until it's like in production.

1:58:30

I do think like there's some discussion.

1:58:31

I think the the borders are too rounded and I think like some of the borders are off like they're not following the right like when you have like two rounded rectangles you should kind of like follow the same curve with those curve um with those round like the border radius.

1:58:46

Um so it looks like an kind of like an even like that there's even spacing alongside all of the all of the kind of path.

1:58:53

Um, but I don't know if that was a mistake someone did for the keynote or they just didn't want to like I don't know they didn't do it correctly.

1:59:02

Um, I hope it was a mistake.

1:59:04

Um, I think it's it seems like really I I think obviously visually interesting, but I I'm still like skeptical until like I see it like how well it's actually works in practice.

1:59:18

Like at linear actually we did have some of this we had this like trans transluent UI at some point and then I decided to remove it because I I thought it was like too distracting and it's actually was kind of slowing the application down.

1:59:32

So I I decided to remove it and and so I'm hoping that Apple can make it performant and also not distracted. Yeah.

1:59:40

Do you think do you think there's always going to be readability challenges with it or is it something you know that uh that they can solve?

1:59:50

I mean I think the starting point it it it is hard to like solve that because like I think it's that was my experience with like having like transparent UI as well is that it it can work well if you have a nice like I don't know solid color background on your computer or or something.

2:00:07

But then like if you have like a photo like on the on the phone you have a photo of your family or something it it can be kind of bright and like there can be a lot of different things going on in the background.

2:00:16

So I do think it it will be hard to like make it kind of easy like the contrast to be enough to to read it.

2:00:23

But I don't know if they're going to do some kind of magic there that they could figure out like what's on the background and then adjust it somehow.

2:00:33

Um, so I'm hoping that they can figure it out, but um I'm I remain a little bit skeptical until like I actually see our batteries our batteries are going to be cooked.

2:00:45

I think they'll figure it out.

2:00:45

Um, well, congratulations to to you and the whole team and uh yeah, excited to uh see what you guys continue to cook up. Yeah, this is fantastic. Getting started. We'll talk to you soon. Have a good one. Thanks. Have a good one, Ky.

2:00:58

Uh, let's check in with Tyler.

2:01:01

Apparently, he has iOS 26 installed.

2:01:04

Give us the update, Tyler. How's it going? Let's see it. Yeah.

2:01:08

So, I got it fully installed.

2:01:08

I mean, we might have to put those uh those posts in the truth zone.

2:01:12

It looks pretty good on my phone. It looks good.

2:01:15

It's like pretty readable. Give us the review.

2:01:17

I think it's I I I like it.

2:01:17

I might I mean, it's it's a bit slow on my phone.

2:01:22

That might be because Which one do you have? I have an 11.

2:01:23

So, it's like 6 years old. Wait, I'm on like 16.

2:01:26

He's got a vintage behind.

2:01:29

So, it's either that or I think also usually in the beta versions it's it's a bit like slower. I have a 16 Pro.

2:01:35

Yeah, I'm going to light years ahead of you. Oh my god.

2:01:38

But yeah, it looks pretty good. I'll bring it up there. Okay, cool. Bring it up. Yeah, bring it up. Let's see it.

2:01:43

We're putting on the printer cam. We'll see it.

2:01:45

Uh and uh yeah, here we go. Okay, cool.

2:01:49

Uh can we see I don't see much it.

2:01:51

It actually looks pretty similar.

2:01:57

I I expect Okay, there's the there's the there translation.

2:02:00

Yeah, this doesn't look as it's it's mostly just the home screen.

2:02:04

Like if you go I I went into a bunch of the like alphabet opening the calculator. No, no, no, I'm kidding. I'm kidding.

2:02:14

Yeah, I mean I mean you can see the glass effect uh like right here up at the top. Um yeah, it's nice.

2:02:18

It's and look so so look at the search bar as as I scroll the apps here.

2:02:24

You can see you know that that that glass effect. It's not too bad.

2:02:30

Um you bring down the the settings. I'm bullish. This is groundbreaking.

2:02:34

I think this is I think this is groundbreaking. I think this works.

2:02:37

This is this is pretty readable.

2:02:39

Anyway, thank you for volunteering.

2:02:39

Uh you'll have to we'll have to check in with you over the next couple days.

2:02:44

We're sorry if it destroys your productivity, but uh you're cracked. So, you're cracked. You'll figure it out.

2:02:51

Anyway, thank you, Tyler.

2:02:51

Um, you know, Apple's going to be pushing this pretty hard.

2:02:55

They got to do some out of home advertising.

2:02:57

They got get they got to get on adqu. com.

2:02:58

Out ofome advertising made easy and measurable. Drop the Genmoji ads.

2:03:04

Market by every single Yep.

2:03:09

billboard in San Francisco.

2:03:12

Say goodbye to the headaches of out of home advertising.

2:03:13

Only ad quick combines technology out of home expertise and data to enable efficient seam by seamless ad buying across the globe. I'll be right back.

2:03:23

Um, we have our next guest, Scott Bellski, coming into the studio in just a minute.

2:03:29

In the meantime, we will react to some posts on the timeline.

2:03:34

Uh Kendall says, "Trying to quickly change the subject on the Zoom call when everyone else is cracking jokes about the Whimos and I can feel I can feel myself choking up."

2:03:42

Lots of sympathy for the Whimos.

2:03:45

Uh, lots of coverage in the Wall Street Journal today about the about the burning whimos, talking about how this played directly into the hands of of the of the Trump administration by uh making the tech company clearly align with um, you know, against the burning of Whimos. Very sad to see.

2:04:05

Um, hopefully things resolve.

2:04:08

It does feel like the report from LA I've been driving around today.

2:04:11

Uh, it feels like things have calmed down a lot.

2:04:13

Um, in general, I was able to drive all the way across LA and without any I was in downtown, didn't really notice anything, and so it does seem like things are are calming down, thankfully.

2:04:23

Um, anyway, um, I like this post from Tyler.

2:04:26

Uh, I'm going to mispronounce this name.

2:04:28

Well, I'll just say Tyler.

2:04:30

Um, he says, "Unlike the rest of you cowards, I think the W the Y Combinator valuations are too low."

2:04:35

Uh we will find out what the valuations are coming in at tomorrow when we're at YC Demo Day live in San Francisco.

2:04:42

We're bringing a huge swath of the crew.

2:04:45

We're going up right after the show wraps. The team is stoked.

2:04:49

We'll be giving out hats.

2:04:51

We have a whole bunch of different hats.

2:04:52

Some TBPN hats, some ramp hats, and the ramp hats have TVPN on them.

2:04:55

So they're all limited editions.

2:04:58

I think people really like them.

2:05:00

So, if you're a founder at YC Demo Day or you're an investor at YC Demo Day, stop by our table, come chat with us for a couple minutes and we will uh get your take and hear your pitch and hopefully turn uh your demo day into a massive party round because we will be live from the Palace of Party rounds.

2:05:18

Um Mike Salana uh reposted the video of the Whimos leaving Los Angeles.

2:05:24

Apparently, Whimo is moving their cars out of LA.

2:05:26

I don't know how real this is, but there it was a video of several Whimos uh driving through LA kind of all together. Maybe they're leaving.

2:05:36

Doesn't quite make sense because you think you could just put them wherever they store them and charge them and clean them, but yeah, I don't necessarily believe that this was a response.

2:05:43

This seems like fake news, but uh Salana has a great post as always.

2:05:48

The elves are leaving Middle Earth. Very funny.

2:05:50

Um anyway, uh RAMP has a post uh in 2012.

2:05:56

In 2024, RAMP placed 32 on CNBC's disruptors 50. This year, number six.

2:06:02

They're grateful to their customers for betting on a better way and allowing us to fix the parts of finance people hate so they can do more of what they love.

2:06:10

And shout out to our friends at Ander for making number one.

2:06:13

What a fantastic lineup over there.

2:06:14

Um what else is in the news? Oh, uh Warner Brothers. Oh, wait.

2:06:20

We have Scott Bellski in the studio. Let's bring him in.

2:06:23

How are you doing, Scott? Hey, what's up? There he is. Finally. Long overdue.

2:06:29

I I I'm sorry it took me so long to invite you on.

2:06:31

I'm so glad we could make this happen.

2:06:33

Uh it's fantastic to find.

2:06:34

We were we were sending invites constantly.

2:06:36

Mentally, we were like, "This is a dream guest."

2:06:38

So, thank you so much for taking the time to uh join us.

2:06:41

Uh would you mind kind of setting the stage for us because you've done a lot in your career.

2:06:45

What are you focused on right now?

2:06:46

What's interesting to you?

2:06:47

and then we can kind of dig into all the hot topics of the day.

2:06:49

Well, first of all, it's been fun to watch you guys at work and uh congrats on just, you know, creating conversation, which I think is uh is appreciated by all of us.

2:07:01

What am I up to these days?

2:07:01

I mean, my obsession has always been the intersection of creativity and technology. Yeah.

2:07:06

Behance is probably what 58 million 60 million creatives online right now showcasing their work.

2:07:13

that brought me into Adobe.

2:07:13

Had a long stint at Adobe um leading emerging products and design and various other new things there.

2:07:20

Um and uh you know now I'm excited to uh kind of explore the world of storytelling and the role that technology plays there.

2:07:27

um obsessed with the implications of new technology, you know, that emerge and uh I love engaging in conversation about I think you guys were talking about the implications kind of writing I do and uh and riffing off of I don't know like what's going to happen because of what's going to happen is the question. Yeah. Yeah. It's a big question. It's a big question.

2:07:48

Uh maybe we should start with uh some of the news that's coming out of like this idea of collective memory.

2:07:55

What's going on in the enterprise?

2:07:56

We were talking about Glean, OpenAI, deep research.

2:07:58

There's so many new products. We're using stuff. We're wiring up stuff.

2:08:03

We have an intern in the corner vibe coding different stuff for us.

2:08:06

We're we're essentially a podcast or a live show, a media company, and we're we're writing software.

2:08:12

Everything about how we're building this media business is different than I think people would have done uh even just a few years ago.

2:08:19

Um, but yeah, it's actually crazy.

2:08:21

The um if if somebody told me three years ago, I we have a a show, a podcast, and we're building a bunch of internal software, just be so bearish, and yet we get so much value out of our internal software we call Newsmax.

2:08:37

Um, but anyways, um, back back to you.

2:08:40

No, I mean I think the uh well, first of all, it's it's when you're building a new team from scratch these days, it's almost like you're you're able to build with another new generation of tools as opposed to retrofit something built with old tools. Totally.

2:08:55

So I do think there's this advantage that a lot of new companies are realizing now or new teams within companies, you know, but you asked about this this concept of collective memory which I've been obsessed with, you know, this this notion that the context window of these AI tools that we're using.

2:09:09

Of course, those contact windows are context windows are growing, which means that their memory of us and their understanding of us is growing and persisting across all the inquiries we have.

2:09:20

and uh you know and this is becoming almost like you know an extension of our knowledge and opinions and identity and everything else and and it's great when these LMS get to know us and give us better and better answers to our questions.

2:09:32

our questions. um what happens when in the enterprise we access each other's memory right so if if the if the context window of me working you know as one of your interns for years you know is suddenly accessible to you even when I leave you know are you able to keep

2:09:49

saying hey what does Scott think or you know what what what did Scott do when we had this situation and is that a is that does that belong to the enterprise and you do see by the way like every company right now trying to build this memory for each of its products users. And in

2:10:03

And in some cases, a lot of companies are building connectors to get the data from other products that that customer uses to enrich that memory and understanding of their customer.

2:10:13

And it'll be interesting when that kind of memory that's for each of us becomes a collective memory.

2:10:18

And then what happens in the in the social like in the consumer world like you know does your girlfriend say like I want access to your context window, your memory, you know, and is that kind of weird?

2:10:28

I think there's all kinds of weird questions and implications that arise from that.

2:10:31

Do you think memory can be the lock in that I think certain companies would like it to be.

2:10:37

It doesn't feel like it is yet, but I think there's still an idea that it could be.

2:10:42

Sometimes it actually goes the opposite way.

2:10:44

Like I I'll ask Shhat BT to tell me a joke and it'll be like hyper specific about something I talked about a year ago and I'm like that actually makes the joke worse.

2:10:52

Like I'd prefer if you ignored all my questions about trains or something.

2:10:56

Well, that could be in the prompt, right? Yeah, exactly.

2:10:59

I feel like uh you know, you see OpenAI launch um the ability to log into tools with Open AI. Yep.

2:11:05

And you know, when I saw that, I was like instantly thinking, gosh, that's a way to enrich the personalization.

2:11:11

Um I I do think personalization effects are the new network effects.

2:11:16

You know, we used to talk about in terms of the the moat that companies would have with a network effect. today.

2:11:22

I do think they will have with personalization and that is a direct, you know, a direct uh out outcome of the memory and extended context window and all of the data, you know, that they can get to give us a personalized experience that no one else could ever give us.

2:11:37

But you're right, like there are other ramifications of that, you know, if you if you're too wellknown.

2:11:42

I asked OpenAI the other day, you know, what I didn't know about myself and it told me that you're a real hypochondric.

2:11:48

And I was like, well, I didn't know that about myself. So that's funny.

2:11:52

Um I I I I want to know more about um these the like this idea of collective memory in the enterprise.

2:12:00

What sorry sorry to interrupt but it's an interesting thing where like the model is effectively trying to do pattern recognition and it just identifies something that is like you ask a lot of questions.

2:12:09

It's like yeah because you're a question answering machine. Yeah.

2:12:12

Like that's not me that's you.

2:12:14

But uh but on on the concept of like creating a collective memory in the enterprise, I've noticed that even though we are this new company that's starting from scratch, total green field, we have still not been able to go all in on one walled garden.

2:12:26

We have Gmail, we we send a lot of iMessage groups.

2:12:31

We also have a Slack that, you know, we are interfacing with different people on that's a Salesforce product.

2:12:37

And so I'm wondering if uh you know there's been uh Eric Mikovsky was trying to build Beeper, this product to let you create one unified messaging interface.

2:12:48

That was a real struggle because every major company was like we will not let you break our walled garden.

2:12:53

We're not really there yet.

2:12:56

And and it seems like most of the companies are playing ball um with MCP servers and the like.

2:13:00

But what do you think the big dynamics of the big tech companies will be like once they realize that, hey, maybe if I don't want to let the fox in the hen house?

2:13:12

Well, I think you're, you know, you're you're you're forecasting a bit of a call it a data war, you know, in the years ahead where everyone's going to leverage each other's APIs and start start to pull all the data, you know, in and and they're going to probably be some backroom board level bilateral negotiations where it's like, well, let's not cut off Slack because we don't want them to cut off us.

2:13:35

So we're going to let them and may the you know may the best may the best model win right with the data provided to it.

2:13:42

the data provided to it. So um but that means that there if if if the data becomes sort of s you know readily available across the board from all of the connectors that are made for all of the products we use and to your point if you've built the network your your company with all these different

2:13:58

products that's fine because the data is all stored probably in one of three or four clouds and you can just instantly uh access all that data use AI to see it as structured data and then be able to have AI apps built on top of it and you don't even need to care what actual products create the data as long as you have access to all the data. But then

2:14:15

But then the question is what are the modes, right?

2:14:18

I think one of them is the personalization layer that we talked about just now and uh and that context window becoming ever more important uh in the product.

2:14:26

You know, I think another one is permissioning like in the enterprise especially permissioning is freaking hard, right?

2:14:32

To know exactly who's about who's allowed to ask what question and get what answer or what column of information that might relate itself to that answer.

2:14:40

that is a a very very hard thing to crack and I do believe that the enterprise products that have really incredible permissioning layers and products uh that allow people to control and access permissioning you know will also will also have an advantage.

2:14:54

So I mean and then and the operating systems um we talk about operating systems in the consumer world with you know your iOS or Android person or whatever and that's the operating system.

2:15:04

Those those operating systems like if they can't figure it out well shame on them like they literally own the uh the the top layer of everything underneath and they should be able to you know manage our attention and our needs with AI at that level.

2:15:18

But what are the operating systems of work? Mhm.

2:15:20

You know, I think there's going to be another war played around those operating systems.

2:15:23

One might be the browser.

2:15:25

I think one might be the way that projects are managed.

2:15:29

You know, different functions of the enterprise might have different operating systems and people are going to be fighting to own the top layer of those. Yeah.

2:15:36

I wonder if that's like a almost a bullcase for data lakes becoming more of a mid-market or early stage product because like I I I I I take your point about like the the the deals between the large tech companies uh just kind of happening behind the scenes but at the same time I'm just like there's going to be friction and I just know these companies like yes I can export all my data from Facebook if I click 12 buttons and do it every single day.

2:16:04

like the API is not fully there for a lot of these products.

2:16:08

And so I wonder if more and more people are going to be saying like even for my personal life, I want to be able to funnel everything into a data lake that then I can drop my own AI on and I don't necessarily want lock into one AI tool right now.

2:16:21

I'm wondering how that how that will evolve. I don't know.

2:16:25

Yeah, I mean we're going to see this in consumer too.

2:16:26

It'd be really nice right now if you could describe in chat GBT, hey, go find this image and then make it a studio Gibli, right?

2:16:34

or or make it like an impressionist painting, right?

2:16:35

And and obviously there there's that kind of barrier wall.

2:16:39

It just feels like the the big tech companies want they're fine having lock in and like you see this with WWDC like the the Siri button cannot be remapped still.

2:16:50

And it's like that would have been an easy thing to do that would have been something that a lot of consumers demanded.

2:16:55

uh what was your reaction to WWDC and kind of like how how the the AI Apple uh like uh decisions are playing are playing out.

2:17:06

Yeah, I mean I think it's really it's a really fascinating time, you know, in that company's history.

2:17:13

I think from the outside we're questioning like where's the vision, you know, where are we all going?

2:17:18

And I think inside it's probably some sense of let's wait until we're really ready.

2:17:23

We've had a few false starts.

2:17:25

We can't get it wrong again.

2:17:25

And so, we're probably going to get something that's more fully baked, which is hopefully great for Apple.

2:17:31

You know, I never I never discount Apple because of its DNA and its rigor and the quality of talent that's there.

2:17:40

You know, on the other hand, like they're late to the game at this point, like super late.

2:17:43

And I also wonder the things we discussed just a minute ago around personalization and some of the moes that are that are going to play.

2:17:52

Also, by the way, remember this is a new era of experiences that is all about data and Apple's always been all about privacy.

2:18:00

So, Apple in some ways as a policy has done everything to make it impossible for others to get others data.

2:18:05

Y and here we are in a world where you know that's what's going to enrich the experience we have from AI tools.

2:18:11

So, I think it's a it's a different Do you think that Apple do you think that Apple will end up looking really smart on privacy?

2:18:18

Like we're in a very chaotic time where people will let a new software, you know, company just have full access to visual screen recording. Record my screen.

2:18:29

That's like a okay thing now.

2:18:31

And I'm even surprised at this point that we haven't I I can't remember a major incident of a model producing private data in response to sort of like a a general query.

2:18:41

I've heard about little anecdotes here and there, but nothing really.

2:18:45

You can imagine a world some days where you know people get their kind of totally um lines crossed and you ask for you ask about some some you know acquisition for example and somebody at some point dumped in.

2:18:57

We even tried to get ChachiPT to guess a picture that was from your own house and it was and it was smart enough to say, "Hey, you're maybe trying to spy on someone, so I'm not going to do that."

2:19:08

Even though Yeah, but I could I could it would it would basically gave me like the exact description of it without giving me effectively the street.

2:19:15

So, it knew it knew not to step up the line. I I don't know.

2:19:17

Anyway, on privacy, I mean, it's a great question.

2:19:21

You know, I always go back to first principles on this one and I say to myself, you know, first of all, what do we know about the next generation?

2:19:27

They seem to care less about privacy than the generation before them. Yeah.

2:19:30

Um, you know, number two is we're we're willing to trade a lot for less friction in our lives and it seems like people are willing to always click accept or yes or yes or yes, you know, again, just to be able to have a frictionless experience in a product.

2:19:45

Now, I think you're surfacing the point that very, you know, we we don't oftentimes realize like how much we're giving over um in those instances.

2:19:55

And I think the world of AI will make that very apparent to us because we'll start getting these personalized experiences.

2:20:00

We're like, how the hell do they know that about me, right?

2:20:04

Um but I don't know, like there's also part of me that says that the best technology takes us back to the way things once were, but with more scale and efficiency.

2:20:12

Well, the way things once were hundreds of years ago is we were known.

2:20:16

Like everywhere we went in our small towns, we were remembered. They called us by name.

2:20:19

They knew our kids' names.

2:20:21

They knew our favorite cut of the butcher.

2:20:23

Like you were kind of known.

2:20:24

And in some weird way, we're being brought back to a world where we're going to be known again.

2:20:28

Um the question is we want to know how we're known.

2:20:31

And and also we don't want to be known by people that we don't trust. Yeah. Yeah.

2:20:35

Yeah. Yeah. there there is kind of this interesting economic uh dynamic where there's almost like a de facto bug bounty for privacy in the fact that if a company like Apple has a privacy fi fiasco that could wipe off hundreds of billions of dollars of market cap and so they have this massive incentive to invest to not have these privacy fiascos

2:20:57

the data to leak and so you have kind of this massive economic capital cannon towards let's secure the public clouds and So uh that my one of my former colleagues was making the point that um in terms of open- source AI versus closed source AI um oftent times it's actually better to trust a hyperscaler with your data that because it's harder to break into an AWS data center than it

2:21:22

is to the on-rem server that yes you're running it but you're the only security guard and what happens if someone breaks in and just takes the rack like I'll tell you what though like here's a bullish case for Apple would be that models are all going to be local you know x number of years the most power like if you look at the performance of of LMS right there are these small LMS and there's these ones that run locally on

2:21:44

on devices and the the the the delta between those and top LMS is of course decreasing um and so as chips get better and LM run locally you can imagine that all of your data can actually be stored locally in a super encrypted way all these local models can operate to answer all of the questions you have can search the internet when it when is necessary. And maybe we all opt to this like super

2:22:06

And maybe we all opt to this like super private AI world.

2:22:08

Maybe for all we know, Apple's optimizing for that flag that they know the puck is going to, you know, and they're going to launch who knows how many years from now like 100% local AI experience that is world class with zero privacy considerations or or risk rather. Yeah. Yeah. Yeah. Yeah. Yeah. That makes no sense.

2:22:26

Uh can you talk a little bit about knowledge arbitrage?

2:22:28

like these models, we've gone from uh you know, massive databases of facts and so there wasn't as much incentive to just be a the the the person that memorizes all the facts because you can just Google it on your phone.

2:22:42

Now we're in this age of even more significant knowledge retrieval intelligence potentially to chief meter if we can call it intelligence.

2:22:49

Um what is knowledge arbitrage? like what? Yeah.

2:22:55

I mean, it's funny like when I think about the term knowledge arbitrage, like I'm actually brought back to um and I think this is very relevant for like people who are listening to us or kind of earlier in their careers right now and figuring out like how to plot their path forward.

2:23:06

You know, you go back to the early 2000s and the people stood Twitter and social media and things like that were getting hired by like CMOs of Fortune 500 companies to school them on what the heck this thing was and like how to have their brand participate.

2:23:22

And it was really looked upon as like this complex crazy thing that every leader in in in in corporate America felt they needed to understand.

2:23:31

And so there's this moment of knowledge arbitrage where people who were like, you know, in their late teens, early 20s who were deeply natively familiar with this stuff called social media could just like school the people who had no clue. Here we are again.

2:23:43

You know, you have the leaders of all these Fortune 500 companies saying, "Oh my gosh, like we have to refactor how we work and every function is going to operate differently with AI, but we don't even know like when to use chat GPT.

2:23:54

We don't even know what a prompt is and like how does this stuff even work?"

2:23:58

And so once again, these like very young people who got through college using chat GPT and talked to chat GPT about their boyfriend or girlfriend issues or whatever else, like it's native to them.

2:24:10

And so I do think this knowledge arbitrage moment, you know, is here and the windows open right now.

2:24:13

Yeah, it's funny that there's this massive fear from from young people around how the job market is evolving.

2:24:19

Are jobs getting killed or whatever.

2:24:21

Um, and at the same time, yeah, it it feels like social media didn't reinvent every part of a company.

2:24:29

Like it it sort of massively changed marketing and how you should focus marketing dollars and how you should think about building brands and all these things, but it wasn't something that that changed internal comms like you're talking about with like collective memory.

2:24:42

It wasn't something that changed a certain aspect of the business like compliance.

2:24:46

It it didn't change, you know, it wasn't the sort of like full stack transformation.

2:24:52

And and for that reason, it creates more opportunity than the social media wave to just get good at using LLMs and and agents and whatever whatever other tools you have and then use that.

2:25:02

I mean, we the the the last person that we hired was somebody who who vibe coded um uh like a guest directory for us and they did it last like Friday.

2:25:11

Last Thursday and then we hired them that and and then we saw it like Friday.

2:25:18

We they started on Monday. came on.

2:25:20

Yeah, they came they did on Thursday, they came out on Friday and we had them start and just by demonstrating the ability to leverage these tools and create a product that was a V1, but it was a solid V1 and it was just a super easy decision to be like, "Yeah, you should join the team."

2:25:34

So, shout out shout out to Adam. 48 hours work though. That's like incredible.

2:25:37

Um, so and by the way, that's changing the way product is even done.

2:25:41

Like I I'm so used to a world where you concept, you do like a sort of you know product scoping session, then you have the designers work in uh a product like Figma and make prototypes and then engineers don't even see it until the prototypes are locked and then it's like redlinined and engineering and start to like you know now it's a different world, right?

2:26:00

Y it's like we need we need we need this to be done.

2:26:03

You kind of vibe code it out in parallel.

2:26:06

A designer says okay let's how to finesse it.

2:26:08

here's how we can maybe change that, make that more accessible to more people.

2:26:11

And then you just deploy and test and iterate.

2:26:13

It's a different it's a whole different product stack to some degree.

2:26:17

And that's why I always say the best talent these days is like a collapsed stack talent strategy where you hire people that have exposure to different parts of the stack, whether it's engineering and design or design and copy or product and design because you're just trying to collapse the stack with the types of people you have.

2:26:33

So you can leverage these tools, you know, efficiently.

2:26:37

Can you talk a little bit about agency?

2:26:39

Um, it's it's an interesting concept because we don't have like a eval for it.

2:26:43

Uh, in terms of the LLMs, uh, we're we're we're you know destroying all the benchmarks in math and IQ.

2:26:52

Um, but the models don't seem to have valition and yet the trend is around agentic applications.

2:26:57

We're trying to give them agency.

2:26:59

it still seems like uh some there's some sort of combination of uniquely human traits that uh seems to be increasingly valuable.

2:27:07

How are you defining it right now?

2:27:11

Well, I think that when you talk to when you talk about sort of agentic workflows and the the role, you know, the role of agents in the future, you know, and I think about it every company, you know, I'm calling companies these days in my mind cognos like cognition driven businesses where it's ultimately inference in the center, right?

2:27:27

And there are these the functions of a company which were once accounting and legal and design and like all these different functions are going to be AI tools that are running you know AI agents basically that are running that function or collection of agents doing different aspects of the function which then begs the question of what's the role of the humans.

2:27:46

I think we are the orchestration designers and orchestration engineers.

2:27:49

We're like orchestrating how these agents work and how they work together.

2:27:53

And we're also developing enforcing the rules by which they work because remember these agents are told what to do and they're rewarded based on doing it.

2:28:02

They have to be working within a subset of rules that um that need to be administered and enforced to some degree by humans.

2:28:08

So I you know so I I start there and then I start to think okay so what are the functions of every organization going to look like?

2:28:15

you know what and then that dictates like what kinds of tools or agents are empowered to uh quoteunquote take agency in those functions.

2:28:22

But I also want to say that when you say agency at first I think of like the human, you know, the the human getting a got it like we gota dude we got to we got to exercise our agency and our tastes more than ever before these days.

2:28:37

Um and the the the years the days of us kind of getting a prescribed job function and sticking to it that is like the deathbell of a career these days. Yeah, totally.

2:28:49

As soon as it can be defined, it can be reinforcement learned against.

2:28:52

Were you were you surprised at all about this the the concept of taste coming into the the the uh discourse the Silicon Valley discourse?

2:28:59

It feels like one of those things.

2:29:01

It actually reminded me of when venture capitalists discovered the creator economy in 2020 and 2019, but it was a trend that had been happening for like a decade at that point where people were creating content online and turning it into a business.

2:29:16

And then all of a sudden, people I think saw a statistic that was like, you know, look at this, you look how fast this category is growing.

2:29:22

We should invest a bunch of dollars there.

2:29:24

But in many ways, I feel like taste has always been a key part of um our industry.

2:29:28

And and if you look at a lot of the best companies, they don't all look the same, but they have people that run them that have um taste that that sort of gets applied in in many different ways, whether it's hiring all the way through obviously the the visual side.

2:29:47

you know I am brought back to a uh just earlier in my career you know it was all about what skills you had right and and the resume would always were you good at PHP or JavaScript or could you do wrote code in Python or whatever the

2:30:03

case might be come from a world where skills like were the hardest things to achieve and the most differentiating things for humans right in in a project now as a lot of the skills have been offloaded to compute you know, now it's like, well, what's left? Like taste is actually one of

2:30:19

Like taste is actually one of those things that is definitely left, right?

2:30:25

And so I think that the fact that everyone's sort of focused on on on taste these days is more of a commentary on how less focused they are on skill. Yeah.

2:30:34

And how much confidence they have in all these models and coding tools and everything else.

2:30:38

Can taste be taught though? That's the question. Skills can be taught. Taste taste be taught.

2:30:42

Like let's you know can taste be taught is like a thing I think about and debate all the time with with friends. You know what is taste?

2:30:49

Gosh it's like the human experience. It's childhood traumas.

2:30:51

It's mistake of the eyes. It's judgment.

2:30:54

It's knowing how many things to see before you make a decision you know but it's also knowing how to choose something that isn't so on the nose but like leaves something for the imagination, you know.

2:31:07

It's knowing where people are going as opposed to where people are.

2:31:11

Like I think it's all of these factors that are so critical whether you're making a product or making a marketing campaign or a film or whatever the case might be.

2:31:19

And I just, you know, I I I think that hopefully we'll just overindex on human experience in order to achieve taste.

2:31:27

Yeah, there's Yeah, it almost feels like just independent thinking um confidence like you can maybe develop No, but it's independent independent thinking that elicits a collective response that you want in some ways, right?

2:31:40

I mean, I I think of this in the context of how companies get attention.

2:31:44

There's a lot of different ways to get attention.

2:31:46

Some some some ways are are ta, you know, some ways are tasteful and elicit, you know, a positive response.

2:31:52

other others get, you know, a lot of attention, but but a sort of visceral negative reaction and and taste in the context of social media algorithms and timelines is like such an important um question because it's really easy right now to do to instantiate something but not to Yeah, it's fascinating. Yeah.

2:32:13

Taste taste too in the context of AI uh slop, right?

2:32:17

There's tasteful, there's tasteful.

2:32:17

I always keep coming back to the Harry Potter Balenciaga video.

2:32:20

I feel like that was, you know, it it had the aesthetics of AI slop because it was AI generated with it and yes, but it it had the it had the touch of a human to think of combining those two kind of completely unrelated disperate ideas and when you put them together it was something that you had to watch.

2:32:42

And by the way, that's perfect evidence the fact that you're still citing that despite how many months if not years of content generation has happened since. Yeah.

2:32:51

Yeah. It shows you like the taste still stands out and that's why you know people are like oh my gosh content is commoditized like everyone can do everything now uh oh my gosh this is horrible for Hollywood my view is the opposite like in historically when

2:33:06

anything becomes commoditized whether it's shoes handbags liquor whatever case like that's LVMH like LVMH is in all those businesses but they're doing the higherend meaning infused more scarce version of that thing that's available to anyone Yeah, you're now content is commoditized

2:33:24

given all these new tools and I think as consumers of content we are going to seek more scarce meaning infused human you know brand signaled versions of content to fill our attention and time and so I think that's great example you know it doesn't matter how it was made

2:33:39

it matters you know whether there's meaning in it I even knew how the tools I I I knew the tools that were used to make the Harry Potter Balenciaga thing but I couldn't come up with a unique idea that would go viral and so I went to CHPD and I said, "Here's why this worked. It worked because it was

2:33:53

It worked because it was inspired and it combined two things that were so desperate.

2:33:56

Think of another thing that could be iconic like that."

2:34:01

And it couldn't do it at all. It came back. Yeah. Yeah. Exactly. Exactly. It wasn't there.

2:34:05

I you know that that inspiration still needs to strike.

2:34:07

Uh speaking of Hollywood, did you see Mountain Head?

2:34:11

Uh the new Jesse Armstrong film. Have you seen it yet?

2:34:14

I haven't seen Mountain Head yet. No. Okay.

2:34:17

You should you I mean you I if if you don't enjoy it uh they're they're really cooked.

2:34:21

But um it's Jesse Armstrong from Succession making this film.

2:34:26

The the high level concept is you know some podcast. Yeah. Yeah.

2:34:28

You could you could say that.

2:34:31

But uh the thing that the thing that I wanted to get to is that basically the overarch part of the overarching narrative is that deep fakes have gotten so good that they're causing global chaos because people don't know what's real and then they're seeing video and and sort of acting on that video.

2:34:44

Uh I wanted to ask you in that context or or or just generally about the progression of video models and how you're thinking about you know if if V3 uh you know what do you expect from from things like V4 and you know new runway models and any you know I'm assuming you're looking at everything internally at at Yeah.

2:35:03

Let me let me just well two comments like one on video models and then deep fakes real quickly on video models.

2:35:09

I mean this is like a consistent slap a hand game, right?

2:35:13

where oh my god this is the best model and then V2 comes out and then Sora and then runway and then the V3 and it just it just keeps piling up.

2:35:18

This is great for anyone who makes stories because these models are becoming better and increasingly commoditized.

2:35:24

However, um you know it's would I want to be the model you know that's competing in that increasingly commoditized and not as great you know quality sort of vector probably not.

2:35:35

So that's comment number one on the deep on the deep fake situation.

2:35:38

You know, it's interesting like these new these new websites that are coming out where um where uh you have these like anyone can make a deep fake with Trump saying whatever.

2:35:46

You know, I actually think they're playing a secret value to society by inoculating all of us. Totally.

2:35:52

We all get a fake Trump said something crazy video tomorrow and we're inoculated from the fact that we should no longer trust what we see.

2:36:00

That we should instead of going from a world where we would trust but verify, go from a world, you know, to a world where we verify then trust.

2:36:05

Like that would be good for humanity.

2:36:07

So, I'm like I'm actually, you know, for that inoculation because I think I think that uh I think that we need it and we're gonna want to know where where stuff came from.

2:36:18

In a weird wayn it didn't happen.

2:36:20

happen. No, in a weird in a weird way it it it might save legacy media because if legacy media orients around uh it orients around like if CNN were to say we are you know there's a bunch of the you know you have uh usernames like autism capital that are sort of de facto

2:36:38

news on X right these are accounts that get billions of impressions and they act as as you know news content but if CNB you know CNBC and CNN and other services can really orient around we did the you know we were late to the punch on this

2:36:55

but we did the work to you know verify that it was real it actually might save totally and there's credentials now there's metadata through things like content credentials that go into assets that are made on certain cameras and edited in certain software and you know

2:37:08

and whether it's TBPN or CNN or anyone else can surface that information in the reporting and say we verify this is you know done by the so- and so and was edited by so and so and I think that adds to uh a layer of what people are going to need and want in future. So, So, thanks so much. Yeah.

2:37:23

Uh I wish we had a I wish we had 90 minutes. This was super fun.

2:37:27

We have to come back soon. Yeah. To be continued.

2:37:29

Have a great rest of your day. We'll talk to you. Bye. Cheers.

2:37:30

Uh really quickly, let me tell you about Bezel. Go to getb bezel. com. Your bezel concierge.

2:37:35

He's available now to source you any watch on the planet. Seriously, any watch.

2:37:39

And we have our next guest already in the studio.

2:37:42

Roy from Bloomberg Beta coming in to talk about his latest fund raise. How are you doing, Roy? Great to meet you.

2:37:47

Fresh capital in the bank or committed or something like that.

2:37:51

How much how much capital did you raise? Talk to us. Okay.

2:37:57

How much you hit it 75 times for 75.

2:38:03

You know, I'll take one customer sale over fresh capital in the bank.

2:38:05

You know, the old capital formation is is the highest calling of man. It is. It is.

2:38:12

say two guys who do not intend to form their own capital unless you That's right. That's right.

2:38:18

But we we're in the business of covering formation and celebrating it. But congratulations.

2:38:23

Um what are you most excited about?

2:38:25

Where are you planning to deploy this?

2:38:27

What is uh how is the money burning a hole in your pocket? Yeah.

2:38:32

So we 12 years ago started this firm to say we're going to do day zero investing and startups and I'll just give the context because the answer is going to be the same thing.

2:38:42

startups that future our future of work oriented.

2:38:45

Our bet at the time was our personal lives have changed a lot. Our work lives have not. Maybe that'll change.

2:38:52

Like people were still using Lotus Notes for email and uh and now on our fifth fund we are doing basically exactly the same thing.

2:38:59

The craft of day zero work closely with the founder and what's burning a hole in my pocket is continuing to do that you know and I'm looking at our fund one companies and feeling like they're still midway through the journey.

2:39:11

Replet, Flexport, Campus, you know, um, we love these companies.

2:39:18

Many, most of them have been on the show. Fantastic companies. Yeah. Yeah.

2:39:22

No, I've loved watching them.

2:39:23

That's part of what I love about the show.

2:39:24

What, uh, what percentage of funds, venture funds make it to fund five?

2:39:28

That's an excellent question. It's got to be like 5%.

2:39:31

But I always feel like that's sort of like those stats about what percentage of startups like raise their series B.

2:39:37

It's like if the starting denominator has a lot of meh in it.

2:39:42

Like I think to me the more interesting question is who gets there you go.

2:39:45

Who gets to a There you go. Hot off the press.

2:39:47

I printed So I printed your your post because it appears that you printed your post.

2:39:53

I don't know if you can see this, but uh you print meta.

2:39:57

It's a print I think a LinkedIn post and you marked it up.

2:40:00

You said today we're announcing our next fund, our fourth.

2:40:03

And you just crossed it out and put fifth.

2:40:05

And I and and we respect printing out posts here.

2:40:08

So I just wanted to The idea was inspired by this thing I stole from Congress when the Republicans blocked a Democrat Supreme Court nominee and then it went around the other way and they literally just crossed out the names and put in like Schumer. It is the same.

2:40:24

So I think the more interesting question is who gets to a fund five or whatever fund size without trying to gradually expand AUM?

2:40:30

Like it seems like so many of the VC firms out there and we love working with them are just in the AUM expansion business. Yep.

2:40:37

The big scare me personally.

2:40:40

Uh I I looked it up here.

2:40:40

According to Chad GBT, there's probably a 50% chance it's hallucinating, but it's estimating at less than 5% based on pitchbook and Cambridge Associates data.

2:40:49

I mean here here you say you're you aspire to be the most transparent investors.

2:40:54

What does transparency mean in the context of a venture fund? Yeah.

2:40:57

Do you tell the founder, look, we clocked you at about a 15% chance of success.

2:41:01

It's a bet we're willing to take.

2:41:03

We do try to tell them how exactly we're thinking about it.

2:41:05

But here, look up, go to our website right now on those two laptops you got in front of you, and then you'll tell me what but which is to say when I was a founder, so before this, I started a company in games. Yeah.

2:41:15

And you know, you drive down to the 280, end up in an office on Sand Hill Road, and in the first three minutes of the meeting, the person be like, "Oh, but you're not a fit for us. We don't do this."

2:41:26

And it's like, well, why on earth do we just do that? And we are an attacker.

2:41:29

We were coming into an established industry.

2:41:31

And we just asked, are there things the industry does that we can flip the bit and do the other way?

2:41:36

And so the industry seemed very opaque at the time.

2:41:39

It's a lot less true now.

2:41:39

And we're just like, can we be as transparent as possible? Can we put in valuation?

2:41:43

Can we put in diligence questions?

2:41:44

You can actually get our long form actual deal documents from our website.

2:41:49

And the point of it is not transparency for transparency's sake, although that's a very Bloomberg idea about trans.

2:41:54

It's just Founders are our customers.

2:41:56

We want them to not waste time guessing what we do.

2:42:00

And so if they can disqualify out by seeing we don't do that thing, great. Better for everybody.

2:42:05

We're big fans of Bloomberg.

2:42:07

We read a lot of Bloomberg pieces on the show.

2:42:09

What is the actual relationship subscription yet?

2:42:11

No, we got to get one in.

2:42:13

This is This is my go-to terminal every day, a Wall Street Journal, but uh we we we do have subscription and we've had a bunch of Bloomberg folks in the show.

2:42:23

You're like the fifth Bloomberg affiliated person.

2:42:26

We got Joe Weisenthal, Tracy Aloway, uh we got Sharon Gafari coming on the show.

2:42:31

Bigger brands than me, one it all. Yes.

2:42:32

Uh but what is the relationship between the fund and Bloomberg as a whole?

2:42:37

Obviously, uh Bloomberg does a ton of different stuff.

2:42:39

What does that look like and how is it evolved?

2:42:40

The company is the LP in our fund. Period. End of story. Full stop.

2:42:44

We are not a strategic investor.

2:42:45

So unlike a bunch of other corporate back funds, we're not trying to find some startup that's going to be a Bloomberg partner.

2:42:50

Bloomberg wanted to understand what was happening in the world of startups.

2:42:53

The argument was best way to do that is give startups what they need which is just money.

2:42:57

Yeah, that makes a lot of sense. Cool.

2:42:58

Um uh talk to me about deployment of the fund is is 75 million that's a lot of smaller checks.

2:43:06

Are you holding back some for PRAA and scale up like uh you know the line about like tell me the fund size I'll tell you the strategy.

2:43:13

Part of the reason why we've kept our fund size where it is is we want to be as early as possible.

2:43:18

So I can't remember the exact number but it's something like most funds their first check ends up being something like 75 basis points of fund size on average and we end up a little bit around there slightly bigger.

2:43:27

Um we do you know we reserve for followons but then we also have an opportunity fund because what we realized is we wrote some big checks into from our core fund into some of our winners.

2:43:38

We wrote a big check into Replet at one point whatever you know company newfront and it's like well if we're going to do that we might as well have the capital to do that reliably so we've got an opportunity fund. Yeah.

2:43:50

At the early stage uh are you are you trying to pick a winner and then not invest in competitive companies like how do you think about that?

2:43:57

So very old school on all this stuff.

2:43:59

My view on competition is competition is in the eye of the founder. Mhm.

2:44:03

Like I have a attitude on this which is if I back you I want you knowing I have your back not that I'm thinking about which of your competitors to introduce to somebody.

2:44:12

And so any founder we invest in if they tell us that a company is competitive we won't invest in that company.

2:44:17

still happens like you know companies competitive and we got to work it out.

2:44:21

But that's the principle but yeah but yeah but that's not on you.

2:44:25

Um driving the news cycle this week you got WWDC uh Apple kind of pulling it the news cycle.

2:44:30

Well, it drove the news cycle kind of by necessity, but it kind of like if you had said, "But nothing happened," would we have just nodded along politely?

2:44:37

Well, our our in our our intern Tyler spent hours in setting it up.

2:44:43

Well, yeah, he assembled the first Americanmade iPhone yesterday.

2:44:45

Today, he installed arguably a harder challenge installing uh iOS 26.

2:44:52

But I mean there is a there is a bit of a narrative for startups there in the sense that if Apple is truly pulling back and not going to steamroll the the the startup developer community in terms of in AI based apps that could be a a potential boom for you know we could see another rise of a mobile era where AI companies are building on iOS in mo in a little bit more friendly territory than totally than it's been in the past.

2:45:18

Obviously, there's the Fortnite decision and discussion around the app store.

2:45:21

Um, what are you seeing that's interesting or or just what else is driving the news cycle for you? Well, no.

2:45:27

So, I I do think look, Apple has to be an attacker on AI.

2:45:30

You've pointed out the way that the privacy first philosophy makes it a lot harder for them to do AI and AI developers who go there talk about running into that internally.

2:45:39

You know, all the big tech companies want to be the platform on which everybody else share crops.

2:45:43

And at the moment, that's open AI and anthropic.

2:45:47

It's like you have all these fast revenue growth crops is such a savage but real way to describe a 30% cut. It's just 30%.

2:45:54

Just give me 30 30 of course naturally.

2:45:58

But the market didn't exist but for that um and and I think they're going to try to figure out can they disrupt some other part of the ecosystem.

2:46:06

I feel the same way about the scale AI acquisition which is Meta has to attack.

2:46:12

They need a layer that they can control that everybody else depends on and this looks like their play at it.

2:46:18

The other thing I think is interesting about that that I've been thinking about is how many of these big AI companies have effectively been acquired in ways that the government doesn't get to approve.

2:46:27

It's, you know, the big talent acquisitions.

2:46:29

When I saw this, I was like, that looks like an acquisition the FTC doesn't get to approve.

2:46:32

And so, I don't know if that's the motivation.

2:46:36

Have not spoken in any of the parties.

2:46:37

We're not in scale AI, but my sense is you're basically seeing the Game of Thrones play out, but the government is one of the houses.

2:46:43

What's very interesting about that is that we are Yeah.

2:46:46

Lena's gone and we're in a different regime, but it's the same thing.

2:46:49

Let us let let us do some deals.

2:46:52

Let us let us do some some M&A.

2:46:52

Just just $28 billion acquisition.

2:46:55

Just let us sneak it sneak it in. It's fine. Let's get it by. Just one.

2:46:59

Let's open Let's get the M&A window open.

2:47:00

Master I mean the other thing I say is when was the last time you heard a big tech company buy a company for $80 million?

2:47:07

It felt like that used to happen all the time. All the time. Yep.

2:47:09

And now it's a lot less common for they took that from us. They took that from us.

2:47:13

I think I feel the grief. Yeah.

2:47:16

I mean, there used to be there used to be a a really great outcome for a lot of folks where if you're a founder and you start and you still own 20 30% of a company and you sell it for 80 million, like that's that's a house in PaloAlto and kids and generational wealth in some ways.

2:47:30

Um, and yeah, that that has gone by the wayside.

2:47:33

I don't exactly know why because those seem to be easier to get across the finish line from an FTC perspective, but I guess folks just Yeah.

2:47:41

At what point does the FTC just say like, "Look, we know we can see what you're doing." Yeah.

2:47:45

I mean, also 15 billion on this company for and and the CEO no longer works there. Works there. Yeah.

2:47:52

I mean, the flip side Yeah.

2:47:52

I mean, the flip side is like when was the last time a company was valued at 80 million because every company seems to go straight straight from 5 million to 500 million in two days.

2:48:03

And so I I don't know where you're getting 80 million like that.

2:48:08

That's just hard to hard to find.

2:48:10

Uh I do I do have a question for you.

2:48:12

I don't even know if you can speak to this, but there's a lot of companies that are thinking about plugging into the terminal.

2:48:16

We see what Perplexity is doing.

2:48:19

We see uh a bunch of AI agents for financial clear perplexity is trying to disrupt trying to disrupt the terminal.

2:48:25

Uh are you looking at that space?

2:48:27

Would that be too competitive?

2:48:29

Uh is there anything interesting there that you've seen or or or heard rumblings on the other side of the of the fence?

2:48:34

I can't speak to what's competitive with, you know, they're my LP, so speak for their business strategy.

2:48:40

What I will say is when you when you run a firm that's got a name of another company on it, my guess is the Google Ventures GV guys have this too.

2:48:47

Every pitch that's like we are going to be the Bloomberg for X lands on my desk.

2:48:51

Y and maybe not everyone, but many of them do because they're like, "And how amazing would it be to also have Bloomberg as an investor?" Yeah. Yeah.

2:48:56

Almost all of them seem to misunderstand to me what the value of the Bloomberg terminal is because it packages data. Yep.

2:49:03

Community with a messaging system outside in perspective news etc.

2:49:10

I mean that's just some of it and it's more than just let's display some data.

2:49:14

So everybody who's trying to disrupt I think is in for a surprise when they realize what an ecosystem it is. Yep.

2:49:19

I I think this happens constantly especially in media.

2:49:24

People see a media product, they like it, they don't understand why it's successful.

2:49:29

They try to reverse engineer it, but if you don't understand the why, you're never going to be But can I ask you guys though for you on you tried before, what's your hypothesis on your why of why this has been so successful for you?

2:49:42

The main one is that um most people in tech media have done it part-time historically and we decided to just kind of burn all of the ships and make this the full-time thing.

2:49:53

We got some great advice from David Senra, the host of the Founders Podcast, another full-time media creator, and he basically just said, "You guys have something that's that's working.

2:50:04

You should go 10 times harder at this."

2:50:06

And what's interesting, and we also enjoyed it a lot.

2:50:10

it a lot. we liked talking about business together which was kind of the foundation but but yeah the idea that there's a lot of there's a lot of technology podcast there's a lot of business podcasts if you actually drill down and you look at how many people are actually full-time just making media

2:50:27

it's very very small it's pretty small and the nature the other thing is the nature of by taking something way more serious than anyone else it can sort of morph and evolve in the way that the show has from us two and a printer My my my viewers uh uh look on this is it's it felt I'm obsessed with Hamilton for a variety of reasons. One of the reason

2:50:47

One of the reason I'm obsessed with it is nobody would have said one of the great media properties of the last 10 or 20 years would be a musical and so it defied the genre through intensity and seriousness and you feel immersed in a world and like before the show they used to go out on the street and do some little diddy or something like that.

2:51:03

Oops, my camera just froze. Okay, there we go.

2:51:05

And uh and you guys have that same kind of immersion.

2:51:08

I teach this class at Berkeley on the structure of the media industry.

2:51:11

I will be inviting you as guest speakers. Amazing. We'd love that. Let's do it. Not when you're live.

2:51:14

You I grew up in Berkeley.

2:51:16

The other thing that you've realized is it's cheap to start a media company.

2:51:20

So, as long as you don't get too big for your britches and figure like a ventureback company, your financial aspiration, maybe this is yours, is to create one of the most financially successful businesses in the history of capitalism, which is in VC as much as an $80 million exit along the way can be magical for everybody involved.

2:51:35

That's the hope is, you know, is that you can produce something wildly valuable and make some money. Yeah. Yeah. Exactly. Yeah. Fantastic. This is great.

2:51:44

Well, we'll have to have you back. Congratulations. Congratulations, guys.

2:51:47

Appreciate what you're doing.

2:51:47

Keep us all immersed in it. We will. We will come back soon. 75 times. Yeah, we'll hit it.

2:51:55

We We'll wait till after 73 more to go. 73 heads. Done.

2:51:57

I'll come in and bang on that. Have a good one. You're the man. We'll talk to you later. Bye. Cheers, Roy. Bye.

2:52:03

Up next, we have the founder of Metropolis, Alex Israel. He's in the studio.

2:52:08

But really quickly, let me tell you about Wander. Find your happy place.

2:52:11

Book a wander with inspiring views, hotel, great amenities, dreamy beds, top tier cleaning, and 24/7 concier service.

2:52:16

It's a vacation home, but better.

2:52:17

Welcome to the stream, Alex. How are you doing today? Good. How are you guys doing? We're doing great.

2:52:23

We've been having an awesome show.

2:52:24

What's it like to land on the the CNBC list?

2:52:26

You guys are on there, right? You guys are on there. Congrats.

2:52:30

I mean, that's got to be your guys' biggest accomplishment ever.

2:52:33

There's nothing there's nothing that there's nothing that tops that. No. No. No. I'm kidding.

2:52:37

It's a I mean, anytime, you know, I know the CEOs that land on these lists, they're like, "Cool."

2:52:42

You know, they'll post about they'll post about it, but it's like, "You get back to work." Yeah, of course. Yeah.

2:52:47

It's uh Look, it's flattering.

2:52:47

I just like being in the company of, you know, Open AI and Yeah.

2:52:50

You just got to get back to work. Yeah.

2:52:53

The first the first CEO to be like, you know, normally CEO say job's not finished.

2:52:56

In this case, job's finished. No, we're done. We're done. We're just done. We're done.

2:53:01

This was the whole goal the whole time. And now we can retire.

2:53:05

It's kind of like an exit, but better.

2:53:07

Yeah, it's definitely better. Definitely.

2:53:09

Yeah, I can pay my college.

2:53:10

It doesn't pay the bills, but you know, you can send it to a family member and maybe they'll be impressed, you know. Yeah. Yeah.

2:53:16

You'll get some text messages.

2:53:17

Uh anyway, uh c can you kick us off with an introduction on on on the structure of the company and what you guys are building because it's super interesting and I I know we can go a bunch of different directions, but I'd love to get your kind of uh ground setting first. Yeah, of course.

2:53:29

Um, so you know, traditional in a lot of ways startup story.

2:53:34

Founded the company in 2017 and now are one of the fastest growing payments companies in the United States.

2:53:41

We talk about ourselves externally as an AI company for the real world.

2:53:45

But it's all about how you leverage computer vision and artificial intelligence to create next generation payments and commerce everywhere you go.

2:53:52

Whether it's a retail environment, a car wash, or a gas station, how do you just walk in or walk out or in this case drive in and drive out? That is fascinating.

2:54:02

Um, talk to me about the strategy of actual uh building the business and uh acquiring assets and and and actually getting like the go to market motion is different here, right?

2:54:15

Yeah, it was very different.

2:54:15

I mean, look, we started very, you know, I don't know, stereotypical.

2:54:19

We raised the, you know, I guess large, but $20 million seed financing, $40 million series A.

2:54:23

We hit the wait $20 million seed in 2017 that that that that's more than bigger than a mango seed which which started to become popular a bit later.

2:54:34

Uh I don't know was that a water watermelon seed round?

2:54:38

Um what what what what was the catalyst there?

2:54:40

You just you had a bunch of experience in the space and and so people had a lot of confidence in you or why why did you need 20 million at the time?

2:54:48

Yeah, it's a good question. I don't know.

2:54:50

I guess serial tech entrepreneur u I don't know.

2:54:51

My last series A in my last company was 3.

2:54:53

series A in my last company was 3.5 million and I you know I thought I was rich you know and then you know $20 million seed financing but look we knew we were tackling you know the first vertical that we entered was mobility and we wanted to go after the parking industry and we wanted to deploy

2:55:08

technology in the parking industry and we knew that there were a number of companies whether it was standard cognition or Amazon go that were leveraging computer vision to create these next generation experiences and we knew it would take a lot of capital and we kn it would take while a while to penetrate the market. So, we wanted to

2:55:23

So, we wanted to make sure that we had the capital in place to to really go after the market.

2:55:29

Talk about your position in in parking uh today.

2:55:32

It sounds like you're you're thinking about other categories already.

2:55:36

At what point did you decide that you could be thinking about other other applications of the the tech and infrastructure?

2:55:41

Yeah, it's a good question.

2:55:43

You know, I'd say so after our series A, I would say we hit product market fit and unit economic fit really quickly.

2:55:49

quickly. I'd say the problem was we hit a wall with our go to market and that was you know at the time we were scaling our technology to a number of the largest asset owners across the United States and we'd effectively knock on their door asked to take the keys for the parking experience to their $200

2:56:05

million development and they were like cute startup come back in 50 years so we realized we needed a different go to market motion so we shifted strategies and we invented what we qualified internally as a GBL which was this idea of a growth buyout could we raise venture capital dollars and could we acquire old world businesses? So, we

2:56:22

So, we started rolling up oldw world parking operators that are, you know, the cost plus staffing agencies that were evido positive that run parking across the United States.

2:56:31

And we kept rolling them up to a point where now we're the largest parking operator in the United States. It's amazing. What uh Yeah. Yeah.

2:56:39

What is the structure of the of the parking market generally?

2:56:42

I feel like uh I I live in Pasadena.

2:56:44

When I drive around, some of them are cityowned, some of them validate, some of them don't.

2:56:49

It feels very fragmented.

2:56:51

It I I couldn't name one unified brand, but is the is the structure of the parking owner market as fragmented as I perceive it to be? Yeah, completely.

2:57:02

It's I mean, it's as fragmented as the real estate owner market, right?

2:57:04

People that own real estate own parking and there are, you know, hundreds of thousands of real estate owners from a class A perspective all the way through an airport across the United States.

2:57:12

And we deploy our technology to facilitate that type of seamless experience where a consumer can just drive in, get a text message when they arrive, and get charged when they leave. Yeah.

2:57:22

Is that historically just because there's no economy of scale like there is in in real estate, or is that just because the asset class is so big that you can't possibly own it all? It's just so sexy.

2:57:35

You know, everyone drives and they're like, park it. Yes. Yes.

2:57:37

You know, it's like No, it's like the last bastion of non-institutionalized real estate in the United States. Yeah. Yeah. You're right. And it's everywhere.

2:57:45

It's 15% of the surface area of our cities.

2:57:46

And for us, it was the first touch point.

2:57:49

And to your comment earlier, we realized that if we can roll out parking and we can deploy a seam seamless payment product across parking, then we can move into gas stations and car wash and quick serve retail and then we can move past the car and into the store. Yeah.

2:58:02

Can you talk about the uh the kind of longer term vision for city parking?

2:58:07

I feel like there with autonomous cars, people are excited about maybe reclaiming some green space.

2:58:15

Whenever I see a big city and there there's just like one flat parking lot, I'm like that would be way more efficient if it was like three stories of underground parking and then a massive building on top with some mixed retail and some on the autonomous cars.

2:58:28

People like to say, "Oh, when we have autonomous cars, we'll need less parking in cities."

2:58:31

And and and I can see that in some way, but but at the same time, I'm not excited to spend every day in Whimos, effectively taxis.

2:58:44

I am excited to have my own autonomous car.

2:58:46

And the idea that I would drive into the city and then my car would just be driving around all day, like it's got to go somewhere while I'm while I'm podcasting, right? Like it can't, you know?

2:58:56

So, so it's going to be parked somewhere.

2:58:58

And so I think this sense that autonomous driving is going to eliminate the need for for parking is is um or or certain, you know, some some of the parking in in cities is maybe off base.

2:59:10

No, look, I think it's an interesting question.

2:59:12

I mean, when we founded the company, we spent a lot of time thinking about the future of autonomous vehicles.

2:59:16

And to your point, like cars are not going to circle the block endlessly looking for their next job.

2:59:22

They're going to get off the road and back onto the road as quickly as possible.

2:59:25

And that's the conversion of parking from parking lot to mobility hub you know where you can facilitate the cleaning servicing charging and deploying of vehicles.

2:59:34

I mean at this point our underlying technology enables kind of seamless I would say integration or connectivity between an autonomous vehicle and old world infrastructure.

2:59:44

I mean at this point we're interacting with millions of Americans every single day that are on our platform or interacting with our locations.

2:59:52

And I think at this point we're onboarding 50,000 Americans every single day that are signing up for the first time with Metropolis. Yeah. Yeah.

3:00:00

The idea, you know, you're not going to a Whimo is not going to have like a a a humanoid robot in it that presses the parking ticket, you know, button when it's coming in and then is like feeding the ticket back in.

3:00:12

It obviously would just happen, you know, if Metropolis can be that hub for for autonomous vehicles, that it makes makes a ton of sense. Yeah.

3:00:18

Uh talk to me about uh the like the evolution of financing.

3:00:23

you're obviously using a lot of venture capital, but I imagine that it's a certain point um you need to interface with private equity firms or banks or debt providers.

3:00:32

H how can you get creative with the uh uh with the different structuring financially on some of these larger deals?

3:00:39

And can you give me kind of like a 101 on what it what it takes to get a billion dollar deal done these days?

3:00:47

Yeah, I mean we did, you know, the last deal was a $1. 8 billion series C. Amazing. [Music] Huge. Huge. Yeah.

3:00:55

Listen, we took an oldw world, you know, hundred-y old company that was publicly traded private. Yeah.

3:01:02

And yeah, look, it's, if you look at our cap table, it's exactly that.

3:01:07

It's venture and private equity in the same rounds.

3:01:09

So, last round was Eldridge, Vista, 3L, Tamasc, Vista, BDT, MSD.

3:01:18

Um, and like you normally don't find all of those players in one, you know, party capital, but yeah, look, I think that you guys talk about this more than I do, but the capital markets operate very clearly in these very set boxes.

3:01:33

It's credit, it's private equity, it's growth, and we kind of broke through that with an entirely different strategy, which is how do you take kind of next generation technology and artificial intelligence and start acquiring old world businesses to scale into the market even faster.

3:01:45

But in the context to your question, in the context of our business, it's structured to a great extent like any series C venture company would be structured.

3:01:54

Talk to me about what the the communications challenge of taking over a 100-year-old company.

3:02:02

It feels like you're fortunate that you don't have the the the stench of maybe like, oh, we're going to buy and lay everyone off, but it is change management.

3:02:11

It is it is a new it is a new structure in the organization.

3:02:13

I'm sure there's some communication that you have to do uh when you when you buy a company.

3:02:20

What has that been like and what are kind of the best practices?

3:02:24

Yeah, it's a great question.

3:02:24

I mean, look, I think that we went from a 200 person company organically to a 2,000 person company with our first inorganic acquisition and then to a 23,000 person company um with employees in 400 cities.

3:02:41

Uh so yeah, there's massive change management.

3:02:43

There's massive internal communication protocols, but I'd say first and foremost, it's like how do we put our employees and our team first?

3:02:50

And you're right, we were lucky because this was not a turnaround.

3:02:52

This was not a structure where we're looking for cost synergy.

3:02:57

Metropolis and this strategy of taking these old world companies private was all about revenue synergy.

3:03:01

It was how can we drive more revenue to and more value not only to real estate owners but to our employees and our team members. So, it's been exciting.

3:03:09

And what we found is it's really interesting.

3:03:13

You see cultural friction on both sides.

3:03:14

You see cultural friction in the engineer that's worked at Amazon for 10 years that now works for Metropolis.

3:03:21

And then you see friction on the parking attendant.

3:03:23

But you find people that are really excited about building a hyperscaler and really excited about how they can leverage and build on the existing infrastructure of this 100-year-old company. That's great.

3:03:37

Well, thank you so much for stopping by. This is great. This is fantastic.

3:03:39

Come back on when you're uh when you have a good reason for us to hit the size gong.

3:03:45

I'm sure you'll have uh I'm sure you'll have many more in the near future. This is great. Looking forward to it.

3:03:48

Thanks for taking the time, guys. Talk to you soon. Cheers. Bye.

3:03:51

Uh next up, we have Andrew Huberman joining the stream.

3:03:56

We'll bring him in in just a second.

3:03:56

We have some breaking news, too.

3:03:59

Scott Woo has posted about uh uh the new model from OpenAI 03 price drop makes it 15 times cheaper than GT GPT4 32K the state-of-the-art model from two years ago.

3:04:12

Meanwhile, the number of use cases is probably up 1 millionx.

3:04:14

Kudos to the OpenAI team for dropping the price.

3:04:16

So, congratulations to everyone over there and welcome to the stream, Andrew. How are you doing? Great. Great. Great to see you.

3:04:23

Thanks so much for joining. Yeah.

3:04:25

What's new in your world? Uh what's new? Um goodness.

3:04:27

This week we have a big episode of the Huberman Lab podcast out with the current NIH director Dr.

3:04:33

Jay Bacharia who's a MD and a PhD.

3:04:36

A unique background because he has a background in medicine obviously the MD uh but he also has a background in economics. Yeah.

3:04:42

And um incidentally did his undergraduate masters PhD and medical school training and then was a professor of medicine at Stanford.

3:04:52

Stanford um you know he's he's Stanford the whole way and um as NIH director right he he holds a ton of power over what happens for the future of basic and clinical research and he looks at all of that through the lens of an economist um

3:05:08

but mostly through the lens of a you know public health official so it's very unique um perspective and folks on X will recognize James vocal um I don't want to speak for him and and label we have to be careful with labels, but totally anti-lockdown. I don't know. Um I don't know.

3:05:22

Um yeah, you know, you know, not not a huge fan of the lockdowns for most people, right?

3:05:30

He he does say that there are certain populations that he felt should have been uh kept indoors, but other other folks probably in his view should have more actions.

3:05:39

Well, it's a long episode.

3:05:41

I wanted to basically get a preview of it.

3:05:43

You guys focus on a couple things.

3:05:45

one how to fix the issues with science and two the importance of funding research uh both sorry basic research and then uh applied research.

3:05:54

So why don't we kind of cover a couple of those different my question was like the the narrative right now is that uh research funding is being cut like in immensely and I was wondering if you if you got a feel for how severe the cuts are.

3:06:10

Is the narrative overblown?

3:06:13

what is the balance of cuts between applied and basic research and then we can kind of go into some of the implications of that. Sure. Okay.

3:06:19

So, um there is an an upcoming vote in Congress uh in September I believe and it's on the table to cut the overall budget for research for NIH by 40%. 40. That's huge. Which is huge. That's huge.

3:06:35

I want the the budget for research at NIH.

3:06:40

There there multiple dimensions to NIH and I don't want to get lost in the weeds of it.

3:06:43

It's a you know NIH is something I'm very familiar with.

3:06:44

I was on grants panels for you know over a decade.

3:06:47

My lab was funded by NIH.

3:06:47

We could go really deep into the weeds but let's just keep it pretty simple.

3:06:51

NIH funds basic research which is research that it's not specifically geared toward understanding the or trying to solve a particular cure or treatment for a disease.

3:07:01

So think um all everything we understand about cell biology not everything but much of what we understand about cell biology was it was because of NIH funded research into the functioning of the cell over the course of you know 50 or more years and that led to important implications for treatments and cures for cancer.

3:07:18

Um do we we don't have a quote unquote cure for all cancers but many cancers now can be cured.

3:07:25

Um and to be clear these are non-commercial this is like non-commercial research.

3:07:29

So things that you know we cover a lot of yeah we cover a lot of cannot be patented.

3:07:34

So basic research is you know a laboratory uh wants to understand um how cells work, how neurons work um how the immune system functions, gut brain access um uh studies on you know um how stress impacts health, sleep etc.

3:07:48

Then the applied work is also funded by NIH.

3:07:54

So clinical trials are funded by NIH.

3:07:56

This is an enormous portion of the overall budget.

3:07:58

the exact division between basic and um clinical trial funding is hard to demarcate.

3:08:03

But let's just for sake of this conversation just agree because it's true that most of the basic research and clinical trials that are run in the United States are funded by the NIH.

3:08:14

The NSF is a separate entity, right?

3:08:17

Um but NIH is its specific goal is to improve the health and longevity of American citizens and by extension the rest of the world, right?

3:08:25

right? because it it is fair to say that while there are excellent uh you know research funding bodies in the UK and Germany and Switzerland and all over Asia and around the world that the NIH when people say it's the crown jewel it's the one that's devoted the most

3:08:41

billions of dollars to basic and applied research and it's no coincidence that the majority of Nobel prizes um has in physiology and medicine uh and chemistry and related fields have come from work that was either initially seated by or certainly supported by the NIH. So, you

3:08:56

So, you can't overstate the importance of NIH funding basic and applied research.

3:09:00

That overall budget is facing a 40% cut in September.

3:09:07

Now, you know, I'm hearing two things out there, right? I I wear many hats.

3:09:12

One is my lab ran on NIH money.

3:09:14

It no longer depends on NIH money.

3:09:16

There um I'm a podcaster, so I have the ear of folks who are like this is really scary, right?

3:09:22

um that it gets very political because the current administration seems to be taking a more um like that they're going to revise the way that NIH is structured potentially 20 plus institutes down to eight.

3:09:34

So all of it looks at like downsizing.

3:09:36

There are a lot of people who are terrified about this. Okay.

3:09:40

There's another camp that I hear from a lot um and I can't even say particularly on X and I want to be very clear this camp doesn't always lean right.

3:09:49

It's it's pretty even across the board that are saying, "Wait a second.

3:09:53

Why are we giving so much money to these universities to do research from our tax dollars?"

3:09:58

And I know this will upset people who are very science-minded as I am, who care about science, but they're saying, "Why? Why are we doing this?" Right?

3:10:04

Some of these universities, not all, but some of them, Stanford, Harvard, Yale, Princeton, UT Austin, etc.

3:10:10

, the private universities often, although some public ones do, have very large endowments.

3:10:14

And they're thinking, "Why are we funding so much of this work?

3:10:17

Maybe these tax dollars should go elsewhere."

3:10:18

There's another key issue and this came up during the discussion with Dr.

3:10:21

discussion with Dr. about aacharia which is there are many many people okay I'm just who voiced to me that they don't want to give their tax dollars to basic or applied research at all okay this is a large and growing crowd because they feel that there needs to be for lack of

3:10:41

a better way to put it some truth and reconciliation right they want two things acknowledged and I've and I've actually heard this from many of the let's just say the the highly recognizable names in the in the world of Silicon Valley um super tech or or founders and funders and um and um investors etc. And those two things are

3:10:59

And those two things are the following.

3:11:02

One they want the NIH to acknowledge or CDC andor others in government to acknowledge that there were in their mind failures during the pandemic in particular lockdowns that impacted the non-laptop class.

3:11:14

Okay, we're talking about janitors, um, uh, staff, uh, teachers, kids, etc.

3:11:20

that, um, basically had to halt their work and their income.

3:11:25

They're they're they're pissed off about this, right?

3:11:27

That no one kind of acknowledged this.

3:11:28

The other thing that they're very angry about is the lack of acknowledgement from the scientific community that the science community makes errors.

3:11:37

Sometimes errors that, for instance, in the field of Alzheimer's research, I want to point out, not all the work in the field of Alzheimer's is bad.

3:11:45

much of it is is very solid or or excellent but they they are frustrated by some recent kind of uh unveiling of the fact that there were findings that later were found to be fraudulent basically and that it was never checked up on and then that opens up a whole discussion which I also discussed with Dr.

3:12:04

Bachari about what's being done to solve the so-called replication crisis.

3:12:07

So, they're upset about the about the public messaging around health and science, right?

3:12:11

They would have preferred, it sounds like, that um people in government say, "Hey, listen, you know, we have a virus that we don't understand."

3:12:20

Um, and we we have ideas about what might control it, but we don't fully understand this.

3:12:24

So, it was very iterative and a lot of people are pissed off.

3:12:27

are pissed off. kind of like when you're, you know, 15 or 16 and you're being told you can't stay out late and then your parents are staying up late or, you know, you or like we had governors who were saying you had to wear a mask but then we're taped in

3:12:39

fancy restaurants on the northern coast and you know at restaurants and like much in the way that a teenager goes wait a second like you smoke pot in college and you're telling me not to smoke pot like this there's a logical flaw here and we at least need to talk about it. So there's this kind of notion

3:12:52

So there's this kind of notion that um that the this isn't my stance necessarily.

3:12:57

I'd be happy to share my stance, but that the scientific community has kind of cloaked its errors.

3:13:01

Y and and so there are a lot of people in the general public like don't give these universities a dime.

3:13:05

Let them dip into their endowments.

3:13:06

And the last thing I want to say about that is not every university has large endowments.

3:13:13

Most public universities do not have large endowments.

3:13:15

Um it's also true that universities don't like to spend their endowments and the typical way that they hide behind uh their their endowments or endowment spending is to say that money is earmarked for other things. Right?

3:13:26

So it's which is not to say that it isn't but and then the the last thing and I know I'm going kind of fire hose here but I want to make sure this comes out is that the big issue that is really on the table as well is this notion of indirect costs.

3:13:38

You guys are finance guys.

3:13:41

So basically a laboratory get might get a grant of a million dollars across four years.

3:13:46

So 250 a year for four years.

3:13:47

And the university then gets what are called indirect costs.

3:13:51

Um they get let's say 500k.

3:13:53

Typically it's an anywhere from 300k on the million to up to 750k on the million.

3:13:59

There are a few cases of even more than that.

3:14:00

The so-called indirect funds that take care of administrative costs and the the basic cost of doing research.

3:14:06

And earlier this year, the Trump administration said, "We're cutting that to 15% across the board for all universities."

3:14:12

And that was very prominent on X uh because Elon retweeted it and a number of other people retweet it.

3:14:19

And I would say um while the indirects have been very controversial, I I just personally, it's my view.

3:14:25

Okay, this is my personal view is that a a severe cut to the indirects, while on the face of it might sound good, that's going to disproportionately hurt the public schools without large endowments, okay?

3:14:39

Because they don't have money to dip into.

3:14:40

And you know, something more in the range of 30% seemed reasonable to me based on my understanding of what those funds are used for.

3:14:45

But historically there have been some challenges with indirects.

3:14:48

You know there were universities I won't mention which caught for spending some indirects on things that were unrelated to the science.

3:14:55

You know perhaps keeping the lights on in the English department.

3:14:58

That's typically not the case now.

3:14:58

It's for disposal of radioactive waste. It's for yes janitors.

3:15:02

It's for painting the walls of the building but it's not for making you know a lavish lifestyle for the administrators. Right.

3:15:08

If administrators have a lavish lifestyle it's presumably through some other mechanism. Not IDC.

3:15:12

Yeah there was some example.

3:15:15

I don't know if it was UCSF or some school where they had like a multiund million administrative budget and I think people really wanted to push on that and um but I I I think your concern is like obviously there's like this massive um trust issue between the public and new parts of the administration and science and how do we rebuild that trust without destroying the entire system. Right?

3:15:38

Is that is that kind of you nailed it and and I I would like to just highlight in the backdrop of all of this there there are is one very major emotional issue that I'm going to catch a lot of heat for this but I don't really care anymore.

3:15:51

Um you know and we're on X.

3:15:53

So you know a lot of I put out a um a post recently that said hey listen I I I'm very concerned about this 40% overall cut as the most severe uh damage to to science.

3:16:07

We're not talking about allocation.

3:16:09

We're not talking about indirects, you know, we're not talking about what's going to happen with that with that body of money.

3:16:13

Uh we're just accept this 40% cut.

3:16:16

And I'm very concerned about this, but I don't want to talk about, for instance, the fact that federal funding to Harvard or to Colombia has been frozen.

3:16:23

And a lot of people said, well, why not?

3:16:25

I have a lot of friends at Harvard Med and at Colombia and elsewhere, and they're like, wait, this is why why won't you talk about that?

3:16:30

Well, that's actually a different issue, right?

3:16:32

The reason that money has been frozen is that in the eyes of the administration, they are Harvard and Colombia are violating civil rights laws.

3:16:40

Until that's resolved, there's no discussion about NIH to be had. That's not an NIH issue.

3:16:45

It it funnels through NIH money. Yeah.

3:16:48

People are tying the issue even though just because it it has some of the same buzzwords. That's interesting.

3:16:54

I I have a question about the 40%.

3:16:55

Um I I mean there is a world where where like where what becomes important is the ranking of what gets cut.

3:17:03

And so my question is like within the within the basic research that you're seeing, what should we be fighting for hardest to keep?

3:17:09

What basic science or applied science research are you most optimistic about going forward?

3:17:18

Because we saw this with GLP1s.

3:17:18

Because we saw this with GLP1s. I mean I'm sure crisper these stuff lang this stuff was Nahh funded at one point that there was a ton of research and then we get this big boom like but it's 10 years later what's on the frontier what are you most excited about and what should we be fighting for let's keep the funding there no matter what yeah great

3:17:38

great question uh in fact the most important question so regardless of whether or not this 40% cut happens if it's less if it's kept the same um a couple of things first of all despite the fact that NIH funds basic research and that Many laboratories including my own for for many years focused on basic research like how does the visual system work. We always had an eye every

3:17:56

We always had an eye every laboratory has an eye toward you know what the translational implications could be. Okay.

3:18:02

So we were actively involved in trying to solve you know blindness due to glaucoma even though we were focusing on some basic questions.

3:18:09

So I think it it it's a statistical issue.

3:18:12

If you step back and you say okay in the field of let's just say vision my my former field um what is the leading cause of blindness? Cataract.

3:18:18

But you know what you can fix cataract you can slide out the lens and you put in a new lens that's being done now. Great.

3:18:26

What's the second leading cause of blindness?

3:18:27

More than 70 million people worldwide. Glaucoma.

3:18:28

You can test for eye pressures but once the cells in the eyes start deteriorating people go blind.

3:18:33

There's no recovering those cells. So you can say wow. So okay. So let's take the top.

3:18:37

Let's take the the statistically that the the the the top causes of blindness and let's let's fund those. Okay.

3:18:44

Um retinitis, pigmentotosa, etc.

3:18:47

You could do this for pretty much any field.

3:18:48

So in the field of of brain health, you'd say, okay, dementia, you'd say um uh major depression, you'd say a stroke, uh you'd say, you know, I'm going to piss off some people because I'm not going to mention their their particular suffering, you know, here, but it's not hard to find Parkinson's, right? Um MS.

3:19:05

I mean it's not hard to know what the problems are to tackle.

3:19:10

The problem is it deciding what the targets are. Sure.

3:19:13

And as you mentioned like with crisper I mean in many ways it was a fortuitous thing right?

3:19:16

Um D inner lab was working on bacteria.

3:19:19

Uh I mean is you know it's very hard to predict what basic research is going to lead into these different areas.

3:19:25

But we we know what the critical areas are.

3:19:27

So I'm not trying to dodge your question.

3:19:29

not trying to dodge your question. I do want to say that the emphasis from MA on chronic disease and chronic health issues I think has concerned some of the people in the scientific community because listen I as a podcaster that covers science and health will be the first to say that if you're not sleeping

3:19:45

well your mental health and physical health is not going to be good and you can miss a few nights sleep but if you're chronically sleepd deprived you're sicker than you normally would be if your gut health isn't proper if you're not getting exercise if you're not getting sunlight if you're not doing these things of course Right. But I

3:19:58

But I think the people who are in the the kind of hardcore mechanistic science community are like great, we're all going to strive to do those things and we should, but not at the exclusion of figuring out signaling pathways that are vital for uh like the GLP1s are a beautiful example, right?

3:20:14

This peptide acts at the level of the brain and the gut to make people feel more full.

3:20:18

It also, by the way, shut down the debate as to why people are fat.

3:20:21

It's because they eat too much, right?

3:20:23

They eat more than they burn.

3:20:26

Remember people used to argue about it. Yeah. Yeah. Totally. No, no. GLP1 silenced that.

3:20:30

It's like, yeah, that's really true.

3:20:32

Now, are they eating too much because of a hormone issue related to having too much fat?

3:20:36

Maybe there's some depression feel. Sure.

3:20:39

Like, I fully acknowledge like I'm not trying to be completely insensitive, but like, but we we isolated the problem by understanding that this peptide discovered in the discovery of this is worth spending two sentences on.

3:20:49

Hila monster, a reptile that doesn't need to eat very often, makes a lot of this peptide that it turns out in is manufactured by humans, too.

3:20:57

If you increase it, thousandfold in humans, you know, you're not hungry anymore.

3:21:01

And so I think that, you know, the guy studying Hila, the Hila monster, I doubt was thinking about curing obesity, but there you go.

3:21:10

Now, and and of course there's a debate to every one of these things.

3:21:12

No medication should ever replace lifestyle factors, right? Yeah.

3:21:17

There are many I think we sometimes fail as healthy, fit people.

3:21:22

We fail to understand that lifestyle factors are very hard for people to implement even if they have copious amounts of disposable income and some free time. It's it's just tough. It's just tough. It's hard to do.

3:21:36

And so I think that the the emphasis on nutrition and exercise is wonderful.

3:21:40

I think I don't think anyone on either side of the political debate would argue that MA in principle, make America healthy again, isn't a great thing.

3:21:48

I think what they probably would appreciate hearing, now I'm speaking for kind of the more science mechanistic biology-minded folks, they'd probably like to hear a little bit more about, hey, you know, they're probably signaling pathways in the brain that are relevant to um, you know, to depression that maybe a next class of anti-depressant drugs would probably be good.

3:22:08

I don't think anyone would say there's no need to develop anti-depressant drugs.

3:22:10

We probably take too many of the ones that don't work and have too many side effects.

3:22:14

But as a country, but when so when you say what are the most important things, what we really need is a is a very rationally grounded planning committee to sit back and say, you know what, we're going to put x number of dollars towards this, x number of dollars towards that, x number of dollars towards this.

3:22:30

And this is where I think Dr.

3:22:31

Bodachara really um shined on the podcast.

3:22:33

He said, and I will totally agree, and I got I have already my phone's been blowing up with some anger from colleagues about this.

3:22:41

much of the work that's funded by NIH, here's the dirty secret, is already completed because they tend to fund things that are very certain to be completed.

3:22:51

And so people put forward grants based on work and preliminary data showing I can do this and it's already kind of worked out.

3:22:58

Then they use the money for the next iteration.

3:23:00

This is the dirty secret of every NIH funded lab.

3:23:02

And it tends to favor a kind of pedestrian more pedestrian science.

3:23:08

Then they use foundation money and they use um other sources to kind of do the the high-risk stuff.

3:23:12

But if you were to look at like one of the the more impressive funding bodies in science like the Howard Hughes Medical Institute, right?

3:23:19

Um gives the equivalent HHMI folks as they're called never they always say it's not that much money, but let me many we can do the test.

3:23:28

We can take away their money and we can see how well they do or don't do.

3:23:30